The impact of study type and sleep measurement on oxygen desaturation index calculation.

STUDY OBJECTIVES: The oxygen desaturation index (ODI) is an important measure of sleep-disordered breathing during polysomnography (PSG); however, the AASM Manual (V3) does not specify whether to include oxygen desaturations occurring during wake epochs. Additionally, an ODI obtained from PSG can differ from an ODI using home sleep apnea tests (HSATs) that do not measure sleep, hampering diagnostic and treatment decision reliability. This study aimed to (1) compare an ODI that included all desaturations with an ODI that excluded desaturations occurring during wake epochs in PSG and (2) compare ODIs obtained from PSG with HSAT. METHODS: 100 consecutive PSGs for investigation of obstructive sleep apnea were compared. ODIs were calculated including all desaturations (ODIall) and by excluding desaturations entirely during wake epochs (ODIsleep). Additionally, we compared ODIall with an ODI calculated using monitoring time as the denominator (ODIHSAT). RESULTS: The median (interquartile range) 3% ODI for ODIall was 22.8 (13.1, 44.1) events/h and ODIsleep was 17.6 (11.5, 35.2) events/h (median difference: -3.9 events/h [-8.2, -0.9]; 21.0% [8.7%, 33.2%]). This discrepancy was larger with increasing ODI and decreasing sleep efficiency. The ODIHSAT was 17.4 (11.3, 35.2) events/h and the median reduction in ODIHSAT vs ODIall was -4.5 (-10.9, -2.0) events/h (21.6%; 11.1%, 33.8). CONCLUSIONS: ODI was significantly reduced when desaturations in wake epochs were excluded, and when ODI was based on monitoring time rather than sleep time, with the potential for underestimation of disease severity. Results suggest that ODI can differ substantially depending on the calculation and study type used, and that there is a need for standardization to ensure consistent diagnosis and treatment outcomes. CITATION: Whenn CB, Wilson DL, Ruehland WR, Churchward TJ, Worsnop C, Tolson J. The impact of study type and sleep measurement on oxygen desaturation index calculation. J Clin Sleep Med. 2024;20(5):709-717.

Visceral Adipose Tissue Indices Independently Correlated with Obstructive Sleep Apnea in Patients with Type 2 Diabetes.

AIMS: We aimed to explore whether visceral adiposity indices were significantly associated with obstructive sleep apnea (OSA) in type 2 diabetes (T2DM) patients. METHODS: 100 patients with T2DM who underwent overnight polysomnography were analyzed in this study. Anthropometric data, lipid profiles, and glycemic parameters were recorded. Body fat percentage (BFP) and visceral adipose tissue area (VAT area) were collected from a whole body scan using dual-energy X-ray absorptiometry (DXA). Multivariate logistic regression analysis was performed to explore the associations of AHI with BFP, VAT area, and CVAI. RESULTS: The prevalence rate of OSA was 80%, and the mean (±SD) of age was 47.0 ± 13.6 years. Apnea-hypopnea index (AHI) was significantly and positively associated with either VAT area (r = 0.433, p ≤ 0.001) or Chinese visceral adiposity index (CVAI) (r = 0.355, p ≤ 0.001) but not for BFP (r = 0.107, p = 0.294). Multivariate logistic regression analyses showed that VAT area and CVAI were significantly associated with increased risk of OSA, and the adjusted ORs were (95% CI) 1.025 (1.003-1.047, p = 0.023) and 1.018 (1.002-1.034, p = 0.030), respectively. However, there was no significant association between BFP and increased risk of OSA. CONCLUSIONS: VAT area and CVAI were independent risk factors of OSA in the patients with T2DM.

Preliminary study on clinical characteristics of Chinese patients with positional obstructive sleep apnea.

PURPOSE: The objective of this study was to evaluate the prevalence, the clinical characteristics, and the possible predictors of Chinese patients with positional obstructive sleep apnea (POSA) according to the Amsterdam Positional Obstructive Sleep Apnea Classification (APOC). METHODS: A retrospective study in the sleep unit of Peking Union Medical College Hospital was conducted to analyze the clinical and polysomnography data of Chinese patients with obstructive sleep apnea (OSA). RESULTS: Of 372 patients with OSA, 54% met the APOC criteria for POSA. The prevalence of POSA was significantly higher in women with OSA than in men. Chinese patients with POSA had a lower apnea-hypopnea index, oxygen desaturation index, and the percentage of time spent at oxygen saturation below 90% in total sleep time; and a higher mean oxygen saturation (SaO2) and minimum SaO2 during sleep, which were remarkable in the APOC I group. By multivariate logistic regression analyses, the higher mean SaO2 (≥95%) during sleep and mild and moderate OSA were positive predictors of POSA. Mild and moderate OSA was the independent predictor of POSA in women. Higher mean SaO2 (≥95%) during sleep was the independent predictor of POSA in men. CONCLUSION: According to the APOC, the prevalence of POSA is high in Chinese patients with OSA, especially in women. Chinese patients with POSA had less severe OSA and a lower degree of nocturnal hypoxia, which was remarkable in the APOC I group.

Novel screening model of obstructive sleep apnea for snorers with suspected NAFLD undergoing liver sonography.

BACKGROUND/AIMS: Given the increased incidence of obstructive sleep apnea (OSA) among patients with nonalcoholic fatty liver disease (NAFLD), noninvasive screening methods are urgently needed to screen for OSA risk in these patients when conducting an office-based assessment of hepatic steatosis. Therefore, we investigated the controlled attenuation parameter (CAP) and hepatic steatosis index (HSI) in patients with and without OSA and developed screening models to detect OSA. METHODS: We retrospectively reviewed the medical records of all adult snorers with suspected NAFLD undergoing liver sonography between June 2017 and June 2020. Records encompassed CAP and HSI data as well as data collected during in-hospital full-night polysomnography. The multivariate logistic regression models were constructed to explore the predictors of OSA risk. Furthermore, model validation was performed based on the medical records corresponding to the July 2020-June 2021 period. RESULTS: A total of 59 patients were included: 81.4% (48/59) were men, and the mean body mass index (BMI) was 26.4 kg/m2. Among the patients, 62.7% (37/59) and 74.6% (44/59) (detected by the HSI and CAP, respectively) had NAFLD, and 78% (46/59) were diagnosed with OSA on the basis of polysomnography. Three screening models based on multivariate analysis were established. The model combining male sex, a BMI of > 24.8, and an HSI of > 38.3 screened for OSA risk the most accurately, with an area under the receiver operating characteristic curve of 0.81 (sensitivity: 78%; specificity: 85%; and positive and negative predictive values: 95% and 52%, respectively) in the modeling cohort. An accuracy of 70.0% was achieved in the validation group. CONCLUSIONS: The combination screening models proposed herein provide a convenient, noninvasive, and rapid screening tool for OSA risk and can be employed while patients receive routine hepatic check-ups. These models can assist physicians in identifying at-risk OSA patients and thus facilitate earlier detection and timely treatment initiation.

Development of an IoT-Based Sleep Apnea Monitoring System for Healthcare Applications.

Sleep is an essential and vital element of a person's life and health that helps to refresh and recharge the mind and body of a person. The quality of sleep is very important in every person's lifestyle, removing various diseases. Bad sleep is a big problem for a lot of people for a very long time. People suffering from various diseases are dealing with various sleeping disorders, commonly known as sleep apnea. A lot of people die during sleep because of uneven body changes in the body during sleep. On that note, a system to monitor sleep is very important. Most of the previous systems to monitor sleeping problems cannot deal with the real time sleeping problem, generating data after a certain period of sleep. Real-time monitoring of sleep is the key to detecting sleep apnea. To solve this problem, an Internet of Things- (IoT-) based real-time sleep apnea monitoring system has been developed. It will allow the user to measure different indexes of sleep and will notify them through a mobile application when anything odd occurs. The system contains various sensors to measure the electrocardiogram (ECG), heart rate, pulse rate, skin response, and SpO2 of any person during the entire sleeping period. This research is very useful as it can measure the indexes of sleep without disturbing the person and can also show it in the mobile application simultaneously with the help of a Bluetooth module. The system has been developed in such a way that it can be used by every kind of person. Multiple analog sensors are used with the Arduino UNO to measure different parameters of the sleep factor. The system was examined and tested on different people's bodies. To analyze and detect sleep apnea in real-time, the system monitors several people during the sleeping period. The results are displayed on the monitor of the Arduino boards and in the mobile application. The analysis of the achieved data can detect sleep apnea in some of the people that the system monitored, and it can also display the reason why sleep apnea happens. This research also analyzes the people who are not in the danger of sleeping problems by the achieved data. This paper will help everyone learn about sleep apnea and will help people detect it and take the necessary steps to prevent it.

Morbidity and mortality reduction associated with polysomnography testing in idiopathic pulmonary fibrosis: a population-based cohort study.

BACKGROUND: It is not well-known if diagnosing and treating sleep breathing disorders among individuals with idiopathic pulmonary fibrosis (IPF) improves health outcomes. We evaluated the association between receipt of laboratory-based polysomnography (which is the first step in the diagnosis and treatment of sleep breathing disorders in Ontario, Canada) and respiratory-related hospitalization and all-cause mortality among individuals with IPF. METHODS: We used a retrospective, population-based, cohort study design, analyzing health administrative data from Ontario, Canada, from 2007 to 2019. Individuals with IPF were identified using an algorithm based on health administrative codes previously developed by IPF experts. Propensity score matching was used to account for potential differences in 41 relevant covariates between individuals that underwent polysomnography (exposed) and individuals that did not undergo polysomnography (controls), in order minimize potential confounding. Respiratory-related hospitalization and all-cause mortality were evaluated up to 12 months after the index date. RESULTS: Out of 5044 individuals with IPF identified, 201 (4.0%) received polysomnography, and 189 (94.0%) were matched to an equal number of controls. Compared to controls, exposed individuals had significantly reduced rates of respiratory-related hospitalization (hazard ratio [HR] 0.43, 95% confidence interval [CI] 0.24-0.75), p = 0.003) and all-cause mortality (HR 0.49, 95% CI 0.30-0.80), p = 0.004). Significantly reduced rate of respiratory-related hospitalization (but not all-cause mortality) was also observed among those with > = 1 respiratory-related hospitalization (HR 0.38, 95% CI 0.15-0.99) and systemic corticosteroid receipt (HR 0.37, 95% CI 0.19-0.94) in the year prior to the index date, which reflect sicker subgroups of persons. CONCLUSIONS: Undergoing polysomnography was associated with significantly improved clinically-important health outcomes among individuals with IPF, highlighting the potential importance of incorporating this testing in IPF disease management.

Transforming electronic health record polysomnographic data into the Observational Medical Outcome Partnership's Common Data Model: a pilot feasibility study.

Well-defined large-volume polysomnographic (PSG) data can identify subgroups and predict outcomes of obstructive sleep apnea (OSA). However, current PSG data are scattered across numerous sleep laboratories and have different formats in the electronic health record (EHR). Hence, this study aimed to convert EHR PSG into a standardized data format-the Observational Medical Outcome Partnership (OMOP) common data model (CDM). We extracted the PSG data of a university hospital for the period from 2004 to 2019. We designed and implemented an extract-transform-load (ETL) process to transform PSG data into the OMOP CDM format and verified the data quality through expert evaluation. We converted the data of 11,797 sleep studies into CDM and added 632,841 measurements and 9,535 observations to the existing CDM database. Among 86 PSG parameters, 20 were mapped to CDM standard vocabulary and 66 could not be mapped; thus, new custom standard concepts were created. We validated the conversion and usefulness of PSG data through patient-level prediction analyses for the CDM data. We believe that this study represents the first CDM conversion of PSG. In the future, CDM transformation will enable network research in sleep medicine and will contribute to presenting more relevant clinical evidence.

The feasibility and reliability of actigraphy to monitor sleep in intensive care patients: an observational study.

BACKGROUND: Sleep amongst intensive care patients is reduced and highly fragmented which may adversely impact on recovery. The current challenge for Intensive Care clinicians is identifying feasible and accurate assessments of sleep that can be widely implemented. The objective of this study was to investigate the feasibility and reliability of a minimally invasive sleep monitoring technique compared to the gold standard, polysomnography, for sleep monitoring. METHODS: Prospective observational study employing a within subject design in adult patients admitted to an Intensive Care Unit. Sleep monitoring was undertaken amongst minimally sedated patients via concurrent polysomnography and actigraphy monitoring over a 24-h duration to assess agreement between the two methods; total sleep time and wake time. RESULTS: We recruited 80 patients who were mechanically ventilated (24%) and non-ventilated (76%) within the intensive care unit. Sleep was found to be highly fragmented, composed of numerous sleep bouts and characterized by abnormal sleep architecture. Actigraphy was found to have a moderate level of overall agreement in identifying sleep and wake states with polysomnography (69.4%; K = 0.386, p < 0.05) in an epoch by epoch analysis, with a moderate level of sensitivity (65.5%) and specificity (76.1%). Monitoring accuracy via actigraphy was improved amongst non-ventilated patients (specificity 83.7%; sensitivity 56.7%). Actigraphy was found to have a moderate correlation with polysomnography reported total sleep time (r = 0.359, p < 0.05) and wakefulness (r = 0.371, p < 0.05). Bland-Altman plots indicated that sleep was underestimated by actigraphy, with wakeful states overestimated. CONCLUSIONS: Actigraphy was easy and safe to use, provided moderate level of agreement with polysomnography in distinguishing between sleep and wakeful states, and may be a reasonable alternative to measure sleep in intensive care patients. Clinical Trial Registration number ACTRN12615000945527 (Registered 9/9/2015).

Sleep classification from wrist-worn accelerometer data using random forests.

Accurate and low-cost sleep measurement tools are needed in both clinical and epidemiological research. To this end, wearable accelerometers are widely used as they are both low in price and provide reasonably accurate estimates of movement. Techniques to classify sleep from the high-resolution accelerometer data primarily rely on heuristic algorithms. In this paper, we explore the potential of detecting sleep using Random forests. Models were trained using data from three different studies where 134 adult participants (70 with sleep disorder and 64 good healthy sleepers) wore an accelerometer on their wrist during a one-night polysomnography recording in the clinic. The Random forests were able to distinguish sleep-wake states with an F1 score of 73.93% on a previously unseen test set of 24 participants. Detecting when the accelerometer is not worn was also successful using machine learning ([Formula: see text]), and when combined with our sleep detection models on day-time data provide a sleep estimate that is correlated with self-reported habitual nap behaviour ([Formula: see text]). These Random forest models have been made open-source to aid further research. In line with literature, sleep stage classification turned out to be difficult using only accelerometer data.

Screening for Obstructive Sleep Apnea in Children With Sickle Cell Disease: A Pilot Study.

OBJECTIVES/HYPOTHESIS: Obstructive sleep apnea (OSA) and sickle cell disease (SCD) represent two complex disease processes. Current guidelines recommend that children with SCD receive polysomnography (PSG) after presenting with signs or symptoms of sleep-disordered breathing (SDB). Recent studies suggest a disproportionately elevated prevalence of SDB in the population of children with SCD, and traditional risk factors may not be evident within these patients. Further objective testing might be needed to screen all pediatric patients with SCD, even in the absence of overt signs or symptoms of OSA to prevent complications of both conditions. STUDY DESIGN: Prospective cohort study. METHODS: Institutional review board approval was obtained. An eight-question OSA risk assessment screening questionnaire was presented prospectively to 100 consecutive patients with SCD in the pediatric hematology clinic regardless of complaints of SDB. RESULTS: Out of 100 patients, 51 were female. The average age, body mass index (BMI), BMI percentile, and I'M SLEEPY score of the entire cohort were 3.97 years, 15.97%, 55.4%, and 1.63%, respectively. Nineteen patients had a positive sleep apnea screening score and were referred for PSG. The average age BMI, BMI percentile, and I'M SLEEPY score for those 19 patients were 3.77%, 16.67%, 65%, and 3.95%, respectively. Ten patients completed PSG, with seven diagnosed with OSA. CONCLUSIONS: This pilot study demonstrates a higher incidence of SDB and OSA in children with SCD relative to the general pediatric population. Although more PSG reports and further testing is needed to determine whether the results hold, preliminary data indicate that children with SCD should at least undergo OSA screening in the office regardless of overt symptoms. LEVEL OF EVIDENCE: 3 Laryngoscope, 131:E1022-E1028, 2021.

The role of dry mouth in screening sleep apnea.

PURPOSE OF THE STUDY: Effective screening questionnaires are essential for early detection of obstructive sleep apnea (OSA). The STOP-Bang questionnaire has high sensitivity but low specificity. Dry mouth is a typical clinical sign of OSA. We hypothesised that adding dry mouth in the STOP-Bang questionnaire would improve its specificity. STUDY DESIGN: A survey of the incidence of dry mouth was performed in a general population group and suspected sleep apnea clinical population group. Patients with suspected OSA were assessed by laboratory polysomnography and STOP-Bang questionnaire was performed. Adding the option of dry mouth to the OSA screening questionnaire resulted in a new quesionnaire, where cut-off value, diagnostic efficacy and the predictive parameters (sensitivity, specificity, positive predictive value and negative predictive value) were explored. RESULTS: (In the 912 general population group, the incidence of dry mouth in the snoring group (54.0%) was much higher than that in the non-snoring group (30.5%) (p<0.05). In 207 patients with suspected OSA, the incidence of dry mouth in the OSA group was much higher than that in the non-OSA group (p<0.05). The sensitivity and specificity of the STOP-Bang questionnaire were 88.8% and 23.7% for identifying OSA, and 92.2% and 23.1% for identifying moderate and severe OSA, respectively. Adding the option of dry mouth (dry mouth every morning) to the STOP-Bang questionare resulted in a new questionnaire (STOP-Bang-dry-mouth questionnarie) with 9 items. Its sensitivity and specificity were 81.70% and 42.10% for identifying OSA, and 89.10% and 42.30% for identifying moderate and severe OSA, respectively. CONCLUSIONS: The dry mouth symptom correlated with snoring and sleep apnea. The specificity of the STOP-Bang questionnaire can be improved by integrating dry mouth. The diagnostic accuracy of the STOP-Bang-dry mouth questionnaire is yet to be further verified in prospective studies.

Comparison of Traditional Upper Airway Surgery and Upper Airway Stimulation for Obstructive Sleep Apnea.

OBJECTIVE: To compare patients with moderate-severe obstructive sleep apnea (OSA) undergoing traditional single and multilevel sleep surgery to those undergoing upper airway stimulation (UAS). STUDY DESIGN: Case control study comparing retrospective cohort of patients undergoing traditional sleep surgery to patients undergoing UAS enrolled in the ADHERE registry. SETTING: 8 multinational academic medical centers. SUBJECTS AND METHODS: 233 patients undergoing prior single or multilevel traditional sleep surgery and meeting study inclusion criteria were compared to 465 patients from the ADHERE registry who underwent UAS. We compared preoperative and postoperative demographic, quality of life, and polysomnographic data. We also evaluated treatment response rates. RESULTS: The pre and postoperative apnea hypopnea index (AHI) was 33.5 and 15 in the traditional sleep surgery group and 32 and 10 in the UAS group. The postoperative AHI in the UAS group was significantly lower. The pre and postoperative Epworth sleepiness scores (ESS) were 12 and 6 in both the traditional sleep surgery and UAS groups. Subgroup analysis evaluated those patients undergoing single level palate and multilevel palate and tongue base traditional sleep surgeries. The UAS group had a significantly lower postoperive AHI than both traditional sleep surgery subgroups. The UAS group had a higher percentage of patients reaching surgical success, defined as a postoperative AHI <20 with a 50% reduction from preoperative severity. CONCLUSION: UAS offers significantly better control of AHI severity than traditional sleep surgery. Quality life improvements were similar between groups.

Evaluation of Surgical Learning Curve Effect on Obstructive Sleep Apnea Outcomes in Upper Airway Stimulation.

OBJECTIVE: An increasing number of facilities offer Upper Airway Stimulation (UAS) with varying levels of experience. The goal was to quantify whether a surgical learning curve exists in operative or sleep outcomes in UAS. METHODS: International multi-center retrospective review of the ADHERE registry, a prospective international multi-center study collecting UAS outcomes. ADHERE registry centers with at least 20 implants and outcomes data through at least 6-month follow-up were reviewed. Cases were divided into two groups based on implant order (the first 10 or second 10 consecutive implants at a given site). Group differences were assessed using Mann-Whitney U-tests, Chi-squared tests, or Fisher's Exact tests, as appropriate. A Mann-Kendall trend test was used to detect if there was a monotonic trend in operative time. Sleep outcome equivalence between experience groups was assessed using the two one-sided tests approach. RESULTS: Thirteen facilities met inclusion criteria, contributing 260 patients. Complication rates did not significantly differ between groups (P = .808). Operative time exhibited a significant downward trend (P < .001), with the median operative time dropping from 150 minutes for the first 10 implants to 134 minutes for the subsequent 10 implants. The decrease in AHI from baseline to 12-month follow-up was equivalent between the first and second ten (22.8 vs 21.2 events/hour, respectively, P < .001). Similarly, the first and second ten groups had equivalent ESS decreases at 6 months (2.0 vs 2.0, respectively, P < .001). ESS outcomes remained equivalent for those with data through 12-months. CONCLUSIONS: Across the centers' first 20 implants, an approximately 11% reduction operative time was identified, however, no learning curve effect was seen for 6-month or 12-month AHI or ESS over the first twenty implants. Ongoing monitoring through the ADHERE registry will help measure the impact of evolving provider and patient specific characteristics as the number of implant centers increases.

The Value of Oxygen Desaturation Index for Diagnosing Obstructive Sleep Apnea: A Systematic Review.

OBJECTIVES: Intermittent hypoxemia is a risk factor for developing complications in obstructive sleep apnea (OSA) patients. The objective of this systematic review was to identify articles evaluating the accuracy of the oxygen desaturation index (ODI) as compared with the apnea-hypopnea index (AHI) and then provide possible values to use as a cutoff for diagnosing adult OSA. STUDY DESIGN: Systematic Review of Literature. METHODS: PubMed, the Cochrane Library, and SCOPUS databases were searched through November 2019. RESULTS: Eight studies (1,924 patients) met criteria (age range: 28-70.9 years, body mass index range: 21.9-37 kg/m2 , and AHI range: 0.5-62 events/hour). Five studies compared ODI and AHI simultaneously, and three had a week to months between assessments. Sensitivities ranged from 32% to 98.5%, whereas specificities ranged from 47.7% to 98%. Significant heterogeneity was present; however, for studies reporting data for a 4% ODI ≥ 15 events/hour, the specificity for diagnosing OSA ranged from 75% to 98%, and only one study reported the positive predictive value, which was 97%. Direct ODI and AHI comparisons were not made because of different hypopnea scoring, different oxygen desaturation categories, and different criteria for grading OSA severity. CONCLUSION: Significant heterogeneity exists in studies comparing ODI and AHI. Based on currently published studies, consideration should be given for diagnosing adult OSA with a 4% ODI of ≥ 15 events/hour and for recommending further evaluation for diagnosing OSA with a 4% ODI ≥ 10 events/hour. Screening with oximetry may be indicated for the detection of OSA in select patients. Further study is needed before a definitive recommendation can be made. Laryngoscope, 131:440-447, 2021.

Home Sleep Testing to Direct Upper Airway Stimulation Therapy Optimization for Sleep Apnea.

OBJECTIVES/HYPOTHESIS: Selective upper airway stimulation (sUAS) is a well-established treatment option for obstructive sleep apnea (OSA). This study aimed to determine if there are benefits in performing a home sleep test (HST) to evaluate postoperative sUAS effectiveness after patient acclimatization compared to the generally used polysomnography (PSG) titration, as measured by long-term follow-up outcomes. STUDY DESIGN: Retrospective comparative cohort analysis. METHODS: We conducted an analysis of consecutive patients at our center who had completed a 6-month follow-up (month 6 [M6]) and recorded data from M6, month 12 (M12), and month 24 (M24). After device activation, we performed an HST with the patient's stimulation settings, and measured the apnea-hypopnea index (AHI), Epworth Sleepiness Scale (ESS), and device usage. These values were compared to patients who had undergone PSG-based device titration. RESULTS: Baseline values of the initial 131 patients show high ESS and moderate OSA. At the 2-month time point of the HST, nearly half of the patients (46.2%) reached an AHI ≤15/hr, and approximately a fifth (19.2%) reached <5/hr. The PSG and HST groups differed in median ESS at M24, but no other differences were observed for ESS at M6 and M12. Both groups showed similar AHI, oxygen desaturation, and usage hours per week. CONCLUSIONS: Adjusting therapy by using the HST technique after device activation and acclimatization has clinical and economic advantages. These advantages are contingent on several conditions being met when deviating from the standard device protocol, including precise communication with the referring sleep medicine physicians, especially their role in helping with long-term follow-up. LEVEL OF EVIDENCE: 4 Laryngoscope, 131:E1375-E1379, 2021.

Reducing cost and time to diagnosis and treatment of obstructive sleep apnea using ambulatory sleep study: a Singapore sleep centre experience.

PURPOSE: The current gold standard for diagnosis of obstructive sleep apnea (OSA) is overnight in laboratory polysomnography (PSG). However, PSGs are expensive, labor-intensive, and have long wait times. An ambulatory sleep study device, the WatchPAT, has been shown to have high correlation for sleep indices measured compared with PSG (AASM, 2016). Use of the WatchPAT could potentially lead to shorter waiting times and earlier diagnosis of OSA (Lancet Resp Med 3:310-8, 2015). Our study aimed to investigate if WatchPAT reduces time to diagnosis and treatment of OSA in a tertiary healthcare setting. A secondary aim was to investigate the cost-benefit of an ambulatory sleep study. METHODS: All patients who underwent diagnostic sleep studies in a single tertiary institution from 2014 to 2017 were retrospectively reviewed. Baseline characteristics and time from ordering of sleep study to prescription of continuous positive airway pressure were recorded. Data were categorized into two groups by type of diagnostic sleep study, PSG, and WatchPAT. The time to treatment and cost for diagnosis of OSA were compared between groups with the Paired T test/Wilcoxon signed-rank test. RESULTS: Of 1898 patients who had diagnostic sleep studies over a 4-year period, 1660 patients (88%) underwent PSG and 238 patients (12%) underwent WatchPAT. Patients in the WatchPAT group had a shorter time to diagnosis (21 days versus 79.8 days, p < 0.001) and treatment (46.3 days versus 118.4 days, p < 0.001) compared to the PSG group. Cost-benefit calculation showed that this earlier treatment led to cost-saving of US $1179.50 per patient. CONCLUSION: An ambulatory sleep study is an option for earlier access to diagnosis and treatment of OSA with the potential of considerable cost savings.

The effect of in-lab polysomnography and home sleep polygraphy on sleep position.

PURPOSE: Little is known regarding the influence of in-laboratory polysomnography (PSG) equipment on sleep position, especially on the prevalence of supine positioning, which in many cases may lead to a more severe sleep apnea diagnosis. The aim of this study was to assess the percentage of supine sleep during an in-laboratory PSG compared to that seen during a home sleep apnea test (HSAT). METHODS: This was a retrospective cohort study comparing in-laboratory PSG and HSAT using a peripheral arterial tone (PAT) technology device. RESULTS: Of 445 PSG and 416 HSAT studies analyzed, there was no significant difference in the proportion of supine sleep time between PSG (44%) and HSAT (45%, p = 0.53). Analysis of the differences in sleep position (supine versus non-supine), analyzed by sex, BMI (≥ 30 kg/m2 versus < 30 kg/m2), and age (≥ 60 years versus < 60 years), was significant only for women, who had more supine sleep during HSAT at 61 ± 24% than during PSG at 45 ± 26% (p < 0.001). CONCLUSION: Overall there was no difference in the percentage of supine sleep when comparing in-laboratory PSG to HSAT. However, women had more supine sleep with HSAT than with PSG.

Adherence to prescribed overnight sleep study in patients suspected of sleep apnea: problem size and influential factors.

PURPOSE: Despite the serious consequences of sleep apnea, some patients do not follow their physicians' advice to undergo a sleep study. The present study aimed to determine the rate of adherence and influencing factors in conducting a polysomnography test in patients suspected of obstructive sleep apnea. METHODS: This qualitative and quantitative analysis was conducted between July 2017 and November 2019 on patients suspected of sleep apnea. The quantitative analysis aimed at determining the rate of adherence through a retrospective cross-sectional study. The qualitative content analysis was conducted on purposefully selected subgroup of patients suspected of obstructive sleep apnea who were referred for polysomnography. The required data were collected through the semi-structured in-depth interviews and then recorded, transcribed, and analyzed using SPSS.22 and MAXQDA10. RESULTS: Quantitative part: Of 311 patients (mean age: 47.6 ± 13.1 years) referred for polysomnography, 283 patients (91%) were at a high risk of developing obstructive sleep apnea. Among those referred for polysomnography, 31% (n = 95) adhered to recommendations for a sleep study. Qualitative part: Factors affecting adherence to polysomnography were categorized as "barriers" and "triggers." Barriers included inadequate knowledge, psychological factors, cost, and the service system. Triggers included adequate knowledge and tangible experience of consequences of the illness. CONCLUSION: The majority of patients at risk of developing obstructive sleep apnea did not follow the recommendation for polysomnography, indicating a need for systematic interventions. Among the identified barriers, knowledge and psychological factors are modifiable ones that can be addressed with the patient. We theorize that raising awareness among patients by providing additional information and eliminating concerns may help to increase the rate of adherence. Insurance coverage or subsidy to reduce the sleep study costs may also be an effective strategy to increase adherence to recommendations for polysomnography.