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Record W2935240992 · doi:10.5935/0103-507x.20190007

Pharmacological and nonpharmacological measures of pain management and treatment among neonates

2019· article· en· W2935240992 on OpenAlexaff
Hanna Isa Almeida Maciel, Marcela Foureaux Costa, Anna Caroline Leite Costa, Juliana de Oliveira Marcatto, Bruna Figueiredo Manzo, Mariana Bueno

Bibliographic record

VenueRevista Brasileira de Terapia Intensiva · 2019
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicinePsychological interventionNeonatal intensive care unitPain reliefPain managementIntensive careAnesthesiaPediatricsIntensive care medicineNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: This study sought to describe and quantify the pharmacological and nonpharmacological strategies used to relieve the pain/stress of neonates during hospitalization in neonatal intensive care units. METHODS: This quantitative, longitudinal, and descriptive study examined 50 neonates from neonatal intensive care unit admission to discharge. RESULTS: A total of 9,948 painful/stressful procedures were recorded (mean = 11.25 ± 6.3) per day per neonate. A total of 11,722 pain-management and relief interventions were performed, of which 11,495 (98.1%) were nonpharmacological strategies, and 227 (1.9%) were pharmacological interventions. On average, each neonate received 235 pain-management and treatment interventions during hospitalization, 13 nonpharmacological interventions per day, and one pharmacological intervention every 2 days. CONCLUSION: Neonates receive few specific measures for pain relief given the high number of painful and stressful procedures performed during hospitalization. Thus, it is essential to implement effective pain-relief protocols.

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)0.001
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 score0.031
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.031
GPT teacher head0.297
Teacher spread0.266 · 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

Citations88
Published2019
Admission routes1
Has abstractyes

Explore more

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