Association Between Pre-Stroke Subjective Sleep Status and Post-Stroke Cognitive Impairment: A Nationwide Multi-Center Prospective Registry
Bibliographic record
Abstract
Jia-Li Zhang,1,2,* An-Xin Wang,1,2,* Yang Yang,2,3 Qin Xu,1,2 Xiao-Ling Liao,1,2 Wei-Guo Ma,4 Ning Zhang,2,3 Chun-Xue Wang,2,3,5 Yong-Jun Wang1,2 1Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, People’s Republic of China; 2China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, People’s Republic of China; 3Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology, Beijing Tiantan Hospital, Capital Medical University, Beijing, People’s Republic of China; 4Beijing Anzhen Hospital, Capital Medical University, Beijing, People’s Republic of China; 5Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ning Zhang; Chun-Xue Wang, Beijing Tiantan Hospital, 119 South 4th Ring West Road, Beijing, 100070, People’s Republic of China, Emails 827582777@qq.com; snowsen@126.comBackground: Although sleep disorders significantly increase the risk of cognitive impairment, literature is relatively scarce regarding the impact of sleep status on cognitive function in patients with acute ischemic stroke (AIS). We seek to study the association between pre-stroke subjective sleep status and cognitive function at 3 months after stroke.Patients and methods: Data were analyzed for 1,759 AIS patients from the Impairment of Cognition and Sleep after Acute Ischemic Stroke or Transient Ischemic Attack in Chinese Patients Study (ICONS). Pre-stroke subjective sleep status was assessed by the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS). Greater sleep fragmentation was defined as waking up in the middle of the night or early morning ≥ 3 times a week. Cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA) at 3 months after stroke. Primary endpoint was the incidence of post-stroke cognitive impairment (PSCI) at 3 months after stroke. The association between subjective sleep status and PSCI was evaluated using multivariable logistic regression.Results: PSCI occurred in 52.1% at 3 months after stroke. Patients with very bad sleep quality before stroke were at increased risk of PSCI (OR, 2.11; 95% CI, 1.11– 4.03; P=0.03). Subgroup analysis found that the association between very bad sleep quality and PSCI was more evident among patients with high school education or above (OR, 5.73; 95% CI, 1.92– 17.10; P for interaction=0.02). In addition, patients with greater sleep fragmentation before stroke were also at higher risk of PSCI (OR, 1.55; 95% CI, 1.20– 2.01; P< 0.01). Similarly, subgroup analysis showed that the risk of PSCI was more pronounced among patients without employment (OR, 2.45; 95% CI, 1.59– 3.77; P for interaction=0.01).Conclusion: Very bad sleep quality and greater sleep fragmentation before stroke were identified as independent risk factors for PSCI at 3 months after stroke.Keywords: subjective sleep status, cognitive impairment, ischemic stroke
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".