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Variability: Analysis01:11

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Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
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Related Experiment Video

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Real-Time Monitoring and Modulation of Blood Pressure in a Rabbit Model of Ischemic Stroke
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Relation between Blood Pressure Variability within a Single Visit and Stroke.

Wei Ma1, Ying Yang1, Litong Qi1

  • 1Division of Cardiology, Peking University First Hospital, Dahongluochang Street, Xicheng District, Beijing 100034, China.

International Journal of Hypertension
|March 22, 2021
PubMed
Summary
This summary is machine-generated.

High blood pressure variability within a single visit, indicated by the white coat effect, is linked to an increased stroke risk. This finding highlights the importance of monitoring blood pressure changes during medical appointments.

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Area of Science:

  • Cardiology
  • Neurology
  • Public Health

Background:

  • Blood pressure variability (BPV) is a recognized risk factor for cardiovascular events.
  • The white coat effect (WCE), a measure of BPV within a single visit, is quantified by the difference between the first and subsequent blood pressure readings.
  • Understanding WCE's impact on stroke risk is crucial for cardiovascular event prediction.

Purpose of the Study:

  • To investigate the association between the white coat effect (WCE) and the risk of stroke.
  • To determine if BPV within a single clinical visit is an independent predictor of stroke.

Main Methods:

  • A cohort of 2,972 participants with three blood pressure measurements per visit was analyzed.
  • Participants were stratified into three groups based on WCE percentiles: normal range (WCE2.5-97.5), low WCE (WCE2.5), and high WCE (WCE97.5).
  • Multiple logistic regression was employed to assess the relationship between WCE and stroke, adjusting for established cardiovascular disease risk factors.

Main Results:

  • The low WCE group (WCE2.5) exhibited a significantly higher odds ratio (OR) for stroke (OR=2.78, p=0.015) compared to the normal WCE group.
  • After adjusting for cardiovascular risk factors, the OR for stroke in the low WCE group remained significant (OR=3.12, p=0.017).
  • A significant inverse association was observed between WCE and stroke risk (OR=0.93, p=0.036), suggesting that extreme WCE values, particularly low WCE, may be linked to increased stroke incidence.

Conclusions:

  • Blood pressure variability within a single visit, as indicated by the white coat effect, is significantly associated with an increased risk of stroke.
  • The magnitude and direction of blood pressure changes during a single visit may be important indicators of stroke risk.
  • Monitoring within-visit BPV could offer novel insights into stroke risk stratification and prevention strategies.