Eligibility Criteria of Participants in Randomized Controlled Trials Assessing Conservative Management of Cervical Radiculopathy: A Systematic Review
Bibliographic record
Abstract
STUDY DESIGN: Systematic review. OBJECTIVE: The aim of this study was to evaluate the inclusion and exclusion criteria for participants in randomized control trials (RCTs) assessing conservative management for cervical radiculopathy (CR), to determine if any consensus exists within the literature. SUMMARY OF BACKGROUND DATA: A 2012 systematic review identified a lack of uniformity for the eligibility criteria of participants in RCTs evaluating conservative interventions for CR. Since then, a large number of RCTs have been published, signaling the need for an updated evaluation of this topic. MATERIALS AND METHODS: We electronically searched MEDLINE, CENTRAL, CINAHL, Embase, and PsycINFO from inception to June 15, 2022, to identify RCTs assessing conservative management of CR. Information extracted was analyzed to determine the level of homogeneity and/or heterogeneity of the inclusion and exclusion criteria across studies. RESULTS: Seventy-six RCTs met our inclusion criteria with 68 distinct trials identified. The inclusion of arm pain with or without another symptom ( i.e. numbness, paresthesia, or weakness) was required in 69.12% of trials, 50% of trials required participants to exhibit neck symptoms, and 73.53% of studies required some form of clinical examination findings, but inconsistencies existed for the number and type of tests used. Furthermore, 41.18% of trials included imaging, with 33.82% of trials requiring magnetic resonance imaging findings. The most common exclusion criteria included were the presence of red flags and cervical myelopathy in 66.18% and 58.82% of trials, respectively. CONCLUSIONS: Overall, there is still a lack of uniformity for the inclusion/exclusion criteria of trials assessing the conservative management of CR, with some improvements noted compared with the 2012 review. Based on the current literature assessing the diagnostic utility of clinical symptoms and confirmatory tests, we proposed inclusion criteria for trials assessing conservative interventions. Future research should aim to develop standardized classification criteria to improve consistency among studies.
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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 | 0.216 | 0.415 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.019 | 0.014 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.009 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".