The effect of hypersensitivity pneumonitis guideline on pathologic diagnosis of interstitial pneumonia Hypersensitivity pneumonitis (HP) and interstitial pneumonia (IP) have several overlapping characteristics, and a high diagnostic concordance rate of HP is rarely obtained. New guideline, highly influenced by pathology, were devised for its diagnosis. We recently reported that the 2020 HP guideline may result in a possible overdiagnosis of fibrotic HP (fHP) through multidisciplinary discussion. Here, we attempted to investigate the impact of the 2020 HP guideline on the pathological diagnosis of cases previously diagnosed as IP. We classified 247 cases with fibrotic IP diagnoses sourced from 2014-2019 into three categories according to the 2020 HP guideline: typical, probable, and indeterminate HP. The original pathological diagnosis and categorization based on the 2020 HP guideline were compared. The clinical data including serum data and pulmonary function tests were compared among groups. The number of cases that changed to HP from an original diagnosis other than HP based on the guideline was 56 (23%). The clinical data of these cases bore a greater resemblance to cases diagnosed as indeterminate for HP than those diagnosed as typical or probable. The ratio of typical and probable HP to the total cases was significantly lower when using a transbronchial lung cryobiopsy (TBLC). Based on the new guideline, the pathological diagnosis of HP efficiently excluded HP cases but increased the rate of HP diagnosis for cases with fibrotic IP that may not suit an HP diagnosis. Thus, a TBLC may not be useful when imparting findings for fibrotic HP diagnosis using the new criteria.

Key messagesO_LIWhat is the key question? >
Does the 2020 HP Guideline improve pathological diagnosis?
C_LIO_LIWhat is the bottom line? >
By applying the new guideline, about 1/4 of the pathological diagnoses were changed from not chronic HP to probable or typical fHP, but most of the changed cases showed a clinical picture closer to not chronic HP.
C_LIO_LIWhy read on? >
To understand that simple application of the pathological criteria of the HP guideline may cause a misleading diagnosis.
C_LI
Variability in proteoglycan biosynthetic genes reveals new facets of heparan sulfates diversity. A systematic review and analysis Proteoglycans are complex macromolecules formed of glycosaminoglycan chains covalently linked to core proteins through a linker tetrasaccharide common to heparan sulfate proteoglycans (HSPG) and chondroitin sulfate proteoglycans (CSPG). Biosynthesis of a single proteoglycan requires the expression of dozens of genes, which together create the large structural and functional diversity reflected by the numerous diseases or syndromes associated to their genetic variability. Among proteoglycans, HSPG are the most structurally and functionally complex. To decrease this complexity, we retrieved and linked information on pathogenic variants, polymorphism, expression, and literature databases for 50 genes involved in the biosynthesis of HSPG core proteins, heparan sulfate (HS) chains, and their linker tetrasaccharide. This resulted in a new gene organization and biosynthetic pathway representation in which the phenotypic continuum of disorders as linkeropathies and other pathologies could be predictable. Moreover, ubiquitous NDST1, GLCE, HS2ST1, and HS6ST1 appeared to generate ubiquitous heparan sulfate (HS) sequences essential for normal development and homeostasis, whereas the tissue restricted NDST2-4, HS6ST2-3, and HS3ST1-6 appeared to generate specialized HS sequences mainly involved in responsiveness to stimuli. Supported by data on genetic polymorphism and clinical variants, we afford a new vision of HSPG involvement in homeostasis, disease, vulnerability to disease, and behavioral disorders.
Precision Diagnostic Approach to Predict 5-Year Risk for Microvascular Complications in Type 1 Diabetes BackgroundIndividuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facilitate the goals of precision diagnostics, including earlier diagnosis and individualized risk scoring.

MethodsUsing data in a cohort of 537 adults with type 1 diabetes (T1D) we predicted five-year progression to DCs. Prediction models were computed first with clinical risk factors at baseline and then with clinical risk factors and blood-derived molecular data at baseline. Progression of diabetic kidney disease and diabetic retinopathy were predicted in two complication-specific models.

FindingsThe model predicts the progression to diabetic kidney disease with accuracy: 0.96{+/-}0.25 and 0.96{+/-}0.06 area under curve, AUC, with clinical measurements and with small molecule predictors respectively and highlighted main predictors to be albuminuria, glomerular filtration rate, retinopathy status at baseline, sugar derivatives and ketones. For diabetic retinopathy, AUC 0.75{+/-}0.14 and 0.79{+/-}0.16 with clinical measurements and with small molecule predictors respectively and highlighted key predictors, albuminuria, glomerular filtration rate and retinopathy status at baseline. Individual risk scores were built to visualize results.

InterpretationWith further validation ML tools could facilitate the implementation of precision diagnosis in the clinic. It is envisaged that patients could be screened for complications, before these occur, thus preserving healthy life-years for persons with diabetes.

FundingThis study has been financially supported by Novo Nordisk Foundation grant NNF14OC0013659.

Research in context

Evidence before this studyMicrovascular diabetes complications (DCs), such as diabetic kidney disease (DKD) and diabetic retinopathy (DR), lead to increased mortality, blindness, kidney failure and overall decreased quality of life in individuals with diabetes.

Added value of this studyWe have developed four algorithms based on traditional risk factors alone and risk factors with metabolomic and lipidomic data. Two accurately predicted the future progression in individuals with type 1 diabetes. The top predictors chosen by the algorithm were hemoglobin A1c, albuminuria and retinopathy status at baseline for diabetic retinopathy. The most promising models predicted future diabetic kidney disease in which albuminuria, eGFR, retinopathy status at baseline were complemented with a number of ketones and sugar derivatives.

Implications of all the available evidenceWith further validation in several cohorts, the prediction models presented here have the potential for early diagnosis of CKD in persons with diabetes, thus enabling appropriate decisions on the available therapies. It is envisaged that these algorithms will be trialed and support clinicians with precision diagnosis and treatments. Impact of a Multidisciplinary Nutritional Support Team on Quality Improvement in Home Parenteral Nutrition IntroductionHPN is essential for patients requiring long term nutritional support. This Quality Improvement Project for HPN Patients (QIP-PN) studied the effect of a Physician Nutrition Expert (PNE)- led multidisciplinary nutritional support team (MNST) on HPN care.

ObjectiveTo test the effect of an MNST on adherence to protocols, outcomes and QOL in HPN.

MethodsData review was conducted in phases 1a and 1b, observation in phase 2 and intervention in phase 3. In Phase 3 the MNST made recommendations to treating physicians. All long-term HPN patients were offered study participation. 75 signed consent forms. Treating physician study participation agreements were signed for 42 patients (the study group). A random sample of 30 long-term HPN patients comprised the case-matched control group (control). Data were collected on demographics, treating physicians PNE status, HPN care variables, recommended interventions, quality-of-life assessment, adverse outcomes and hospitalizations. Independent samples t-test was used for continuous data between study group and control group. Paired t-test was used for phase 2 and phase 3 patient data. Comparison between the study and control group utilized a negative binomial regression model. Statistical analysis utilized R (https://www.r-project.org/).

Results34 patients were reviewed retrospectively in phase 1a and 197 prospectively in phase 1b. 40 study patients completed phase 2 and progressed into phase 3, of whom 30 completed [&ge;]60 therapy days. Improvements in weight, BMI and QOL were seen in the study patients during intervention. Recommendations made and accepted by treating physicians differed based on PNE status. Study patients had fewer adverse outcomes and related hospitalizations than case matched controls.

ConclusionMNST recommendations improved clinical, biochemical parameters and patients self-reported overall health. It reduced adverse outcomes, hospitalization and hospital length of stay. MNST input could have a significant impact on the quality and cost of HPN care. Simple risk scores to predict hospitalization or death in outpatients with COVID-19 including the Omicron variant ImportanceOutpatient physicians need guidance to support their clinical decisions regarding management of patients with COVID-19, in particular whether to hospitalize a patient and if managed as an outpatient, how closely to follow them.

ObjectiveTo develop and prospectively validate a clinical prediction rule to predict the likelihood of hospitalization for outpatients with COVID-19 that does not require laboratory testing or imaging.

DesignDerivation and temporal validation of a clinical prediction rule, and prospective validation of two externally derived clinical prediction rules.

SettingPrimary and Express care clinics in a Pennsylvania health system.

ParticipantsPatients 12 years and older presenting to outpatient clinics who had a positive polymerase chain reaction test for COVID-19.

Main outcomes and measuresClassification accuracy (percentage in each risk group hospitalized) and area under the receiver operating characteristic curve (AUC).

ResultsOverall, 7.4% of outpatients in the early derivation cohort (5843 patients presenting before 3/1/21) and 5.5% in the late validation cohort (3806 patients presenting 3/1/21 or later) were ultimately hospitalized. We developed and temporally validated three risk scores that all included age, dyspnea, and the presence of comorbidities, adding respiratory rate for the second score and oxygen saturation for the third. All had very good overall accuracy (AUC 0.77 to 0.78) and classified over half of patients in the validation cohort as very low risk with a 1.7% or lower likelihood of hospitalization. Two externally derived risk scores identified more low risk patients, but with a higher overall risk of hospitalization (2.8%).

Conclusions and relevanceSimple risk scores applicable to outpatient and telehealth settings can identify patients with very low (1.6% to 1.7%), low (5.2% to 5.9%), moderate (14.7% to 15.6%), and high risk (32.0% to 34.2%) of hospitalization. The Lehigh Outpatient COVID Hospitalization (LOCH) risk score is available online as a free app: https://ebell-projects.shinyapps.io/LehighRiskScore/. Diagnostic Model of in-Hospital Mortality in Patients with Acute ST-Segment Elevation Myocardial Infarction Used Artificial Intelligence Methods BackgroundPreventing in-hospital mortality in Patients with ST-segment elevation myocardial infarction (STEMI) is a crucial step.

ObjectivesThe objective of our research was to to develop and externally validate the diagnostic model of in-hospital mortality in acute STEMI patients used artificial intelligence methods.

MethodsWe divide non-randomly the American population with acute STEMI into a training set, a test set,and a validation set. We converted the unbalanced data into balanc ed data. We used artificial intelligence methods to develop and externally validate the dia gnostic model of in-hospital mortality in acute STEMI patients. We used confusion matrix combined with the area under the receiver operating characteristic curve (AUC) to evaluat e the pros and cons of the above models.

ResultsThe strongest predictors of in-hospital mortality were age, gender, cardiogenic shock, atrial fibrillation(AF), ventricular fibrillation(VF),third degree atrioventricular block,in-hospital bleeding, underwent percutaneous coronary intervention(PCI) during hospitalization, underwent coronary artery bypass grafting (CABG) during hospitalization, hypertension history, diabetes history, and myocardial infarction history.The F2 score of logistic regression in the training set, the test set, and the validation data set were 0.81, 0.6, and 0.59 respectively.The AUC of logistic regression in the training set, the test set, and the validation data set were 0.77, 0.78, and 0.8 respectively. The diagnostic model built by logistic regression was the best.

ConclusionWe had used artificial intelligence methods developed and externally validated the diagnostic model of in-hospital mortality in acute STEMI patients.

We registered this study with WHO International Clinical Trials Registry Platform (ICTRP) (registration number: ChiCTR1900027129; registered date: 1 November 2019). Association of preference and frequency of teleworking with work functioning impairment: a nationwide cross-sectional study of Japanese full-time employees ObjectiveWe examined whether teleworking preference and frequency were associated with work functioning impairment.

MethodsThis online cross-sectional study was conducted using a self-administered questionnaire among 27,036 full-time Japanese workers. The Work Functioning Impairment Scale was used to measure work functioning impairment, and we performed multilevel logistic regression analysis.

ResultsHigher odds ratios for work functioning impairment were observed among employees who preferred to telework compared with those who preferred working in the workplace. A similar trend was observed among employees who teleworked 4 or more days a week compared with those who almost never teleworked. When teleworking preference and frequency were adjusted, only teleworking preference was associated with work functioning impairment.

ConclusionsA preference for teleworking was associated with work functioning impairment and one factor that increased the teleworking frequency. Substance Use Onset in High-Risk 9-13 Year-Olds in the ABCD Study AimA key aim of the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting obscures accurate drug use characterization. Hair toxicology tests provide objective historical substance use data, but are rarely investigated in youth. Here, we compare objective hair toxicology results with self-reported substance use in youth.

MethodsA literature-based substance use risk algorithm identified 696 ABCD Study(R) participants for hair sample collections between baseline and 2-year follow-up (spanning ages 9-13) for laboratory analysis. Chi-square and t-tests assessed differences between participants demographics, positive and negative hair tests, risk algorithm scores, and self-reported substance use.

ResultsHair testing confirmed that 17% of at-risk 9-13 year-olds had evidence of past 3-month use of one (n=99), two (n=17), three (n=3), or four (n=2) drug classes. After considering prescribed medication use, 11% had a positive test incongruent with self- or parent-report. No participant with a positive result self-reported substance use consistent with their toxicology results. Participants with positive tests under-reported use (p<.001), reported less sipping of alcohol (p<.001), and scored higher on the risk algorithm (p<.001) than those with negative hair toxicology.

ConclusionsAn alarming 11% of tested samples in at-risk 9-13 year-olds were positive for at least one unreported substance, suggesting underreporting in this population when participating in a national healthy development study. The degree of underreporting cannot yet be calculated, as at-risk samples were prioritized for assays. Expanded toxicology testing is key to characterize substance use in youth. Airway management, procedural data, and mortality records of patients undergoing surgery for mucormycosis associated with coronavirus disease (COVID-19) In India, the second wave of coronavirus disease (COVID -19) was associated with a distinct surge in cases of invasive fungal infection with mucormycosis. This disease was seen typically in the sinonasal form in COVID-19 patients. Uncontrolled diabetes, steroid use in COVID-19 treatment, etc. were some of the postulated risk factors for the association of COVID 19 and Mucormycosis. The management plan of these cases included surgical debridement, systemic antifungal therapy, sugar control, and management of antifungal related systemic adverse effects. In this retrospective case record review, we aimed to evaluate the airway management plan, demographics, and overall outcomes in patients undergoing surgical resection for COVID-19 associated mucormycosis. Forty-one (71.9 %) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) had a diagnosis of rhino-orbital mucormycosis, and 2 patients (3.5%) were diagnosed with palatal mucormycosis. Total 44 (77.19 %) patients had co-morbidities. The most common co-morbidity was Diabetes Mellitus 42 (73.6%), followed by hypertension 21 (36.84%) and Acute kidney injury 14 (28.07%). We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 out of 57 patients. In our study, mortality occurred in 7 (12.28 %) patients. The median mortality time was 60 (range, 27-74) days. The median time to hospital discharge was 53.5 (range,10-85) days. Managing COVID-19 on its own is challenging and additional mucormycosis can lead to increased morbidity and mortality. Despite challenges and risks, timely and meticulous interventions can reduce complications. Short Practical Regimen of Acupuncture for Melasma: A Prospective Cohort Study in a Tertiary Hospital in Thailand BackgroundMelasma is a common skin pigmentation disorder. Acupuncture shows benefits for patients with melasma, although no standardized method or optimal number of sessions have been determined.

ObjectiveTo comparatively assess clinical outcomes of melasma between five vs ten standard acupuncture sessions.

MethodsWe performed a prospective observational cohort study in all melasma patients at the Acupuncture Clinic, King Chulalongkorn Memorial Hospital, Bangkok, Thailand. All patients were treated with standard acupuncture procedure twice a week and were evaluated after the fifth and the tenth sessions of acupuncture, with a follow-up one week after the last session. Participants were divided into two treatment groups: Groups A and B received five and ten acupuncture sessions respectively. Melasma outcomes were assessed by using the Melanin Index (MI), Melasma Area and Severity Index (MASI), patient-reported improvement scores and acupuncture-related adverse events.

ResultsOf 113 participants, 67 received five sessions of acupuncture treatment while 39 received ten sessions. 7 participants did not finish treatment. After five sessions of acupuncture in Group A, the mean MI decreased by 28.7 (95%CI -38.5 to -18.8), whereas the median MASI decreased by 3.4 (-6.9, -1.2) points. After ten sessions of acupuncture in Group B, the mean MI decreased by 31.3 (95%CI -45.0 to -17.6), whereas the median MASI decreased by 5.4 (-9.9, - 3.0) points. The first five sessions of acupuncture had a higher effect on the change in magnitude than the last five sessions, although there was no statistically significant difference. However, ten-session of acupuncture, had not reached the peak benefit on melasma yet. Further studies should be done with a higher number of sessions to determine the optimal rounds of treatment. Twenty-nine participants reported minor side effects, mostly consisting of persistent pain and small hematoma. Group B had RR of having adverse events 1.8 times (95% CI 1.0-3.4) compared to group A.

ConclusionAcupuncture has a potential dose-response effect on clinical and patient-reported melasma outcomes with minor side effects. Effects of repeated injection of 1% lidocaine vs. radial extra-corporeal shock wave therapy for treating myofascial trigger points: a randomized controlled trial Background and ObjectivesThis study tested the hypothesis that treatment of myofascial trigger points (MTrPs) in the upper trapezius muscle (UTM) with repeated injection of 1% lidocaine results in better alleviation of muscular stiffness and soreness as well as improved metabolism in the hypercontracted MTrP area than treatment with radial extracorporeal shock wave therapy (rESWT).

Materials and MethodsA single-blinded, prospective, randomized controlled trial was conducted on patients suffering from MTrPs in the UTM. Thirty patients were treated with repeated injection of 2 ml of 1% lidocaine (three injections; one injection per week). Another 30 patients were treated with rESWT (three treatment sessions; one treatment session per week; 2000 radial extracorporeal shock waves per treatment session; positive energy flux density = 0.10 mJ/mm2). The primary outcome measure was pain severity using the VAS score. The secondary outcome measures included muscle elasticity index, pressure pain threshold and neck disability index. Evaluation was performed at baseline (T1), 15-30 minutes after the first treatment in order to register immediate treatment effects (T2), before the second treatment (i.e., one week after baseline) (T3) and one week after the third treatment (i.e., four weeks after baseline) (T4).

ResultsThere were no statistically significant differences in the primary and secondary outcome measures between the patients in the lidocaine arm and the patients in the rESWT arm at T1 and T4. Within the arms, the mean differences of all outcomes were statistically significant (P < 0.001) when comparing the data obtained at T1 with the data obtained at T3 and the data obtained at T4.

ConclusionsThe results of this pilot study suggest that the use of rESWT in patients with MTrPs in the UTM is safe and leads to reduced pain and improved muscle elasticty, pressure pain threshold and neck disability index, without adverse effects. Larger trials are necessary to verify this. Clinicians should consider rESWT instead of injections of lidocaine in the treatment of MTrPs in the UTM. High concordance of 70-gene recurrence risk signature and 80-gene molecular subtyping signature between core needle biopsy and surgical resection specimens in early-stage breast cancer IntroductionWith an increase in neoadjuvant therapy recommendations for most early-stage breast cancer patients due to the COVID-19 pandemic, it has become increasingly imperative to ensure that molecular diagnostic assays provide reliable results from preoperative core needle biopsies. Therefore, the objective of this study was to determine the concordance of MammaPrint results (70-gene signature) and BluePrint results (80-gene signature) between core needle biopsies (CNB) and surgical resection (SR) specimens using prospectively collected matched tissues from patients enrolled in the FLEX trial (NCT03053193).

MethodsWe analyzed 113 matched CNB and SR tumor specimens from women with early-stage breast cancer enrolled in the FLEX trial. Each patient enrolled in the trial receives a MammaPrint recurrence risk classification test with or without BluePrint molecular subtyping. Concordance of MammaPrint is reported using overall percentage agreement, positive predictive value (PPV, High Risk), negative predictive value (NPV, Low Risk), and Cohens kappa coefficient. Additionally, correlations between sample types are reported using Pearson correlation coefficient.

ResultsWe found good concordance for MammaPrint results between CNB and SR tumor samples (90.3%, {kappa} = 0.803), with a 95.1% NPV and 84.6% PPV. There was also a strong correlation of MammaPrint indices between CNB and SR specimens (r = 0.94). In addition to our primary objective, we determined the concordance of BluePrint subtyping in the matched tumor samples, and found excellent concordance (98.2%) and strong correlation of BluePrint scores within each subtype.

ConclusionCNB samples demonstrated overall high concordance with paired SR samples for MammaPrint risk classification, ensuring that physicians are provided with accurate prognostic information for therapy decisions based on testing of core biopsy tissue. Further, BluePrint molecular subtyping also had good concordance between the sample types, outperforming concordance rates based on traditional IHC based classification. Overall, with an increase in neoadjuvant therapy, physicans and patients can be assured that MammaPrint and BluePrint provide reliable results that guide timely and appropriate therapies using preoperative CNB specimens. Effectiveness of a short term induction regimen of a biosimilar Adalimumab in the long term management of symptomatic Ankylosing Spondylitis Symptomatic Ankylosing Spondylitis: A Community Based Proof of Concept Observational Study IntroductionCost and drug toxicity often deter prolonged therapeutic use of anti-TNF agents in ankylosing spondylitis (AS). A planned study was completed to endorse our clinic based observation of long term relief following short-term administration of anti-TNF agent.

Methods50 consenting patients with symptomatic active chronic AS under rheumatology care in a community clinic were enrolled. They had no past history of anti-TNF use. 40 mg standard biosimilar adalimumab (BS-ADA, Exemptia trade name)was injected subcutaneously every fortnight for six injections (10 weeks). Patients were monitored at several time points. Improvement was assessed at regular interval as per protocol which included standard indices (Bath and Assessment Spondyloarthritis International Society /ASAS). An intention to treat analysis with significant p<0.05 was carried out.

ResultsPatients showed early and substantial significant improvement in pain, NSAID requirement, function and in several indices (ASAS 20 & 40, ASAS partial remission, BASDAI, BASFI, ASDAS) which persisted after stopping injections. 84% and 52 % of patients respectively showed ASAS 20 improvement at week 12 and 48: corresponding ASAS partial remission 34% and 24%. Over 50% patients maintained prolonged improvement and provided proof of concept (defined a-priori). Serum Interleukin-6 assay showed a sharp reduction at 24 weeks. None developed TB or serious drug toxicity. 11 patients withdrew (mostly inadequate response). Absence of control was a limitation.

ConclusionA ten-week administration of biosimilar adalimumab in difficult to treat AS showed early substantial improvement which often persisted for 24 weeks. This unconventional strategy was socioeconomically appealing. It merits further validation and acceptance especially in resource strained settings. Classifying Radiology Abstracts with Deep Learning BackgroundThe Radiological Society of North America (RSNA) receives more than 8000 abstracts yearly for scientific presentations, scientific posters, and scientific papers. Each abstract is assigned manually one of 16 top-level categories (e.g. "Breast Imaging") for workflow purposes. Additionally, each abstract receives a grade from 1-10 based on a variety of subjective factors such as style and perceived writing quality. Using machine learning to automate, at least partially, the categorization of abstract submissions can result in saving many hours of manual labor.

MethodsA total of 45527 RSNA abstract submissions from 2014 through 2019 were ingested, tokenized, and pre-processed with a standard natural language programming protocol. A bag-of-words (BOW) model was used as a baseline to evaluate two more sophisticated models, convolutional neural networks and recurrent neural networks, and also evaluate an ensemble model featuring all three neural networks.

Resultsensemble model was able to achieve 73% testing accuracy for classifying the 16 top-level categories, outperforming all other models. The top model for classifying abstract grade was also an ensemble model, achieving a mean average error (MAE) of 1.01.

ConclusionWhile the baseline BOW model was the highest performing individual classifier, ensemble models that included state-of-the-art neural networks were able to outperform it. Our research shows that machine learning techniques can, to a reasonable degree of accuracy, predict both objective factors such as abstract category as well as subjective factors such as abstract grade. This work builds upon previous research involving using natural language processing on scientific abstracts to make useful inferences that address a meaningful problem. Covid-19 Associated Hepatitis in children (CAH-C) during the second wave of SARS-CoV-2 infections in Central India: Is it a complication or transient phenomenon. Objective: While pediatric population has largely remained free of severe COVID-19, in some cases SARS-CoV-2 infection has been associated with complications like Multiple Inflammatory Syndrome in children (MIS-C). We mention another unique presentation subsequent to asymptomatic infection of SARS-CoV-2, a unique form of hepatitis designated by us as COVID-19 Associated Hepatitis in Children (CAH-C). The contrasting clinical presentations, temporal association and viral parameters of CAH-C cases, to the MIS-C cases are presented here. Methods: As a retrospective and follow-up observational study we reviewed all children testing positive for SARS-CoV-2 during study period. Children presenting with sudden onset of hepatitis, elevated transaminases, non-obstructive jaundice, lacking marked inflammatory responses and without evidence of (a) other known causes of acute hepatitis or previous underlying liver disease (b) multi-system involvement were classified as CAH-C, are described here. Results: Among 475 children who tested positive, 47 patients presented with hepatitis, 37 patients who had features of CAH-C, having symptoms of hepatitis only, with un-elevated inflammatory markers and uneventful recovery following supportive treatment. Whereas remaining 10 MIS-C hepatitis had protracted illness, multiple system involvement, required admission to critical care, and had mortality of 30%. Conclusion: With the emergence of newer variants of concern (VOC) including the Delta variant which predominated the second wave of infections in India and has now spread to more than 142 countries with changing presentations, CAH-C might be one of them. Cases of such new entities need to be identified early and differentiated from other emerging syndromes in children during the ongoing pandemic for preventing adversities by timely intervention. Meta-analytic findings on reading in children with cochlear implants This meta-analysis study aims to quantify the group differences in reading skills between children with cochlear implants and their hearing peers and between children with cochlear implants and children with hearing aids (aged between 3 to 18 years old). Of the 5,642 articles screened, 47 articles met predetermined inclusion criteria (published between 2002 and 2019). The robust variance estimation based meta-analysis models were used to synthesize all the effect sizes. Children with cochlear implants scored significantly lower than their hearing peers in phonological awareness (g = - 1.62, p < .001), vocabulary (g = -1.50, p < .001), decoding (g = -1.24, p < .001), and reading comprehension (g = -1.39, p < .001), but not for fluency (g = -.67, p = .054). Compared to children with hearing aids, children with cochlear implants scored significantly lower in phonological awareness (g = -.30, p = .028). The percentage of unilateral cochlear implant negatively impacts the group difference between children with cochlear implants and their hearing peers. Findings from this study confirm a positive shift in reading outcomes for profoundly deaf children due to cochlear implantation. Some children with cochlear implants may need additional supports in educational settings. The kidney releases a non-polymerizing form of Uromodulin in the urine and circulation that retains the external hydrophobic patch domain Uromodulin (Tamm-Horsfall protein, THP) is a glycoprotein uniquely produced in the kidney. It is released by cells of the thick ascending limbs (TAL) apically in the urine, and basolaterally in the renal interstitium and systemic circulation. Processing of mature urinary THP, which polymerizes into supra-molecular filaments, requires cleavage of an external hydrophobic patch (EHP) at the C terminus. However, THP in the circulation is not polymerized, and it remains unclear if non-aggregated forms of THP exist natively in the urine. We propose that an alternative processing path, which retains the EHP domain, can lead to a non-polymerizing form of THP. We generated an antibody that specifically recognizes THP with retained EHP (THP+EHP) and established its presence in the urine in a non-polymerized native state. Proteomic characterization of urinary THP+EHP revealed its C-terminus to end at F617. In the human kidney, THP+EHP was not only detected in TAL cells, but also diffusely in the renal parenchyma. Using immunoprecipitation followed by proteomic sequencing and immunoblotting, we then demonstrated that serum THP has also retained EHP. In a small cohort of patients at risk for acute kidney injury (AKI), admission urinary THP+EHP was significantly lower in patients who subsequently developed AKI during hospitalization. Our findings uncover novel insights into uromodulin biology by establishing the presence of an alternative path for cellular processing, which could explain the release of non-polymerizing THP in the circulation. Larger studies are needed to establish the utility of urinary THP+EHP as a sensitive biomarker of kidney health and susceptibility to injury. Adaptation of HL7 FHIR for the exchange of patients' gene expression profiles High-throughput technologies, especially gene expression analyses can accurately capture the molecular state in patients under different conditions. Thus, their application in clinical routine gains increasing relevance and fosters patient stratification towards individualized treatment decisions. Electronic health records already evolved to capture genomic data within clinical systems and standards like FHIR enable sharing within, and even between institutions. However, FHIR only provides profiles tailored to variations in the molecular sequence, while expression patterns are neglected although being equally important for decision making. Here we provide an exemplary implementation of gene expression profiles of a microarray analysis of patients with acute myeloid leukemia using an adaptation of the FHIR genomics extension. Our results demonstrate how FHIR resources can be facilitated in clinical systems and thereby pave the way for usage for the aggregation and exchange of transcriptomic data in multi-center studies. Adjunctive Ketamine for Sedation in Critically Ill Mechanically Ventilated Patients: An Active-Controlled, Pilot, Feasibility Clinical Trial ObjectiveKetamine has been shown to decrease sedative requirements in intensive care unit (ICU). Randomized trials are limited on patient-centered outcomes. We designed this pilot clinical trial to evaluate the feasibility of using ketamine as an adjunct analgosedative compared with standard of care (SOC) alone and determine preliminary effect size on 28-day mechanical ventilation (MV) duration and ventilator-free days (VFDs).

DesignPilot, single-center, active-controlled, open-label, randomized clinical trial.

SettingMedical, surgical, and transplant ICUs at King Faisal Specialist Hospital and Research Center, Saudi Arabia.

Patients and MethodsAdult patients who were intubated within 24 hours, expected to require MV for the next calendar day, and had institutional pain and sedation protocol initiated.

InterventionAdjunct ketamine infusion 1-2 g/kg/min for 48 hours versus SOC.

Measurements and Main ResultsTotal of 83 patients (43 in SOC and 40 in ketamine) were included. Demographics were balanced between groups. Median MV duration was 7 (interquartile range [IQR] 3-9.25 days) in ketamine and 5 (IQR 2-8 days) in SOC, p= 0.15. Median VFDs was 19 (IQR 0-24.75 days) in ketamine and 19 (IQR 0-24 days) in the SOC (p=0.70). More patients attained goal RASS score at 24 and 48 hours in ketamine (67.5% and 73.5%, respectively) compared with SOC (52.4% and 66.7%, respectively). Sedatives and vasopressors cumulative doses, and hemodynamic changes were similar. ICU length-of-stay was 12.5 (IQR 6-21.2 days) in ketamine, compared with 12 (IQR 5.5-23 days) in SOC, p=0.89. Consent and protocol adherence rate were adequate. No serious adverse events were observed in either group.

ConclusionsUse of ketamine as an adjunct analgosedative agent appeared to be feasible and safe with no negative impact on outcomes, including hemodynamics. The protocol of this pilot trial could be improved by modifying ketamine dosing regimen. These findings provide a basis for future, adequately powered, multicenter trial to investigate its association with patient-centered outcomes further. Examining the Factor Structure of the DSM-5 Level 1 Cross-Cutting Symptom Measure ObjectivesThe DSM-5 Level 1 Cross-Cutting Symptom Measure (DSM-XC) is a transdiagnostic mental health symptom measure that has shown promise in informing clinical diagnostic evaluations and as a screening tool for research. However, few studies have assessed the latent dimensionality of the DSM-XC. We examined the factor structure of the DSM-XC in a large convenience sample of participants with varying degrees of psychological health.

MethodsParticipants (n=3533) enrolled in a protocol conducted at the National Institute of Mental Health (NCT04339790). We used a factor analytic framework to evaluate an existing two-factor solution (Lace & Merz, 2020) and two additional candidate solutions.

ResultsThe Lace and Merz solution had acceptable fit. Exploratory factor analysis yielded two candidate solutions: a six-factor (characterized as mood, worry, activation, somatic, thoughts, and substance use) and a bifactor (general factor of non-specific psychopathology, residual factors characterized as internalizing and thought disorder), which both had good fit and full measurement invariance across age, sex, and enrollment date.

ConclusionsOur findings confirm that the DSM-XC may be conceptualized as a multidimensional instrument and provide a scoring solution for researchers who wish to measure distinct constructs. Future research on the psychometric profile of the DSM-XC is needed, focused on the validity of these candidate solutions and their performance across research populations and settings. Strain-resolved analysis in a randomized trial of antibiotic pretreatment and maintenance dose delivery mode with fecal microbiota transplant for ulcerative colitis Fecal microbiota transplant is a promising therapy for ulcerative colitis. Parameters maximizing effectiveness and tolerability are not yet clear, and it is not known how import the transmission of donor microbes to patients is. Here (clinicaltrails.gov: NCT03006809) we have tested the effects of antibiotic pretreatment and compared two modes of maintenance dose delivery, capsules versus enema, in a randomized, pilot, open-label, 2x2 factorial design with 22 patients analyzed with mild to moderate UC. Clinically, the treatment was well-tolerated with favorable safety profile. Of patients who received antibiotic pretreatment, 6 of 11 experienced remission after six weeks of treatment, versus 2 of 11 non-pretreated patients (odds ratio: 1.69, 95% confidence interval: -0.25 to 3.62). No significant differences were found between maintenance dosing via capsules versus enema. In exploratory analyses, microbiome turnover at both the species and strain levels was extensive and significantly more pronounced in the pretreated patients. Associations were also revealed between taxonomic turnover and changes in the composition of primary and secondary bile acids. Together these findings suggest that antibiotic pretreatment contributes to microbiome engraftment and possibly clinical effectiveness, and validate longitudinal strain tracking as a powerful way to monitor the dynamics and impact of microbiota transfer. COVID Outcome Prediction in the Emergency Department (COPE): Development and validation of a model for predicting death and need for intensive care in COVID-19 patients Background and aimCOVID-19 is putting extraordinary pressure on emergency departments (EDs). To support decision making in the ED, we aimed to develop a simple and valid model for predicting mortality and need for intensive care unit (ICU) admission in suspected COVID-19 patients.

MethodsFor model development, we retrospectively collected data of patients who were admitted to 4 large Dutch hospitals with suspected COVID-19 between March and August 2020 (first wave of the pandemic). Based on prior literature we considered quickly and objectively obtainable patient characteristics, vital parameters and blood test values as predictors. Logistic regression analyses with post-hoc uniform shrinkage was used to obtain predicted probabilities of in-hospital death and of the need for ICU admission, both within 28 days after hospital admission. We assessed model performance (Area Under the ROC curve (AUC); calibration plots) with temporal validation in patients who presented between September and December 2020 (second wave). We used multiple imputation to account for missing values.

ResultsThe development data included 5,831 patients, of whom 629 (10.8%) died and 5,070 (86.9%) were discharged within 28 days after admission. ICU admission was fully recorded for 2,633 first wave patients in 2 hospitals, with 214 (8%) ICU admissions within 28 days. A simple model - COVID Outcome Prediction in the Emergency Department (COPE) - with age, respiratory rate, C-reactive protein, lactic dehydrogenase, albumin and urea captured most of the ability to predict death. COPE was well-calibrated and showed good discrimination in 3,252 second wave patients (AUC in 4 hospitals: 0.82 [0.78; 0.86]; 0.82 [0.74; 0.90]; 0.79 [0.70; 0.88]; 0.83 [0.79; 0.86]). COPE was also able to identify patients at high risk of needing IC in 706 second wave patients with complete information on ICU admission (AUC: 0.84 [0.78; 0.90]; 0.81 [0.66; 0.95]). The models are implemented in web-based and mobile applications.

ConclusionCOPE is a simple tool that is well able to predict mortality and need for ICU admission for patients who present to the ED with suspected COVID-19 and may help patients and doctors in decision making.

CONTRIBUTION TO THE LITERATUREO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIPrediction models have the potential to support decision making about hospital admission of patients presenting to the emergency department with suspected COVID-19
C_LIO_LIMost currently available models that were independently assessed contain a high risk of bias
C_LIO_LIPromising models were developed in different patient selections and included predictors that are not quickly and objective obtainable in emergency departments
C_LI

What this study addsO_LIA simple and objective tool ("COPE") is well able to predict mortality and need for ICU admission for patients who present to the ED with suspected COVID-19
C_LIO_LICOPE may support ED physicians to identify high-risk patients - i.e. those at high risk of deterioration and/or death - requiring treatment in the ICU, intermediate-risk patients requiring admission to the clinical ward, and low-risk patients who can potentially be sent home
C_LI When efficacy and adherence conflict: preferences and patterns of response to mask-wearing and social distancing public health advice during the COVID-19 pandemic With recurring waves of the Covid-19 pandemic, a dilemma facing public health leadership is whether to provide public advice that is medically optimal (e.g., most protective against infection if followed), but unlikely to be adhered to, or advice that is less protective but is more likely to be followed. To provide insight about this dilemma, we examined and quantified public perceptions about the tradeoff between (a) the stand-alone value of health behavior advice, and (b) the advices adherence likelihood. In a series of studies about preference for public health leadership advice, we asked 1,061 participants to choose between (1) strict advice that is medically optimal if adhered to but which is less likely to be broadly followed, and (2) relaxed advice, which is less medically effective but more likely to gain adherence - given varying infection expectancies. Participants preference was consistent with risk aversion. Offering an informed choice alternative that shifts volition to advice recipients only strengthened risk aversion, but also demonstrated that informed choice was preferred as much or more than the risk-averse strict advice. Culture and understanding the role of feedback for health professions students: Realist synthesis protocol. IntroductionClinical education has moved to a "competency-based" model with an emphasis on workplace-based learning and assessment which, in turn, depends on feedback to be effective. Further, the understanding of feedback has changed from information about a performance directed to the learner performing the task, to a dialogue, which enables the learner to act and develop.

In health professional education, feedback is a complex interaction between trainee, supervisor, and the healthcare system. Most published research on feedback in health professional education originates in Europe and North America. Our interest is on the impact of Culture on this process, particularly in the context of Asian cultures.

The (scientific) realist approach of Pawson and Tilley provides a means to examine complex interventions in social situations, and thus is an appropriate lens to use for this study. This is a protocol for a realist synthesis which asks how, why and in what circumstances do Asian Cultures influence health professional trainees to seek, respond to and use feedback given in the clinical environment, if at all.

Methods and analysisAn initial search was performed to help define the scope of the review question and develop our initial program theory. The formal electronic search was carried out in February 2020 and included: CINAHL, ERIC, MEDLINE, and PsycInfo, and repeated in October 2020.

Retrieved articles were imported into Covidence for screening and data extraction, after which components of the Context - Mechanisms - Outcomes configurations will be sought to refine the initial program theory.

Ethics and DisseminationAs this study is a literature review, ethics approval is not required.

The findings will be documented in line with the RAMESES publications standards for Realist syntheses,[41] and we plan to disseminate the findings by means of a peer-reviewed journal article and conference presentation(s).

Strengths and limitations of this studyO_LIThe synthesis aims to identify the how and why Asian Cultures may influence feedback seeking and provision to health professional trainees, if at all.
C_LIO_LITo our knowledge, there are few studies of feedback seeking and provision to health professional trainees in Asia.
C_LIO_LIA Realist approach has the potential to help explain the complex nature of Cultures impact on feedback.
C_LIO_LIOnly studies published in the English language will be included, so transferability of our findings to non-English speaking environments may be lacking.
C_LIO_LIIn addition to formal literature database searches, we will need to conduct citation mining to locate other relevant resources.
C_LI