Intraoperative Features Improve Model Risk Predictions After Coronary Artery Bypass Grafting.

Background: Intraoperative physiologic parameters could offer predictive utility in evaluating risk of adverse postoperative events yet are not included in current standard risk models. This study examined whether the inclusion of continuous intraoperative data improved machine learning model predictions for multiple outcomes after coronary artery bypass grafting, including 30-day mortality, renal failure, reoperation, prolonged ventilation, and combined morbidity and mortality (MM).

Methods: The Society of Thoracic Surgeons (STS) database features and risk scores were combined with retrospectively gathered continuous intraoperative data from patients.

Reintervention after aortic root replacement with allograft, xenograft, and stented bioprosthetic valves.

Background: There has been a significant increase in the utilization of non-mechanical valves in the aortic position over time. However, details in reinterventions after aortic root replacement (ARR) with non-mechanical prosthesis were limited in the literature, despite the potential importance of reinterventions in the lifetime management of aortic valve disease.

Methods: This is a single-center retrospective study, identifying all patients who underwent ARR with allograft, xenografts, and stented bioprosthetic valved conduit from 2010 to 2020.

Outcomes of acute type A aortic dissection repair in patients under the age of 75 versus 75 and older.

Objective: Elderly patients are less likely to undergo surgery for an acute type A aortic dissection (ATAAD). This study aims to understand the risks of surgical treatment in patients 75 and older.

Methods: This was a retrospective study using an institutional database of patients who underwent ATAAD repair from 2007 to 2021.

Functional protein mining with conformal guarantees.

Molecular structure prediction and homology detection offer promising paths to discovering protein function and evolutionary relationships. However, current approaches lack statistical reliability assurances, limiting their practical utility for selecting proteins for further experimental and in-silico characterization. To address this challenge, we introduce a statistically principled approach to protein search leveraging principles from conformal prediction, offering a framework that ensures statistical guarantees with user-specified risk and provides calibrated probabilities (rather than raw ML scores) for any protein search model.

National and regional trends in the prevalence of Perthes' disease among the male population in South Korea.

Aims: We evaluated the national and regional trends from 2013 to 2022, in the prevalence of Perthes' disease among adolescent males in South Korea.

Methods: This retrospective, nationwide, population-based study included a total of 3,166,669 Korean adolescent males examined at regional Military Manpower Administration (MMA) offices over ten years. Data from the MMA were retrospectively collected to measure the national and regional prevalence per 100,000 and 95% CI of Perthes' disease according to the year (1 January 2013 to 31 December 2022) and history of pelvic and/or femoral osteotomy in South Korea.