Key result
Clinical nomogram predicts moderate to severe OSA in chronic coronary syndrome with ~0.77 AUC.
Why the study?
Obstructive sleep apnea syndrome is common in patients with chronic coronary syndrome, but predictive models for OSAS in this population remain rarely reported.
Can a clinical nomogram based on routine variables predict moderate to severe obstructive sleep apnea in patients with chronic coronary syndrome?
Observational (n=527)
No
Can a clinical nomogram based on routine variables predict moderate to severe obstructive sleep apnea in patients with chronic coronary syndrome?
Effect estimate: AUC 0.771 (95% CI 0.731-0.811)
p-value: p=<0.001
A novel nomogram using routine clinical variables can effectively identify patients with chronic coronary syndrome who are at high risk for moderate to severe obstructive sleep apnea.
May aid OSA risk stratification in chronic coronary syndrome; hypothesis-generating pending prospective validation.
Background . Obstructive sleep apnea syndrome (OSAS) is common in patients with chronic coronary syndrome (CCS); however, a predictive model of OSAS in patients with CCS remains rarely reported. The study aimed to construct a novel nomogram scoring system to predict OSAS comorbidity in patients with CCS. Methods . Consecutive CCS patients scheduled for sleep monitoring at our hospital from January 2019 to September 2020 were enrolled in the current study. Coronary CT angiography or coronary angiography was used for the diagnosis of CCS, and clinical characteristics of the patients were collected. Significant predictors for OSAS in patients with moderate/severe CCS were estimated via logistic regression analysis, and a clinical nomogram was constructed. A calibration plot, examining discrimination (Harrell’s concordance index) and decision curve analysis (DCA), was applied to validate the nomogram’s predictive performance. Internal validity of the predictive model was assessed using bootstrapping (1000 replications). Results . The nomograms were constructed based on available clinical variables from 527 patients which were significantly associated with moderate/severe OSAS in patients with CCS, including body mass index, impaired glucose tolerance, hypertension, diabetes mellitus, nonalcoholic fatty liver disease, and routine laboratory indices such as neutrophil to lymphocyte ratio, platelet‐to‐lymphocyte ratio, high‐density lipoprotein cholesterol, and low‐density lipoprotein cholesterol. The C‐index (0.793) and AUC (0.771, 95% CI: 0.731–0.811) demonstrated a favorable discriminative ability of the nomogram. Moreover, calibration plots revealed consistency between moderate/severe OSAS predicted by the nomogram and validated by the results of sleep monitoring. Clinically, DCA showed that the nomogram had good discriminative ability to predict moderate/severe OSAS in patients with CCS. Conclusions . The risk nomogram constructed via the routinely available clinical variables in patients with CCS showed satisfying discriminative ability to predict comorbid moderate/severe OSAS, which may be useful for identification of high‐risk patients with OSAS in patients with CCS.
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Xu et al. (2022) conducted an observational in Chronic coronary syndrome (CCS) (n=527). Clinical and biochemical predictors (hypertension, diabetes mellitus, impaired glucose tolerance, NAFLD, BMI, HDL-C, LDL-C, NLR, PLR) was evaluated on Discriminative ability of the nomogram for moderate to severe OSAS (AUC) (AUC 0.771, 95% CI 0.731-0.811, p=<0.001). A clinical nomogram incorporating routine variables demonstrated favorable discriminative ability (AUC 0.771) to predict moderate to severe obstructive sleep apnea in patients with chronic coronary syndrome.
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