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Background Patient-reported measures include preferences and reports about care received, health behaviors, and outcomes of care (patient satisfaction and healthrelated quality of life). These measures are a core aspect of health care, but there is much to be learned about how to use them to improve clinical practice. Method We specify linkages among different patient-reported measures and focus upon the prospects and challenges for use of patient-reported outcomes in clinical practice. Results Patient-reported measures are important throughout the continuum of patient care. At the initial visit, patientreported outcomes provide information about what is important to the patient, the patient's current behaviors, and the patient's baseline health-related quality of life. At subsequent visits, patient-reported outcomes help evaluate disease progression or regression as well as treatment effects. Conclusions Patient-reported measures can help clinicians target interventions that will improve patient outcomes of care. However, there are a number of challenges in using patient-reported outcomes in clinical practice.

Nocturia is associated with poor sleep quality; however, little is known about the relationship between nocturia and sleep quality across different workforce-relevant age groups of adults. This has implications for developing new treatment strategies that are well tolerated across populations. We conducted a cross-sectional study involving merged data from the 2005–2006 and 2007–2008 waves of the National Health and Nutrition Examination Survey. Participants responded to validated questions on nocturia frequency and sleep from the Functional Outcomes of Sleep Questionnaire General Productivity subscale (FOSQ-gp, range 1–4). Analyses included multivariable linear regression with stratification by gender to examine associations between nocturia frequency (higher worse) and the FOSQ-gp scores (lower scores indicating worse daytime function related to sleep disturbance). Of 10,512 adults aged ≥20 years who completed the survey, 9148 (87%) had complete nocturia and FOSQ-gp data. The population age-adjusted prevalence of nocturia at least twice nightly was 21.1% among men and 26.6% among women (P < 0.001), and nocturia increased with age (P < 0.001). Compared with those with no or 1 episode of nocturia, those with nocturia at least twice nightly reported lower mean FOSQ-gp scores (3.65; 95% CI, 3.61–3.69 vs 3.19; 95% CI, 3.09–3.31 for men and 3.52; 95% CI, 3.48–3.56 vs 3.09; 95% CI, 3.02–3.16 for women). Older adults (aged >65 years) with greater nocturia frequency reported worse FOSQ-gp scores compared with younger adults with similar nocturia frequency (P < 0.001 among men and women). In a population-based sample of community-dwelling men and women, the association between nocturia and worsened functional outcomes of sleep was greater among adults older than 65 years—a group more vulnerable to drug side effects, and in whom nocturia is typically multifactorial. Additionally, these analyses found that the association between nocturia and functional outcomes of sleep is stronger with increasing age among men. Effective treatment strategies that are well tolerated by older adults, such as multicomponent treatments that simultaneously address the combined effects of lower urinary tract and sleep dysfunction, are needed.

Background Nocturia (i.e., waking to void during the primary sleep period) of two or more times per night affects nearly one-third of older adults and can have a severe impact on sleep, contributing to insomnia symptoms. Current treatment approaches for nocturia often overlook non-lower urinary tract factors that may contribute to nighttime awakenings. Nocturia management, for example, may benefit from more effective integration of cognitive behavioral therapy for insomnia (CBT-I) principles that address other factors underlying insomnia symptoms, and early evidence suggests it also reduces nocturia and the bother it causes. Because nocturia treatment crosses specialties, coordinated delivery of urological and sleep therapies is a treatment barrier. The overall purpose of this trial is to determine whether a promising coordinated, integrated behavioral, non-pharmacological, non-surgical treatment that simultaneously addresses both the urological and insomnia factors contributing to nocturia is efficacious for improving nocturia, sleep, and daytime function. Methods This multicenter parallel-group randomized, efficacy trial compares a 5-week integrated behavioral treatment program delivered by a single interventionist (psychologist, nurse practitioner, or physician assistant) to a health education control program in adults aged 60 years or older (proposed n  = 192) recruited from sites in Atlanta and Los Angeles, who report typically getting up to urinate two or more times per night (International Consultation on Incontinence Questionnaire-Overactive bladder [ICIQ-OAB] nocturia item) and insomnia symptoms (Insomnia Severity Index > 7). The integrated program includes components of CBT-I and pelvic floor muscle exercise-based behavioral therapy for nocturia. The primary outcome is ICIQ-OAB-measured nocturia frequency 4 months after randomization. Secondary outcomes are sleep diary-measured wake after sleep onset (mean minutes) and Insomnia Severity Index total score. Discussion The interdisciplinary trial team has developed a program aimed at improving nocturia symptoms and overall sleep of older adults in an efficient and safe manner. The integrated behavioral program has the potential to address nocturia, which is a challenging symptom because it has many etiologies that cross multiple specialties. Findings will provide rigorous evidence of the efficacy of the integrated behavioral treatment program to reduce nocturia frequency as well as sleep disturbance in older adults. Trial registration Clinicaltrials.gov NCT06110091, registered 10/25/2023.

Study Objectives: Home sleep apnea testing (HSAT) is an efficient and cost-effective method of diagnosing obstructive sleep apnea (OSA). However, nondiagnostic HSAT necessitates additional tests that erode these benefits, delaying diagnoses and increasing costs. Our objective was to optimize this diagnostic pathway by using predictive modeling to identify patients who should be referred directly to polysomnography (PSG) due to their high probability of nondiagnostic HSAT. Methods: HSAT performed as the initial test for suspected OSA within the Veterans Administration Greater Los Angeles Healthcare System was analyzed retrospectively. Data were extracted from pre-HSAT questionnaires and the medical record. Tests were diagnostic if there was a respiratory event index (REI) ≥ 5 events/h. Tests with REI < 5 events/h or technical inadequacy—two outcomes requiring additional testing with PSG—were considered nondiagnostic. Standard logistic regression models were compared with models trained using machine learning techniques. Results: Models were trained using 80% of available data and validated on the remaining 20%. Performance was evaluated using partial area under the precision-recall curve (pAUPRC). Machine learning techniques consistently yielded higher pAUPRC than standard logistic regression, which had pAUPRC of 0.574. The random forest model outperformed all other models (pAUPRC 0.862). Preferred calibration of this model yielded the following: sensitivity 0.46, specificity 0.95, positive predictive value 0.81, negative predictive value 0.80. Conclusions: Compared with standard logistic regression models, machine learning models improve prediction of patients requiring in-laboratory PSG. These models could be implemented into a clinical decision support tool to help clinicians select the optimal test to diagnose OSA. Citation: Stretch R, Ryden A, Fung CH, Martires J, Liu S, Balasubramanian V, Saedi B, Hwang D, Martin J, Della Penna N, Zeidler M. Predicting nondiagnostic home sleep apnea tests using machine learning. J Clin Sleep Med . 2019;15(11):1599–1608.

Background There is evidence of increased risk of cognitive disability due to short sleep duration and adverse Social Determinants of Health (SDoH). To determine whether spatial associations (correlation between spatially distributed variables within a given geographic area) exist between neighborhoods with short sleep duration and cognitive disability across the United States (US) after adjusting for other factors. We conducted a spatial analysis using a spatial lag model at the neighborhood-level with the census tract as unit-of-analysis within each state in the US. We aggregated our results nationally using a weighted analysis to adjust for the number of census tracts per state. This study used Centers for Disease Control and Prevention (CDC) data on short sleep duration, cognitive disability and other health factors. We used 2021–2022 neighborhood-level data from the CDC and US Census Bureau adjusting for social determinants of health (SDoH) and demographics, excluding Florida due to inconsistencies in data availability. Our exposure variable was self-reported short sleep defined by the CDC (“sleep less than 7 hours per 24 hour period”). Our outcome was self-reported cognitive disability defined by the CDC (“difficulty concentrating, remembering, or making decision”). We adjusted for other factors including ‘health outcomes’, ‘preventive practices’, and the CDC’s Social Vulnerability Index. Results The spatial analysis revealed a significant association between short sleep duration and an increased risk of cognitive disability across the US (estimate range [0.29; 1.27], p  < 0.005) after adjustment. Notably, six Western states (New Mexico, Alaska, Arizona, Nevada, Idaho, and Oregon) were at increased risk of cognitive disability due to short sleep duration and this pattern was significant ( p  = 0.007). Conclusions Our study highlights the importance of short sleep duration as a significant predictor of cognitive disability across the US after adjusting for other confounders. The association between short sleep and cognitive disability was especially strong in the Western region of the US providing a deeper understanding of how geographic context and local factors can shape health outcomes.

Objectives To examine the feasibility of individuals with spinal cord injury or disease (SCI/D) to perform combined oropharyngeal and respiratory muscle training (RMT) and determine its impact on their respiratory function. Methods A prospective study at a single Veterans Affairs (VA) Medical Center. Inclusion criteria included: 1) Veterans with chronic SCI/D (>6 months postinjury and American Spinal Injury Association (ASIA) classification A–D) and 2) evidence of OSA by apnea‐hypopnea index (AHI ≥5 events/h). Eligible participants were randomly assigned to either an experimental (exercise) group that involved performing daily inspiratory, expiratory (using POWERbreathe and Expiratory Muscle Strength Trainer 150 devices, respectively), and tongue strengthening exercises or a control (sham) group that involved using a sham device, for a 3‐month period. Spirometry, maximal expiratory pressure (MEP), maximal inspiratory pressure (MIP), polysomnography, and sleep questionnaires were assessed at baseline and at 3 months. Results Twenty‐four individuals were randomized (12 participants in each arm). A total of eight (67%) participants completed the exercise arm, and ten (83%) participants completed the sham arm. MIP was significantly increased (p < 0.05) in the exercise group compared with the baseline. Conclusions Combined oropharyngeal and RMT are feasible for individuals with SCI/D. Future studies are needed to determine the clinical efficacy of these respiratory muscle exercises.

Background Older adults with insomnia who use benzodiazepine receptor agonists (BZAs) may be at increased risk of cognitive impairment. Cognitive testing outside of clinical settings may yield results that are more reflective of individuals’ cognition in their natural environment, where they experience fluctuations in mental state (e.g. drowsiness). We assessed the feasibility of self-administered cognitive testing via smartphone apps for collecting in-moment, in-context data about a person’s current state (ecological momentary assessment, EMA). Methods Participants ( n = 20; median age 66 years; 14 females, 18 white) aged ≥ 55 years who were recruited from a BZA deprescribing trial were invited to complete (over a 28 day period) daily drowsiness assessments on an EMA app (cued by smartwatch alerts) and weekly self-administered digit span (DGS) forward/backward (2 [minimum] – 9 [maximum]), verbal paired associates (VPA; 0 [best]—24 [worst] total errors), and cued delayed recall of VPA (VPA-DR; 0 [best] – 8 [worst] errors) tests on a cognitive app. We assessed the completion of EMA (0–28 days) and cognitive sessions (# of participants per # sessions completed). We performed thematic analysis of the participant interviews. Results The median number of days that EMA was completed was 24.5. Twelve (60%) individuals participated in 4 sessions; 2 (10%) individuals participated in 3 sessions; 2 (10%) individuals participated in 2 sessions; and 4 (20%) individuals participated in 1 session. No drowsiness was reported 36% of the time, whereas 38% of the responses reflected feeling “a little bit” drowsy and 26% at least “somewhat” drowsy. Mean cognitive test scores were DGS-Forward = 7 (SD 1.3), DGS-Backward = 5.6 (SD 1.0), VPA total errors = 9.9 (SD 3.7), and VPA-DR = 2.2 (SD 1.9). Three themes emerged from the participant interviews: 1) concern for one’s own cognitive abilities, 2) strategies employed for optimizing scores (including strategies that would invalidate results), and 3) ease of use of the applications. Conclusions Our findings indicate that mobile cognitive tests and EMAs are feasible in this older population. Further work is needed to understand how scores are influenced by the setting, mood, and behaviors.

Background To determine whether objective markers of sleepiness can be collected passively using voice data to detect sleepiness in individuals undergoing testing in situations where sleepiness is not the focal point of assessment. We assessed verbal reaction time (VRT) as a vocalic marker of subjective sleepiness in middle aged and older adults with history of insomnia and benzodiazepine-receptor-agonist (BZRA) use. Methods Adults aged ≥55 without a diagnosis of dementia were recruited from a BZRA deprescribing clinical trial and enrolled in the present study that tested the feasibility of cognitive testing using out-of-office, self-directed mobile apps. Participants’ working/episodic memory were assessed through recorded verbal responses to Verbal Paired Associates (VPA) tests, and ecological momentary assessments (EMA) of self-reported sleepiness (1[not at all] to 4[more prominent]). Using a generalized additive model, we examined the association between VRT during VPA testing and self-reported sleepiness, adjusting for demographic, test parameters, caffeine intake, cognition, mood, and BZRA-use ( p ≤0.05 was considered significant). A stratified k-fold cross-validation/random forest (SKCV/RF) was performed to classify sleepiness levels, adjusting for other variables. Results We analyzed 1,513 observations from 16 patients. VRT was operationalized as the time duration between recording start time and first speech epoch. Longer VRTs were positively associated with greater EMA sleepiness ( p ≤0.05). The SKCV/RF model yielded a mean F1-score of 0.80 ± 0.08 across folds. Conclusions Longer VRTs correlated with greater self-reported sleepiness, indicating that voice data can be used as a marker of sleepiness in patients undergoing cognitive testing in out-of-office settings.

Intolerance of positive airway pressure therapy for obstructive sleep apnea is common. Upper airway muscle therapies show promise as alternative treatments. The didgeridoo, which is a musical instrument, can be used for upper airway muscle training. Our goal was to develop a group-based didgeridoo training program for obstructive sleep apnea. We conducted a proof-of-concept single-arm study consisting of a structured didgeridoo training regimen. We surveyed patients at a large medical facility about their interest in the program. We developed and tested a manual of procedures for conducting a 4-session group program conducted over 8 weeks that instructed participants on use of the Medical Didgeridoo. We also refined procedures for baseline and 4-month follow-up assessments, which included measures of daytime sleepiness and apnea–hypopnea index. Interviews were conducted at follow-up to obtain feedback about the program. Of the 56 survey respondents, 67% reported difficulty with positive airway pressure, expressed interest in participating in a structured upper airway muscle training program, and indicated that they would be willing to practice exercises for 30 min per day. After in-depth screening of 15 patients, we recruited five patients to participate in the structured training program; all five completed the program and were able to learn to play basic sounds on the provided instrument, and four stated they would continue to play the Medical Didgeridoo after completion of the program. Given the significant level of interest and excellent participation in the didgeridoo training program, it may be feasible to conduct a large-scale study to assess treatment response.

Female veterans are at high risk for sleep problems, and there is a need to provide effective treatment for this population who experience insomnia. This study’s primary goal was to compare the acceptability of medication versus nonmedication treatments for insomnia among female veterans. In addition, we examined the role of patient age, severity of sleep disturbance, and psychiatric symptoms on acceptability of each treatment approach and on the differences in acceptability between these approaches. A large nationwide postal survey was sent to a random sample of 4000 female veterans who had received health care at a Veterans Administration (VA) facility in the previous 6 months (May 29, 2012–November 28, 2012). A total of 1559 completed surveys were returned. Survey items used for the current analyses included: demographic characteristics, sleep quality, psychiatric symptoms, military service experience, and acceptability of medication and nonmedication treatments for insomnia. For analysis, only ratings of “very acceptable” were used to indicate an interest in the treatment approach (vs ratings of “not at all acceptable,” “a little acceptable,” “somewhat acceptable,” and “no opinion/don׳t know”). In the final sample of 1538 women with complete data, 57.7% rated nonmedication treatment as very acceptable while only 33.5% rated medication treatment as very acceptable. This difference was statistically significant for the group as a whole and when examining subgroups of patients based on age, sleep quality, psychiatric symptoms, and military experience. The percentage of respondents rating medication treatment as very acceptable was higher for women who were younger, had more severe sleep disturbances, had more psychiatric symptoms, who were not combat exposed, and who had experienced military sexual trauma. By contrast, the percentage of respondents rating nonmedication treatment as very acceptable differed only by age (younger women were more likely to find nonmedication treatment acceptable) and difficulty falling asleep. Female veterans are more likely to find nonmedication insomnia treatment acceptable compared with medication treatment. Thus, it is important to match these patients with effective behavioral interventions such as cognitive behavioral therapy for insomnia. Efforts to educate providers about these preferences and about the efficacy of cognitive behavioral therapy for insomnia may serve to connect female veterans who have insomnia to the treatment they prefer. These findings also suggest that older female veterans may be less likely to find either approach as acceptable as their younger counterparts.