Perioperative adverse cardiac events in maxillofacial surgery: A systematic review and meta-analysis
Bibliographic record
Abstract
Background and Aims: Maxillofacial surgeries, including procedures to the face, oral cavity, jaw, and head and neck, are common in adults. However, they impose a risk of adverse cardiac events (ACEs). While ACEs are well understood for other non-cardiac surgeries, there is a paucity of data about maxillofacial surgeries. This systematic review and meta-analysis report the incidence and presentation of perioperative ACEs during maxillofacial surgery. Methods: We included primary studies that reported on perioperative ACEs in adults. To standardise reporting, ACEs were categorised as 1. heart rate and rhythm disturbances, 2. blood pressure disturbances, 3. ischaemic heart disease and 4. heart failure and other complications. The primary outcome was ACE presentation and incidence during the perioperative period. Secondary outcomes included the surgical outcome according to the Clavien-Dindo classification and trigeminocardiac reflex involvement. STATA version 17.0 and MetaProp were used to delineate proportion as effect size with a 95% confidence interval (CI). Results: = 0.001). Heart rate and rhythm disturbances resulted in the greatest incidence at 3.84% among the four categories. Most commonly, these ACEs resulted in intensive care unit admission (i.e. Clavien-Dindo score of 4). Conclusion: Despite an incidence of 2.58%, ACEs can disproportionately impact surgical outcomes. Future research should include large-scale prospective studies that may provide a better understanding of the contributory factors and long-term effects of ACEs in patients during maxillofacial surgery.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.029 | 0.020 |
| Bibliometrics | 0.002 | 0.002 |
| 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; both teacher heads 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".