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Painful procedures and pain management in newborns admitted to an intensive care unit

2021· article· en· W3208518195 on OpenAlex

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

VenueRevista da Escola de Enfermagem da USP · 2021
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineObservational studyVital signsAnalgesicNeonatal intensive care unitFentanylIntensive careStatisticMedical recordIntensive care unitEmergency medicineIntensive care medicineAnesthesiaPediatricsSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To characterize painful procedures, analgesic strategies, vital signs, and pain scores in hospitalized newborns. METHOD: This is a primary, observational, prospective clinical study, developed in a Brazilian public hospital. Demographic data, painful procedures, pain relief measures, vital signs, and pain scores were collected from the clinical records of 90 newborns admitted to the intensive care unit and evaluated between admission and the third day of admission. For statistical analysis, the software Statistic Package for the Social Sciences and the R Software were used. RESULTS: Newborns underwent 2,732 painful procedures, 540 non-pharmacological and 216 pharmacological strategies. The most frequently performed procedure was the heel prick (20.96%). The most commonly recorded non-pharmacological strategy was dim lighting (28.33%) and continuous fentanyl (48.83%) was the main pharmacological measure adopted. Pain score and vital signs show variability in the period evaluated. CONCLUSION: Despite the high number of painful procedures, pain assessment records do not reflect procedural pain and the use of analgesic strategies was insufficient.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.034
GPT teacher head0.336
Teacher spread0.302 · 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