bluuebunny/crossref_metadata_2025_split huggingface dataset:
0484 Heart Rate Variability and Deep Learning Analysis of Obstructive Sleep Apnea Using ECG from Polysomnography
Authors: Kim Kiyong , Yang Tae-Won , Kim Ji Yoon , Choi Woo Ri , Kwon Kyung Won , Lee So Young , Kim Seung Hwan , Jeon Byeong Gu , Ko Nak Gyeong , Kim Young-Soo , Kwon Oh-Young , Kim Do-Hyung 
Published: April 2024

Abstract

Introduction
Previous studies suggested that obstructive sleep apnea (OSA) can affect the autonomic nervous system. Patients with OSA appear to have a higher sympathetic component, a lower parasympathetic component, and greater autonomic nervous system (ANS) imbalance. We compared heart rate variability (HRV) with existing studies and confirmed classification accuracy through deep learning analysis (DLA), using electrocardiogram (ECG) data extracted from polysomnography (PSG).

Methods
We retrospectively surveyed people who underwent PSG at our hospital from January 2015 to March 2023. The diagnosis of OSA was classified into normal, mild, moderate, and severe based on AHI, and whether arrhythmia was identified during the test was also investigated. HRV analysis performed by frequency domain analysis of the tachogram. For DLA, the tachogram was converted to a Mel-spectrogram and a Convolutional Neuronal Network (CNN) was used to confirm the confusion matrix.

Results
Of a total of 1,806 PSG, 1,554 cases were selected, excluding 252 cases of arrhythmia. OSA confirmed by PSG was normal in 282 patients, mild in 334, moderate in 293, and severe in 645. When comparing the results of HRV divided into AHI below 15 and above, VLF power (ms2/Hz) was 940.78 ± 763.72 vs 1132.75 ± 1104.50 (p &lt; 0.001), LF power (ms2/Hz) was 719.26 ± 734.71 vs. 724.46 ± 945.26 (p = 0.908), HF power (ms2/Hz) was 763.61 ± 1058.92 vs 595.53 ± 1386.75 (p = 0.011), and LF/HF ratio was 1.27 ± 0.74 vs 1.63 ± 1.02 (p &lt; 0.001). As a result of DLA, the ROC AUC Score was confirmed to be 0.7077 and the F1 Score was 0.67.

Conclusion
As a result of HRV using ECG from PSG, OSA patients were found to have low HF power and high LF/HF ratio, similar to previous studies. Additionally, if tachogram's DLA accuracy can be improved through preprocessing and deep learning model improvements, it is expected that it can be used as a screening tool in various place.

Support (if any)
This work was partly supported by Institute of Information & Communications Technology Planning & Evaluation grant funded by the Korea government No.RS_2023_00227552, Development of artificial intelligence video background removal SaaS service using domestic semiconductor 64 TOPS.
0487 Polysomnography Associations with All-cause Hospitalization Following TBI Neurorehabilitation Discharge
Authors: Zayed Randa , Martin Aaron , Almeida Emily , Silva Marc , Pinto Shanti , Beaulieu Cynthia , O’Connor Kristen Dams , Anderson William , Nakase-Richardson Risa 
Published: April 2024

Abstract

Introduction
Obstructive Sleep Apnea (OSA) is prevalent in neurorehabilitation admissions in patients with traumatic brain injury (TBI). OSA is independently associated with hospital readmission within 30 days of discharge in the general population. Prior studies showed rates of rehospitalizations in TBI patients are estimated at 28%. The most common rehospitalization causes are infection, neurologic issues, neurosurgical procedures, injury, psychiatric, and orthopedic. While older age, history of seizure, and greater physical and mental health comorbidities have been associated with rehospitalization following TBI, early objective measures of OSA have not been examined.

Methods
This is a retrospective analysis of TBI Model Systems (TBIMS) participants enrolled in a multicenter comparative effectiveness trial followed over the first two years post-discharge (n=175). Participants received level I polysomnography (PSG) during inpatient neurorehabilitation. Differences in PSG indices were examined by rehospitalization rates to determine associations. Mean age of 43.4 (SD 17.6), mostly of white ethnicity (74%). Multiple regression was used to examine rates of hospitalizations across PSG indices controlling for age.

Results
102 patients (58%) had no hospitalization in the first 2 years of follow-up while 73 (42%) had at least 1 hospitalization (28 had 1 hospitalization, 45 had &gt;1 hospitalization). While the apnea hypopnea index between the re-hospitalized (15.7) vs non-re-hospitalized (14.8) was not significantly different, the mean O2 nadir was 84.8% and 86.9%, respectively (r2=-2.49, p &lt; 0.02, CI: -4.53, -0.45).

Conclusion
This is the first study looking at rehospitalization in patients with TBI and OSA, showing that re-hospitalized patients were more likely to have a worse O2 nadir warranting further exploration of PSG indices and the role of sleep apnea in rehospitalization following neurorehabilitation discharge after TBI.

Support (if any)
The research reported in this abstract was funded through a Patient-Centered Outcomes Research Institute (PCORI) Award. The TBI Model Systems is a funded collaboration between the Department of Veterans Affairs and the Department of Health and Human Services: National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR).
0490 Sleep Apnea Severity Has a U-shaped Association with All-cause Mortality
Authors: Azarian Mehrnaz , Ramezani Amin , Sharafkhaneh Amir , Maghsoudi Arash , Jones Melissa , Razjouyan Javad 
Published: April 2024

Abstract

Introduction
Sleep apnea (SA) severity is determined by apnea hypopnea index (AHI). The interaction between SA and mortality is debated. We explored the relationship between severity of SA and mortality. We further investigated the effect of age on this relationship.

Methods
We developed an Natural Language Processing program (evaluated with 972 notes manually annotated notes) to extract apnea hypopnea index (AHI) from text of physician interpretation of sleep studies, i.e., polysomnograms and home sleep apnea testing, performed at the veteran health administration (VA) from 2000-2022. We grouped the participants to no-SA (n-SA, AHI&lt; 5), mild to moderate SA (m-SA, 5 &lt; AHI &lt; 30) and severe SA (s-SA, AHI&gt;30). We further stratified the cohort based on age: Young, &lt; 40; Middle, &gt;40 and &lt; 65; and older, &gt;65 adults. Using logistic regression, we estimated odds ratio (aOR) for mortality adjusted for age, sex, race, ethnicity, and Charlson-Comorbidity Index using m-SA as reference.

Results
427,587 patients (age, 55.1±14.6 years; BMI, 32.7±6.2; male, 90.5% and 65% male) had at least one documented AHI. The NLP algorithm achieved to high recall (89%), specificity (91%) and F1-score (88%). Mortality rates were 10.8%, 7.7%, and 13.4% in the n-SA, m-SA, and s-SA, respectively. aOR for all-cause mortality rates in Young for n-SA was 1.08 (0.94-1.20) vs s-SA 1.20 (1.08-1.26); in Middle Age for n-SA was 1.40 (1.33-1.41) vs s-SA 1.20 (1.15-1.24); and in Older was for n-SA 1.49 (1.45-1.52), s-SA 1.04 (1.00-1.08).

Conclusion
All-cause mortality rate relates to the severity of SA in a U-Shaped appearance. The U-shape appearance increases markedly with age. Further investigations into mechanisms of the U-Shaped appearance is needed.

Support (if any)
Supported by NIH-NHLBI-K25 funding (#1K25HL152006-01 [J.R.]); seed funding by AHBPCE (#FY2024-002 [J.R.]); and Center for Innovations in Quality, Effectiveness, and Safety (CIN 13-413), Michael E. DeBakey VA Medical Center, Houston, TX.
0492 US Veterans with COMISA, Sleep Apnea, and Insomnia: Chronotype Prevalence and Patient-reported Outcomes
Authors: Wallace Douglas , Sweetman Alexander , Wohlgemuth William 
Published: April 2024

Abstract

Introduction
Among US veterans, it is unclear whether insomnia, obstructive sleep apnea (OSA), and comorbid insomnia in sleep apnea (COMISA) carry disproportionate burden to patient-reported functional outcomes (PROs). Furthermore, whether chronotypes vary among these sleep disorders groups and contribute independently to PROs has not been explored.

Methods
Veterans at risk for OSA evaluated at the Miami VA Sleep Center evaluated over one year. Veterans completed home polysomnography (PSG) and questionnaires (demographics, insomnia severity index [ISI], patient-reported outcomes [PROMIS-29]). OSA diagnosis was per AHI ≥ 5 on PSG while insomnia was per ISI ≥ 15. Those with COMISA fulfilled both of these criteria. Chronotype was self-reported as “morning [M]”, “more morning than evening [M&gt;E]”, “more evening than morning [E&gt;M]” or “evening [E]” type. Sleep group characteristics were compared by ANOVA or Chi-square. Then, regression models were constructed to determine the association of COMISA and insomnia disorder reference to OSA alone on PROMIS domain T-scores. Finally, to explore whether chronotype was associated with PROs within each sleep group, regression models stratified by sleep disorder group were constructed.

Results
The cohort consisted of 387 veterans (85% male, mean age 52 ± 15 years ) where 60 participants (16%) had OSA alone, 68 (18%) had insomnia alone, and 259 (67%) met COMISA criteria. Participants in the insomnia group were significantly more likely to be female, have lower mean BMI and were younger than the OSA alone and COMISA groups. The chronotype prevalence of morning, M&gt;E, E&gt;M, and evening were 33%, 24%, 26%, 16%, respectively. These did not vary across sleep disorder groups (p=0.15). In regression analyses, participants with insomnia alone and COMISA had worse anxiety, depression, fatigue, sleep disturbance, social disruption, physical function, and pain interference than veterans with OSA alone. However, in analyses stratified by sleep disorder groups, chronotype was not associated with any of these PROs

Conclusion
Veterans with COMISA and insomnia alone were more functionally impaired than those with OSA alone. However, chronotype prevalence was similar across veterans with OSA, insomnia, and COMISA and chronotype itself was not associated with PROs. Larger studies with objective measures of chronotype are needed to replicate these findings.

Support (if any)
None
0496 A Narrative Review of the Relationship Between Head and Neck Cancer and OSA
Authors: Sharma Abhay , Le Trung 
Published: April 2024

Abstract

Introduction
Cancer patients with comorbidities have suboptimal treatment outcomes and lower survival rate. Obstructive sleep apnea (OSA) is an underdiagnosed and undertreated cancer comorbidity, especially within the head and neck cancer (HNC) population. There are complex, bidirectional associations between OSA and HNC. Refining HNC-OSA management necessitates an improved grasp of the HNC-OSA relationship. This study reviews the current course of HNC therapy, causal and associative relationships before and after treatment, and statistical methods quantifying HNC-OSA interactions.

Methods
A review of the literature was conducted using PubMed, Google Scholar, Web of Science, Microsoft academic, Semantic, Europe PMC, Scopus, and Crossref databases to collect articles related to OSA in patients with HNCs.

Results
The search yielded 3122 articles, which was narrowed to 26 articles using PRISMA guidelines. There was a total of 382 patients in this review. The investigation confirms a positive correlation between the apnea-hypopnea index and primary tumor size. The associate and causal relationship between OSA and HNC treatment was complex and requires further study.

Conclusion
The paper provides an overview of existing statistical models, offers suggestions for model selection, framework for designing experiments that delve into research questions surrounding the link between OSA and HNC across various stages of cancer treatment. Despite progress, understanding of the HNC-OSA interplay remains incomplete due to limited histological, molecular, and clinical data. Future studies with longitudinal data are crucial for comprehensive insights.

Support (if any)
T. Le, P. Huynh, A. Sharma, A. Setty, Blanchard, and T. Le.” A narrative review of the relationship between head and neck cancer and obstructive sleep apnea: Clinical studies and statistical analysis.” Sleep Medicine Reviews Journal, 2023 (Under Review)
0503 The Impact of Health Disparities on Access to Care for Obstructive Sleep Apnea Patients: A Retrospective Study
Authors: Saltsgaver Megan , Thambi Rakhi , Zhan Weihai 
Published: April 2024

Abstract

Introduction
Health disparities among sleep medicine patients can further worsen sleep-related breathing disorders. Sex, race, and insurance were analyzed to find association with access to care in patients with obstructive sleep apnea (OSA).

Methods
Inclusion criteria resulted in 11,896 adults aged 18 years or older through the years of 2015-2019 with diagnosis of OSA, snoring, hypersomnia, sleep related hypoventilation, or central sleep apnea. Multiple logistic regression models were used to examine significant correlates of outcomes.

Results
About 56% female and 57% black patients had a revisitation within one year, while 52% male (51.8%) and 49% white patients did so. Patients with Medicaid insurance (59%) had a higher percentage of revisitation within one year than those with HMO/PPO/EPO insurance (51%, p &lt;.0001). These factors remain significant in the multiple logistic regression model. The average gap between visits for Medicaid patients was 72 days whereas the gaps for HMO/PPO/EPO and Medicare patients were 82 and 88 days, respectively. The odds of having a shorter gap between visits were 20% higher among Medicaid patients (odds ratio [OR], 1.20; 95% confidence interval [CI], 1.06 - 1.35), and 17% lower among Medicare patients (OR, 0.83, 95% CI, 0.73-0.94), when compared to the odds among HMO/PPO/EPO patients. No significant differences in the average gap between visits were observed across different sex and race groups.

Conclusion
Sex, race, and insurance type were significantly associated with repeated visits within one year of initial visit; insurance type was further found to be associated with a shorter gap between visits. Policy to promote access to OSA care shall address these disparities. Ethnicity, age, and surgical procedure data will be additionally analyzed.

Support (if any)
0508 Age-Related Disparities in Sleep Apnea Diagnosis: Implications of 4% vs. 3% Hypopnea Scoring Criteria
Authors: Abbasimoradi Farnaz , Ferri Raffaele , Mogavero Maria P , Palomino Melissa , DelRosso Lourdes 
Published: April 2024

Abstract

Introduction
The distinction between mild, moderate, and severe apnea is crucial, as it classifies patients into different categories of modifiable risk factors. In hypopnea scoring, Centers for Medicare and Medicaid Services use the 4% criterion, differing from American Academy of Sleep Medicine 's 3%, affecting AHI measurement and the assessment of apnea severity. This study examines age-related differences in the application of these two criteria leading to different apnea severity diagnosis and to potential under-treatment, especially in the elderly.

Methods
An FDA-cleared home sleep test (SleepImage Ring 2.3.0) was utilized with clinical diagnosis involving a comprehensive review by a Board-Certified Sleep Medicine Physician. Descriptive statistics and the chi-square test were employed to assess differences in frequencies. The Bland-Altman method was used to evaluate the difference in AHI estimation between the two scoring criteria, calculating the mean difference (bias) and 95% limits of agreement.

Results
In total, 1,021 subjects (mean age 53.3±14.7 years) were analyzed. The Bland-Altman plot revealed the average bias was 8.76 (95% CI: 8.46-9.06), with the 3% criterion yielding higher values. In subjects aged 18-30 years, the most significant discordance was for the diagnosis of mild OSA (35.8%), diagnosed as normal by the 4% criterion. Interestingly, this criterion classified 2.5% of subjects as normal who were moderate by the 3% criterion. Similarly, in subjects aged 41-50 years, the greatest discordance was for mild OSA (29.8%), and 24.9% were classified as having moderate OSA by the 3% criterion but mild by the 4% criterion. For subjects aged 51-60 years, the greatest discordance was in subjects classified as having moderate OSA by the 3% criterion but mild by the 4% criterion (29.4%), and the agreement on normality was very low (6.3%). The last two age groups (61-70 and &gt;70 years) showed a pattern of concordance/discordance very similar to that of subjects aged 51-60 years.

Conclusion
Our study unveils notable disparities in hypopnea scoring criteria (4% vs. 3%). Over 20% of individuals aged 70 and above with OSA may be under-treated using the 4% criterion, emphasizing the necessity for nuanced OSA diagnosis in older individuals to ensure precise care.

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0512 ABED: Automatic Sleep-Disordered Breathing Event Detection
Authors: Kjaer Magnus Ruud , Hanif Umaer , Brink-Kjaer Andreas , Mignot Emmanuel 
Published: April 2024

Abstract

Introduction
Sleep disordered breathing (SDB) affects more than 10% of the global population and is associated with cardiovascular diseases. Manual annotation of SDB events is time consuming and suffers from inter-rater variances and biases. We propose Automatic Sleep-Disorder Breathing Event Detection (ABED), a method capable of localizing and classifying obstructive apneas (OA), central apneas (CA), and hypopneas (HYPO).

Methods
ABED was trained on 5,456 PSGs and evaluated on 1,099 PSGs from 4 different cohorts. The respiratory modalities included measures of nasal flow, oral thermistor, thoracoabdominal plethysmography, and blood oxygen saturation. These were passed directly as input for ABED. EEG and EOG were passed through another automated detector to ascertain arousals and wake probabilities, which was also passed as input. ABED uses an end-to-end deep learning architecture based on state-of-the-art object detection methods Unified-Real-Time-Object-Detection, ResNet for feature extraction and bi-directional long-short-term-memory layers for temporal processing. ABED was trained on 240 second windows and apnea classes were balanced by sampling less prevalent classes (OA, CA) multiple times during training. ABED was optimized based on event class (cross-entropy loss) and position (Huber loss) weighted towards the class. At the point of inference, non-maximum suppression was used to remove overlapping predictions.

Results
Results show that the apnea-hypopnea index (AHI) values based on ABED’s predictions correlate well with experts (R^2=0.86;β_0=0.95,β_1=3.29 ) and predict sleep apnea diagnosis (AHI≥15) and severity (no, mild, moderate, severe) with a mean accuracy of 89% and 76%, respectively. ABED was able to predict the central apnea index (CAI) with a high correlation (R^2=0.82;β_0=1.16,β_1=0.51 ). When inferring individual events, ABED achieved an overall F1 score of 0.78 in distinguishing between the presence of an event or regular breathing. For specific event types, the F1 scores were: 0.72 OA, 0.51 for CA, and 0.66 for HYPO.

Conclusion
ABED was trained and tested on a multi-cohort dataset and demonstrates generalizing properties on intra-cohort variability along with consistent scoring, making ABED suitable as support for medical experts in SDB annotation. Overall apnea event detection performance demonstrates that ABED can discern between apneic events and regular breathing. Additional work will involve integration of additional cohorts.

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0515 Demographic Study of Inpatient Polysomnograpy from 2019 Through 2022
Authors: Williams George , Ascencio Claudio Gomez , Wani Anna 
Published: April 2024

Abstract

Introduction
Sleep disordered breathing (SDB) refers to abnormalities in ventilation and oxygenation that occur during sleep. Common etiologies of SDB include obesity, craniofacial abnormalities, neuromuscular disorders, and adenotonsillar hypertrophy. The gold standard for diagnosis of SDB is polysomnography (PSG) which evaluates for obstructive sleep apnea, central apnea, persistent desaturations, nocturnal hypoxia, or to determine readiness for decannulation from tracheostomy, and can be performed in either the outpatient or inpatient setting. The primary objective of this study is to determine any temporal changes in patient demographics, PSG parameters, and prevalence of airway comorbidities among pediatric patients receiving at least one inpatient PSG during the COVID19 pandemic, from 2019 through 2022.

Methods
Retrospective analysis of medical records from 422 pediatric patients admitted to Children’s Hospital in Dallas from 2019 through 2022 who received at least one PSG was conducted. Parameters from PSG were recorded and analyzed. Values and demographics from each year were compared against each other and analyzed.

Results
A total of 422 children had 467 PSGs from 2019 through 2022. Demographically, there was no difference in age, gender, height, weight, race, ethnicity, language spoken at home, or primary insurance over these years. In terms of PSG parameters, there was a significant difference in AHI between 2019 12.83(95%CI 9.33-16.32) and 2022 19.04(95%CI 12.39-25.69, p&lt; 0.05) as well as percentage of total sleep time spent hypercapnic between 2020 9.78%(95%CI 5.09-14.48%) and 2022 4.90%(95%CI 1.55-8.24%, p&lt; 0.01). There was no difference among prevalence of airway comorbidities. There was also a significant difference in hospital stay between children hospitalized in 2019 15.29(95%CI 12.06-18.52 days) compared to 2020 25.98(95%CI 18.10-33.85 days, p&lt; 0.05), 2021 29.74(95%CI 19.00-40.48 days, p&lt; 0.05), and 2022 31.24(95%CI 24.04-38.44 days, p&lt; 0.001).

Conclusion
Hospitalized pediatric patients in 2019 prior to the onset of COVID19 pandemic had shorter hospital stays compared to 2020, 2021, and 2022. The longer length of hospital stay observed in 2020-2022 likely reflected initiatives to limit inpatient PSGs in favor of performing them in the outpatient setting. Further research comparing the specific management by PSG metrics would provide insight on changes in treatments for SDB throughout the COVID19 pandemic.

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