A novel model gauging risk for post-transplant death may be used to guide the medical care of the kidney recipient at the time of transplant surgery.

Please provide your email address to receive an email when new articles are posted on . Researchers found 54% of studies had risk for bias due to inadequate population selection. Moreover, 30% of ...

ROC curves illustrating the discriminative ability of the VR-specific 30-day mortality prediction models. (A–C) Performance of the high VR model in the ARDSnet training cohort (A), internal validation ...

Among hospitalized patients with cirrhosis, a machine learning (ML) model enhanced mortality prediction compared with traditional methods and was consistent across country income levels in a large ...

Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may underestimate risk in elderly East Asian patients. Researchers from Japan used ...

Patients with myelodysplastic syndromes (MDS) exhibit diverse disease trajectories necessitating different clinical approaches ranging from watch-and-wait strategies to hematopoietic stem cell ...

It would be greatly beneficial to physicians trying to save lives in intensive care units if they could be alerted when a patient's condition rapidly deteriorates or shows vitals in highly abnormal ...

This study validates the Predicting Risk of CVD Events (PREVENT) score across diverse racial and ethnic populations, highlighting its effectiveness in predicting cardiovascular risk and mortality, ...

A team of researchers from Boston-based Harvard Medical School, Boston-based Massachusetts General Hospital and IBM Research developed a risk score to predict patient outcomes after cirrhosis-related ...