{"title":"Assessing the risk of heart failure in type 2 diabetes: a prediction algorithm to sustain the evaluation of NT-proBNP in primary care.","authors":"Francesco Lapi, Ettore Marconi, Gerardo Medea, Iacopo Cricelli, Damiano Parretti, Alessandro Rossi, Claudio Cricelli","doi":"10.1007/s12020-024-04157-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Heart failure (HF) is a disease that leads to approximately 300,000 fatalities annually in Europe and 250,000 deaths each year in the United States. Type 2 Diabetes Mellitus (T2DM) is a significant risk factor for HF, and testing for N-terminal (NT)-pro hormone BNP (NT-proBNP) can aid in early detection of HF in T2DM patients. We therefore developed and validated the HFriskT2DM-HScore, an algorithm to predict the risk of HF in T2DM patients, so guiding NT-proBNP investigation in a primary care setting.</p><p><strong>Methods: </strong>Using a primary care database, we formed a cohort of patients aged ≥18 years diagnosed with T2DM between 2002 and 2022. A multivariate Cox model was adopted to assess the determinants associated with the occurrence of HF to combine them to form an individual score.</p><p><strong>Results: </strong>Within a cohort of 167,618 patients (52.3% males; mean age 64.4 (SD: 14.4); HF rate equal to 6.7 cases per 1000 person-years), we developed the HFriskT2DM-HScore. When it was applied to the validation sub-cohort we found an explained variation and discrimination value of 43% (95% CI: 42-44) and 81% (95% CI: 0.80-0.83), respectively. Calibration slope was equal to 0.93 (95% CI: 0.81-1.1; p = 0.3123).</p><p><strong>Conclusion: </strong>The HFriskT2DM-HScore might be implemented as a decision support system for primary care to appropriately ease the prescription of NT-proBNP and early identification of HF.</p>","PeriodicalId":49211,"journal":{"name":"Endocrine","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Endocrine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12020-024-04157-9","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: Heart failure (HF) is a disease that leads to approximately 300,000 fatalities annually in Europe and 250,000 deaths each year in the United States. Type 2 Diabetes Mellitus (T2DM) is a significant risk factor for HF, and testing for N-terminal (NT)-pro hormone BNP (NT-proBNP) can aid in early detection of HF in T2DM patients. We therefore developed and validated the HFriskT2DM-HScore, an algorithm to predict the risk of HF in T2DM patients, so guiding NT-proBNP investigation in a primary care setting.
Methods: Using a primary care database, we formed a cohort of patients aged ≥18 years diagnosed with T2DM between 2002 and 2022. A multivariate Cox model was adopted to assess the determinants associated with the occurrence of HF to combine them to form an individual score.
Results: Within a cohort of 167,618 patients (52.3% males; mean age 64.4 (SD: 14.4); HF rate equal to 6.7 cases per 1000 person-years), we developed the HFriskT2DM-HScore. When it was applied to the validation sub-cohort we found an explained variation and discrimination value of 43% (95% CI: 42-44) and 81% (95% CI: 0.80-0.83), respectively. Calibration slope was equal to 0.93 (95% CI: 0.81-1.1; p = 0.3123).
Conclusion: The HFriskT2DM-HScore might be implemented as a decision support system for primary care to appropriately ease the prescription of NT-proBNP and early identification of HF.
期刊介绍:
Well-established as a major journal in today’s rapidly advancing experimental and clinical research areas, Endocrine publishes original articles devoted to basic (including molecular, cellular and physiological studies), translational and clinical research in all the different fields of endocrinology and metabolism. Articles will be accepted based on peer-reviews, priority, and editorial decision. Invited reviews, mini-reviews and viewpoints on relevant pathophysiological and clinical topics, as well as Editorials on articles appearing in the Journal, are published. Unsolicited Editorials will be evaluated by the editorial team. Outcomes of scientific meetings, as well as guidelines and position statements, may be submitted. The Journal also considers special feature articles in the field of endocrine genetics and epigenetics, as well as articles devoted to novel methods and techniques in endocrinology.
Endocrine covers controversial, clinical endocrine issues. Meta-analyses on endocrine and metabolic topics are also accepted. Descriptions of single clinical cases and/or small patients studies are not published unless of exceptional interest. However, reports of novel imaging studies and endocrine side effects in single patients may be considered. Research letters and letters to the editor related or unrelated to recently published articles can be submitted.
Endocrine covers leading topics in endocrinology such as neuroendocrinology, pituitary and hypothalamic peptides, thyroid physiological and clinical aspects, bone and mineral metabolism and osteoporosis, obesity, lipid and energy metabolism and food intake control, insulin, Type 1 and Type 2 diabetes, hormones of male and female reproduction, adrenal diseases pediatric and geriatric endocrinology, endocrine hypertension and endocrine oncology.