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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".