Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea

Abstract

Among patients referred for OSA evaluation, routine polysomnographic data can identify physiological phenotypes that capture risk of adverse cardiovascular outcomes otherwise missed by conventional OSA severity classification.

Incorporating polysomnography into obstructive sleep apnoea phenotyping: moving towards personalised medicine for OSA

“…The longitudinal association between OSA clusters and continuous positive airway pressure (CPAP) adherence was first addressed by Gagnadoux et al 6 with reduced CPAP compliance in situations of an association between insomnia and OSA, or mild OSA and comorbid OSA. In the study of Zinchuck et al ,7 the percentage of patients with optimal CPAP adherence (>4 hours per night) varied broadly among clusters from 25% to 50%. The novelty here was to demonstrate in the whole study population that regular CPAP use was associated with a 36% decreased risk of primary outcome, but this attenuation varied by cluster.…”

Cerebrovascular Accident Risk in a Population with Periodic Limb Movements of Sleep: A Preliminary Meta-Analysis

“…With respect to randomized grouping, the patients with more severe PLM index were statistically older in the studies by Koo et al [8], Chen et al [7], Zinchuk et al [32], and Xie et al [33]. In the studies by Lindner et al [9] and Xie et al [33], there were significantly more male patients in the groups with more severe PLM index than in those with a less severe PLM index.…”

“…The sensitivity test via one study removed revealed that the main results of the meta-analysis became statistically insignificant after removing the datasets by Koo et al [8], Zinchuk et al [32], and Xie et al [33]. This may have been due to the smaller sample sizes after removing these datasets.…”

“…Meanwhile, the 4 studies (Chen et al [7], Koo et al [8], Zinchuk et al [32] and Lindner et al [9]) that reported the prevalence of CVA in patients with PLMS showed a general trend that a lower PLM index was correlated with a lower incidence of CVA. This was also seen in our random-effects meta-analysis models of the studies by Chen et al [7] and Xie et al [33] The person-time scale of the subgroup with a PLM index > 30 in the study by Xie et al [33] was 22,252 person-years, compared to 39,404 person-years in the subgroup with a PLM index < 30.…”

The ageing brain in sleep apnoea: paradoxical resilience, survival of the fittest, or simply comparing apples and oranges?

“…Over the last several decades, we have witnessed substantial increases in the granularity of the morbid phenotype of OSA, and such observations have prompted us to rethink some of the stricter early concepts. Among them, rather than viewing OSA as a single disease model that is applicable to all patients, we have formulated the conceptual framework of distinct phenotypes of OSA that may be driven by different mechanisms, link to different clinical manifestations, and display divergent responses to therapy [1][2][3][4][5][6]. In this contextual setting, the aspirational goals of the field are to first and foremost identify those OSA patients likely to benefit from treatment and administer the correct intervention, i.e.…”