Obesity and early reoperation rate after elective lumbar spine surgery: a population-based study
Bibliographic record
Abstract
STUDY DESIGN: Population-based retrospective cohort study. CLINICAL QUESTION: Are patients with a body mass index (BMI) of 35 or more who undergo elective lumbar spine surgery at increased risk of post-surgical complications, as evidenced by reoperation within a 3-month period? METHODS: The Alberta Health and Wellness Administrative database was queried to identify patients who underwent elective lumbar spine surgery over a 24-month period. This same database was used to classify subjects as obese (BMI ≥35) and non-obese (BMI <35) and to determine who underwent repeated surgical intervention. The rate of reoperation was determined for both the obese and non-obese groups; further analyses were performed to determine whether certain subjects were at increased risk of reoperation. RESULTS: The point estimate for relative risk for requiring reoperation was 1.73 (95% confidence interval, 1.03-2.90) for obese subjects compared with non-obese subjects. The adjusted point estimate shows that deformity correction surgery is predictive for early reoperation while obesity is not. CONCLUSIONS: In obese subjects we observed an increased complication rate after elective lumbar spine surgery, as evidenced by reoperation rates within 3 months. When we considered other possible associations with reoperation, in adjusted analysis, deformity surgery was found to be predictive of early reoperation.Final class of evidence-prognosisSTUDY DESIGNProspective CohortRetrospective Cohort•Case controlCase seriesMETHODSPatients at similar point in course of treatment•F/U ≥ 85%•Similarity of treatment protocols for patient groups•Patients followed up long enough for outcomes to occur•Control for extraneous risk factorsOverall class of evidenceIIIThe definiton of the different classes of evidence is available on page 55.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".