Nomogram Based on Cytokines for Cardiovascular Diseases in Xinjiang Kazakhs

Mediators Inflamm. 2019 May 5:2019:4756295. doi: 10.1155/2019/4756295. eCollection 2019.

Abstract

Background: This study involved the development of a predictive 5-year morbidity nomogram for cardiovascular diseases (CVD) in Xinjiang Kazakhs based on cytokine levels.

Methods: The nomogram was based on a baseline survey of the town of Nalati in the Kazakh Autonomous Prefecture of Xinjiang from 2009 to 2013. By 2016, we had monitored 1508 people for a median time of 5.17 years and identified CVD events in the study population by collecting case information from local hospitals. The study population was divided into the training (n = 1005) and validation cohorts (n = 503) in a 2 : 1 ratio. The area under the receiver operating characteristic curve (AUC) was used to verify the predictive accuracy of the nomogram. The result was assessed in a validation cohort.

Results: At the end of the study, the incidence of CVD in Xinjiang Kazakhs was found to be 11.28%. We developed a new nomogram to predict the 5-year incidence of CVD based on age, interleukin-6 (IL-6), and adiponectin (APN) levels, diastolic blood pressure, and dyslipidemia. The AUC for the predictive accuracy of the nomogram was 0.836 (95% confidence interval: 0.802-0.869), which was higher than that for IL-6 and APN. These results were supported by validation studies.

Conclusions: The nomogram model can more directly assess the risk of CVD in Kazakhs and can be used for CVD risk assessment.

MeSH terms

  • Aged
  • Blood Glucose / metabolism
  • Cardiovascular Diseases / blood
  • Cardiovascular Diseases / metabolism*
  • Cytokines / blood
  • Cytokines / metabolism*
  • Female
  • Humans
  • Lipoproteins, HDL / blood
  • Male
  • Middle Aged
  • Nomograms*
  • ROC Curve
  • Risk Assessment
  • Risk Factors
  • Triglycerides / blood
  • Waist Circumference / physiology

Substances

  • Blood Glucose
  • Cytokines
  • Lipoproteins, HDL
  • Triglycerides