Effects of different concentrations of desflurane on the index of cardiac electrophysiological balance in gynecologic surgery patients
Bibliographic record
Abstract
The objectives were to observe the effects of different concentrations of desflurane on QT, QTc, Tp-e, Tp-e/QT, and the index of cardiac electrophysiological balance (iCEB). Sixty patients were randomly divided into group D1, group D2, and group D3 by using a random number table, 20 in each group. After entering the operating room, patients received 10 mL/kg hydroxyethyl starch, 0.1 mg/kg midazolam, 0.1 mg/kg vecuronium, 3 μg/kg fentanyl, and 0.3 mg/kg etomidate intravenously and then accepted intubation and mechanical ventilation. The desflurane evaporator was opened. The concentrations of desflurane in the D1, D2, and D3 groups were maintained at 0.6, 1.3, and 2.0 minimum alveolar concentration (MAC), respectively. Twelve-lead ECGs were recorded at time before induction (T1) and at 20 min after desflurane reached the required concentration (T2). HR and MAP were recorded measure and the QT interval, QTc interval, Tp-e interval, Tp-e/QT ratio, and iCEB were calculated. Compared with before inhalation (T1), the QTc interval was prolonged in the D1, D2, and D3 groups after inhalation of different concentrations of desflurane for 20 min (T2) (P < 0.05) and the Tp-e/QT ratio decreased in the D1 and D2 groups at T2 (P < 0.05). Compared with the D1 and D2 groups, the Tp-e/QT ratio of the D3 group increased at T2 (P < 0.05). There was no significant difference in Tp-e interval and iCEB at any time (P > 0.05). The study suggested that inhalation of desflurane at a normal concentration cannot cause arrhythmogenic characteristics and affect the cardiac electrophysiological stability.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".