0947 Sleep-wake Disturbances In The Post-acute Phase Of Stroke Impact Quality Of Life And Outcome
Bibliographic record
Abstract
The objective was to investigate the impact of sleep-wake disturbances (SWD) on cognitive function and quality of life measures in the post-acute phase of stroke. Sex differences were also investigated. Adult stroke (n=58) patients were assessed for SWD via overnight polysomnography. The mean age was 51 ± 2 years and mean latency from injury was 116 ± 13 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 outcome measures were: Montreal Cognitive Assessment (MoCA), Neuro-QoL and Mayo Portland Adaptability Inventory (MPAI). Women had lower AHI (F(1,51)=12.236, p<.01), fewer arousals (F(1,51)=7.184, p<.01), and spent significantly more time in SWS (F(1,51)=5.923, p<.05) than men; however, SWS was reduced in both sexes. SWS made up <3% of TST in 67% of patients. Analysis of NeuroQOL measures indicated the following: Longer latencies to sleep were associated with increases in subjective stigma and depression (p<.05), as well as decreases in positive affect (p<.05). Longer latencies to REM sleep were associated with increases in anxiety and emotional/behavioral dyscontrol (p<.05). Decreased sleep efficiency led to increased emotional/behavioral dyscontrol (p<.05). Increased time in REM sleep decreased subjective sleep disturbance (p<.05). Higher AHI and number of awakenings led to decreased ability to participate and positive affect (p<.05). Decreased sleep efficiency was associated with higher scores on the MPAI, indicating poorer outcomes with disrupted sleep (p<.05). Poorer outcomes measured by the MPAI were also associated with a higher percentage of WASO (p<.05). Male stroke patients display significantly higher AHI, and arousals, and spend significantly less time in SWS than female patients. For both sexes, objective sleep measures were significantly correlated with quality of life measures, where improved sleep indicated better subjective quality of life. Additionally, sleep measures were significantly correlated with outcome measures such as the MPAI. Apnea was not significantly correlated with BMI, which could be indicative of respiratory dysregulation driven by injury-related autonomic disturbances. Support (If Any)
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".