Physician Decision Making and Clinical Outcomes With Laboratory Polysomnography or Limited-Channel Sleep Studies for Obstructive Sleep Apnea

Chai-Coetzer, Ching Li; Antic, Nick A.; Hamilton, Garun S.; McArdle, Nigel; Wong, Keith; Yee, Brendon J.; Yeo, Aeneas; Ratnavadivel, Rajeev; Naughton, Matthew T.; Roebuck, Teanau; Woodman, Richard; McEvoy, R. Doug

doi:10.7326/m16-1301

Cited by 51 publications

(37 citation statements)

References 33 publications

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“…It may be just as important to abolish snoring as well as improve the adverse health consequences associated with OSA (eg, reduced daytime sleepiness). It is worth noting that the surgical nonresponders had a significant reduction in ESS post surgery of two points, which is a clinically significant difference for the ESS, 36 this finding was observed in nonresponders regardless of the definition of success applied (see Supplementary material, Tables E5-E7).…”

Section: Limitationsmentioning

confidence: 80%

Loop Gain Predicts the Response to Upper Airway Surgery in Patients With Obstructive Sleep Apnea

Joosten

Leong

Landry

et al. 2017

Sleep

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Study Objectives: Upper airway surgery is often recommended to treat patients with obstructive sleep apnea (OSA) who cannot tolerate continuous positive airways pressure. However, the response to surgery is variable, potentially because it does not improve the nonanatomical factors (ie, loop gain [LG] and arousal threshold) causing OSA. Measuring these traits clinically might predict responses to surgery. Our primary objective was to test the value of LG and arousal threshold to predict surgical success defined as 50% reduction in apnea-hypopnea index (AHI) and AHI <10 events/hour post surgery. LG remained a significant predictor of surgical success after controlling for covariates (logistic regression p = .018; receiver operating characteristic area under curve = 0.80). Conclusions: Our study provides proof-of-principle that upper airway surgery most effectively resolves OSA in patients with lower LG. Predicting the failure of surgical treatment, consequent to less stable ventilatory control (elevated LG), can be achieved in the clinic and may facilitate avoidance of surgical failures.

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Section: Limitationsmentioning

confidence: 80%

Loop Gain Predicts the Response to Upper Airway Surgery in Patients With Obstructive Sleep Apnea

Joosten

Leong

Landry

et al. 2017

Sleep

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“…The authors concluded that the proposed protocol could potentially offer a cost-effective tool to manage OSAS and expedite diagnosis particularly in rural and remote regions. In a recent study, Chai-Coetzer et al [53] analyzed the influence of abbreviated sleep studies on physician decision making and patient outcomes.…”

Section: Oximetry In Clinical Practicementioning

confidence: 99%

“…A recent study found no major changes in patient outcomes and physician confidence in the diagnoses when using cardiorespiratory polygraphy. Additionally, a significantly lower improvement in symptoms and CPAP compliance, as well as lower diagnostic confidence were reported when using pulse oximetry alone, primarily in milder cases [53]. Similarly, data supporting simplified monitoring 29 at home for the diagnosis of OSAS in children is currently insufficient.…”

Section: Oximetry Portable Monitoring By Means Of Smartphonesmentioning

confidence: 99%

Oximetry use in obstructive sleep apnea

Campo

Crespo

Cerezo-Hernández

et al. 2018

Expert Review of Respiratory Medicine

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Introduction. Overnight oximetry has been proposed as an accessible, simple, and reliable technique for obstructive sleep apnea syndrome (OSAS) diagnosis. From visual inspection to advanced signal processing, several studies have demonstrated the usefulness of oximetry as a screening tool. However, there is still controversy regarding the general application of oximetry as a single screening methodology for OSAS.Areas covered. Currently, high-resolution portable devices combined with pattern recognitionbased applications are able to achieve high performance in the detection this disease. In this review, recent studies involving automated analysis of oximetry by means of advanced signal processing and machine learning algorithms are analyzed. Advantages and limitations are highlighted and novel research lines aimed at improving the screening ability of oximetry are proposed. Expert commentary. Oximetry is a cost-effective tool for OSAS screening in patients showinghigh pretest probability for the disease. Nevertheless, exhaustive analyses are still needed to further assess unattended oximetry monitoring as a single diagnostic test for sleep apnea, particularly in the pediatric population and in especial groups with significant comorbidities. In the following years, communication technologies and big data analysis will overcome current limitations of simplified sleep testing approaches, changing the detection and management of OSAS.

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“…Furthermore, as oxygen desaturation has been linked with adverse consequences associated with OSA (Bradley & Floras, ; Drager, Jun, & Polotsky, ; Ryan, Taylor, & Mcnicholas, ), detecting those with nocturnal hypoxaemia may be arguably more important than detecting those with apnoeas and hypopnoeas without significant oxygen desaturation. Nevertheless, physicians’ confidence in managing patients with OSA based solely on ODI 3% has been shown to be lower than when full polysomnographic data are available, despite the high diagnostic utility of ODI 3% (area under the receiver operating characteristic curve being 0.94 [95% CI 0.90–0.98]) and non‐inferior clinical improvement in patients treated based solely on ODI versus full polysomnography data (Chai‐Coetzer et al., ). This lack of confidence among the physicians may arise from inadequate prior experience in management models solely using ODI 3% data (cf.…”

Section: Discussionmentioning

confidence: 99%

Comparison of apnoea–hypopnoea index and oxygen desaturation index when identifying obstructive sleep apnoea using type‐4 sleep studies

Senaratna

Lowe

Perret

et al. 2018

Journal of Sleep Research

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Summary The concordance of different indices from type‐4 sleep studies in diagnosing and categorising the severity of obstructive sleep apnoea is not known. This is a critical gap as type‐4 sleep studies are used to diagnose obstructive sleep apnoea in some settings. Therefore, we aimed to determine the concordance between flow‐based apnoea–hypopnoea index (AHIflow50%) and oxygen desaturation index (ODI3%) by measuring them concurrently. Using a random sub‐sample of 296 from a population‐based cohort who underwent two‐channel type‐4 sleep studies, we assessed the concordance between AHIflow50% and ODI3%. We compared the prevalence of obstructive sleep apnoea of various severities as identified by the two methods, and determined their concordance using coefficient Kappa(κ). Participants were aged (mean ± SD) 53 ± 0.9 years (48% male). The body mass index was 28.8 ± 5.2 kg m−2 and neck circumference was 37.4 ± 3.9 cm. The median AHIflow50% was 5 (inter‐quartile range 2, 10) and median ODI3% was 9 (inter‐quartile range 4, 15). The obstructive sleep apnoea prevalence reported using AHIflow50% was significantly lower than that reported using ODI3% at all severity thresholds. Although 90% of those with moderate–severe obstructive sleep apnoea classified using AHIflow50% were identified by using ODI3%, only 46% of those with moderate–severe obstructive sleep apnoea classified using ODI3% were identified by AHIflow50%. The overall concordance between AHIflow50% and ODI3% in diagnosing and classifying the severity of obstructive sleep apnoea was only fair (κ = 0.32), better for males (κ = 0.42 [95% confidence interval 0.32–0.57] versus 0.22 [95% confidence interval 0.09–0.31]), and lowest for those with a body mass index ≥ 35 (κ = 0.11). In conclusion, ODI3% and AHIflow50% from type‐4 sleep studies are at least moderately discordant. Until further evidence is available, the use of ODI3% as the measure of choice for type‐4 sleep studies is recommended cautiously.

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Physician Decision Making and Clinical Outcomes With Laboratory Polysomnography or Limited-Channel Sleep Studies for Obstructive Sleep Apnea

Abstract: National Health and Medical Research Council and Repat Foundation.

Cited by 51 publications

References 33 publications

Loop Gain Predicts the Response to Upper Airway Surgery in Patients With Obstructive Sleep Apnea

Loop Gain Predicts the Response to Upper Airway Surgery in Patients With Obstructive Sleep Apnea

Oximetry use in obstructive sleep apnea

Comparison of apnoea–hypopnoea index and oxygen desaturation index when identifying obstructive sleep apnoea using type‐4 sleep studies

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