Impairment of cognition and sleep after acute ischaemic stroke or transient ischaemic attack in Chinese patients: design, rationale and baseline patient characteristics of a nationwide multicentre prospective registry
Bibliographic record
Abstract
BACKGROUND AND AIM: Cognitive impairment and sleep disorder are both common poststroke conditions and are closely related to the prognosis of patients who had a stroke. The Impairment of CognitiON and Sleep after acute ischemic stroke or transient ischemic attack in Chinese patients (ICONS) study is a nationwide multicentre prospective registry to investigate the occurrence and associated factors of cognitive impairment and sleep disorder after acute ischaemic stroke (AIS) or transient ischaemic attack (TIA). METHODS: Consecutive AIS or TIA in-hospital patients within 7 days after onset were enrolled from 40 participating sites in China. Comprehensive baseline clinical and imaging data were collected prospectively. Blood and urine samples were also collected on admission and follow-up visits. Patients were interviewed face to face for cognition and sleep related outcomes at 2 weeks, 3, 6 and 12 months after AIS/TIA and followed up for clinical outcomes by telephone annually over 5 years. RESULTS: Between August 2015 and January 2018, a total of 2625 patients were enrolled. 92.65% patients had AIS and 7.35% patients had TIA. Overall, the average age was 61.04 years, and 72.38% patients were male. Median National Institutes of Health Stroke Scale score was 3 in AIS patients. CONCLUSIONS: The ICONS study is a large-scale nationwide prospective registry to investigate occurrence and the longitudinal changes of cognitive impairment and sleep disorder after AIS or TIA. Data from this registry may also provide opportunity to evaluate associated factors of cognitive impairment or sleep disorder after AIS or TIA and their impact on clinical outcome.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".