Use of PROMIS for Patients Undergoing Primary Total Shoulder Arthroplasty
Bibliographic record
Abstract
Background: The Patient-Reported Outcomes Measurement Information System (PROMIS) consists of question banks for health domains through computer adaptive testing (CAT). Hypothesis: For patients with glenohumeral arthritis, (1) there would be high correlation between traditional patient-reported outcome (PRO) measures and the PROMIS upper extremity item bank (PROMIS UE) and PROMIS physical function CAT (PROMIS PF CAT), and (2) PROMIS PF CAT would not demonstrate ceiling effects. Study Design: Cohort study (diagnosis); Level of evidence, 3. Methods: Sixty-one patients with glenohumeral osteoarthritis were included. Each patient completed the American Shoulder and Elbow Surgeons (ASES) assessment form, Marx Shoulder Activity Scale, Short Form–36 physical function scale (SF-36 PF), EuroQol 5 Dimensions (EQ-5D) questionnaire, Western Ontario Osteoarthritis Shoulder (WOOS) index, PROMIS PF CAT, and the PROMIS UE. Correlation was defined as high (>0.7), moderate (0.4-0.6), or weak (0.2-0.3). Significant floor and ceiling effects were present if more than 15% of individuals scored the lowest or highest possible total score on any PRO. Results: The PROMIS PF demonstrated excellent correlation with the SF-36 PF ( r = 0.81, P < .0001) and good correlation with the ASES ( r = 0.62, P < .0001), EQ-5D ( r = 0.64, P < .001), and WOOS index ( r = 0.51, P < .01). The PROMIS PF demonstrated low correlation with the Marx scale ( r = 0.29, P = .02). The PROMIS UE demonstrated good correlation with the ASES ( r = 0.55, P < .0001), SF-36 ( r = 0.53, P < .01), EQ-5D ( r = 0.48, P < .01), and WOOS ( r = 0.34, P <.01), and poor correlation with the Marx scale ( r = 0.06, P = .62). There were no ceiling or floor effects observed. The mean number of items administered by the PROMIS PRO was 4. Conclusion: These data suggest that for a patient population with operative shoulder osteoarthritis, PROMIS UE and PROMIS PF CAT may be valid alternative PROs. Additionally, PROMIS PF CAT offers a decreased question burden with no ceiling effects.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.003 | 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".