A comparison of the effects of ketamine-midazolam and ketamine-propofol combinations on vital signs of non-cooperative children with dental diseases in a crossover study with repeated measurements: The Bayesian approach
Bibliographic record
Abstract
Background: Vital parameters must be monitored during sedation. This study aimed to evaluate the effects of ketamine-midazolam (KM) and ketamine-propofol (KP) combinations on the heart rate (HR) and oxygen saturation (SPO2 ) of non-cooperative children. The model parameters were estimated using the Bayesian approach. Methods: The data were collected in a double-masked crossover study with repeated measurements (CSWRM). Twenty-two noncooperative children 3–6 years old were included, and the linear mixed model was adopted for data analysis. The Bayesian estimation of the parameters and their 95% credible interval were calculated in SAS 9.4. Results: The mean HR of KM recipients compared to KP recipients was significantly different by 4.47 beats per minute (bpm). The mean HR in KP was lower than KM’s, but SPO2 was not significantly different. Conclusion: Although the two drug combinations did not differ in SPO2 , they differed in HR. As such, the KP combination is recommended.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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 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".