Anesthetic Influence on Occurrence and Treatment of the Trigemino-Cardiac Reflex
Bibliographic record
Abstract
Trigeminocardiac reflex (TCR) is defined as sudden onset of parasympathetic dysrhythmia including hypotension, apnea, and gastric hypermotility during stimulation of any branches of the trigeminal nerve. Previous publications imply a relation between TCR and depth of anesthesia. To gain more detailed insights into this hypothesis, we performed a systematic literature review.Literature about occurrence of TCR was systematically identified through searching in Cochrane Central Register of Controlled Trials (CENTRAL), PubMed (MEDLINE), EMBASE (Ovid SP), and the Institute for Scientific Information (ISI Web of Sciences) databases until June 2013, as well as reference lists of articles for risk calculation. In this study, TCR was defined as drop in mean arterial blood pressure and heart rate, both >20% to baseline. We calculated intraoperative cerebral state index (CSI) of each TCR-case using a newly developed method. These data were further divided into 3 subgroups: CSI <40 (deep anesthesia), CSI 40-60 (regular anesthesia), and CSI >60 (slight anesthesia).Including 45 studies with 910 patients, 140 (15%) presented with TCR, and 770 (85%) without TCR during operation. TCR occurrence showed a 1.2-fold higher pooled risk slighter anesthesia (CSI <40: 13%, at CSI 40-60: 21%, and at CSI >60: 27%) compared with deeper anesthesia. In addition, we could discover a 1.3-fold higher pooled risk of higher MABP drop with a strong negative correlation (r = -0.935; r = 0.89) and a 4.5-fold higher pooled risk of asystole during TCR under slight anesthesia compared with deeper anesthesia.Our work is the first systematic review about TCR and demonstrates clear evidence for TCR occurrence and a more severe course of the TCR in slight anesthesia underlying the importance of skills in anesthesia management during skull base surgery. Furthermore, we have introduced a new standard method to calculate the depth of anesthesia.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".