scholarly journals Predicting Polysomnography Parameters from Anthropometric Features and Breathing Sounds Recorded during Wakefulness

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 905
Author(s):  
Ahmed Elwali ◽  
Zahra Moussavi
Keyword(s):  
Primary Outcome ◽  
Screening Tool ◽  
Correlation Coefficients ◽  
Random Forest Classifier ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Bilinear Model ◽  
Arousal Index ◽  
Obstructive Sleep ◽  
Anthropometric Features

Background: The apnea/hypopnea index (AHI) is the primary outcome of a polysomnography assessment (PSG) for determining obstructive sleep apnea (OSA) severity. However, other OSA severity parameters (i.e., total arousal index, mean oxygen saturation (SpO2%), etc.) are crucial for a full diagnosis of OSA and deciding on a treatment option. PSG assessments and home sleep tests measure these parameters, but there is no screening tool to estimate or predict the OSA severity parameters other than the AHI. In this study, we investigated whether a combination of breathing sounds recorded during wakefulness and anthropometric features could be predictive of PSG parameters. Methods: Anthropometric information and five tracheal breathing sound cycles were recorded during wakefulness from 145 individuals referred to an overnight PSG study. The dataset was divided into training, validation, and blind testing datasets. Spectral and bispectral features of the sounds were evaluated to run correlation and classification analyses with the PSG parameters collected from the PSG sleep reports. Results: Many sound and anthropometric features had significant correlations (up to 0.56) with PSG parameters. Using combinations of sound and anthropometric features in a bilinear model for each PSG parameter resulted in correlation coefficients up to 0.84. Using the evaluated models for classification with a two-class random-forest classifier resulted in a blind testing classification accuracy up to 88.8% for predicting the key PSG parameters such as arousal index. Conclusions: These results add new value to the current OSA screening tools and provide a new promising possibility for predicting PSG parameters using only a few seconds of breathing sounds recorded during wakefulness without conducting an overnight PSG study.

scholarly journals Cardiorespiratory Polygraphy for Detection of Obstructive Sleep Apnea in Patients With Atrial Fibrillation

2021 ◽  
Vol 8 ◽  
Author(s):  
Michiel Delesie ◽  
Lieselotte Knaepen ◽  
Johan Verbraecken ◽  
Karolien Weytjens ◽  
Paul Dendale ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Screening Tool ◽  
Area Under The Curve ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Automated Algorithm ◽  
Obstructive Sleep ◽  
At Home

Background: Obstructive sleep apnea (OSA) is a modifiable risk factor of atrial fibrillation (AF) but is underdiagnosed in these patients due to absence of good OSA screening pathways. Polysomnography (PSG) is the gold standard for diagnosing OSA but too resource-intensive as a screening tool. We explored whether cardiorespiratory polygraphy (PG) devices using an automated algorithm for Apnea-Hypopnea Index (AHI) determination can meet the requirements of a good screening tool in AF patients.Methods: This prospective study validated the performance of three PGs [ApneaLink Air (ALA), SOMNOtouch RESP (STR) and SpiderSAS (SpS)] in consecutive AF patients who were referred for PSG evaluation. Patients wore one of the three PGs simultaneously with PSG, and a different PG during each of three consecutive nights at home. Severity of OSA was classified according to the AHI during PSG (<5 = no OSA, 5–14 = mild, 15–30 = moderate, >30 = severe).Results: Of the 100 included AF patients, PSG diagnosed at least moderate in 69% and severe OSA in 33%. Successful PG execution at home was obtained in 79.1, 80.2 and 86.8% of patients with the ALA, STR and SpS, respectively. For the detection of clinically relevant OSA (AHI ≥ 15), an area under the curve of 0.802, 0.772 and 0.803 was calculated for the ALA, STR and SpS, respectively.Conclusions: This study indicates that home-worn PGs with an automated AHI algorithm can be used as OSA screening tools in AF patients. Based on an appropriate AHI cut-off value for each PG, the device can guide referral for definite PSG diagnosis.

scholarly journals Validation of the Berlin Questionnaire and American Society of Anesthesiologists Checklist as Screening Tools for Obstructive Sleep Apnea in Surgical Patients

2008 ◽  
Vol 108 (5) ◽  
pp. 822-830 ◽  
Author(s):  
Frances Chung ◽  
Balaji Yegneswaran ◽  
Pu Liao ◽  
Sharon A. Chung ◽  
Santhira Vairavanathan ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
High Risk ◽  
Screening Tools ◽  
Surgical Patients ◽  
Apnea Hypopnea Index ◽  
Berlin Questionnaire ◽  
Obstructive Sleep ◽  
American Society ◽  
American Society Of Anesthesiologists ◽  
Stop Questionnaire

Background Because of the high prevalence of obstructive sleep apnea (OSA) and its adverse impact on perioperative outcome, a practical screening tool for surgical patients is required. This study was conducted to validate the Berlin questionnaire and the American Society of Anesthesiologists (ASA) checklist in surgical patients and to compare them with the STOP questionnaire. Methods After hospital ethics approval, preoperative patients aged 18 yr or older and without previously diagnosed OSA were recruited. The scores from the Berlin questionnaire, ASA checklist, and STOP questionnaire were evaluated versus the apnea-hypopnea index from in-laboratory polysomnography. The perioperative data were collected through chart review. Results Of 2,467 screened patients, 33, 27, and 28% were respectively classified as being at high risk of OSA by the Berlin questionnaire, ASA checklist, and STOP questionnaire. The performance of the screening tools was evaluated in 177 patients who underwent polysomnography. The sensitivities of the Berlin questionnaire, ASA checklist, and STOP questionnaire were 68.9-87.2, 72.1-87.2, and 65.6-79.5% at different apnea-hypopnea index cutoffs. There was no significant difference between the three screening tools in the predictive parameters. The patients with an apnea-hypopnea index greater than 5 and the patients identified as being at high risk of OSA by the STOP questionnaire or ASA checklist had a significantly increased incidence of postoperative complications. Conclusions Similar to the STOP questionnaire, the Berlin questionnaire and ASA checklist demonstrated a moderately high level of sensitivity for OSA screening. The STOP questionnaire and the ASA checklist were able to identify the patients who were likely to develop postoperative complications.

Association of sleep characteristics with adiposity markers in children

2020 ◽  
Vol 33 (7) ◽  
pp. 845-852
Author(s):  
Theresa Herttrich ◽  
Johann Daxer ◽  
Andreas Hiemisch ◽  
Jens Kluge ◽  
Andreas Merkenschlager ◽  
...  
Keyword(s):  
Density Lipoprotein ◽  
Hdl Cholesterol ◽  
Normal Weight ◽  
Overweight And Obesity ◽  
Sleep Diary ◽  
Apnea Hypopnea Index ◽  
Prepubertal Children ◽  
Arousal Index ◽  
Obstructive Sleep ◽  
Obesity In Children

AbstractBackgroundAccumulating evidence suggests a relationship between sleep alterations and overweight/obesity in children. Our aim was to investigate the association of sleep measures other than obstructive sleep apnea or sleep duration with overweight/obesity and metabolic function in children.MethodsWe conducted a prospective cohort study in school- aged children (aged 5 to 8 years, prepubertal, and 12 to 15 years, pubertal) with overweight/obesity and normal-weight children. All children underwent a standardized in-laboratory polysomnography followed by a fasting blood assessment for glucose and metabolic testing. Subjective sleep measures were investigated by a 7-day sleep diary and questionnaire. We analyzed prepubertal and pubertal groups separately using logistic regression and partial correlation analyses.ResultsA total of 151 participants were analyzed. Overweight/obese children had significantly higher odds for arousal index (prepubertal children: 1.28, Confidence interval (CI): 1.06, 1.67; pubertal children: 1.65, CI: 1.19, 2.29) than normal-weight children, independent of age and gender. In prepubertal children, arousal-index was positively associated with C-peptide (r=0.30, p=0.01), whereas Minimum O2 saturation was negatively associated with triglycerides (r=−0.34, p=0.005), adjusting for age and sex. However, associations were attenuated by further adjustment for body mass index standard deviation scores (BMI-SDS). In pubertal children, higher level of apnea-hypopnea-index and pCO2 predicted increased lipoprotein (a) levels (r=0.35, p=0.03 and r=0.40, p=0.01, respectively), independent of age, sex, and BMI-SDS. A negative association was found between pCO2 and high-density lipoprotein (HDL)-cholesterol (r=−0.40, p=0.01).ConclusionsOverall, we report that sleep quality as measured by arousal index may be compromised by overweight and obesity in children and warrants attention in future intervention programs.

scholarly journals Effect of continuous positive airway pressure treatment of obstructive sleep apnea-hypopnea in multiple sclerosis: A randomized, double-blind, placebo-controlled trial (SAMS-PAP study)

2021 ◽  
pp. 135245852110103
Author(s):  
Sulaiman Khadadah ◽  
R John Kimoff ◽  
Pierre Duquette ◽  
Vincent Jobin ◽  
Yves Lapierre ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Continuous Positive Airway Pressure ◽  
Airway Pressure ◽  
Primary Outcome ◽  
Positive Airway Pressure ◽  
Apnea Hypopnea Index ◽  
Double Blind ◽  
Obstructive Sleep

Objective: The aim of this study was to evaluate the effect of continuous positive airway pressure (CPAP) treatment on the Fatigue Severity Scale (FSS, preplanned primary outcome), another fatigue measure, sleep quality, somnolence, pain, disability, and quality of life in multiple sclerosis (MS) patients with obstructive sleep apnea-hypopnea (OSAH). Methods: In a randomized, double-blind trial (NCT01746342), MS patients with fatigue, poor subjective sleep quality, and OSAH (apnea-hypopnea index of ⩾ 15 events per hour/sleep), but without severe OSAH (apnea-hypopnea index > 30, and 4% oxygen desaturation index > 15 events/hour or severe somnolence), were randomized to fixed CPAP or sham CPAP for 6 months. Outcome assessments were performed at 3 and 6 months. Results: Of 49 randomized patients, 34 completed the protocol. Among completers, FSS did not improve with CPAP compared to sham at 6 months. FSS tended to improve ( p = 0.09), and sleepiness (Epworth Sleepiness Scale) improved significantly ( p = 0.03) at 3 months with CPAP compared to sham, but there were no other improvements with CPAP at either study evaluation. Conclusion: In non-severe OSAH patients, CPAP did not significantly improve the primary outcome of FSS change at 6 months. In secondary analyses, we found a trend to improved FSS, and a significant reduction in somnolence with CPAP at 3 months.

scholarly journals Validation of the NoSAS Score for the Screening of Sleep-Disordered Breathing in a Sleep Clinic

2020 ◽  
Vol 2020 ◽  
pp. 1-6 ◽  
Author(s):  
Yi Rong ◽  
Shihan Wang ◽  
Hui Wang ◽  
Feng Wang ◽  
Jingjing Tang ◽  
...  
Keyword(s):  
Predictive Value ◽  
Sleep Disordered Breathing ◽  
Screening Tool ◽  
Characteristic Curve ◽  
Population Based ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Portable Monitor ◽  
Number Of Patients ◽  
Disordered Breathing

Background. There is a growing number of patients with sleep-disordered breathing (SDB) referred to sleep clinics. Therefore, a simple but useful screening tool is urgent. The NoSAS score, containing only five items, has been developed and validated in population-based studies. Aim. To evaluate the performance of the NoSAS score for the screening of SDB patients from a sleep clinic in China, and to compare the predictive value of the NoSAS score with the STOP-Bang questionnaire. Methods. We enrolled consecutive patients from a sleep clinic who had undergone apnea-hypopnea index (AHI) testing by type III portable monitor device at the hospital and completed the STOP-Bang questionnaire. The NoSAS score was assessed by reviewing medical records. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of both screening tools were calculated at different AHI cutoffs to compare the performance of SDB screening. Results. Of the 596 eligible patients (397 males and 199 female), 514 were diagnosed with SDB. When predicting overall (AHI ≥ 5), moderate-to-severe (AHI ≥ 15), and severe (AHI ≥ 30) SDB, the sensitivity and specificity of the NoSAS score were 71.2, 80.4, and 83.1% and 62.4, 49.3, and 40.7%, respectively. At all AHI cutoffs, the AUC ranged from 0.688 to 0.715 for the NoSAS score and from 0.663 to 0.693 for the STOP-Bang questionnaire. The NoSAS score had the largest AUC (0.715, 95% CI: 0.655–0.775) of diagnosing SDB at AHI cutoff of ≥5 events/h. NoSAS performed better in discriminating moderate-to-severe SDB than STOP-Bang with a marginally significantly higher AUC (0.697 vs. 0.663, P=0.046). Conclusion. The NoSAS score had good performance on the discrimination of SDB patients in sleep clinic and can be utilized as an effective screening tool in clinical practice.

scholarly journals 0879 Outcomes of Adenotonsillectomy in Children with Down Syndrome and Obstructive Sleep Apnea

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A335-A335
Author(s):  
A Morello Gearhart ◽  
B Gunaratnam ◽  
E Senthilvel
Keyword(s):  
Obstructive Sleep Apnea ◽  
Down Syndrome ◽  
Sleep Apnea ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Apnea Hypopnea Index ◽  
P Value ◽  
Children With Down Syndrome ◽  
Arousal Index ◽  
Obstructive Sleep

Abstract Introduction Obstructive sleep apnea (OSA) is highly prevalent in children with Down Syndrome (DS). The aim of this study was to assess the effectiveness of adenotonsillectomy (T&A) on polysomnographic parameters of children with DS. Methods Retrospective chart review of children with DS who underwent T&A between 2012-2019 was performed. Preoperative OSA severity was categorized by obstructive apnea-hypopnea index (OAHI): mild = 1-4.9 events/h; moderate = 5-9.9 events/h; severe ≥ 10 events/h. Results We identified 43 DS children with pre and post T&A polysomnographic data in a population of 162 DS patients. A total of 25 were male, mean age 5.1 years (± 3.8 years) and 56% Caucasians. Preoperative data showed 19% mild OSA, 30% moderate and 51% severe. Postoperatively, apnea-hypopnea index (AHI) normalized in 9.3%, 37.2% had mild OSA, 18.6% moderate and 34.9% severe. Overall, T&A resulted in significant improvement (p-value <0.05) in mean AHI, (18.51 ± 28.05 vs 11.72 ± 16.43), SaO2 nadir (80.00 ± 14.82 vs 85.51 ± 5.94), sleep efficiency (81.97 ± 11.15 vs 85.9 ± 8.28), arousal index (16.14 ± 10.23 vs 14.45 ± 12.34), and wake after sleep onset (67.19 ± 46.89 vs 50.55 ± 40.83) and no statistical difference (p-value >0.05) in end-tidal carbon dioxide (43.86 ± 9.56 vs 44.17 ± 3.78), Rapid Eye Movement (REM)% (15.86 ± 7.75 vs 15.92 ± 7.41), sleep latency (24.03 ± 34.39 vs 22.55 ± 21.11), and central apnea index (0.86 ± 1.38 vs 0.66 ± 0.82) in pre and post T&A data. There was no statistically significant difference in pre and post T&A polysomnographic parameters between 17 DS and 17 age and gender-matched non-DS control subjects. Conclusion Adenotonsillectomy resulted in improvement in AHI, oxygen desaturation nadir, sleep efficiency, arousal index and wake after sleep onset. However, a significant portion of children with DS continued to have moderate to severe OSA after T&A. Support None.

scholarly journals Validity and Reliability of the Thai Version of the Pediatric Obstructive Sleep Apnea Screening Tool

2021 ◽  
Author(s):  
Archwin Tanphaichitr ◽  
Pitchayanan Chuenchod ◽  
Kitirat Ungkanont ◽  
Wish Banhiran ◽  
Vannipa Vathanophas ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Internal Consistency ◽  
Screening Tool ◽  
Apnea Hypopnea Index ◽  
Sleep Study ◽  
Retest Reliability ◽  
Obstructive Sleep ◽  
The Mean ◽  
Test Retest Reliability

Objective: Obstructive sleep apnea (OSA) is highly prevalent in children and requires an expensive and relatively unavailable sleep study for diagnosis. This study was undertaken to translate the previously validated OSA screening tool (POSAST) to the Thai language and assess its accuracy and test-retest reliability in at-risk symptomatic children. Study design: Prospective cross-sectional cohort study Methods: Pediatric patients clinically referred for suspected OSA who underwent overnight polysomnography (PSG) were recruited, and caregivers completed the Thai version of the POSAST. The same questionnaire was completed again after 2-4 weeks. Results: One hundred and ten subjects completed the study. The mean age was 8.4±2.9 years. The mean apnea-hypopnea index (AHI) was 10.9±11.9 events/hour. Test-retest reliability (Pearson correlation coefficient = 0.96, P<0.001) and internal consistency (Cronbach’s alpha coefficient = 0.82, P<0.001) between each question were excellent. A cumulative equation-derived score cut-off of 1.9 yielded 78.4% sensitivity and 50.0% specificity, while a numerical additive score cut-off of 8 corresponded to 81.1% sensitivity and 52.8% specificity for diagnosing moderate and severe OSA (AHI ≥5 events per hour) Conclusion: The internal consistency and reproducibility of the Thai version of the POSAST are satisfactory, display acceptable validity, and the instrument can be used for screening symptomatic Thai children for OSA.

423 Evaluation of Electronic Medical Record Artificial Intelligence Screening Tools for Undiagnosed OSA

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A167-A168
Author(s):  
Sam Rusk ◽  
Yoav Nygate ◽  
Fred Turkington ◽  
Chris Fernandez ◽  
Nick Glattard ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Sleep Apnea ◽  
Information Exchange ◽  
The United States ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Type I ◽  
Sleep Study ◽  
Data Set ◽  
Obstructive Sleep

Abstract Introduction The STOP-Bang is a concise, simple and widely adopted obstructive sleep apnea (OSA) screening tool. However, it has limited predictive ability and is susceptible to subjective reporting bias. Artificial Intelligence (AI) methodologies can be utilized together with existing data in electronic medical records (EMRs) to create new screening tools to increase diagnostic sensitivity and facilitate discovery of preclinical OSA phenotypes. Methods The study comprised two independent retrospective sleep study datasets: 1) Type III HSATS (N=5583) and, 2) Type I polysomnograms (N=1037). Each contained raw sleep study waveforms, manually scored sleep events (respiratory, arousal, sleep staging), and standard report indices (apnea-hypopnea index; AHI, arousal index). Additionally, the first dataset contained 90 EMR based metadata variables and the second dataset contained 54 EMR based metadata variables. Three random forest models were trained to detect OSA diagnostic thresholds (AHI&gt; 5, AHI&gt;15, and AHI&gt;30) over three different screening models: STOP-Bang, P-Bang (blood-pressure, BMI, age, neck-size, gender), and Common Clinical Data Set (CCDS)-OSA (all metadata variables simulating EMR CCDS standard). Results CCDS-OSA ROC-AUC exceeded STOP-Bang and P-Bang for both sleep study collections, resulting in AHI&gt;15 ROC-AUC values of 0.73 and 0.71 (CCDS-OSA) compared to AHI&gt;15 ROC-AUC values of 0.68 and 0.69 (STOP-Bang). Additionally, we analyzed the Gini feature importance ranking of the trained CCDS-OSA model to evaluate which variables showed highest predictive value of OSA. The ranking revealed the top 5 features were the five physiologic based STOP-Bang parameters, followed by EMR based physiologic measurements such as HDL, triglycerides, systolic BP, and disease conditions such as diabetes, hypertension, and depression. Conclusion This study shows that while STOP-Bang contains data critical to OSA screening, a variety of other EMR-based parameters can improve performance of OSA detection. AI-based EMR screening can provide a critical tool for more systematic and accurate screening of undiagnosed sleep apnea. Nationwide standards facilitating patient EMR data interoperable health information exchange, particularly the United States Core Data for Interoperability (USCDI CCDS), holds promise to foster broad clinical and research opportunities. Resulting data sharing will allow application of AI screening tools at the population health scale with ubiquitous, existing EMR data to improve population sleep health. Support (if any):

scholarly journals Evaluating four –variable screening tool in european population of a sleep clinic for assessing obstructive sleep apnea syndrome

2015 ◽  
Vol 7 (2) ◽  
pp. 21-27 ◽  
Author(s):  
Athanasia Pataka ◽  
Seraphim Kotoulas ◽  
Evdokia Sourla ◽  
Sofia Akritidou ◽  
Evangelia Panagiotidou ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Roc Curve ◽  
Screening Tool ◽  
European Population ◽  
Apnea Hypopnea Index ◽  
Sleep Study ◽  
Predictive Values ◽  
Variable Screening ◽  
Obstructive Sleep

Background: Different questionnaires have been used to evaluate patients with Obstructive sleep apnea/hypopnea syndrome (OSAHS). The 4-Variable screening tool (4-V) was developed and validated in Asian population for identifying moderate to severe OSAHS.Aims and Objectives: To evaluate the ability of 4-V to identify patients at high risk for OSAHS in a European Population visiting a Sleep Clinic. Methods: 1057 (73.8% males), 52±14 years, BMI 33±7kg/m2, Epworth Sleepiness Scale (ESS) 11.5±5.4 and Apnea Hypopnea Index (AHI) 32.7±26.5 were included. All patients had an in laboratory sleep study and  4-V was calculated.Results: The mean 4-V score was 13.3±2.5. Sensitivities of 4-V≥11 for AHI ≥5, ≥15 and ≥30 were 78%, 79% and 81%, respectively; specificities 40.8%, 36%, 32%;  positive predictive values (PPV)  84.3%, 71%, 52%;  negative predictive values (NPV) 31% , 46.5%, 65% and  area under the ROC curve at AHI≥ 15 was 0.58. For  4-V ≥14, sensitivities  for AHI ≥5, ≥15 and ≥30 were 50.7%, 55% and 61%, respectively; specificities 78%, 74.4%, 69%; PPV  90.3%, 81%, 64%; NPV 27.9%, 45%, 66%  and area under the ROC curve at AHI≥ 15 was 0.68. The 4-V differed significantly between no and mild and between moderate and severe OSAHS, but not  between mild and moderate OSAHS  in both genders. Sensitivity was better in men, but specificity was higher in women.Conclusion: In Caucasians the 4-V≥14 had low sensitivity and NPV, rather good specificity and PPV. For a cut-off ≥11, sensitivity was better but specificity was low. However the predictive values differed between genders. Asian Journal of Medical Sciences Vol.7(2) 2015 21-27

scholarly journals 0606 Comparative Effectiveness of Sleep Apnea Screening Tools During Inpatient Rehabilitation for Moderate to Severe TBI

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A231-A232
Author(s):  
R Richardson ◽  
D Schwartz ◽  
L Drasher-Phillips ◽  
J Ketchum ◽  
K Calero ◽  
...  
Keyword(s):  
Sleep Apnea ◽  
Comparative Effectiveness ◽  
Military Service ◽  
Area Under The Curve ◽  
Inpatient Rehabilitation ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Relative Level ◽  
Obstructive Sleep ◽  
Severe Tbi

Abstract Introduction Recent studies highlight prevalent obstructive sleep apnea after moderate to severe TBI during a time of critical neural repair. The purpose of this study is to determine the diagnostic sensitivity, specificity and comparative effectiveness of traditional sleep apnea screening tools in TBI neurorehabilitation admissions. Methods This is a prospective diagnostic comparative effectiveness trial of sleep apnea screening tools (STOPBANG, Berlin, MAPI [Multi-Apnea Prediction Index]) relative Level 1 polysomnography at six TBI Model System Inpatient Rehabilitation Centers. Between 05/2017 and 02/2019, 449 of 896 screened were eligible for the trial with 345 consented (77% consented). Additional screening left 263 eligible for and completing polysomnography with final analyses completed on 248. The primary outcome was the Area Under the Curve (AUC) of screening tools relative to total apnea hypopnea index ≥15 (AHI, moderate to severe apnea) measured at a median of 47 days post-TBI (IQR 29-47). Results Participants were primarily young to middle age (AGE IQR 28,40,59), male (81%), white (74%), and had primarily severe TBI (IQR GCS 3,6,14). A subset (26%) had a history of military service. Results revealed that the Berlin high risk score (ROC-AUC=0.63) was inferior to the MAPI (ROC-AUC = 0.7802) (p=.0211, CI: 0.0181, 0.2233) and STOPBANG (ROCAUC = 0.7852) (p=.0006, CI: 0.0629, 0.2302); both of which had comparable AUC (p=.7245, CI: -0.0472, 0.0678). Findings were similar for AHI≥30 (severe apnea); however, no differences across scales was observed at AHI&gt;5. The pattern was similar across TBI severity subgroups except for delirium or post-traumatic amnesia status wherein the MAPI outperformed the Berlin and STOPBANG. Youden’s Index to determine risk yielded lower sensitivities but higher specificities relative to non-TBI samples. Conclusion This study is the first to provide clinicians with data to support a choice for which sleep apnea screening tools are more effective during inpatient rehabilitation for moderate to severe TBI (STOPBANG, MAPI vs Berlin) to help reduce comorbidity and possibly improve neurologic outcome. Support PCORI (CER-1511-33005), GDHS (W91YTZ-13-C-0015; HT0014-19-C-0004)) for DVBIC, NIDILRR (NSDC Grant # 90DPTB00070, #90DP0084, 90DPTB0013-01-00, 90DPTB0008, 90DPT80004-02).

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