A clinic-based cluster analysis in patients with moderate-severe obstructive sleep apnea (OSA) in Chile

Clinical Application of the Multicomponent Grading System for Sleep Apnea Classification and Incident Cardiovascular Mortality

Objective  To evaluate the clinical utility of the Baveno classification in predicting incident cardiovascular mortality after five years of follow-up in a clinic-based cohort of patients with obstructive sleep apnea (OSA). Materials and Methods  We evaluated the reproducibility of the Baveno classification using data from the Santiago Obstructive Sleep Apnea (SantOSA) study. The groups were labeled Baveno A (minor symptoms and comorbidities), B (severe symptoms and minor comorbidities), C (minor symptoms and severe comorbidities), and D (severe symptoms and comorbidities). Within-group comparisons were performed using analysis of variance (ANOVA) and post hoc tests. The associations between groups and incident cardiovascular mortality were determined through the Mantel-Cox and Cox proportional hazard ratios (HRs) adjusted by covariables. Results  A total of 1,300 OSA patients were included (Baveno A: 27.7%; B: 28%; C: 16.8%; and D: 27.5%). The follow-up was of 5.4 years. Compared to Baveno A, the fully-adjusted risk of cardiovascular mortality with Baveno B presented an HR of 1.38 (95% confidence interval [95%CI]: 0.14-13.5; p  = 0.78); with Baveno C, it was of 1.71 (95%CI: 0.18-16.2; p  = 0.63); and, with Baveno D, of 1.04 (95%CI: 0.12-9.2; p  = 0.98). We found no interactions involving Baveno group, sex and OSA severity. Discussion  Among OSA patients, the Baveno classification can describe different subgroups. However, its utility in identifying incident cardiovascular mortality is unclear. Long-term follow-up studies and the inclusion of demographic variables in the classification could improve its ability to detect a high-risk phenotype associated with cardiovascular mortality. Conclusion  The Baveno classification serves as a valuable method for categorizing varying groups of patients afflicted with OSA. Nevertheless, its precision in identifying occurrence of cardiovascular mortality is still unclear.

Pulse rate variability predicted cardiovascular disease in sleep disordered breathing: The Guangdong sleep health study

OBJECTIVES

Pulse rate variability (PRV) predicts stroke in patients with sleep disordered breathing (SDB). However, the relationship between PRV and cardiovascular disease (CVD) was unknown in SDB.

METHODS

This was a cross-sectional study. Community residents in Guangdong were investigated. Sleep study were conducted with a type Ⅳ sleep monitoring. PRV parameters was assessed from the pulse waveforms derived from the sleep monitoring.

RESULTS

3747 participants were enrolled. The mean age was 53.9 ± 12.7 years. 1149 (30.7%) were diagnosed as SDB. PRV parameters, except for the averages of pulse-to-pulse intervals (ANN), were higher in participants with SDB than those without. After adjusting for traditional CVD risk factors, deceleration capacity of rate (DC), ANN, and the percentage of pulse-to-pulse interval differences that were more than 50 ms (PNN50) were correlated with CVD risk in participants with SDB (OR were 0.826, 1.002, and 1.285; P were 0.003, 0.009, and 0.010), but not in participants without SDB. There was no interaction effect between DC, ANN, PNN50 and oxygen desaturation index. In hierarchical analysis, DC and ANN were predictors for CVD in SDB patients with age <60 years, male, overweight, diabetes, and normal lipid metabolism. PNN50 was predictor for CVD in the elderly SDB patients without overweight, diabetes or dyslipidemia.

CONCLUSIONS

PRV parameters may be specific predictors for CVD in SDB. PNN50 was a potent biomarker for CVD risk in the elderly with SDB, event without traditional CVD risk factors.

Unmasking Heterogeneity of Sleep Apnea

Sleep apnea is heterogeneous in multiple dimensions. There are different physiological risk factors that may have clinical relevance. However, assessing them is challenging. An approach to ascertain them using a simple model of ventilatory control has been proposed. It is based, however, on untenable assumptions. There are limited validation data and reproducibility is not stellar. There are also different symptom subtypes. They have been found in multiple population-based and clinical cohorts worldwide. Symptomatic benefit from therapy is most marked in the excessively sleepy subtype. This group may also be the group at increased CV risk from obstructive sleep apnea.

The U-Shaped Association between Sleep Duration, All-Cause Mortality and Cardiovascular Risk in a Hispanic/Latino Clinically Based Cohort

Sleep is essential for life, and inappropriate sleep duration patterns may lead to chronic consequences regarding human health. Several studies have confirmed the presence of a U-shaped association between sleep duration and mortality. Moreover, many consequences related to cardiometabolic aspects have been suggested in patients with abnormal sleep durations. In this study, we analyzed the associations between sleep duration, total sleep time (TST), the risk of all-cause mortality, and 10-year cardiovascular risk in a cohort of patients at a sleep medicine center in Santiago, Chile. We conducted a prospective cohort study of patients (SantOSA). A short TST was defined as ≤6 h, a normal TST as 6 to 9 h, and a long TST as ≥9 h. Adjusted hazard ratios (aHRs) for all-cause mortality were calculated. A cross-sectional analysis between TST and 10-year cardiovascular risk (calculated using the Framingham 2008 formula) was determined using logistic regression models. A total of 1385 subjects were included in the results (78% male; median age: 53, interquartile range (IQR): 42-64 years; median BMI: 29.5, IQR: 16.7-33.1). A total of 333 subjects (24%) reported short TSTs, 938 (67.7%) reported normal TSTs, and 114 (8.3%) reported long TSTs. In the fully adjusted model, the association remained significant for short (aHR: 2.51 (1.48-4.25); p-value = 0.01) and long TSTs (aHR: 3.97 (1.53-10.29); p-value = 0.04). Finally, a U-shaped association was found between short and long TSTs, with an increase in cardiovascular risk at 10 years. Compared with normal TSTs, short (≤6 h) and long (≥9 h) TSTs were significantly associated with all-cause mortality and increased 10-year cardiovascular risk.

Multidimensional assessment and cluster analysis for OSA phenotyping

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is a heterogeneous disease with varying phenotype. A cluster analysis based on multidimensional disease characteristics, including symptom, anthropometry, polysomnography (PSG), and craniofacial morphology, in combination with auto-continuous positive airway pressure (CPAP) titration response and comorbidity profiles was performed within a well-characterized cohort of patients with OSA, with the aim to refine current phenotypic expressions of OSA with clinical implications.

METHODS

Two hundred and ninety-one subjects with a new diagnosis of moderate to severe OSA, referred for auto-CPAP titration to the sleep center were included for analysis. In-laboratory PSG and craniofacial computed tomography (CT) scanning was performed, followed by an auto-CPAP titration. The symptom of excessive daytime sleepiness (EDS) was assessed by Epworth sleepiness scale (ESS).

RESULTS

Three patient phenotypes, corresponding to the "normal weight, non-sleepy and moderate OSA", the "obese, non-sleepy and severe OSA" and "obese, sleepy, very severe OSA with craniofacial limitation" were identified. Among the PSG parameters, only N3% and mean pulse oxygen saturation (SPO₂) were found to be associated with ESS, and they only explain small fraction of the variation (R²=0.136). Neck circumference and craniofacial limitation were associated the more severe phenotype, which had higher prevalence of hypertension, metabolic syndrome, greater diurnal blood gas abnormalities and worse PAP titration response.

CONCLUSIONS

Three OSA phenotypes were identified according to multiple aspect of clinical features in patients with moderate to severe OSA, which differed in prevalence of hypertension, metabolic syndrome, diurnal blood gas parameters and CPAP titration response. Self-reported EDS was not related with the severity of sleep breathing disturbance, and craniofacial limitation was associated the more severe phenotype. These findings highlight the necessity of integrate multiple disease characters into phenotyping to achieve better understanding of the clinical pictures of OSA.

A Validation Study of Four Different Cluster Analyses of OSA and the Incidence of Cardiovascular Mortality in a Hispanic Population

BACKGROUND

Previous studies reported a strong association between sleepiness-related symptoms and comorbidities with poor cardiovascular outcomes among patients with moderate to severe OSA (msOSA). However, the validation of these associations in the Hispanic population from South America and the ability to predict incident cardiovascular disease remain unclear.

RESEARCH QUESTION

In Hispanic patients with msOSA, are four different cluster analyses reproducible and able to predict incident cardiovascular mortality?

STUDY DESIGN AND METHODS

Using the SantOSA cohort, we reproduced four cluster analyses (Sleep Heart Health Study [SHHS], Icelandic Sleep Apnea Cohort [ISAC], Sleep Apnea Cardiovascular Endpoints [SAVE], and The Institute de Recherche en Sante Respiratoire des Pays de la Loire [IRSR] cohorts) following a cluster analysis similar to each training dataset. The incidence of cardiovascular mortality was constructed using a Kaplan-Meier (log-rank) model, and Cox proportional hazards models were adjusted by confounders.

RESULTS

Among 780 patients with msOSA in our cohort, two previous cluster analyses (SHHS and ISAC) were reproducible. The SAVE and IRSR cluster analyses were not reproducible in our sample. We identified the following subtypes for SHHS: "minimally symptomatic," "disturbed sleep," "moderate sleepiness," and "severe sleepiness." For ISAC, three different subtypes ("minimally symptomatic," "disturbed sleep," and "excessive sleepiness") were similar to the original dataset. Compared with "minimally symptomatic," we found a significant association between "excessive sleepiness" and cardiovascular mortality after 5 years of follow-up in SantOSA, hazard ratio (HR), 5.47; 95%CI, 1.74-8.29; P < .01; and HR, 3.23; 95%CI, 1.21-8.63; P = .02, using the SHHS and ISAC cluster analyses, respectively.

INTERPRETATION

Among patients with msOSA, a symptom-based approach can validate different OSA patient subtypes, and those with excessive sleepiness have an increased risk of incident cardiovascular mortality in the Hispanic population from South America.

Comorbidity clusters in patients with moderate-to-severe OSA

PURPOSE

Obstructive sleep apnea (OSA) is a prevalent and multifaceted disease. To date, the presence and severity of objectively identified comorbidities and their association with specific OSA phenotypes, CPAP adherence, and survival remain to be elucidated. The aim of this study is to cluster patients with OSA based on 10 clinically important objectively identified comorbidities, and to characterize the comorbidity clusters in terms of clinical and polysomnographic characteristics, CPAP adherence, and survival.

STUDY DESIGN AND METHODS

Seven hundred ten consecutive patients starting CPAP for moderate-to-severe OSA were included. Comorbidities were based on generally accepted cutoffs identified in the peer-reviewed literature. Self-organizing maps were used to order patients based on presence and severity of their comorbidities and to generate clusters.

RESULTS

The majority of patients were men (80%). They were generally middle-aged (52 years) and obese (BMI: 31.5 kg/m²). Mean apnea-hypopnea index (AHI) was 41 ± 20 per h of sleep. More than 94% of the patients had one or more comorbidities with arterial hypertension, dyslipidemia, and obesity being the most prevalent. Nine comorbidity clusters were identified. The clinical relevance of these comorbidity clusters was highlighted by the difference in symptoms, PSG parameters, and cardiovascular risk. Also, differences in CPAP adherence, improvements in ESS, and long-term survival were present between the clusters.

CONCLUSION

Comorbidity prevalence in patients with OSA is high, and different comorbidity clusters, demonstrating differences in cardiovascular risk, CPAP adherence, and survival, can be identified. These results further substantiate the need for a comprehensive assessment of patients with OSA beyond the AHI.

Clusters of sleep apnoea phenotypes: A large pan-European study from the European Sleep Apnoea Database (ESADA)

BACKGROUND AND OBJECTIVE

To personalize OSA management, several studies have attempted to better capture disease heterogeneity by clustering methods. The aim of this study was to conduct a cluster analysis of 23 000 OSA patients at diagnosis using the multinational ESADA.

METHODS

Data from 34 centres contributing to ESADA were used. An LCA was applied to identify OSA phenotypes in this European population representing broad geographical variations. Many variables, including symptoms, comorbidities and polysomnographic data, were included. Prescribed medications were classified according to the ATC classification and this information was used for comorbidity confirmation.

RESULTS

Eight clusters were identified. Four clusters were gender-based corresponding to 54% of patients, with two clusters consisting only of men and two clusters only of women. The remaining four clusters were mainly men with various combinations of age range, BMI, AHI and comorbidities. The preferred type of OSA treatment (PAP or mandibular advancement) varied between clusters.

CONCLUSION

Eight distinct clinical OSA phenotypes were identified in a large pan-European database highlighting the importance of gender-based phenotypes and the impact of these subtypes on treatment prescription. The impact of cluster on long-term treatment adherence and prognosis remains to be studied using the ESADA follow-up data set.