The effect of platelet-rich plasma in patients with early hip osteoarthritis: a pilot study
Bibliographic record
Abstract
Abstract We investigate whether platelet-rich plasma (PRP) injections can improve symptoms and function in patients with mild to moderate osteoarthritis (OA). Data were prospectively collected and retrospectively reviewed for all patients receiving PRP intra-articular hip injections between February 2017 and June 2017. The inclusion criteria were patients with a well-preserved joint space (Tönnis 0 or 1) whose magnetic resonance imaging (MRI) findings demonstrated degenerative joint disease or a Tönnis grade of 2. The patient-reported outcomes (PROs) used were the modified Harris Hip Score (mHHS), Hip Outcome Score-Activities of Daily Living Subscale (HOS-ADL), Hip Outcome Score-Sports Specific Subscale (HOS-SSS), International Hip Outcome TOOL (iHOT-12), Single Assessment Numeric Evaluation (SANE) and Mental and Physical aspects of the Veteran RAND 12 Item Health Survey (VR-12M and VR-12P). The visual analog scale (VAS) was utilized to indicate pain. Nine patients (11 hips) were eligible for inclusion. All PROs and VAS improved from pre- to post-injection. These improvements were present at the 3-month follow-up visit and stable until the 12-month follow-up. There was statistically significant improvement for mHHS (P < 0.001), HOS-ADL (P = 0.006), iHOT-12 (P = 0.003) and VR-12M (P = 0.005) at 12 months post-injection. Similarly, VAS improved from 4.1 to 2.3, although the change was not statistically significant. PRP injections significantly improved PROs in all measured scales at time points up to a year after intervention, except for VR-12P and HOS-SSS. In conclusion, patients with early OA of the hip had significant improvement of patient-reported functional outcomes up to 12 months after PRP intra-articular injections.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".