Prevalence of Surgical Site Infections Following Coronectomy: A Systematic Review and Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background/Objectives: This systematic review and meta-analysis aimed to investigate the prevalence of surgical site infections (SSIs) following coronectomy of mandibular third molars. Methods: A comprehensive literature search was conducted in Medline, Scopus, Web of Science, and Google Scholar databases up to 30 July 2024. Two independent reviewers performed study selection, data extraction, and quality assessment using the Newcastle–Ottawa Scale. Observational studies assessing SSI prevalence following coronectomy were included. The pooled prevalence of SSI with 95% confidence intervals (CI) was calculated using a random-effects model. Heterogeneity was assessed using the I2 statistic, and meta-regression was conducted to explore the influence of continuous variables. Results: A total of 22 studies involving 2173 coronectomy procedures were included. The overall pooled prevalence of SSI was 2.4% (95% CI: 1–4.3%), with substantial heterogeneity (I2 = 81%). Meta-regression showed no significant effect of the examined variables on SSI prevalence. No study was identified as a significant outlier. Quality assessments revealed that all studies had moderate methodological quality. Conclusions: Considerable heterogeneity was observed, likely due to variations in study settings, geographical regions, and timeframes, among other factors. Therefore, this study underscores the need for further rigorous research to better understand SSI risk factors and enhance management strategies for this postoperative complication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| 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) | 0.001 | 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 it