Linear and logistic regression models were used to analyze the relationship between different antibiotics and the major genes contributing to the clustering of observations for the different animal groups. Clustering revealed different farm clusters for sows, suckling piglets, and weaned piglets, with the most remarkable diversity in antibiotic use among weaned piglets. Amoxicillin, lincomycin, and enrofloxacin were identified as the most probable cause of increased odds of the presence of relevant antibiotic resistance genes . Still, direct effects of a specific antibiotic on its associated resistance gene were rare. Enrofloxacin and florfenicol favored the occurrence of C. difficile in sows. The E. coli fimbriae genes were less affected by antibiotic use in sows and piglets, but the F4 fimbriae gene could be associated with the integrase 1 gene in piglets. The results confirm that multidrug-resistant enterobacteria are widespread in German pig farms and give awareness of the impact of current antibiotic use while searching for alternative health strategies.Reducing antibiotic use is one of the biggest challenges in pig farming, as antibiotics have been used for years to control typical problems such as newborn or post-weaning diarrhea. The pressure a one health approach has created on animal production regarding antimicrobial resistance is an opportunity to find other strategies against enterobacterial pathogens in suckling and weaned piglets. A farm-specific approach could have a good success due to the individual farm structures in Germany and other countries. In this study, non-metric multidimensional scaling, hierarchical clustering, and latent class analysis were used to determine the impact of antibiotic use on antibiotic resistance patterns and pathogen prevalence in 20 German pig farms. This may help to develop individualized health strategies. 802 fresh fecal samples were collected from sows and piglets from 20 piglet production and rearing farms at different production times . In addition, the use of antibiotics was recorded. DNA extracts were subjected to quantitative real-time qPCR with primers specific for antibiotic resistance genes ( In modern pig production, two problems are facing each other: antibiotic resistance and pathogenic agents, which hinder a desired reduction of antibiotic consumption. Especially newborn and weaning animals are susceptible to diarrheal diseases, which can often only be controlled with antibiotics. Therefore, most antibiotics are used at a young age, especially during the weaning transition, and are usually administered for metaphylaxis .Escherichia coli (ETEC), with fimbriae F4 and F18 being the major pathogenicity factors found in pigs [Post-weaning diarrhea (PWD) is mainly governed by enterotoxigenic  in pigs . Environ in pigs . Neverthmcr-1 gene, first discovered in China [Colistin is widely used for antibiotic control of intestinal disorders in piglets . Still, in China , is alsoin China –8 and thin China .CTX-M types are widely distributed in farm animals, such as pigs and poultry [Another problem are ESBL-producing enterobacteria, which are resistant to beta-lactam antibiotics such as penicillin, amoxicillin, and cephalosporins. For a long time, they have been among the greatest threats to human medicine, and their spread in food-producing animals forms an additional danger of dissemination . In part poultry ,12. Beta poultry . Other ain vitro. Mobile genetic elements on plasmids lead to the easy spread of resistance genes within the bacterial community, and antibiotics enhance this via selection pressure [E. coli [Mechanisms of resistance transfer have been well studied pressure . So-callpressure . Some ob[E. coli . Links b[E. coli , but eviIn Germany, antibiotics dispensed by veterinarians to farmers are documented and monitored by law (German Veterinary Medicine Act). If limits are exceeded, the veterinarian and farmer must initiate measures to reduce them. Since the recording of the quantities of antibiotics dispensed to veterinarians in 2011, there has been a significant decrease in antibiotic use, also in the area of pig production . NeverthE. coli, Clostridium perfringens and Clostridioides difficile are associated with diarrhea [Salmonella plays a role throughout pig production. Infections also lead to enteritis, and some Salmonella strains can carry a broad spectrum of antibiotic resistance. Even without a clinical outbreak in the host, they pose a risk to the end consumer because pork is one of the most significant vectors for Salmonella [In newborn piglets, besides diarrhea . Howeverdiarrhea . In addilmonella ,22.The present study is part of a larger project called OptiBiom, which aims to combat typical problems in pig production such as neonatal and post weaning diarrhea. An earlier study has already found evidence that there are farm-specific- and sow-piglet-specific patterns in the fecal microbiota composition in German sow farms . Thus, tThis study focuses on investigating 20 German pig farms for antibiotic resistance genes, bacterial genes, and virulence genes as well as antibiotic treatment at different production times. This approach may help to build knowledge and databases for relevant antimicrobial resistance and virulence patterns in German pig farms. Additionally, the data of the present study might alone help to give awareness to combat routine antibiotic treatment.The present study is not an animal experiment as defined by the German Animal Welfare Act (TierSchG 2006). Fecal samples were collected non-invasively. The farm owners gave their written consent to sampling and data collection on their farms and to the publication of our results.The study design was based on sampling the same sows and their offspring over a period of seven weeks during the production cycle . A total of 802 fresh fecal samples were acquired from 10 ± 1 sows and 10 ± 1 piglets from 20 different piglet production and rearing farms. The antibiotic use on the farms was recorded throughout the sampling phase  according to the manufacturer’s instructions. Fluorescence was measured with a microplate reader  at 506 nmEx/535 nmEm.DNA concentration was determined using Promega QuantiFluorDNA extracts were subjected to quantitative real-time qPCR with primers specific for antibiotic resistance genes, pathogen genes, and virulence factors of relevant bacteria . A level of 95% confidence was deemed as significantly different.Due to a large amount of information on antibiotic use present in the data, a nonmetric multidimensional scaling (NMDS) procedure was used to reduce the dimensionality and improve the visualization of the results. This procedure assesses similarities between samples when considering multiple variables of interest. It creates a matrix of similarities (dissimilarities) for each animal group’s binary variable–application or no application–of different antibiotics. The Jaccard distance was used as a dissimilarity measure, given the dataset structure. Unlike principal component analysis, this procedure was more suitable for the data type at hand since it did not require to fulfill multivariate normality nor multivariate homoscedasticity assumptions. The generated NMDS matrices allowed a hierarchical clustering for the observations in each animal group.To analyze the presence/absence (binary data) of target genes, the Latent Class Analysis (LCA) was implemented to cluster the data. This method allows the creation of classes or clusters characterized by a pattern of conditional probabilities indicating the chance that a target gene has to take on specific values, also giving probabilities of observations belonging to the class. The LCA was conducted first on a different number of classes to find the optimal number of classes to use for the analysis by comparing the Akaike Information Criterion (AIC) of each model. This optimal number was the same for all animal groups analyzed. Then the procedure was applied repeatedly several times to ensure model optimality. The analysis was conducted separately for the two classes of target pathogenic and resistance genes for both sows and piglets, divided into antepartum and postpartum sows and suckling and weaning piglets. NMDS analysis and LCA were conducted using software R (version 4.1.0.).Following the LCA on the antibiotic resistance genes, a variable selection procedure has been conducted to detect the most relevant genes contributing to clustering the observations for the different animal groups. Once those genes had been detected, the aim was to analyze their relationship with different antibiotics. A generalized linear regression model has been implemented for those cases with low zeros. In the case of inflation of zeros, first, a logistic model was implemented using the presence/absence of the gene information (1/0 variable) as the dependent variable and then applying the normal linear model on those observations having a concentration greater than zero. This methodology was used to spot the potential differences between those units not having/having a concentration of one of the relevant genes. For those genes where the Shapiro test indicated a poor normal fit, a transformation was applied to the distribution of the gene concentration, scaling it between 0 and 1. Then a beta regression was used in those cases. The application/not application of antibiotics was used as a predictor for the models. In each model, all antibiotics available for that particular animal group were used at the first step, then using a variable selection method based on the AIC indicator. Each model was updated, dropping those predictors (antibiotics), resulting in not being relevant for the model.blaCTX-M, sul1-3, dfrA1, mcr-1, int1), bacteria, and virulence genes (C. perfringens (cpa), C. difficile (Cdiff)), Salmonella (QVR), Escherichia/Hafnia/Shigella (Escherichia), and E. coli virulence factors  were recorded. The whole data set is shown in the supporting information  and sul1-3 (>98%), as well as the 16S rDNA copy numbers for the Escherichia group (>98%)  and the mcr-1 gene for colistin resistance (26%). Overall, E. coli fimbriae genes were also seen at low prevalence (<20%). Genes for C. perfringens and C. difficile, as well as for trimethoprim resistance (dfrA1) were highly prevalent (>76%), while the gene for ESBL (blaCTX-M) had a wide range (27–78%) of prevalence between farms , and colistin (mcr-1) resistance significantly decreased after birth, while the prevalence for the ESBL gene blaCTX-M significantly increased.The comparison of antepartum and postpartum sows showed that C. perfringens and C. difficile in weaned piglets, while only a marginal, albeit significant, increase for the Escherichia group was observed (S5 Table in dfrA1) and the related enterobacterial integrase I showed significantly lower concentrations in weaned piglets. Similarly, the prevalence of these genes also significantly decreased after weaning. Regarding the E. coli fimbriae genes, the fedA gene displayed a drastic increase in both quantity and prevalence. The prevalence of the fae gene increased after weaning, while the fas gene decreased significantly.Suckling and weaned piglets showed significantly lower concentrations and the prevalence of A non-metric multidimensional scaling (NMDS) approach with a hierarchical clustering analysis was employed to differentiate individual farms according to their antibiotic use to investigate possible farm-specific patterns. First, the NMDS analysis found farms that belonged to the same similarity cluster. Due to the use of different antibiotics in sows and piglets, different clusters formed. Thus, two NMDS clusters were found for sows . The larE. coli fimbriae was analyzed by cluster. For example, a higher prevalence of blaCTX-M -positive farms was calculated for postpartum sows from farms belonging to cluster 2  in suckling piglets. In post-weaning piglets, there were more significant differences in gene prevalence between clusters. While blaCTX-M is present in suckling piglets in all farms, it is absent in post-weaning piglets, especially in clusters 2 and 3. In addition, C. difficile is mainly present in cluster 2, while it is equally distributed in cluster 1. The cpa gene is more prevalent in all farms, in contrast to the suckling piglets. FedA is predominantly absent in all farms, as in the suckling piglets, but it is more abundant in cluster 1. Fae is present in cluster 4 (only one farm) but similar to suckling piglets, absent in all other clusters.Only the dfrA1), colistin (mcr-1), and the ESBL gene blaCTX-M were most relevant for clustering. However, time- and animal-related differences were noticed. Thus, dfrA1 and blaCTX-M were most relevant in ante- and postpartum sows, while in suckling piglets dfrA1 and mcr-1 were most relevant. All three antibiotic resistance genes were relevant in weaned piglets. The association of relevant antibiotic resistance genes with individual antibiotics use on the farms was studied depending on the data via general linear or beta linear regression on gene concentration or logistic regression on the odds of presence  enabled us to select the most relevant genes that contribute to the clustering of observations for the different animal groups. The LCA analysis showed that the antibiotic resistance genes for trimethoprim  and the sulfonamide (sul-3) resistance showed relatively high and much more uniform results among those specific genes. These two genes are more or less ubiquitous in German pig farms. The sul3 gene was detected 20 years ago and was already present in one-third of the sulfonamide-resistant pathogenic E. coli isolates from pigs in Switzerland [sul3 carrying bacterial isolates from manured soils and pig slurries [sul1-3 genes was measured and may yield a complete picture of sul1-3 mediated sulfonamide resistance potential of the fecal resistome in pigs. The presence of int1 has been associated with increased antibiotic resistance in antibiotic-resistant E. coli isolates [int1 gene can be closely related to sulfonamide resistance in uropathogenic E. coli [int1 and sul1-3 in this study. Furthermore, this acknowledges the far-spread potential of enterobacteria to incorporate foreign DNA via integrons. Finally, due to its ubiquitous presence, the int1 gene may be a suitable quantitative indicator gene to assess the potential for gene transfer in enterobacterial populations in pigs. A higher quantity of the fedA gene was also observed in weaned piglets than in suckling. In contrast, most other pathogens and antibiotic-resistance genes showed comparable or lower quantities after weaning. This may be because pathogenic E. coli are typical post-weaning pathogens that capitalize on the intestinal disorder caused by the drastic changes in the animal that occurs during weaning [C. difficile and C. perfringens are pathogens that primarily infect suckling piglets [The present study is part of the research project ‘Optibiom’, which combines metadata from farms with data from the fecal microbiota of sows and piglets to find a framework for the development of new health strategies. Thus, this study aimed to associate antibiotic resistance patterns and the presence of (facultative) bacterial pathogens and virulence factors with antibiotic use on 20 German pig farms. For this purpose, we used different methods to find answers to a chain of questions successively. First, we quantified a number of relevant genes via qPCR. As expected, farm-specific differences existed for most antibiotic resistance genes, as well as for tzerland . Howeverslurries . In thisisolates . Thus, t E. coli , which m weaning . On the  piglets ,28. Thusmcr-1 gene was relatively low compared to the other genes. Nevertheless, it has been found on every farm and is more prevalent than in earlier investigations in Germany [mcr-1 gene in nearly 30% of samples [From quantitative qPCR data, we also calculated the prevalence of the respective genes. The prevalence of the  Germany ,29. In tfedA) or the colistin resistance (mcr-1) was lower after birth in some farms.Birth led to a quantitative increase of most pathogens and antibiotic resistance genes in sows. This is expected because parturition introduces drastic changes on many levels for the animal and, consequently, bacterial composition changes . HoweverData on antibiotic use were then submitted to NMDS analysis and hierarchical clustering to detect possible cluster formation on the farms. This revealed the presence of distinct antibiotic-use clusters of farms. Antibiotic use between the three observation times  was heterogeneous within the farms, so a different number of clusters resulted for all three groups. Differences with high significance were found in weaner pigs, where 4 clusters were formed. In a study about antibiotic drug usage in German pig farms from 2013 to 2015, twelve antibiotic drug classes were identified used for weaner pigs . Individgene mcr-1, as well as for cefotaxime use and cefotaxime resistance gene blaCTX-M, also exemplify this. Thus, there is no direct causal relationship between the prevalence of antibiotic resistance genes and antibiotic use. Instead, indirect effects that affect the intestinal microbiota may have come into play. For example, in elderly humans, C. difficile has been known to colonize the colon after antibiotic treatment [Next, Latent Class Analysis was performed to detect the most relevant antibiotic resistance genes that were associated witrh antibiotic use. However, antibiotic use clusters in sows and piglets yielded only a few significant relations. The exclusive use of certain antibiotics  in sow cluster 2 did not automatically lead to an increased prevalence of respective antibiotic resistance genes. The missing associations for colistin use and colistin resistance reatment  because reatment . Furtherreatment . Thus, imcr-1), trimethoprim- (dfrA1), and cefotaxime (blaCTX-M) resistance genes as the most relevant factors for cluster formation. Trimethoprim (a folate reductase inhibitor), in combination with sulfonamides, is often used in German sow and piglet production [dfrA1. However, amoxicillin enhanced the odds of dfrA1 prevalence in antepartum and postpartum sows and weaned piglets. The association between trimethoprim resistance and amoxicillin use has been shown in humans [Finally the LCA- and regression model analysis detected colistin-  producing bacteria have developed into a global threat [per se, the frequent incorporation of foreign DNA by enterobacteria can produce pathogenic ESBL-carrying bacteria that are difficult to treat. As antibiotic use was only recorded in one production cycle, it is possible that previous antibiotic use and thus resistance profiles have interfered with the present antibiotic use. Regression analysis does not depict causation and thus, this bias cannot be completely ruled out.The use of colistin is also quite common in pig production, especially in weaned piglets . Therefol threat . AlthougC. difficile in sows before and after parturition. C. difficile infects only newborn piglets; thus, increased odds for C. difficile in mother sows should be avoided, as maternal contamination with C. difficile can be carried over to the offspring. However, both antibiotics played no role in suckling- or weaned piglets. Resistance against enrofloxacin and florfenicol is common in C. difficile strains [E. coli fimbriae genes fedA, fas, and fae were less affected in sows and piglets by antibiotic use. Like lincomycin, enrofloxacin use impacted the odds of the presence in sows but not in piglets. Farm-specific antibiotic use generally had a lesser effect on the presence of facultative pathogens or virulence factors than on those of antibiotic resistance genes. The reverse conclusion could be that the genetic transfer of antibiotic resistance patterns due to antibiotic pressure does not directly produce antibiotic-resistant pathogens [E. coli there are findings of a link between antibiotic resistance and virulence but also less of a relation between antibiotic use and virulence [int 1 gene, for example, could also be associated with the virulence gene fae for F4 fimbriae and the Escherichia group. The logistic regression showed increased odds of presence with the simultaneous presence of int 1 for both parameters. Furthermore, in the linear regression, an increase in the gene concentration with an increase of int 1 was visible. This relationship between int1 and virulence factors has also been found in E. coli isolates from river water [int1 gene is ubiquitous in the pig farms studied could be associated with the spread of antibiotic resistance and virulence factors via horizontal gene transfer.Regarding associations of facultatively pathogenic bacteria and their virulence factors to antibiotic use, we found that only enrofloxacin and florfenicol favored the odds of the presence of  strains ,39, and  strains . The E. athogens . In E. cirulence . In the er water . The facmcr1, dfrA1, blaCTX-M) and bacterial virulence genes in many cases. However, direct effects of antibiotic use and corresponding resistance genes were uncommon. The association of integrase 1 with the Escherichia/Shigella/Hafnia group and E. coli fimbriae gene fae showed a possible link between multidrug resistance and virulence. The results confirm that multidrug-resistant enterobacteria are widespread in German pig farms, with varying patterns depending on age and farm. These findings give awareness of the impact of current antibiotic use while searching for alternative health strategies in modern pig production. More studies are necessary to figure out the effects of antibiotic use on virulence of bacteria.The NMDS and LCA analyses used in this study yielded groups of farms with specific antibiotic use, and the corresponding patterns differed between clusters. Regression models revealed that amoxicillin, lincomycin, and enrofloxacin were the most probable cause of increased odds of the presence of prominent antibiotic resistance genes (S1 Dataset(XLSX)Click here for additional data file.S1 File(PDF)Click here for additional data file.


Background: the treatment of infected non-union to allow for bony healingfollowing orthopedic surgery remains a challenge. Antibiotic-impregnatedcalcium sulfate (AICS) is an effective vehicle for antibiotic delivery, butits efficacy in treating infected non-union in the setting of trauma andfracture remains unclear. Methods: this systematic review analyses ninestudies from 2002 to 2022 that investigated AICS as a local antibioticdelivery system for cases of fracture-related infection and infected non-union.Results: in total, 214 patients who received AICS were included in thisreview. Of these patients, there were 154 cases of infected non-union orfracture-related infection. Across all studies analyzed, patients treatedconcurrently with AICS and systemic antibiotics experienced a 92.9 %rate of bony union and a 95.1 % rate of infection eradication. Inaddition, 100 % of the 13 patients who were treated with AICS aloneexperienced eradication of infection and successful bony union. Conclusion:AICS is an effective method of antibiotic delivery with a low risk profilethat results in high rates of bony union and infection eradication even whenused in the absence of systemic antibiotics. The successful treatment ofbony defects in the setting of local bacterial infection often requiresdebridement of infected bone and soft tissue and antibiotic deliveryintravenously, orally, or via local delivery.Bone infections are notoriously difficult to treat due to the lack ofantibiotic penetrance when delivered via the bloodstream Alternatively,antibiotics can be impregnated into bone cement and synthetic graftmaterial, such as calcium sulfate and polymethyl methacrylate (PMMA), and beeluted over time at the site of infection. While systematic review articles by Thahiret al. (2022) and Shi et al. (2022) have recently been published reviewing theefficacy of antibiotic-impregnated calcium sulfate (AICS) in treatingosteomyelitis, there is no comprehensive review of the literature exploringits effects in treating infected non-union and fracture-related infectionspecifically.In 1892, German physicians were the first to use calcium sulfate as syntheticgraft material to address bony defects . In the past2 decades however, calcium sulfate has been shown to effectively carryantibiotics, especially vancomycin, tobramycin, and gentamycin, when used assynthetic bone graft.AICS affords multiple advantages when treating infected non-union incomparison to antibiotic-impregnated PMMA or systemic antibiotics alone.PMMA beads are non-resorbable and require secondary debridement for removalweeks after their initial placement . Calcium sulfate, on the other hand, effectively fills the deadspace created by excision of infected tissue while being fully resorbable;therefore, it provides the advantage of requiring only a single procedurewithout the need to remove the material from the surgical site during afuture operation .Unlike PMMA, AICS induces bone formation, improves bone remodeling, andincreases cartilaginous surface area at the site of the defect, likely viamodulation of mesenchymal stem cells.Furthermore, calcium sulfate is capable of delivering 10 times moreantibiotic to the site of infection when compared to antibiotic-impregnatedPMMA, and in vitro data indicate that AICS inhibits bacterial growth similarly ormore effectively than antibiotic-impregnated PMMA.AICS also has the benefit of reducing the need for high doses of systemicantibiotics. Indeed, a recent investigation by Masrouha et al. (2018) foundthat AICS alone effectively united bone and eradicated infection without theneed for systemic antibiotics .This application of AICS is especially promising for patient populationswith poor compliance and in medical settings with limited resources andaccess to surgical services.The primary purpose of this systematic review is to investigate the rates offracture healing and infection eradication of AICS in the setting ofinfected non-union and similar pathologies. We also discuss complications ofAICS noted in the literature and the efficacy of AICS alone in treatingthese issues sans a prolonged systemic antibiotic regimen.2A systematic review of the literature was conducted in accordance with thePreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)checklist . The search strategy utilized the following search terms:“stimulan” or “calcium sulfate” or “calcium sulphate” and “union.”This search was independently performed by two authors (Connor C. Jacob and Jad H. Daw) on 23 May 2022. The authors utilized the following databases: Pubmed(1950–present), SPORTDiscus (1975–present), and The National Library ofMedicine's MEDLine (1964–present). The studies included in this review wereclassified with evidence levels 1, 2, 3, or 4 according to the Oxford Centerfor Evidence-Based Medicine. Printed publications and electronicallypublished publications were eligible for inclusion. Web search enginesincluding Google and Bing were used to discover any relevant studies that did notappear in the initial databases.Our inclusion criteria limited results to English language clinical outcomestudies involving the application of antibiotic-impregnated calcium sulfateas a local antibioticvehicle and bone graft substitute to orthopedic injuries complicated byinfection, the potential for infection, infected non-union, or infected bonydefect with evidence levels 1–4.Non-English studies, and studies of level 5 evidence includingsingle-case reports, expert opinions, and personal observation, wereexcluded. Basic science and animal models investigating the properties ofantibiotic elution, antibiotic selection, and mode of calcium sulfateapplication were excluded. Additionally, studies investigating the use ofcalcium sulfate alone (without antibiotic) as a bone graft substitute andthe application of calcium sulfate with or without antibiotic for purposesother than treating infection and/or non-union of bones were excluded.Studies that investigated the use of antibiotic-impregnated calcium sulfateduring the treatment of arthroplasty, hemiarthroplasty, or proceduresinvolving joint prosthesis were also excluded.Descriptive statistics were calculated with categorical data reported asfrequencies (percentages) and continuous data reported as means plus or minus standard deviations from the mean. Any ranges of data were reported asminimum to maximum absolute values. For any and all statistical analysesincluded within the studies analyzed, 3®-T from Wright Medical. Stimulan is aresorbable preparation of calcium sulfate commonly used to deliveryvancomycin, gentamycin, or tobramycin in bone or soft tissue with settingtimes ranging from 2–15 min. OSTEOSET®-T is a resorbablebone graft material composed of calcium sulfate and 4 % tobramycin that is sold aspellets capable of being packed into bony defects.Nine studies were deemed to be appropriate for inclusion and analysis forthis review (Table 1). All the included studies are clinical in nature andinvestigated AICS used as graft material for infected non-union fracture-related infection and post-traumatic osteomyelitis with bony defect atvarious surgical sites such as the tibia, femur, humerus, etc. Seven studieswere retrospective reviews of patients that received AICS as an adjunct tosystemic antibiotic therapy, one study compared AICS to PMMA, and one studyinvestigated AICS as a standalone therapy without the use of a prolongedcourse of intravenous (IV) or oral antibiotics. The synthetic bone graft material waspacked into the bony defect after debridement and excision of infected ornecrotic tissue for all patients in each study. The types of calcium sulfateutilized in these studies include the Stimulan Bullet Mat and Introducerfrom Biocomposites Limited and OSTEOSETIn total, the studies included in this review reported on 229 patients.There was a total of 214 patients who received AICS across all studies and15 patients who received antibiotic-impregnated PMMA beads in the comparisonstudy by McKee et al. (2010). Of the patients who received AICS, there were154 cases of infected non-union or fracture-related infection: the 60 otherpatients were diagnosed with non-fracture-related forms of osteomyelitis.The average age of all patients was 41.3 years. Because this review focuseson the subset of those patients with infected non-union and fracture-relatedinfection, data concerning cases of osteomyelitis not directly related tofracture or non-union are not extensively discussed here: information on therole of AICS in chronic osteomyelitis can be found in other systematicreviews on the topic.®-T, 93.3 % achieved bony union at an average timeof 6.9 months. The 74 non-union patients who received Stimulan achieved unionwith a rate of 92.5 % at an average of 5.3 months. While there was nostatistically significant difference in union outcomes or infectioneradication between the AICS and PMMA groups, the use of AICS was associatedwith a statistically significant decrease in re-operations compared to PMMA.The composite rate of infection eradication across all studies analyzed inthis paper was 95.1 %. OSTEOSET-T plays an effective role as an adjunct tosystemic antibiotics; indeed, the rate of eradication was 95.2 % with onlyone patient of the 21 total requiring further debridement to resolvepersistent infection . Of these infections,38 % were caused by a Rates of complications varied between the papers analyzed in this review.Qin et al. (2018) found that pain was the most common complication followingsurgery . Itwas found that the presence of wound leakage . Unlikesystemic antibiotics and antibiotic-impregnated PMMA, the literature hasclearly demonstrated that AICS induces bone formation, improves boneremodeling, and increases cartilaginous surface area: these effects aremassively important when comparing treatment options for instances ofinfected non-union especially. Theresorbable nature of AICS provides great utility in the treatment ofinfected non-unions in comparison to non-resorbable PMMA. AICS applicationallows patients to avoid secondary procedures necessary to removenon-resorbable material such as PMMA while maintaining similar rates of bonyunion and infection eradication. Inthese ways, AICS provides an excellent platform for addressing cases ofinfected non-union and fracture-related infection.AICS is an effective adjunct to systemic antibiotic delivery. However, AICScan also be considered as the sole antibiotic delivery route in the rightpatient population. The findings of Masrouha et al. (2018) are especiallyintriguing when considering the utility of AICS in areas of the world withlimited surgical infrastructure and in patient populations with poorcompliance. It is the first clinical study to demonstrate the efficacy ofAICS as the primary antibiotic vehicle for cases of infected non-union: noneof the 13 patients received systemic antibiotics after leaving the hospital,yet the rates of infection eradication and of bony union were 100 % at anaverage time of 5.5 months. This is in comparison to a study by Ferguson etal. (2014) that investigated AICS as an adjunct to systemic antibiotics as atreatment for osteomyelitis: the researchers demonstrated an infectionremission rate of 91.8 %. While both studies demonstrated high rates of infectioneradication, the results from Masrouha et al. (2018) are compelling. Larger studiesare needed to support the potential AICS to stand alone as a vector forantibiotic delivery and to definitively conclude that side effects ofsystemic antibiotics outweigh the benefits when treating cases of infectednon-union and fracture-related infection, especially in the presence oforthopedic hardware.The potential benefits of the use of AICS outweigh the risks. The mostcommon complication of AICS is wound drainage. This is understood to be theresult of sterile effluent draining from the surgical site after AICSinsertion . While AICShas been associated with instances of acute kidney injury, there was onlyone case of nephrotoxicity which resolved spontaneously within 1 week ofdiagnosis . There wasalso a one case of tibial nerve neuropraxia that required removal ofhardware to resolve, but this was likely unrelated to the AICS itself.Approximately 10 AICS patients experienced refracture. In patients withpoor compliance or with poor access, AICS could be appropriate as the soleantibiotic delivery route: as identified by Cheung et al. (2009), intravenousadministration of antibiotics is associated with several side effectsincluding infection, stenosis, and thrombosis . Antibiotics themselves pose well-known toxicity risks, and AICSprovides the opportunity to spare patients from the traditional 6 or moreweeks of systemic antibiotics following surgery for infected non-union.However, data on the use of AICS in isolation are very scarce, and thesurgeon should only consider this when systemic antibiotic delivery is not aviable option. Further studies would be of great interest.There are limitations to this review. Firstly, this review is retrospectivein nature and lacks standardized control groups. Secondly, there were ninestudies including a total of 229 patients that met inclusion criteria. Agreater number of patients would increase statistical power and strengthenthe applicability of our conclusions. Thirdly, cases of infected non-unionand fracture-related infections lack uniformity in etiologic pathogen,location, and lesion size, and variables such as comorbidities, medications,immune status, and prior operations vary widely from patient to patient.These factors have the potential of impacting outcomes. A prospectiveclinical research study with standardized operative and rehabilitativeprotocols could mitigate these limitations.5AICS is effective as a vector for antibiotic delivery and demonstratesefficacy in promoting union of bones after instances of infected non-unionand fracture-related infection. The resorbable nature of calcium sulfate canresult in sterile drainage, but this risk is outweighed by their efficacy inlocal antibiotic delivery, use as a synthetic graft, and no need forsecondary procedures for removal of beads, as would be the case for PMMA.AICS also offers the potential of efficacious local antibiotic deliverywithout long-term systemic antibiotic treatment following surgery. These results are especiallysignificant when considering the utility of AICS among patient populationsthat lack financial resources and easy access to medical and surgicalcenters.


Objectives: In tertiary-care settings, up to 50% of patients are prescribed at least 1 antibiotic. However, patients are often not proactively provided with information nor involved in shared decisions regarding their antibiotic therapies. Understanding inpatients’ knowledge and the extent of their involvement in antibiotic therapy help reduce inappropriate or unnecessary antibiotic use. Methods: A cross-sectional survey was conducted from March to December 2021 in a 1,600-bed, adult, acute-care, tertiary-care hospital. Patients prescribed antibiotics for the past 1 week during their hospital stay were surveyed. Ten questions assessing patients’ knowledge of their antibiotic therapy and 3 questions adapted from the NHS Care Quality Commission Inpatient survey (2013) were included in the survey questionnaire. Results: Among the 323 patients surveyed, 88% knew that they had been given antibiotics, and 80% felt that it was important to be informed of the reason, 76% felt that it was important to be informed of side effects, 74% felt that it was important to be informed of duration, and 72% felt that it was important to be informed of dosing frequency. However, only 71% knew the dosing frequency, 54% knew the side effects, 37% knew the duration, and 13% knew the name of the antibiotic agent administered. Of those unaware of the antibiotic name, 59% had indicated their desire to know. Among those aware of their antibiotic therapy, 85% had trust in their doctors but only 42% felt that they always received answers to their questions on antibiotics in an understandable manner from their doctors. Furthermore, 41% felt that they were often or always not given enough time to question their doctors. To raise their awareness on antibiotic use, 73% of respondents felt that having protected time with the doctors to understand more about their antibiotic therapy would be effective. Conclusions: Most inpatients lacked knowledge of details of their antibiotic therapy, and fewer than half were involved in it. Allocation of protected time with doctors to understand their antibiotic therapy can be a potentially effective strategy to increase patient engagement to enhance hospital antibiotic stewardship efforts.


Athletes’ perceptions of fairness toward coaching behaviors and decisions can play a crucial role in the development and maintenance of a strong coach–athlete relationship. However, scholars have given limited attention to athletes’ perceptions of fairness. Therefore, the current study aimed to explore the relationship between coaches and athletes by applying the concept of organizational justice based on met-expectation theory. The primary objective of the study was to empirically examine the direct and indirect relationships between the met-expectation of athletic justice and athletes’ attitudinal outcomes, such as athletic satisfaction and organizational commitment, through leader–member exchange (LMX). Data were collected from 289 elite athletes (238 men and 51 women) in the Kingdom of Saudi Arabia using a mixed-mode approach (paper-and-pencil and online surveys). The results of Structural Equation Modeling indicated that when athletes perceive that their expectations of fair treatment are met, it positively affects their satisfaction. This relationship is partially influenced by the quality of their relationship with their leader. However, the findings also suggest that while the athletes’ met-expectation of athletic justice has a positive effect on their satisfaction, it does not have a significant impact on their commitment to the team. The findings provide insight about important work-related outcomes by validating the coach–athlete relationship based on met-expectation of athletic justice. The findings can be utilized to improve athlete satisfaction and commitment, leading to positive team and individual outcomes. Building a strong and trusting relationship between athletes and coaches is an essential component of developing a successful team ,2. A teaTwo prominent concepts related to understanding employees’ satisfaction and commitment are met-expectation and the psychological contract. Met-expectation relates to the extent to which an individual employee’s expectations regarding their work environment and employment relationship  are metUnlike previous studies ,7,8,9 thIn the context of athlete–coach interactions, when athletes join a team, they tend to develop expectations of their roles, playing time, and performance on the team and compare those expectations with their actual experiences. Met-expectation theory suggests that when athletes’ actual experiences on the team align with the expectations, they are more likely to feel satisfied and commit to their team, which is likely to help improve individual or team performance. However, when athletes perceive that their coaches are unfair or unjust in contrast with their expectations, they are more likely to have negative emotions , which may have a negative impact on performance .The met-expectation theory provides a useful means of understanding how organization members’ perceptions of fairness in the workplace can impact their outcomes. In turn, a conceptual framework regarding the relationships between the met-expectation of athletic justice, leader–member exchange (LMX), and attitudinal outcomes  was developed, as shown in The concept of organizational justice has received considerable attention since the 1980s in the field of organizational behavior due to its significant impact on members’ attitudinal and behavioral outcomes . Hums anOrganizational justice is a multi-dimensional construct . AccordiBased on the organizational justice literature, it is expected that there would be a positive relationship between the met-expectation of organizational justice and attitudinal or behavioral outcomes . AthleteAthlete satisfaction is defined as an athlete’s feeling of pleasure or happiness regarding their athletic experience . It is cLMX, the quality of the relationship between a leader  and their followers , can affect the attitudes of both the leaders and followers . CoachesThe current study explored the impact of met-expectations, combined with organizational justice, on commitment. In other words, if athletes perceive that their expectations are being met in terms of fair treatment by their coach, they may be more likely to demonstrate commitment to the team. Numerous studies have found positive relationships between organizational justice and LMX  and betwHypothesis 1:LMX will mediate the relationship between the met-expectation of fairness perception toward coaching behaviors and athlete satisfaction.Hypothesis 2:LMX will mediate the relationship between the met-expectation of fairness perception toward coaching behaviors and team commitment.The current study employed a cross-sectional research design. Data collection was undertaken through a mixed-mode approach combining traditional paper-and-pencil surveys with online surveys. Research Ethics Committee (REC) approval was obtained prior to data collection. Permission to collect data via offline or online surveys were acquired from each sport club before administering paper–pencil surveys or sending emails containing a survey link. The participants for this study were athletes based in the Kingdom of Saudi Arabia. A total of 356 responses were collected, out of which 289 were usable for the study, with the rest being excluded due to perceived insincerity or incomplete responses. The sample size aligns with the recommended criteria of Westland , who proThe present study consisted of four main variables: (a) met-expectation of fairness perception towards coaching behaviors, (b) LMX, (c) athlete satisfaction, and (d) team commitment. A set of questionnaires, comprising 35 items, was used to measure the data for these variables, as well as collect demographic information .The current study developed a scale of met-expectation of athletic justice based on the authors’ athletic justice scale . While tThe remaining constructs—LMX, athlete satisfaction, and team commitment—were measured using existing scales in the field of organizational behavior. These variables were carefully chosen, building upon the existing literature, to ensure comprehensive and robust outcomes. The scales have been frequently employed in sport studies with contextual modifications. First, LMX for elite athletes was assessed using the 7-item scale developed by Scandura and Graen . Sample p-value of 0.05 or less, SRMR < 0.08, RMSEA < 0.01, CFI > 0.9, and TLI > 0.9. After removing inappropriate items and ensuring model fit, the final questionnaire included 9 items for met-expectation, 7 items for LMX, 3 items for athlete satisfaction, and 3 items for team commitment, respectively. Following the CFA, investigators performed SEM to verify research hypotheses. This statistical procedure was chosen to uncover complex relationships between variables and to ascertain the strength and direction of these relationships. The SEM allowed for estimation of the direct, indirect, and total effects of the variables and testing of the proposed causal relationships between the met-expectation of athletic justice, LMX, athlete satisfaction, and team commitment.To ensure the robustness of our measurements, we conducted validation and reliability assessments using statistical tests like Confirmatory Factor Analysis (CFA). Subsequently, we utilized Structural Equation Modeling (SEM) to empirically test our hypotheses. First, the investigators performed Confirmatory Factor Analysis (CFA) on the collected data to verify the measurement validity and reliability of the variables. This statistical procedure confirmed the factor structure of our observed variables and the factor loads of each item. Items with factor loading values lower than 0.6 were removed, ensuring a high level of construct validity and reliability. In general, there are serval goodness-of-fit indices that CFA requires for validation of a measurement scale. According to Hair et al., , the chiThe results of the study are organized into several sections that correspond to each stage of the data analysis. First, the CFA and associated model fit indices are reported, followed by tests of convergent and discriminant validity. Lastly, the Structural Equation Modeling (SEM) results are presented.2 = 4594.612, degrees of freedom (df) were 231, CFI was 0.919, TLI was 0.908, RMSEA was 0.078, and the SRMR was 0.053, all of which were within the acceptable range, thus providing evidence for construct validity.Next, we assessed the internal consistency of the constructs using Composite Reliability (CR). The CR values for met-expectation, athlete satisfaction, team commitment, and LMX were 0.924, 0.888, 0.865, and 0.890, respectively, exceeding the suggested threshold of 0.7 , which i2 = 4594.621, df = 231, CFI = 0.919, TLI = 0.908, RMSEA = 0.078, SRMR = 0.053), which indicates the model fitted the data well . ResultThe current study was designed based on prior research and theories in the field of organizational behavior to propose two research hypotheses. Specifically, we hypothesized that LMX would mediate the relationship between the met-expectation of fairness perception toward coaching behaviors and athlete satisfaction (H1) and the relationship between the met-expectation of fairness perception toward coaching behaviors and team commitment (H2). The results of the current study have important academic contributions and practical implications for the field of sport management and coaching.First, the results of descriptive statistics indicate that most elite athletes in Saudi Arabia generally perceive their coaches as treating them fairly and with respect and develop quality relationship with their coaches. Additionally, the athletes report high levels of athletic satisfaction, which may reflect their positive experiences. However, they rated team commitment slightly lower than the other variables, which indicates an area for further consideration and improvement. Thus, coaches in this context should work on strategies that could enhance team commitment, such as team-building exercises and promoting a sense of shared goals and purposes among athletes. Given the high levels of athletic satisfaction and relatively strong commitment among athletes in Saudi Arabia, coaches have an opportunity to enhance overall team performance and cultivate a more cohesive and supportive athletic environment.This study assessed athletes’ perception toward coaching styles and behaviors using the concept of organizational justice. Given the important influence of coaches on athletes’ experience and performance in teams, while numerous studies ,53 have The current study also reinforces the importance of LMX and the quality of athlete–coach relationships on athletes’ attitudinal outcomes. The findings of the study supported a mediating role of LMX, showing that athletes’ satisfaction with their sports is directly linked to both the congruence between the athletes’ expectations and actual experiences regarding coaches’ decisions and behaviors in their teams, and their perceived quality of the social exchange relationships with their coaches. This highlights the importance of coaches’ fair and just behaviors and decisions in enhancing athlete satisfaction, which may ultimately lead to better overall team performance ,7,8. In The findings of this study indicate that compared to athlete satisfaction, the met-expectation of athletic justice and LMX did not have a significant impact on team commitment. These findings suggest that while LMX plays a crucial role in promoting athlete satisfaction, it may not be as significant in promoting team commitment, which has implications for athlete retention and overall team performance. In the literature, LMX and POS are considered important social exchange variables to influence organizational commitment ,54. HoweThe findings of the study provide several practical implications for coaches, athletes, and sport management professionals. First, this study reinforces the importance of coaches striving to create fair and just practices and team policies to enhance athlete satisfaction and performance. By understanding the importance of fair and just coaching practices in promoting athlete satisfaction, coaches can develop strategies to enhance athlete satisfaction and ultimately improve team performance. For athletes, this study emphasizes the importance of understanding the role of the met-expectation of athletic justice toward coaching behaviors in their satisfaction with their athletic experience. Athletes should be encouraged to communicate their expectations with their coach and provide feedback on their coaching experience. Additionally, athletes should be aware of the importance of their relationship with their coach in their overall satisfaction with their athletic experience. For sport management professionals, the study highlights the limitations of LMX in promoting team commitment. While LMX is an important factor in promoting athlete satisfaction, other factors, such as team cohesion, shared goals, and a sense of belonging, may be more important in promoting team commitment. Sport management professionals should consider these factors when developing strategies to promote team commitment and cohesion.The current study contributes to our understanding of the effects of fair or unfair coaching behaviors on athletes’ attitudinal outcomes among elite athletes in Saudi Arabia. However, there are several limitations that need to be addressed in future research on the topic. First, this focus of this study was on elite athletes in Saudi Arabia. As such, readers should use appropriate caution when extrapolating the data to other populations, and future studies could be conducted in other cultural contexts or across different levels of sports  to increase the generalizability of the findings in the athlete–coaching relationship. Second, this study relied on self-reported data from athletes, which may introduce biases and social desirability effects. For example, athletes have been hesitant to address negative attitudes toward their coaches. Future studies may utilize a mixed-methods approach to help further explore these issues. Observations or interviews could provide a more comprehensive understanding of the relationships between the met-expectation of athletic justice and outcomes. Furthermore, the study examined the effect of athletic justice on athletic satisfaction and team commitment through LMX. Future studies could incorporate other social exchange variables, such as perceived organizational support, and quality relationships between athletes and the team, to capture the full range of social exchange relationships between athletic justice and outcomes. Finally, a longitudinal design is recommended to examine the proposed relationships at multiple time points over an extended period to better understand the causal relationships between the met-expectation of athletic justice and attitudinal outcomes.Coaches’ decisions greatly influence athletes’ satisfaction and commitment within the team. Therefore, this study advanced the knowledge of the relationships between coaches and athletes by examining athletes’ perceptions of fairness based on organizational justice and met-expectation theories. The results yielded insight into the direct and indirect relationships between the met-expectation of athletic justice and athletes’ attitudes through leader–member exchange based on social exchange theory. Specifically, leader–member exchange partially mediated the association between athletes’ met-expectation of athletic justice and satisfaction. However, no mediation effect was observed for team commitment. These results emphasize the importance of coaching fairness in improving athlete satisfaction. By validating the coach–athlete relationship based on met-expectation of athletic justice, teams could improve athlete satisfaction and commitment, benefiting both individuals and teams. Further research is needed to explore additional factors influencing the coach–athlete relationship and its consequences.


Crystal polymorphism has been a topic of much interestfor thepast 20 years or so, especially since its scientific  importanceto the pharmaceutical industry was realized. By contrast, the formationof solid solutions in molecular crystals has been overlooked despiteits long-standing prevalence in the analogous field of inorganic crystals.Wilfully forgotten, crystalline molecular solid solutions may be verycommon in our world since molecular compounds are rarely producedwith 100% purity, and impurities able to form solid solutions aredifficult to reject via recrystallization. Given the importance ofboth polymorphism and solid solutions in molecular crystals, we sharehere some tips, tricks, and observations to aid in their understanding.First, we propose a nomenclature system fit for the description ofmolecular crystalline solid solutions capable of polymorphism (tips).Second, we highlight the challenges associated with their experimentaland computational characterization (tricks). Third, we show that ourrecently reported observation that polymorph stabilities can changeby virtue of solid solution formation is a general phenomenon, reportingit on a second system (switches). Our work focuses on the historicallyimportant compound benzamide forming solid solutions with nicotinamideand 3-fluorobenzamide. A common adage repeated in the study of polymorphism isthat “in general, the number of forms known for a compoundis proportional to the time and money spent in its research”.2 In some cases, a metastable crystallineform of a compound has more desirable physical properties for a particularapplication, resulting in a need for experimental methods to obtainmetastable polymorphs reliably and efficiently.4 Thespontaneous and unexpected appearance of new more stable and lesssoluble forms can have significant consequences for drug delivery(as seen in the famous case of Ritonavir).5The physiochemical propertiesof a crystalline material can bealtered by changing the spatial arrangement of its constituents, aphenomenon known as crystal polymorphism. First reported in 1832 forthe molecular system benzamide (bzm),6 Analogous to liquidsolutions, crystalline SSs contain a major component or components(the “host”) and a minor component(the “guest”), which is distributedin the crystal lattice in sites otherwise occupied by the host inthe pure crystal. When referring to “host” or “guest”,one can refer to the structure of the compound itself (host compound)or the structure of the crystal . The crystallinehost molecules act as “solvent”, while guest moleculesact as “solute” within the host crystal structure. SSscan exist in a range of compositions, from small and undetectablemolar fractions (xg ≈ 0), to equimolar(xg = 0.5) or even dominant fractionsof the guest . The difference between a SSwith xg = 0.5 and a 1:1 cocrystal is thatin the SS, guest and host molecules sit in equivalent lattice siteswhile in the cocrystal, the different components occupy differentlattice sites. Like liquid solutions, some SSs can become saturatedthus forming what is known as a partial SS.7 For these, one can thus find a maximum valueof xg  above which no further guest molecules can be incorporated intothe lattice of the SS . In other SSs, all xg compositions are possible (from 0 to 1), thus the host:guest systemis capable of forming a continuous SS. Thermodynamicsdictate the incorporation of a guest in the lattice of a host andwhether or not the SS is possible across the entire compositionalrange.8 The crystal structure of the SSis usually similar to the structure of the pure host, though thisis not always the case, and in certain cases various crystal structuresof SSs are possible . While it is not obviouswhen a given guest molecule will form a SS with a given host moleculein a specific crystal structure, molecular similarity between theguest and the host is often  a necessity for theformation of a SS. Early works by Kitaigorodskii and recent worksby Lusi et al. have explored this question in more detail, a subjecttopic which is beyond the scope of the present study.9 Here we ask a different question in relation to SSs and polymorphism:given a host able to crystallize in different polymorphic forms, whatis the effect of SS formation on the host crystal polymorphism?12Beyond polymorphs, crystalline molecular systems can alsoformsolid solutions (SSs).13 we have shown that the otherwisevery elusive form III of bzm can be consistently crystallized fromsolution in the presence of nicotinamide (ncm). We showed that bzmform I  and bzm form III  switch thermodynamic stabilities upon SS formation with ncmand that such a switch occurs at xncm ≥0.03. The study of SS formation with modeling and experimental approachesis in its infancy, with only a small pool of articles investigatingtheir formation with two approaches.20 Our previous work lies in an even smaller pool of studies, demonstratingthat SS formation can result in a switch of thermodynamic stabilitiesof crystal forms.23 In the present work, our intention is to demonstratethat our previous observation is common and that polymorph stabilityswitches in SSs can occur in other systems. Here we show that thethermodynamic stability switch between BZM-I and BZM-III can alsobe achieved with a different guest: 3-fluorobenzamide (3fbzm). Forthis system, however, our computer simulations as performed in ourprevious work fell short in reproducing the experimental findings.After much work to improve our experimental characterization and simulationsof the SSs, we found that consideration of the conformational disorderof the guest molecules, as well as other entropiccontributions in the calculations, is a necessity for the correctstability computation of polymorphic SSs. The results are encouragingsince with these complex calculations we can now derive very accuratephase diagrams for the SS systems, but they are also inconvenientsince they confirm the necessity for complex and computationally expensivesimulations to achieve the correct modeling.In recent work inspired by the ball mill grinding resultsof Fischeret al.,In this article,we first introduce appropriate general nomenclaturefor dealing with these multicomponent polymorphic systems (tips).We then demonstrate techniques for accurately identifying and characterizingpolymorphic SSs experimentally, along with methods to simulate themcomputationally (tricks). Alongside the discussion of this two-prongedapproach, we demonstrate its applicability supported by results fromour host compound, bzm, crystallized in its BZM-I and BZM-III polymorphsin the presence of two different guests: ncm and 3fbzm 1. Finall22.1In this section we present nomenclature“tips” for concise and meaningful descriptions of SSsystems. Robust systems of nomenclature and terminology are crucialfor discussing SSs, as interpretations of their compositions and structurescan vary widely in scientific discussion.2.1.1Our systems here can vary in molecular composition and crystalstructure. As such, it is important that our abbreviations distinguishbetween compounds and crystal structures. For clarity, when referringto compounds lower case abbreviations are used, while when referringto crystal structures upper case abbreviations followed by roman numeralsdenoting the form are used. For example, bzm and 3fbzm are used torefer to compounds benzamide and 3-fluorobenzamide, respectively.In contrast, BZM-I, BZM-III, and 3FBZM-I are used to refer to thecrystal structures of form I of bzm, form III of bzm, and form I of3fbzm, respectively.0.75:3fbzm0.25] refersto a SS adopting the crystal structure of BZM-III, containing thetwo components bzm and 3fbzm. The subscripts indicate the mole fractionsof each of the components within the lattice. In this case, bzm isthe host compound and 3fbzm is the guest since the former is the majorcomponent. This is also reflected in the order of the molecular componentsin the formula.Here we propose an efficient and clearabbreviation system for describing molecular SSs. For this, we statethe crystal structure of the SS with its composition in brackets.For example, BZM-III [bzm0.75:3fbzm0.25] and3FBZM-I [bzm0.75:3fbzm0.25] would be equallyaccepted abbreviations for the same SS, though the former nomenclatureshould be preferred because the host (major component) at the reportedcomposition is bzm.Cases will exist where the crystal structureof the pure host isidentical to the crystal structure of the pure guest. This is truefor bzm and 3fbzm, with BZM-III being isostructural to 3FBZM-I. Insuch a case, BZM-III , 3fbzm exists in a 0.25 mole fraction andit can be orientated in two configurations A and B, with B being themajor and A the minor configuration.In cases where components can exist in twoor more configurationsor conformations, we can also refer to the configurational compositionby adding an extra subscript denoting the mole fraction of the A–B–C–M···configurations possible. While this may not always be known or determinedexperimentally, these considerations are of importance for the modelingof SSs. Hence in BZM-III  in the workflow. This parameter is calculated alongside Elatt,gSS[xgSS] for all cells listed previously. The mean Elatt,gSS[xgSS] and Fvib,gSS[xgSS] can be taken from all cells simulatedat the same xgSS to be used for further calculations to accountfor disorder.Once the SS cells have been generated,they are optimized withVASP , and the Elatt,gSS[xgSS], comprised of a weighted average of Elatt,gSS[xgSS] from each guest conformer substituted SS cell. Second the mixingeffect on the Fvib,gSS[xgSS] due to guest conformers is computedin the same manner; however, the Fvib,gSS[xgSS] is first convertedto a relative term ΔFvib,gSS[xgSS] . This is necessaryto avoid computation of Fvib for a moleculein the gas phase and thus requires only the simulation of vibrationalmodes in the solid phase. Finally, the mixing effect of host and gueston the entropy is also considered by calculating ΔSmix,gSS using R denotes the gas constant,and the mole fractions of host and guest are denoted following theconventions shown in the Tips section of this manuscript. Should theguest (or the host) exist in different conformations, each conformationwill be treated with an independent mixing term. For example, a SSwith a guest able to be included into two different conformationswill have three terms for the entropy of mixing .Moving to the final stage of the workflow, oncethe energetic parametersare calculated for the SS cells, mixing effects must be considered.SSs are mixed solids, and therefore neglecting these terms can unfairlypenalize their stability versus pure solids. As computing all combinationsof mixed guest molecules and conformers in host cells at this levelof theory would be prohibitively expensive, some simplifications arenecessary. First, the mixing effect on enthalpy due to guest conformersis considered by calculating a mixed GgSS) is then computedby adding the three host:guest terms, as in xgSS for all desired host crystal structures,and conformational disorder of the host and/or guest is also consideredif necessary.The final free energy of the system (323 we extend ourwork to a second guest (3fbzm) for which similar observations areseen. We compare both systems side-by-side to illustrate the differentnature of the SSs forming and that a switch in phase stabilities asa function of guest concentration is a common phenomenon.In this section, we applyour tricks for the generation and characterizationof SSs of bzm with two guest compounds: (i) ncm and (ii) 3fbzm. Followingon our previously reported observation that polymorphs can switchin thermodynamic stability through the incorporation of impuritiesfor the bzm:ncm system,3.11), bzm plays a significantrole in the history of polymorphism. The structure of its stable formI (BZM-I) was characterized in 1959,30 andother metastable forms reported thus far are BZM-II, BZM-III, andthe recently discovered BZM-IV.33 It is notoriously difficult tocrystallize and characterize the metastable forms of bzm since theyare very elusive, and they often crystallize concomitantly with BZM-I.In our recent paper, we have shown that good quality single crystalsof BZM-III can be crystallized exclusively in the presence of ncm.This observation was ascribed to the fact that, through SS formationwith ncm, BZM-III becomes the most stable polymorph.23 Here, we revised our characterization and modeling of thisbzm system with ncm and expand the work with a new guest, 3fbzm.As the first molecular compound reported to be polymorphic . Previous mechanochemistrystudies on bzm indicated that while LAG of pure BZM-I in IPA affordsBZM-I, as soon as small amounts of ncm are added to the grinding jaror in neat grinding, BZM-III is obtained.and DSC 5.xgLAG ≈ 0.2, the PXRD peaks matchwell those of the BZM-IIIstructure of both systems, with no evidence of BZM-I formation. Whencomparing the milled samples to the pattern of pure BZM-III, thereis an evident shift of some PXRD peaks of the tested sample, indicativeof SS formation. A detailed analysis of peak shifts and unit cellvariations upon SS formation for both host:guest systems was carriedout and is presented in SI. For clarity,however, we only show results for a single peak per system: (i) the(004) peak for the BZM-III[bzm(1-x):ncmx] system and (ii) the (013) peak for the BZM-III[bzm(1-x):3fbzmx] system. Thesepeaks were chosen because of being low 2θ peaks, not overlappingwith other phases, and having a linear relation between the shiftand the guest concentration. The structures of these BZM-III (004)and (013) planes are shown in SI for theinterested reader.As shown in Additionally, DSC traces of the milled samplesshowed single meltingevents with melting temperatures lower than those of the pure hostand guest structures. These results led to the unequivocal conclusionthat SS formation had taken place in both systems upon LAG in thepresence of IPA together with a switch in the polymorphic crystalstructure.3.3xgLAG. Diffractionpeaks and their positions at different xgLAG values werecompared with those of pure bzm polymorphs and the stable forms ofthe respective guest compounds. xgLAG for peaks corresponding to the (004) planeand the (013) plane in the BZM-III crystal structure for the in bzm:ncmand the bzm:3fbzm SSs, respectively.After establishingthat the two systems form SSs, the subsequent step was to examinethe nature and polymorphic behavior of the bzm SSs. This was achievedvia analysis of the PXRD patterns obtained at different trick that can be utilizedwith PXRD data when studying SSs—analysis of diffraction peakshifts as a function of xgLAG to determine the solid solubilityof a partial SS. xncmLAG ≈ 0.3, revealing the solid solubility limit of ncm in thehost crystal structure BZM-III . This xncm,satSS valuewas reconfirmed by a careful analysis of corresponding PXRD patternsand DSC traces of the LAG samples obtained. At xncmLAG = 0.3, milledsamples analyzed showed evidence of a small amount of NCM-I present.Consequently, the SS achieved in the bzm:ncm system can be classifiedas a partial SS.The approach used in x3fbzmLAG ≈ 0.3 (Tm ≈ 121 °C). All observations suggest that a continuousSS is formed in the bzm:3fbzm system.In contrast, a plateau in the peak shift ofthe (013) plane forthe bzm:3fbzm system is never observed 6b. In thxgSS is also a necessity. For the bzm:ncm system at the tested rangeof concentrations, the PXRD patterns of all milled products matchedthat of BZM-III with some shifted peaks. Because BZM-III SSs format very low concentrations of ncm (xncmLAG = 0.05), wewere unable to determine the exact guest concentration required forthe polymorph stability switch  with the LAG experiments.This must be in the range 0.00–0.05  were prepared in IPA and stirredfor 1 week at 25 °C. The resulting solids were filtered and characterizedwith PXRD .After sufficient time, slurries of solids in a saturated solution(relative to the existing form) may lead to the nucleation and growthof a more stable (less soluble) polymorph.ith PXRD 7, DSC, oxncmslurry = 0.3, and a continuous SS wasfound in the bzm:3fbzm system (Supporting Information (SI) 2.4).The slurry results were in excellent agreementwith LAG, confirmingthat the driving force for the SS formation is thermodynamics; stableSSs were obtained in both bzm:3fbzm and bzm:ncm systems. Consistentwith LAG, a partial SS was found for the bzm:ncm system, with excessncm crystallizing at m system 7. FurthexgSS) when the SSs are prepared from solution .In summary, the experimentsand multiple characterization analysesof the slurried solids reconfirmed that SSs form for the bzm:ncm andthe bzm:3fbzm systems and that their formation and the resulting polymorphicform obtained are driven by thermodynamics. Unlike with LAG, the concentrationof the guest in the solution will be different from the final guestconcentration in the solids. Thus, further quantification of the amountof guest incorporating into the SS crystal structure is required (xgSS) can be analyzedusing a quantitative characterization technique such as 1H NMR spectroscopy. The exact guest uptake into a SS (SI 2.2). The guest molecules of ncm, on the other hand, were nottaken up by the bzm polymorphs to the same level, perhaps due to theabsence of the isostructurality in BZM-III and NCM-I. The differencein uptake efficiency for ncm in BZM-I and BZM-III was also almostnegligible (0.03), whereas it was more prominent for the bzm:3fbzmsystem (0.07).The data in 38 For the case of thermodynamic control, there willbe a guest switch concentration  below and above whichthe polymorphic structures change in relative stability. This criticalguest switch concentration was estimated based on the correspondingPXRD patterns. In slurries, the guest switch concentration was estimatedas the incorporated amount of guest where PXRD peaks correspondingto BZM-III first began to appear, shown in xncm,switchSS was estimated to be just 0.032 ±0.001; this indicates the very small amount of ncm required for apolymorph stability switch. For the bzm:3fbzm system from the slurrydata, the x3fbzm,switchSS value was estimated to be 0.107 ±0.004. For the second system, a significantly higher amount of guestis required for the switch. In LAG experiments, the guest switch regionwas approximated to be between the maximum amount of guest testedthat resulted in BZM-I and the minimum amount of guest tested thatresulted in BZM-III. The switch concentrations obtained from the slurryexperiments are in good agreement with those approximated for LAGin Finally, as with LAG, the phases obtained asa function of guestincorporation also need to be monitored. If experiments are performedunder thermodynamic control ,the observation of polymorphic SSs at different concentrations isan indication that a thermodynamic stability “switch”has occurred where a previously metastable polymorph has become stablethrough the incorporation of guest species. This is, of course, notrepresentative of all crystallization conditions, and metastable polymorphicSSs may also be produced due to kinetics effects during crystallizationfrom solution or the melt.3.539 the guest compound is incorporated in one orientation (ncmA) whist for pure 3FBZM-I, 3fbzm is conformationally disorderedas 3fbzmA,0.33:3fbzmB,0.66. There exists, therefore,the possibility that both of these guests may exist in one of thoseconformations or a combination of both in the SSs.For the studied systems, both guest compoundscan exist in two different conformations . In contrast, when BZM-III-SSis formed, a relative A:B ratio of 0.30:0.70 is observed for 3fbzmindependent of its concentration (x3fbzmSS) and consistent with theratio observed in pure 3FBZM-I. Conducting slurries and analysis ofsamples at higher and lower temperatures appeared to have a negligibleimpact on this conformer ratio of the guest observed (SI 2.5). For the ncm guest  and three  different concentrations of ncm and 3fbzm,respectively . Single crystals of good quality were obtained for the SSsfrom slurries at two – and the full approach including computation of free energieswith improved model energies (TS-MBD), frequency calculations, andconsideration of entropy of host:guest mixing and guest disorder.The evolution of results upon adding each of the energetic approximationsis fully presented in the xgSS  including mixtures of multiplephases. The free energies of mixtures of phases can be simply calculatedby extrapolating the values GgSS[xgSS] between thephases involved. For example, the free energy of the mixture of purehost and pure guest can be plotted by drawing the line between thefree energy of the pure host most stable crystal structure (xg = 0) and the free energy of the pure guestmost stable crystal structure (xg = 1).Energies for mixtures of different SSs can also be calculated by connectingthe energies of the two SSs at their respective xgSS valuesand then extrapolating to either pure component in excess, dependingon xgSS or xg. Further details on howthese free energies are extrapolated along with a detailed discussionof their significance when evaluating the output of lattice energycalculations can be found in SI 3.4.For a SS to be the most stable form, its free energy mustbe the lowest overall when compared to the free energy of the othercompeting systems at a given value of xgSS. For bzm:ncm, although this model shows apolymorph stability switch (SS-I → SS-III), the physical mixtureof the pure components (dashed black line) is predicted to be themost stable outcome. For bzm:3fbzm, no polymorph switch is predicted,with SS-I being the most stable form across the entire compositionalrange. While this methodology was used to predict the polymorph stabilityswitch in the bzm:ncm system before,21 whenapplied to the bzm:3fbzm system and the energetics compared to thoseof the mixtures of pure forms, the predictions do not validate theexperimental outcomes.First, we compare the lattice energies of both host:guest systemscomputed across the entire compositional range 10, wherexncm,switchSS = 0.07, which is in good agreement with experiments . Further, the calculations also predict that thebzm:ncm would only form a partial SS with a predicted xncm,sat.SS =0.48. This value is also in good agreement with the experimental xncm,satSS ≈ 0.03. For bzm:3fbzm, the free energy calculationsnow predict SS formation as well as a change in polymorph stabilitiesat x3fbzm,switchSS = 0.09, in excellent agreement with experiment. In addition to this, a continuousSS was still predicted, as seen in previous models.Second, we compare the free energies of both host:guestsystemscomputed across the entire compositional range with our full modelingprocedure discussed in the previous section 11. The f3.7SI 3.3). For a blindconformer disorder prediction, the lowest possible free energy needsto be computed for each SS at each value of xgSS by varying theconformers A/B ratio from 1:0 to 0:1 in order to find the “optimalconformer disorder ratio”. Incorporation of an enthalpicallydisfavored conformer offers some gain in entropy due to the additionalcombinatorial microstates accessible with a third component presentin the solid, and can result in a lower overall free energy for theSS.For the modeling of SS disorder in the section above 11, repreThe free energies obtained from the predicted “optimalconformer disorder ratio” are listed in B in both BZM-I and BZM-III lattices (SI 3.5.1), with BZM-III demonstrating the lowest incorporation of ncmA from the pair of structures . Only small changes are observed in theconformer preference with the addition of mixing and vibrational corrections(SI 3.5.2). Disorder preferences vary betweenBZM-I and BZM-III more dramatically for bzm:3fbzm (SI 3.5.3), with BZM-I preferring 3fbzmA whereasBZM-III prefers a mix of conformers . Both structures are predicted to incorporate more 3fbzmB with increasing temperature according to the vibrationalcontributions to the free energy.Modeling of the absolute disorder resulting inthe lowest freeenergies in bzm:ncm demonstrates a clear preference for ncm4In this study we have presentedgeneral methods for communicating,synthesizing, characterizing, and simulating polymorphic SSs. Thesystem of nomenclature has been designed to be robust while also beingflexible enough to convey relationships between systems in a conciseand clear manner.SI 3.7.1). These tricks complement existing approachesfor synthesizing and characterizing SSs and highlight the informationthat can be gleaned from different approaches.Our experimental tricks show a general guidefor the synthesisand characterization of SSs, with a deeper dive into the study ofpolymorphic SSs, with thermodynamic switches caused by the incorporationof guest species. Expansion of these characterization tools to thequantification of guest conformations incorporated in SSs demonstratesthe complexity of these systems, where different polymorphic SSs havedifferent conformer preferences, and can drive the incorporation ofconformers generally not observed in solution crystallization . The latter two of the correctionsare crucial for enantiotropic and conformationally disordered systems.Through this type of modeling, we can predict and compose accuratephase diagrams for both continuous and partial polymorphic SSs . Highly accurate models are required,and each corrective factor has been evaluated in its impact on theenergies of SSs. Entropy of mixing is required to stabilize SSs relativeto pure components, along with vibrational and conformer mixing termsto extract free energies for polymorphic SSs with accurate guest switchconcentrations  and NCM-I (99%)were obtained from Sigma-Aldrich, and both were confirmed as formI by powder X-ray diffraction (PXRD). 3FBZM-I (99%) was purchasedfrom Acros Organics. Solvents: isopropanol was obtained from Honeywell; acetone-D6 (deuteration degree −99.8%)was obtained from VWR International Ltd. All materials were used withoutfurther purification.5.2Liquid Assisted Grinding (LAG) experiments werecompleted using a Retsch MM400 Mixer Mill with screw top 5 mL stainlesssteel milling jars fitted with a Teflon gasket and 7 mm stainlesssteel milling balls. Approximately 300 mg of sample and 300 μLof solvent were used. The samples were milled at a frequency of 30Hz for 60 min. Different ratios of guest:host were tested to examinethe impact of guest presence on the host’s polymorphism.5.323Excess solids consisting of different ratiosof BZM-I to 3FBZM-I  were stirred in 3 g of 2-propanolin sealed 20 mL vials. Temperature control was conducted at the stabilityof ±0.02 °C using a Polar Bear Plus (Cambridge Reactor Design)with a stirring speed of 250 rpm. Slurries were allowed to equilibratefor 1 week at 25 °C. After 1 week, slurries were filtered usinga Büchner flask connected to a vacuum pump and washed withsmall amounts of isopropanol to aid the separation from saturatedsolution. The crystallites were characterized immediately via PXRDand after drying at 40 °C in vacuum oven for 48 h, using differentialscanning calorimetry (DSC), nuclear magnetic resonance (NMR), andPXRD. Slurry methodology for bzm:ncm system is described elsewhere.Attempts were also made to examine theimpact of temperature on the slurry outcome and configurational conformationof 3fbzm. Slurries containing 12.5 wt % of 3fbzm were tested at 5,35, 40, 45, and 50 °C. Furthermore, the impact of time of slurringat 3fbzm switch concentration was examined by slurrying for 1 monthat 25 °C.To modify the procedure to produce larger SScrystals for SCXRD,slurries were first heated to 60 °C with all solids dissolvedwhile stirring, then followed by rapid cooling to 25 °C. Thistemperature was then held for 1 week to allow crystallization andequilibration. Slurries that were stirred, even at a very low speed,produced crystals that were too small to obtain good quality SCXRDdata. Consequently, experiments were repeated with stirring turnedoff once the slurries were cooled to 25 °C. This resulted insuspensions with crystals of sufficient size after 1 week, which werethen filtered, dried, and characterized with SCXRD.5.4For detailed comparison and confirmation of SS formation, physicalmixtures of BZM-I and NCM-I or 3FBZM-I were prepared. Various ratiosof BZM-I and NCM or 3FBZM-I were weighed out and transferred to vials,followed by subtle mixing with the aid of a spatula and PXRD and DSCcharacterization procedures.5.55.5.1PXRD patterns for the differentsamples were recorded using a Bruker D2 Phaser diffractometer equippedwith a LYNXEYE detector in the Bragg–Brentano geometry, usingCu Kα radiation (λ= 1.54 Å). Intensity data wererecorded in the 2θ range of 5°–40° at timeper step of 0.3s, with a 2θ increment of 0.018° per step.x:ncmx1–] SSs, BZM-III [bzmx:fbzmx1–] SSs, BZM-I [bzmx:fbzmx1–] SSs, and pure BZM-III. While the SSs crystals wereobtained from slurries, BZM-III crystals were obtained from crashcooling crystallizations, cooled from 50 to 25 °C. BZM-III crystalswere retrieved immediately to prevent the conversion of BZM-III toBZM-I. The data for all crystals were collected at 100 and 150 K usingan Oxford Cryostream 800 Plus cooling device on a four-circle XtaLABAFC11 (RINC): Kappa single diffractometer equipped with Hybrid PixelArray Detector using Cu Kα (λ = 1.54 Å) radiation.Data reduction and face indexing were performed with the CrysAlisProsoftware (version 171.40_64.69a - Rigaku). OLEX2 (version 1.2)40 was used to solve the structures with the SHELXS41 program by employing direct methods and to refinethe structures with the least-squares procedure using the SHELXL package.42 The refinement was based on F2 forall reflections, except those with negative intensities. WeightedR factors (wR) and all goodness-of-fit (S) valueswere based on F2, whereas conventional R factors were basedon the amplitudes, with F set to zero for negative F2.Scattering factors were taken from the International Tables for Crystallography.43 Crystal data, data collection, and refinementdetails are summarized in the Supplementary Tables 2.7.1–2.7.3.Single crystal X-raydiffraction (SCXRD) was conducted on BZM-III  for the bzm:ncm and bzm:3fbzm SS systems, respectively.To plot the Elatt,gSS[xgSS] values where more than one simulationcell permutation is available , the meanvalue for the energies is taken. Standard errors (standard deviationdivided by the square root of the sample size) can also be computedfrom the data and are presented in SI 3.6 for the lattice energy and free energy plots.To calculate and ncmA 1 chosen 5.6.355 was extended to multicomponent solids to investigatethe effect of temperature on Elatt,gSS originally computed at0 K. Vibrational modes were calculated using VASP, via the finite-differencemethod and converted to energy values with an in-house Python script.Sufficiently sized supercells of the TS optimized structures wereused to perform these calculations, as recommended in literature.56 Temperature corrections were then added as a relative value comparedwith the BZM-I  cell at each guest concentration. Addingthis parameter as a relative term ensures that vibrational mode contributionsare only computed from solid phases, and not for the gas phase referencemolecule .Anapproach used previously within our group for tolfenamic acid5.6.4Elatt of the experimentally observed stable pure components.Pure Elatt values were calculated usingthe same methodology and parameters as those for the SS cells . This canbe extended to mixtures of SSs by adding data points at their respective xgSS values, linking each SS point together with increasing xg, and then extrapolating said points for the SSs at themaximum and minimum points on the xg scaleto the energy for pure guest and pure host energies, respectively.The energies for the physical mixtures of BZM-I and NCM-I or 3FBZM-Iwere computed assuming linearity between the Elatt,gSS values for BZM-I and BZM-III are shown for each structure. Fulldiscussion of the computational methodology is provided in SI 1.3, while additional computational resultsare provided in SI 3.Across this paper, only the conformers which result in the lowest


Despite the fact that paediatric community-acquired pneumonia (CAP) is usually caused by viruses, antibiotics are often prescribed. The objective of this study was to understand caregiver perspectives and experiences relating to the treatment of paediatric CAP.This was a phenomenologically-informed qualitative study involving interviews with caregivers of young children in Hamilton, Ontario. Caregivers were interviewed with open-ended questions relating to germ theory, the nature of pneumonia, and the role of antibiotic treatment. The principles of conventional content analysis were used to guide the coding and synthesis of the transcribed interviews.Eleven caregivers were interviewed. Most had a good understanding of the difference between bacteria and viruses and many knew that antibiotics were not effective against all types of infections. Many also stated that there was an increased risk of developing resistance with frequent antibiotic use. However, there were misconceptions that probiotics effectively mitigated antibiotic side effects and few were familiar with the potential long-term impacts of antibiotic use in children. There was variability in the perceived severity of paediatric CAP. For children sick enough to require treatment in the emergency department (ED), some participants thought that antibiotic treatment would be important to prescribe to accelerate recovery, as well as to prevent caregivers from feeling helpless. However, participants also thought it was inappropriate for physicians to prescribe antibiotics solely to make the caregiver feel better. Many caregivers also felt strongly that clinical follow-up and discussions on treatment risks and benefits would be desirable and might counteract feelings of helplessness that might result from being sent home without a prescription.Recognizing that parents may have misperceptions about antibiotic use for CAP  can inform clinicians’ efforts to better educate and support caregivers in the ED. Care strategies informed by caregiver experiences can improve parent-provider communication, increase trust in the attending clinician, and reduce antibiotic misuse.Jeffrey Pernica, MD, MSc, FRCPC, DTMH, MedImmune: Grant/Research Support|Merck: Grant/Research Support


Amoxicillin for a 5-day duration is the first-line recommended treatment for pediatric uncomplicated community acquired pneumonia (CAP). This project sought to identify the impact of a revised AgileMD clinical care pathway (CCP) on antibiotic prescribing and clinical outcomes.In April 2021, a revised CAP CPP was implemented into clinical practice. Changes included prioritizing amoxicillin as the treatment of choice, discouraging use of broad-spectrum antibiotics and azithromycin, and decreasing treatment duration to 5 days. In this quasi-experimental study patients, 60 days-18 years, admitted from January 2018 to July 2022 who were diagnosed and treated with antibiotics for uncomplicated CAP were included. Patients with complex chronic conditions, respiratory failure at presentation, septic shock, complicated CAP, and hospitalization in the prior 30 days were excluded. Data collected included patient demographics, admission diagnoses, antibiotic prescribing, and 7-day readmission rates. Primary outcomes included (1) percent of patients receiving each antibiotic and (2) median days of total antibiotic therapy (inpatient plus outpatient) for CAP. Statistical process control charts, Fisher exact and Mann Whitney U tests were utilized to compare clinical characteristics and antibiotic prescribing practices between the pre-CCP (1/2018-3/2021) and post-CCP (4/2021-7/2022) groups.Of 900 CAP encounters that met inclusion criteria, 65% were pre-intervention period and 35% post-intervention (Table 1). Most patients received supplemental oxygen at presentation  and nearly all patients had a chest x-ray obtained . Prescribing of amoxicillin increased from 67% to 78%. The largest decrease occurred in azithromycin prescribing from 24% to 3% . Duration of therapy in the post-CCP group was statistically shorter compared to the pre-CCP group (7.5 days vs 5.9 days) . Readmission rates were not statistically different between groups (p=0.33).Clinical pathway incorporation into the EMR significantly improved antibiotic choice and decreased duration for children with CAP.Jillian Cotter, MD, MSCS, Pfizer: Grant/Research Support Lilliam Ambroggio, PhD, Pfizer Inc.: Grant/Research Support