1139 Sleep Disturbances In Chronic Stroke Patients: Emotional And Cognitive Impact
Bibliographic record
Abstract
Abstract Introduction The objective was to investigate the impact of sleep-wake disturbances (SWD) on cognition and quality of life in the post-acute phase of stroke. Methods Adult stroke (n=92) patients were assessed for SWD via overnight polysomnography. The mean age was 52 ± 1 years and mean latency from injury was 117 ± 10 days. Sleep measures included total sleep time (TST), sleep and REM latency, percent time in sleep stages, apnea/hypopnea index (AHI), wake after sleep onset (WASO), and arousal index. The primary cognitive/outcome measures were: Montreal Cognitive Assessment (MoCA), California Verbal Learning Test (CVLT-II), Neuro-QoL and Mayo Portland Adaptability Inventory (MPAI). Results Women had lower AHI (F(1,88)=9.360, p<.01), fewer arousals (F(1,90)=4.53, p<.05), and spent significantly more time in SWS (F(1,90)=11.525, p<.001) than men; however, SWS was reduced in both sexes. SWS made up < 3% of TST in 60% of patients and was not correlated with higher AHI. SWDs negatively impacted subjective quality of life (NeuroQOL). Longer latencies to sleep were associated with increased depression (p<.05) and decreased positive affect (p<.01). Increased sleep efficiency led to improved positive affect (p<.05) and decreases in emotional/behavioral dyscontrol (p<.05). Increased time in REM sleep decreased emotional/behavioral dyscontrol (p<.05), while increasing satisfaction with social roles and activities(p<.01). SWDs also negatively impacted cognitive/outcome scores. Increased TST and sleep efficiency led to higher scores on CVLT-II list B and long delay free recall (p<.05), while higher AHI led to poorer performance on long delay and forced choice recognition trials (p<.01). Additionally, non-REM AHI negatively impacted MPAI adjustment scores (F(1,69)=4.036, p<.05). Conclusion Male stroke patients displayed significantly more arousals and spent less time in SWS than females. For both sexes, better sleep indicated improved quality of life. Sleep measures were correlated with cognitive/outcome measures. Non-REM AHI significantly predicted outcome at discharge from rehabilitation facility. Support
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".