Surgeons' perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey.

Background: Artificial intelligence (AI) is gaining traction in medicine and surgery. AI-based applications can offer tools to examine high-volume data to inform predictive analytics that supports complex decision-making processes. Time-sensitive trauma and emergency contexts are often challenging.

Population Health Strategies to Support Hospital and Intensive Care Unit Resiliency During the COVID-19 Pandemic: The Italian Experience.

Italy was one of the countries most affected by the number of people infected and dead during the first COVID-19 wave. The authors describe the rapid rollout of a population health clinical and organizational response in preparedness and capabilities to support the first wave of the COVID-19 pandemic in the Italian province of Modena. The authors review the processes, the challenges faced, and describe how excess demand for hospital services was successfully mitigated and thus overwhelming the healthcare services avoided the collapse of the local health care system.

Estimating the glomerular filtration rate in the general population using different equations: effects on classification and association.

Background/aims: Several formulas for glomerular filtration rate (GFR) estimation, based on serum creatinine or cystatin C, have been proposed. We assessed the impact of some of these equations on estimated GFR (eGFR) and chronic kidney disease (CKD) prevalence, and on the association with cardiovascular risk factors, in a general population sample characterized by a young mean age.

Methods: We studied 1,199 individuals from three Alpine villages enrolled into the MICROS study.

Importance of different types of prior knowledge in selecting genome-wide findings for follow-up.

Biological plausibility and other prior information could help select genome-wide association (GWA) findings for further follow-up, but there is no consensus on which types of knowledge should be considered or how to weight them. We used experts' opinions and empirical evidence to estimate the relative importance of 15 types of information at the single-nucleotide polymorphism (SNP) and gene levels. Opinions were elicited from 10 experts using a two-round Delphi survey.

SNP prioritization using a Bayesian probability of association.

Prioritization is the process whereby a set of possible candidate genes or SNPs is ranked so that the most promising can be taken forward into further studies. In a genome-wide association study, prioritization is usually based on the P-values alone, but researchers sometimes take account of external annotation information about the SNPs such as whether the SNP lies close to a good candidate gene. Using external information in this way is inherently subjective and is often not formalized, making the analysis difficult to reproduce.