Accuracy and Outcome of Sonographically Guided Intra-articular Sodium Hyaluronate Injections in Patients With Osteoarthritis of the Hip
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate the accuracy and outcome of sonographically guided intra-articular sodium hyaluronate injections in patients with osteoarthritis of the hip. METHODS: The prospective study involved 10 patients who had the diagnosis of unilateral hip osteoarthritis. The mean age of the patients was 63.2 years (range, 27-80 years). Depending on patient body weight, either a 3.5- to 5-MHz convex transducer or a 5- to 12-MHz linear transducer was used to examine each affected joint. Every subject received 3 injections of sodium hyaluronate, 1 per week for 3 consecutive weeks. With real-time sonographic monitoring, each joint was penetrated with a 20-gauge Chiba needle. Contrast medium was injected initially, and proper intra-articular placement was verified with computed tomography before the hyaluronate injection. Each patient's outcome was assessed on the basis of visual analog scale results and Western Ontario and McMaster Universities osteoarthritis index findings that were recorded before the set of injections and 2, 4, and 6 months after the third injection. RESULTS: Computed tomography confirmed accurate placement in all 30 injections in the study. The visual analog scale and the Western Ontario and McMaster Universities osteoarthritis index scores showed that 80% of the patients had less pain in the joint at 6 months after the last injection. CONCLUSIONS: Sonographically guided intra-articular injection of sodium hyaluronate for patients with hip osteoarthritis is easy to perform and is a safe, economical, and well-tolerated form of treatment. In contrast to fluoroscopic or computed tomographic guidance, the sonographic technique exposes neither the patient nor the physician to radiation.
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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 | 0.009 |
| 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 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".