PROMIS Physical Function Score Strongly Correlates With Legacy Outcome Measures in Minimally Invasive Lumbar Microdiscectomy
Bibliographic record
Abstract
STUDY DESIGN: Retrospective cohort. OBJECTIVE: This study aims to determine the validity of the patient-reported outcomes measurement information system (PROMIS) physical function (PF) in minimally invasive lumbar discectomy (MIS LD) patients. SUMMARY OF BACKGROUND DATA: PROMIS was designed to allow for assessment of clinical outcomes in fewer questions than previous outcome measures with the goal of reducing noncompliance associated with longer, time-consuming surveys. However, there exists a paucity of evidence regarding the efficacy of the PROMIS PF domain in patients undergoing MIS LD. METHODS: A surgical database of patients undergoing 1-3 level MIS LD was retrospectively reviewed. Postoperative changes in PROMIS PF scores were analyzed at 6-weeks, 12-weeks, and 6-months using paired Student t tests. PROMIS scores were compared to Oswestry disability index (ODI), visual analog scale (VAS) back, and VAS leg scores. Correlations were tested using Pearson correlation coefficient. RESULTS: Forty-one MIS LD patients were identified, reporting an average preoperative PROMIS PF score of 35.36 ± 7. Patients demonstrated significant improvement in ODI, VAS back, and VAS leg scores. Additionally, strong associations with PROMIS scores were observed for preoperative and postoperative ODI (r range: 0.5735-0.8543) and postoperative VAS back (r range: 0.5332-0.6522) and VAS leg pain (r range: 0.5257-0.6412). CONCLUSION: Patients undergoing MIS LD demonstrated significant improvements in PROMIS PF, ODI, VAS back, and VAS leg pain postoperatively. Additionally, improvements in PROMIS physical function scores at each postoperative time point were determined to be significantly correlated with ODI, VAS back, and VAS leg pain. The results of the current study demonstrate PROMIS PF has strong utility as a postoperative outcome assessment tool. LEVEL OF EVIDENCE: 4.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".