Comparing Nonrandomized Observational Studies With Randomized Controlled Trials in Cervical Disc Arthroplasty
Bibliographic record
Abstract
STUDY DESIGN: Systematic review and meta-analysis. OBJECTIVE: To compare the treatment effects of observational studies versus randomized controlled trials (RCTs) in cervical disc arthroplasty. SUMMARY OF BACKGROUND DATA: RCTs can be logistically challenging and sometimes insufficiently generalizable; well-designed observational studies have been suggested as an alternative. We hypothesized that treatment effects of observational studies in cervical disc arthroplasty are similar to those of RCTs. METHODS: We searched electronic database from 2000 to 2014. The Neck Disability Index (NDI) was the primary outcome from which the standardized pre-and-post mean difference (Hedges's g) was determined. Meta-analysis was performed to compare Hedges's g from observational studies to that of RCTs. Potential moderator variables including study quality, age, gender, industry sponsorship, location by continent, and disc types were also collected and analyzed. Observational studies were further stratified into prospective and retrospective, and they were compared to each other as well as to RCTs. RESULTS: We identified nine RCTs, 28 observational studies, and one hybrid study for meta-analysis. NDI Hedges's g was 2.15 for RCTs and 2.03 for observational studies, which was not significant (P = 0.416). No significant difference was found in secondary outcomes. However, after further stratification, prospective observational studies had less treatment effect in Visual Analog Scale neck compared with that of RCTs (1.60 vs. 2.11, P = 0.006). RCTs recruited younger patients (44.1 vs. 45.6, P = 0.008) with worse NDI at baseline (54.30 vs. 46.92, P < 0.001). Patients treated with ProDisc-C showed less standardized improvement on the NDI compared with the patients treated with Prestige (1.41 vs. 2.48, P = 0.026). CONCLUSION: Prospective observational studies that utilize the same features of RCTs such as inclusion and exclusion criteria validated clinical outcomes, and statistical methods can provide valuable information about the treatment effects on a generalizable population. LEVEL OF EVIDENCE: 4.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.050 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".