Spine Adverse Events Severity System
Bibliographic record
Abstract
STUDY DESIGN: A prospective validation study, preliminary single-center report. OBJECTIVE: The purpose of this study was to assess the content validity and interobserver reliability of a simple severity classification system for adverse events (AEs) associated with spinal surgery. SUMMARY OF BACKGROUND DATA: In the surgical literature what is defined as an AE, the severity of an AE, and the reporting of AEs are variable. Consequently, valid comparison of AEs within or among specialties or surgical centers for the same or different procedures is often impossible. METHODS: Since 2002, a Spine Adverse Events Severity system (SAVES) has been locally developed and prospectively used. AEs were graded as I (requires none/minimal treatment, minimal effect [<1-2 days] on length of stay [LOS]), II (requires treatment and/or increases LOS [3-7 days] with no long-term sequelae), III (requires treatment and/or increased LOS [>7 days] with long-term sequelae [>6 months]), and IV (death). Content validity of the grading system was assessed using the hospital chart abstraction (current defacto gold standard) compared with the SAVES from 200 randomly selected patients. Interobserver reliability was assessed in consecutive operative cases for 1 spine surgeon during a 1-year period (2006) using 3 raters (staff surgeon, fellow, and/or resident). RESULTS: The prospectively administered form reported a higher number of surgical AEs (n = 43 vs. n = 30) and a similar number of medical AEs (n = 31 vs. n = 27). Compared with the chart, the AE form displayed substantial agreement for number (70%; weighted Kappa [wK] = 0.60) and type (75%; wK = 0.67) of AE. The interobserver reliability was near perfect (kappa = 0.8) for the actual grade of AE and moderate (kappa = 0.5) for the criteria behind the grading (i.e., clinical effect of the AE or the effect of the AE on LOS or both). CONCLUSION: The result of this study demonstrates improved capture of surgical AEs using SAVES. Excellent interobserver reliability between surgeons at different level of training was demonstrated with minimal education or training regarding the use of SAVES.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".