Comparison of the safety of outpatient cervical disc replacement with inpatient cervical disc replacement
Bibliographic record
Abstract
BACKGROUND: Cervical disc replacement (CDR) has been widely used as an effective treatment for cervical degenerative disc diseases in recent years. However, the cost of this procedure is very high and may bring a great economic burden to patients and the health care system. It is reported that outpatient procedures can reduce nearly 30% of the costs associated with hospitalization compared with inpatient procedures. However, the safety profile surrounding outpatient CDR remains poorly resolved. This study aims to evaluate the current evidence on the safety of outpatient CDR METHODS:: Four English databases were searched. The inclusion and exclusion criteria were developed according to the PICOS principle. The titles and abstracts of the records will be screened by 2 authors independently. Records that meet the eligibility criteria will be screened for a second time by reading the full text. An extraction form will be established for data extraction. Risk of bias assessment will be performed by 2 authors independently using Cochrane risk of bias tool or Newcastle-Ottawa scale. Data synthesis will be conducted using Stata software. Heterogeneity among studies will be assessed using I test. The funnel plot, Egger regression test, and Begg rank correlation test will be used to examine the publication bias. RESULTS: The results of this meta-analysis will be published in a peer-review journal. CONCLUSION: This will be the first meta-analysis that compares the safety of outpatient CDR with inpatient CDR. Our study will help surgeons fully understand the complications and safety profile surrounding outpatient CDR. OSF REGISTRATION NUMBER:: doi.org/10.17605/OSF.IO/3597Z.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.017 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".