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Record W2911835690 · doi:10.1111/apa.14732

Providing clarity around ethical discussion: development of a neonatal intervention score

2019· article· en· W2911835690 on OpenAlexaff
Trisha Prentice, Annie Janvier, Lynn Gillam, Susan Donath, Peter G. Davis

Bibliographic record

VenueActa Paediatrica · 2019
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersNational Health and Medical Research Council
KeywordsMedicineCronbach's alphaPsychological interventionIntervention (counseling)Longitudinal studyCLARITYNeonatal intensive care unitPediatricsIntensive carePredictive validityEmergency medicineIntensive care medicineClinical psychologyNursingPsychometrics

Abstract

fetched live from OpenAlex

AIM: To develop a Neonatal Intervention Score (NIS) to describe the clinical trajectory of a neonate throughout their neonatal intensive care unit (NICU) admission. METHODS: The NIS was developed by modifying the Neonatal Therapeutic Intervention Scoring System (NTISS) to reflect illness severity, dependency on life-sustaining interventions and overall life trajectory on a longitudinal basis, rather than illness burden. Validity for longitudinal use within the NICU was tested by calculating the score for 99 preterm babies born less than 28 weeks at predetermined time points throughout their admission to tertiary level care at two institutions. RESULTS: A total of 1333 NISs were analysed, ranging from 0 to 32.5 (mean 9.77, SD 5.4). Internal consistency (Cronbach alpha) reached 0.8. NIS moderately correlated to both SNAPPE-II and SNAP-II (Spearman's rho = 0.47, p =< 0.001) within the first 24 hours. CONCLUSION: The NIS is a useful and reliable descriptive tool of relative illness severity and degree of medical interventions throughout a baby's admission. Integrating a longitudinal description of medical dependency of a patient may assist both clinical and ethical decision-making and empirical research by providing an objective account of a baby's clinical trajectory. Establishment of validity within individual institutions is required.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.362
Teacher spread0.316 · 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 designOther design
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

Citations8
Published2019
Admission routes1
Has abstractyes

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