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Record W4386989411 · doi:10.1093/pch/pxad055.072

72 Criteria for Discharge of Preterm Infants in Canadian Neonatal Intensive Care Units

2023· article· en· W4386989411 on OpenAlexaboutno aff
Walid El‐Naggar, Elise Fieldhouse, Helen McCord

Bibliographic record

VenuePaediatrics & Child Health · 2023
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntensive careMilestoneNeonatologyNeonatal intensive care unitHospital dischargePediatricsFamily medicineBenchmarkingIntensive care medicinePregnancy

Abstract

fetched live from OpenAlex

Abstract Background Discharging to home is a milestone that impacts preterm infants, their parents, and the neonatal intensive care units (NICU). Standardized discharge programs that are individualized for family needs can ensure a safe transfer of care to parents, decrease the length of hospital stay and costs, and improve parental satisfaction. Objectives To assess the degree of variability in discharge criteria for preterm infants <34 weeks’ gestation across Canadian NICUs, explore different institution-specific guidelines, and evaluate the degree of adherence to Canadian Paediatric Society (CPS) guidelines. Design/Methods A clinical representative for each of 117 level 2, 3 and 4 Canadian NICUs was contacted via email to participate in an anonymous survey link (OPINIO) regarding their discharge criteria for preterm infants. French and English versions of the survey were available. Results Ninety-eight respondents (83.7%), representing all Canadian provinces and the NWT, completed the survey (Figure 1). The majority of the responders were nurse practitioners (42.8%) and neonatologists (30.7%) with >5 years of experience (87%). 63% of responses came from level 3 and 4 NICUs. Most respondents (80.6%) lacked written guidelines in their units for discharging preterm infants. 60.2% did not have a dedicated discharge coordinator, and 45% did not have a post-discharge clinic. Table 1 summarizes the different discharge practices. Conclusion There is a significant heterogeneity in discharge practices for preterm infants in Canadian NICUs, despite the presence of CPS guidelines. This survey provides a basis for benchmarking and knowledge-sharing, but more research is needed to guide best evidence-based practice. Potential competing interests Dr. El-Naggar served as a consultant for Aerogen Pharma Limited and is a site investigator of its funded study: A Partially-Blind, Randomized, Controlled, Parallel-Group, Dose-Ranging Study to Determine the Efficacy, Safety and Tolerability of AeroFactTM (SF-RI 1 surfactant for inhalation combined with a dedicated drug delivery system) in Preterm Infants at Risk for Worsening Respiratory Distress Syndrome.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.035
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.053
GPT teacher head0.390
Teacher spread0.337 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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