Development and Validation of a Prognostic Model to Predict High-Risk Patients for Coronary Heart Disease in Snorers With Uncontrolled Hypertension

Abstract

PurposeSnoring or obstructive sleep apnea, with or without uncontrolled hypertension, is common and significantly increases the risk of coronary heart disease (CHD). The aim of this study was to develop and validate a prognostic model to predict and identify high-risk patients for CHD among snorers with uncontrolled hypertension.MethodsRecords from 1,822 snorers with uncontrolled hypertension were randomly divided into a training set (n = 1,275, 70%) and validation set (n = 547, 30%). Predictors for CHD were extracted to construct a nomogram model based on multivariate Cox regression analysis. We performed a single-split verification and 1,000 bootstraps resampling internal validation to assess the discrimination and consistency of the prediction model using area under the receiver operating characteristic curve (AUC) and calibration plots. Based on the linear predictors, a risk classifier for CHD could be set.ResultsAge, waist circumference (WC), and high- and low-density lipoprotein cholesterol (HDL-C and LDL-C) were extracted as the predictors to generate this nomogram model. The C-index was 0.720 (95% confidence interval 0.663–0.777) in the derivation cohort and 0.703 (0.630–0.776) in the validation cohort. The AUC was 0.757 (0.626–0.887), 0.739 (0.647–0.831), and 0.732 (0.665–0.799) in the training set and 0.689 (0.542–0.837), 0.701 (0.606–0.796), and 0.712 (0.615–0.808) in the validation set at 3, 5, and 8 years, respectively. The calibration plots showed acceptable consistency between the probability of CHD-free survival and the observed CHD-free survival in the training and validation sets. A total of more than 134 points in the nomogram can be used in the identification of high-risk patients for CHD among snorers with uncontrolled hypertension.ConclusionWe developed a CHD risk prediction model in snorers with uncontrolled hypertension, which includes age, WC, HDL-C, and LDL-C, and can help clinicians with early and quick identification of patients with a high risk for CHD.

The association of coronary non-calcified plaque loading based on coronary computed tomography angiogram and adverse cardiovascular events in patients with unstable coronary heart disease-a retrospective cohort study

“…In addition, the ROC curve analysis of this study showed that the diagnostic value of non-calcified plaque volume and loading for the recurrence of adverse cardiovascular events within 1 year in unstable CHD patients was comparable to that of carotid intima-media thickness, LVEF, hypertension, and so on. The carotid intima-media thickness, LVEF, and hypertension have been confirmed to be good predictors of adverse cardiovascular events (17)(18)(19)(20), which indicates that the use of CCTA to measure the volume and loading of non-calcified plaques is of good value in diagnosing adverse cardiovascular events that recur within 1 year in patients with unstable CHD.…”

Development and Validation of a Coronary Heart Disease Risk Prediction Model in Snorers with Hypertension: A Retrospective Observed Study

“…Our previous studies have demonstrated that WC is an important risk factor for CHD in snorers with uncontrolled hypertension. 27 We think that this is because WC is a better indicator of abdominal obesity in snorers than BMI. Epidemiological data show that snorers have increased abdominal obesity 1 and WC is positively associated with CHD.…”

“…The outcome was CHD that occurred during follow-up, including hospitalized angina, myocardial infarction, coronary revascularization and coronary death. 27 …”

Risk factors and prediction models for cardiovascular complications of hypertension in older adults with machine learning: A cross-sectional study

“…The initial step toward this goal is to identify the risk factors related to cardiovascular complications. Previous studies have demonstrated that cardiovascular complications may arise from multiple factors, including demographic and disease characteristics: age [ 7 ], sex [ 8 ], age of onset [ 9 ] and blood pressure [ 10 ]. Additionally, ultrasonography findings and several laboratory test results may also be factors correlated with cardiovascular complications and include uric acid [ 11 ], pro-brain (B-type) natriuretic peptide [ 7 ], serum lipid [ 8 ], homocysteine [ 12 ], and interventricular septum thickness [ 13 ].…”

“…Previous studies have demonstrated that cardiovascular complications may arise from multiple factors, including demographic and disease characteristics: age [ 7 ], sex [ 8 ], age of onset [ 9 ] and blood pressure [ 10 ]. Additionally, ultrasonography findings and several laboratory test results may also be factors correlated with cardiovascular complications and include uric acid [ 11 ], pro-brain (B-type) natriuretic peptide [ 7 ], serum lipid [ 8 ], homocysteine [ 12 ], and interventricular septum thickness [ 13 ]. Furthermore, anxiety and depression [ 14 , 15 ], diet [ 16 ], smoking, and drinking [ 17 , 18 ] may also contribute to the occurrence of cardiovascular complications.…”