Predictive Analytics for Determining Extended Operative Time in Corrective Adult Spinal Deformity Surgery
Bibliographic record
Abstract
Background More sophisticated surgical techniques for correcting adult spinal deformity (ASD) have increased operative times, adding to physiologic stress on patients and increased complication incidence. This study aims to determine factors associated with operative time using a statistical learning algorithm. Methods Retrospective review of a prospective multicenter database containing 837 patients undergoing long spinal fusions for ASD. Conditional inference decision trees identified factors associated with skin-to-skin operative time and cutoff points at which factors have a global effect. A conditional variable-importance table was constructed based on a nonreplacement sampling set of 2000 conditional inference trees. Means comparison for the top 15 variables at their respective significant cutoffs indicated effect sizes. Results Included: 544 surgical ASD patients (mean age: 58.0 years; fusion length 11.3 levels; operative time: 378 minutes). The strongest predictor for operative time was institution/surgeon. Center/surgeons, grouped by decision tree hierarchy, a and b were, on average, 2 hours faster than center/surgeons c-f, who were 43 minutes faster than centers g-j, all P < 0.001. The next most important predictors were, in order, approach (combined vs posterior increases time by 139 minutes, P < 0.001), levels fused (<4 vs 5–9 increased time by 68 minutes, P < 0.050; 5–9 vs < 10 increased time by 47 minutes, P < 0.001), age (age <50 years increases time by 57 minutes, P < 0.001), and patient frailty (score <1.54 increases time by 65 minutes, P < 0.001). Surgical techniques, such as three-column osteotomies (35 minutes), interbody device (45 minutes), and decompression (48 minutes), also increased operative time. Both minor and major complications correlated with <66 minutes of increased operative time. Increased operative time also correlated with increased hospital length of stay (LOS), increased estimated intraoperative blood loss (EBL), and inferior 2-year Oswestry Disability Index (ODI) scores. Conclusions Procedure location and specific surgeon are the most important factors determining operative time, accounting for operative time increases <2 hours. Surgical approach and number of levels fused were also associated with longer operative times, respectively. Extended operative time correlated with longer LOS, higher EBL, and inferior 2-y ODI outcomes. Clinical Relevance We further identified the poor outcomes associated with extended operative time during surgical correction of ASD, and attributed the useful predictors of time spent in the operating room, including site, surgeon, surgical approach, and the number of levels fused. Level of Evidence 3.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".