366
Views
10
CrossRef citations to date
0
Altmetric
Research Articles

Pulse pressure and stroke risk: development and validation of a new stroke risk model

, , , , , , & show all
Pages 2453-2460 | Accepted 25 Sep 2014, Published online: 10 Oct 2014
 

Abstract

Objective:

This study aims to develop and validate a stroke risk model incorporating pulse pressure (PP) as a potential risk factor. Recent evidence suggests that PP, defined as the difference between systolic blood pressure (SBP) and diastolic blood pressure (DBP), could be an incremental risk factor beyond SBP.

Methods:

Electronic health records (EHRs) of hypertensive patients from a US integrated health delivery system were analyzed (January 2004 to May 2012). Patients with ≥1 PP reading and ≥6 months of observation prior to the first diagnosis of hypertension were randomly split into development (two-thirds of sample) and validation (one-third of sample) datasets. Stroke events were identified using ICD-9-CM 433.xx–436.xx. Cox proportional hazards models assessed time to first stroke event within 3 years of first hypertension diagnosis based on baseline risk factors, including PP, age, gender, diabetes, and cardiac comorbidities. The optimal model was selected using the least absolute shrinkage and selection operator (LASSO); performance was evaluated by the c-statistic.

Results:

Among 34,797 patients selected (mean age 59.3 years, 48% male), 4272 patients (12.3%) had a stroke. PP was higher among patients who developed stroke (mean [SD] PP, stroke: 02.0 [15.3] mmHg; non-stroke: 58.1 [14.0] mmHg, p < 0.001). The best performing risk model (c-statistic, development: 0.730; validation: 0.729) included PP (hazard ratio per mmHg increase: 1.0037, p < 0.001) as a significant risk factor.

Limitations:

This study was subject to limitations similar to other studies using EHRs. Only patient encounters occurring within the single healthcare network were captured in the data source. Though the model was tested internally, external validation (using a separate data source) would help assess the model’s generalizability and calibration.

Conclusions:

This stroke risk model shows that greater PP is a significant predictive factor for increased stroke risk, even in the presence of known risk factors. PP should be considered by practitioners along with established risk factors in stroke treatment strategies.

Transparency

Declaration of funding

This study was funded by Novartis.

Contributorship: R.A. served as principal author of the study. S.H.O., F.V., P.L., E.F., A.T., G.M. and M.S.D. had primary responsibility for study concept and design. R.A., F.V., P.L., E.F., and A.T. had primary responsibility for data handling. All authors contributed to data interpretation and analysis. R.A., E.F., and F.V. wrote the original manuscript. All authors contributed substantively to the revision of the manuscript.

Declaration of financial/other relationships

S.H.O. and G.M. have disclosed that they are employees of Novartis. R.A., F.V., P.L., E.F., A.T., and M.S.D. have disclosed that they are employees of Analysis Group, a company which has received research grants from Novartis.

CMRO peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Acknowledgment

The underlying work for the manuscript was previously accepted for podium presentation at the 23rd European Meeting on Hypertension and Cardiovascular Protection, Milan, June 14-17, 2013.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 681.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.