Prediction of Return to Work after Mild Traumatic Brain Injury by Different Assessment Scales
Bibliographic record
Abstract
Background: Mild Traumatic Brain Injury (m-TBI) based on a score of 15 on the Glasgow Coma Scale; a score of 13 or 14 is due to confusion and will be associated with a long duration of posttraumatic amnesia. Identifying factors that increase the risk of m-BTI is necessary to develop public health programs and reduce the risk of being unable to return to work. Therefore, early detection of disability and interven-tion training is a very important treatment strategy to enable the injured patients to return to their works.Aim of Study: Is to predict disability effect on Return to Work (RTW) by assessment scales for patients with mild traumatic brain injury during hospital stay and eight to twelve weeks follow-up.Material and Methods: Different assessment scales in-cluding; Glasgow Coma Scale (GCS), the Montreal Cognitive Assessment (MOCA) Arabic Version, Disability Rating Scale (DRS) and Post Traumatic Amnesia Time (PTAT) were re-ported a detailed understanding of patients temporally changes in physical and mental statues and its impact on successful RTW and community integration. A prospective cohort study of sixty-one patients with mild traumatic brain injury (m-TBI) admitted consecutively to Neurotrauma Departments at Emergency Hospital, in El-Kasr El-Aini Hospital.Results: The results revealed that return to work and recovery from m-TBI occurred after hospital discharging between eight to twelve weeks in 6 patients (9.8%), six to eight weeks in 28 patients (45.9%), two to four weeks in 9 patients (14.8%) and one week in 18 patients (29.5%) and this was supported by using GCS, MOCA [highly predicted (94.86%)] and DRS [highly predicted (96.03%)] scales to predict and develop a suitable work plan according to patient disability.Conclusion: Return to work and recovery from mild traumatic brain injury occurred mainly between six and eight weeks and were followed for twelve weeks post-traumatic, indicating a high rate of predictability using GCS, MOCA, DRS and PTAT and helped to develop a remedial plan suitable for disability reasons.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".