↓ Skip to main content

A prediction study of warfarin individual stable dose after mechanical heart valve replacement: adaptive neural-fuzzy inference system prediction

Overview of attention for article published in BMC Surgery, February 2018
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
34 Mendeley
Title
A prediction study of warfarin individual stable dose after mechanical heart valve replacement: adaptive neural-fuzzy inference system prediction
Published in
BMC Surgery, February 2018
DOI 10.1186/s12893-018-0343-1
Pubmed ID
Authors

Huan Tao, Qian Li, Qin Zhou, Jie Chen, Bo Fu, Jing Wang, Wenzhe Qin, Jianglong Hou, Jin Chen, Li Dong, on behalf of the CLIATHVR multicenter clinical study team

Abstract

It's difficult but urgent to achieve the individualized rational medication of the warfarin, we aim to predict the individualized warfarin stable dose though the artificial intelligent Adaptive neural-fuzzy inference system (ANFIS). Our retrospective analysis based on a clinical database, involving 21,863 patients from 15 Chinese provinces who receive oral warfarin after the heart valve replacement. They were allocated into four groups: the external validation group (A group), the internal validation group (B group), training group (C group) and stratified training group (D group). We used a univariate analysis of general linear models(GLM-univariate) to select the input variables and construct two prediction models by the ANFIS with the training and stratified training group, and then verify models with two validation groups by the mean squared error(MSE), mean absolute error(MAE) and the ideal predicted percentage. A total of 13,639 eligible patients were selected, including 1639 in A group, 3000 in B group, 9000 in C group, and 3192 in D group. Nine input variables were selected out and two five-layered ANFIS models were built. ANFIS model achieved the highest total ideal predicted percentage 63.7%. In the dose subgroups, all the models performed best in the intermediate-dose group with the ideal predicted percentage 82.4~ 86.4%, and the use of the stratified training group slightly increased the prediction accuracy in low-dose group by 8.8 and 5.2%, respectively. As a preliminary attempt, ANFIS model predicted the warfarin stable dose properly after heart valve surgery among Chinese, and also proved that Chinese need lower anticoagulation intensity INR (1.5-2.5) to warfarin by reference to the recommended INR (2.5-3.5) in the developed countries.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 15%
Student > Master 5 15%
Student > Bachelor 4 12%
Lecturer 2 6%
Student > Ph. D. Student 2 6%
Other 4 12%
Unknown 12 35%
Readers by discipline Count As %
Medicine and Dentistry 8 24%
Computer Science 5 15%
Nursing and Health Professions 3 9%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Arts and Humanities 1 3%
Other 3 9%
Unknown 12 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 February 2018.
All research outputs
#14,967,526
of 23,023,224 outputs
Outputs from BMC Surgery
#324
of 1,336 outputs
Outputs of similar age
#276,694
of 474,288 outputs
Outputs of similar age from BMC Surgery
#3
of 12 outputs
Altmetric has tracked 23,023,224 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,336 research outputs from this source. They receive a mean Attention Score of 1.8. This one has gotten more attention than average, scoring higher than 71% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 474,288 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.