Responsiveness of standard spine outcome tools: do they measure up?
Bibliographic record
Abstract
OBJECTIVE: Over the past 2 decades, spine outcome research has become more standardized in response to recommendations from Deyo and others. By using the same generic and condition-specific patient-reported outcome (PRO) measures across studies, results are more easily compared. Given the challenges of maintaining high-quality data in clinical research studies, it would be important to evaluate the contribution of each PRO to confirm that it merits the respondent burden. This study aimed to examine the spine PROs' association with clinically important change and relative responsiveness in explaining variance in patients' global assessment of change (GAC). METHODS: This prospective longitudinal cohort study included adults recruited from 4 active spine surgery practices at a Toronto-based hospital. Patients were diagnosed with a degenerative lumbar spinal condition and underwent spinal decompression and/or fusion surgery. Participants completed the RAND-36 (to generate the physical component score [PCS] and mental component score [MCS]), Oswestry Disability Index (ODI), the numeric rating scale (NRS) for pain, Patient-Reported Outcomes Measurement Information System (PROMIS) pain interference, and a GAC item. Random-effects models were used to investigate the sensitivity of PROs to the GAC and their responsiveness over time (i.e., PRO main effects and PRO-by-time interactions, respectively). RESULTS: The study sample included 168 patients (mean age 61 years, 50% female) with preoperative and up to 12 months of postoperative data. Random-effects models revealed significant main effects for all PROs. Significant time-by-PRO interactions were detected for the PCS, PROMIS, ODI, and NRS (p < 0.0005 in all cases), but not for the MCS. Further examination revealed different sensitivity of the PROs to the GAC at different times. The NRS, PROMIS, and PCS showed higher sensitivity early after surgery, and the PCS evinced a marked drop in sensitivity to the GAC at about 8 months postsurgery. CONCLUSIONS: All PROs currently included in the spine outcome core measures are associated with patients' subjective assessment of a clinically important change, and all but the MCS scores are responsive to such change. Based on these findings, the core spine PROs could be reduced to include fewer estimates of pain. The authors suggest replacing the less responsive measures with tools that help to characterize factors that are driving the patients' subjective assessment of change and that meaningfully address some of the higher levels in the hierarchy of quality-of-life outcomes.
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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 | 0.205 | 0.431 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".