Diagnostic Test Accuracy of Provocative Maneuvers for the Diagnosis of Carpal Tunnel Syndrome: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to summarize and evaluate the research on the accuracy of provocative maneuvers to diagnose carpal tunnel syndrome (CTS). METHODS: The MEDLINE, CINAHL, Cochrane, and Embase databases were searched, and studies that assessed the diagnostic accuracy of at least 1 provocative test for CTS were selected. Study characteristics and data about the diagnostic accuracy of the provocative tests for CTS were extracted. A random-effects meta-analysis of the sensitivity (Sn) and specificity (Sp) of the Phalen test and Tinel sign was conducted. The risk of bias (ROB) was rated using the QUADAS-2 tool. RESULTS: Thirty-one studies that assessed 12 provocative maneuvers were included. The Phalen test and the Tinel sign were the 2 most assessed tests (in 22 and 20 studies, respectively). The ROB was unclear or low in 20 studies, and at least 1 item was rated as having high ROB in 11 studies. Based on a meta-analysis of 7 studies (604 patients), the Phalen test had a pooled Sn of 0.57 (95% CI = 0.44-0.68; range = 0.12-0.92) and a pooled Sp of 0.67 (95% CI = 0.52-0.79; range = 0.30-0.95). For the Tinel sign (7 studies, 748 patients), the pooled Sn was 0.45 (95% CI = 0.34-0.57; range = 0.17-0.97) and the pooled Sp was 0.78 (95% CI = 0.60-0.89; range = 0.40-0.92). Other provocative maneuvers were less frequently studied and had conflicting diagnostic accuracies. CONCLUSION: Meta-analyses are imprecise but suggest that the Phalen test has moderate Sn and Sp, whereas the Tinel test has low Sn and high Sp. Clinicians should combine provocative maneuvers with sensorimotor tests, hand diagrams, and diagnostic questionnaires to achieve better overall diagnostic accuracy rather than relying on individual clinical tests. IMPACT: Evidence of unclear and high ROB do not support the use of any single provocative maneuver for the diagnosis of CTS. Clinicians should consider a combination of noninvasive clinical diagnostic tests as the first choice for the diagnosis of CTS.
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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 | 0.029 | 0.086 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.040 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".