Retrospective Comparison of Landmark Based and Ultrasound Guided Suprascapular Nerve Steroid Injections in a Patient
Bibliographic record
Abstract
Background : Suprascapular nerve steroid injections are performed for the relief of chronic shoulder pain. This retrospective comparison between landmark based and ultrasound guidance was undertaken to see the advantages of using ultrasound guidance for the performance of these injections. Methods : After institutional review board approval a chart review of all the suprascapular nerve steroid injections performed between 2005 and 2009 was done. Statistical analysis was performed using T-test and Wilcoxon Rank-Sum test and Mann-Whitney test for the confidence interval. Results : There were a total of 12 suprascapular nerve steroid injections performed. The mean decrease in VAS from pre-procedure for the landmark based was -2.67 + 0.577 and for ultrasound guidance was -4.50 + 1.173. There was a statistically significant difference of changes in VAS between the landmark based and ultrasound guidance (P = 0.0409). The median difference in the change in VAS was 2 points, and the 95% median confidence interval was 0.0 and 3.0. In addition, there was a 50% reduction in the volume of injectate and dose of methylprednisolone using the ultrasound guidance technique. Conclusions : This study shows that there is a possibility for using lesser injectate volume and steroid for suprascapular nerve blocks along with a marginal increase in pain relief with ultrasound guidance. Larger prospective studies are needed to further validate the utility of ultrasound guidance in chronic shoulder pain. doi:10.4021/jnr19e
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".