Does a Multidisciplinary Triage Pathway Facilitate Better Outcomes After Spine Surgery?
Bibliographic record
Abstract
STUDY DESIGN: Single-center prospective non-randomized matched cohort comparison. OBJECTIVE: To compare elective lumbar spine surgery outcomes for cases triaged through a multidisciplinary spine pathway versus conventional referral processes. SUMMARY OF BACKGROUND DATA: Many health care systems have facilitated low back pain (LBP) guidelines into primary care practice by creating local or regional "pathways" with the goal of enhanced quality of care, improved patient satisfaction and optimal resource utilization, particularly for imaging and surgery. Few comparative outcomes exist for LBP pathways, particularly for surgical outcomes. METHODS: One-hundred-fifty patients (SSP group n = 75; conventional group n = 75) undergoing elective lumbar surgery for degenerative conditions between 2011 and 2016 were analyzed with 1-year follow-up. Patient self-reported outcomes included the Oswestry disability index (ODI), visual analogue pain scores (VAS) for back and leg, and EuroQol Group 5-Dimension self-report (EQ-5D). We also assessed baseline clinical features, indications for surgery, therapies received prior to surgery, type of surgery, wait times, and overall patient satisfaction. RESULTS: The groups had equivalent baseline demographics, body mass index, Saskatchewan Spine Pathway (SSP) classification of pain pattern, pain scores, functional scores, quality of life scores, indication for surgery, and type of surgery (instrumented or non-instrumented). There was no difference with respect to wait times to see the surgeon or for surgery. Wait time for magnetic resonance imaging (MRI) was significantly shorter for the SSP group (16.8 vs. 63.0 days, P < 0.001). Patients triaged through the SSP were significantly more likely to utilize multiple nonoperative treatment strategies prior to seeing the surgeon (P < 0.04). Patient satisfaction was significantly higher for SSP patients prior to surgical assessment (P = 0.03) but did not differ between groups after surgery. CONCLUSION: The SSP facilitates significantly shorter wait times for MRI and promotes nonoperative treatment strategies. Preoperative patient satisfaction is significantly higher among SSP patients, but there were no significant differences in surgical outcomes.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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".