AI‐assisted warfarin dose optimisation with <scp>CURATE</scp>.<scp>AI</scp> for clinical impact: Retrospective data analysis

In this retrospective study of 127 patients, CURATE.AI fared better in terms of Percentage Absolute Prediction Error and Percentage Prediction Error of 20% compared to other models in the literature. It also had negligible underprediction bias, potentially translating into lower bleeding risk. Modeled potential time in therapeutic range with CURATE.AI was not significantly different from physician-guided dosing, so it is on-par yet provides a systematic approach to warfarin dosing, easing the mental-burden on guesswork by physicians.This study lays the groundwork for the prospective study of CURATE.AI as a clinical decision support system. CURATE.AI may facilitate the effective use of affordable warfarin with a well-established safety profile, without the need for costly, new oral anticoagulants. This can have significant impact both on the individual and public health.

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Publication Details

Journal
Bioengineering & Translational Medicine
Published
2025-02-03
DOI
https://doi.org/10.1002/btm2.10757
Citations
2
Primary Topic
Atrial Fibrillation Management and Outcomes
Type
article
Field-Weighted Citation Impact
2.78

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article

AI‐assisted warfarin dose optimisation with CURATE.AI for clinical impact: Retrospective data analysis

Shi‐Bei Tan, Sarah Si Lin Tang, Dean Ho, Mathias Egermark et al.
2 citations
Bioengineering & Translational Medicine
Atrial Fibrillation Management and Outcomes
2.78
article

AI‐assisted warfarin dose optimisation with CURATE.AI for clinical impact: Retrospective data analysis

Shi‐Bei Tan, Sarah Si Lin Tang, Dean Ho, Mathias Egermark, Tiffany Rui Xuan Gan, Boon Cher Goh, Kee Yuan Ngiam, Anh T. L. Truong, Lester W. J. Tan, Kirthika Senthil Kumar, Agata Blasiak
article en
2 citations

Abstract

In this retrospective study of 127 patients, CURATE.AI fared better in terms of Percentage Absolute Prediction Error and Percentage Prediction Error of 20% compared to other models in the literature. It also had negligible underprediction bias, potentially translating into lower bleeding risk. Modeled potential time in therapeutic range with CURATE.AI was not significantly different from physician-guided dosing, so it is on-par yet provides a systematic approach to warfarin dosing, easing the mental-burden on guesswork by physicians.This study lays the groundwork for the prospective study of CURATE.AI as a clinical decision support system. CURATE.AI may facilitate the effective use of affordable warfarin with a well-established safety profile, without the need for costly, new oral anticoagulants. This can have significant impact both on the individual and public health.

Bioengineering & Translational MedicineVol. 10(3)
National University of Singapore (SG), Ng Teng Fong General Hospital (SG), National University Hospital (SG)
Micron Foundation, National Research Foundation, National University of Singapore, National Research Foundation Singapore, Medical Research Council, National Medical Research Council
Openalex Percentile: Top 12%
Atrial Fibrillation Management and Outcomes
2.78
DOIOpen Access PDFOpenAlex
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