Transparent and complete reporting of randomized controlled trials (RCTs) is essential for critical scientific appraisal of the results. It has been argued whether publications during the COVID-19 pandemic have met reporting standards. In this study, we assessed reporting adherence of RCTs on treatment interventions in COVID-19 patients to the CONSORT checklist and discuss which lessons can be learned to improve reporting in the future.This was a retrospective, cross-sectional study performed at the University Hospital RWTH Aachen, Germany. We conducted a pragmatic systematic literature search in the PubMed database to identify RCTs on treatment interventions in COVID-19 patients in the first year of publications on the topic (March 2020-February 2021). We investigated the adherence of each publication to the CONSORT checklist and assessed the association between specific predictors and percentage adherence in an exploratory multivariable regression model.We analyzed 127 RCTs and found that the median percentage adherence to the CONSORT checklist was 54.3% [IQR 38.9 to 65.7]. In the exploratory multivariable regression model, the impact factor ) and authors’ referral to the CONSORT statement  were associated with a higher percentage adherence to the CONSORT checklist.The reporting quality of RCTs on treatment interventions in COVID-19 patients during the first year of publications was poor. Measures to improve reporting quality are urgently needed. Transparent and accurate reporting of clinical trials is essential to enable progress in medicine , 2. Randreporting quality of RCTs on treatment interventions in COVID-19 patients, which is pivotal for critical scientific appraisal of findings, has only been partially investigated. One study assessed the reporting quality on COVID-19 treatment interventions and found suboptimal adherence to the CONSORT guideline ) AND (COVID-19)) AND (("2020/03/01"[Date-Publication]: "2021/02/28"[Date-Publication]))) NOT  OR (Case reports[Publication Type])) OR (Comment[Publication Type])) OR (Review[Publication Type])) OR ) OR (Letter[Publication Type])). One author (CE) screened all titles and abstracts for suitability of publication and topic type. Only original publications on randomized treatment interventions in COVID-19 patients were included. Publications not available in the English language, brief preliminary reports, or RCTs on other than treatment interventions in COVID-19 patients, e.g., vaccination, prevention therapy, post- or pre-exposure therapy were excluded. In case of uncertainty concerning inclusion of a study, two further authors  were consulted, and a consentaneous decision was made. Due to the explorative nature of the study, no sample size calculation was performed.The first RCT meeting our inclusion criteria was published in March 2020. Hence, we searched publications that were published in the 12 months between March 2020 and February 2021. Our search based on the PubMed’s ‘clinical queries’–search filter which was developed by Haynes and colleagues and has been validated and used before –20. Acco’ was only rated “complete”, when information on the method of recruitment as well as on the inclusion and exclusion criteria were provided.In order to standardize the evaluation of adherence to the CONSORT statement distinct requirements for every item of the CONSORT checklist were predefined in conformity with the CONSORT’s explanation and elaboration document , and bas’), 12b , and 18  as “incomplete” if no information about the respective item was given. E.g., even if there were no protocol deviations, this needed to be reported.As we focused exclusively on the reporting quality of publications, study protocols were not investigated. Similar to Stevanovic et al.  we evalu(‘similarity of interventions’) in case the trial was not blinded and 17b (‘reporting of absolute and relative effect size of binary outcomes’) in case no binary outcomes were used. After an initial analysis of 30 articles, the evaluation data sheet was reviewed by the three assessors  to detect potential misinterpretation and the wording of some items was adapted to improve objective comprehensibility. The final evaluation data sheet is presented in  Item adherence of all articles was evaluated in the full text (CE) and every uncertainty regarding evaluation of item adherence was solved in consensus by three authors .Authors could reference to supplementary materials for extra information on an item. For items to be checked, the reference had to be specific . However, following CONSORT recommendations, information on the randomization process items 8–10) always had to be included in the body of the main article  for continuous variables, and number (percentage) for categorical variables. Each checklist item was weighted equally. Mann-Whitney-U test and Kruskal-Wallis test were used to investigate differences between two or multiple groups.In an exploratory multiple linear regression analysis, we investigated the association between CONSORT checklist adherence and the potential predictors country of origin (defined as corresponding author’s affiliation), IF of journal , month of publication, journal endorsement of the CONSORT checklist and author referral to the CONSORT checklist. These potential predictors of CONSORT-checklist adherence were identified based on prior knowledge. Categorical variables were transformed into dummy variables. First, univariable linear regression was performed for country of origin, IF, month of publication, journal endorsement and author referral to the CONSORT checklist or flowchart, and eventually an exploratory multivariable regression was fit to model the association between these potential predictors and percentage adherence to the CONSORT checklist. Graphical analysis via quantile-quantile (Q-Q) plot were used to assess normality. Assumptions of homoscedasticity and linearity were tested graphically. Coefficients, 95% Confidence Intervals (CI), standard error and p-values are reported. All analysis were conducted using STATA . for details. Finally, 127 publications were included and analyzed upon adherence to the CONSORT checklist. A detailed list of all included publications is presented in Our search identified 7323 studies. After the manual screening of titles and abstract, a total of 430 interventional studies were identified, out of which 304 were RCTs. Out of these, 177 publications were excluded due to unsuitability of topic , language or being a brief preliminary report, see The majority of included RCTs reported the outcomes of pharmacological interventions . Others covered e.g., oxygen therapy or prone positioning. Most of the investigated RCTs were two-armed . More than half of the analyzed publications randomized at least 100 participants . The smallest trial included 10 participants and the largest reported 7763 participants. Corresponding authors’ affiliations were located in 28 different countries. The majority of corresponding authors’ affiliations were in Asia . Out of these, 29 publications were from China and 15 from Iran. Corresponding authors from institutions in North America made up for 22.8% (n = 29), in Europe 16.5% (n = 21) and in South America 11.0% (n = 14). Only three corresponding authors (2.4%) had their affiliation in Africa. In North America, corresponding authors’ affiliations were mostly located in the United States (n = 26), in Europe they were mostly located in Great Britain (n = 7), in South America mostly in Brazil (n = 12), and in Africa mostly in Egypt (n = 2). The 127 articles were published in 68 journals. The median impact factor was 9.1 [4.7 to 56.3], for 19 publications no impact factor was available yet. Out of the 127 investigated publications, 61 were published in journals that endorsed the CONSORT checklist. However, in only 31 publications of the 127 publications, authors referred to the checklist. The majority of publications was published in the second half of the observation period .S2 File. The lowest percentage adherence was 8.6% and the highest was 86.1%. The frequency of the overall percentage adherence to the CONSORT checklist is presented in The overall mean percentage adherence to the CONSORT checklist was 52.4% (standard deviation:16.5) and the overall median percentage adherence was 54.3 [interquartile range: 38.9 to 65.7]. The individual percentage adherence of each investigated publication is shown in . The most frequently sufficiently addressed items were objectives and hypothesis  and presentation of ‘baseline demographic and clinical characteristics’ . The items least frequently sufficiently addressed were ‘implementation of the randomization process’  and ‘description of trial design’ . Only 3.1% (n = 4) of the investigated publications adhered to all the recommendations regarding the reporting of information in the abstract, 76.4% (n = 97) used the word “randomized” in the title.The percentage adherence of all publications to each CONSORT checklist item is shown in Table 1. This table shows the number and percentage adherence of the analyzed publications to each CONSORT item and the overall adherence to the CONSORT checklist. The short descriptions of the items refer to the original CONSORT checklist , those from Great Britain (n = 7) had a median percentage adherence of 63.9 [58.3 to 69.4], followed by publications from USA (n = 26) with 58.1% [50 to 68.6], China (n = 29) with 50.0% [40.0 to 62.9], Iran (n = 15) with 41.7% [36.1 to 48.6] and India (n = 8) with 41.7% [37.1 to 57.3] .No differences were found between publications published in different tertiles of month of publication . The Kruskal-Wallis test showed a difference in percentage adherence between different tertiles of impact factor  We found a difference in distributions of percentage adherence of publications in journals that endorsed CONSORT  in comparison to journals that did not , z = -4.004, p<0.001. No difference was found in the median percentage adherence of publications in which authors referred to CONSORT  and publications in which authors did not , z = -0.618, p = 0.54) , p<0.001, whereas author referral to CONSORT was not associated with a difference in percentage adherence. Publications originating from Iran were associated with a decrease of -14.0 percentage points  concerning percentage adherence in comparison to publications originating from the USA. The month published was neither associated with percentage adherence when modelled continuously nor when investigating tertiles. The impact factor was associated with a statistically significant increase of 0.25 percentage points  when modelled continuously and resulted in a difference of 15.2 percentage points  between publications published in the middle tertile in comparison to the lowest and a difference of 24.5 percentage points  between publications published the highest tertile in comparison to the lowest.The coefficients of the linear regression models for each separate predictor are presented in Table 2). As the assumption of linearity concerning the relationship between the IF and percentage adherence as well as between month of publication and percentage adherence could be questioned, we modelled these categorically by grouping them into tertiles. However, this did not change the overall directions of associations, nor the conclusions drawn from the model with IF and month of publication modelled as continuous variables . The variance inflation factor (VIF) did not detect multicollinearity (mean VIF = 1.74).In the exploratory multivariable model, the IF and author referral to CONSORT were shown to be predictors of percentage adherence to CONSORT (The table shows the associations of the prespecified independent variables (predictors) with the percentage adherence to the CONSORT checklist according to a multiple linear regression model. Overall regression model: Number of observation n = 108 ; R2 = 0.5155; adjusted R2 = 0.4543; F  = 8.42, p<0.001.Interrater reliability of cross-checked items showed a kappa of 0.914.In our retrospective cross-sectional study assessing the quality of publications on 127 RCT for the treatment of COVID-19, we found that the mean adherence to the CONSORT checklist was only 52.4%. In our exploratory multivariable regression model, the IF and authors’ referral to CONSORT were associated with a higher CONSORT adherence, whereas the month of publication or the respective journal’s endorsement were not.The COVID-19 pandemic shed the spotlight on the scientific community, especially within the first year after the breakout of SARS-CoV-2. In face of rapidly increasing numbers of cases and deaths around the world results of RCTs were urgently needed—not only in order to guide clinical decision-making but also in order to inform further public actions. It has been questioned whether the scientific community stood the test of delivering high quality publications in such an unprecedented situation. There is now growing evidence that many publications did not meet the reporting standards scientific journals and researchers agreed upon in the CONOSRT statement , 23, 24.The overall average percentage adherence of 52.4% found in our investigated publications calls for improvement. Scientists and clinicians already perform clinical studies according to ethical guidelines. It should be discussed whether maintaining transparent reporting standards constitutes an ethical imperative, too –in partiall reporting recommendations in the abstract correctly. The mean percentage adherence concerning reported items in the abstract was 56.4%. When time and resources are scarce, the title and abstract may influence whether researchers and clinicians continue reading and hence can consider the findings in their own work. In some settings, the abstract remains the only information on a trial that is available underlining the importance of precise reporting [Several lessons can be learned from our assessment of reporting quality during the stressing test of the first year of COVID publications. First, only 76.4% of publications were identified as RCTs through their title and only 3.1% of publications followed eporting . In a dieporting  and founeporting . Of noteeporting . In addieporting .generation of allocation sequence, process of allocation concealment, implementation of allocation concealment”) so that readers can appraise the extend of bias [’ is crucial for readers to evaluate whether the presented findings are generalizable to their own population of interest. Authors of the broad majority of investigated publications followed this recommendation. Regarding the presentation of results, we found a low adherence of reporting the absolute and relative effect size of outcomes (item 17 b ‘In case of binary outcomes: absolute and relative effect size’). Reporting both is essential to understand and communicate the effect of an intervention and its implications to different audiences [Concerning the main article, the CONSORT recommendations addressing the ‘trial design’ and ‘implementation of the randomization’ have hardly been followed sufficiently. Both items are imperative to evaluate the reliability and validity of findings. Authors should explain who implemented the three steps of a randomization process Click here for additional data file.S2 File(PDF)Click here for additional data file.S3 File(PDF)Click here for additional data file.S4 File(PDF)Click here for additional data file.S5 File(PDF)Click here for additional data file.


Antibiotics have been associated with several individual autoimmune diseases (ADs). This study aims to discover whether pre-diagnostic antibiotics are associated with the onset of ADs in general.n = 708) were traced from national registers.From a cohort of 11,407 children, 242 developed ADs , or inflammatory bowel diseases) by a median age of 16 years. Antibiotic purchases from birth until the date of diagnosis  was associated with the onset of ADs . Regardless of frequent use in childhood , penicillin group antibiotics were not related to any ADs.Use of antibiotics was relatively safe regarding the overall development of ADs. However, broad-spectrum antibiotics should be used considerately as they may associate with an increased likelihood of JIA.Increasing numbers of antibiotic purchases before the age of 3 years or throughout childhood were not associated with the development of pediatric autoimmune diseases.Broad-spectrum antibiotics were related to the development of autoimmune diseases, especially juvenile idiopathic arthritis in children, while penicillin group antibiotics were not.The use of broad-spectrum antibiotics in children should be cautious as they may carry along a risk for autoimmune disease development. Some ADs such as type 1 diabetes (DM), autoimmune thyroiditis (AIT), juvenile idiopathic arthritis (JIA), and inflammatory bowel diseases (IBD) may have overlapping genetic pathways19 In the eastern neighboring countries of Finland (Estonia and Russian Karelia), the incidence of ADs such as DM is lower than in Finland. This finding was suggested to derive from different exposures to environmental pathogens and microbes.20 In line with this, Finnish children used more antibiotics during the first and second years of life compared with Estonian children, and this is reflected in the composition of the gut microbiota and immune stimulation.21 Previous studies have connected antibiotic exposures  with the onset of JIA and Crohn’s disease, while findings regarding DM were controversial.27 AIT has been related to tetracycline use in adolescence, but the mechanism has remained unspecified.28For unknown reasons, the incidences of pediatric-onset DM, AIT, JIA, and IBD in Finland are particularly high, presuming a presence of mutual environmental risk factors in addition to potential genetic predisposition.25 Our aim was to investigate whether the development of ADs  is associated with (1) number of antibiotic exposures during different periods in childhood and (2) exposures to particular types of antibiotics.Most of the previous studies on exposures to antibiotics and the development of ADs addressed each disease individually in different settings, making it challenging to estimate whether antibiotic exposures could be associated with the development of pediatric autoimmunity in general, yet manifesting as different diseases. This register-based case–control study focuses on the potential relationship between antibiotics and the onset of ADs in general.29 The cohort represents children from densely populated areas across Finland, with relatively high maternal socioeconomic status.15 Using a unique personal identity code of every Finnish resident, children in the Fin-HIT cohort were linked to three well-established national registers: (1) the Special Reimbursement Register (SRR)—containing records on patients with chronic diseases requiring medication (including entry dates and physician verified diagnosis), who are entitled to drug refunds regardless of their socioeconomic status; (2) the Drug Purchase Register (DPR)—containing data on all purchased drugs by prescriptions in Finland ; and (3) the Medical Birth Register (MBR)—containing information on gestational age, delivery modes, and postnatal antibiotic treatment before discharge. These registers are maintained by the Finnish Social Insurance Institution (SRR and DPR) and Finnish Institute for Health and Welfare (MBR).The study population was derived from Finnish Health in Teens (Fin-HIT) cohort—a nationwide prospective school-based cohort to address health behaviors of Finnish children and adolescents, comprising 11,407 children (born 2000–2005) without specific exclusion criteria. More details on recruitment and characteristics of the cohort have been described elsewhere.31 DPR was chosen for identifying AIT because thyroxin is inexpensive and therefore, not everyone using this medication is applying special reimbursement and registered in the SRR.The outcome of this study was the diagnosis of at least one AD by the end of the follow-up on December 31, 2018—when the median age of the participants was 16 years. DM, JIA, and IBD , and IBD unclassified (IBDU)) diagnoses were obtained from the SRR using International Classification of Diseases, 10th revision (ICD-10) codes: E10 for DM; M08 for JIA; K50 (Crohn’s disease) and K51 (UC/IBDU) for IBD. AIT diagnoses were obtained from the DPR using ATC  code H03AA01 for thyroxin—the prescription-only drug used for AIT. The excellent coverage of these registers has been described previously.15 Therefore, gestational age (preterm/term), and delivery mode  were also considered in the matching. Due to the limited number of potential controls, most children born preterm and/or with cesarean section had only one matching control.Of the 11,407 children in the Fin-HIT cohort, 242 developed a primary AD after the first year of life and generated the case group. Depending on the availability of potential controls, each child in the case group was matched with one to four children from the same cohort of similar age , sex, and residential area . Furthermore, preterm birth has been identified as a potential risk factor for ADs.Data on perinatal antibiotic treatment during pregnancy and in the birth hospital were obtained from the DPR and MBR, respectively. Outpatient antibiotic purchases were collected from the DPR using ATC codes starting with J01. The data were collected from birth until two months prior to the index date (date of diagnosis for children with ADs/compatible date for their matched controls). The two-month period was chosen to reduce the possibility of including antibiotic purchases during the symptomatic phase of ADs.Antibiotic exposures were analyzed in several observation periods based on the age distribution of antibiotic purchases Fig. : (1) thrDifferent types of antibiotics were categorized based on ATC codes (Supplementary Table 32 Results were presented with odds ratio (OR) and 95% confidence interval (CI). The software used was IBM SPSS Statistics 26.0 and a 5% statistical significance level was adopted.The background data of cases and controls are presented as mean and standard deviation (SD), median , or number/proportion (%). A matched case–control study design with an equal length of the observation period in which these exposures may occur in cases and in their controls was used. The pre-diagnostic antibiotic exposures of each case were compared with the antibiotic exposures of his/her matched control(s) until the index date, and the association between antibiotic exposures and the development of ADs was estimated using conditional logistic regression with strata analysis.n = 3825) were bought before the age of 3 years . Age at and the type of the first antibiotic purchase did not differ between cases and matched controls (Supplementary Table The background characteristics of the 242 children who developed ADs (cases) and their 708 matched controls who did not develop ADs are presented in Table ars Fig. . ThroughThe total number of antibiotic purchases from birth to the index date was not associated with the development of the studied ADs as one group Table . HoweverRegarding individual diagnoses, onset of JIA was more common in children receiving more than 4 courses of antibiotics  than in those receiving <4 antibiotic courses through the entire study period from birth to the index date , followed by macrolides  , Fig.  in threeOur study is the first to investigate the association of the number and types of antibiotic exposures in different stages of childhood with the onset of four common pediatric ADs  in a mutual setting. The total number of antibiotic purchases from birth to the index date was not associated with the development of the studied ADs as one group. However, we found a nonlinear and timing-dependent relationship between the number of antibiotic exposures and the onset of ADs. Furthermore, although the total exposure to antibiotics throughout childhood was not related to the development of these ADs, the more recent and frequent exposures within 2 years prior to the diagnosis were associated. This finding was further supported by purchases of macrolides 2 years prior diagnosis, which increased the risk of ADs. Regarding specific diagnosis of AD, the number of antibiotic exposures throughout childhood was associated with the onset of JIA. Intriguingly, early exposures to broad-spectrum antibiotics were associated with JIA as well. Despite being the most common antibiotic used in childhood, penicillins (predominantly amoxicillin) were safe to use at any age in relation to the development of ADs.26 while studies from other countries assessing parental reports or prescription records have not reported a significant association between early childhood antibiotic exposures and DM.34 Studies from the United Kingdom, Finland, and Sweden have associated early life antibiotic exposures with the onset of JIA.35 As for IBD, early antibiotic exposures have been related to Crohn’s disease, but this association was not apparent regarding UC.37 However, a recent meta-analysis did not confirm the relationship between antibiotics and IBD.38Antibiotic purchases during the first year of life were not associated with the development of any ADs. On contrary, higher exposures to antibiotics at later stages, i.e., close to the age of diagnosis (the median age of 9 years) were associated with the onset of ADs. How do these findings align with previous studies? A Swedish register-based study presented a connection between prescribed antibiotics during infancy and the onset of DM,39 it is reassuring that antibiotics used in early childhood hardly increased the risk for developing pediatric ADs.Most studies have assumed a linear association between antibiotic exposure and the onset of a particular AD, i.e. the risk increases with increasing antibiotic exposure. Our study challenges this presumption, as we did not detect linear associations between antibiotic exposures and onset of ADs. In fact, penicillins (as the most common antibiotic type to treat pediatric infections) were not related to the development of any ADs at any age. Since infancy is the most susceptible period for common infectious diseases and consequently the period of most frequent antibiotic use,40 The pathogenesis of JIA involves several types of immunological cells, with interacting mechanisms that are not entirely known. For instance, JIA has been treated with non-steroid anti-inflammatory drugs, which have not been used in other ADs—suggesting a broader spectrum of inflammatory responses in its disease mechanism. Therefore, we suggest that early childhood infections, antibiotics, or both of them together, might influence a disease mechanism of JIA that is rather different than those of other ADs. What this disease mechanism might be is still beyond our understanding and warrants further studies.We reported that recent purchases of macrolides (within the two years before a diagnosis) were related to obtaining an AD in general, while purchases of sulfonamides and trimethoprim during preschool and adolescence were particularly associated with DM. Exposures to amoxicillin-clavulanic acid during the toddler phase were related to the development of an AD as well, but this finding was most likely driven by the association between this antibiotic and JIA. Intriguingly, in addition to amoxicillin-clavulanic acid, the use of other broad broad-spectrum antibiotics such as macrolides and cephalosporins before the age of three years was also associated with JIA but not with DM, AIT, or IBD. The reason for this finding can only be speculated. JIA is a group of complex, multifactorial, and heterogenous diseases.41 In our study, penicillins were the most common antibiotics used, yet having no prominent association with ADs. Furthermore, a recent cohort study from Sweden showed that while early antibiotic use was associated with JIA, the infections causing the antibiotic exposures were not.35 Finally, both antibiotic use  and ADs are more common in industrialized countries than in developing countries, while infections are generally more common in developing countries.46 Therefore, infections may not be the most plausible explanation in relating antibiotics and ADs.Antibiotic exposures could be interpreted as exposures to infections, which might act as triggers for ADs.47 antibiotic exposures could be related to ADs through altering gut microbiota composition, often seen in different autoimmune diagnosis.53 Magnitude and type of gut microbiota modification varies according to given antibiotics, hence recovery time after different types of antibiotic exposures may vary as well.56 For example, macrolides targeting and inhibiting intracellular ribosomal protein synthesis have both a broad spectrum and a long-term influence on gut microbiota that may persist even for several years.59 In addition, macrolides have immunomodulatory properties.60 These characteristics may yield a summative response in the immune system. In our study, azithromycin was the most often used antibiotic among macrolides. Azithromycin has a broad bacteriostatic spectrum, a marked tissue penetration, a high stability, and a low clearance rate due to its long half-life, which enable it to reach a higher cellular concentration compared to penicillin.57 These characteristics may explain the long-term influences of azithromycin on gut microbiota compared with penicillin. Furthermore, a previous Fin-HIT study showed that azithromycin presented the strongest inverse association with salivary microbiota diversity.61 Since dysbiosis of gut and salivary microbiota have also been associated with ADs,62 we suggest that macrolides might catalyze long-term dysbiosis, explaining their association with ADs. Further studies to examine the potential link between the use of broad-spectrum antibiotics, the duration of their influence on gut microbiota, gut dysbiosis, and the onset of ADs are warranted.Since antibiotics have been shown to have an influence on gut microbial homeostasis,63 For example, we were able to trace purchased antibiotics as outpatients rather than just prescribed. In addition, we studied several ADs in a mutual setting, using a comprehensive Fin-HIT cohort with small variations in socioeconomic status as the source of the study population.15 The controls were matched for age (with a maximum difference of four days), sex, residential area, gestational age, and delivery method to limit the number of potential confounding factors. This matching design provided an additional benefit by indirectly limiting the role of the season as a confounder—since season-related factors, such as infections and daylight exposures, would similarly influence both cases and controls. In addition, our study setting made it possible to examine the association between childhood antibiotic exposures at different stages of childhood and onsets of the four pediatric ADs together, and to reliably compare one disease to another.The strength of our study lies in the comprehensive and excellent coverage of longitudinal data from national registers, which has been shown before.As for limitations, we lack information on the children’s genetic susceptibility to infections or to ADs. We also did not know why the antibiotics were purchased—for treating infections  or for prophylactic purposes—and on whether secondary antibiotic courses for the same infection were needed. In addition, we had no access to the antibiotics given during inpatient care. Yet, antibiotic treatments during hospitalization are often continued orally after discharge, and our data cover these post-discharge antibiotic purchases. Finally, we have no guarantee on the consumption of the purchased antibiotics. However, since monitoring antibiotic consumption of over 11,000 children for over a decade is technically not possible, a study design based on antibiotic purchases is the second-best option, which we used in this study.Use of antibiotics throughout childhood can be considered relatively safe in relation to the development of pediatric ADs. Antibiotics in the penicillin group are unlikely to be associated with the development of any ADs. In contrast, broad-spectrum antibiotics should be used considerately as they may associate with the development of ADs, especially JIA. In conclusion, the development of an AD is a multifactorial process in which antibiotics have a role to play, but the importance of that role still needs to be determined.Supplementary Information


Land system intensification has substantially enhanced crop production; however, it has also created soil antibiotic pollution, undermining crop production. Here, we projected soil antibiotic pollution risks to crop production at multiple geographical scales in China and linked them to land system intensification (including arable land expansion and input increase). Our projections suggest that crop production will substantially decrease when the soil antibiotic pollution risk quotient exceeds 8.30–9.98. Land systems explain most of the variability in antibiotic pollution risks (21–66%) across spatial scales. The convex nonlinearities in tradeoffs between antibiotic pollution risk and crop production indicate that vegetable and wheat production have higher thresholds of land system intensification at which the risk–yield tradeoffs will peak than do maize and rice production. Our study suggests that land system intensification below the minimum thresholds at multiple scales is required for acceptable antibiotic pollution risks related to crop yield reduction. Crop intensification has increased agricultural production albeit with an increase in field antibiotic pollution. Here, Chen et al. project how antibiotic pollution undermines production and how intensification needs to be kept below a threshold. As an emerging issue, antibiotics are used worldwide to control microorganisms 5. Unfortunately, antibiotics are generally emitted into the soils during their manufacture, use, and disposal, and agricultural practices have been one of most important sources of antibiotic emissions, such as manure fertilization and wastewater irrigation, which contain a large amount of antibiotics6. Soil antibiotic pollution thereby increasingly undermines the health of agricultural ecosystems, such as by inhibiting plant growth, disturbing soil functioning, and ultimately reducing crop production8. Given the increase in human emissions of antibiotics, risks to crop production caused by antibiotic pollution are expected to increase in the future5. Thus, managing antibiotic pollution risks is crucial for maintaining crop production and sustainability9.Since the onset of the Anthropocene, human activities have driven substantial socioeconomic development; however, they have also created significant environmental risks from food security to chemical pollution, which must be managed10, the repercussions of antibiotic dispersion in the soil remain largely unknown. In both developed and underdeveloped countries, it is difficult to determine soil antibiotic pollution risks on a massive scale, which exacerbates the lack of a robust analysis that allows us to synthesize the risks to crop production. This has proven to be a serious scientific challenge that limits our understanding of the linkages between antibiotic pollution and food security. Several studies have attempted to simulate the spatial characteristics of antibiotics in soil12. However, these approaches are limited in that they have restricted geographic extents and do not directly characterize the risks to crop production14.Although the antibiotic footprint has received considerable attention16; however, the causes of antibiotic pollution risks are still substantially challenging, partially because land systems change over a vast range of spatial scales. Land system intensification, particularly arable land expansion and increased agricultural inputs , which seeks to increase crop yields and associated economic returns, can substantially exacerbate soil antibiotic pollution in parallel with improvements in crop yields18. For instance, high manure application rates increase the loading of antibiotics into soil and result in serious soil antibiotic pollution in a given region19. It has also been recognized that larger areas of arable land have higher likelihoods of receiving agriculture-originated antibiotics15. Thus, understanding the responses of antibiotic pollution to land system regimes and the thresholds for sustainable land system intensification is greatly beneficial for corresponding risk management. Recent studies suggest that land systems distinctly affect antibiotic pollution risks from regional to global scales20. Controlling human societies to reduce antibiotic pollution at multiple scales requires sustainable land system intensification, including modifications to land use patterns and land management practices21. How land system intensification considering different spatial scales affects antibiotic pollution is the key question in addressing the risks to crop production; however, few efforts have attempted to bridge these gaps.It has been highlighted that land use plays a crucial role in soil antibiotic pollution20. The risk quotient  of antibiotics to arable crop growth is estimated to characterize soil antibiotic pollution risk, and the risk quotient is defined as the extent to which environmental concentrations surpass their no-effect concentrations22. We first predict the risk associated with antibiotics on a broad scale using machine learning logarithms and analyze the relationships with maize, rice, wheat, and vegetable production. According to the development Kuznets curve hypothesis, which describes nonlinear relationships between sustainable development and inequality 23, we examine inverted U-shaped relationships between land system intensification and antibiotic pollution risk to crop production when spatial scales change  Do antibiotic pollution risks reduce crop production at a broad scale? (ii) How do land systems affect soil antibiotic pollution risks with changing spatial scales? (iii) How can land system intensification be managed to balance antibiotic pollution risk and crop yield based on the potential thresholds where risk–yield tradeoffs take their maximum values? To address these questions, we examine the scale-dependent effects of land system intensification on soil antibiotic pollution risk by taking China as a case study, which is one of the greatest consumers of antibiotics worldwide and is exposed to antibiotic pollution24. The average cumulative RQ of antibiotics in the Chinese soil environment was 6.1 ± 2.1  models fed with georeferenced datasets  of manure fertilization than maize and rice production, particularly at small scales. For irrigated areas, vegetable and wheat production generally also had high thresholds  at small scales, while rice production had high thresholds at large scales (46.0–66.5%). Given the importance of arable land to antibiotic pollution risk  containing antibiotics is usually not applied on urban land and is transported to agricultural land as fertilizer or other neighboring sites34. Given that wastewater is one of the main sources of antibiotics in agricultural soils, the fact that the irrigated area proportion was positively correlated with antibiotic pollution risks supported our hypothesis, that is, increased inputs  enriched antibiotics in soils. Moreover, population and economic growth would significantly promote land system intensification and thus increasingly introduce antibiotics into soils. As an example, it has been demonstrated that the expansion of arable lands, which are treated with antibiotic-containing fertilizer, could result in antibiotic pollution to more land35.Here, we quantitatively investigated human impacts on risks to soil antibiotic pollution across a broad range of scales Fig. . Despite36. From the viewpoint of a broad scale, the variability in land use is generally lower than the variability in management among watersheds, and it is the latter that causes the differences in antibiotic pollution risks. Second, human use that triggers antibiotic discharges can vary dramatically across spaces and respond differently to human activities across scales. Bu et al.37 found an inconsistent pattern of antibiotic use with scale change, suggesting that some western regions of China possessed low antibiotic use on a large scale but high use on a small scale. Therefore, scale change will modify the spatial patterns of management-induced antibiotic discharges .Interestingly, we found that the effects of land systems on antibiotic pollution risks were influenced by spatial scale in this study, indicating that the cumulative effects of land systems declined with increasing scales Fig. . Land ma31. Based on a simple assumption, land system intensification may linearly increase crop yield. However, we observed nonlinear trends in crop yield increase with increasing land system intensification, suggesting that benefits for crop yields were partially offset by soil antibiotic pollution. This can be confirmed by our finding that antibiotic pollution reduced crop yields when its cumulative RQ exceeded 8.30–9.98. Given the substantial effects on risk–yield tradeoffs, sustainable land system intensification may offer an alternative for risk management. It can be expected that watersheds consisting of a higher proportion of arable land experience more severe antibiotic pollution7. Thus, reducing the area proportion of arable land can potentially mitigate antibiotic pollution. However, it is unreasonable to crudely decease areas of human-dominated landscapes in a watershed to reduce soil antibiotic pollution risks, which might also reduce socioeconomic outcomes . Intensification of the land system is now one of the main agendas benefiting socioeconomic development across and within human societies and thus is typically associated with benefit–risk tradeoffs17. In our study, the tradeoffs between crop yield and antibiotic pollution risk show that the high priority afforded to sustainable land system intensification efforts is necessary to achieve the expected likelihood of win–win outcomes, that is, crop production and risk control.One of the facts about land systems with regard to sustainability is that land systems often create tradeoffs between social equality  and environmental safety  rather than win‒win outcomes23, we elucidated the inverted U-shaped relationships between land system intensification and risk–yield tradeoffs. Thus, the thresholds where the risk–yield tradeoffs take their maximum values fall on the inverted U-shaped curves. These thresholds are comforting for decision-makers as they can capture the desired information for land system management. When land system intensification exceeded the thresholds, we will risk a reduction in crop production; that is, the relative benefits for crop yields decreased and antibiotic pollution risks increased  We assumed the nonexistence of target antibiotics that were not reported; however, these antibiotics might be present but below the detection limit of the adopted methodology. (iv) This study was performed based on modeling results without the inclusion of a validation experiment, and thus lacks a mechanistic understanding. When the universal screening of antibiotic pollution is difficult and not cost-effective, a modeling approach can provide reliable evidence. Several studies have modeled antibiotic concentrations in soil using regression techniques, although with limited modeling accuracy41. Additional biophysical models and available data should be developed to accurately predict the risks associated with antibiotics in multiple environmental compartments and investigate the mechanisms underlying the socioecological system.Our study goes beyond previous work on the risk assessment of antibiotic pollution in soil on multiple spatial scales. However, the following uncertainties and limitations need to be further considered. (i) The antibiotic pollution risk presented in this study may be overestimated, mainly because the risk assessment model assumed maximum exposure and minimum tolerance of nontarget organisms to represent the worst scenario; nonetheless, the estimated risk can be a good reference for regulatory agencies in making critical decisions because the worst scenario represented soil antibiotic pollution risks that can maximally lead to negative changes  in land systems. (ii) This study only considered the exposure risks to crops, but the spread of antibiotic-induced resistance was not included. In addition, biotic factors seem overlooked in the present work, although soil microbes or plant microbiomes are believed to play crucial roles in the relationships between antibiotic pollution and crop yield. Unfortunately, long time-series datasets of biotic factors  are lacking at a broad scale. It has been shown that the diversity of soil microbes and plant microbes is significantly correlated with soil organic carbon, precipitation, and temperatureNevertheless, our findings might enable generalization to other regions or countries. Intensive land systems often result in high soil antibiotic pollution risks, which hinder crop production. Inverted U-shaped relationships between land system intensification and risk–yield tradeoffs were generally observed, and the thresholds of land system intensification, where tradeoffs were maximized, provide a comforting guide for decision-makers aiming to manage land systems based on a balance between crop yields and antibiotic pollution risks. Sustainable land systems are required for antibiotic pollution control to protect crop production. In addition, to achieve sustainability goals, cooperation among innovative and effective policies, implementation strategies, and stakeholder actions for land system sustainability is required for sustainable soil use and sustainable living with low exposure to antibiotic pollution.42. We combined a linear model, generalized additive model, and moving-window approach to describe the relationships between human activities and antibiotic pollution risks on four scales. All modeling and analyses were conducted using R software 4.2.1.We collected data on the measured environmental concentrations (MECs) of antibiotics in Chinese soil. Many antibiotics widely occurred in soil, and nine frequently detected antibiotics with wide distribution and high toxicity were selected: tetracycline, chlortetracycline, oxytetracycline, doxycycline, ofloxacin, norfloxacin, ciprofloxacin, enrofloxacin, and lomefloxacin. Then, we evaluated the risks of these target antibiotics to crop production. We also collected data on anthropogenic factors, climatic factors, and soil and vegetation characteristics that could explain the variability in antibiotic pollution risks as predictors. Next, we scaled up the risks associated with target antibiotics in soil using a machine learning model 43, which records antibiotic occurrence and distribution in Chinese soil. This dataset contains georeferenced occurrences for our target antibiotics, considering land use type  and experiment location (coordinates) at a specific sampling time. Concentrations that were ‘not detected’ or ‘below detection limit’ were regarded as zero values. The MECs were converted into standardized units (μg/kg or ng/g). We revisited the data sources of the dataset of Zhang et al.43 and found that the measurements of antibiotics were performed with a depth of 20 cm in most cases. When scaling up the risks of soil to antibiotic pollution, we considered a fixed depth value of 0–20 cm.To determine the risks of soil antibiotic pollution, a comprehensive MEC dataset was established. We mainly compiled the publicly available dataset of Zhang et al.43, which comprehensively depicts the MECs of soil antibiotics in most regions of China.To expand the existing data, we also collected soil samples from Yunnan and Zhejiang provinces and measured the concentrations of target antibiotics. The soil samples were transported to the laboratory, freeze-dried, and stored at −20 °C until further analysis. The extraction and analysis of antibiotics are detailed in the Supplementary Methods , and the results suggested that our dataset does not appear to be significantly different than random distribution. Finally, our selection criteria generated a dataset of 484 locations which is higher than the minimal sample size requirement20. Our measured data are available in Supplementary Data figshare44.The following selection criterion procedures were performed for our combined dataset to minimize possible bias: (i) we only considered the field samples that were not experimentally treated, such via addition of antibiotics; (ii) soil samples collected from seriously polluted sites , where high levels of introduced antibiotics might add a layer of uncertainty, were not considered in this study; and (iii) we calculated the Moran’s 45. In this study, risk assessment of antibiotics is performed following the risk quotient (RQ) approach, with RQs for individual mixture components determined from MECs and predicted no-effect concentrations (PNECs). To assess the risks of the target antibiotics, the PNECs were first estimated via the assessment factor approach22. PNECs were determined as the ratio of the median effective concentration (EC50) or median lethal concentration (LC50) to the assessment factor (AF = 1000) or the ratio of the chronic no-observed-effect concentration (NOEC) to the assessment factor (AF = 100); that is, PNEC = EC50 (or LC50)/1000 or PNEC = NOEC/100. Owing to the scarcity of available data, the toxicity data of the relevant terrestrial organisms  were collected from the literature (Supplementary Table soil) were estimated from their values in water (PNECwater), which were corrected by the soil–water partition coefficient (Kd) via the equilibrium partitioning method . To consider the worst scenarios, we defined the risk levels of antibiotic pollution as the highest RQ values. We determined the cumulative risks in soil as the sum of the highest RQs of each target antibiotic.Given the disparities in the tolerance of crop growth to different antibiotics, the risk of antibiotics to crop growth can be better representative of the consequences of antibiotic pollution than their concentrationtor AF = 000 or th46. Land use data were released from the Resource and Environmental Science and Data Center (https://www.resdc.cn). Five anthropogenic factors were collected, namely, livestock density , human population density, GDP, chemical fertilization (nitrogen and phosphorus), and pesticide use, which are linked to socioeconomic development and agricultural activities. Soil properties, which substantially influence the fates and behaviors of antibiotics in soil, were collected as important predictor variables; they included clay content, organic carbon content, bulk density, soil thickness (distance to bedrock), and saturated hydraulic conductivity. We selected the groundwater table depth and normalized difference vegetation index as indicators of leaching and plant uptake capacity. Moreover, we obtained terrain information from the GTOPO30 database47, as terrain can influence antibiotic movement on land. To ensure compatibility across datasets and variables, we processed all data at a spatial resolution of 1 km, which was consistent with the land use data. Gridded datasets with higher pixel resolutions were resampled by the mean aggregation method, and datasets with lower resolutions were resampled by simple upsampling 48. The data were extracted according to the experimental site location and sampling year. We assumed that several predictor variables  had limited temporal changes due to the lack of time-series datasets, while the other predictor variables generally had long time-series datasets from 2000 to 2020. Anthropogenic and climatic factors as well as soil and vegetation characteristics determine the amount of antibiotic residue in soil and the soil susceptibility to antibiotic pollution.The predictor variables were determined from spatially explicit datasets (Supplementary Table 42 was fitted to the log-transformed (log10) RQs of each antibiotic using the R packages randomForest49 and Caret50. All predictor variables were standardized using the Z score. We constrained the RF models by setting the maximum number of allowed trees to 1000. Since the RQ data were modeled using 2020 datasets, cross-validation was performed. The dataset was randomly divided into training and validation sets, corresponding to 70% and 30% of the data, respectively. Finally, the data-trained RF model was applied to the gridded data of predictors to estimate the risk levels of nine target antibiotics on a larger scale. Ecosystems not covered by soil (including bare land and water) were excluded from the analysis based on the land-cover map. An ensemble model for our final predictions and uncertainty analysis was developed via the Monte Carlo approach. Our final model was an ensemble of 500 RF models  to generate a distribution of model error on random data51. The distribution density of differences between measured and predicted data was determined for each target antibiotic, and the root mean square errors (RMSE) and Pearson’s correlation coefficients between measured and predicted data were used to assess the accuracy of the RF models. We derived the models’ mean prediction across the ensemble models and determined the uncertainties associated with the predictions from the standard deviation. Maps of the distribution of risks related to soil antibiotic pollution, expressed as average RQs, and the corresponding uncertainty maps were derived using the data-trained RF models at a resolution of 1 km.An RF model including all of the predictor variables31. Thus, we identified areas highly subject to human disturbance using the geographically gridded maps of the land system, which includes land use patterns and management practices (Supplementary Table 2/yr) and irrigated area proportion because manure application and irrigation are generally considered the main pathways of antibiotics into soil30.The land system can be manipulated by technologies and governance systems across spatial scales and is more sensitive than other human activitiesTo analyze the responses of antibiotic pollution risks (response variable) to human activities using each generated dataset, we listed three land use composition indicators and two land management indicators as explanatory variables using linear regression models, while population and GDP were also considered socioeconomic indicators. We standardized the land use composition (area proportion of arable land) and management indicators via the minimum–maximum method. Land system intensification was estimated by summing the standardized scores of land use composition and management within a specific watershed.52 to represent the changes in spatial grain  grain of scale: generating datasets by changing the grain size , and (ii) extent of scale: resampling the datasets by changing the scale extent . To explore the scale effects, four watershed levels  were selected from the HydroSHEDS dataset53, the subdatasets represented a gradient of human footprints. When the whole dataset across China was used, the large spatial extent only reflected the average condition and might consequently hide some local-specific relationships between land system intensification and antibiotic pollution risks to a small extent54. Thus, the model results based on the whole dataset could not completely represent the relationships between land system intensification and antibiotic pollution risks. To avoid arbitrary model choices, we conducted 20 runs by selecting different data to explore the effects of spatial extent change. Following the rank of whole datasets according to increasing human footprints, the scale extent was reduced through the omission of segments from the ranked datasets. We omitted 0–90% of the upper segments  from the ranked datasets in sequence; that is, 0–90% of the watersheds with high human footprints were removed from the datasets in sequence and 10 subdatasets were generated , which can be identified without prior subjective model specifications, were used to analyze the nonlinear relationships between antibiotic pollution risk (predictor variable) and crop yield (response variable). In the GAMs, nonparametric smoothers were used, and the basis dimension of the smoothing function was five58.The crop yield data included rice, maize, wheat, and vegetable yields59. To remove the effects of differences in the measurement scale, we first standardized the two objectives: antibiotic pollution risk and crop yield, and the improvement (P) of land system intensification for one objective was estimated (antibiotic pollution risk is defined as one disservice):Ai is the observed value of this objective in watershed i, and Amax and Amin are the maximum and minimum values in all watersheds, respectively. When the magnitude of improvement ranged from 0 to 1, a higher P value in watershed i represented a higher level for this objective in comparison with other watersheds, indicating that this objective could obtain more benefits from land system intensification in watershed i. Then, we quantified their tradeoffs in two dimensions. On the 1:1 line, improvement in crop yield equals improvement in antibiotic pollution risk, and their tradeoffs increase with distance from the 1:1 line. The risk–yield tradeoff is defined as the P value of crop yield subtracting the P value of antibiotic pollution risk, that is, the distance from the 1:1 line  of the scattered point cloud is divided into 50 parts to obtain 50 point columns (10 parts for the level-1 watershed). For the crop yields and risk–yield tradeoffs, we calculated the 99% upper boundaries as their constraint lines  and the 1% lower boundary for RQs as the constraint line of antibiotic pollution risks. The 99% upper boundary and 1% lower boundary were constructed to include most points of point clouds, indicating the maximum likelihood considering most scenarios. Due to nonlinearities, thresholds between constraint variables and response variables are often detected.The constraint line is the percentile boundary of the scattered point cloud between the response variable  and the constraint variable 61. We generated a range of window sizes and calculated the relative range of RQs . When the relative range exceeded 60%, we fixed the window size. For each window, we calculated the mean values of RQ, crop yield, and land system intensification . Then, we fitted risk–yield tradeoffs (y) against the land system variables (x) using inverted U-shaped curves as follows in Eq. (a, b and c are fitting parameters. The thresholds for land system variables were defined as x values when slopes were zero. That is:Using a moving-window approach, we analyzed the effects of land systems on antibiotic-related riskss in Eq. :2\documeFurther information on research design is available in the Supplementary InformationReporting SummaryDescription of Additional Supplementary FilesSupplementary Data 1Peer Review File


Prior research found an association between mother–infant attachment and antibiotic use. Ambivalent-attached infants are more likely to take antibiotics than other infants, and their mothers tend to be less sensitive to their needs than most. This finding is important because it shows the association between psychological processes, early relationships, and health outcomes. We aim to learn about children with high-risk attachment relationships, such as disorganized-attached infants. This study compares antibiotic use, infant–mother interactive behavior, and health indicators according to infant attachment patterns (including disorganized attachment). For this purpose, we observed mothers–infants’ interactive behavior in free play at nine months and infants’ attachment in the Ainsworth Strange Situation at twelve months. Participants included 77 girls and 104 boys (full-term and preterm) and their mothers. Paradoxically, mothers of disorganized-attached infants reported that their children were ill only 1.56 times on average, but 61% of their children used antibiotics in the first nine months. The other mothers reported that their children were sick 5.73 times on average, but only 54% of their children used antibiotics in the same period. Infants with disorganized attachment had mothers who were more literate and less sensitive. These results add to a body of research that shows that early high-risk relationships affect children’s lives at multiple levels. Recent research has found an association between maternal behavior, infant attachment, and antibiotic use. Fuertes et al. studied infants born at full term and found that the proportion of ambivalent-attached infants that took antibiotics in the first nine months of life was significantly higher than among secure and avoidant-attached infants . FurtherIt is undeniable that antibiotics represent an enormous medical discovery of the 20th century. However, bacteria frequently become antibiotic-resistant. There are two main routes toward resistance.First, in some instances, specific single mutations in the bacterial chromosome are sufficient to turn antibiotic-sensitive bacterial cells into antibiotic-resistant. These are the cases, for example, of antibiotics as different as rifampicin (which acts on RNA synthesis), streptomycin (which inhibits protein synthesis), or nalidixic acid . These mutations may appear within a few hours of bacterial growth. In the presence of antibiotics, sensitive bacteria die or halt cell division, leaving resources to antibiotic-resistant cells . The second route toward antibiotic resistance is based on a phenomenon common among bacteria but rare or absent in other living beings: bacteria often receive DNA from the environment and other bacterial cells. These moving DNA strands  frequently encode genes that confer antibiotic resistance . These D2 publications/year in 1983 to 4.70 × 104 publications/year in 2022), the database only increased 8-fold in the same period (from 4.32 × 105 publications/year in 1983 to 3.47 × 106 publications/year in 2022). World Health Organization considers antibiotic resistance as one of the biggest global public health threats facing humanity . The proportion of ambivalent-attached infants that used antibiotics (64.9%) is higher than among secure (30.6%). The proportion of disorganized infants that used antibiotics was also high (61.1%), although the difference is not statistically significant. For the association between attachment pattern and antibiotic use, there are middle-size effects according to Cramer’s V . Among the six disorganized infants coded as secure under the original attachment scale, two took antibiotics in the first nine months; among the five disorganized infants coded as insecure-ambivalent under the original scale, five took antibiotics; finally, among the seven disorganized infants coded as insecure-avoidant under the original scale, four took antibiotics.According to Regarding prematurity, as expected, we found more disorganized attachment in infants born preterm, but differences are not significant .M = 15.56; SD = 2.55) than mothers of infants with a secure attachment  and mothers of infants with an ambivalent attachment  . Furthermore, mothers of infants with disorganized attachment reported fewer diseases  than other mothers, particularly mothers of infants with avoidant attachment  .Infant gestational weight, number of years of maternal formal education, and number of infants’ diseases in the first nine months of life (according to the mothers’ reports) varied according to the infant’s attachment strategy . MothersMothers of disorganized-attached infants reported that 61% of their children used antibiotics in the first nine months and that their children were ill 1.56 times on average, while the other mothers (together) reported that only 54% of their children used antibiotics in the first nine months, but their children were sick 3 times more often (5.73 times on average).According to Infants with a disorganized attachment (D) are at risk for social and emotional developmental problems . An earlIn this study, we applied the D attachment classification to a sample we previously coded with original attachment classification to learn if the amount of antibiotic use is higher in a group of infants generally associated with behavioral perturbation and atypical caregiving ,70. InteMoreover, although mothers of infants with ambivalent and disorganized attachment reported similar percentages of antibiotic use, ambivalent-attached infants were ill more than twice the number of disorganized-attached infants . This mismatch between the number of diseases and the percentage of antibiotic use is even more striking by comparing ambivalent-attached and disorganized-attached infants with the other infants. Although mothers of infants with avoidant and secure attachment reported lower proportions of antibiotic use than mothers of ambivalent and disorganized infants, their children were ill 9.87 and 4.94 times, respectively .Concerning the D group, one wonders if the mothers’ reports are reliable or if their infants had antibiotic prescriptions each time they were ill. It is important to stress that mothers of infants classified with a disorganized pattern had higher levels of education than other mothers. Thus, they are able to understand health information and report their infant’s health history. Further investigation of infants classified with disorganized attachment is necessary to understand the quality of health care provided to them and their mother’s mental health . Moreover, future studies need to observe maternal behavior in daily routines to understand if these mothers are absent and only attend to their infants’ health needs when they are already in pain or sick for a while and already in need of an antibiotic prescription. To illustrate the major findings of this study, As prior research documented, mothers of infants classified with disorganized patterns were less sensitive to their infant’s needs and more controlling or unresponsive than mothers of other infants . Moreoveractions ,73: whilwas high .One cannot change infants’ genomes . However, these studies show that infants with disorganized attachment have mothers with very low levels of sensitivity. Family-centered early intervention may prevent these inadequate interactions. For that purpose, the support for parents should start as early as during pregnancy, including screening maternal and paternal mental health in obstetric care. Cases of mental problems should be immediately addressed. The transition from the maternity ward to the family’s home (postpartum discharge) is another key moment. Some parents may struggle with the transition to parenthood once leaving a structured clinical environment and without health professionals; it is necessary to support parents in adapting to this period . AttachmOverall, this research sheds light on the complex interplay between psychological processes, early relationships, and health outcomes, calling for further investigation and targeted interventions to mitigate the adverse effects of disorganized attachment on children’s rights and well-being.In conclusion, this study provides evidence of the association between attachment relationships, antibiotic consumption, and maternal sensitivity in infants with disorganized attachment.Our findings revealed that 61.1% of children exhibiting disorganized attachment had taken antibiotics, yet they experienced sickness less often than the other children. This result suggests these children are significantly more inclined to use antibiotics concerning the number of illnesses they encounter, compared to children displaying different attachment patterns.Moreover, mothers of children with disorganized attachment showed very low levels of maternal sensitivity, indicating high-risk interactions. Strikingly, these mothers had high levels of literacy. Future studies need to include maternal stress and mental health variables to understand the behavior of mothers of disorganized-attached infants.The findings emphasize the need for early intervention and support for mothers and infants with disorganized attachment to promote healthier attachment relationships and potentially reduce antibiotic use in infancy.


Wooden partitions are extensively used as formwork for pouring concrete in wood–concrete composite beams, especially in the restoring of wood structures. However, limited research has been conducted on the shear properties of pitched screw connectors in wood–concrete composite beams with wooden partitions. Therefore, this study investigated the shear performance of pitched screws in wood–concrete composite beams with wooden partitions through push-out tests and finite element analysis. The test results revealed that the failure mode of pitched screws was characterized by the pulling failure of the screws under tensile–shear action. The finite element analysis accurately predicted the failure mode, stress distribution, and load–slip behavior of pitched screws. Furthermore, the effects of the screw embedding angle, wooden partition thickness, concrete strength, and the length–diameter ratio of the screw were investigated through parametric analyses. It was found that when the screw diameter was 12 mm, the shearing capacity of the pitched screws with embedding angles of ±45°, ±60°, and ±75° decreased by 3.9%, 11.9%, and 26.9%, respectively, compared to the screws with an embedding angle of ±30°. The shearing capacity of pitched screws improved with the increase in the concrete strength and length–diameter ratio of the screw. However, the improvement in shearing capacity became less significant as the concrete strength and length–diameter ratio of the screw increased. Moreover, an increase in wooden partition thickness reduced the shearing capacity of pitched screws. The wood–concrete composite beam is composed of the wood beam and concrete flange, making full use of the mechanical properties of concrete under compression and wood under tension. The composite action is achieved through shear connections, which serve the purpose of transferring longitudinal shear forces at the interface and resisting the lift-up effect between the composite components. During the renovation and repair of traditional wood structures, the wooden partition is utilized as a construction platform for concrete pouring and retained as an integral part of the composite structure. The wood–concrete composite structures have gained significant traction in the construction industry and achieved applications in high-rise wooden buildings and bridge slab systems ,2.Currently, extensive experimental analyses and theoretical studies have been conducted on the shear behavior of screw connections ,9,10,11.In recent years, several finite element studies have been conducted on wood–concrete composite beams with screw connectors ,15,16,17Currently, there is limited research available on the shear properties of pitched screw connectors in wood–concrete composite beams with wooden partitions. Therefore, this paper aimed to address this gap by conducting an experimental study on pitched screw connectors in wood–concrete composite beams with wooden partitions. Additionally, the three-dimensional finite element analysis was performed using the ABAQUS 2020 finite element analysis software to analyze the behavior of the pitched screws. This study focused on investigating the influence of various factors, such as screw embedding angle, wooden partition thickness, concrete strength, and screw length–diameter ratio on the shearing capacity of the pitched screws.Two glulam–concrete specimens (GCS-1 and GCS-2) were constructed and tested under static load. The detailed parameters of the test specimens are depicted in 3. The compressive elastic modulus parallel to the wood grain was determined to be 12,570 N/mm2. Furthermore, the average compressive strength parallel to the wood grain was found to be 57.6 N/mm2, and the shearing capacity parallel to the wood grain was measured as 4.3 N/mm2. The cylinder compression strength of the concrete was determined to be 26.2 N/mm2. The screw fasteners had a tensile strength of 461.6 N/mm2.The wood used in the test specimens had an average moisture content of 11.3% and an average air-dry density of 0.58 g/cmDuring the initial loading stage, the wood–concrete composite beam exhibited good mechanical performance, with minimal relative slip and lifting displacement between the concrete slab and wood beam. However, as the applied load increased, various cracks and damages were observed. At a load of 109 kN, the cracks were observed at the upper part of the concrete slab, as shown in During the push-out tests, the load–slip curves of the pitched screws in the wood–concrete composite beam with wooden partitions were obtained through continuous monitoring, as shown in a and b = calculation coefficient, a is taken as 1.7, and b is taken as 2.0 in this model.To investigate the shear properties of pitched screw connectors in wood–concrete composite beams with wooden partitions, a three-dimensional finite element model was developed using the ABAQUS 2020 software. According to the research results in the literature [The wood material in this model was simplified as an orthotropic material. The relationship between the elastic modulus and shear modulus of wood was determined based on the guidelines provided by EN 338 . The ortIn the finite element simulation, the concrete slabs, wood beams, screw connectors, and wooden partitions were modeled using three-dimensional solid reduced integral elements known as C3D8R elements. These elements were hexahedral in type and linear in geometric order. The surface contact setup in ABAQUS was utilized to simulate the interaction between different components. The friction model “penalty” was used in the tangential direction to account for the frictional behavior, while hard contact was set in the normal direction to prevent interpenetration. The type of applied load was concentrated force, with the direction perpendicular to the side of the concrete slab. To facilitate the application of loads, the reference points were established in a coupling manner. The coupling type was selected as continuous distribution, ensuring the load transfer between the components. Based on the boundary conditions of the push-out test, the translational degrees of freedom and rotational degrees of freedom along the X, Y, and Z directions were constrained at one end of the glued wood beam. Similarly, the translational degrees of freedom of the concrete slab were restricted at the other end, ensuring proper fixation of the specimen during the simulation. The analysis step type for the solution procedure is static and universal, considering the geometric nonlinearity of the material. The Newton–Raphson iterative method was used in the nonlinear solution procedure.Based on the numerical results, the stress–strain behavior of the concrete slab, wooden partition, wood beam, and screw connectors in the specimen was analyzed. The failure mode observed in the composite specimen under the limit state was the pulling out of the pitched screw connectors under tensile shear action, with the concentration of stresses mainly occurring at the joint of the pitched screws a. The scThe influence of the screw embedding angle on the shearing capacity of pitched screws was investigated through finite element analysis. The analysis considered screw connectors with embedding angles of ±15°, ±30°, ±45°, ±60°, and ±75°, and the simulation results are shown in The influence of wooden partition thickness on the shearing capacity of pitched screws was examined through finite element analysis. The composite beam specimens with wooden partition thicknesses ranging from 0 mm to 30 mm were considered in the analysis. The finite element results of the shearing capacity of pitched screws are shown in The effect of concrete strength on the shearing capacity of pitched screws was investigated through finite element analysis. The pitched screw connectors were analyzed, with concrete strengths ranging from C20 to C50. The analysis results of the shearing capacity are presented in To analyze the influence of the screw length–diameter ratio on the shear resistance of pitched screws, a finite element analysis was conducted on pitched screw connectors with different length–diameter ratios . It was (1)The failure mode of pitched screws was characterized as the pulling failure of the screw fasteners under tensile shear action. The load–slip curve exhibited linear growth initially, with a relatively small slip. As the applied load increased, the curve showed nonlinear growth, indicating a reduction in the shear rigidity of the screw connectors. At the ultimate load, the load began to decrease gradually with increasing slip, demonstrating progressive failure and good ductility of the pitched screw connectors. The finite element analysis accurately predicted the failure mode, stress distribution, and load–slip behavior of pitched screws.(2)When the screw diameter was 12 mm, the shearing capacity of the pitched screws with embedding angles of ±45°, ±60°, and ±75° decreased by 3.9%, 11.9%, and 26.9%, respectively, compared to the screws with an embedding angle of ±30°. The shearing capacity of pitched screw connections decreased as the screw embedding angle increased beyond 30°. This reduction could be attributed to the diminishing rope effects of the screw fasteners. Additionally, an increase in wooden partition thickness led to a gradual decrease in the shearing capacity of the pitched screw connectors.(3)Compared to the screws with a length–diameter ratio of 6.6, the shearing capacity of pitched screws with length–diameter ratios of 8.3, 10, 11.7, 13.4, and 15.1 was improved by 8.8%, 18.4%, 24.2%, 25.1%, and 25.8%, respectively. The shearing capacity of pitched screws improved with an increase in the length–diameter ratio due to the enhanced withdrawal strength of the screw fasteners. However, the rate of improvement became less significant as the length–diameter ratio increased. The optimal length–diameter ratio was found to be approximately 11.7.(4)The shearing capacity of pitched screw connectors increased with an increase in concrete strength. However, the rate of increase became more gradual as the concrete strength increased. This effect could be attributed to the relatively large elastic modulus of concrete compared to wood, causing a diminishing influence of concrete strength on the shear properties of the pitched screws.The experimental and numerical investigations conducted in this study provided valuable insights into the shear performance of pitched screws in wood–concrete composite beams with wooden partitions. The following key findings were observed:The present study focused on analyzing the shear performance of pitched screws in wood–concrete composite beams with wooden partitions. The results can inform the design and optimization of pitched screw connectors in wood–concrete composite structures, enabling improved shear resistance and overall structural performance. A subsequent paper will investigate the shear performance of notched connectors and steel plate connectors in wood–concrete composite beams with wooden partitions. Furthermore, it is recommended that future research should also explore the shear performance of pitched screws in wood–concrete composite beams under fire conditions.


Many studies have found that supported employment (SE) has effectively helped people with severe mental illness obtain and maintain competitive employment. However, most SE studies have asked “What works?” rather than discerning what works for whom, in what circumstances, in what respects and how. It is important to understand the outcomes of SE and identify the impact factors (contexts and mechanisms) that can trigger them. Four literature databases were searched for studies that analyzed counseling settings. Overall, 104 publications met the inclusion criteria. The review showed that most of the research on SE programs were one-dimensional, looking at either the effects of SE programs, the client or the professional, or the relationship between clients and professionals. The model reveals that impact factors are interconnected and can have a cumulative impact on the client, professionals, and the environment.The online version contains supplementary material available at 10.1007/s10775-022-09533-3. For many people, work means belonging to a society. It is an essential part of their lives and improves their self-esteem, helps establish social relationships, and sets life goals  in a counseling setting influence the effectiveness of SE programs , guaranteeing a broad search approach.Step 3 Search the literature: Four electronic databases were searched: (1) Web of Science, (2) PsycInfo, (3) WISO, and (4) Social Science Abstracts. The focus was on post-1999 publications because the debate about impact began during that time, and publications have continued to increase since then. Before deciding on this search term, the most common synonyms of “effectiveness” and “supported employment” were combined, including “impact,” “impact factors,” “effects,” “efficacy,” “vocational rehabilitation,” and “individual placement and support.” This procedure allowed for the inclusion of the largest number of relevant articles that have been excluded from a combination of the other search terms. For example, when evaluating the search terms, “impact” was excluded as the results were less satisfactory than for “effectiveness” and yet the relevant “impact” articles occurred in the results. The chosen search term, therefore, used a combination of “effectiveness” AND “supported employment” (German: “Wirkung” UND “Arbeitsintegration”) to include as many publications as possible.Science,  PsycInfoearched:  Web of SStep 4 Survey the literature A multistep screening process was executed to identify relevant publications. First, a screening of all 2023 titles eliminated clearly irrelevant articles that did not meet the inclusion criteria. Of the remaining ones, abstracts were checked for relevance. Because of this screening, 1691 publications did not meet the inclusion criteria and were not relevant to the study context. Afterward, full-text availability was proven, excluding 10 unavailable publications. The remaining 322 publications were evaluated by two authors for content based on their full text. After finding no discrepancies, the first author conducted a full review of the identified articles. Only 104 publications that met all the inclusion criteria were analyzed and coded. Those that did not meet the inclusion criteria were flagged for removal. Afterward, two reviewers evaluated those studies. The decision whether the study should be removed or included was based on consensus. Figure The publications were coded for further information using MAXQDA, a software package for qualitative data analysis, since it is flexible when subcoding is needed.Part I program information ; and Part II impact factors and impacts separated into context–mechanism–outcome (CMO) regarding RE. This contains the coding to the research question “What components work in supported employment for whom, in what circumstances, in what respect and how?.” We refer to Step 5: Critique the literature—draw conclusions in the following chapter, and to Step 6: Write the review—communicate and evaluate the conclusions in the closing chapter.The codes were developed by the four-member project team according to the realist review  or resources  during the SE program setting. Some contexts might trigger mechanisms while others might not. The interaction between contexts and mechanisms affects the outcomes (or lack thereof) of programs and the CMO hypothesis  shape SE results. The mechanisms are mainly found on the microsystem level, that is, clients and professionals, while some are found on the macrosystem level. The outcomes are mostly related to clients (microsystem level) with the exception of the environment (macrosystem level).The microsystem level of professionals, clients, and their interaction plays an essential role in SE success. The microsystem level contains the main CMO, describing how SE programs work under certain circumstances. An SE program cannot be successful without a participating client  affecting the success rates of SE programs  growth, and unemployment rates but also the political and societal structures. Researchers determined that unemployment rate and GDP growth might influence the employment rates of SE program clients Below is the link to the electronic supplementary material.


Gene–diet interaction is related to the progression of diabetes and cardiovascular diseases biomarkers. We aimed to evaluate the interaction between diet quality indices and BDNF Val66Mat (rs6265) on cardiometabolic markers among diabetic patients.This cross-sectional study was conducted on 634 patients with type 2 diabetes mellitus, which were randomly recruited from diabetic centers in Tehran. Dietary intakes were estimated by a previously validated semi-quantitative food frequency questionnaire comprising 147 items. All participants were categorized into three categories, based on healthy eating index (HEI), diet quality index (DQI), and phytochemical index (PI) scores. Polymerase chain reaction was used for genotyping the BDNF Val66Met. Interactions were tested using analysis of covariance in adjusted and crude models.P interactions < 0.05). Moreover, the highest quartile of the DQI and PI, compared to the lowest, showed lower TG level among Met allele carriers compared to Val/Val homozygotes  and a faster reduction in IL-18 and TC level was seen among Met/Met, Val/Met who had higher HEI intake than those with Val/Val genotype.Our result showed that higher DQI, HEI, and PI scores significantly decrease body mass index and waist circumference among individuals with Met/Met, Val/Met, and Val/Val genotypes (BDNF Val66Met polymorphism may interact with HEI, DQI, and PI. We have revealed that Met allele acts as a protective allele for diabetic patients and may have a beneficial influence on cardio-metabolic factors through regulating dietary intake. Type 2 diabetes mellitus (T2DM) as a major multi-factorial chronic health concern is rising rapidly worldwide, and cardiovascular diseases (CVDs) are known as the most common disorders and the main cause of death among patients with T2DM . ConclusA few studies have evaluated the association between DQI and HEI with CVDs risk factors among diabetic patients. An inverse relationship between HEI and obesity but no relationship between DQI and body mass index (BMI) has been reported in a recent review among Chinese people . Also, tThis study is part of a larger investigation in which 634 T2DM patients (252 men and 382 women) aged 35–65 years were randomly recruited from diabetes centers such as the Iranian diabetes society and other health centers in Tehran . This grGeneral information including age, gender, job, smoking and alcohol abuse, lipid-lowering drug consumption, family history of T2DM, and other diseases was collected through interviews. Anthropometric data (body mass index (BMI) and WC) and physical activity (METs) information were taken according to standard protocols . PhysicaThe participant’s usual dietary intake during the last year was evaluated through face-to-face interviews with a trained dietitian and using a semiquantitative food frequency questionnaire (FFQ) for 147 food items. This questionnaire was validated by Esmaillzadeh et al. . The subThree dietary indices were used for evaluating diet quality including the Healthy Eating Index (HEI), assessing dietary intake according to the 2015–2020 dietary guidelines for Americans (DGA) based on a 1000 kcal/day diet. HEI-2015 score ranged from 0 to 100 and consisted of 13 components  (higher intakes receive lower scores) . We calcThe Diet Quality Index-International (DQI-I) was a second dietary measurement that focuses on four main aspects of a healthy diet . The score for each category is calculated as the sum of the scores for each component in that category. Overall food group variety includes meat/poultry/fish/eggs/dairy/beans/grain/fruit/vegetable (0–15 points), and within-group variety for protein source includes meat/poultry/fish/dairy/beans/eggs (0–5 points), protein sources, vegetable, fruit, grain, fiber, protein, iron, calcium, vitamin C group (0–5 points), moderation foods such as saturated and total fat, cholesterol (CL), sodium and junk foods (0–30 points), macronutrient, and fatty acid (0–10 points) . The totMoreover, phytochemical index (PI) is known as the percentage of calorie intake derived from foods rich in phytochemicals including fruits, vegetables, whole grains, nuts, seeds, vegetable juices, soy products, and olive oil. The dietary phytochemical index (DPI) was calculated according to the modified method previously developed by McCarty ; [PI =   of serumNormal distribution of data was measured using Kolmogorov–Simonov test. Logarithmic transformations were applied to variables with skewed distribution. Participants were divided into two groups: those with Val/Val and Val/Met genotypes versus those of Met/Met homozygotes (Met/Met group). The data were presented as frequency (%) for categorical variables and as mean ± SD for continuous variables. An independent T test was used to compare the quantitative variables between the two groups, and Chi-square test was used to compare the qualitative variables.P value < 0.05 was considered statistically significant.The association between diet quality indices and anthropometric or biochemical parameters was evaluated by one-way analysis of variance (ANOVA). The interactions between BDNF Val/Met polymorphism and DEI, DQI, and PI on BMI, WC, TC, HDL-C, LDL-C, LDL/HDL, TG, CRP, PTX3, IL18, TAC, SOD, PGF2α, leptin, and ghrelin were tested using analysis of covariance (ANCOVA) test in two multivariate interaction models, before and after adjustment for potential confounders including age, sexuality, smoking, alcohol consumption, and physical activity. The data were analyzed by IBM SPSS , and P = 0.008 and P = 0.02, respectively). Although we found no significant difference regarding other clinical and general parameters across BDNF Val66Met genotypes among the groups, it was seen that Met allele carriers  had nominally significantly higher energy intakes and correspondingly higher intakes of all macronutrients  than those with Val/Val genotype.This cross-sectional study was conducted on 634 T2DM patients with sex distribution of 39.7% and 60.3% in men and women, respectively. The prevalence of the Val66Met genotype among study participants was as follows: The Met allele carrier group had a frequency of 44.2% , and accordingly, the major allele frequency was 55.8% . Anthropometric, general characteristics, nutrient intakes, and comparison of clinical parameters among participants according to BDNF Val66Met genotypes are presented in Tables P = 0.01, P = 0.02, and P = 0.03, respectively). Also, WC level was higher among patients in the first quartiles of HEI and DPI . Patients in the last quartile of HEI and DPI had higher levels of LDL-C . Moreover, a higher level of HDL-C was seen among the patients in the last quartile of HEI (P = 0.01). Regarding HEI, greater adherence reduced the inflammatory markers. There were lower PGF2α (P = 0.03) and PTX (P = 0.02) levels among patients in the second and third quartile, respectively.All participants were categorized into three tertiles, based on HEI, DQI, and DPI scores. Analysis for general and biochemical markers between the tertiles is presented in Table P = 0.001 and P = 0.0, respectively). Our results revealed that higher scores for all diet-quality indices are significantly associated with lower BMI and WC values among all participants. It remained consistently significant even after adjusting for various potential confounders including age, weight, height, and physical activity. Also, interactions between DQI and DPI and Val66Met polymorphism for BMI and WC were significant after adjustment.Significant interactions between BDNF Val66Met polymorphism and DQI, HEI, and PI scores on cardiometabolic markers are shown in Figs. P interaction = 0.01).The highest quartile of DQI was associated with elevated levels of SOD among individuals with Val/Met and Met/Met (This cross-sectional study aimed to assess the interactions between BDNF Val66Met polymorphism and HEI, DQI, and DPI on anthropometric and metabolic markers among diabetic patients. We found patients with lower scores of HEI, DQI, and DPI were more likely to be obese. There was a significant decreasing trend in the odds of BMI and WC across increasing quartiles of all measured dietary indices. Also, WC level was significantly lower among diabetic patients with higher scores for HEI and DPI. It is noteworthy that patients in the highest group of DQI and DPI had lower total fat intake including saturated fats and dietary cholesterol and lower TC level compared with those in the lower quartiles. In addition, higher protein intake was observed among the highest quartile of all the indices compared to the lower groups. A few studies which have investigated the association between dietary indices and anthropometric or cardiometabolic risk factors, reported controversial results. The inverse association between diet quality indices and obesity was approved by some previous studies , 30. QuaIt should be considered that monitoring the overall eating patterns which reflect the intake of all food groups is more effective for finding about diet quality than investigating the effects of particular micro- or macronutrients . SurprisTo our knowledge, the association between diet quality indices and BMI or metabolic markers has been widely investigated. However, a few recent studies have highlighted gene-nutrition interaction on health outcomes , 42. ThuWe present novel findings regarding the interaction between HEI, DQI, DPI, and BDNF Val66Met polymorphism on BMI and WC levels. Moreover, we found significant interactions between DQI and Val66Met polymorphism on SOD, HDL, and leptin, between HEI and the Val66Met polymorphism on PGF2α, HDL, and leptin levels, and between DPI and this polymorphism on HDL levels. We observed BDNF variants affected daily dietary intake such as total energy, carbohydrates, fiber, protein, and fat in diabetic patients. Generally, Met allele carrier group had significantly higher nutritional intake compared to subjects with Val/Val genotype. It might be related to their leptin level, which basically was higher among Met allele carriers. They were also more likely to increase their leptin level in higher scores of HEI and DQI. Further major finding is related to a significant decrease in cardiometabolic risk factors among diabetic patients with higher adherence to HEI and DQI. Met allele carriers were more likely to have experienced a faster reduction in IL-18 and TC levels by having higher HEI intake compared to those with Val/Val genotype. Interestingly, Met allele carriers who consumed diets higher in DQI had a significant decrease in TG level, while it showed an increase for those carrying Val/Val. Several studies have reported that the relationship between T2DM and BDNF Val66Met depends on diet . They foAbaj et al. showed a significant interaction between dietary insulin index and dietary insulin load scores and BDNF Val66Met on BMI level . ConsistThe main limitation of this research is that we could not measure the blood sugar and serum BDNF levels of participants due to time and budget limitations. So, we missed potentially relevant interactions. Besides, although we controlled for several potential confounders, the effects of remaining confounders cannot be ignored. Thus, further investigations in different populations are needed to confirm the findings.The present study revealed a protective effect of Met allele against cardiometabolic markers through modulating dietary patterns among individuals with T2DM. Participants with Met/Met and Val/Met genotypes who had higher DQI and DPI intake have experienced a significant decrease in TG level, while it has increased in homozygous patients for Val allele. Moreover, a major decrease in BMI levels among all patients with higher adherence to HEI, DQI, and DPI was seen. However, it has been shown that consuming higher PUFAs is much more effective for lowering the risk of obesity rather than lower energy and fat intake, especially among those with higher HEI.


Pseudomonas aeruginosa (Pa). It is widely accepted that increasing antibiotic resistance develops in Pa following repeated antibiotic exposure. With the advent of elexacaftor/tezacaftor/ivacaftor (ETI) modulator therapy, we wished to assess Pa antibiotic resistance to beta-lactam and fluoroquinolone (FQ) antibiotics in both children receiving ETI, and those not eligible for ETI (nonETI) who continue to experience recurrent pulmonary exacerbation (PEx) and require repeated antibiotic treatment.CF is a genetic disease characterized by chronic lung infection, often with We examined current patterns of antibiotic resistance over 3 years for a cohort of 11 children with CF having 5 or more positive sputum cultures for Pa between January 2020-December 2022 obtained from CF clinic and hospital PEx sputum samples. Chart review included: demographic data; dates of PEx/hospitalization; dates of CF clinic visits; dates and results of CF sputum cultures; and antibiotics used and dates for intravenous (IV) and oral (PO) treatment courses.Six males and 5 females were reviewed (6/11 [54%] were Hispanic), with 3/11 (27%) on ETI therapy (average age 14.6 yr), and 8/11 (73%) not on ETI therapy (average age 11.6 yr). Average age at acquisition of Pa was 10.2 yrs. The average number of cultures yielding Pa over 3 years was 11 for both ETI and nonETI subjects. Average number of IV antibiotic courses was 6 for nonETI, but 0 for ETI subjects, while the average number of oral (PO) FQ courses with ciprofloxacin/levofloxacin was 6 in nonETI, and only 1 in ETI subjects. No increase in antibiotic resistance was noted against any IV antibiotic over 3 years of observation (Table), but of the 9 subjects (both ETI and nonETI) who received PO FQ, 5 (55%) were documented to have at least one nonsusceptible isolate, as shown for one 16 year old nonETI subject .Current antibiotic/pulmonary management of children with CF was not associated with an increased risk of IV antibiotic resistance over 3 years of observation despite repeated exposure for PEx (mean of 6 IV antibiotic courses per nonETI subject), but susceptibility to FQ decreased in 55% of those treated over 3 years following repeated FQ oral therapy courses.All Authors: No reported disclosures