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Record W2090085923 · doi:10.1159/000088192

Neonatal Persistent Pulmonary Hypertension Treated with Milrinone: Four Case Reports

2005· article· en· W2090085923 on OpenAlexaff
Dirk Bassler, Karen Choong, Patrick J. McNamara, Haresh Kirpalani

Bibliographic record

VenueNeonatology · 2005
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsHospital for Sick ChildrenMcMaster University Medical Centre
Fundersnot available
KeywordsMilrinoneMedicineAnesthesiaPulmonary hypertensionCardiac indexAfterloadExtracorporeal membrane oxygenationIntensive careCardiologyCardiac outputInternal medicineHemodynamicsIntensive care medicine

Abstract

fetched live from OpenAlex

Current standard therapy for persistent pulmonary hypertension of the newborn (PPHN) consists of optimal lung inflation, hemodynamic support and selective vasodilation with inhaled nitric oxide (iNO). However, not all infants will respond. Milrinone, a phosphodiesterase (PDE) III inhibitor, is routinely used in pediatric cardiac intensive care units to improve inotropy and reduce afterload. Although its use in post-operative cardiac failure has been proven in a randomized trial, it has not been reported to be beneficial in PPHN. We report four cases with severe PPHN treated with a combination of iNO and Milrinone. All four cases were unresponsive to therapy including iNO, with a mean oxygenation index (OI) of 40 (standard deviation (SD) 12)) before Milrinone. Substantial improvement in OI (mean of 28; SD 16) was followed by extubation and survival. However, of 4 patients, 2 developed serious intraventricular hemorrhages (IVHs), and 1 had a small IVH. To clarify the risk benefit ratio, of death versus survival with impairment, a randomized controlled trial is needed.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.261
Teacher spread0.234 · 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 designCase report
Domainnot available
GenreEmpirical

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

Citations142
Published2005
Admission routes1
Has abstractyes

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