{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T22:02:41Z","timestamp":1755036161291,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643685274"}],"license":[{"start":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T00:00:00Z","timestamp":1721779200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,24]]},"abstract":"<jats:p>Visit-to-visit (VVV) blood pressure variability (BPV) is associated with cardiovascular disease. However, in practice, BPV at sequential clinic visits is often regarded as mere random fluctuations and frequently under-appreciated by the clinicians. Therefore, this meta-analysis aims to compare the effect size of VVV BPV on cardiovascular outcome, by comparing studies that have used the electronic health record (EHR) and non-EHR data. The pooled hazard ratio for VVV BPV is comparable between studies using EHR and non-EHR data. Studies using EHR reported a pooled hazard ratio (HR) for VVV systolic BPV of 1.22 (95% CI: 1.07-1.38), while non-EHR studies had a HR of 1.16 (95% CI: 1.10-1.22). The pooled HR for VVV diastolic BPV in EHR studies was 1.09 (95% CI: 0.86-1.39), whereas non-EHR studies showed a HR of 1.10 (95% CI: 1.04-1.17). EHR data is a reliable source for assessing BPV, which in turn can predict the CVD outcomes.<\/jats:p>","DOI":"10.3233\/shti240149","type":"book-chapter","created":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T11:04:57Z","timestamp":1721819097000},"source":"Crossref","is-referenced-by-count":1,"title":["Association Between Visit to Visit Blood Pressure Variability and Cardiovascular Outcome: A Meta-Analysis"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3971-7418","authenticated-orcid":false,"given":"Mifetika","family":"Lukitasari","sequence":"first","affiliation":[{"name":"PhD student, School of Population Health, UNSW Sydney, NSW 2052 Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9912-2344","authenticated-orcid":false,"given":"Jitendra","family":"Jonnagaddala","sequence":"additional","affiliation":[{"name":"Senior Research Fellow, School of Population Health, UNSW Sydney, NSW 2052 Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5989-3614","authenticated-orcid":false,"given":"Siaw-Teng","family":"Liaw","sequence":"additional","affiliation":[{"name":"Emeritus Professor, School of Population Health, UNSW Sydney, NSW 2052 Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7664-9621","authenticated-orcid":false,"given":"Bin","family":"Jalaludin","sequence":"additional","affiliation":[{"name":"Conjoint Professor, School of Population Health, UNSW Sydney, NSW 2052 Australia"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Innovation in Applied Nursing Informatics"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI240149","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T11:04:57Z","timestamp":1721819097000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI240149"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,24]]},"ISBN":["9781643685274"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti240149","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2024,7,24]]}}}