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Development and validation of a risk prediction model in patients with adult congenital heart disease

VJM. Baggen, E. Venema, R. Živná, AE. van den Bosch, JA. Eindhoven, M. Witsenburg, JAAE. Cuypers, E. Boersma, H. Lingsma, JR. Popelová, JW. Roos-Hesselink,

. 2019 ; 276 (-) : 87-92. [pub] 20180822

Jazyk angličtina Země Nizozemsko

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc19035036

AIMS: To develop and validate a clinically useful risk prediction tool for patients with adult congenital heart disease (ACHD). METHODS AND RESULTS: A risk model was developed in a prospective cohort of 602 patients with moderate/complex ACHD who routinely visited the outpatient clinic of a tertiary care centre in the Netherlands (2011-2013). This model was externally validated in a retrospective cohort of 402 ACHD patients (Czech Republic, 2004-2013). The primary endpoint was the 4-year risk of death, heart failure, or arrhythmia, which occurred in 135 of 602 patients (22%). Model development was performed using multivariable logistic regression. Model performance was assessed with C-statistics and calibration plots. Of the 14 variables that were selected by an expert panel, the final prediction model included age (OR 1.02, 95%CI 1.00-1.03, p = 0.031), congenital diagnosis (OR 1.52, 95%CI 1.03-2.23, p = 0.034), NYHA class (OR 1.74, 95%CI 1.07-2.84, p = 0.026), cardiac medication (OR 2.27, 95%CI 1.56-3.31, p < 0.001), re-intervention (OR 1.41, 95%CI 0.99-2.01, p = 0.060), BMI (OR 1.03, 95%CI 0.99-1.07, p = 0.123), and NT-proBNP (OR 1.63, 95%CI 1.45-1.84, p < 0.001). Calibration-in-the-large was suboptimal, reflected by a lower observed event rate in the validation cohort (17%) than predicted (36%), likely explained by heterogeneity and different treatment strategies. The externally validated C-statistic was 0.78 (95%CI 0.72-0.83), indicating good discriminative ability. CONCLUSION: The proposed ACHD risk score combines six readily available clinical characteristics and NT-proBNP. This tool is easy to use and can aid in distinguishing high- and low-risk patients, which could further streamline counselling, location of care, and treatment in ACHD.

Citace poskytuje Crossref.org

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$a AIMS: To develop and validate a clinically useful risk prediction tool for patients with adult congenital heart disease (ACHD). METHODS AND RESULTS: A risk model was developed in a prospective cohort of 602 patients with moderate/complex ACHD who routinely visited the outpatient clinic of a tertiary care centre in the Netherlands (2011-2013). This model was externally validated in a retrospective cohort of 402 ACHD patients (Czech Republic, 2004-2013). The primary endpoint was the 4-year risk of death, heart failure, or arrhythmia, which occurred in 135 of 602 patients (22%). Model development was performed using multivariable logistic regression. Model performance was assessed with C-statistics and calibration plots. Of the 14 variables that were selected by an expert panel, the final prediction model included age (OR 1.02, 95%CI 1.00-1.03, p = 0.031), congenital diagnosis (OR 1.52, 95%CI 1.03-2.23, p = 0.034), NYHA class (OR 1.74, 95%CI 1.07-2.84, p = 0.026), cardiac medication (OR 2.27, 95%CI 1.56-3.31, p < 0.001), re-intervention (OR 1.41, 95%CI 0.99-2.01, p = 0.060), BMI (OR 1.03, 95%CI 0.99-1.07, p = 0.123), and NT-proBNP (OR 1.63, 95%CI 1.45-1.84, p < 0.001). Calibration-in-the-large was suboptimal, reflected by a lower observed event rate in the validation cohort (17%) than predicted (36%), likely explained by heterogeneity and different treatment strategies. The externally validated C-statistic was 0.78 (95%CI 0.72-0.83), indicating good discriminative ability. CONCLUSION: The proposed ACHD risk score combines six readily available clinical characteristics and NT-proBNP. This tool is easy to use and can aid in distinguishing high- and low-risk patients, which could further streamline counselling, location of care, and treatment in ACHD.
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$a Venema, Esmee $u Department of Public Health, Erasmus Medical Centre, Rotterdam, the Netherlands; Department of Neurology, Erasmus Medical Centre, Rotterdam, the Netherlands.
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$a Živná, Renata $u Department of Cardiac Surgery, Hospital Na Homolce, Prague, Czech Republic; Pediatric Heart Centre, Faculty Hospital Motol, Prague, Czech Republic.
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$a van den Bosch, Annemien E $u Department of Cardiology, Erasmus Medical Centre, Rotterdam, the Netherlands.
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$a Boersma, Eric $u Department of Cardiology, Erasmus Medical Centre, Rotterdam, the Netherlands; Cardiovascular Research School COEUR, Rotterdam, the Netherlands; Department of Clinical Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands.
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$a Lingsma, Hester $u Department of Public Health, Erasmus Medical Centre, Rotterdam, the Netherlands.
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$a Popelová, Jana R $u Department of Cardiac Surgery, Hospital Na Homolce, Prague, Czech Republic; Pediatric Heart Centre, Faculty Hospital Motol, Prague, Czech Republic.
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$a Roos-Hesselink, Jolien W $u Department of Cardiology, Erasmus Medical Centre, Rotterdam, the Netherlands. Electronic address: j.roos@erasmusmc.nl.
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