Efficiently screening heart failure in patients with type 2 diabetes
| Autor: | Frans H. Rutten, Marcel A.J. Landman, Leandra J.M. Boonman-de Winter, Anho H. Liem, Nicolaas P.A. Zuithoff, Arno W. Hoes, Maarten J. Cramer |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
medicine.medical_specialty
medicine.diagnostic_test business.industry False Negative Reactions Physical examination Type 2 diabetes medicine.disease Confidence interval Heart failure Predictive value of tests Internal medicine medicine Cardiology Medical history Cardiology and Cardiovascular Medicine business Intensive care medicine Electrocardiography |
| Zdroj: | European Journal of Heart Failure. 17:187-195 |
| ISSN: | 1388-9842 |
| DOI: | 10.1002/ejhf.216 |
| Popis: | A total of 581 consecutive patients from 21 primary care practices in The Netherlands with type 2 diabetes, in whom the diagnosis of heart failure (HF) was not known, underwent an extensive diagnostic assessment, including medical history taking, physical examination, ECG, and echocardiography. The presence or absence of HF was established by a panel of two cardiologists and one general practitioner following the guidelines on HF of the European Society of Cardiology. In 161 patients, HF was considered present. A model based on the medical history and symptoms had a good discriminative value for detecting or excluding HF [C-statistic after bootstrapping 0.80; 95% confidence interval (CI) 0.76–0.83]. Adding signs improved the C-statistic to 0.82 (95% CI 0.79–0.86). A diagnostic screening score based on the clinical model had good discriminative properties applying a cut-off of 3 points (24.7% risk of HF) with sensitivity 70.8%, specificity 79.0%, negative predictive value 87.6%, and positive predictive value 56.4%. ECG and natriuretic peptides both had independent added value beyond the clinical model and increased the C-statistic to 0.86 (95% CI 0.83– 0.89). With a 20% threshold, the net reclassification of adding ECG and NT-proBNP to the clinical model was only 0.06. |
| Databáze: | OpenAIRE |
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