Correlative study of cognitive dysfunction, activities of daily living and quality of life in patients with traumatic brain injury
Bibliographic record
Abstract
Objective To investigate the current situation and correlation of cognitive dysfunction, activities of daily living (ADL) and quality of life in patients with traumatic brain injury (TBI) . Methods A total of 148 patients hospitalized in the Rehabilitation Department of the Second Affiliated Hospital of Kunming Medical University from January to December 2016 were included in this study. The Montreal cognitive assessment scale (MoCA) , modified Barthel Index scale (MBI) and WHO quality of life scale (WHO-QOL) were used to investigate the status of patients with traumatic brain injury. Results There were 78 of 148 patients with cognitive dysfunction and the incidence rate was 52.98%. Cognitive dysfunction after TBI was significantly positively related to the ADL ability (r=0.968, P<0.01) ; the visual space and executive function, attention, abstraction, delayed recall and orientation had the prediction effect on the ADL ability. Cognitive dysfunction after TBI was significantly positively related to the quality of life (r=0.973, P<0.01) ; cognitive items except the name could predict the quality of life. Conclusions There is a high incidence of cognitive dysfunction in patients with traumatic brain injury, which can affect their ADL ability and quality of life. It is necessary to take effective measures to improve the rehabilitation training of the cognitive function in early stage. Key words: Traumatic brain injury; Cognitive dysfunction; Activities of daily living; Quality of life
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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) | 0.001 | 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".