Performance of the PROMIS After Operative Interventions for Shoulder Instability
Bibliographic record
Abstract
BACKGROUND: The Patient-Reported Outcomes Measurement Information System (PROMIS) was developed to capture patient-reported outcomes (PROs) in an efficient manner. Few studies have assessed this instrument postoperatively. PURPOSE: To compare the PROMIS Physical Function computer adaptive test (PROMIS PF CAT) and Upper Extremity (PROMIS UE) item bank to other previously validated PRO instruments and to evaluate ceiling and floor effects and construct validity responsiveness in patients who underwent operative interventions for shoulder instability. STUDY DESIGN: Cohort study (diagnosis); Level of evidence, 2. METHODS: A total of 72 patients who underwent operative interventions for shoulder instability completed the American Shoulder and Elbow Surgeons (ASES) assessment form, Marx shoulder activity scale (Marx), 36-Item Short Form Health Survey physical function (SF-36 PF) and general health (SF-36 GH), Western Ontario Shoulder Instability Index (WOSI), PROMIS PF CAT, and PROMIS UE before surgery and then at 6 weeks and 6 months postoperatively. Correlation coefficients were calculated among these tools. The effect size of change was also calculated for each tool at each time point. A total of 91 patients who had also undergone surgery for shoulder instability completed these PRO instruments 2 years postoperatively. The percentage of patients hitting the ceiling and floor effects of each of the PRO instruments was calculated at all time points. RESULTS: < .01). Both the PROMIS PF CAT and PROMIS UE demonstrated the ability to detect change after surgical interventions with a medium to large effect size. The PROMIS UE demonstrated a ceiling effect at 6 months (68.1%) and 2 years (67.0%) postoperatively. The PROMIS PF CAT demonstrated no ceiling effect at any time point. CONCLUSION: The PROMIS PF CAT demonstrated good to excellent correlation with other previously validated PRO instruments that assess physical function in patients with shoulder instability postoperatively. The PROMIS UE demonstrated good correlation with other PRO tools but had a significant ceiling effect and is not recommended for this patient population. Both tools demonstrated an ability to detect change after surgical interventions with a good effect size.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".