IS ULTRASONOGRAPHY AN ACCURATE TOOL IN DETECTING ROTATOR CUFF TEARS? A SYSTEMATIC REVIEW.
Bibliographic record
Abstract
Shoulder pain is a common problem presenting to the primary care physician office. Ultrasonography has shown promises that it is an accurate tool in assessing rotator cuff tear. However, there have been inconsistencies in the reports of its sensitivity, specificity, and predictive values. PURPOSE: To perform a systematic review of studies evaluating the accuracy of ultrasonography in detecting rotator cuff tear. METHODS: Data sources: Systematic search, to August 2001, of MEDICINE (from 1966), CINAHL (from 1982), HealthSTAR (from 1975), hand search of textbooks, and reference lists. Study selection: Studies of any methodological design were included if they evaluated adult patients with painful shoulder problems who received ultrasonography. These studies must provided data on the sensitivity, specificity, and predictive values of the ultrasonographic examination for full thickness or partial thickness tears of the rotator cuff tendons. Data extraction: From the hard copy of the study reports: first author's names, publication years, study designs, types of ultrasound machine used, number of patients entered into the study, number of patients included in the analysis, number of patients dropping out of the studies, and the values of the sensitivity, specificity, predictive values of ultrasonography on partial thickness or full thickness rotator cuff tears. RESULTS: Data synthesis: 20 studies purporting to evaluate the accuracy of ultrasonography in detecting rotator cuff tears were identified and 16 were included in the analysis. Four studies were excluded because they did not specify the extent of the rotator cuff tear. The sensitivity, specificity, and predictive values were quite variable, depending on the type of machines used and the operator. The mean sensitivity, specificity, positive predictive values, negative predictive value, and accuracy of the ultrasonographic examination for full thickness of the rotator cuff tendon were 86.0 (SD = 9.54), 91.9 (SD = 10.72), 91.6 (SD = 10.50), 88.6 (SD = 9.54), and 89.9 (SD = 8.23) respectively. The mean sensitivity, specificity, positive predictive values, negative predictive value, and accuracy of the ultrasonographic examination for partial thickness tear of the rotator cuff tendon were 64.5 (SD = 23.14), 94.9 (SD = 4.84), 79.1 (SD = 15.67), 89.4 (SD = 7.88), and 87.8 (SD = 7.67) respectively. CONCLUSION: Ultrasonography appears to be an accurate tool in detecting rotator cuff tears especially for full thickness tears.
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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 | 0.023 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.018 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".