Evidence map›Paper›PMID 33336021›Full record

ArticleOpen medicine (Warsaw, Poland)2020

A novel age-biomarker-clinical history prognostic index for heart failure with reduced left ventricular ejection fraction.

Hao Li, Yuan Cui, Jin Tian, Hong Yang, Qing Zhang, Ke Wang, Qinghua Han, Yanbo Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Open medicine (Warsaw, Poland), 2020. 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
–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

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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. 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

8 authors.

Hao LiDepartment of Health Statistics, Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, School of Public Health, Shanxi Medical University, 56 South XinJian Road, Taiyuan, Shanxi Province 030001, People's Republic of China.
Yuan CuiDepartment of Health Statistics, Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, School of Public Health, Shanxi Medical University, 56 South XinJian Road, Taiyuan, Shanxi Province 030001, People's Republic of China.
Jin TianDepartment of Cardiology, First Hospital of Shanxi Medical University, 85 South XinJian Road, Taiyuan, Shanxi Province 030001, People's Republic of China.
Hong YangDepartment of Health Statistics, Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, School of Public Health, Shanxi Medical University, 56 South XinJian Road, Taiyuan, Shanxi Province 030001, People's Republic of China.
Qing ZhangDepartment of Health Statistics, Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, School of Public Health, Shanxi Medical University, 56 South XinJian Road, Taiyuan, Shanxi Province 030001, People's Republic of China.
Ke WangDepartment of Health Statistics, Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, School of Public Health, Shanxi Medical University, 56 South XinJian Road, Taiyuan, Shanxi Province 030001, People's Republic of China.
Qinghua HanDepartment of Cardiology, First Hospital of Shanxi Medical University, 85 South XinJian Road, Taiyuan, Shanxi Province 030001, People's Republic of China.
Yanbo ZhangDepartment of Health Statistics, Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, School of Public Health, Shanxi Medical University, 56 South XinJian Road, Taiyuan, Shanxi Province 030001, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeA model for predicting the prognosis of patients with heart failure with reduced left ventricular ejection fraction (HFrEF) is currently not available. This study aimed to develop an age-biomarker-clinical history prognostic index (ABC-PI) and validate it for the assessment of individual prognosis. PATIENTS AND

methodsA total of 5,974 HFrEF patients were enrolled and 1,529 were included in this study after excluding missing values and loss to follow-up. Variables that significantly contributed to prediction of all-cause mortality were assessed by Cox regression and latent trait analysis (LTA) was used to validate discrimination of variables.

resultsAfter Cox regression, the following seven most significant variables were selected: age, N-terminal pro-B-type natriuretic peptide, renal dysfunction, left ventricular mass index, percutaneous coronary intervention, atrial fibrillation, and New York Heart Association (C-index: 0.801 ± 0.013). After verification by LTA, discrimination of these seven variables was proven. A nomogram was used to form the ABC-PI, and then the total score was set to 100 points. A lower score indicated a higher risk. After verification, the 3-year mortality rate was 34.7% in the high-risk group and only 2.6% in the low-risk group.

conclusionOur novel ABC-PI shows a good performance and does not require re-input in the original model. The ABC-PI can be used to effectively and practically predict the prognosis of HFrEF patients.

Indexed as

HFrEFlatent trait analysisnomogramNT-proBNP

Identifiers

PMID33336021
PMCPMC7712124

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