Pulse Wave Velocity and Machine Learning to Predict Cardiovascular Outcomes in Prediabetic and Diabetic Populations.

Few studies have addressed the predictive value of arterial stiffness determined by pulse wave velocity (PWV) in a high-risk population with no prevalent cardiovascular disease and with obesity, hypertension, hyperglycemia, and preserved kidney function. This longitudinal, retrospective study enroll...

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Published in:Journal of Medical Systems Vol. 44; no. 1; pp. 1 - 11
Main Authors: Garcia-Carretero, Rafael, Vigil-Medina, Luis, Barquero-Perez, Oscar, Ramos-Lopez, Javier
Format: research tables/charts Journal Article
Published: Springer Nature Jan2020
Online Access:View this record in EBSCOhost
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      dt: Jan2020
      vid: 44
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      pub: Springer Nature
      place: New York, New York
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        atl: Pulse Wave Velocity and Machine Learning to Predict Cardiovascular Outcomes in Prediabetic and Diabetic Populations.
      aug:
        au:
          Garcia-Carretero, Rafael
          Vigil-Medina, Luis
          Barquero-Perez, Oscar
          Ramos-Lopez, Javier
        affil: Department of Internal Medicine, Mostoles University Hospital, Rey Juan Carlos University, Móstoles, Spain
      sug:
        subj:
          Arterial Stiffness Evaluation
          Pulse Wave Velocity
          Blood Pressure Monitoring, Ambulatory
          Cardiovascular Diseases
          Risk Assessment
          Diabetic Patients
          Prediabetic State
          Hypertension
          Models, Statistical
          Spain
          Human
          Retrospective Design
          Prospective Studies
          Special Populations
          Tonometry
          Survival Analysis
          Cox Proportional Hazards Model
          Confidence Intervals
          Machine Learning
          Descriptive Statistics
          Chi Square Test
          Mann-Whitney U Test
          Wilcoxon Rank Sum Test
          Data Analysis Software
          Multivariate Analysis
          Obesity
      ab: Few studies have addressed the predictive value of arterial stiffness determined by pulse wave velocity (PWV) in a high-risk population with no prevalent cardiovascular disease and with obesity, hypertension, hyperglycemia, and preserved kidney function. This longitudinal, retrospective study enrolled 88 high-risk patients and had a follow-up time of 12.4 years. We collected clinical and laboratory data, as well as information on arterial stiffness parameters using arterial tonometry and measurements from ambulatory blood pressure monitoring. We considered nonfatal, incident cardiovascular events as the primary outcome. Given the small size of our dataset, we used survival analysis (i.e., Cox proportional hazards model) combined with a machine learning-based algorithm/penalization method to evaluate the data. Our predictive model, calculated with Cox regression and least absolute shrinkage and selection operator (LASSO), included body mass index, diabetes mellitus, gender (male), and PWV. We recorded 16 nonfatal cardiovascular events (5 myocardial infarctions, 5 episodes of heart failure, and 6 strokes). The adjusted hazard ratio for PWV was 1.199 (95% confidence interval: 1.09–1.37, p < 0.001). Arterial stiffness was a predictor of cardiovascular disease development, as determined by PWV in a high-risk population. Thus, in obese, hypertensive, hyperglycemic patients with preserved kidney function, PWV can serve as a prognostic factor for major adverse cardiac events.
      pubtype: Academic Journal
      doctype:
        research
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        Journal Article
      ougenre: Article
    language: English
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