Evidence map›Paper›PMID 39553845›Full record

ArticleFrontiers in cardiovascular medicine2024

Personalized risk prediction of mortality and rehospitalization for heart failure in patients undergoing mitral valve repair surgery.

Ning Zhou, Kui Zhang, Bokang Qiao, Cong Chen, Xiaobo Guo, Wei Fu, Jubing Zheng, Jie Du, Ran Dong

Registry-linked trialAbstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05141292 (A Registry Study of Biomarkers in Mitral Valve Disease), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

NCT05141292 unknown statusnot on this map

A Registry Study of Biomarkers in Mitral Valve Disease

TypeobservationalSponsorBeijing Institute of Heart, Lung and Blood Vessel DiseasesRan2016 to 2025Enrolled5,000ConditionsCardiovascular Diseases
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

9 authors.

Ning ZhouCoronary Artery Disease Surgical Center, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, China.
Kui ZhangCoronary Artery Disease Surgical Center, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, China.
Bokang QiaoCoronary Artery Disease Surgical Center, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, China.
Cong ChenCoronary Artery Disease Surgical Center, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, China.
Xiaobo GuoCoronary Artery Disease Surgical Center, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, China.
Wei FuCoronary Artery Disease Surgical Center, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, China.
Jubing ZhengCoronary Artery Disease Surgical Center, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, China.
Jie DuCoronary Artery Disease Surgical Center, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, China.
Ran DongCoronary Artery Disease Surgical Center, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Accurately assessing the postoperative mortality and rehospitalization for heart failure risks in patients undergoing mitral valve repair surgery is of significant importance for individualized medical strategies. Objective: We sought to develop and validate a risk assessment system for the prediction of mortality and rehospitalization for heart failure. Methods: Personalized risk prediction system of mortality and rehospitalization for heart failure was developed. For developing a prediction system with death as the outcome, there were 965 patients (70%) and 413 patients (30%) were included in the the derivation cohort and the validation cohort. For developing a prediction system with rehospitalization for heart failure as the outcome, there were 927 patients (70%) and 398 patients (30%) were included in the derivation cohort and the validation cohort. There were 42 routine clinical variables used to develop the models. The performance evaluation of the model is based on the area under the curve (AUC). Evaluate the improvement with Euro Score II according to NRI and IDI net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results: The median follow-up time was 685 days, the incidence of death was 3.85% ( Conclusion: The developed and validated models exhibit satisfactory performance in prediction of all-cause mortality and rehospitalization for heart failure after mitral valve repair surgery. Clinical Trial Registration: http://www.clinicaltrials.gov, Unique identifier: (NCT05141292).

Indexed as

machine learning (ML)mitral valve repair (MV repair)mortalitypersonalized risk predictionrehospitalization for heart failure

Identifiers

PMID39553845
PMCPMC11563966

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.