Using Claims Data to Predict Pre-Operative BMI Among Bariatric Surgery Patients: Development of the BMI Before Bariatric Surgery Scoring System (B3S3).

Background: Lack of body mass index (BMI) measurements limits the utility of claims data for bariatric surgery research, but pre-operative BMI may be imputed due to existence of weight-related diagnosis codes and BMI-related reimbursement requirements. We used a machine learning pipeline to create a claims-based scoring system to predict pre-operative BMI, as documented in the electronic health record (EHR), among patients undergoing a new bariatric surgery. Methods: Using the Optum Labs Data Warehouse, containing linked de-identified claims and EHR data for commercial or Medicare Advantage enrollees, we identified adults undergoing a new bariatric surgery between January 2011 and June 2018 with a BMI measurement in linked EHR data ≤30 days before the index surgery (n=3226). We constructed predictors from claims data and applied a machine learning pipeline to create a scoring system for pre-operative BMI, the B3S3. We evaluated the B3S3 and a simple linear regression model (benchmark) in test patients whose index surgery occurred concurrent (2011-2017) or prospective (2018) to the training data. Results: The machine learning pipeline yielded a final scoring system that included weight-related diagnosis codes, age, and number of days hospitalized and distinct drugs dispensed in the past 6 months. In concurrent test data, the B3S3 had excellent performance (R2 0.862, 95% confidence interval [CI] 0.815-0.898) and calibration. The benchmark algorithm had good performance (R2 0.750, 95% CI 0.686-0.799) and calibration but both aspects were inferior to the B3S3. Findings in prospective test data were similar. Conclusion: The B3S3 is an accessible tool that researchers can use with claims data to obtain granular and accurate predicted values of pre-operative BMI, which may enhance confounding control and investigation of effect modification by baseline obesity levels in bariatric surgery studies utilizing claims data.

Pre-operative BMI is an important potential confounder in comparative effectiveness studies of bariatric surgeries.Claims data lack clinical measurements, but insurance reimbursement requirements for bariatric surgery often result in pre-operative BMI being coded in claims data.We used a machine learning pipeline to create a model, the B3S3, to predict pre-operative BMI, as documented in the EHR, among bariatric surgery patients based on the presence of certain weight-related diagnosis codes and other patient characteristics derived from claims data.Researchers can easily use the B3S3 with claims data to obtain granular and accurate predicted values of pre-operative BMI among bariatric surgery patients.

Dimorphic effect of TFE3 in determining mitochondrial and lysosomal content in muscle following denervation.

BACKGROUND: Muscle atrophy is a common consequence of the loss of innervation and is accompanied by mitochondrial dysfunction. Mitophagy is the adaptive process through which damaged mitochondria are removed via the lysosomes, which are regulated in part by the transcription factor TFE3. The role of lysosomes and TFE3 are poorly understood in muscle atrophy, and the effect of biological sex is widely underreported. METHODS: Wild-type (WT) mice, along with mice lacking TFE3 (KO), a transcriptional regulator of lysosomal and autophagy-related genes, were subjected to unilateral sciatic nerve denervation for up to 7 days, while the contralateral limb was sham-operated and served as an internal control. A subset of animals was treated with colchicine to capture mitophagy flux. RESULTS: WT females exhibited elevated oxygen consumption rates during active respiratory states compared to males, however this was blunted in the absence of TFE3. Females exhibited higher mitophagy flux rates and greater lysosomal content basally compared to males that was independent of TFE3 expression. Following denervation, female mice exhibited less muscle atrophy compared to male counterparts. Intriguingly, this sex-dependent muscle sparing was lost in the absence of TFE3. Denervation resulted in 45% and 27% losses of mitochondrial content in WT and KO males respectively, however females were completely protected against this decline. Decreases in mitochondrial function were more severe in WT females compared to males following denervation, as ROS emission was 2.4-fold higher. In response to denervation, LC3-II mitophagy flux was reduced by 44% in females, likely contributing to the maintenance of mitochondrial content and elevated ROS emission, however this response was dysregulated in the absence of TFE3. While both males and females exhibited increased lysosomal content following denervation, this response was augmented in females in a TFE3-dependent manner. CONCLUSIONS: Females have higher lysosomal content and mitophagy flux basally compared to males, likely contributing to the improved mitochondrial phenotype. Denervation-induced mitochondrial adaptations were sexually dimorphic, as females preferentially preserve content at the expense of function, while males display a tendency to maintain mitochondrial function. Our data illustrate that TFE3 is vital for the sex-dependent differences in mitochondrial function, and in determining the denervation-induced atrophy phenotype.

Impact of the Breast Cancer Index for Extended Endocrine Decision-Making: First Results of the Prospective BCI Registry Study.

BACKGROUND: The Breast Cancer Index (BCI) test assay provides an individualized risk of late distant recurrence (5-10 years) and predicts the likelihood of benefitting from extended endocrine therapy (EET) in hormone receptor-positive early-stage breast cancer. This analysis aimed to assess the impact of BCI on EET decision-making in current clinical practice. METHODS: The BCI Registry study evaluates long-term outcomes, decision impact, and medication adherence in patients receiving BCI testing as part of routine clinical care. Physicians and patients completed pre-BCI and post-BCI test questionnaires to assess a range of questions, including physician decision-making and confidence regarding EET; patient preferences and concerns about the cost, side effects, drug safety, and benefit of EET; and patient satisfaction regarding treatment recommendations. Pre-BCI and post-BCI test responses were compared using McNemar's test and Wilcoxon signed rank test. RESULTS: Pre-BCI and post-BCI questionnaires were completed for 843 physicians and 823 patients. The mean age at enrollment was 65 years, and 88.4% of patients were postmenopausal. Of the tumors, 74.7% were T1, 53.4% were grade 2, 76.0% were N0, and 13.8% were HER2-positive. Following BCI testing, physicians changed EET recommendations in 40.1% of patients (P<.0001), and 45.1% of patients changed their preferences for EET (P<.0001). In addition, 38.8% of physicians felt more confident in their recommendation (P<.0001), and 41.4% of patients felt more comfortable with their EET decision (P<.0001). Compared with baseline, significantly more patients were less concerned about the cost (20.9%; P<.0001), drug safety (25.4%; P=.0014), and benefit of EET (29.3%; P=.0002). CONCLUSIONS: This analysis in a large patient cohort of the BCI Registry confirms and extends previous findings on the significant decision-making impact of BCI on EET. Incorporating BCI into clinical practice resulted in changes in physician recommendations, increased physician confidence, improved patient satisfaction, and reduced patient concerns regarding the cost, drug safety, and benefit of EET.

Validation of the Prognostic Performance of Breast Cancer Index in Hormone Receptor-Positive Postmenopausal Breast Cancer Patients in the TEAM Trial.

PURPOSE: Patients with early-stage hormone receptor-positive (HR+) breast cancer face a prolonged risk of recurrence even after adjuvant endocrine therapy. The Breast Cancer Index (BCI) is significantly prognostic for overall (0-10 years) and late (5-10 years) distant recurrence (DR) risk in N0 and N1 patients. Here, BCI prognostic performance was evaluated in HR+ postmenopausal women from the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial. EXPERIMENTAL DESIGN: 3,544 patients were included in the analysis (N = 1,519 N0, N = 2,025 N+). BCI risk groups were calculated using pre-specified cutoff points. Kaplan-Meier analyses and log-rank tests were used to assess the prognostic significance of BCI risk groups based on DR. Hazard ratios (HR) and confidence intervals (CI) were calculated using Cox models with and without clinical covariates. RESULTS: For overall 10-year DR, BCI was significantly prognostic in Ni0 (N = 1,196) and N1 (N = 1,234) patients who did not receive prior chemotherapy (P < 0.001). In patients who were DR-free for 5 years, 10-year late DR rates for low- and high-risk groups were 5.4% and 9.3% (N0 cohort, N = 1,285) and 4.8% and 12.2% (N1 cohort, N = 1,625) with multivariate HRs of 2.25 (95% CI, 1.30-3.88; P = 0.004) and 2.67 (95% CI, 1.53-4.63; P < 0.001), respectively. Late DR performance was substantially improved using previously optimized cutoff points, identifying BCI low-risk groups with even lower 10-year late DR rates of 3.8% and 2.7% in N0 and N1 patients, respectively. CONCLUSIONS: The TEAM trial represents the largest prognostic validation study for BCI to date and provides a more representative assessment of late DR risk to guide individualized treatment decision-making for HR+ patients with early-stage breast cancer.

The role of TFE3 in mediating skeletal muscle mitochondrial adaptations to exercise training.

Transcription factor E3 (TFE3) is a transcription factor that activates the expression of lysosomal genes involved in the clearance of dysfunctional mitochondria, termed mitophagy. With exercise, TFE3 is presumed to optimize the mitochondrial pool through the removal of organelles via lysosomes. However, the molecular mechanisms of the involved pathways remain unknown. Wild-type (WT) and TFE3 knockout (KO) mice were subjected to 6 wk of voluntary wheel running as an endurance training regimen. This was followed by a 45-min bout of in situ stimulation of the sciatic nerve innervating hindlimb muscles to evaluate muscle fatigue and contractile properties. A subset of animals was treated with colchicine to measure autophagy and mitophagy flux. Fatigability during stimulation was reduced with training in WT animals, as seen by a 13% increase in the percentage of maximum force at 5 min of stimulation, and a 30% increase at 30 minutes. Permeabilized fiber oxygen consumption was also improved with training. Concurrent with improved muscle and mitochondrial function, cytochrome c oxidase (COX) activity and COX I protein expression were increased in trained WT animals compared to untrained animals, signifying an increase in mitochondrial content. These training adaptations were abolished with the loss of TFE3. Surprisingly, the absence of TFE3 did not affect lysosomal content nor did it blunt the induction of mitophagy flux with contractile activity compared to WT mice. Our results suggest that the loss of TFE3 compromises beneficial training adaptations that lead to improved muscle endurance and mitochondrial function.NEW & NOTEWORTHY Our understanding of the role of transcription factor E3 (TFE3) in skeletal muscle is very limited. This research shows that TFE3 plays a direct role in skeletal muscle mitochondrial enhancement with exercise training, thereby introducing a paradigm shift in our perception of the function of TFE3 in mitochondrial maintenance, beyond mitophagy. This research serves to introduce TFE3 as a protein that holds promise as a future therapeutic target for metabolic diseases and skeletal muscle dysfunction.

Measuring Diaphragm Thickness and Function Using Point-of-Care Ultrasound.

The diaphragm is the main component of the respiratory muscle pump. Diaphragm dysfunction can cause dyspnea and exercise intolerance, and predisposes affected individuals to respiratory failure. In mechanically ventilated patients, the diaphragm is susceptible to atrophy and dysfunction through disuse and other mechanisms. This contributes to failure to wean and poor long-term clinical outcomes. Point-of-care ultrasound provides a valid and reproducible method for evaluating diaphragm thickness and contractile activity (thickening fraction during inspiration) that can be readily employed by clinicians and researchers alike. This article presents best practices for measuring diaphragm thickness and quantifying diaphragm thickening during tidal breathing or maximal inspiration. Once mastered, this technique can be used to diagnose and prognosticate diaphragm dysfunction, and guide and monitor response to treatment over time in both healthy individuals and acute or chronically ill patients.

Combining meta-analysis with multiple imputation for one-step, privacy-protecting estimation of causal treatment effects in multi-site studies.

Missing data complicates statistical analyses in multi-site studies, especially when it is not feasible to centrally pool individual-level data across sites. We combined meta-analysis with within-site multiple imputation for one-step estimation of the average causal effect (ACE) of a target population comprised of all individuals from all data-contributing sites within a multi-site distributed data network, without the need for sharing individual-level data to handle missing data. We considered two orders of combination and three choices of weights for meta-analysis, resulting in six approaches. The first three approaches, denoted as RR + metaF, RR + metaR and RR + std, first combined results from imputed data sets within each site using Rubin's rules and then meta-analyzed the combined results across sites using fixed-effect, random-effects and sample-standardization weights, respectively. The last three approaches, denoted as metaF + RR, metaR + RR and std + RR, first meta-analyzed results across sites separately for each imputation and then combined the meta-analysis results using Rubin's rules. Simulation results confirmed very good performance of RR + std and std + RR under various missing completely at random and missing at random settings. A direct application of the inverse-variance weighted meta-analysis based on site-specific ACEs can lead to biased results for the targeted network-wide ACE in the presence of treatment effect heterogeneity by site, demonstrating the need to clearly specify the target population and estimand and properly account for potential site heterogeneity in meta-analyses seeking to draw causal interpretations. An illustration using a large administrative claims database is presented.

Does Using a Stacking Ensemble Method to Combine Multiple Base Learners Within a Database Improve Model Transportability?

We investigated a stacking ensemble method that combines multiple base learners within a database. The results on external validation across four large databases suggest a stacking ensemble could improve model transportability.

Imputing missing covariates in time-to-event analysis within distributed research networks: A simulation study.

PURPOSE: In distributed research network (DRN) settings, multiple imputation cannot be directly implemented because pooling individual-level data are often not feasible. The performance of multiple imputation in combination with meta-analysis is not well understood within DRNs. METHODS: To evaluate the performance of imputation for missing baseline covariate data in combination with meta-analysis for time-to-event analysis within DRNs, we compared two parametric algorithms including one approximated linear imputation model (Approx), and one nonlinear substantive model compatible imputation model (SMC), as well as two non-parametric machine learning algorithms including random forest (RF), and classification and regression trees (CART), through simulation studies motivated by a real-world data set. RESULTS: Under the setting with small effect sizes (i.e., log-Hazard ratios [logHR]) and homogeneous missingness mechanisms across sites, all imputation methods produced unbiased and more efficient estimates while the complete-case analysis could be biased and inefficient; and under heterogeneous missingness mechanisms, estimates with RF method could have higher efficiency. Estimates from the distributed imputation combined by meta-analysis were similar to those from the imputation using pooled data. When logHRs were large, the SMC imputation algorithm generally performed better than others. CONCLUSIONS: These findings suggest the validity and feasibility of imputation within DRNs in the presence of missing covariate data in time-to-event analysis under various settings. The performance of the four imputation algorithms varies with the effect sizes and level of missingness.

Strategies for lung- and diaphragm-protective ventilation in acute hypoxemic respiratory failure: a physiological trial.

BACKGROUND: Insufficient or excessive respiratory effort during acute hypoxemic respiratory failure (AHRF) increases the risk of lung and diaphragm injury. We sought to establish whether respiratory effort can be optimized to achieve lung- and diaphragm-protective (LDP) targets (esophageal pressure swing - 3 to - 8 cm H2O; dynamic transpulmonary driving pressure ≤ 15 cm H2O) during AHRF. METHODS: In patients with early AHRF, spontaneous breathing was initiated as soon as passive ventilation was not deemed mandatory. Inspiratory pressure, sedation, positive end-expiratory pressure (PEEP), and sweep gas flow (in patients receiving veno-venous extracorporeal membrane oxygenation (VV-ECMO)) were systematically titrated to achieve LDP targets. Additionally, partial neuromuscular blockade (pNMBA) was administered in patients with refractory excessive respiratory effort. RESULTS: Of 30 patients enrolled, most had severe AHRF; 16 required VV-ECMO. Respiratory effort was absent in all at enrolment. After initiating spontaneous breathing, most exhibited high respiratory effort and only 6/30 met LDP targets. After titrating ventilation, sedation, and sweep gas flow, LDP targets were achieved in 20/30. LDP targets were more likely to be achieved in patients on VV-ECMO (median OR 10, 95% CrI 2, 81) and at the PEEP level associated with improved dynamic compliance (median OR 33, 95% CrI 5, 898). Administration of pNMBA to patients with refractory excessive effort was well-tolerated and effectively achieved LDP targets. CONCLUSION: Respiratory effort is frequently absent  under deep sedation but becomes excessive when spontaneous breathing is permitted in patients with moderate or severe AHRF. Systematically titrating ventilation and sedation can optimize respiratory effort for lung and diaphragm protection in most patients. VV-ECMO can greatly facilitate the delivery of a LDP strategy. TRIAL REGISTRATION: This trial was registered in Clinicaltrials.gov in August 2018 (NCT03612583).

Applying Machine Learning in Distributed Data Networks for Pharmacoepidemiologic and Pharmacovigilance Studies: Opportunities, Challenges, and Considerations.

Increasing availability of electronic health databases capturing real-world experiences with medical products has garnered much interest in their use for pharmacoepidemiologic and pharmacovigilance studies. The traditional practice of having numerous groups use single databases to accomplish similar tasks and address common questions about medical products can be made more efficient through well-coordinated multi-database studies, greatly facilitated through distributed data network (DDN) architectures. Access to larger amounts of electronic health data within DDNs has created a growing interest in using data-adaptive machine learning (ML) techniques that can automatically model complex associations in high-dimensional data with minimal human guidance. However, the siloed storage and diverse nature of the databases in DDNs create unique challenges for using ML. In this paper, we discuss opportunities, challenges, and considerations for applying ML in DDNs for pharmacoepidemiologic and pharmacovigilance studies. We first discuss major types of activities performed by DDNs and how ML may be used. Next, we discuss practical data-related factors influencing how DDNs work in practice. We then combine these discussions and jointly consider how opportunities for ML are affected by practical data-related factors for DDNs, leading to several challenges. We present different approaches for addressing these challenges and highlight efforts that real-world DDNs have taken or are currently taking to help mitigate them. Despite these challenges, the time is ripe for the emerging interest to use ML in DDNs, and the utility of these data-adaptive modeling techniques in pharmacoepidemiologic and pharmacovigilance studies will likely continue to increase in the coming years.

Association of Antidepressant Prescription Filling With Treatment Indication and Prior Prescription Filling Behaviors and Medication Experiences.

BACKGROUND: Given the wide range of uses for antidepressants, understanding indication-specific patterns of prescription filling for antidepressants provide valuable insights into how patients use these medications in real-world settings. OBJECTIVE: The objective of this study was to determine the association of antidepressant prescription filling with treatment indication, as well as prior prescription filling behaviors and medication experiences. DESIGN: This retrospective cohort study took place in Quebec, Canada. PARTICIPANTS: Adults with public drug insurance prescribed antidepressants using MOXXI (Medical Office of the XXIst Century)-an electronic prescribing system requiring primary care physicians to document treatment indications and reasons for prescription stops or changes. MEASURES: MOXXI provided information on treatment indications, past prescriptions, and prior medication experiences (treatment ineffectiveness and adverse drug reactions). Linked claims data provided information on dispensed medications and other patient-related factors. Multivariable logistic regression models estimated the independent association of not filling an antidepressant prescription (within 90 d) with treatment indication and patients' prior prescription filling behaviors and medication experiences. RESULTS: Among 38,751 prescriptions, the prevalence of unfilled prescriptions for new and ongoing antidepressant therapy was 34.2% and 4.1%, respectively. Compared with depression, odds of not filling an antidepressant prescription varied from 0.74 to 1.57 by indication and therapy status. The odds of not filling an antidepressant prescription was higher among adults filling < 50% of their medication prescriptions in the past year and adults with an antidepressant prescription stopped or changed in the past year due to treatment ineffectiveness. CONCLUSION: Antidepressant prescription filling behaviors differed by treatment indication and were lower among patients with a history of poor prescription filling or ineffective treatment with antidepressants.

Prognostic Utility of Breast Cancer Index to Stratify Distant Recurrence Risk in Invasive Lobular Carcinoma.

PURPOSE: The prognostic utility of Breast Cancer Index (BCI) for risk assessment of overall (0-10 years), early (0-5 years), and late (5-10 years) distant recurrence (DR) in hormone receptor-positive (HR+) invasive lobular carcinoma (ILC) was evaluated. EXPERIMENTAL DESIGN: BCI gene expression analysis was performed blinded to clinical outcome utilizing tumor specimens from patients with HR+ ILC from a multi-institutional cohort. The primary endpoint was time to DR. Kaplan-Meier analyses of overall, early, and late DR risk were performed, and statistical significance was evaluated by log-rank test and Cox proportional hazards regression. The prognostic contribution of BCI in addition to clinicopathologic factors was evaluated by likelihood ratio analysis. RESULTS: Analysis of 307 patients (99% ER+, 53% T1, 42% N+, 70% grade II) showed significant differences in DR over 10 years based on BCI risk categories. BCI low- and intermediate-risk patients demonstrated similar DR rates of 7.6% and 8.0%, respectively, compared with 27.0% for BCI high-risk patients. BCI was a significant independent prognostic factor for overall 10-year DR [HR = 4.09; 95% confidence interval (CI), 2.00-8.34; P = 0.0001] as well as for both early (HR = 8.19; 95% CI, 1.85-36.30; P = 0.0042) and late (HR = 3.04; 95% CI, 1.32-7.00; P = 0.0224) DR. In multivariate analysis, BCI remained the only statistically significant prognostic factor for DR (HR = 3.49; 95% CI, 1.28-9.54; P = 0.0150). CONCLUSIONS: BCI is an independent prognostic factor for ILC and significantly stratified patients for cumulative risk of 10-year, early, and late DR. BCI added prognostic value beyond clinicopathologic characteristics in this distinct subtype of breast cancer.

Abdominal Muscle Use During Spontaneous Breathing and Cough in Patients Who Are Mechanically Ventilated: A Bi-center Ultrasound Study.

BACKGROUND: Ultrasound may be useful to assess the structure, activity, and function of the abdominal muscles in patients who are mechanically ventilated. RESEARCH QUESTION: Does measurement of abdominal muscle thickening on ultrasound in patients who are mechanically ventilated provide clinically relevant information about abdominal muscle function and weaning outcomes? STUDY DESIGN AND METHODS: This study consisted of two parts, a physiological study conducted in healthy subjects and a prospective observational study in patients who were mechanically ventilated. Abdominal muscle thickness and thickening fraction were measured during cough and expiratory efforts in 20 healthy subjects, and prior to and during a spontaneous breathing trial in 57 patients being ventilated. RESULTS: In healthy subjects, internal oblique and rectus abdominis thickening fraction correlated with pressure generated during expiratory efforts (P < .001). In patients being ventilated, abdominal muscle thickness and thickening fraction were feasible to measure in all patients, and reproducibility was moderately acceptable. During a failed spontaneous breathing trial, thickening fraction of transversus abdominis and internal oblique increased substantially from baseline (13.2% [95% CI, 0.9-24.8] and 7.2% [95% CI, 2.2-13.2], respectively). The combined thickening fraction of transversus abdominis, internal oblique, and rectus abdominis measured during cough was associated with an increased risk of reintubation or reconnection to the ventilator following attempted liberation (OR, 2.1; 95% CI, 1.1-4.4 per 10% decrease in thickening fraction). INTERPRETATION: Abdominal muscle thickening on ultrasound was correlated to the airway pressure generated by expiratory efforts. In patients who were mechanically ventilated, abdominal muscle ultrasound measurements are feasible and moderately reproducible. Among patients who passed a spontaneous breathing trial, reduced abdominal muscle thickening during cough was associated with a high risk of liberation failure. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT03567564; URL: www.clinicaltrials.gov.

Diaphragm function in acute respiratory failure and the potential role of phrenic nerve stimulation.

PURPOSE OF REVIEW: The aim of this review was to describe the risk factors for developing diaphragm dysfunction, discuss the monitoring techniques for diaphragm activity and function, and introduce potential strategies to incorporate diaphragm protection into conventional lung-protective mechanical ventilation strategies. RECENT FINDINGS: It is increasingly apparent that an approach that addresses diaphragm-protective ventilations goals is needed to optimize ventilator management and improve patient outcomes. Ventilator-induced diaphragm dysfunction (VIDD) is common and is associated with increased ICU length of stay, prolonged weaning and increased mortality. Over-assistance, under-assistance and patient-ventilator dyssynchrony may have important downstream clinical consequences related to VIDD. Numerous monitoring techniques are available to assess diaphragm function, including respiratory system pressures, oesophageal manometry, diaphragm ultrasound and electromyography. Novel techniques including phrenic nerve stimulation may facilitate the achievement of lung and diaphragm-protective goals for mechanical ventilation. SUMMARY: Diaphragm protection is an important consideration in optimizing ventilator management in patients with acute respiratory failure. The delicate balance between lung and diaphragm-protective goals is challenging. Phrenic nerve stimulation may be uniquely situated to achieve and balance these two commonly conflicting goals.

Risk of in-hospital falls among medications commonly used for insomnia in hospitalized patients.

STUDY OBJECTIVES: To investigate the risk of in-hospital falls among patients receiving medications commonly used for insomnia in the hospital setting. METHODS: Retrospective cohort study of all adult hospitalizations to a large academic medical center from January, 2007 to July, 2013. We excluded patients admitted for a primary psychiatric disorder. Medication exposures of interest, defined by pharmacy charges, included benzodiazepines, non-benzodiazepine benzodiazepine receptor agonists, trazodone, atypical antipsychotics, and diphenhydramine. In-hospital falls were ascertained from an online patient safety reporting system. RESULTS: Among the 225,498 hospitalizations (median age = 57 years; 57.9% female) in our cohort, 84,911 (37.7%) had exposure to at least one of the five medication classes of interest; benzodiazepines were the most commonly used (23.5%), followed by diphenhydramine (8.3%), trazodone (6.6%), benzodiazepine receptor agonists (6.4%), and atypical antipsychotics (6.3%). A fall occurred in 2,427 hospitalizations (1.1%). The rate of falls per 1,000 hospital days was greater among hospitalizations with exposure to each of the medications of interest, compared to unexposed: 3.6 versus 1.7 for benzodiazepines (adjusted hazard ratio [aHR] 1.8, 95%CI 1.6-1.9); 5.4 versus 1.8 for atypical antipsychotics (aHR 1.6, 95%CI 1.4-1.8); 3.0 versus 2.0 for benzodiazepine receptor agonists (aHR 1.5, 95%CI 1.3-1.8); 3.3 versus 2.0 for trazodone (aHR 1.2, 95%CI 1.1-1.5); and 2.5 versus 2.0 for diphenhydramine (aHR 1.2, 95%CI 1.03-1.5). CONCLUSIONS: In this large cohort of hospitalizations at an academic medical center, we found an association between each of the sedating medications examined and in-hospital falls. Benzodiazepines, benzodiazepine receptor agonists, and atypical antipsychotics had the strongest associations.