Clinical application of Ilioinguinal/Iliohypogastric nerve block in pediatric anesthesia of inguinal incision surgery
Bibliographic record
Abstract
Objective:To investigate the clinical application of IINB(Ilioinguinal/Iliohypogastric Nerve Block) in pediatric anesthesia of inguinal incision surgery;and evaluate the effect on the early period of postoperative analgesia.Methods:Forty-eight children required inguinal incision surgeries were randomly divided into two groups: IINB group(n=24) and control group(n=24).In IINB group,IINB was administed after basal anesthesia,while in control group,followed with basal anesthesia,total intravenous anesthesia was administered.Four indexes including the anesthesia effect of IINB at the point of cutting skin,the total dosages of propofol and(or) ketamine during operation,the recover time from anesthesia and the score of CHEOPS(Children's Hospital Eastern Ontario Pain Scale) before leaving PACU(postanesthesia care unit) were observed.Results:The anesthesia effect during operation showed better in IINB group than in control group(P0.01).The total dosage of propofol used in operation in IINB group was less than that in control group,and ketamine need not be used in IINB group.Furthermore,the effect on analgesia in IINB group was better than that in control group at the time of leaving PACU.Conclusion:IINB combined with basal anesthesia is a proper choice for inguigal region surgery in pediatrics.In addition,IINB can provide satisfactory postoperative analgesia.
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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) | 0.001 | 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".