Citations

Imaging is integral to detection and characterization of complications after prostate interventions, including vascular, infectious, urinary, and radiation-related complications, and facilitates timely diagnosis and management.

Objective We aimed to use machine learning (ML) models to investigate the impact of clinical, social and behavioural factors on 1-year progression from pre-diabetes to type 2 diabetes mellitus (DM). Design A retrospective cohort study. Setting A large health system including eight sites in southeast Michigan. Participants Adults with haemoglobin A1c (HbA1c) between 5.7% and 6.4% for two consecutive years between 1 January 2008 and 31 December 2023, and no prior history of type 2 DM or metformin use. Primary outcome measure New-onset type 2 DM (HbA1c ≥6.5%) in 1 year. Results Among 11 809 individuals, 815 (6.9%) progressed to type 2 DM within 1 year. CatBoost demonstrated the best performance (average area under the curve 0.78). Prior-year HbA1c was the most influential covariate (SHapley Additive exPlanations 1.02). Traditional metabolic factors (high-density lipoprotein, body mass index (BMI), white blood cell, age, gender, triglycerides) also contributed. Lastly, while inclusion of social and behavioural determinants of health (SBDH) did not significantly improve the overall model performance, depression emerged as the prominent SBDH covariate. Depression was a stronger predictor of diabetes progression in individuals with higher baseline BMI and lower baseline HbA1c. Conclusions Inclusion of social and behavioural covariates provided no incremental value for prediction of diabetes progression from pre-diabetes. However, machine learning revealed that depression may play a role in progression to type 2 DM.

Objectives To understand the trade-offs between different statistical modeling approaches, using real world data with small sub-populations, with rare exposures and increasingly rare outcomes. In particular, to compare adjusted regression, inverse probability weighting, and matching. Methods Data for these analyses came from the RADAR (N=1,134) and combined CNICS/JHHCC (N=14,434) cohorts. We estimated prevalence ratios (PRs) for self-reported use of specific substances comparing subpopulations (SP), SP-1 vs SP-3 and SP-2 vs SP-3, where SP-1 was the largest proportion (92% in RADAR, 81% in CNICS/JHHCC), SP2 was moderate proportion (18% in CNICS/JHHCC) and SP-3 was the smallest proportion (8% in RADAR, 1% in CNICS/JHHCC) of the population. We calculated PRs using 1) unadjusted relative risk regression (RR); and adjusted estimates controlling for age, race/ethnicity, study site, and year of interview using: 2) standard adjustment in RR; 3) stabilized inverse probability of treatment weighting (IPTW); and 4) matching with up to 3 matches from SP-1 or SP-2 per SP-3 participant. Results For most substances, all methods yielded consistent estimates. There were large weights in some of the IPTW analyses and in three cases these resulted in substantially divergent estimates. For the comparison between SP-1 and SP-3, the estimate for smoking was 1.3-fold greater in the matched analysis (PR=1.33, 95% CI: 1.02-1.75) than in IPTW (PR=1.03, 95% CI: 0.78-1.37 ATE and PR=1.05, 95% CI: 0.88-1.26 ATT). Even more extreme divergence in estimates was observed for differences between SP-2 and SP-3 with respect to methamphetamine/amphetamine, (IPTW-ATE: PR=1.51, 95% CI: 0.79-2.89; IPTW-ATT: PR=2.36, 95% CI: 1.36-4.12); vs Matching: PR=2.71, 95%CI: 1.47-4.99) and cocaine (IPTW-ATE: PR=1.15, 95% CI: 0.55-2.38; IPTW-ATT: PR=1.81, 95% CI: 1.03-3.18); vs Matching: PR=1.38, 95%CI: 0.76-2.53). Conclusion The combination of a rare exposure and a rare outcome can produce challenges for commonly used confounding adjustment strategies, and it is often best to compare different modeling approaches to gain greater insight.

Background: Penile inversion vaginoplasty (PIV) is a common gender-affirming procedure for transgender women, but validated, transgender-specific patient-reported outcomes remain limited. This study evaluated long-term outcomes after PIV using the Post-Affirming Surgery Form and Function Individual Reporting Measure (AFFIRM), a validated instrument assessing appearance, urologic, and gynecologic domains. Methods: We conducted a single-institution retrospective cohort with a cross-sectional, anonymous AFFIRM survey distributed in 2024. Demographics, perioperative outcomes, and complications were obtained by chart review. AFFIRM domain scores, reported on a 0–200 scale with lower scores indicating better outcomes, were analyzed descriptively. Results: Of 193 eligible patients who underwent PIV between 2017 and 2023, surveys were delivered to 186 patients, and 47.8% responded. Median age at surgery was 34.3 years (interquartile range 26.1–49.1), with a median follow-up time of 50.0 months. Most respondents reported high satisfaction with genital appearance, and 90% strongly agreed their anatomy aligned with gender identity. Clitoral sensation was reported by 93%, most commonly as pleasurable. Urologic symptoms were generally minimally bothersome; although 59% reported a misdirected urine stream, mean bother score was low (1.64 ± 1.77). Vaginal dryness and dyspareunia were reported by 43% and 44%, respectively, with 27% describing symptoms as bothersome. Major complications occurred in 13.9% and revision surgery in 34.2%, most commonly for stenosis or depth concerns (13.5%). Conclusions: AFFIRM captured meaningful, transgender-specific, long-term outcomes after PIV, complementing traditional surgical metrics and identifying opportunities to improve preoperative counseling, surgical refinement, and postoperative management of vaginal dryness and urinary symptoms.

Background: Platelet-rich plasma (PRP) is an emerging therapy that demonstrates potential benefits for knee osteoarthritis (OA); however, the accessibility of PRP remains limited, in part, because its use is not covered by insurance. Purpose: To identify factors contributing to health disparities in PRP treatment for knee OA using machine learning models. Study Design: Cross-sectional study; Level of evidence, 3. Methods: The authors collected data from electronic medical records at 2 upper Midwest medical centers (Mayo Clinic and Detroit Medical Center) from 2022 to 2023 encompassing demographic, socioeconomic, and clinical factors. Data collection encompassed age, sex, race, ethnicity, area deprivation index, marital status, income, rurality, insurance, employment, language, religion, treatment site, and region. Logistic regression and random forest models were applied to 3667 samples (80% training, 20% testing), comparing PRP recipients against a standard care group. Models were evaluated using 10-fold cross-validation to ensure robust performance assessment. Results: Logistic regression revealed that increased age, widowed status, lower income, rural residence, unemployment/disability, and Medicaid/Medicare insurance were associated with lower odds of receiving PRP. Upper-middle income, contracted insurance, and treatment at the Mayo-Arizona and Mayo-Florida sites were associated with higher odds. The model achieved areas under the curve of 0.83 (training set) and 0.82 (testing set). Random forest analysis identified distance to care, age, area deprivation index, income, and treatment site as top predictors, with areas under the curve of 0.92 (training) and 0.87 (testing). Conclusion: The current study demonstrated that both models discerned key barriers (income, distance to care, retirement status) and facilitators (regional differences) affecting PRP accessibility. These findings provide potential policy initiatives aimed at improving PRP access for underserved demographics, offering a quantitative blueprint to foster equitable access to regenerative therapies for knee OA.

Abstract Objectives This study aimed to characterize susceptibility profiles of both currently approved and investigational β-lactam agents against difficult-to-treat resistant Pseudomonas aeruginosa (DTR P. aeruginosa) clinical isolates, including carbapenemase-producing strains. Patients and methods A total of 502 consecutive DTR P. aeruginosa clinical isolates were collected from unique hospitalized patients between 2022 and 2024 across three tertiary care centres. Isolates originated from bloodstream, respiratory, urinary and intra-abdominal infections. Minimum inhibitory concentrations (MICs) for seven β-lactam agents were determined using triplicate reference broth microdilution. Susceptibility interpretations were based on CLSI criteria or, where applicable, investigational breakpoints. Whole-genome sequencing was performed to detect β-lactamase genes. Results Among the 502 isolates, cefepime-zidebactam exhibited the highest in vitro activity (100% susceptibility), followed by cefiderocol-xeruborbactam (98%), cefiderocol (95%), ceftolozane-tazobactam (90%), cefepime-taniborbactam (86%), ceftazidime-avibactam (85%), and imipenem-relebactam (41%). Notably, only 35% of isolates were susceptible to all seven agents. Carbapenemase genes were identified in 4% of isolates, including blaGES (n = 13), blaVIM (n = 7), blaKPC (n = 1) and blaIMP (n = 1). Among carbapenemase-producing isolates, cefepime-zidebactam retained activity against all isolates (100%), exceeding that of other approved β-lactam/β-lactamase inhibitor combinations (0%–24% susceptible), cefiderocol (76%), cefiderocol-xeruborbactam (86%) and cefepime-taniborbactam (81%). Conclusions While currently approved β-lactam agents retained activity against many DTR P. aeruginosa isolates, their performance was markedly compromised in the presence of carbapenemases, with the notable exceptions of cefepime-zidebactam and cefiderocol. Investigational β-lactam/β-lactamase inhibitor combinations exhibited consistently robust activity across resistance phenotypes, including carbapenemase-producing isolates, representing promising options for DTR P. aeruginosa infections.

Abstract Background Failure to rescue (FTR) is a key driver of postoperative mortality and reflects a hospital’s ability to recognize, escalate, and treat complications. Although FTR varies substantially between hospitals, the hospital characteristics that underpin this variation are inconsistently described. The aim of this study was to synthesize evidence on hospital-level factors associated with FTR after postoperative complications across surgical populations and health systems. Methods A systematic review of observational studies evaluating associations between hospital-level characteristics and FTR in surgical patients was undertaken. MEDLINE, EMBASE, and Scopus were systematically searched on 17 July 2024 and updated to 31 December 2025. Hospital factors were classified into structural, staffing, and system domains. Where three or more non-overlapping studies reported adjusted estimates in comparable formats, random-effects meta-analyses were performed; otherwise, findings were summarized narratively. Methodological quality of included studies was assessed using the ROBINS-I tool (version 2). Results A total of 111 studies encompassing over 137 million patients and 301 hospital factors were included. Meta-analyses demonstrated lower FTR rates in larger hospitals (odds ratio 0.85, 95% confidence interval 0.74 to 0.97), hospitals with greater intensive care unit capacity (odds ratio 0.80, 0.71 to 0.90), and teaching hospitals (odds ratio 0.88, 0.83 to 0.93). Better nursing resources were consistently associated with lower FTR, including patient-to-nurse ratios (odds ratio 1.07, 1.03 to 1.10), higher nurse education (odds ratio 0.95, 0.91 to 0.99), and more favourable work environments (odds ratio 0.93, 0.90 to 0.95). Safety-net hospital status was associated with higher FTR (odds ratio 1.22, 1.03 to 1.45). Substantial heterogeneity was observed across most analyses. Conclusion Hospital-level structural, staffing, and system characteristics are associated with variation in FTR. Postoperative mortality is closely linked to institutional capacity to detect and manage complications, underscoring the importance of adequate resourcing and system organization to improve surgical outcomes.

Abstract Background Cardiac magnetic resonance elastography (MRE) allows the non-invasive quantification of myocardial stiffness, but long-interval reproducibility data at 3.0 T single-frequency 140-Hz remain limited. Purpose To evaluate the short- and long-interval reproducibility of 3.0 T cardiac MRE for left ventricular (LV) myocardial stiffness across healthy volunteers and patients with conditions associated with elevated myocardial stiffness. Materials and Methods This prospective single-center study included 69 participants: 60 healthy volunteers and 9 with cardiovascular disease (6 with aortic stenosis and 3 with long-standing hypertension). All participants underwent baseline cardiac MRE (scanner: Signa Premier 3.0 T, GE Healthcare, driver: Resoundant), an immediate short-interval rescan (SIR) within 5 minutes, and a long-interval rescan (LIR) after approximately 1 month. Left ventricular myocardial stiffness and octahedral shear strain signal-to-noise ratio were measured independently by 2 readers. Reproducibility was assessed using Bland-Altman analysis, intraclass correlation coefficients (ICCs), within-subject coefficient of variation, standard error of measurement, and smallest detectable change at the 95% confidence (SDC95) level. Results Baseline LV myocardial stiffness was higher in the disease group than in healthy volunteers, 11.73 ± 1.01 kPa and 7.80 ± 0.70 kPa (mean ± SD; P < .001), respectively. Inter-reader agreement was excellent across all timepoints, with ICCs of 0.970 at baseline (95% CI, 0.953-0.982), 0.966 for SIR (95% CI, 0.945-0.979), and 0.962 for LIR (95% CI, 0.939-0.976). Within-reader scan-rescan reproducibility was also excellent. For Reader 1, stiffness ICC was 0.979 for the SIR (95% CI, 0.966-0.987) and 0.957 for the LIR (95% CI, 0.932-0.973), with SDC95 values of 0.616 kPa (95% CI, 0.528-0.741) and 0.869 kPa (95% CI, 0.744-1.044), respectively. Reader 2 showed excellent reproducibility, with ICCs ≤0.943. Conclusions 3D single-frequency 140-Hz cardiac MRE at 3.0 T provides excellent short- and long-interval reproducibility for LV myocardial stiffness quantification. The SDC95 values may help distinguish true longitudinal stiffness changes from measurement variability.