TARGET-HF: developing a model for detecting incident heart failure among symptomatic patients in general practice using routine health care data

Autor: Lukas De Clercq, Martijn C Schut, Patrick M M Bossuyt, Henk C P M van Weert, M Louis Handoko, Ralf E Harskamp
Přispěvatelé: Cardiology, ACS - Heart failure & arrhythmias, APH - Personalized Medicine, General practice, Graduate School, APH - Digital Health, Central Diagnostic Laboratory, APH - Methodology, Epidemiology and Data Science, APH - Quality of Care
Rok vydání: 2022
Předmět:
Zdroj: Family Practice, 40(1), 188-194. Oxford University Press
de Clercq, L, Schut, M C, Bossuyt, P M M, van Weert, H C P M, Handoko, M L & Harskamp, R E 2023, ' TARGET-HF : developing a model for detecting incident heart failure among symptomatic patients in general practice using routine health care data ', Family Practice, vol. 40, no. 1, pp. 188-194 . https://doi.org/10.1093/fampra/cmac069
Family practice, 40(1), 188-194. Oxford University Press
ISSN: 1460-2229
0263-2136
Popis: 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 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.
Databáze: OpenAIRE
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