Factors associated with increased length of stay in degenerative cervical spine surgery: a cohort analysis from the Canadian Spine Outcomes and Research Network
Bibliographic record
Abstract
OBJECTIVE: Postoperative length of stay (LOS) significantly contributes to healthcare costs and resource utilization. The primary goal of this study was to identify patient, clinical, surgical, and institutional variables that influence LOS after elective surgery for degenerative conditions of the cervical spine. The secondary objectives were to examine the variability in LOS and institutional practices used to decrease LOS. METHODS: This was a multicenter observational retrospective cohort study of patients enrolled in the Canadian Spine Outcomes and Research Network (CSORN) between January 2015 and October 2020 who underwent elective anterior cervical discectomy and fusion (ACDF) (1-3 levels) or posterior cervical fusion (PCF) (between C2 and T2) with/without decompression for degenerative conditions of the cervical spine. Prolonged LOS was defined as LOS greater than the median for the ACDF and PCF populations. The principal investigators at each participating CSORN healthcare institution completed a survey to capture institutional practices implemented to reduce postoperative LOS. RESULTS: In total, 1228 patients were included (729 ACDF and 499 PCF patients). The median (IQR) LOS for ACDF and PCF were 1.0 (1.0) day and 5.0 (4.0) days, respectively. Predictors of prolonged LOS after ACDF were female sex, myelopathy diagnosis, lower baseline SF-12 mental component summary score, multilevel ACDF, and perioperative adverse events (AEs) (p < 0.05). Predictors of prolonged LOS after PCF were nonsmoking status, education less than high school, lower baseline numeric rating scale score for neck pain and EQ5D score, higher baseline Neck Disability Index score, and perioperative AEs (p < 0.05). Myelopathy did not significantly predict prolonged LOS within the PCF cohort after multivariate analysis. Of the 8 institutions (57.1%) with an enhanced recovery after surgery (ERAS) protocol or standardized protocol, only 3 reported using an ERAS protocol specific to patients undergoing ACDF or PCF. CONCLUSIONS: Patient and clinical factors predictive of prolonged LOS after ACDF and PCF are highly variable, warranting individual consideration for possible mitigation. Perioperative AEs remained a consistent independent predictor of prolonged LOS in both cohorts, highlighting the importance of preventing intra- and postoperative complications.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".