Reliability of patient-reported functional outcome in a joint replacement registry
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Patient-reported outcome measures (PROMs) are used by some arthroplasty registries to evaluate results after surgery, but non-response may bias the results. The aim was to identify a potential bias in the outcome scores of subgroups in a cohort of patients from the Danish Shoulder Arthroplasty Registry (DSR) and to characterize non-responders. METHODS: Patient-reported outcome of 787 patients operated in 2008 was assessed 12 months postoperatively using the Western Ontario Osteoarthritis of the Shoulder (WOOS) index. In January 2012, non-responders and incomplete responders were sent a postal reminder. Non-responders to the postal reminder were contacted by telephone. Total WOOS score and WOOS subscales were compared for initial responders (n = 509), responders to the postal reminder (n = 156), and responders after telephone contact (n = 27). The predefined variables age, sex, diagnosis, geographical region, and reoperation rate were compared for responding and non-responding cohorts. RESULTS: A postal reminder increased the response rate from 65% (6% incomplete) to 80% (3% incomplete) and telephone contact resulted in a further increase to 82% (2% incomplete). We did not find any statistically significant differences in total WOOS score or in any of the WOOS subscales between responders to the original questionnaire, responders to the postal reminder, and responders after telephone contact. However, a trend of worse outcome for non-responders was found. The response rate was lower in younger patients. INTERPRETATION: Non-responders did not appear to bias the overall results after shoulder replacement despite a trend of worse outcome for a subgroup of non-responders. As response rates rose markedly by the use of postal reminders, we recommend the use of reminders in arthroplasty registries using PROMs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.045 | 0.113 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".