Citations

ABSTRACT Skeletal muscle (SM) is an integral organ component in the pathophysiology of many acute and chronic diseases. But is there a ‘gold’ standard or accepted reference method for quantifying the amount and composition of human SM mass? Exploring that question led us to recognize the existence of a SM measurement paradigm that divides methods into two broad categories, in vitro and in vivo. In vitro methods quantify SM mass, weighing intact muscles as part of whole cadaver evaluations, only 51 of which are reported in medical literature with no recent additions. In vivo methods are used to evaluate SM in vivo, and two tiers were revealed in our analyses. An upper tier that included three methods considered ‘reference’ approaches for their accuracy and precision: computed tomography, magnetic resonance imaging and dual‐energy X‐ray absorptiometry. A lower in vivo method tier included bioimpedance analysis, three‐dimensional imaging, several approaches involving creatine metabolism, ultrasound and anthropometry. A feature common to all of the lower tier methods is their need for calibration or validation against reference approaches in the upper in vivo method tier. A critical review of the three in vivo reference methods in the upper tier revealed widely variable SM volume/mass acquisition protocols, image analysis methods and applied terminology. Some reports espouse an upper tier reference method as the ‘gold’ standard while providing minimal details of exactly how and what was measured, thus making replication in follow‐up studies difficult. Any technical issues related to an in vivo reference method are propagated to the in vivo methods in the lower tier that are calibrated or validated against them. Our review of in vivo reference methods of quantifying SM mass and composition led us to two broad recommendations. First, published reports including these reference methods should provide enough details related to acquisition and analysis protocols so that readers can replicate their findings. Second, an effort should be made to apply precise terminology in published reports in order to avoid confusion on exactly what was measured; suggestions are made on definitions of commonly used terms when referring to body composition compartments. Lastly, because there is no consensus on what constitutes a ‘gold’ standard for SM measurement, we suggest expert groups convene in the future to recommend optimum approaches and working guidelines for quantifying muscle mass and composition in vivo.

ABSTRACT Background and Aim Determining the location of gastrointestinal (GI) bleeding is critical for guiding diagnostic and therapeutic strategies but often results in patients receiving pan‐endoscopy with upper endoscopy, colonoscopy, and small bowel capsule endoscopy, which can be unnecessary, costly, and waste limited healthcare resources. The blood urea nitrogen‐to‐creatinine ratio (BUN/Cr) may help discriminate between upper GI bleeding (UGIB) and lower GI bleeding (LGIB). This study aims to assess the diagnostic performance of the BUN/Cr in distinguishing UGIB from LGIB. Methods A literature search was conducted in MEDLINE, EMBASE, and Cochrane Library to identify diagnostic test accuracy studies published from inception through January 31, 2025, which evaluated BUN/Cr in patients with UGIB versus LGIB. A linear mixed‐effects model meta‐analysis was conducted using the “diagmeta” package. The pooled sensitivity, specificity, diagnostic odds ratio, and area under the summary receiver operating characteristic curve (AUC) were estimated, and optimal threshold was determined using the Youden index. Results Seventeen studies were included in this meta‐analysis. The pooled mean difference in BUN/Cr between UGIB and LGIB patients was 11.44 (95% confidence interval [95% CI] 8.35–14.52). At a threshold of > 30, pooled sensitivity was 38.8% (95% CI 28.1%–50.8%) and specificity was 89.3% (95% CI 81.0%–94.2%). At the optimal cut‐off of 22, sensitivity was 66.2% (95% CI 57.8%–73.7%), specificity was 71.0% (95% CI 58.5%–81.0%), and AUC was 0.740 (95% CI 0.683–0.794). Conclusion BUN/Cr demonstrates moderate diagnostic accuracy for distinguishing UGIB from LGIB, particularly at a threshold of ≥ 22. This readily accessible and inexpensive blood test may assist in early clinical triage and assessment of the location of GI bleeding, particularly in those patients where the clinical presentation is obscure.

Abstract Objective To develop a comprehensive risk stratification model to identify patients at high risk of cesarean surgical site infection (cSSI) based on information available at the time of hospital discharge. Methods This is a retrospective cohort study based on datasets from two independent level IV academic medical centers to improve generalizability. The first study includes 2336 cesarean deliveries for analysis with 109 instances of cSSI (4.7%). The second study includes 2936 cesarean deliveries with 72 instances of cSSI (2.5%). The first study cohort was utilized for both model training and internal validation, using the 15 shared features present in both datasets. Random search with cross‐validation was used to choose the type of machine learning (ML) model and its hyperparameters, with area under the receiver operating characteristic curve (AUC) as the validation metric. The second study cohort was then used to evaluate testing accuracy (external validation) and generalization capability of this model. The predictive importance of each feature was evaluated using permutation importance applied to the second cohort. Risk stratification cutoff scores were defined based on centiles over the first patient cohort and evaluated on the second cohort. Results The ML model with the highest validation AUC was an XGBoost classifier. This trained model achieved an AUC of 0.78 on the training data and a 0.72 cross‐validated AUC. When tested on data from the second study cohort, it achieved an AUC of 0.69. The features showing the strongest predictive generalization, as measured by permutation importance, were length of hospital stay, primary indication for cesarean delivery, and estimated blood loss. Using the second cohort to test our model, the model shows a 22.7% positive predictive value (PPV) of cSSI among women in the highest risk group, and a 0.8% PPV among women in the bottom risk group, compared with 2.5% cSSI incidence for the study population at large. Conclusion We developed and validated a predictive ML model for cSSI with information available to healthcare professionals at the time of hospital discharge. This model suggests that the most predictive risk factors for cSSI include length of hospital stay, primary indication for cesarean delivery, and estimated blood loss. Additionally, the model provides reasonable risk stratifications for individual patients. This tool may be used for identifying subgroups at higher risk of cSSI and identifying those who may require closer surveillance or clinical intervention.

Background: Circulating tumor DNA (ctDNA) is predictive of recurrence in resected stage III melanoma, yet its role in the neoadjuvant setting for clinical stage III (cSIII) is unclear. Objective: Assess the association between ctDNA and outcomes following neoadjuvant immunotherapy (IO) + targeted therapy (TT) in cSIII melanoma. Design: Patients in the NeoACTIVATE study were treated with neoadjuvant IO + TT, underwent lymphadenectomy, and received adjuvant immunotherapy. Methods: Patients with ctDNA testing performed at baseline, pre- and post-operation were analyzed. Baseline positron emission tomography–computed tomography volumetrics and surgical, major pathological responses (MPR) were assessed. Results: Thirteen patients had serial ctDNA, 10 (77%) were detectable at baseline, and 9/10 (90%) had ctDNA clearance. Seven (54%) achieved MPR, all with undetectable preoperative ctDNA, yet 3/7 (43%) had disease recurrence. Conclusion: ctDNA and MPR are poor predictors of recurrence following neoadjuvant IO + TT for cSIII melanoma patients. Further studies are warranted to define the role of ctDNA in this setting.

ABSTRACT Background VEXAS is a relatively newly described immunocompromising condition with hematopoietic stem cell transplant increasingly being used. Little is known regarding infections in this high‐risk population. Methods We conducted a retrospective review of ten adult patients diagnosed with VEXAS who underwent HSCT in the Mayo Clinic Rochester and the Arizona medical record system. Results Nine out of ten individuals developed bacterial infection with bacteremia found in eight individuals despite being on prophylaxis at the time of infection. Six of the ten individuals were found to have viral infection; there were no documented invasive fungal infections and only one individual had a parasitic infection. Conclusion Providers should have a high suspicion for infection, especially bacterial, in this patient population, regardless of prophylaxis use. Patients should also be educated on signs and symptoms of infection.

ABSTRACT Background Solid organ transplant (SOT) recipients are at risk for Pneumocystis jirovecii pneumonia (PCP), yet how their clinical phenotype and outcomes compare with other immunocompromised patients without HIV remains poorly defined. Methods We conducted a multicenter retrospective cohort study of adults with proven or probable PCP from 2017 to 2025, including 95 SOT recipients and 588 non‐SOT, non‐HIV immunocompromised patients. The primary outcome was 90‐day mortality, secondary outcomes included new renal failure requiring dialysis, and 30‐day mortality. Outcomes were analyzed using inverse probability weighting (IPW) with winsorization to adjust for baseline differences. Results In unadjusted analysis, SOT recipients had lower 90‐day mortality (hazard ratio [HR]: 0.62, 95% CI 0.39–0.97, p = 0.037). After IPW with winsorization of extreme weights, SOT status remained associated with lower 90‐day mortality (HR: 0.32, 95% CI 0.13–0.76, p = 0.009), and 30‐day mortality (HR: 0.35, 95% CI: 0.14–0.92, p = 0.034). SOT recipients had higher odds of renal failure requiring dialysis in unadjusted analysis (OR: 3.49, 95% CI 1.94–6.14, p < 0.001), which persisted after IPW adjustment (OR: 1.62, 95% CI: 1.04–2.51, p = 0.032). Conclusions Despite higher rates of renal failure requiring dialysis, SOT recipients with PCP experienced significantly improved short‐ and intermediate‐term survival compared with other non‐HIV immunocompromised patients, underscoring the need for further investigation into transplant‐associated contributors to PCP outcomes.

Purpose This study assessed the association between holding an additional graduate degree beyond a Doctor of Medicine (MD) or Doctor of Osteopathic Medicine (DO) and residency match outcomes. Specifically, the authors examined graduate degree attainment trends among residency applicants and evaluated whether graduate degree holders experience lower match rates than non-holders. Methods A retrospective, observational analysis was conducted using publicly available data from the National Resident Matching Program's Charting Outcomes in the Match reports (2016-2024). The 10 specialties with the highest applicant volumes were analyzed, encompassing 80 136 matched and 6820 unmatched U.S. MD and DO senior applicants. Trends in graduate degree attainment were evaluated using linear regression models. Match rates were stratified by graduate degree status and compared using two-proportion z-tests based on aggregated matched and unmatched counts for each specialty and overall. Results From 2016 to 2024, the proportion of graduate degree holders entering the match increased significantly for MD (15.77% to 18.29%, P = .0008) and DO (19.93% to 23.31%, P = .0151) applicants. Across all 10 specialties, graduate degree holders matched at lower rates than non-holders. Among MD applicants, graduate degree holders matched at 92.57% compared with 94.12% for non-graduates (P < .0001), with specialty-specific differences ranging from 0.22% in Psychiatry to 4.61% in Anesthesiology; five specialties demonstrated statistically significant disparities. Among DO applicants, graduate degree holders matched at 84.54% compared with 88.64% for non-graduates (P < .0001), with specialty-specific differences ranging from 1.44% in Family Medicine to 10.48% in Obstetrics and Gynecology; five specialties also reached statistical significance. Conclusions The proportion of graduate degree holders in the residency match is increasing, and these applicants experience lower match rates than non-holders. These findings challenge the assumption that additional graduate education provides a competitive advantage and underscore the need for further research into the applicant-level factors contributing to these disparities.