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Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction : An Individual-Participant-Data Meta-Analysis
- Source :
- American Journal of Epidemiology 186 (2017) 8, American Journal of Epidemiology, 186(8), 899, Am. J. Epidemiol. 186, 899-907 (2017), American Journal of Epidemiology, Paige, E, Barrett, J, Pennells, L, Sweeting, M, Willeit, P, Di Angelantonio, E, Gudnason, V, Nordestgaard, B G, Psaty, B M, Goldbourt, U, Best, L G, Assmann, G, Salonen, J T, Nietert, P J, Verschuren, W M M, Brunner, E J, Kronmal, R A, Salomaa, V, Bakker, S J L, Dagenais, G R, Sato, S, Jansson, J-H, Willeit, J, Onat, A, de la Cámara, A G, Roussel, R, Völzke, H, Dankner, R, Tipping, R W, Meade, T W, Donfrancesco, C, Kuller, L H, Peters, A, Gallacher, J, Kromhout, D, Iso, H, Knuiman, M, Casiglia, E, Kavousi, M, Palmieri, L, Sundström, J, Davis, B R, Njølstad, I, Couper, D, Danesh, J, Thompson, S G & Wood, A 2017, ' Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction : An Individual-Participant-Data Meta-Analysis ', American Journal of Epidemiology, vol. 186, no. 8, pp. 899-907 . https://doi.org/10.1093/aje/kwx149, American Journal of Epidemiology, 186(8), 899-907, American Journal of Epidemiology, 186(8), 899-907. Oxford University Press
- Publication Year :
- 2017
- Publisher :
- Uppsala universitet, Kardiologi, 2017.
-
Abstract
- The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.
- Subjects :
- Adult
MODELS
Blood Pressure
Cholesterol/blood
Risk Assessment
risk prediction
Systematic Reviews, Meta- and Pooled Analyses
SDG 3 - Good Health and Well-being
cardiovascular disease
MULTIPLE
Humans
risk factors
CORONARY-HEART-DISEASE
longitudinal measurements
Cardiac and Cardiovascular Systems
Risk Assessment/methods
repeated measurements
Human Nutrition & Health
Aged
Cardiovascular Disease
Longitudinal Measurements
Repeated Measurements
Risk Factors
Risk Prediction
repeated risk factors
Kardiologi
Cardiovascular Diseases/epidemiology
Humane Voeding & Gezondheid
Blood Pressure Determination
Public Health, Global Health, Social Medicine and Epidemiology
Middle Aged
3142 Public health care science, environmental and occupational health
VARIABILITY
Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi
Cholesterol
Cardiovascular Diseases
Female
Subjects
Details
- Language :
- English
- ISSN :
- 00029262
- Database :
- OpenAIRE
- Journal :
- American Journal of Epidemiology 186 (2017) 8, American Journal of Epidemiology, 186(8), 899, Am. J. Epidemiol. 186, 899-907 (2017), American Journal of Epidemiology, Paige, E, Barrett, J, Pennells, L, Sweeting, M, Willeit, P, Di Angelantonio, E, Gudnason, V, Nordestgaard, B G, Psaty, B M, Goldbourt, U, Best, L G, Assmann, G, Salonen, J T, Nietert, P J, Verschuren, W M M, Brunner, E J, Kronmal, R A, Salomaa, V, Bakker, S J L, Dagenais, G R, Sato, S, Jansson, J-H, Willeit, J, Onat, A, de la Cámara, A G, Roussel, R, Völzke, H, Dankner, R, Tipping, R W, Meade, T W, Donfrancesco, C, Kuller, L H, Peters, A, Gallacher, J, Kromhout, D, Iso, H, Knuiman, M, Casiglia, E, Kavousi, M, Palmieri, L, Sundström, J, Davis, B R, Njølstad, I, Couper, D, Danesh, J, Thompson, S G & Wood, A 2017, ' Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction : An Individual-Participant-Data Meta-Analysis ', American Journal of Epidemiology, vol. 186, no. 8, pp. 899-907 . https://doi.org/10.1093/aje/kwx149, American Journal of Epidemiology, 186(8), 899-907, American Journal of Epidemiology, 186(8), 899-907. Oxford University Press
- Accession number :
- edsair.pmid.dedup....8eabc86a22a05afd96b84b4219382ab4