MétaCan
Menu
Back to cohort
Record W3088033547 · doi:10.1002/pbc.28716

Dexamethasone dosing for prevention of acute chemotherapy‐induced vomiting in pediatric patients: A systematic review

2020· review· en· W3088033547 on OpenAlexaff
Priya Patel, Ana Cornelia Olteanu, Sandra Cabral, Nancy Santesso, Paula D. Robinson, L. Lee Dupuis

Bibliographic record

VenuePediatric Blood & Cancer · 2020
Typereview
Languageen
FieldMedicine
TopicNausea and vomiting management
Canadian institutionsMcMaster UniversityImpactInstitute for Clinical Evaluative SciencesUniversity of TorontoPediatric Oncology GroupSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineDosingDexamethasoneVomitingChemotherapyIntensive care medicineAntiemeticMEDLINEAnesthesiaPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract A systematic review was undertaken to describe dexamethasone doses studied for chemotherapy‐induced vomiting (CIV) prophylaxis in pediatric patients and their effects on achieving complete acute CIV control. No dose‐finding studies were identified. However, 16 studies assessing pediatric patients who received dexamethasone were included and classified according to the emetogenicity of chemotherapy administered. Eight different total daily dexamethasone doses were administered to patients on day 1 of highly emetogenic chemotherapy: three in conjunction with aprepitant/fosaprepitant plus a 5HT3 antagonist and five in conjunction with a 5HT3 antagonist. Five different total daily dexamethasone doses were administered in conjunction with a 5HT3 antagonist to patients on day 1 of moderately emetogenic chemotherapy. Due to the heterogeneity of studies identified, meta‐analysis was not possible. The optimal dexamethasone dose to control acute CIV and to minimize harms in pediatric patients remains uncertain. This is a key area for future research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.045
GPT teacher head0.367
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations14
Published2020
Admission routes1
Has abstractyes

Explore more

Same venuePediatric Blood & CancerSame topicNausea and vomiting managementFrench-language works237,207