Flow chart of the study population selection.

<div>BackgroundLeft ventricular ejection fraction (EF) is used to categorize heart failure (HF) into phenotypes but this information is often missing in electronic health records or non-HF registries.MethodsWe tested the applica...

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Bibliographic Details
Main Author:	Elisa Dal Canto (9582176) (author)
Other Authors:	Alicia Uijl (20114277) (author), N. Charlotte Onland-Moret (9530919) (author), Sophie H. Bots (10175957) (author), Leonard Hofstra (168398) (author), Igor Tulevski (20114280) (author), Folkert W. Asselbergs (7588589) (author), Pim van der Harst (65060) (author), G. Aernout Somsen (10956451) (author), Hester M. den Ruijter (12409468) (author)
Published:	2024
Subjects:	Molecular Biology Biotechnology Developmental Biology Cancer Science Policy Infectious Diseases Biological Sciences not elsewhere classified negative predictive values electronic health records ejection fraction prediction categorize heart failure 73 &# 8211 69 &# 8211 66 &# 177 65 &# 8211 58 &# 8211 routine clinical characteristics 63 &# 8211 calculated model sensitivity primary care data multivariable multinomial analysis heart failure patients ef &# 8805 simple algorithm based netherlands </ p tested model discrimination multivariable algorithm based algorithm multinomial model netherlands database clinical variables 63 ). model performance xlink "> simplified version similar results preserved ef predict ef internally validated hospital cardiologist highest sensitivities general practitioner cardiology datasets cardiology centres cardiology centers additionally performed 868 patients 12 years
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Flow chart of the study population selection.

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