Reported Outcomes and Outcome Measures in Proximal Interphalangeal Joint Arthroplasty: A Systematic Review
Bibliographic record
Abstract
Purpose: There is a lack of scientific consensus on the best arthroplasty implant option for proximal interphalangeal joint (PIPJ) arthritis, due to diversity in outcome reporting and measurement methods. The development of a standardized core outcome set (COS) and standard outcome measures could mitigate this issue. This study catalogs the reported outcomes and outcome measures found in PIPJ arthroplasty studies, which can be used in the first step of developing a COS. Methods: A database search of MEDLINE, EMBASE, and Web of Science (January 1, 2010, to March 10, 2021) was performed to retrieve studies that reported outcomes of the 3 most common primary PIPJ arthroplasty implants: silicone, pyrocarbon, and metal-polyethylene. The primary objectives of this study include reported outcomes and outcome measures. Secondary objectives include clinimetric properties of outcome measures, study design, and implant types. Results: Fifty articles met inclusion criteria. Of the included studies, 41 (82%) were case series, 8 (16%) were cohort studies, and 1 (2%) was a randomized control trial. Thirty-three unique outcomes were identified. Fifteen (46%) outcomes were clinician-reported and 26 (79%) were patient-reported. Eighteen unique outcome measures were identified. Of the outcome measures, 15 (83%) were patient-reported, 1 (6%) was clinician-reported, and 2 (11%) were reported by both patients and clinicians. Conclusions: Substantial heterogeneity was found in reported outcomes and outcome measures across studies evaluating PIPJ arthroplasty, impeding knowledge translation. The development of a COS for PIPJ arthroplasty is necessary to help compare and pool data across studies, and advance scientific knowledge.
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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 | 0.034 | 0.167 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.021 | 0.022 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".