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Record W4308053484 · doi:10.1542/peds.2022-056415k

Analgesia, Sedation, and Anesthesia for Neonates With Cardiac Disease

2022· article· en· W4308053484 on OpenAlexaff
Melissa Smith-Parrish, Dianna P. Vargas Chaves, Katherine Taylor, Barbara-Jo Achuff, Javier J. Lasa, Andrew Hopper, Chandra Ramamoorthy

Bibliographic record

VenuePEDIATRICS · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineSedationEmergence deliriumAnesthesiaDeliriumIntensive care medicineAdverse effectNeurocognitiveAnestheticDiseaseAirway managementBradycardiaHeart diseaseAirwayCognitionBlood pressureHeart ratePsychiatry

Abstract

fetched live from OpenAlex

Analgesia, sedation, and anesthesia are a continuum. Diagnostic and/or therapeutic procedures in newborns often require analgesia, sedation, and/or anesthesia. Newborns, in general, and, particularly, those with heart disease, have an increased risk of serious adverse events, including mortality under anesthesia. In this section, we discuss the assessment and management of pain and discomfort during interventions, review the doses and side effects of commonly used medications, and provide recommendations for their use in newborns with heart disease. For procedures requiring deeper levels of sedation and anesthesia, airway and hemodynamic support might be necessary. Although associations of long-term deleterious neurocognitive effects of anesthetic agents have received considerable attention in both scientific and lay press, causality is not established. Nonetheless, an early multimodal, multidisciplinary approach is beneficial for safe management before, during, and after interventional procedures and surgery to avoid problems of tolerance and delirium, which can contribute to long-term cognitive dysfunction.

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 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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.024
GPT teacher head0.259
Teacher spread0.235 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations12
Published2022
Admission routes1
Has abstractyes

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