Devastating neurologic injuries in the Syrian war
Bibliographic record
Abstract
BACKGROUND: Since 2011, hundreds of thousands of Syrians have been displaced and injured due to the ongoing Syrian civil war. In this study, we report the prevalence of neurologic injuries in a major rehabilitation center on the Turkish-Syrian border where death and injury tolls continue to rise. METHOD: Based on several on-site visits from 2013 to 2016, medical practitioners collected data from patients in the major rehabilitation center on the border of Turkey and Syria. The clinical data, which included the type and cause of injury, laterality, paralysis, areas injured, and treatment offered, were analyzed. RESULTS: A total of 230 patients were identified as having sustained a neurologic injury, 221/230 (96.1%) male and 9/230 (3.91%) female, ranging from ages 2-52 years. A total of 305 total injuries were documented over the course of a 4-year analysis due to several patients having multiple injuries. Gunshot wounds were the dominant mechanism of injury in 125/230 (54.3%) patients. Patients more frequently sustained single injuries 152/230 (66.1%) than multiple injuries 78/230 (33.9%). Peripheral nerve injuries were the most prevalent injuries, at 92.5% of all neurologic injuries (282/305), specifically injury to the radial nerve, at 19.1% (54/282) of peripheral injuries. Patients with spinal cord injuries made up 20/230 (8.7%) of all patients, with thoracic spine injuries composing 50% (10/20). Traumatic brain injuries were the least prevalent, 3/230 (1.3%), with an equal distribution of subtypes. CONCLUSION: This study and critical analysis of the devastation in Syria suggests the desperate need for emergency aid.
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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 | 0.002 | 0.014 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".