Evidence map›Paper›PMID 36991222›Full record

ArticleInternational journal of clinical pharmacy2023

Developing Chinese race-specific warfarin dose prediction algorithms.

Weiqi Gao, Zhijiao Zhang, Zhaobo Guan, Weihong Chen, Zhihong Li

Abstract read
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In one paragraph

Article in International journal of clinical pharmacy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 46% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.

  1. Pooled it
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

5 authors at 1 institution in 1 country.

Weiqi GaoShanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, 99 Longcheng Street, Taiyuan, 030032, China.
Zhijiao ZhangSchool of Pharmacy, Shanxi Medical University, Taiyuan, 030001, China.
Zhaobo GuanSchool of Pharmacy, Shanxi Medical University, Taiyuan, 030001, China.
Weihong ChenShanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, 99 Longcheng Street, Taiyuan, 030032, China.
Zhihong LiShanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, 99 Longcheng Street, Taiyuan, 030032, China. whhchenrkx@sina.com.ORCID http://orcid.org/0000-0001-5525-4161
Shanxi Medical University · CN

Funding

Fundamental Research Program of Shanxi Province 20210302124649Wu Jieping Medical Foundation 320.6750.2021-08-12
6 · The paper itself

Abstract

backgroundNumerous genotype-guided warfarin dosing algorithms have been developed to individualize warfarin doses, but they can only explain 47-52% of the variability.

aimThis study aimed to develop new warfarin algorithms suitable to predict the stable warfarin dose for the Chinese population and to compare their prediction performance with those of the most commonly used algorithms.

methodMultiple linear regression analysis with the warfarin optimal dose (WOD), logarithm (log) WOD, 1/WOD, and [Formula: see text], respectively, as the dependent variables were performed to deduce a new warfarin algorithm (NEW-Warfarin). WOD was the stable dose that maintained the international normalized ratio (INR) within the target range (2.0-3.0). Three major genotype-guided warfarin dosing algorithms were selected and compared against NEW-Warfarin predictive performance using the mean absolute error (MAE). Furthermore, patients were divided into five groups according to warfarin indications [atrial fibrillation (AF), pulmonary embolism (PE), cardiac-related disease (CRD), deep vein thrombosis (DVT), and other diseases (OD)]. Multiple linear regression analyses were also performed for each group.

resultsThe regression equation with [Formula: see text] as the dependent variable had the highest coefficient of determination (R

conclusionDosing algorithms based on warfarin indications are more suitable for predicting warfarin doses. Our research provides a novel strategy to develop indication-specific warfarin dosing algorithms to improve the efficacy and safety of warfarin prescribing.

Indexed as

Atrial FibrillationWarfarinAlgorithmsAnticoagulantsCytochrome P-450 CYP2C9East Asian PeopleGenotypeHumansInternational Normalized RatioPharmacogeneticsVitamin K Epoxide ReductasesAnticoagulantsCytochrome P-450 CYP2C9Vitamin K Epoxide ReductasesWarfarinClinical factorsDose prediction algorithmIndicationsPharmacogenomicsPredictive accuracyWarfarin

Identifiers

PMID36991222
OpenAlexW4361293033

What OpenQuestion holds

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Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.