Evidence map›Paper›PMID 39105329›Full record

ArticleESC heart failure2024

Development and validation of a multifactorial nomogram to predict 48 month mortality in decompensated heart failure.

Chenlin Zhuang, Yudai Chen, Kongyan Weng, Mei Zhuang, Huizhen Yu, Pengli Zhu

Abstract readValidation Study
In one paragraph

Article in ESC heart failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the 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

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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

6 authors.

Chenlin ZhuangShengli Clinical Medical College, Fujian Medical University, Fuzhou, China.ORCID 0000-0002-6601-6131
Yudai ChenShengli Clinical Medical College, Fujian Medical University, Fuzhou, China.
Kongyan WengDepartment of Transfusion, Fujian Provincial Hospital, Fuzhou, China.
Mei ZhuangDepartment of Pharmacy, Fujian Provincial Hospital, Jinshan Branch, Fuzhou, China.
Huizhen YuShengli Clinical Medical College, Fujian Medical University, Fuzhou, China.
Pengli ZhuShengli Clinical Medical College, Fujian Medical University, Fuzhou, China.

Funding

Fujian Province Natural Science Foundation 2020J011072Fujian Province Natural Science Foundation 2021J01388Fujian Provincial Health Commission Science and Technology Plan 2021CXA008
6 · The paper itself

Abstract

BACKGROUND AND

aimsAs the incidence of heart failure (HF) increases, the need for practical tools to evaluate the long-term prognosis in these patients remains critical. Our study aimed to develop a 48 month prediction model for all-cause mortality in decompensated HF patients using available clinical indicators.

methodsHF patients (n = 503), 60 years or older, were divided into a training cohort (n = 402) and a validation cohort (n = 101). Data on demographics, comorbidities, laboratory results and medications were gathered. Prediction models were developed using the Prognostic Nutritional Index (PNI), cholinesterase (ChE) and a multifactorial nomogram incorporating clinical variables. These models were constructed using the least absolute shrinkage and selection operator algorithm and multivariate logistic regression analysis. The performance of the model was assessed in terms of calibration, discrimination and clinical utility.

resultsThe mean age was 77.11 ± 8.85 years, and 216 (42.9%) were female. The multifactorial nomogram included variables of ChE, lymphocyte count, albumin, serum creatinine and N-terminal pro-brain natriuretic peptide (all P < 0.05). In the training cohort, the nomogram's C-index was 0.926 [95% confidence interval (CI) 0.896-0.950], outperforming the PNI indices at 0.883 and ChE at 0.804 (Z-tests, P < 0.05). The C-index in the validation cohort was 0.913 (Z-tests, P < 0.05). Calibration and decision curve analysis confirmed model reliability, indicating a more significant net benefit than PNI and ChE alone.

conclusionsBoth the ChE- and PNI-based prediction models effectively predict the long-term prognosis in patients over 60 years of age with decompensated HF. The multifactorial nomogram model shows superior performance, improving clinical decision-making and patient outcomes.

Indexed as

Heart FailureNomogramsAgedCause of DeathFemaleFollow-Up StudiesHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk AssessmentRisk FactorsSurvival RateTime FactorsCongestive heart failureNet benefitNomogramPNIPrognostic model

Identifiers

PMID39105329
PMCPMC11631327

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