The challenge of identifying family medicine patients with obstructive sleep apnea: addressing the question of gender inequality

Validation of the Slovene Version of the Stop-Bang Questionnaire in a Primary Practice Setting

Aim

The aim of our study was to validate the Slovene translation of the STOP-BANG (SBQ) questionnaire for use in the primary practice setting.

Methods

We recruited 158 randomly selected visitors at four primary practice clinics who came to the practice for any reason. Participants completed the Slovene SBQ and underwent type 3 respiratory polygraphy, which was analysed by an experienced somnologist. The SBQ was previously translated in to Slovene and validated for the sleep clinic.

Results

Of 158 participants, 153 had valid recordings. The mean age of the participants was 49.5 years (±13.0 years), and 47.7% were male. OSA was identified in 49.0% of the participants. The questionnaire, with a cutoff of ≥3, demonstrated an area under the curve of 0.823 for any OSA (REI≥5), 0.819 for moderate and severe OSA (REI≥15) and 0.847 for severe OSA (REI≥30). Sensitivity was 65.3%, 81.8%, and 90.0%, and specificity was 87.2%, 73.3% and 65.0% for any, moderate to severe and severe OSA, respectively.

Conclusions

The Slovene translation of the SBQ is a reliable instrument for OSA risk stratification in the primary practice setting.

Should testing for obstructive sleep apnea be offered routinely to older family medicine patients? A prospective cohort study

In our previous studies, we offered older family medicine patients testing for obstructive sleep apnea (OSA) and discovered that 80% of patients who accepted, were later diagnosed with unsuspected OSA. In the present study, we followed such patients for 3 years of usual treatment. The goals were to (1) observe whether wider testing for OSA would increase case recognition and treatment uptake; (2) identify symptom and health characteristics associated with diagnosis and treatment efficacy. 101 women and 75 men (>45 years) recruited from family medicine clinics completed questionnaires, polysomnography and consented to chart review (Time 1). Participants with OSA were offered treatment and follow-up with a sleep medicine specialist. All were re-evaluated after 3 years (Time 2). At Time 1, 93% of participants received a diagnosis of OSA. Of these, 53 initiated treatment (46 PAP therapy); at Time 2, 24 PAP users met criteria for adherence. PAP-adherent participants had worse OSA and worse reported symptoms at Time 1 than non-adherent participants. At Time 2, PAP-adherent participants improved on insomnia and daytime symptoms compared to non-adherent participants who showed no change. Adherent and non-adherent participants showed no difference in health indices at Time 1 and no change at three-year follow-up. Benefits of treatment included improvements in co-morbid insomnia and daytime functioning; however, offering wider testing for OSA to older, family medicine patients yielded a high rate of diagnosis but low treatment adoption and adherence. Therefore, a cost-effective strategy would identify and support those likely to adopt and adhere to treatment.

Evaluation of Obstructive Sleep Apnea in Female Patients in Primary Care: Time for Improvement?

Obstructive sleep apnea (OSA) has historically been regarded as a male disease. However, there are a number of significant gender-related differences in the symptoms, diagnosis, and consequences of OSA, which seems to be more severe in male than in female patients, although this sex difference decreases with increasing age. Female patients with OSA tend to present nonspecific symptoms, such as insomnia, depressive symptoms, fatigue, morning headache, and nightmares, often resulting in underdiagnosis and undertreatment compared to male patients. Understanding these differences in women is essential for early identification and referral of patients for diagnosis and treatment of OSA.

Breath variability increases in the minutes preceding obstructive sleep apneic events

PURPOSE

It is unclear if there is a consistent signature in breath patterns prior to an impending obstructive apneic event in patients with sleep-disordered breathing (SDB).

OBJECTIVE

To use continuous recordings of ambient sound in sleep using a smartphone to track auditory signatures of breaths and measure their regularity preceding apneic events.

METHODS

We studied 50 patients evaluated for SDB in whom sound was recorded using smartphones concurrently with polysomnography (PSG). Whole-night sound files were analyzed for time and frequency domain analyses of breath periodicity during periods of normal and sleep-disordered breathing.

RESULTS

Fifty patients (44% women, 42.0 ± 9.4 years old, BMI 32.8 ± 10.8 kg/m²) recorded sound, of whom 30 were diagnosed with OSA and 20 were not. We analyzed a total of 497 apneic (≥10 s) and 481 non-apneic intervals, confirmed by PSG. Interbreath intervals were 3.75 ± 0.62 s for 1 min in quiet breathing, with SD 1.11 ± 0.48 s that increased to 4.16 ± 3.06 s in successive 60-s epochs up to apnea (p < 0.001). Interbreath SD in the 60 s immediately preceding apnea was higher than the SD in random non-apneic periods (p < 0.01, ANOVA). Interbreath SD ≥1.49 s gave 87.3% sensitivity and 86.5% specificity for predicting apnea in the next minute (c-statistic 0.94).

CONCLUSIONS

Breaths increase in variability minutes before proven obstructive apnea in patients with suspected SDB. These results suggest that it may be possible to predict and thus potentially avert apneic events and provide insights into events leading to SDB.

TRIAL REGISTRATION

NCT03288376, clinicaltrials.org.

Noncontact identification of sleep-disturbed breathing from smartphone-recorded sounds validated by polysomnography

PURPOSE

Diagnosis of obstructive sleep apnea by the gold-standard of polysomnography (PSG), or by home sleep testing (HST), requires numerous physical connections to the patient which may restrict use of these tools for early screening. We hypothesized that normal and disturbed breathing may be detected by a consumer smartphone without physical connections to the patient using novel algorithms to analyze ambient sound.

METHODS

We studied 91 patients undergoing clinically indicated PSG. Phase I: In a derivation cohort (n = 32), we placed an unmodified Samsung Galaxy S5 without external microphone near the bed to record ambient sounds. We analyzed 12,352 discrete breath/non-breath sounds (386/patient), from which we developed algorithms to remove noise, and detect breaths as envelopes of spectral peaks. Phase II: In a distinct validation cohort (n = 59), we tested the ability of acoustic algorithms to detect AHI < 15 vs AHI > 15 on PSG.

RESULTS

Smartphone-recorded sound analyses detected the presence, absence, and types of breath sound. Phase I: In the derivation cohort, spectral analysis identified breaths and apneas with a c-statistic of 0.91, and loud obstruction sounds with c-statistic of 0.95 on receiver operating characteristic analyses, relative to adjudicated events. Phase II: In the validation cohort, automated acoustic analysis provided a c-statistic of 0.87 compared to whole-night PSG.

CONCLUSIONS

Ambient sounds recorded from a smartphone during sleep can identify apnea and abnormal breathing verified on PSG. Future studies should determine if this approach may facilitate early screening of SDB to identify at-risk patients for definitive diagnosis and therapy.

CLINICAL TRIALS

NCT03288376; clinicaltrials.org.