Addressing adherence to guidelines on prevention of acute chemotherapy‐induced nausea and vomiting in pediatric patients
Bibliographic record
Abstract
BACKGROUND: Chemotherapy-induced nausea and vomiting (CINV) is a distressing adverse effect in children receiving cancer treatment. There are evidence-based pediatric clinical practice guidelines (CPG) on chemotherapy emetogenicity and acute CINV prevention, but adherence to these guidelines is low. PROCEDURE: A quality improvement-based study was conducted at McMaster Children's Hospital. The SMART aim was to increase adherence to guidelines on prevention of acute CINV in hospitalized patients receiving high (HEC) and moderately emetogenic chemotherapy (MEC) from baseline 25% to more than 70% by June 2021. Barriers were identified by process mapping, and a series of interventions were implemented. RESULTS: Guideline adherence was assessed in 270 inpatient chemotherapy administrations (HEC, MEC). Data were collected on 131 charts pre interventions and 139 charts post interventions. Interventions included education, addition of guideline-recommended anti-emetics to the inpatient formulary, and implementation of a standardized CPG tool. Initial rates of total CINV guideline adherence were 25%, which improved to 72% post intervention (p < .001). In subgroup analysis, guideline adherence in the MEC group improved from 13% to 34% (p = .015), and in the HEC group from 32% to 93% (p < .001). The most common reason for nonadherence in the HEC group was failure to use aprepitant as anti-emetic, and in MEC was option for ondansetron monotherapy prophylaxis. CONCLUSION: Using quality improvement methodology, barriers to guideline adherence were identified and interventions implemented. Guideline adherence for prevention of CINV improved, particularly in the HEC group but less for the MEC group. Future steps will include sustainability of interventions and addressing adherence in the MEC group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".