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A scalable method of determining physiological endotypes of sleep apnea from a polysomnographic sleep study.

ABSTRACT: Sleep apnea is caused by several endophenotypic traits, namely pharyngeal collapsibility, poor muscle compensation, ventilatory instability (high loop gain), and arousability from sleep (low arousal threshold). Measures of these traits have shown promise for predicting outcomes of therapies (e.g. oral appliances, surgery, hypoglossal nerve stimulation, CPAP, and pharmaceuticals), which may become an integral part of precision sleep medicine. Currently, the methods Sands et al. developed for endotyping sleep apnea from polysomnography (PSG) are embedded in the original authors' code, which is computationally expensive and requires technological expertise to run. We present a reimplementation and validation of the integrity of the original authors' code by reproducing the endo-Phenotyping Using Polysomnography (PUP) method of Sands et al. The original MATLAB methods were reprogrammed in Python; efficient algorithms were developed to detect breaths, calculate normalized ventilation (moving time-average), and model ventilatory drive (intended ventilation). The new implementation (PUPpy) was validated by comparing the endotypes from PUPpy with the original PUP results. Both endotyping methods were applied to 38 manually scored polysomnographic studies. Results of the new implementation were strongly correlated with the original (p < 10-6 for all): ventilation at eupnea V??passive (ICC = 0.97), ventilation at arousal onset V??active (ICC = 0.97), loop gain (ICC = 0.96), and arousal threshold (ICC = 0.90). We successfully implemented the original PUP method by Sands et al. providing further evidence of its integrity. Additionally, we created a cloud-based version for scaling up sleep apnea endotyping that can be used more easily by a wider audience of researchers and clinicians.

SUBMITTER: Finnsson E

PROVIDER: S-EPMC7819840 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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A scalable method of determining physiological endotypes of sleep apnea from a polysomnographic sleep study.

Finnsson Eysteinn E Ólafsdóttir Guðrún H GH Loftsdóttir Dagmar L DL Jónsson Sigurður Æ SÆ Helgadóttir Halla H Ágústsson Jón S JS Sands Scott A SA Wellman Andrew A

Sleep 20210101 1

Sleep apnea is caused by several endophenotypic traits, namely pharyngeal collapsibility, poor muscle compensation, ventilatory instability (high loop gain), and arousability from sleep (low arousal threshold). Measures of these traits have shown promise for predicting outcomes of therapies (e.g. oral appliances, surgery, hypoglossal nerve stimulation, CPAP, and pharmaceuticals), which may become an integral part of precision sleep medicine. Currently, the methods Sands et al. developed for endo ...[more]

PMID: 32929467

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Project description:Rationale: Oral appliance therapy is efficacious in many patients with obstructive sleep apnea (OSA), but prediction of treatment outcome is challenging. Small, detailed physiological studies have identified key OSA endotypic traits (pharyngeal collapsibility and loop gain) as determinants of greater oral appliance efficacy.Objectives: We used a clinically applicable method to estimate OSA traits from routine polysomnography and identify an endotype-based subgroup of patients expected to show superior efficacy.Methods: In 93 patients (baseline apnea-hypopnea index [AHI], ≥20 events/h), we examined whether polysomnography-estimated OSA traits (pharyngeal: collapsibility and muscle compensation; nonpharyngeal: loop gain, arousal threshold, and ventilatory response to arousal) were associated with oral appliance efficacy (percentage reduction in AHI from baseline) and could predict responses to treatment. Multivariable regression (with interactions) defined endotype-based subgroups of "predicted" responders and nonresponders (based on 50% reduction in AHI). Treatment efficacy was compared between the predicted subgroups (with cross-validation).Results: Greater oral appliance efficacy was associated with favorable nonpharyngeal traits (lower loop gain, higher arousal threshold, and lower response to arousal), moderate (nonmild, nonsevere) pharyngeal collapsibility, and weaker muscle compensation (overall R2 = 0.30; adjusted R2 = 0.19; P = 0.003). Predicted responders (n = 54), compared with predicted nonresponders (n = 39), exhibited a greater reduction in AHI from baseline (mean [95% confidence interval], 73% [66-79] vs. 51% [38-61]; P < 0.0001) and a lower treatment AHI (8 [6-11] vs. 16 [12-20] events/h; P = 0.002). Differences persisted after adjusting for clinical covariates (including baseline AHI, body mass index, and neck circumference).Conclusions: Quantifying OSA traits using clinical polysomnography can identify an endotype-based subgroup of patients that is highly responsive to oral appliance therapy. Prospective validation is warranted.

Project description:BackgroundA high comorbidity between attention-deficit/hyperactivity disorder (ADHD) and obstructive sleep apnea (OSA) as well as similar impairments across neurobehavioral outcomes has been described in children. However, there is a paucity of research examining the comorbidity of these two disorders in adolescents. This study examined the association of OSA with sleep, neurobehavioral, and cardiometabolic outcomes in adolescents with ADHD from the general population.Methods421 adolescents (16.9 ± 2.3 years, 53.9% male) underwent 9-hr polysomnography, neurobehavioral, and physical evaluation. ADHD was ascertained by a parent-or-self-report of a lifetime diagnosis/treatment of ADHD. OSA was defined as an apnea hypopnea index of ≥2 events/hour. Groups of controls (n = 208), OSA-alone (n = 115), ADHD-alone (n = 54), and ADHD+OSA (n = 44) were studied. Multivariable-adjusted general linear models tested group differences in PSG parameters, neurobehavioral, and cardiometabolic outcomes after controlling for sex, race/ethnicity, age, and/or body mass index percentile.ResultsThe ADHD+OSA group had significantly longer sleep onset latency, shorter total sleep time, lower sleep efficiency, and higher percent of stage 1 sleep, as compared with all other groups, however, these differences were diminished by excluding adolescents on psychoactive medication. The ADHD-alone group showed significantly higher periodic limb movements than controls. The ADHD+OSA and ADHD-alone groups did not significantly differ on any measure of neurocognitive or behavioral functioning. The ADHD+OSA and OSA-alone groups showed significantly worse cardiometabolic and inflammatory biomarkers when compared to controls or the ADHD-alone, but did not significantly differ between each other.ConclusionsAdolescents with a diagnosis ADHD+OSA showed phenotypic risk factors for OSA (i.e., overweight/obesity, visceral adiposity, metabolic syndrome, and inflammation) but not worse neurobehavioral outcomes when compared with ADHD-alone. While comorbidity is possible, these data support that adolescents with a suspicion of ADHD should be screened for OSA, before a diagnosis is reached and psychoactive medication initiated.

Project description:Study objectivesVideo-polysomnography (v-PSG) is the gold standard for the diagnosis of sleep disorders. Quantitative assessment of type and distribution of physiological movements during sleep for the differentiation between physiological and pathological motor activity is lacking. We performed a systematic and detailed analysis of movements during physiological sleep using v-PSG technology.DesignProspective v-PSG investigation.SettingAcademic referral center sleep laboratory.ParticipantsOne hundred healthy sleepers aged 19-77 years recruited from a representative population sample after a two-step screening.InterventionsN/A.Measurements and resultsAll subjects underwent v-PSG. In all cases where electromyographic activity > 100 msec duration was visible during sleep in the mentalis, submentalis, flexor digitorum superficialis, or anterior tibialis muscles, the time-synchronized video was analyzed. Visible movements were classified according to movement type and topography, and movement rates were computed for the different sleep stages. A total of 9,790 movements (median 10.2/h, IQR 4.6-16.2) were analyzed: 99.7% were elementary, 0.3% complex. Movement indices were higher in men than women (men: median 13/h, interquartile range 7.1-29.3, women: median 7.9/h, interquartile range 3.4-14.5; P = 0.006). The majority of movements involved the extremities (87.9%) and were classified as focal (53.3%), distal (79.6%), and unilateral (71.5%); 15.3% of movements were associated with arousals. REM-related movements (median 0.8 sec, IQR 0.5-1.2) were shorter than NREM-related movements (median 1.1 sec, IQR 0.8-1.6; P = 0.001). Moreover, REM-related movements were predominantly myocloniform (86.6%), whereas NREM-related movements were more often non-myocloniform (59.1%, P < 0.001).ConclusionMinor movements are frequent during physiological sleep, and are associated with low arousal rates. REM-related movements were predominantly myocloniform and shorter than NREM movements, indicating different influences on motor control during both sleep states.

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A scalable method of determining physiological endotypes of sleep apnea from a polysomnographic sleep study.

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A scalable method of determining physiological endotypes of sleep apnea from a polysomnographic sleep study.

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