Validation of endovascular and open thoracoabdominal aortic aneurysm repair in Ontario health administrative databases
Bibliographic record
Abstract
PURPOSE: The positive predictive value (PPV) of endovascular and open thoracoabdominal aortic aneurysm (TAAA) repair coding was assessed in Ontario health administrative databases. METHODS: Between 1 January 2006 and 31 March 2016, a random sample of 192 patients was identified using Canadian Classification of Health Intervention (CCI) procedure codes and Ontario Health Insurance Plan (OHIP) billing codes from administrative data. Blinded chart reviews were conducted at two cardiovascular centers to assess the level of agreement between the administrative records and the corresponding patients' hospital charts. The PPV was calculated with 95% confidence intervals using hospital charts as the gold standard. RESULTS: The PPV for the single endovascular TAAA repair code, 1ID80GQNRN, was 0.90 (0.78, 0.97). A combination of all nine CCI open TAAA repair codes was performed, with a PPV of 0.62 (0.47, 0.76). The combination of any one of the nine CCI codes AND the single OHIP code for open TAAA repair (R803) rendered a PPV of 0.98 (0.90, 1.00). CONCLUSIONS: Endovascular TAAA repair may be identified using a single CCI code (1ID80GQNRN). Open TAAA repair may be identified using a combination of CCI and OHIP codes. Researchers may therefore use administrative data to conduct population-based studies of endovascular and open repair of TAAA.
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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 | 0.014 | 0.098 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".