期刊
HYPERTENSION
卷 77, 期 2, 页码 640-649出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/HYPERTENSIONAHA.120.16303
关键词
blood pressure; cardiovascular; data analysis; mortality; risk
The addition of home and 24-hour blood pressure to office blood pressure significantly improves the prediction of cardiovascular and all-cause mortality, especially with the addition of home blood pressure. However, the quantitative improvement is modest, raising questions about the extended use of these methods in clinical practice.
Home and 24-hour blood pressure (BPHome and BP24h) are believed to improve the prognostic value of office BP (BPOffice) alone, but the evidence has limitations such as that (1) these 3 BPs are characterized by multicollinearity and (2) the procedures adopted do not allow quantification of the prognostic advantage. One thousand eight hundred thirty-three individuals belonging to the PAMELA (Pressioni Arteriose Monitorate e Loro Associazioni) were followed for 16 years. Prediction of cardiovascular and all-cause mortality was determined via the goodness of fit of individual data (Cox model), the area underlying the receiving operator curves and the net reclassification improvement of cardiovascular and all-cause mortality risk. Calculations were made for BPOffice alone and after addition of BPHome, BP24h, or both, limited to their residual portion which was found to be unexplained by, and thus independent on, BPOffice. With all methods addition of residual out-of-office systolic or diastolic BP to BPOffice significantly improved cardiovascular and all-cause mortality prediction. The improvement was more consistent when BPHome rather than BP24h was added to BPOffice and, compared with BPOffice plus BPHome, no better prediction was found when addition was extended to BP24h. With all additions, however, the improvement was quantitatively modest, which was the case also when data were separately analyzed in younger and older individuals or in dippers and nondippers. Thus, addition of out-of-office to BPOffice improves prediction of cardiovascular risk, even when data analysis avoids previous limitations. The improvement appears to be limited, however, which raises the question of the advantage to recommend their extended use in clinical practice.
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