Risk factors for chemotherapy‐induced nausea in pediatric patients receiving highly emetogenic chemotherapy
Bibliographic record
Abstract
BACKGROUND: Little is known regarding risk factors for chemotherapy-induced nausea (CIN) in pediatric patients. PROCEDURE: A secondary analysis was conducted of a previously published multicenter, prospective, randomized, single-blind, sham-controlled trial assessing the efficacy of acupressure in preventing CIN in pediatric patients receiving highly emetogenic chemotherapy. The primary outcome was nausea severity, self-reported using the Pediatric Nausea Assessment Tool. The relationships between acute and delayed nausea severity and patient- (sex, race, age, and cancer diagnosis) and treatment-related (chemotherapy, antiemetic prophylaxis, CIN, and vomiting control) factors were analyzed by a proportional odds generalized estimating equation approach. The acute phase started with administration of the first and continued for 24 hours after the last chemotherapy dose. The delayed phase started at the end of the acute phase and continued until the next chemotherapy block (maximum seven days). RESULTS: In the acute and delayed phases, 165 and 144 patients provided data for analysis, respectively. Nonwhite race was significantly associated with higher acute phase nausea severity (OR, 1.7; 95% CI, 1.1-2.6). Poor CIN control in the acute phase (OR, 16; 95% CI, 4.0-64.6), diagnosis of a cancer other than a central nervous system (CNS) tumor (OR, 2.5; 95% CI, 1.2-5.3), and cisplatin administration (OR, 3.7; 95% CI, 2.1-6.0) were significantly associated with higher delayed phase nausea severity. CONCLUSION: Acute phase CIN was associated with nonwhite race. Delayed phase CIN was associated with poor acute phase CIN control, diagnosis of non-CNS cancer, and receipt of cisplatin. These findings will inform future antiemetic trial design.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".