The Burden of Spine Fractures in India
Bibliographic record
Abstract
STUDY DESIGN: Prospective cohort study. OBJECTIVES: The objectives of this study were (1) to determine the characteristics of patients sustaining spinal trauma in India and (2) to explore the association between patient or injury characteristics and outcomes after spinal trauma. METHODS: In affiliation with the ongoing INternational ORthopaedic MUlticentre Study (INORMUS), 192 patients with spinal injuries were recruited during an 8-week period (November 2011 to June 2012) from 14 hospitals in India and followed for 30-days. The primary outcome was a composite of mortality, complications, and reoperation. This was regressed on a set of 13 predictors in a multiple logistic regression model. RESULTS: Most patients were middle-aged (mean age = 51.0 years; median age = 55.5 years; range = 18.0 to 72.0 years), male (60.4%), injured from falls (72.4%), and treated in a private setting (59.9%). Fractures in the lumbar region (51.0%) were most common, followed by thoracic (30.7%) and cervical (18.2%). More than 1 in 5 (21.6%) patients experienced a treatment delay greater than 24 hours, and 36.5% arrived by ambulance. Thirty-day mortality and complication rates were 2.6% and 10.0%, respectively. Care in the public hospital system (odds ratio [OR] = 6.7, 95% CI = 1.1-41.6), chest injury (OR = 11.1, 95% CI = 1.8-66.9), and surgical intervention (OR = 4.8, 95% CI = 1.2-19.6) were independent predictors of major complications. CONCLUSIONS: Treatment in the public health care system, increased severity of injury, and surgical intervention were associated with increased risk of major complications following spinal trauma. The need for a large-scale, prospective, multicenter study taking into account spinal stability and neurologic status is feasible and warranted.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".