MétaCan
Menu
Back to cohort
Record W4300434673 · doi:10.1159/000480994

Epidemiology of Adverse Drug Reactions in the Newborn

2019· article· en· W4300434673 on OpenAlex
Jacob V. Aranda, Ana Portuguez-Malavasi, Judith M. Collinge, Terri Germanson, Eugene W. Outerbridge

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDevelopmental Pharmacology and Therapeutics · 2019
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsMcGill UniversityMontreal Children's Hospital
Fundersnot available
KeywordsMedicineEpidemiologyIncidence (geometry)DigoxinIntensive care unitProspective cohort studyEosinophiliaInternal medicineAdverse effectIntensive care medicinePediatricsHeart failure

Abstract

fetched live from OpenAlex

A prospective study on the epidemiology of adverse drug reactions (ADR) in the 200 neonates consecutively admitted to a newborn intensive care unit had shown that 136 ADR occurred in 60 babies (incidence = 30%). 20 of these ADR (14.7%) were major (life-threatening), 34 (25 %) were moderate (prolonged hospital stay) and 82 (60.3 %) were minor (resolved spontaneously, no therapy required). Respiratory depression, cardiac arrhythmias, renal failure, metabolic abnormalities (hyperglycemia, electrolyte imbalance) and gastrointestinal bleeding were the most common major and moderate ADR. Hematologic (eosinophilia, thrombocytopenia) and metabolic (lipemia, hyperglycemia) were the most frequent minor ADR. The case fatality rate is 5 %. Most commonly suspected drugs associated with the ADR were cardiovascular drugs (tolazoline, digoxin, methoxamine), antibiotics, diuretics and components of intravenous nutrition solutions.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.402
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