Evidence-Based Review of Clinical Diagnostic Tests and Predictive Clinical Tests That Evaluate Response to Conservative Rehabilitation for Posterior Glenohumeral Instability: A Systematic Review
Bibliographic record
Abstract
CONTEXT: Posterior glenohumeral instability is poorly understood and can be challenging to recognize and evaluate. Using evidence-based clinical and predictive tests can assist clinicians in appropriate assessment and management. OBJECTIVE: To review evidence-based clinical diagnostic tests for posterior glenohumeral instability and predictive tests that identify responders to conservative management. DATA SOURCES: A comprehensive electronic bibliographic search was conducted using Embase, Ovid MEDLINE, PEDro, and CINAHL databases from their date of inception to February 2017. STUDY SELECTION: Studies were included for further review if they (1) reported on clinical diagnostic tests for posterior or posteroinferior instability of the glenohumeral joint, (2) assessed predictive clinical tests for posterior instability of the glenohumeral joint, and (3) were in English. STUDY DESIGN: Systematic review. LEVEL OF EVIDENCE: Level 4. DATA EXTRACTION: Data were extracted from the studies by 2 independent reviewers and included patient demographics and characteristics, index/reference test details (name and description of test), findings, and data available to calculate psychometric properties. RESULTS: Five diagnostic and 2 predictive studies were selected for review. There was weak evidence for the use of the jerk test, Kim test, posterior impingement sign, and O'Brien test as stand-alone clinical tests for identifying posterior instability. Additionally, there was weak evidence to support the use of the painless jerk test and the hand squeeze sign as predictive tests for responders to conservative management. These findings are attributed to study design limitations, including small and/or nonrepresentative samples. CONCLUSION: Clustering of thorough history and physical examination findings, including the aforementioned tests, may identify those with posterior glenohumeral instability and assist in developing management strategies.
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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 | 0.013 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.010 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".