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Record W1894574950 · doi:10.1136/bjsports-2014-094570

Ultrasound-guided hip joint injections are more accurate than landmark-guided injections: a systematic review and meta-analysis

2015· review· en· W1894574950 on OpenAlexaff
Shane Hoeber, Abdel-Rahman Aly, Nigel Ashworth, Sathish Rajasekaran

Bibliographic record

VenueBritish Journal of Sports Medicine · 2015
Typereview
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLandmarkMedicineMeta-analysisAnatomical landmarkMEDLINEInclusion and exclusion criteriaSurgeryComputer scienceInternal medicineArtificial intelligencePathology

Abstract

fetched live from OpenAlex

AIM: To compare the accuracy of ultrasound (US)-guided versus landmark-guided hip joint injections. METHODS: PubMed, Medline and Cochrane libraries were searched up to 31 July 2014. Two independent authors selected studies assessing accuracy of intra-articular hip injections based on predetermined inclusion and exclusion criteria. Selected papers were then evaluated for quality and a meta-analysis of accuracy was performed using random effects models. RESULTS: 4 US-guided (136 hip injections) and 5 landmark-guided (295 hip injections) studies were reviewed. The weighted means for US-guided and landmark-guided hip injection accuracies were 100% (95% CI 98% to 100%) and 72% (95% CI 56% to 85%), respectively. US-guided hip injection accuracy was significantly higher than landmark-guided accuracy (p<0.0001). SUMMARY: This is the first systematic review and meta-analysis of the accuracy of US-guided versus landmark-guided hip joint injections that has revealed that US-guided injections are significantly more accurate than those that are landmark guided. Future studies should compare US with fluoroscopic-guided hip joint injections for accuracy, efficacy, safety profile, cost-effectiveness and patient satisfaction.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0180.003
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.131
GPT teacher head0.382
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations110
Published2015
Admission routes1
Has abstractyes

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