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.

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.

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.

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).

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.

Can Hyperparameter Tuning Improve the Performance of a Super Learner?: A Case Study.

BACKGROUND: Super learning is an ensemble machine learning approach used increasingly as an alternative to classical prediction techniques. When implementing super learning, however, not tuning the hyperparameters of the algorithms in it may adversely affect the performance of the super learner. METHODS: In this case study, we used data from a Canadian electronic prescribing system to predict when primary care physicians prescribed antidepressants for indications other than depression. The analysis included 73,576 antidepressant prescriptions and 373 candidate predictors. We derived two super learners: one using tuned hyperparameter values for each machine learning algorithm identified through an iterative grid search procedure and the other using the default values. We compared the performance of the tuned super learner to that of the super learner using default values ("untuned") and a carefully constructed logistic regression model from a previous analysis. RESULTS: The tuned super learner had a scaled Brier score (R) of 0.322 (95% [confidence interval] CI = 0.267, 0.362). In comparison, the untuned super learner had a scaled Brier score of 0.309 (95% CI = 0.256, 0.353), corresponding to an efficiency loss of 4% (relative efficiency 0.96; 95% CI = 0.93, 0.99). The previously-derived logistic regression model had a scaled Brier score of 0.307 (95% CI = 0.245, 0.360), corresponding to an efficiency loss of 5% relative to the tuned super learner (relative efficiency 0.95; 95% CI = 0.88, 1.01). CONCLUSIONS: In this case study, hyperparameter tuning produced a super learner that performed slightly better than an untuned super learner. Tuning the hyperparameters of individual algorithms in a super learner may help optimize performance.

A novel non-invasive method to detect excessively high respiratory effort and dynamic transpulmonary driving pressure during mechanical ventilation.

BACKGROUND: Excessive respiratory muscle effort during mechanical ventilation may cause patient self-inflicted lung injury and load-induced diaphragm myotrauma, but there are no non-invasive methods to reliably detect elevated transpulmonary driving pressure and elevated respiratory muscle effort during assisted ventilation. We hypothesized that the swing in airway pressure generated by respiratory muscle effort under assisted ventilation when the airway is briefly occluded (ΔPocc) could be used as a highly feasible non-invasive technique to screen for these conditions. METHODS: Respiratory muscle pressure (Pmus), dynamic transpulmonary driving pressure (ΔPL,dyn, the difference between peak and end-expiratory transpulmonary pressure), and ΔPocc were measured daily in mechanically ventilated patients in two ICUs in Toronto, Canada. A conversion factor to predict ΔPL,dyn and Pmus from ΔPocc was derived and validated using cross-validation. External validity was assessed in an independent cohort (Nanjing, China). RESULTS: Fifty-two daily recordings were collected in 16 patients. In this sample, Pmus and ΔPL were frequently excessively high: Pmus exceeded 10 cm H2O on 84% of study days and ΔPL,dyn exceeded 15 cm H2O on 53% of study days. ΔPocc measurements accurately detected Pmus > 10 cm H2O (AUROC 0.92, 95% CI 0.83-0.97) and ΔPL,dyn > 15 cm H2O (AUROC 0.93, 95% CI 0.86-0.99). In the external validation cohort (n = 12), estimating Pmus and ΔPL,dyn from ΔPocc measurements detected excessively high Pmus and ΔPL,dyn with similar accuracy (AUROC ≥ 0.94). CONCLUSIONS: Measuring ΔPocc enables accurate non-invasive detection of elevated respiratory muscle pressure and transpulmonary driving pressure. Excessive respiratory effort and transpulmonary driving pressure may be frequent in spontaneously breathing ventilated patients.

Assessing the accuracy of using diagnostic codes from administrative data to infer antidepressant treatment indications: a validation study.

PURPOSE: To assess the accuracy of using diagnostic codes from administrative data to infer treatment indications for antidepressants prescribed in primary care. METHODS: Validation study of administrative diagnostic codes for 13 plausible indications for antidepressants compared with physician-documented treatment indications from an indication-based electronic prescribing system in Quebec, Canada. The analysis included all antidepressant prescriptions written by primary care physicians between January 1, 2003 and December 31, 2012 using the electronic prescribing system. Patient prescribed antidepressants were linked to physician claims and hospitalization data to obtain all diagnoses recorded in the past year. RESULTS: Diagnostic codes had poor sensitivity for all treatment indications, ranging from a high of only 31.2% (95% CI, 26.8%-35.9%) for anxiety/stress disorders to as low as 1.3% (95% CI, 0.0%-5.2%) for sexual dysfunction. Sensitivity was notably worse among older patients and patients with more chronic comorbidities. Physician claims data were a better source of diagnostic codes for antidepressant treatment indications than hospitalization data. CONCLUSIONS: Administrative diagnostic codes are poor proxies for antidepressant treatment indications. Future work should determine whether the use of other variables in administrative data besides diagnostic codes can improve the ability to predict antidepressant treatment indications.

A Dynamic Predictive Model for Progression of CKD.

BACKGROUND: Predicting the progression of chronic kidney disease (CKD) is vital for clinical decision making and patient-provider communication. We previously developed an accurate static prediction model that used single-timepoint measurements of demographic and laboratory variables. STUDY DESIGN: Development of a dynamic predictive model using demographic, clinical, and time-dependent laboratory data from a cohort of patients with CKD stages 3 to 5. SETTING & PARTICIPANTS: We studied 3,004 patients seen April 1, 2001, to December 31, 2009, in the outpatient CKD clinic of Sunnybrook Hospital in Toronto, Canada. CANDIDATE PREDICTORS: Age, sex, and urinary albumin-creatinine ratio at baseline. Estimated glomerular filtration rate (eGFR), serum albumin, phosphorus, calcium, and bicarbonate values as time-dependent predictors. OUTCOMES: Treated kidney failure, defined by initiation of dialysis therapy or kidney transplantation. ANALYTICAL APPROACH: We describe a dynamic (latest-available-measurement) prediction model using time-dependent laboratory values as predictors of outcome. Our static model included all 8 candidate predictors. The latest-available-measurement model includes age and the latter 5 variables as time-dependent predictors. We used Cox proportional hazards models for time to kidney failure and compared discrimination, calibration, model fit, and net reclassification for the models. RESULTS: We studied 3,004 patients, who had 344 kidney failure events over a median follow-up of 3 years and an average of 5 clinic visits. eGFR was more strongly associated with kidney failure in the latest-available-measurement model versus the baseline visit static model (HR, 0.44 vs 0.65). The association of calcium level was unchanged, but male sex and phosphorus, albumin, and bicarbonate levels were no longer significant. Discrimination and goodness of fit showed incremental improvement with inclusion of time-dependent covariates (integrated discrimination improvement, 0.73%; 95% CI, 0.56%-0.90%). LIMITATIONS: Our data were derived from a nephrology clinic at a single center. We were unable to include time-dependent changes in albuminuria. CONCLUSIONS: A latest-available-measurement predictive model with eGFR as a time-dependent predictor can incrementally improve risk prediction for kidney failure over a static model with only a single eGFR.

Long-term efavirenz use is associated with worse neurocognitive functioning in HIV-infected patients.

Neurocognitive (NC) complications continue to afflict a substantial proportion of HIV-infected people taking effective antiretroviral therapy (ART). One contributing mechanism for this is antiretroviral neurotoxicity. Efavirenz (EFV) is associated with short-term central nervous system (CNS) toxicity, but less is known about its long-term effects. Our objective was to compare NC functioning with long-term use of EFV to that of a comparator, lopinavir-ritonavir (LPV/r), in a cohort of well-characterized adults. Four hundred forty-five patients were selected from the CNS HIV Antiretroviral Therapy Effects Research (CHARTER) cohort based on their use of either EFV (n = 272, mean duration 17.9 months) or LPV/r (n = 173, mean duration 16.4 months) and the lack of severe NC comorbidities. All patients had undergone standardized comprehensive NC testing. Univariable and multivariable analyses to predict NC outcomes were performed. Compared with LPV/r users, EFV users were more likely to be taking their first ART regimen (p < 0.001), were less likely to have AIDS (p < 0.001) or hepatitis C virus (HCV) coinfection (p < 0.05), had higher CD4+ T cell nadirs (p < 0.001), had lower peak (p < 0.001) and current (p < 0.001) plasma HIV RNA levels, and were less likely to have detectable HIV RNA in cerebrospinal fluid (CSF) (p < 0.001). Overall, EFV users had worse speed of information processing (p = 0.04), verbal fluency (p = 0.03), and working memory (p = 0.03). An interaction with HCV serostatus was present: Overall among HCV seronegatives (n = 329), EFV users performed poorly, whereas among HCV seropositives (n = 116), LPV/r users had overall worse performance. In the subgroup with undetectable plasma HIV RNA (n = 269), EFV users had worse speed of information processing (p = 0.02) and executive functioning (p = 0.03). Substantial differences exist between EFV and LPV/r users in this observational cohort, possibly because of channeling by clinicians who may have prescribed LPV/r to more severely ill patients or as second-line therapy. Despite these differences, EFV users had worse functioning in several cognitive abilities. A potentially important interaction was identified that could indicate that the NC consequences of specific antiretroviral drugs may differ based on HCV coinfection. The complexity of these data is substantial, and findings would best be confirmed in a randomized clinical trial.

A cross-sectional, population-based study of HIV physicians and outpatient health care use by people with HIV in Ontario.

BACKGROUND: People with HIV are living longer and their care has shifted towards the prevention and management of comorbidities. However, little is known about who is providing their care. Our objective was to characterize the provision of HIV care in Ontario by physician specialty. METHODS: We conducted a retrospective population-based observational study using linked administrative databases in Ontario, Canada, a single payer health care system. All Ontarians with HIV were identified using a validated case ascertainment algorithm. We examined office-based health care visits for this cohort between April 1, 2009 and March 31, 2012. Physician characteristics were compared between specialty groups. We stratified the frequency and distribution of physician care into three categories: (a) care by physician specialty (family physicians, internal medicine specialists, infectious disease specialists, and other specialists), (b) care based on physician caseload (low, medium or high categorized as ≤5, 6-49 or ≥50 HIV patients per physician), and (c) care that is related to HIV versus unrelated to HIV. RESULTS: Family physicians were older, graduated earlier, were more often female, and were the only group practicing in rural settings. Unlike other specialists, most family physicians (76.8%) had low-volume caseloads. There were 406,411 outpatient visits made by individuals with HIV; one-third were for HIV care. Family physicians provided the majority of care (53.6% of all visits and 53.9% of HIV visits). Internal medicine specialists provided 4.9% of all visits and 9.6% of HIV visits. Infectious disease specialists provided 12.5% of all visits and 32.7% of HIV visits. Other specialties provided 29.0% of visits; most of these (33.0%) were to psychiatrists. CONCLUSIONS: The distribution of visits to physicians caring for HIV patients reveals different patterns of health care delivery by specialty and HIV caseload. Further research should delineate how specialties share care for this population and how different patterns relate to quality of care.

Independent influence of negative blood cultures and bloodstream infections on in-hospital mortality.

BACKGROUND: The independent influence of blood culture testing and bloodstream infection (BSI) on hospital mortality is unclear. METHODS: We included all adults treated in non-psychiatric services at our hospital between 2004 and 2011. We identified all blood cultures and their results to determine the independent association of blood culture testing and BSI on death in hospital using proportional hazards modeling that adjusted for important covariates. RESULTS: Of 297 070 hospitalizations, 48 423 had negative blood cultures and 5274 had BSI. 12 529 (4.2%) died in hospital. Compared to those without blood cultures, culture-negative patients and those with BSI were sicker. Culture-negative patients had a significantly increased risk of death in hospital (adjusted hazard ratio [HR] ranging between 3.1 and 4.4 depending on admission urgency, extent of comorbidities, and whether the blood culture was taken in the intensive care unit). Patients with BSI had a significantly increased risk of death (adj-HR ranging between 3.8 and 24.3] that was significantly higher when BSI was: diagnosed within the first hospital day; polymicrobial; in patients who were exposed to immunosuppressants or were neutropenic; or due to Clostridial and Candidal organisms. Death risk in culture negative and bloodstream infection patients decreased significantly with time. CONCLUSIONS: Risk of death in hospital is independently increased both in patients with negative blood cultures and further in those with bloodstream infection. Death risk associated with bloodstream infections varied by the patient's immune status and the causative microorganism.

A cross-sectional, population-based study measuring comorbidity among people living with HIV in Ontario.

BACKGROUND: As people diagnosed with HIV and receiving combination antiretroviral therapy are now living longer, they are likely to acquire chronic conditions related to normal ageing and the effects of HIV and its treatment. Comordidities for people with HIV have not previously been described from a representative population perspective. METHODS: We used linked health administrative data from Ontario, Canada. We applied a validated algorithm to identify people with HIV among all residents aged 18 years or older between April 1, 1992 and March 31, 2009. We randomly selected 5 Ontario adults who were not identified with HIV for each person with HIV for comparison. Previously validated case definitions were used to identify persons with mental health disorders and any of the following physical chronic diseases: diabetes, congestive heart failure, acute myocardial infarction, stroke, hypertension, asthma, chronic obstructive lung disease, peripheral vascular disease and end-stage renal failure. We examined multimorbidity prevalence as the presence of at least two physical chronic conditions, or as combined physical-mental health multimorbidity. Direct age-sex standardized rates were calculated for both cohorts for comparison. RESULTS: 34.4% (95% confidence interval (CI) 33.6% to 35.2%) of people with HIV had at least one other physical condition. Prevalence was especially high for mental health conditions (38.6%), hypertension (14.9%) and asthma (12.7%). After accounting for age and sex differences, people with HIV had significantly higher prevalence of all chronic conditions except myocardial infarction and hypertension, as well as substantially higher multimorbidity (prevalence ratio 1.30, 95% CI 1.18 to 1.44) and combined physical-mental health multimorbidity (1.79, 95% CI 1.65 to 1.94). Prevalence of multimorbidity among people with HIV increased with age. The difference in prevalence of multimorbidity between the two cohorts was more pronounced among women. CONCLUSION: People living with HIV in Ontario, especially women, had higher prevalence of comorbidity and multimorbidity than the general population. Quantifying this morbidity at the population level can help inform healthcare delivery requirements for this complex population.

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.

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.

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.

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.

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.