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Record W1840981603 · doi:10.1186/s40748-015-0025-2

Newborn intensive care survivors: a review and a plan for collaboration in Texas

2015· review· en· W1840981603 on OpenAlexfundno aff
Alice Gong, Yvette R. Johnson, Judith Livingston, Kathleen Matula, Andrea F. Duncan

Bibliographic record

VenueMaternal Health Neonatology and Perinatology · 2015
Typereview
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
FundersUniversity of Texas Health Science Center at San AntonioMcGill UniversityUniversity of OklahomaTexas Children's HospitalTexas Tech University
KeywordsReferralPsychological interventionMedicineNeonatal intensive care unitBest practiceIntensive careDevelopmental MilestoneSummitPediatricsFamily medicineNursingIntensive care medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Neonatal intensive care is a remarkable success story with dramatic improvements in survival rates for preterm newborns. Significant efforts and resources are invested to improve mortality and morbidity but much remains to be learned about the short and long-term effects of neonatal intensive care unit (NICU) interventions. Published guidelines recommend that infants discharged from the NICU be in an organized follow-up program that tracks medical and neurodevelopmental outcomes. Yet, there are no standardized guidelines for provision of follow-up services for high-risk infants. The National Institute of Child Health and Human Development Neonatal Research Network and the Vermont Oxford Network have made strides toward standardizing practices and conducting outcomes research, but only include a subset of developmental follow-up programs with a focus on extremely preterm infants. Several studies have been conducted to gain a better understanding of current practices in developmental follow-up. Some of the major themes in these studies are the lack of personnel and funding to provide comprehensive follow-up care; feeding difficulties as a primary issue for NICU survivors, families, and programs; wide variability in referral and follow-up care practices; and calls for standardized, systematic developmental surveillance to improve outcomes. FINDINGS: We convened a one-day summit to discuss developmental follow-up practices in Texas involving four academic and three nonacademic centers. All seven centers described variable age and weight criteria for follow-up of NICU patients and a unique set of developmental practices, including duration of follow-up, types and timing of developmental assessments administered, education and communication with families and other health care providers, and referrals for services. Needs identified by the centers focused on two main themes: resources and comprehensive care. Participants identified key challenges for developmental follow-up, generated recommendations to address these challenges, and outlined components of a quality program. CONCLUSIONS: The long-term goal is to ensure that all children maximize their potential; a goal supported through quality, comprehensive developmental follow-up care and outcomes research to continuously improve evidence-based practices. We aim to contribute to this goal through a statewide working group collaborating on research to standardize practices and inform policies that truly benefit children and their families.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.051
GPT teacher head0.404
Teacher spread0.353 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2015
Admission routes1
Has abstractyes

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