Towards the Development of an Outcome Instrument for Spinal Trauma
Bibliographic record
Abstract
In Brief Study Design. International web-based survey. Objective. To identify the most relevant aspects of human function and health status from the perspective of health care professionals involved in the treatment of spinal trauma patients. Summary of Background Data. There is no universally accepted outcome instrument available that is specifically designed or validated for spinal trauma patients, contributing to controversies related to the optimal treatment and evaluation of many types of spinal injuries. Therefore, the AOSpine Knowledge Forum Trauma aims to develop such an instrument using the International Classification of Functioning, Disability, and Health (ICF) as its basis. Methods. Experts from the 5 AOSpine International world regions were asked to give their opinion on the relevance of a compilation of 143 ICF categories for spinal trauma patients on a 3-point scale: “not relevant,” “probably relevant,” or “definitely relevant.” The responses were analyzed using frequency analysis. Possible differences in responses between the 5 world regions were analyzed with the Fisher exact test and descriptive statistics. Results. Of the 895 invited AOSpine International members, 150 (16.8%) participated in this study. A total of 13 (9.1%) ICF categories were identified as definitely relevant by more than 80% of the participants. Most of these categories were related to the ICF component “activities and participation” (n = 8), followed by “body functions” (n = 4), and “body structures” (n = 1). Only some minor regional differences were observed in the pattern of answers. Conclusion. More than 80% of an international group of health care professionals experienced in the clinical care of adult spinal trauma patients indicated 13 of 143 ICF categories as definitely relevant to measure outcomes after spinal trauma. This study creates an evidence base to define a core set of ICF categories for outcome measurement in adult spinal trauma patients. Level of Evidence: N/A To explore the perspective of worldwide experts on aspects relevant to the measurement of outcomes after spinal trauma, a cross-sectional online survey among spine surgeons was conducted. The International Classification of Functioning, Disability, and Health (ICF) system was used as a reference. Thirteen ICF categories were indicated as definitely relevant by more than 80% of the participants.
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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 | 0.167 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".