Development of a prediction model to target screening for high blood pressure in children
| Autor: | Jos W. R. Twisk, Marieke Welten, Daan Nieboer, Guannan Bai, Marlou L. A. de Kroon, Alet H. Wijga, Yvonne Vergouwe, Martijn W. Heymans, Marleen Hamoen, Hein Raat |
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| Přispěvatelé: | Erasmus MC other, Public Health, Public Health Research (PHR), Epidemiology and Data Science, APH - Personalized Medicine, ACS - Atherosclerosis & ischemic syndromes, APH - Methodology, APH - Health Behaviors & Chronic Diseases |
| Rok vydání: | 2018 |
| Předmět: |
Male
Pediatrics medicine.medical_specialty Percentile Epidemiology Population Overweight Logistic regression 01 natural sciences Risk Assessment Body Mass Index 03 medical and health sciences 0302 clinical medicine children Predictive Value of Tests Ethnicity Medicine Birth Weight Humans 030212 general & internal medicine Obesity Prospective Studies 0101 mathematics Overdiagnosis Prospective cohort study education Child Pregnancy education.field_of_study Models Statistical business.industry screening 010102 general mathematics Public Health Environmental and Occupational Health birth cohort medicine.disease prediction model Blood pressure Hypertension Female medicine.symptom business high blood pressure |
| Zdroj: | Preventive Medicine, 132. Academic Press Preventive Medicine, 132:105997. ACADEMIC PRESS INC ELSEVIER SCIENCE Preventive Medicine Preventive Medicine, 132:105997. Academic Press Inc. Hamoen, M, Welten, M, Nieboer, D, Bai, G, Heymans, M W, Twisk, J W R, Raat, H, Vergouwe, Y, Wijga, A H & de Kroon, M L A 2020, ' Development of a prediction model to target screening for high blood pressure in children ', Preventive Medicine, vol. 132, 105997 . https://doi.org/10.1016/j.ypmed.2020.105997 |
| ISSN: | 1096-0260 0091-7435 |
| Popis: | Targeted screening for childhood high blood pressure may be more feasible than routine blood pressure measurement in all children to avoid unnecessary harms, overdiagnosis or costs. Targeting maybe based e.g. on being overweight, but information on other predictors may also be useful. Therefore, we aimed to develop a multivariable diagnostic prediction model to select children aged 9-10 years for blood pressure measurement. Data from 5359 children in a population-based prospective cohort study were used. High blood pressure was defined as systolic or diastolic blood pressure ≥ 95th percentile for gender, age, and height. Logistic regression with backward selection was used to identify the strongest predictors related to pregnancy, child, and parent characteristics. Internal validation was performed using bootstrapping. 227 children (4.2%) had high blood pressure. The diagnostic model included maternal hypertensive disease during pregnancy, maternal BMI, maternal educational level, parental hypertension, parental smoking, child birth weight standard deviation score (SDS), child BMI SDS, and child ethnicity. The area under the ROC curve was 0.73, compared to 0.65 when using only child overweight. Using the model and a cut-off of 5% for predicted risk, sensitivity and specificity were 59% and 76%; using child overweight only, sensitivity and specificity were 47% and 84%. In conclusion, our diagnostic prediction model uses easily obtainable information to identify children at increased risk of high blood pressure, offering an opportunity for targeted screening. This model enables to detect a higher proportion of children with high blood pressure than a strategy based on child overweight only. |
| Databáze: | OpenAIRE |
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