The enigma of neurogenic thoracic outlet syndrome following motor vehicle collisions
Bibliographic record
Abstract
BACKGROUND: The concept of neurogenic thoracic outlet syndrome (N-TOS) including upper and lower plexus syndromes secondary to soft tissue neck injury after motor vehicle collisions (MVCs) has been contentious. We considered that analysis of objective data from this group of patients could provide insight into this controversial type of N-TOS. METHODS: During the 10-year period January 2001 through December 2010 we examined patients who had received a diagnosis of N-TOS following an MVC. We graded the principal diagnosis based on the objective data from our physical examination. RESULTS: In total 263 patients received a diagnosis of N-TOS during the study period. At the highest accuracy level of diagnosis there were 56 patients with ulnar entrapment syndrome (UES), 40 with carpal tunnel syndrome (CTS) and 55 with nonorganic disease (NOD), for a total of 151 (57.4%) cases in which the diagnosis of N-TOS was brought into question. The elevated arm stress test (EAST) reproduced the symptoms of UES in 33 of the 56 patients of UES (58.9%) and reproduced the symptoms of CTS in 18 of the 40 patients with CTS (45.0%). CONCLUSION: There appears to be a high incidence of misdiagnosis of N-TOS following MVCs. The EAST is not a prime test for N-TOS.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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 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".