Incidence of pain after craniotomy in children
Bibliographic record
Abstract
BACKGROUND: There is very few information regarding pain after craniotomy in children. OBJECTIVES: This multicentre observational study assessed the incidence of pain after major craniotomy in children. METHODS: After IRB approval, 213 infants and children who were <10 years old and undergoing major craniotomy were consecutively enrolled in nine Italian hospitals. Pain intensity, analgesic therapy, and adverse effects were evaluated on the first 2 days after surgery. Moderate to severe pain was defined as a median FLACC or NRS score ≥ 4 points. Severe pain was defined as a median FLACC or NRS score ≥ 7 points. RESULTS: Data of 206 children were included in the analysis. The overall postoperative median FLACC/NRS scores were 1 (IQR 0 to 2). Twenty-one children (16%) presented moderate to severe pain in the recovery room and 14 (6%) during the first and second day after surgery. Twenty-six children (19%) had severe pain in the recovery room and 4 (2%) during the first and second day after surgery. Rectal codeine was the most common weak opiod used. Remifentanil and morphine were the strong opioids widely used in PICU and in general wards, respectively. Longer procedures were associated with moderate to severe pain (OR 1.30; CI 1.07-1.57) or severe pain (OR 1.41; 1.09-1.84; P < 0.05). There were no significant associations between complications, pain intensity, and analgesic therapy. CONCLUSION: Children receiving multimodal analgesia experience little or no pain after major craniotomy. Longer surgical procedures correlate with an increased risk of having postoperative pain.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".