Evidence map›Paper›PMID 35647078›Full record

ArticleFrontiers in cardiovascular medicine2022

Long Short-Term Memory Network for Development and Simulation of Warfarin Dosing Model Based on Time Series Anticoagulant Data.

Yun Kuang, Yaxin Liu, Qi Pei, Xiaoyi Ning, Yi Zou, Liming Liu, Long Song, Chengxian Guo, Yuanyuan Sun, Kunhong Deng and 5 more

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02211326 (Pharmacogenetic Algorithm of Response to Warfarin During Initial Anticoagulation in Chinese Elderly Patients), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02211326 nacompletednot on this map

Pharmacogenetic Algorithm of Response to Warfarin During Initial Anticoagulation in Chinese Elderly Patients

TypeinterventionalSponsorThe Third Xiangya Hospital of Central South UniversityRan2014 to 2017Enrolled660ConditionsAtrial Fibrillation, Deep Venous ThrombosisArmsGenotype-guided dosing algorithm for warfarin, Standard initiation dose for warfarin
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Machine Learning for Warfarin Therapy: A Systematic Review.Pharmaceuticals (Basel, Switzerland) · 2025
    Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Yun KuangCenter of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, Changsha, China.
Yaxin LiuXiangYa School of Pharmaceutical Sciences, Central South University, Changsha, China.
Qi PeiDepartment of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China.
Xiaoyi NingCenter of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, Changsha, China.
Yi ZouSchool of Mathematics and Statisics, Central South University, Changsha, China.
Liming LiuDepartment of Cardiovascular Surgery, The Second Xiangya Hospital, Central South University, Changsha, China.
Long SongDepartment of Cardiovascular Surgery, The Second Xiangya Hospital, Central South University, Changsha, China.
Chengxian GuoCenter of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, Changsha, China.
Yuanyuan SunCenter of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, Changsha, China.
Kunhong DengCenter of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, Changsha, China.
Chan ZouCenter of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, Changsha, China.
Dongsheng CaoXiangYa School of Pharmaceutical Sciences, Central South University, Changsha, China.
Yimin CuiInstitute of Clinical Pharmacology, Peking University First Hospital, Beijing, China.
Chengkun WuState Key Laboratory of High Performance Computing, Institute for Quantum Information, College of Computer Science and Technology, National University of Defense Technology, Changsha, China.
Guoping YangCenter of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Warfarin is an effective treatment for thromboembolic disease but has a narrow therapeutic index, and dosage can differ tremendously among individuals. The study aimed to develop an individualized international normalized ratio (INR) model based on time series anticoagulant data and simulate individualized warfarin dosing. Methods: We used a long short-term memory (LSTM) network to develop an individualized INR model based on data from 4,578 follow-up visits, including clinical and genetic factors from 624 patients whom we enrolled in our previous randomized controlled trial. The data of 158 patients who underwent valvular surgery and were included in a prospective registry study were used for external validation in the real world. Results: The prediction accuracy of LSTM_INR was 70.0%, which was much higher than that of MAPB_INR (maximum posterior Bayesian, 53.9%). Temporal variables were significant for LSTM_INR performance (51.7 vs. 70.0%, Conclusion: The results indicate that temporal variables are necessary to be considered in warfarin therapy, except for clinical factors and genetic factors. LSTM network may have great potential for long-term drug individualized therapy. Trial Registration: NCT02211326; www.chictr.org.cn:ChiCTR2100052089.

Indexed as

applicationlong short-term memory networkmodelingtime serieswarfarin

Identifiers

PMID35647078
PMCPMC9130657

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Registered trials

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