Pigmented villonodular synovitis: a crowdsourcing study of two hundred and seventy two patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: We aimed to ascertain the feasibility of crowdsourcing via Facebook for medical research purposes; by investigating surgical, oncological and functional outcome and quality-of-life (QOL) in patients with pigmented villonodular synovitis (PVNS) enrolled in a Facebook community (1112 members). METHODS: Patients completed online open surveys on demographics, surgery and clinical outcomes (group 1); and patient-reported outcome measures (PROMs) including knee-injury osteoarthritis outcome score (KOOS), hip-disability osteoarthritis outcome score (HOOS), Toronto extremity salvage score (TESS) and SF-36 (group 2). Mean follow-up was 70 months (12-374). Consistency checks were performed with Cohen's kappa statistic for intra-rater agreement. RESULTS: The first survey was completed by 272 patients (group 1) and 72 patients completed the second (group 2). In group 1, recurrence-rate was 58 % (69/118) after arthroscopic, 36 % (35/97) after open and 50 % (5/10) after combined synovectomy (p = 0.003). In group 2, recurrence-rate was 67 % (26/39) after arthroscopic and 51 % (17/33) after open synovectomy (p = 0.19). Recurrence-risk was increased for diffuse disease (OR = 16; 95%CI = 3.2-85; p < 0.001). Mean function and QOL did not differ after arthroscopic or open synovectomy: KOOS 49 vs. 58 (p = 0.24), HOOS 62 vs. 53 (p = 0.56), TESS 78 vs. 82 (p = 0.86), SF-36 61 vs. 66 (p = 0.41). Cohen's kappa statistic for intra-rater agreement was good to outstanding (κ = 0.68-0.95; p < 0.001). CONCLUSION: Local recurrence-risk was higher for diffuse-type disease and arthroscopic synovectomy. Functional outcome and QOL were comparable for both types of surgery. Gathering data via crowdsourcing seems a promising and innovative way of evaluating rare diseases including PVNS.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it