id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-302336-zj3oixvk	Clift, Ash K	Living risk prediction algorithm (QCOVID) for risk of hospital admission and mortality from coronavirus 19 in adults: national derivation and validation cohort study	2020-10-21		.txt	text/plain	7352	320	44	13 The use of primary care datasets with linkage to registries such as death records, hospital admissions data, and covid-19 testing results represents a novel approach to clinical risk prediction modelling for covid-19. Patients entered the cohort on 24 January 2020 (date of first confirmed case of covid-19 in the UK) and were followed up until they had the outcome of interest or the end of the first study period (30 April 2020), which was the date up to which linked data were available at the time of the derivation of the model, or the second time period (1 May 2020 until 30 June 2020) for the temporal cohort validation. 25 D statistics (a discrimination measure that quantifies the separation in survival between patients with different levels of predicted risks) and Harrell's C statistics (a discrimination metric that quantifies the extent to which people with higher risk scores have earlier events) were evaluated at 97 days (the maximum followup period available at the time of the derivation of the model) and 60 days for the second temporal validation, with corresponding 95% confidence intervals.	./cache/cord-302336-zj3oixvk.txt	./txt/cord-302336-zj3oixvk.txt