Clinical Epidemiology

Background Graft versus host disease (GVHD) remains a major determinant of morbidity and mortality following allogeneic hematopoietic stem cell transplantation (allo HSCT). Existing GVHD prediction models demonstrate modest discrimination and limited generalizability, and calibration drift across external populations is rarely characterized despite its essential role in the clinical interpretability of predicted probabilities. Objectives To develop and externally validate an explainable machine learning framework for predicting acute and chronic GVHD and associated overall survival in patients with acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), and myelodysplastic syndromes (MDS) undergoing allo HSCT, and to systematically characterize calibration across heterogeneous external validation cohorts to inform deployment requirements. Study Design The model was developed on three publicly available registry-derived datasets (N = 2,509) and externally validated across six independent cohorts (N = 14,788) comprising adult and pediatric allo HSCT recipients, including a regional Middle Eastern cohort (UAE and Jordan). A standardized preprocessing pipeline harmonized heterogeneous datasets. Gradient boosting models (CatBoost) were used for binary GVHD prediction; exploratory overall survival analysis used a Cox proportional hazards model with predicted acute GVHD risk as a covariate. Discrimination (AUROC with bootstrap 95% CI), calibration (logistic recalibration intercept and slope with analytical 95% CI), and feature importance (SHapley Additive exPlanations, SHAP) were assessed in training out-of-fold and all external cohorts. Results In internal validation, AUROC was 0.63 (95% CI 0.61-0.65) for acute GVHD and 0.72 (95% CI 0.70-0.74) for chronic GVHD. External validation demonstrated AUROC ranges of 0.51-0.57 (acute) and 0.54-0.64 (chronic), with consistent performance across disease subgroups despite substantial heterogeneity in transplant practices and feature availability. In exploratory survival analysis, the acute-GVHD-informed Cox model achieved a training-cohort C-index of 0.679 (95% CI 0.658-0.697); external C-indices ranged from 0.47-0.53. Calibration analysis identified systematic external risk overestimation (negative calibration intercept in 10 of 11 evaluable external cohort-target combinations) with heterogeneous slope drift requiring cohort-specific recalibration. Key predictors included recipient age, graft source, conditioning intensity, GVHD prophylaxis, and HLA match ratio. Conclusions An explainable, externally validated GVHD prediction framework was developed using heterogeneous registry-derived datasets, with systematic characterization of calibration drift across multiple external cohorts, an analysis rarely reported in prior GVHD prediction literature. Predictive performance was modest for acute GVHD and moderate for chronic GVHD, constrained by missing immunobiological variables and incomplete HLA characterization. Per-cohort recalibration is required before clinical deployment, with prospective validation and benchmarking against established GVHD risk scores identified as priority next steps.

Background The incidence of post-operative periprosthetic femoral fractures (POPFFs) is increasing. However, specific clinical guidance relating to patient management does not exist, resulting in variations in care and outcomes. This study aimed to elicit and synthesise expert knowledge in POPFF service delivery and explore views on variations in service provision and the factors influencing these. Methods Semi-structured interviews were undertaken with healthcare professionals with expertise in POPFF care from England and Wales to explore current practices, challenges, service variations and perceived future opportunities. Participants were identified through specialist research and clinical networks for POPFF and hip fracture care, authors of key publications on the subject, national leads for POPFF/hip fracture networks, and research team contacts. Interviews were analysed using thematic analysis. Results Ten interviews were undertaken with experts in POPFF services across a range of professional roles. Four themes were identified: conceptualisation of POPFF (by different professional groups and in different service settings) and understanding of POPFF patient needs; sources of variation in management and care of POPFF patients; service model rationales, advantages and disadvantages; and potential strategies to improve POPFF care. Conclusion When designing POPFF services, we suggest that four key areas need consideration: the extent to which POPFF patients are a distinct group with particular care needs; the necessity for and consequences of patient transfer between wards and hospitals; the resourcing of extensive multidisciplinary support for POPFF patients; and the need for national initiatives to encourage service developments. These findings should form the basis of future clinical guidance. Sensitivity to contextual factors driving variation in services is needed to ultimately improve care for POPFF patients.

Chronic postsurgical pain (CPSP) prevalence after total knee arthroplasty (TKA) is >20%. Circulating immune biomarkers are known factors of musculoskeletal pain but poorly understood as CPSP predictors. This prospective, longitudinal study of 203 patients s/p TKA tested presurgical plasma biomarkers associated with 6-month CPSP, using promising approaches from geriatrics biomarker research: expected recovery differential (ERD; resilience outcome) and penalized, machine-learning regularization modeling (elastic net and LASSO regression). Forty-nine presurgical candidate biomarkers were considered. CPSP was operationalized using ERDs built around PROMIS pain intensity and pain interference, which quantified the difference between observed and expected recovery after accounting for demographic, comorbidity, reserve, and perioperative factors. Plasma/ERDs from ~130 patients revealed 13 biomarkers with the highest selection stability criteria, and either positive or negative (+/-) associations with ERDs. Interleukin (IL) 5 (-) and Lipopolysaccharide-Binding Protein (LBP; +) were associated with both ERDs. Unique associations with pain intensity ERD included Cytomegalovirus-Specific IgG Negative (CMV IGg-; -), Macrophage Inflammatory Protein-1 Beta (MIP1b; -), IL12p70 (-, Cluster of Differentiation 30 (sCD30;-), Interferon alpha 2a (IFN2a;+), and Leukemia Inhibitory Factor (LIF;+). Unique associations with pain interference ERD included Lipopolysaccharide (LPS;-), Activin A (-), IL8 (-), Serum Amyloid A (SAA;-), and IL7 (+). Protein-protein interaction analyses and topology motifs suggest a centralized network with higher-than-expected connectivity, involving IL5, IL7, IL8, MIP1{beta}, and IFN2a, among others. This study proposes rigorous yet feasible approaches to expedite pain biomarker research, and introduces presurgical biomarkers t0 consider in future TKA-CPSP biosignature derivation.

Background Annually, nearly 2 million hip, knee, and spinal inpatient surgeries are performed in Canada and the US for osteoarthritis (OA), costing over $37 billion in hospital expenditures. However, 15-30% of patients experience limited or no improvement, resulting in poor value for money. This study evaluated the one-year cost-utility of joint and spine procedures for OA by comparing non-responders to responders, considering various responder definitions. Methods Individual micro-costing data were collected for 1,175 elective hip, knee, and spine patients enrolled in the Longitudinal Evaluation in the Arthritis Program - Osteoarthritis (LEAP-OA) between 2014 and 2018. Quality-adjusted life years (QALYs) were derived using the SF-6D utility index. One-year incremental cost-utility ratios (ICURs) were calculated from the hospital perspective. Results Responder rates varied by definition, ranging from 78%-94% for hip replacements, 64%-90% for knee replacements, 60%-64% for spine fusions, and 50%-68% for spine decompressions. Corresponding ICURs were: $45,956-$51,773/QALY for responders versus $108,593-$485,762/QALY for non-responders for hip replacements; $54,831-$71,151/QALY for responders versus $200,486-$1,203,596/QALY for non-responders for knee replacements; $65,980-$74,422/QALY for responders versus $262,039-$729,686/QALY for non-responders for spine fusions; and $29,947-$42,168/QALY for responders versus $63,195-$662,586/QALY for non-responders for spine decompressions. Conclusions While surgical response rates were highly dependent on the responder definition, ICURs for non-responders were significantly higher than those for responders across all definitions. Beyond the negative impact on patients, there is a compelling economic argument for investment in improved pre-operative identification of patients at risk of surgical non-response. Such efforts could enable more personalized, value-based care pathways and reduce the provision of low-value surgical interventions.

Introduction: Acute compartment syndrome (ACS) is a limb-threatening complication of extremity trauma that requires timely diagnosis to prevent irreversible muscle and nerve injury. Current diagnostic methods are invasive, intermittent, and operator-dependent. We evaluated the feasibility of a novel, Bluetooth-enabled electrical impedance myography (EIM) device (mAlert, Myolex, Inc., Brookline, MA, USA) for continuous, noninvasive detection of ACS-related tissue changes. Methods: Ten Yorkshire swine underwent anterior tibial compartment monitoring using three ACS models: albumin infusion (ALB, n=3), femoral artery and vein ligation (LIG, n=3), and combined albumin infusion plus ligation (ALB+LIG, n=4). Resistance (R), reactance (X), and phase (P) were measured every minute across 1 to 199 kHz alongside continuous intra-compartmental pressure (ICP) monitoring. Group differences in normalized impedance trends were evaluated using the Kruskal Wallis test with Dunn post hoc correction. As a proof-of-concept human study, nine healthy volunteers wore the device for up to five days to assess electrode durability and signal stability. Tissue ischemia was validated using pimonidazole immunohistochemistry. Results: ALB infusion produced progressive, frequency-dependent decreases in R, X, and P, whereas LIG produced consistent increases in R and X across frequencies. The ALB+LIG model generated mixed responses, reflecting the competing effects of edema and ischemia. Normalized phase slopes differed significantly among groups (H=6.14, p=0.046), with post hoc testing showing significant divergence between the ALB and LIG models (p=0.041). Control limbs remained stable throughout monitoring. Pimonidazole staining confirmed hypoxic injury in the intervention limb. In the human pilot study, three participants completed five days of monitoring, demonstrating sustained signal acquisition, while electrode degradation limited data collection in the remaining participants. Conclusions: This preliminary feasibility study demonstrates that wearable EIM can continuously detect model-specific physiological changes associated with ACS in a large-animal model. These findings support further development and clinical evaluation of wearable EIM as a non-invasive monitoring technology for early ACS detection in trauma patients.

Rationale. Racial disparities in outcomes among patients with acute respiratory failure are well-described, but the contributions of clinicians to these disparities have not been evaluated. Objectives. Among mechanically ventilated patients, we evaluated racial disparities in severity of illness trajectories and adapted value-added modeling to quantify nurse and physician relationships with these disparities. Methods. In a retrospective cohort of mechanically ventilated patients across five hospitals between 2018 and 2022, we used generalized estimating equations to model the change in Laboratory-based Acute Physiology Score version 2 (LAPS) from the start to end of intensive care unit admission ({Delta}LAPS). Consistent with value-added modeling, we randomly allocated the cohort into development and testing partitions, and fit separate multiple linear regression models of {Delta}LAPS using concurrent nurse and physician assignments (determined at 4-hour intervals), patient race, and clinician-race interaction terms as fixed effects. Clinician-specific and clinician-race interaction coefficients were extracted to determine race-specific value-add for each clinician. We defined the race-contextual value-add difference (RCVAD) as a clinician-level measurement of the difference in that clinician's value-add between Black and White patients in their care; a positive RCVAD indicates a more favorable severity of illness trajectory for Black relative to White patients and vice versa. Measurement and Main Results. Among 6,555 distinct patients, 7,247 clinical encounters, 405 nurses, and 70 physicians, Black patients accounted for 2,926 (40%) encounters. Overall, Black patients had significantly less improvement in {Delta}LAPS than White patients (difference in LAPS decline = 2.26 [0.23, 4.29], p=0.029). In the development partition, median nurse RCVAD was -0.10 (interquartile range [IQR]: -1.17, 1.14) with 191 (47%) nurses having a positive RCVAD; median physician RCVAD was -0.18 (IQR: -1.34, 0.56) with 29 (41%) having a positive RCVAD. Conclusions. Black mechanically ventilated patients experience less improvement in severity of illness during intensive care unit admission than White patients. While the majority of physicians and nurses were associated with disparities-exacerbating illness trajectories, many other clinicians were associated with disparities-mitigating trajectories. Future work to understand practices associated with disparities-exacerbating and disparities-mitigating care profiles could inform interventions to reduce disparities overall.

Abstract Background:Sickle cell disease (SCD) is concentrated in sub-Saharan Africa, where delivery of guideline-referenced care remains challenging. Current evaluation approaches rely largely on access indicators and clinical outcomes, which do not directly measure care delivery. We developed the Care Delivery Gap (CDG) framework, a patient-reported approach for identifying care-process omissions, and conducted a proof-of-concept study to assess feasibility and explore variation across income strata. Methods: We conducted a cross-sectional framework-development study involving a proof-of-concept sample of 52 individuals with SCD or caregivers recruited through clinics and moderated SCD communities across Africa, North America, and Europe between June 2025 and March 2026. The CDG framework assessed patient-reported omissions in specialist involvement, follow-up continuity, cardiovascular screening, and biochemical surveillance. Analyses were descriptive. Results: Substantial multi-domain care-process omissions were identified despite high reported healthcare engagement. Across geographic income strata, cardiovascular screening was reported by 4/35 (11%) LMIC versus 16/17 (94%) HIC participants, and regular follow-up within the preceding 12 months by 14/35 (40%) versus 16/17 (94%), respectively. High CDG scores, representing 1 omissions across three or four domains, occurred in 20/35 (57%) LMIC compared with 1/17 (6%) HIC participants. Similar disparities were observed across specialist review and vitamin B12 surveillance domains. Conclusion: A structured patient-reported framework identified multi-domain omissions in guideline-referenced SCD care, including among individuals reporting healthcare access. The divergence between access indicators and reported care delivery suggests that service contact alone may not reflect care quality. The framework provides a feasible foundation for future process-level quality measurement in high-burden settings.

Background and Aims: Cardiovascular risk scores guide primary prevention, but their comparative performance remains uncertain. We externally validated 16 established and contemporary cardiovascular risk-prediction models in a common primary-prevention evaluation framework. Methods: UK Biobank participants free from cardiovascular disease and cancer at baseline were included. 16 models, corresponding to 19 configurations, were implemented as published and evaluated against a harmonized incident CVD endpoint. Performance at 5 and 10 years was assessed using discrimination, calibration, Brier score, decision curve analysis, and TRIPOD+AI reporting quality. Results: Among 438,640 participants, 45,003 incident cardiovascular events occurred over a median follow-up of 13.5 years. Ten-year area under the curve ranged from 0.668 for QRISK3 to 0.734 for PREDICT, and C-index from 0.655 to 0.717. Calibration varied substantially: PROCAM, Framingham, ASSIGN, and QRISK1 overestimated risk, whereas PREVENT, PREDICT, SCORE, SCORE2, SCORE2-OP, and China-PAR generally underestimated risk. QRISK2 showed the best calibration, while PREVENT had the lowest Brier score. At higher treatment thresholds, net benefit diverged, with PREVENT and PCE performing most consistently. Composite assessment favored PREVENT, QRISK2, PREDICT, PCE, and northern China-PAR variants. Conclusions: Direct application of cardiovascular risk scores across populations can produce clinically important differences in calibration and net benefit. Model selection for primary prevention should require external validation, local recalibration, and assessment of clinical utility, rather than reliance on discrimination alone. PREVENT, QRISK2, PREDICT, PCE, and northern China-PAR variants showed the most balanced performance in this cohort.

Purpose To explore patient and caregiver perspectives on factors influencing mobility during hospitalization after hip fracture surgery, and how these are experienced and negotiated in everyday hospital practice. Materials and methods A qualitative interview study informed by a hermeneutic-phenomenological perspective was conducted in a hospital setting in Denmark. Using purposive sampling with maximum variation, ten patients and nine caregivers were interviewed during hospitalization. Data were analyzed using reflexive thematic analysis following Braun and Clarke. Results Five interrelated themes were identified; (1) Body and mind in transition; (2) Communication as a prerequisite for safety and mobility; (3) Structural barriers and ambiguities in responsibility; (4) The physical environment and ward culture; and (5) Mobility as preparation for life after discharge. Across themes, mobility emerged as a socially shaped and negotiated practice through everyday interactions, communication, organizational routines, and situational support during hospitalization. Conclusions Mobility during hospitalization after hip fracture surgery emerged as a context-dependent and socially shaped practice rather than a purely physical task. These findings suggest that rehabilitation during hospitalization may need to attend not only to mobility prescription, but also to relational, communicative, and contextual aspects of everyday ward routines that shape patients' confidence and participation.

Background: Endovenous techniques are considered the gold standard for treating great saphenous vein (GSV) insufficiency, but access remains limited in low- and middle-income countries. In such contexts, simplified conventional surgeries may represent viable alternatives. This study aimed to compare outcomes of isolated GSV stripping with conventional surgery (stripping plus varicose vein resection) in patients with varicose veins (VV) associated with GSV insufficiency. Methods: A prospective interventional study was conducted including 34 patients with VV (CEAP C2-C6), divided into two groups: Conventional (C, n=17) and Isolated Saphenectomy (IS, n=17). Quality of life was assessed preoperatively and at 2 and 6 months postoperatively using the Venous Clinical Severity Score (VCSS) and VEINES-QoL/Sym questionnaires. Varicose vein evolution in the IS group was quantified using a standardized visual scoring system. Statistical analyses included Students t-test, chi-square, and generalized estimating equations (p[&le;]0.05). Results: Both groups were demographically comparable. Surgical treatment significantly improved VCSS and VEINES scores in both groups (p<0.005), with no intergroup difference at 6 months. In the IS group, the mean reduction in visible VV was 46% (range 20-90%). CEAP classification improved in both groups, with migration toward less severe categories postoperatively. No major complications were reported. Conclusion: Isolated GSV stripping yields comparable short- and mid-term improvements in symptoms and quality of life to conventional surgery, while reducing operative extent. In resource-limited settings, this abbreviated technique may expand access to treatment for VV, improving patient outcomes and reducing healthcare costs without compromising clinical efficacy.

Background Hypercapnia may indicate a primary ventilatory syndrome, a complication of another illness, or an epiphenomenon of severe disease. The presenting context of hypercapnia is poorly quantified, limiting clinical interpretation and synthesis of epidemiologic studies. Methods We performed a retrospective cross-sectional study of Medical Information Mart for Intensive Care IV (MIMIC-IV) hospital admissions linked to an emergency department (ED) presentation from 2011 through 2019. Admissions were included if the triage chief complaint was not missing and at least one prespecified criterion for hypercapnia was met: an International Classification of Diseases (ICD) code for hypercapnic respiratory failure or obesity hypoventilation syndrome, arterial blood gas (ABG) PCO2 45 mmHg, venous blood gas (VBG) PCO2 50 mmHg, or indeterminate-source blood gas PCO2 50 mmHg. Triage chief-complaint text was classified by natural language processing (NLP) into 17 National Hospital Ambulatory Medical Care Survey reason-for-visit (RFV) categories using a multi-label framework. Primary analyses estimated admission-level RFV category prevalences; secondary analyses compared distributions by overlapping ascertainment indicator, age, and acidemia. Results The total cohort included 11,941 admissions: 1,542 (12.9%) met both blood-gas and ICD-code criteria, 9,958 (83.4%) met blood-gas criteria only, and 441 (3.7%) met ICD-code criteria only. Median age at admission was 68 years (IQR 56-78), and 6,423 admissions (53.8%) were for male patients. Respiratory RFV categories were most prevalent (30.2%), followed by administrative reasons (17.5%), digestive symptoms (14.0%), injuries and adverse effects (14.0%), and nervous-system symptoms (13.8%); categories were not mutually exclusive. Respiratory categories were more common in ICD-positive admissions (50.2%) than in VBG-defined (36.3%) or ABG-defined admissions (27.3%). Injuries and adverse effects were most prevalent among admissions for patients aged 18-39 years (34.4%), whereas respiratory categories increased from 13.7% among admissions for patients aged 18-39 years to 36.5% among admissions for patients aged 80 years. NLP-derived classifications showed mean set-F1 of 0.84 against adjudicated clinician labels in the full annotated benchmark sample. Conclusions Among ED-linked admissions with hypercapnia by diagnosis code, blood gas, or both, respiratory complaints were the most common chief-complaint category but represented fewer than one-third of admissions. Presentation context should be incorporated when defining, comparing, and interpreting hypercapnia cohorts, particularly those ascertained by blood-gas criteria.

Background: Cardiovascular disease (CVD), cardiometabolic and neurocognitive conditions share risk factors and frequently co-occur. We evaluated whether four established CVD risk prediction models (QRISK3, PCE, SCORE2, SCORE2-OP) can be repurposed to predict 10-year risk of these conditions and their co-occurrence with CVD. Methods: The models were recalibrated using 20% of the UK Biobank (UKB) and evaluated in the remaining 80%. We performed external validation using data from Clinical Practice Research Datalink (CPRD) Aurum, assessing model discrimination (c-statistics) and calibration (intercept and slope). We used permuted feature importance to determine the influence of each individual predictor in the models. Results: Depending on the model, the c-statistics for incident CVD ranged from 0.71 to 0.74 in the UKB test set (16,137 events). Discrimination was equal to or higher than CVD when evaluated against non-traditional CVD outcomes: 0.74 to 0.77 for heart failure (3,471 events), 0.72 to 0.73 for atrial fibrillation (9,213 events), 0.73 to 0.75 for peripheral arterial disease (1,927 events) and 0.80 to 0.82 for abdominal aortic aneurysm (595 events). For the multimorbidity endpoints, model discrimination ranged from 0.74 for the composite of CVD and T2DM (SCORE2-OP) to 0.83 for the composite of CVD and dementia or Parkinson's disease (QRISK3). When considering the onset of any cardiovascular, cardiometabolic, or neurocognitive outcome discrimination ranged from 0.71 to 0.72. The repurposed models slightly underestimated the predicted risk in the CPRD compared to the UKB: average difference in calibration intercept was at most -0.64. After age and sex, smoking status and systolic blood pressure contributed most to model predictions. Conclusions: Repurposed CVD models can be used to identify 10-year risk of many CVD-related conditions and their multimorbidity. These may be used to support risk-based approaches to prevention and screening. The repurposed models have been made available at: https://repurposed-cvd-risk-models.shinyapps.io/cvd_cmd_dementia_app/ Keywords: Risk prediction; cardiovascular disease; cardiometabolic disease; dementia; disease prevention.

Importance: Adverse drug events in older adults are a substantial public health burden, yet spontaneous reporting systems detect them poorly owing to underreporting and the lack of a defined population. These limitations are of particular concern for older adults, who are underrepresented in pre-approval trials yet at elevated risk owing to polypharmacy, multimorbidity, and age-related changes in drug metabolism. Objective: To develop and apply an active, claims-based pharmacovigilance framework using sequential target trial emulation to detect adverse drug event signals in older adults, with atorvastatin as the initial application. Methods: Using Medicare fee-for-service claims (2017-2019), we studied statin-naive beneficiaries aged 65 years or older following myocardial or cerebral infarction. We emulated up to 14 daily sequential trials from the discharge date, classifying patients as initiating atorvastatin (A1), initiating a different medication (A2), or no new medication (A0); the primary contrast was A1 versus A2. For each trial, incident outcomes were ascertained and classified into 552 outcomes based on the Clinical Classifications Software Refined categories. Per-protocol effects were estimated over a 6-month follow-up period using Fine-Gray regression models weighted by the inverse probability of treatment and censoring, treating death as a competing risk, with the false discovery rate controlled via the Benjamini-Hochberg procedure. A signal was declared when the q-value was 0.10 or lower and the subdistribution hazard ratio (sHR) was 1.20 or greater in any prespecified analytic stratum (sensitivity analyses used thresholds of q 0.20 or lower and sHR 1.20 or greater). Results: Of 70,130 eligible patients, 39,948 initiated atorvastatin (A1) and 19,182 initiated another new medication (A2); after weighting, baseline characteristics were closely balanced. After excluding outcomes with sparse cell counts, 295 outcomes were analyzed; five met the primary signal detection criteria: valve disorders (sHR 1.71, 1.20 to 2.43); sprains and strains (sHR 1.79, 1.26 to 2.54); general sensation/perception symptoms (sHR 1.23, 95 percent CI 1.11 to 1.36); abnormal findings without diagnosis (sHR 1.55, 1.18 to 2.05); and prediabetes (sHR 1.71, 1.24 to 2.36). In the sensitivity analysis, we additionally detected posthemorrhagic anemia, hemorrhagic stroke, varicose veins, and other circulatory and skin conditions. Conclusions: An active, claims-based framework using sequential target trial emulation detected both expected and previously unrecognized adverse drug event signals following atorvastatin initiation in older adults, offering a systematic alternative to passive surveillance that can be extended to other commonly prescribed medications.

Progestin-IUD use was more frequent among IUA cases (29.9%) than polyp (3.4%) or infertile (11.1%) comparison groups. Compared to infertile comparators, any prior progestin-IUD use was independently associated with IUA (aOR 3.12; 95% CI 2.01, 4.85). There was a duration-response pattern: use of 5 years or less was modestly associated with IUA case status (aOR 1.99; 1.09, 3.64), whereas use >5 years conferred more than a seven-fold increase (aOR 7.26; 3.27, 16.11). The association persisted among surgically naive women (aOR 3.98; 2.44, 6.48) and was concentrated in those who were nulliparous, where use beyond five years conferred an approximately twelve-fold increase in odds (aOR 12.74; 5.25, 30.92). Progestin-IUD use was less frequent in polyp controls relative to IUA and infertile comparators, suggesting a possible role for progestin exposure in preventing endometrial polyp formation. The case control design does not allow for estimation of absolute risk for an individual and cannot inform causation. Further prospective studies are needed to better assess the relationship between progestin-IUD's, particularly when used beyond five years, and adverse fertility outcomes.

Background: Transthyretin amyloidosis cardiomyopathy (ATTR-CM) is an infiltrative cardiomyopathy and an increasingly recognized cause of heart failure. With improved survival from disease-modifying therapies, an increasing number of patients are presenting for surgery and may be at increased risk of adverse postoperative outcomes. This study reports outcomes of ATTR-CM patients undergoing surgery and evaluates the utility of the Revised Cardiac Risk Index (RCRI), a perioperative risk tool. Methods: A total of 145 ATTR-CM patients were included, among which 51 patients underwent at least one eligible surgical procedure. Preoperative risk was assessed using the RCRI, analyzed both as a categorical and as a dichotomized ({greater than or equal to}3 vs <3) variable. Postoperative outcomes included unplanned hospital admission, length of stay (LOS), prolonged hospitalization (>48 hours), and major adverse cardiac events. Models were adjusted for frailty (Clinical Frailty Scale {greater than or equal to}5) and major surgery, using multivariable, ordinal, and Firth penalized logistic regression analyses. Results: Patients were predominantly male (86%) with a mean age of 76 {plus minus} 9 years, and 61% were frail. Higher RCRI scores were associated with unplanned postoperative hospital admission (RCRI {greater than or equal to}3: adjusted OR 48.9, 95% CI 4.8-502.2) and longer LOS (RCRI {greater than or equal to}3: adjusted OR 40.7, 95% CI 4.3-382.8). RCRI {greater than or equal to}3 was also associated with prolonged hospitalization (>48 hours) in Firth penalized logistic regression, whereas frailty was not independently associated. Conclusions: In a real-world ATTR-CM cohort undergoing major non-cardiac surgery, the overall risk of adverse outcomes was low, and higher RCRI scores were associated with increased postoperative hospital admission and longer LOS, including hospitalization exceeding 48 hours. The RCRI retains prognostic utility in this high-risk cohort and may support peri-operative risk stratification.

Background: The PREVENT (Predicting Risk of CVD EVENTs) equations estimate the risk of incident cardiovascular disease (CVD) in primary prevention patients. We hypothesized that risk factors incorporated in the equations may be relevant to prognosis in heart failure (HF) and investigated the association between estimated CVD risk and clinical outcomes in patients with preserved ejection fraction (HFpEF). Methods: We estimated the 10-year CVD risk using the PREVENT equations in 278 patients hospitalized for acutely decompensated HFpEF (median 75 years, 51.4% male). We divided them into four groups according to the quartiles of estimated CVD risk and followed them to observe major adverse cardiovascular events (MACE), a composite of all-cause death, HF hospitalization, and stroke. Results: MACE occurred in 125 patients (45.0%) over a median follow-up of 1,050 days. The estimated CVD risk classification was an independent predictor for MACE (p=0.02) in the multivariable Cox proportional hazard model. There was a difference in MACE-free survival across the four quartile groups (p<0.001 by log-rank test), and the lowest CVD risk group had significantly lower MACE incidence than other groups. The estimated CVD risk provided incremental prognostic value beyond N-terminal pro-B type natriuretic peptide (C-index: 0.626 vs, P=0.009). The predictive value of the estimated CVD risk for MACE at 1 year was comparable to that of the MAGGIC score (AUC 0.676 vs. 0.639, p=0.42). Conclusions: The 10-year CVD risk estimated by the PREVENT equations had a moderate predictive value for MACE in patients hospitalized for HFpEF.

Background: Colorectal cancer (CRC) disproportionately affects non-Hispanic Black (NHB) Americans compared to Non-Hispanic White (NHW), with more cases arising before age 50. Racial disparities in outcomes reflect complex interactions among healthcare access, socioeconomic factors, and structural racism, yet analyses linking individual-level data for these factors to survival remain limited. Methods: We examined overall and CRC-specific survival among NHB and NHW patients diagnosed between 2013 and 2022 enrolled in the Disparities and Cancer Epidemiology (DANCE) cohort, a population-based study of CRC in metropolitan Detroit and Louisiana. Multivariable Cox regression and competing-risks models were used to assess the roles of race, age of onset, neighborhood deprivation, and stage on survival outcomes. Results: Among 1,019 CRC cases (57% NHB, 43% NHW), NHB patients were more likely to reside in high-deprivation neighborhoods, report lower household incomes, and present with right-sided tumors, though stage at diagnosis did not differ by race. In multivariable analysis, stage was the strongest predictor of survival, while neighborhood deprivation (per 10-unit ADI increase: HR = 1.14) was independently associated with worse survival; NHB race was not significantly associated with survival after adjustment. Younger age at diagnosis was associated with a survival advantage in regional-stage disease but paradoxically with worse survival in distant-stage disease, and higher deprivation predicted worse survival in both local and distant but not regional stage. Conclusion: Our study shows that socioeconomic factors, as measured by ADI and household income, accounts for some, but not all, of the disparities in survival between NHB and NHW CRC cases.

Background: Postoperative atrial fibrillation (POAF) is a frequent complication following coronary artery bypass grafting (CABG) and is associated with increased acute morbidity and resource utilization. However, its independent role in driving post-discharge adverse events in contemporary practice remains debated. Objective: To evaluate the association between POAF and short-term outcomes after CABG, and to utilize empirical Bayesian risk updating to stratify 90-day post-discharge vulnerabilities. Methods: A retrospective cohort analysis of 4,684 adult patients who underwent isolated CABG in Florida between January 1, 2021, and June 30, 2024, was conducted, excluding those with documented preoperative AFib. We employed multivariable negative binomial and logistic regression models to assess length of stay (LOS), discharge disposition, 90-day readmission, and 90-day composite complications. Additionally, a Bayesian Beta-Binomial conjugate model with an objective Jeffreys Prior was utilized to estimate the posterior probabilities of adverse outcomes across key clinical phenotypes. Results: POAF occurred in 355 patients (7.58%). Multivariable analysis demonstrated a 30% relative increase in expected LOS (IRR 1.30, 95% CI [1.23 - 1.36], P < .001) and 33% higher odds of facility discharge (OR 1.33, 95% CI [1.03 - 1.72], P = .030) for patients with POAF. However, POAF was not independently associated with 90-day readmission (OR 1.25, P = .063) or composite complications (OR 1.20, P = .118). Chronic heart failure (CHF) emerged as the dominant predictor. Bayesian risk updating revealed that while the baseline posterior probability for a 90-day complication was 27.2%, the synergistic presence of both POAF and CHF radically shifted this posterior risk to 42.6% (Probability of Direction > 0.999 vs. baseline). Conclusions: POAF prolongs hospitalization and drives non-home discharges, but it does not independently dictate 90-day morbidity. Bayesian stratification demonstrates that post-discharge outcomes are predominantly driven by underlying chronic conditions. Effective reduction of readmissions requires robust transition-of-care frameworks, empowering primary care clinicians to aggressively optimize heart failure and metabolic disease rather than focusing solely on the acute surgical arrhythmic event.

Background Cardiovascular diseases (CVD) are the leading cause of death worldwide, and their epidemiology is correlated with genetic predisposition, exposure to risk factors, sex, age, access to medical care, and other sociodemographic characteristics. Brazil is a developing country with a vast territory, which leads to structural inequalities. Estimates of CVD in Brazil, in its regions, and in its population are poorly evaluated and analysed. Methods We obtained CVD-related data from the Brazilian Unified Health System (SUS) and analysed mortality and morbidity from 1996 to 2023 by sex, race/ethnicity, age, and region. We calculated the risk of death from the most prevalent diseases, the average length of hospital stay, and the costs associated with heart transplantation. Findings In Brazil, acute myocardial infarction was the pathology that led to the highest number of deaths across all variables analysed during the evaluated period. Other CVD were also related to causes of death and morbidity, such as hypertensive diseases and heart failure. Interpretation Brazil presents a serious challenge to the public health system due to the high number of deaths and the progressive mortality rate. This study represents a fundamental contribution to the basis for formulating public health policies aimed at reducing the growing impact associated with these diseases. Funding CNPq, CAPES, FAPEMIG, INCT

Background: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome comprising multiple pathophysiological phenotypes. HFpEF trials have largely enrolled diverse populations and reported average treatment effects, consistently yielding neutral results that may obscure drug-specific benefits within distinct subgroups. To address this issue, we employ an interaction-based that incorporates treatment-by-variable interactions to uncover drug-specific responses. Methods: We leveraged four HFpEF clinical trials (TOPCAT, RELAX, NEAT-HFpEF, INDIE-HFpEF) and developed a framework comprising two complementary approaches. The first employed a prognostic responder model to evaluate whether conventional responder definitions reflect treatment-specific benefit or instead capture favorable clinical trajectories common to both treatment and placebo groups. The second used an interaction-based individual treatment effect (ITE) modeling to identify baseline variables that modify therapy effect, distinguishing drug-specific response from prognostic phenotypes. Results: Although the prognostic responder model demonstrated good discrimination, further analisys suggested it primarily captured a prognostic signal associated with favorable clinical trajectories common to both treatment and placebo arms. In contrast, the ITE model identified distinct, drug-specific effect modifiers across trials (cardiorenal-inflammatory for spironolactone (TOPCAT), NO-mediated anti-inflammatory for isosorbide mononitrate (NEAT-HFpEF), afterload-reducing for inorganic nitrite (INDIE-HFpEF), and anti-volume-overload for sildenafil (RELAX). Each ITE model demonstrated significance only within its own trial suggesting drug-specific signal. Conclusions: The proposed method identifies mechanism-specific effect modifiers, and uncovers clinically meaningful heterogeneity in treatment response, which is not captured by conventional MCID-based approaches. Although exploratory, these findings support phenotype-guided therapy in HFpEF and argue for phenotype-informed trial design to enhance treatment-effect detection and therapy targeting.