The Diagnostic Process of Spinal Post-traumatic Deformity
Bibliographic record
Abstract
STUDY DESIGN: Survey of cases. OBJECTIVE: To evaluate the opinion of experts in the diagnostic process of clinically relevant Spinal Post-traumatic Deformity (SPTD). SUMMARY OF BACKGROUND DATA: SPTD is a potential complication of spine trauma that can cause decreased function and quality of life impairment. The question of when SPTD becomes clinically relevant is yet to be resolved. METHODS: The survey of 7 cases was sent to 31 experts. The case presentation was medical history, diagnostic assessment, evaluation of diagnostic assessment, diagnosis, and treatment options. Means, ranges, percentages of participants, and descriptive statistics were calculated. RESULTS: Seventeen spinal surgeons reviewed the presented cases. The items' fracture type and complaints were rated by the participants as more important, but no agreement existed on the items of medical history. In patients with possible SPTD in the cervical spine (C) area, participants requested a conventional radiograph (CR) (76%-83%), a flexion/extension CR (61%-71%), a computed tomography (CT)-scan (76%-89%), and a magnetic resonance (MR)-scan (89%-94%). In thoracolumbar spine (ThL) cases, full spine CR (89%-100%), CT scan (72%-94%), and MR scan (65%-94%) were requested most often. There was a consensus on 5 out of 7 cases with clinically relevant SPTD (82%-100%). When consensus existed on the diagnosis of SPTD, there was a consensus on the case being compensated or decompensated and being symptomatic or asymptomatic. CONCLUSIONS: There was strong agreement in 5 out of 7 cases on the presence of the diagnosis of clinically relevant SPTD. Among spine experts, there is a strong consensus to use CT scan and MR scan, a cervical CR for C-cases, and a full spine CR for ThL-cases. The lack of agreement on items of the medical history suggests that a Delphi study can help us reach a consensus on the essential items of clinically relevant SPTD. LEVEL OF EVIDENCE: Level V.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".