Abstract Introduction Without consistent PAP data monitoring, clinics struggle to identify issues with patients' PAP receipt and usage. To address this, we created PennPALS (Penn PAP Automated Learning System), a cloud-based platform that filters PAP data extracted from the electronic medical record (EMR) through algorithms to identify common PAP issues, such as non-adherence, mask leaks, elevated residual AHI, or delayed setups. Patients are contacted about issues through two-way text messaging. Methods PennPALS auto-enrolls patients based on an EMR PAP order. Patients can opt out at any time during the 90-day monitoring program. We conducted a retrospective evaluation of PennPALS for patients enrolled June 2023. Results In one month, 279 patients were enrolled (mean age 54.9 (14.5) years, 56.3% male, 48.8% white, 40.5% Black or African American and 6% Hispanic). One hundred eighty-nine patients entered a 90-day data monitoring window (mean age 54.1 (14) years, 57.7% males, 45.5% white, 41.8% Black or African American, 3.8% Hispanic, and 58.7% new to PAP). Ninety patients never had PAP data in EMR. Two patients were ineligible due to invalid phone number in EMR and 25 opted out (4 at enrollment; 21 during monitoring). During the 90 day monitoring, the following number of triggers were activated: 247 non-adherence (7 day avg. < 4hrs), 571 adherence (7 day avg. >4hrs), 314 mask leak (Phillips: avg % time in large leak ≥ 30% for ≥3 of 7 days; ResMed: leak ≥ 24 L/min for ≥3 of 7 days), 8 high residual AHI (7 day avg ≥ 10 events/hr), 62 no data triggers (no data for 5 days), and 9 continued no data triggers. Of patients that completed the exit survey (n=20), average “how helpful” score (scale 0-10) was 7.9 (3.9) and Net Promotor Score (e.g., likelihood to recommend) was 87. Conclusion PennPALS demonstrates real-word feasibility to monitor patients and identify issues with algorithms based on discrete PAP data within EMR. Identified issues triggered two-way text messaging to improve PAP communications. The high number of patients without PAP data requires further investigation (e.g., patient did not pursue PAP, modem not linked). Patients reported that PennPALS was helpful and they would recommend it. Support (if any) K12HS026372

Abstract Introduction Sleepiness, a common symptom of various sleep disorders, has been subjectively measured using the Epworth Sleepiness Scale (ESS) and objectively quantified using the Psychomotor Vigilance Test (PVT). The relative merit of these two measures of sleepiness has been debated, and both have shown inconsistent relationships with severity of obstructive sleep apnea (OSA) and responses to treatment. We report the relative associations of ESS and PVT with hours of CPAP use within a clinical sample. Methods Patients being evaluated for sleep disorders at the University of Pennsylvania’s Sleep Center competed both the ESS and PVT measurements in a single clinical visit. Thirty-nine patients had a diagnosis of OSA and were currently using CPAP. Pearson’s correlations were utilized to examine the association between CPAP adherence and both the ESS and PVT measures (transformed lapses [sum of square root of number of lapses and square root of lapses+1]) and mean reciprocal response time (RRT). Results total of 39 patients (64.1% males; 52.6% White, 39.5% Black) were studied, with a mean (SD) age of 61.1 (16.4) years and BMI of 35.2 (9.5) kg/m2; residual apnea-hypopnea index (AHI) was 6.5 (10.8) events/hour (23 [63.9%] had residual AHI < 5 events/hour). Participants used CPAP an average of 5.87 (2.27) hours/night in the past 30 days, 5.87 (2.47) hours/night over the past 7 days, and 5.91 (2.86) hours/night the day prior to ESS/PVT measurement. Overall, we observed a strong correlation between less subjective sleepiness based on ESS and more CPAP usage at 30-days (rho = -0.48, p=0.002), 7-days (rho = -0.43, p=0.006) and the prior day (rho = -0.38, p=0.017). However, there was no correlation between hours/night of CPAP adherence and objective function as measured on PVT. Conclusion Among patients with OSA using CPAP evaluated at University of Pennsylvania’s Sleep Center, greater amounts of CPAP use were significantly associated with lower ESS scores (e.g., less sleepiness). Conversely, no significant correlations were observed between CPAP use and objective data on PVT. Larger studies examining the causal effects of CPAP on subjective and objective sleepiness, including with repeat assessments of ESS and PVT during therapy, are warranted. Support (if any)

Abstract Introduction Black or African American and Hispanic of any race (B/H) adults are disproportionately affected by obstructive sleep apnea (OSA). Positive Airway Pressure (PAP) treatment may reduce disparities, but short-term PAP outcomes are worse among under-represented minority (URM) adults compared to other, mainly White, adults. No studies have examined if adherence disparities persist/worsen long-term. We evaluated disparities in PAP usage between B/H adults and other race/ethnicities. Methods We defined a clinical cohort of adults with moderate-severe OSA (apnea-hypopnea index [AHI]≥15 events/h) that underwent diagnostic sleep studies and initiated PAP between 01/2015-03/2018. Logistic regression was used to examine differences in the likelihood of still using PAP or meeting adherence threshold of ≥4 hours/night at 18-24 months. We performed mixed model for repeated measures to examine differences in h/night of PAP use over two years. Analyses were controlled for age, sex, BMI, AHI, and 3-month PAP usage to understand whether disparities emerged independent of short-term differences. Results Analyses included 1,518 individuals (694 [45.7%] B/H) with PAP usage at 3 months, who were middle-aged (53.4±14.1 years-old), majority men (64.4%), obese (38.2±9.8 kg/m2) and had severe OSA (46.6±30.2 events/h). B/H adults had 70% higher odds (OR [95% CI] = 1.70 [1.33-2.17]) of no longer using PAP 18-24 months after initiation. B/H adults using PAP had ~2 hours/night less usage than other race/ethnicities at 18-24 months (2.72 [2.49-2.97] vs. 4.52 [4.31-4.73] hours/night; p< 0.0001). This difference was attenuated but remained significant after accounting for 3-month usage (mean [95% CI] difference = -0.64 [-0.92, -0.37] hours/night). B/H adults using PAP were also 3-times more likely to be non-adherent at 18-24 months (OR [95% CI] = 3.00 [2.28-2.95]), and remained 2-times more likely to be non-adherent controlling for 3-month usage (2.14 [1.56-2.92]). Conclusion At 18-24 months, Black or Hispanic of any race adults with moderate-severe OSA were less likely to use PAP, had less usage when still using PAP, and were less likely to achieve adherence thresholds. Long-term PAP disparities exist, even after accounting for short-term differences. Promoting longer-term PAP adherence for URM is a priority to reduce these disparities and address healthcare inequities. Support (if any) AHA (20CDA35310360), NIH P01 HL094307, AHRQ K12HS026372

Abstract Introduction Sleepiness is a primary symptom among patients presenting at sleep clinics. Sleepiness is typically subjectively evaluated using the Epworth Sleepiness Scale (ESS), which has been associated with worse cardiovascular outcomes among sleep apnea patients. On the other hand, functional deficits due to sleepiness can be objectively quantified using a Psychomotor Vigilance Test (PVT). To better understand the presentation of “sleepiness”, we examined the relationship between subjective ESS and objective PVT among a clinical sample. We hypothesized that these two different measures of sleepiness would be correlated. Methods A prospective sample of patients being evaluated for sleep disorders in the Sleep Center at the University of Pennsylvania completed the ESS and PVT at the same clinical visit. Demographic data were obtained at the visit or derived from the electronic health record. Pearson’s linear correlations were utilized to examine the association between the ESS and both the transformed lapses (sum of square root of number of lapses and square root of lapses+1) and mean reciprocal response time (RRT) on the PVT. Results In total, 167 patients (98 [58.7%] males) were studied, with a mean (±SD) age of 54.7±16.8 years and BMI of 34.5±9.9 kg/m2. There were a similar number of White (67 [42.1%]) and Black (71 [44.7%]) participants and 129 (77.3%) had diagnosed or suspected obstructive sleep apnea (OSA). Patients had an average ESS of 8.1±5.4, and 10.5±10.6 lapses, 5.9±2.9 transformed lapses, and mean RRT of 3.4±0.7 seconds-1 on PVT. Among all patients, there was no statistically significant correlation between ESS and either transformed lapses (rho = 0.10, p=0.200) or mean RRT (rho = -0.10, p=0.201). Results were similar when comparing the two sleepiness measures restricted to patients with OSA. Conclusion Within patients being evaluated in a clinical sleep center, there was only a weak association between subjective sleepiness on the ESS and objective sleepiness on PVT. Thus, not all patients reporting daytime sleepiness have objective deficits, and vice versa. Results support using both assessments to fully characterize a patient’s sleepiness. Future studies should evaluate the relationship between adverse outcomes and subjective and objective sleepiness, alone and in combination. Support (if any)

Many patients with obstructive sleep apnea (OSA), but not all, have a reduction in blood pressure (BP) with positive airway pressure (PAP) treatment. Our objective was to determine whether the BP response following PAP treatment is related to obesity. A total of 188 adults with OSA underwent 24-hour BP monitoring and 24-hour urinary norepinephrine collection at baseline. Obesity was assessed by waist circumference, body mass index, and abdominal visceral fat volume. Participants adherent to PAP treatment were reassessed after 4 months. Primary outcomes were 24-hour mean arterial pressure (MAP) and 24-hour urinary norepinephrine level. Obstructive sleep apnea participants had a significant reduction in 24-hour MAP following PAP treatment (-1.22 [95% CI: -2.38, -0.06] mm Hg; P = .039). No significant correlations were present with any of the 3 obesity measures for BP or urinary norepinephrine measures at baseline in all OSA participants or for changes in BP measures in participants adherent to PAP treatment. Changes in BP measures following treatment were not correlated with baseline or change in urinary norepinephrine. Similar results were obtained when BP or urinary norepinephrine measures were compared between participants dichotomized using the sex-specific median of each obesity measure. Greater reductions in urinary norepinephrine were correlated with higher waist circumference (rho = -0.21, P = .037), with a greater decrease from baseline in obese compared to non-obese participants (-6.26 [-8.82, -3.69] vs -2.14 [-4.63, 0.35] ng/mg creatinine; P = .027). The results indicate that the BP response to PAP treatment in adults with OSA is not related to obesity or urinary norepinephrine levels.

STUDY OBJECTIVES:Few studies have objectively evaluated sleep characteristics during pregnancy or investigated the relationship between altered spectral electroencephalogram (EEG) bands and sleep-disordered breathing (SDB). The study aimed to describe changes in sleep as measured by polysomnography (PSG) and spectral EEG bands during pregnancy and to examine the relationship between delta power in non-rapid eye movement (NREM) sleep and SDB. METHODS:This is a secondary analysis of a prospective study. One hundred twenty-three women underwent full PSG in early pregnancy, and 97 repeated PSG in late pregnancy. Spectral analysis of the EEG in NREM sleep was performed. We used linear and logistic mixed-model regression to analyze the sleep measures and linear regression to explore the association between delta power and apnea-hypopnea index (AHI) changes during pregnancy. RESULTS:In late pregnancy, women had shorter sleep duration, poorer sleep efficiency, more awakenings, more stage N2 sleep, less slow wave sleep, less REM sleep, higher AHI, and higher periodic limb movement index compared to early pregnancy. The percentage of stage N1 sleep, sleep latency, REM sleep latency, and arousal index frequency did not change. Regarding EEG-spectra, delta and theta powers decreased, but beta-2 power increased during pregnancy. In multivariable analyses, greater reduction of delta power was associated with larger increases in AHI (β [95% confidence interval] = -0.038 [-0.073, -0.002], P = .040). Estimates suggest that each one-unit increase in AHI reduces delta power by 4% in late pregnancy. CONCLUSIONS:PSG-measured sleep characteristics change during pregnancy. Delta power decreases when the severity of SDB increases during pregnancy. COMMENTARY:A commentary on this article appears in this issue on page 1095.

Older adults have high prevalence rates of insomnia symptoms, yet it is unclear if these insomnia symptoms are associated with objective impairments in sleep. We hypothesized that insomnia complaints in older adults would be associated with objective differences in sleep compared with those without insomnia complaints. To test this hypothesis, we conducted a cross-sectional study in which older adults with insomnia complaints (cases, n = 100) were compared with older adults without insomnia complaints (controls, n = 100) using dual-night in-lab nocturnal polysomnography, study questionnaires and 7 days of at-home actigraphy and sleep diaries. Cases were noted to have reduced objective total sleep time compared with controls (25.8 +/- 8.56 min, P = 0.003). This was largely due to increased wakefulness after sleep onset, and not increased sleep latency. When participants with sleep-related breathing disorder or periodic limb movement disorder were excluded, the polysomnography total sleep time difference became even larger. Cases also had reduced slow-wave sleep (5.10 +/- 1.38 min versus 10.57 +/- 2.29 min, effect size -0.29, P = 0.04). When comparing self-reported sleep latency and sleep efficiency with objective polysomnographic findings, cases demonstrated low, but statistically significant correlations, while no such correlations were observed in controls. Cases tended to underestimate their sleep efficiency by 1.6% (+/-18.4%), while controls overestimated their sleep efficiency by 12.4% (+/-14.5%). In conclusion, we noted that older adults with insomnia complaints have significant differences in several objective sleep findings relative to controls, suggesting that insomnia complaints in older adults are associated with objective impairments in sleep.