Assessment of chemotherapy-induced nausea and vomiting in pediatrics: Adequacy of control and adherence to guidelines
Bibliographic record
Abstract
Chemotherapy-induced nausea and vomiting (CINV) is one of the most common side effects of chemotherapy in patients. Although sufficient evidence regarding its assessment and treatment in adults exists, CINV is more complicated in children. There are established guidelines for its prevention and treatment endorsed by several reputable organizations; however, their adherence varies between institutions. Therefore, this study aimed to assess the incidence and severity of CINV in pediatric patients receiving any form of chemotherapy in the acute and delayed phases and evaluated our institution's adherence to published guidelines by the Pediatric Oncology Group of Ontario. This was a prospective longitudinal single-center study. A structured assessment was administered twice to patients or their caregivers during the acute and delayed phases. Baxter Animated Retching Faces scale was used. A total of 186 patients completed 236 surveys, including those for acute and delayed phases. Incidence of nausea was reported in 33% patients in both phases, while vomiting was observed in 20.3% and 18.8% of the acute and delayed phases, respectively. A total of 31% patients met the criteria for proper adherence in case of prescribed appropriate antiemetic agent(s)/class irrespective of the dose. CINV is a major side effect among children who receive high and moderate emetogenic chemotherapy compared to those receiving minimal and low emetogenic regimens. Despite the low rate of adherence to the guidelines, the incidence and severity of CINV reported in our study were consistent with previous studies. Further research should seek strategies to better implement and standardize these guidelines.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".