Application of nursing team led multidisciplinary cooperative intervention in postoperative cognitive rehabilitation of patients with ischemic stroke
Bibliographic record
Abstract
Objective To explore the application effects of the nursing team led multidisciplinary cooperative intervention in postoperative cognitive rehabilitation of patients with ischemic stroke. Methods From May 2016 to June 2017, 80 patients with cognitive dysfunction after ischemic stroke in a ClassⅢ Grade A hospital in Beijing were selected and randomly divided into observation group and control group based on random number table, with 40 patients in each group. The control group received the routine nursing care and on the basis of that, the observation group received the nursing team led multidisciplinary cooperative intervention. The cognitive function and quality of life in two groups were assessed by the Mini-Mental State Examination (MMSE) , Montreal Cognitive Assessment (MoCA) , and World Health Organization Quality of Life in Brief Version (WHOQOL-BRIEF) before and 6 months after intervention. Results Six months after intervention, the MMSE and MoCA scores of the observation group were (29.35±0.58) and (26.70±2.03) scores, which were statistically different from the control group (t=5.64, 4.15; P<0.05) . The total score, scores of physiological field, psychological field and social field in the quality of life of the observation group were (64.59±5.14) , (16.94±1.43) , (17.10±1.55) , and (15.60±1.07) scores, which were significantly higher than the control group (t=4.82, 5.60, 7.41, 3.23; P<0.01) . Conclusions The nursing team led multidisciplinary cooperative intervention can improve the cognitive function and quality of life in the patients after ischemic stroke and accelerate postoperative recovery forming a virtuous circle. Key words: Multidisciplinary collaboration; Vascular cognitive impairment; Cognitive function; Quality of Life; Interventional training
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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".