Krishnan Warrior

Background: Postoperative atrial arrhythmia (POAA) is common after lung transplant, but data on its implications and management are limited. This study assessed POAA incidence and timing, its association with mortality and rehospitalizations, and outcomes related to postoperative beta‐blocker use. Methods: We retrospectively studied 233 adult lung transplant patients at Northwestern Memorial Hospital (2014–2024) without prior atrial arrhythmia. POAA, defined as atrial fibrillation or flutter, was confirmed by ECG or ambulatory monitoring. Multivariable logistic and Cox regression models evaluated predictors and outcomes, adjusting for covariates. Results: POAA occurred in 69/233 patients (29.6%) and was associated with higher mortality (HR3.09, 95%CI [1.57–6.08]). Among these, 18/69 (26.1%) developed POAA after the index hospitalization at median 216 days post‐transplant, also associated with higher mortality (HR4.37, 95%CI [1.90–10.06]). Additionally, 10/69 (14.5%) required emergency visits or hospitalization specifically for arrhythmia management, and 66.6% underwent additional rhythm control (2.9% cardioversion, 46.4% anti‐arrhythmic drug, 17.4% both). Postoperative beta‐blocker use was associated with 73% less POAA (HR0.27, 95%CI [0.09–0.80]). Conclusion: POAA was common and clinically significant after lung transplant, associated with substantially higher adjusted mortality even when occurring after index hospitalization. We report for the first time that POAA was frequently associated with emergency visits or rehospitalization for arrhythmia, highlighting its clinical burden well beyond the perioperative period. Postoperative beta‐blocker use was associated with markedly less POAA, a novel finding suggesting a potential prophylactic role. Overall, these findings challenge the traditional view of POAA as benign and highlight the need for tailored, evidence‐based guidelines in this high‐risk population.

Background: Interstitial lung disease (ILD) affects > 40% of patients with systemic sclerosis (SSc/scleroderma) and is the leading cause of disease-related mortality. Although therapies may slow progression, outcomes remain poor, partly because ILD is often detected after irreversible lung injury has occurred. Although chest computed tomography (CT) is a sensitive tool for ILD detection and is recommended at SSc diagnosis, it is oftentimes not performed and even less often performed serially. We sought to develop tools to predict ILD and mortality in patients with SSc using data routinely available in the electronic health record (EHR) to inform medical decision-making. Methods: We analyzed longitudinal EHR data from two SSc cohorts: Northwestern University (1,169 participants; derivation cohort) and Yale University (376 participants; validation cohort). We identified clinical features from existing cohort-linked EHR queries composing a convenience sample of data from participants spanning decades rather than employing a single unified data collection effort. Three ILD experts independently reviewed CT reports and classified each as having or lacking ILD. To explore derivation cohort data structure, patients with > =3 forced vital capacity (FVC) results available were identified and stratified according to prevalent or absent ILD. Using unsupervised trajectory-based clustering exploratory analyses, we determined standardized patterns across groups. ML models were then developed using clinical EHR data as predictor variables and prevalent ILD and all-cause mortality as outcome variables. Model performance was assessed using area under the receiver operating characteristic curve (AUC). Results: Seventy-four clinical features with low missingness, including demographic, vital sign, laboratory, and pulmonary function test data, were utilized for analyses. Four robust PFT trajectory clusters were identified that were associated with ILD prevalence and mortality in exploratory analyses. A ML model for ILD detection achieved an AUC of 0.832 and retained performance in the Yale cohort (AUC 0.754). In addition to established predictors such as autoantibodies and pulmonary function, the model identified routine laboratory measurements, including red cell distribution width (RDW), white blood cell count, and serum chloride, as important contributors. One-year mortality prediction achieved AUCs of 0.904 in the North-western cohort and 0.910 in the Yale cohort. Among patients with SSc-ILD, one-year mortality was predicted with AUCs of 0.744 and 0.902 in the Northwestern and Yale cohorts, respectively. Unexpectedly, we found that subtle laboratory abnormalities (such as change in RDW) contributed to predicting mortality. Conclusions: Our prediction models comprised of widely available EHR data are useful tools to identify SSc patients at high risk for prevalent ILD and all-cause mortality. Integration of these models into clinical practice could enable scalable risk stratification and inform individualized ILD screening and monitoring strategies for SSc patients.

Introduction Prompt detection of childhood uveitis is key to minimising negative impact. From an internationally unique inception cohort, we report pathways to disease detection. UNICORNS is a national childhood non-infectious uveitis study with longitudinal collection of a standardised clinical dataset and patient reported outcomes. Descriptive analysis of baseline characteristics are reported. Amongst 150 recruited children (51% female, 31% non-white ethnicity) age at detection ranged from 2–18yrs (median 10). In 69%, uveitis was diagnosed following onset of symptoms: time from first symptoms to uveitis detection ranged from 0-739days (median 7days), with longer time to detection for those presenting initially to their general practitioner. Non symptomatic children were detected through JIA/other disease surveillance (16%), routine optometry review (5%) or child visual health screening (1%). Commonest underlying diagnoses at uveitis detection were JIA (17%), TINU (9%, higher than pre-pandemic reported UK disease frequency) and sarcoid (1%). 60% had no known systemic disease at uveitis detection. At disease detection, in at least one eye: 34% had structural complications (associated with greater time to detection – 17 days versus 4 days for uncomplicated presentation). The larger relative proportions of children with non-JIA uveitis reported here increase the importance of improving awareness of childhood uveitis amongst the wider clinical communities. There is scope for improvement of pathways to detection. Forthcoming analysis on the full cohort (251 recruited to date across 33 hospitals and 4 nations) will provide nationally representative data on management and the determinants of visual and broader developmental/well-being outcomes.