Predicting mortality in acutely hospitalised older patients: the impact of model dimensionality.

ABSTRACT:

Background

The prediction of long-term mortality following acute illness can be unreliable for older patients, inhibiting the delivery of targeted clinical interventions. The difficulty plausibly arises from the complex, multifactorial nature of the underlying biology in this population, which flexible, multimodal models based on machine learning may overcome. Here, we test this hypothesis by quantifying the comparative predictive fidelity of such models in a large consecutive sample of older patients acutely admitted to hospital and characterise their biological support.

Methods

A set of 804 admission episodes involving 616 unique patients with a mean age of 84.5 years consecutively admitted to the Acute Geriatric service at University College Hospital were identified, in w

SUBMITTER: Tsui A 

PROVIDER: S-EPMC9827638 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature