The relationship between social participation and cognitive function early after surgery of glioma patients
Bibliographic record
Abstract
OBJECTIVE: Social Participation (SP) is known to benefit cognitive function. However, whether this positive relationship holds across the people with glioma has not been studied. The present study aimed to investigate the current status of SP and cognitive function of patients early after surgery with glioma, and therefore, explore the associations between cognitive function and SP. METHODS: This study included 179 postoperative patients with gliomas within 6 months of surgery. Cognitive functioning was measured by the Montreal Cognitive Assessment (MoCA) including orientation, attention, learning and memory, executive functioning and verbal fluency. Social participation was obtained also by questionnaire survey with the Impact on Participation and Autonomy Questionnaire (IPA). The Pearson correlation analysis was used to explore the relation between cognitive functioning and social participation, and the efficacy of social participation in predicting cognitive functioning was evaluated using the receiver operating characteristic (ROC). RESULTS: The prevalence of cognitive impairment in early postoperative glioma patients was 77.65%. The mean level of social participation was 37.96 ± 26.85 points, with poorer scores in the autonomy participation of family role and outdoor engagement dimensions. Patients' cognitive functioning was positively correlated with social participation (r = -0.64, P < 0.001). And The areas under the ROC curve for social participation predicting cognitive function were 0.884. CONCLUSION: Early post-operative cognitive impairment was more common in glioma patients, which was positively correlated with social participation. Social rehabilitation programs for glioma patients should be actively constructed to promote the social participation of patients early after surgery in order to protect their cognitive function.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".