PIFA-N Multifactor Model to Predict Adverse Outcomes for Chronic Heart Failure Patients.

IF 2 Q2 MEDICINE, GENERAL & INTERNAL
Journal of clinical medicine research Pub Date : 2026-04-15 eCollection Date: 2026-04-01 DOI:10.14740/jocmr6518
Natalia A Dragomiretskaya, Anastasia V Tolmacheva, Aida I Tarzimanova, Anna E Pokrovskaya, Tatiana S Vargina, Tatiana A Safronova, Ivan D Medvedev, Antonina A Abramova, Daria D Vanina, Valery I Podzolkov
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引用次数: 0

Abstract

Background: In recent years, special attention has been given to developing multifactor models that support a more personal approach to assessing prognosis for chronic heart failure (CHF) patients with varying degrees of systolic dysfunction. The existing scales, namely the Seattle Heart Failure Model (SHFM), Meta-Analysis Global Group in Chronic HF (MAGGIC-HF), PARADIGM Risk of Events and Death in the Contemporary Treatment (PREDICT-HF), and the Barcelona Bio-HF (BCN-Bio-HF) risk calculator, contain numerous variables and biomarkers not readily accessible in actual clinical practice and thus fall short of meeting physicians' requirements. The study aimed to develop a multifactor model for assessing the risk of comorbid CHF patients developing adverse outcomes.

Methods: Our study included 233 patients (129 male and 104 female) aged 73.2 ± 12.4 years, admitted to the Internal Medicine Clinic of the Sechenov University Clinical Hospital No. 4 with symptoms of New York Heart Association Functional Classification (NYHA FC) II to IV CHF, including 91 patients with heart failure with preserved ejection fraction (CHFpEF), 69 with heart failure with mildly reduced ejection fraction (CHFmrEF), and 63 with heart failure with reduced ejection fraction (CHFrEF). All the patients had given their informed and written consent to take part in the study. They were given a standard clinical examination and additionally tested for N-terminal pro-B-type natriuretic peptide (NT-proBNP), soluble interleukin-like protein receptor (sST2), galectin-3, hepcidin, and copeptin levels. Prospective follow-up lasted for 36 ± 3 months. The primary endpoint was defined as death from all causes. The findings were processed statistically using Statistica 12.0 and SPSS software.

Results: All-cause mortality was 33.1% in the cohort examined. We used uni- and multivariate regression analysis to develop a PIFA-N prognostic mathematical model of adverse outcome that factored in community-acquired pneumonia diagnosed on inclusion in the study (odds ratio (OR): 3.09, 95% confidence interval (CI) 1.13-8.5, P = 0.028), a previous myocardial infarction (OR: 4.26, 95% CI 1.54-11.7, P = 0.005), presence of any form of atrial fibrillation (OR: 3.13, 95% CI 1.05-9.2, P = 0.039) and/or anemia (OR: 3.18, 95% CI 1.003-10.1, P = 0.049), and NT-proBNP level (OR: 1.0005, 95% CI 1.0002-1.0008, P = 0.002). Other biomarkers studied showed no predictive value. Our PIFA-N model is 77.1% sensitive and 77.3% specific (area under receiver operating characteristic curve (ROC AUC) 0.845), which meets high efficiency criteria.

Conclusion: We analyzed CHF patients' 3-year survival rate to develop an efficient prognostic model for assessing the risk of lethal outcome, whose arguments are easy-to-check conditions and routine laboratory test figures that can be established without any sophisticated examination techniques.

PIFA-N多因素模型预测慢性心力衰竭患者不良结局。
背景:近年来,人们特别关注开发多因素模型,以支持更个性化的方法来评估具有不同程度收缩功能障碍的慢性心力衰竭(CHF)患者的预后。现有的量表,即西雅图心力衰竭模型(SHFM)、慢性心衰荟萃分析全球小组(maggi -HF)、当代治疗中事件和死亡的范式风险(PREDICT-HF)和巴塞罗那生物心衰风险计算器(bn -Bio-HF),包含许多变量和生物标志物,在实际临床实践中不易获得,因此不能满足医生的要求。该研究旨在建立一个多因素模型来评估合并CHF患者发生不良后果的风险。方法:我们的研究纳入了233例(男性129例,女性104例),年龄73.2±12.4岁,在谢切诺夫大学第四临床医院内科门诊就诊的纽约心脏协会功能分类(NYHA FC) II至IV型CHF患者,其中91例为保留射血分数心力衰竭(CHFpEF), 69例为轻度射血分数降低心力衰竭(CHFmrEF), 63例为降低射血分数心力衰竭(CHFrEF)。所有的患者都有知情的书面同意参加这项研究。他们接受了标准的临床检查,并进行了n端前b型利钠肽(NT-proBNP)、可溶性白介素样蛋白受体(sST2)、半凝集素-3、hepcidin和copeptin水平的检测。前瞻性随访36±3个月。主要终点被定义为全因死亡。使用Statistica 12.0和SPSS软件对结果进行统计学处理。结果:全因死亡率为33.1%。我们使用单因素和多因素回归分析建立了不良结果的pfa - n预后数学模型,该模型考虑了纳入研究时诊断出的社区获得性肺炎(优势比(OR): 3.09, 95%可信区间(CI) 1.13-8.5, P = 0.028)、既往心肌梗死(OR: 4.26, 95% CI 1.54-11.7, P = 0.005)、任何形式的房颤(OR: 3.13, 95% CI 1.05-9.2, P = 0.039)和/或贫血(OR:3.18, 95% CI 1.003-10.1, P = 0.049), NT-proBNP水平(OR: 1.0005, 95% CI 1.0002-1.0008, P = 0.002)。其他研究的生物标志物没有预测价值。我们的PIFA-N模型灵敏度为77.1%,特异度为77.3%(受试者工作特征曲线下面积(ROC AUC) 0.845),符合高效标准。结论:我们分析了CHF患者的3年生存率,以建立一个有效的预后模型来评估致命结局的风险,其参数是易于检查的条件和常规实验室检查数据,无需任何复杂的检查技术即可建立。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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