Ultrasound-Guided Hip Injections with High Density Hyaluronic Acid: Outcome at One Year Follow Up
Bibliographic record
Abstract
Background: The ultrasound-guided viscosupplementation of the hip joint with hyaluronic acid (HA) is considered a standard procedure among the conservative treatments for hip arthritis. The aim of this study was to evaluate the clinical benefit and the incidence of adverse events of the technique in an observational study at one year follow up. Methods: We evaluated a consecutive series of 85 patients with a diagnosis of symptomatic arthritis who underwent intra-articular ultrasound-guided hyaluronic acid injections. The scales used for evaluation were modified Harris Hip Score (mHHS), WOMAC (Western Ontario and McMaster University), and Hip Outcome Score (HOS) with subscale Sport (HOSs), for pain the Visual Analogic Scale (VAS). The patients were classified according to Tonnis’ radiological classification of arthritis (range 0–3): 20 patients (grade 0), 32 (grade 1), 18 (grade 2), 15 (grade 3). Results: At last follow up, all the scales increased: mHHS from 59.35 to 82.1, HOS from 69.45 to 78.53, HOss from 47.4 to 58.11, VAS from 6.09 to 3.97, WOMAC from 33.2 to 31.5 (p < 0.05 for all the parameters); the results were elaborated with GraphPad Prism v5.0 (Prism Software La Jolla, CA, USA) using Wilcoxon’s test. A total of 13 patients out of 85 needed arthroplasty, all classified as Tonnis grade 3. No serious adverse events were noted due to the procedure. Conclusions: Based on our findings, indication for the use of hyaluronic acid is limited to patients with mild to moderate arthritis. Patients in advanced arthritis refusing replacement surgery and asking for this treatment should be informed about the poor results of the technique even in the short term.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".