0597 The Relationship Between Sleep Quality and Functional Outcomes Following Acute Stroke and Inpatient Rehabilitation
Bibliographic record
Abstract
Abstract Introduction There is mounting evidence that sleep plays an important role in the rehabilitation and recovery process following acute stroke. Following acute care, many patients with stroke are admitted to inpatient rehabilitation facilities (IRFs), where they undergo intensive, interdisciplinary therapy to recover or relearn functional skills to minimize long-term disability. The role and impact of sleep in this early stage of stroke rehabilitation, however, is poorly understood. The purpose of this study is to investigate the relationship between sleep quality and clinical outcomes in the IRF setting following acute stroke. Methods Patients wore a collection of wearable sensors to measure sleep and wake throughout their IRF stay. Linear mixed-effect models (LMEMs) were built to determine the relationship between functional outcomes and sleep quality. Independent variables were total sleep time (TST) and sleep efficiency (SE) derived from wearable sensors, calculated between two clinical measures. Dependent variables included scores from repeated measures of the 6-Minute Walk Test (6MWT), 10-Meter Walk Test (10MWT), Berg Balance Scale (BBS), and Action Research Arm Test (ARAT). Covariates included demographics such as age and stroke type. Results Fifty-three individuals with stroke (age: 58.26±15.57 years; BMI: 28.27±6.16 kg/m2) consented to participate during their IRF program within 7 days of admission. All individuals were recruited from a single-site IRF between July 2020 and August 2021. The average length of stay was 17.85±6.99 days. There were no significant differences in TST between the first three nights and the last three nights (5.1±1.9 hours vs. 5.2±2.0 hours) or SE (67.8±17.7% vs. 69.0±17.8%). The greater standard deviation of TST was associated with lower 6MWT scores (R2=0.77, beta=−0.48, p=0.06), while the greater standard deviation of SE was associated with lower 10MWT scores (R2=0.80, beta=−0.20, p=0.18). Conclusion Our preliminary findings indicate that greater variability in TST and SE are associated with walking endurance and mobility recovery. Future analyses will investigate additional measures of sleep and activity in IRF settings and their relationship with patient outcomes. This work can inform novel sleep interventions to optimize post-stroke recovery. Support (If Any) This work is supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development (NIH R01HD097786-01A1).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".