Study on Cognitive Function and Quality of Life of Patients with Depression after Hemorrhagic Stroke
Bibliographic record
Abstract
Objective: To explore the characteristics of the cognitive function and quality of life in patients with depression after hemorrhagic stroke(Post-Stroke Depression, PSD) in different periods. Methods: Prospective cohort study of 57 PSD patients and 91 NPSD patients was designed and the data collection of China Stroke Scale(CSS), Hamilton Depression Scale(HAMD), Montreal Cognitive Assessment(Mo CA) and Barthel Index(BI) occurred during the intervention period at baseline, 6 weeks and 12 weeks. Results: The difference of the Mo CA scores and BI scores between PSD patient and NPSD patient at baseline was not statistically significant(11.6 ±2.9 vs 11.2 ±3.1, P0.05; 45.6 ±8.3 vs 46.2 ±7.2, P0.05 respectively). While the Moca scores and BI scores of PSD patient after 6weeks and 12 weeks after treatment were significantly lower than NPSD patient(13.4±2.3 vs 15.8±2.8, P0.000; 18.2±3.2 vs 22.6±2.4, P0.000; 63.8±6.5 vs 72.2±7.5, P0.000; 77.2±4.1 vs 85.8±5.6, P0.000). Conclusions: The cognitive function was speculated as an independent predictor factor of long-term prognosis of PSD patients, which could help to develop PSD rehabilitation strategies.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".