Association Between Obstructive Sleep Apnea and Metabolic Abnormalities in Patients With Hypertrophic Cardiomyopathy

Machine learning-based detection of sleep-disordered breathing in hypertrophic cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is often concomitant with sleep-disordered breathing (SDB), which can cause adverse cardiovascular events. Although an appropriate approach to SDB prevents cardiac remodelling, detection of concomitant SDB in patients with HCM remains suboptimal. Thus, we aimed to develop a machine learning-based discriminant model for SDB in HCM.

METHODS

In the present multicentre study, we consecutively registered patients with HCM and performed nocturnal oximetry. The outcome was a high Oxygen Desaturation Index (ODI), defined as 3% ODI >10, which significantly correlated with the presence of moderate or severe SDB. We randomly divided the whole participants into a training set (80%) and a test set (20%). With data from the training set, we developed a random forest discriminant model for high ODI based on clinical parameters. We tested the ability of the discriminant model on the test set and compared it with a previous logistic regression model for distinguishing SDB in patients with HCM.

RESULTS

Among 369 patients with HCM, 228 (61.8%) had high ODI. In the test set, the area under the receiver operating characteristic curve of the discriminant model was 0.86 (95% CI 0.77 to 0.94). The sensitivity was 0.91 (95% CI 0.79 to 0.98) and specificity was 0.68 (95% CI 0.48 to 0.84). When the test set was divided into low-probability and high-probability groups, the high-probability group had a higher prevalence of high ODI than the low-probability group (82.4% vs 17.4%, OR 20.9 (95% CI 5.3 to 105.8), Fisher's exact test p<0.001). The discriminant model significantly outperformed the previous logistic regression model (DeLong test p=0.03).

CONCLUSIONS

Our study serves as the first to develop a machine learning-based discriminant model for the concomitance of SDB in patients with HCM. The discriminant model may facilitate cost-effective screening tests and treatments for SDB in the population with HCM.

Implication of sleep apnea for cardiac remodeling in patients with hypertrophic cardiomyopathy

OBJECTIVES

Cardiac remodeling is a life-long process in hypertrophic cardiomyopathy (HCM), and if uncontrolled, would cause substantial morbidity and mortality. Sleep apnea (SA) is a common comorbidity in HCM. This study aimed to investigate the relationship between SA and cardiac remodeling in a large series of patients with HCM.

METHODS

A total of 606 patients with HCM who underwent sleep evaluations at Fuwai Hospital were included. Parameters of cardiac remodeling were evaluated by echocardiographic studies.

RESULTS

SA was present in 363 (59.9%) patients. Left ventricular (LV) end-diastolic diameter (P < 0.001), left atrial (LA) diameter (P = 0.024), ascending aortic diameter (P < 0.001) all increased and maximal end-diastolic wall thickness (P < 0.001) decreased with the severity of SA. After adjustment for sex, age, body mass index, hypertension, hyperlipidemia, diabetes, coronary artery disease and cigarette use, log (apnea-hypopnea index+1) was independently correlated with increasing LV end-diastolic diameter (β = 0.729, P = 0.003) and deceasing maximal end-diastolic wall thickness (β = -0.503, P = 0.009). Log (percentage of total sleep time spent with oxygen saturation<90% + 1) was independently correlated with increasing LV end-diastolic diameter (β = 0.609, P = 0.004) and LA diameter (β = 0.695, P = 0.006). Severity of SA (severe SA with odds ratio, 2.38; 95% CI, 1.20-4.70; P = 0.013), log (apnea-hypopnea index+1) (OR, 1.28; 95% CI, 1.01-1.63; P = 0.045) and log (percentage of total sleep time spent with oxygen saturation<90% + 1) (OR, 1.31; 95% CI, 1.08-1.59; P = 0.006) were also independently associated with LV enlargement.

CONCLUSIONS

Severity of SA is independently associated with cardiac remodeling indicating a trend toward enlarged chamber size and thinned wall. Clinical trials are required to determine whether treatment of SA improves cardiac remodeling and long-term outcomes in patients with HCM.

Association of Types of Sleep Apnea and Nocturnal Hypoxemia with Atrial Fibrillation in Patients with Hypertrophic Cardiomyopathy

BACKGROUND

Data regarding the association between sleep apnea (SA) and atrial fibrillation (AF) in hypertrophic cardiomyopathy (HCM) are still limited. We aim to investigate the association of both types of SA, obstructive sleep apnea (OSA) and central sleep apnea (CSA), and nocturnal hypoxemia with AF in HCM.

METHODS

A total of 606 patients with HCM who underwent sleep evaluations were included. Logistic regression was used to assess the association between sleep disorder and AF.

RESULTS

SA was presented in 363 (59.9%) patients, of whom 337 (55.6%) had OSA and 26 (4.3%) had CSA. Patients with SA were older, more often male, had a higher body mass index, and more clinical comorbidities. Prevalence of AF was higher in patients with CSA than patients with OSA and without SA (50.0% versus 24.9% and 12.8%, p < 0.001). After adjustment for age, sex, body mass index, hypertension, diabetes mellitus, cigarette use, New York Heart Association class and severity of mitral regurgitation, SA (OR, 1.79; 95% CI, 1.09-2.94) and nocturnal hypoxemia (higher tertile of percentage of total sleep time with oxygen saturation < 90% [OR, 1.81; 95% CI, 1.05-3.12] compared with lower tertile) were significantly associated with AF. The association was much stronger in the CSA group (OR, 3.98; 95% CI, 1.56-10.13) than in OSA group (OR, 1.66; 95% CI, 1.01-2.76). Similar associations were observed when analyses were restricted to persistent/permanent AF.

CONCLUSION

Both types of SA and nocturnal hypoxemia were independently associated with AF. Attention should be paid to the screening of both types of SA in the management of AF in HCM.

Serum sTREM2: A Potential Biomarker for Mild Cognitive Impairment in Patients With Obstructive Sleep Apnea

Objective

Cognitive impairment is a common comorbidity in patients with obstructive sleep apnea (OSA) that leads to poor quality of life and a heavier medical burden. However, the assessment and longitudinal tracking of cognitive impairment in OSA is challenging. This study aimed to examine the alternation and related factors of serum soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in patients with OSA, and to explore whether serum sTREM2 could be a biomarker for mild cognitive impairment in OSA patients.

Methods

A total of 94 OSA patients and 13 snoring subjects were enrolled in this cross-sectional study. Demographic information, questionnaires, and polysomnography results were collected. Serum sTREM2 levels were quantified using an enzyme-linked immunosorbent assay. Multivariate linear regression was used to analyze the factors influencing sTREM2, and the receiver operating characteristic curve was used to assess the predictive value of serum sTREM2 for mild cognitive impairment in patients with OSA.

Results

Patients with OSA had higher serum sTREM2 levels than the controls. Multivariate linear regression analysis showed that serum sTREM2 levels in patients with OSA were associated with the Montreal Cognitive Assessment score and oxygen depletion index levels. Additionally, serum sTREM2 levels were higher in OSA patients with mild cognitive impairment (MCI) than in those without. The receiver operating characteristic curve showed that at a cutoff value of >18,437 pg/ml, the sensitivity of serum sTREM2 to predict MCI in OSA was 64.62%, the specificity was 68.97%, and the area under the curve was 0.70 (95% CI: 0.58–0.81).

Conclusion

Serum sTREM2 levels were elevated in patients with OSA, particularly in those with MCI. It therefore has the potential to be a biomarker for MCI in OSA patients.