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Background: Heart failure (HF) is a common cardiac syndrome with a high disease burden and poor prognosis in our aging populations. Understanding the characteristics of patients with newly diagnosed HF is essential for improving care and outcomes. The AMSTERDAM-HF study is aimed to examine the population characteristics of patients with incident HF., Methods: We performed a retrospective dynamic cohort study in the Amsterdam general practice network consisting of 904,557 individuals. Incidence HF rates, geographical demographics, patient characteristics, risk factors, symptoms prior to HF diagnosis, and prognosis were reported., Results: The study identified 10,067 new cases of HF over 6,816,099 person-years. The median age of patients was 77 years (25th-75th percentile: 66-85), and 48% were male. The incidence rate of HF was 213.44 per 100,000 patient-years, and was higher in male versus female patients (incidence rate ratio: 1.08, 95%-CI:1.04-1.13). Hypertension (men 46.3% and women 55.8%), coronary artery disease (men 36% and women 25%) and diabetes mellitus (men 30.5% and women 26.8%) were the most common risk factors. Dyspnoea and oedema were key reported symptoms prior to HF diagnosis. Survival rates at 10-year follow-up were poor, particularly in men (36.4%) compared to women (39.7%). Incidence rates, comorbidity burden and prognosis were worse in city districts with high ethnic diversity and low socio-economic position., Conclusion: Our study provides insights into incident HF in a contemporary Western European, multi-ethnic, urban population. It highlights notable sex, age, and geographical differences in incidence rates, risk factors, symptoms and prognosis., Competing Interests: Declaration of Competing Interest The authors report no relationships that could be construed as a conflict of interest., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objectives: Heart failure (HF) is a prevalent syndrome with considerable disease burden, healthcare utilization and costs. Timely diagnosis is essential to improve outcomes. This study aimed to compare the diagnostic performance of B-type natriuretic peptide (BNP) and N-terminal proBNP (NT-proBNP) in detecting HF in primary care. Our second aim was to explore if personalized thresholds (using age, sex, or other readily available parameters) would further improve diagnostic accuracy over universal thresholds., Methods: A retrospective study was performed among patients without prior HF who underwent natriuretic peptide (NP) testing in the Amsterdam General Practice Network between January 2011 and December 2021. HF incidence was based on registration out to 90 days after NP testing. Diagnostic accuracy was evaluated with AUROC, sensitivity and specificity based on guideline-recommended thresholds (125 ng/L for NT-proBNP and 35 ng/L for BNP). We used inverse probability of treatment weighting to adjust for confounding., Results: A total of 15,234 patients underwent NP testing, 6,870 with BNP (4.5 % had HF), and 8,364 with NT-proBNP (5.7 % had HF). NT-proBNP was more accurate than BNP, with an AUROC of 89.9 % (95 % CI: 88.4-91.2) vs. 85.9 % (95 % CI 83.5-88.2), with higher sensitivity (95.3 vs. 89.7 %) and specificity (59.1 vs. 58.0 %). Differentiating NP cut-off by clinical variables modestly improved diagnostic accuracy for BNP and NT-proBNP compared with a universal threshold., Conclusions: NT-proBNP outperforms BNP for detecting HF in primary care. Personalized instead of universal diagnostic thresholds led to modest improvement., (© 2023 the author(s), published by De Gruyter, Berlin/Boston.)

Background: Timely diagnosis of heart failure (HF) is essential to optimize treatment opportunities that improve symptoms, quality of life, and survival. While most patients consult their general practitioner (GP) prior to HF, the early stages of HF may be difficult to identify. An integrated clinical support tool may aid in identifying patients at high risk of HF. We therefore constructed a prediction model using routine health care data., Methods: Our study involved a dynamic cohort of patients (≥35 years) who consulted their GP with either dyspnoea and/or peripheral oedema within the Amsterdam metropolitan area from 2011 to 2020. The outcome of interest was incident HF, verified by an expert panel. We developed a regularized, cause-specific multivariable proportional hazards model (TARGET-HF). The model was evaluated with bootstrapping on an isolated validation set and compared to an existing model developed with hospital insurance data as well as patient age as a sole predictor., Results: Data from 31,905 patients were included (40% male, median age 60 years) of whom 1,301 (4.1%) were diagnosed with HF over 124,676 person-years of follow-up. Data were allocated to a development (n = 25,524) and validation (n = 6,381) set. TARGET-HF attained a C-statistic of 0.853 (95% CI, 0.834 to 0.872) on the validation set, which proved to provide a better discrimination than C = 0.822 for age alone (95% CI, 0.801 to 0.842, P < 0.001) and C = 0.824 for the hospital-based model (95% CI, 0.802 to 0.843, P < 0.001)., Conclusion: The TARGET-HF model illustrates that routine consultation codes can be used to build a performant model to identify patients at risk for HF at the time of GP consultation., (© The Author(s) 2022. Published by Oxford University Press.)