Stable warfarin dose prediction in sub-Saharan African patients: A machine-learning approach and external validation of a clinical dose-initiation algorithm.

ABSTRACT: Warfarin remains the most widely prescribed oral anticoagulant in sub-Saharan Africa. However, because of its narrow therapeutic index, dosing can be challenging. We have therefore (a) evaluated and compared the performance of 21 machine-learning techniques in predicting stable warfarin dose in sub-Saharan Black-African patients and (b) externally validated a previously developed Warfarin Anticoagulation in Patients in Sub-Saharan Africa (War-PATH) clinical dose-initiation algorithm. The development cohort included 364 patients recruited from eight outpatient clinics and hospital departments in Uganda and South Africa (June 2018-July 2019). Validation was conducted using an external validation cohort (270 patients recruited from August 2019 to March 2020 in 12 outpatient clinics and hospit

SUBMITTER: Asiimwe IG 

PROVIDER: S-EPMC8752108 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature