AIMC Topic: Risk Factors

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Predictive modeling for early detection of refractory esophageal stricture following esophageal atresia surgery: insight from a machine learning study.

Pediatric surgery international
BACKGROUND: Refractory esophageal stricture (RES) presents a challenging complication after esophageal atresia (EA) repair. Earlier identification of patients with RES could help clinical decision-making. However, there are currently limited articles...

Predicting complications in breast reconstruction: External validation of a machine learning model.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: Nipple-sparing mastectomy (NSM) with immediate implant-based breast reconstruction provides aesthetic and psychosocial benefits, but nipple-areolar complex (NAC) necrosis remains a significant risk. This study externally validated a previ...

Renal Dysfunction Across the Spectrum of Cardiogenic Shock: Mechanisms, Clinical Implications, and Therapeutic Strategies.

Current heart failure reports
PURPOSE OF REVIEW: This review aims to elucidate the complex interplay between cardiogenic shock (CS) and renal function, detailing the mechanisms of kidney injury, identifying risk factors, and providing a framework for the diagnosis and management ...

Construction of a novel online calculator for prediction of osteoporosis risk in Chinese type 2 diabetes patients.

Experimental gerontology
BACKGROUND: Type 2 diabetes (T2D) has been established as an independent risk factor for osteoporosis, often resulting in a poor prognosis. Thus, it is crucial for clinicians to diagnose osteoporosis in diabetic patients. This study aimed to develop ...

Mortality risk associated with clinical signs of possible serious bacterial infection (PSBI) in young infants in Africa and Asia: protocol for a secondary pooled analysis.

BMJ open
INTRODUCTION: The WHO's Integrated Management of Childhood Illness (IMCI) in young infants <2 months of age includes the identification and management of signs of possible serious bacterial infection (PSBI). However, equal importance is given to all ...

Exploring the association between volatile organic compound exposure and chronic kidney disease: evidence from explainable machine learning methods.

Renal failure
BACKGROUND: Chronic Kidney Disease (CKD) affects approximately 697.5 million people worldwide. Volatile organic compounds (VOCs) are emerging as potential risk factors, but their complex relationships with CKD may be underestimated by traditional lin...

The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
: Early identification and timely preventive interventions play an essential role for improving the prognosis of newborns with necrotizing enterocolitis (NEC). Thus, establishing a novel and simple prediction model is of great clinical significance. ...

Cross-jurisdictional factors linked to gambling frequency in adolescents from 28 European countries: a machine learning approach.

Psychiatry research
Adolescents are vulnerable to experiencing problematic gambling, although its prevalence and potential risk factors vary across countries. This study aims to identify cross-jurisdictional factors associated with higher gambling frequency among adoles...