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Record W2749930327 · doi:10.1055/s-0037-1606188

Corticosteroid Therapy in Neonatal Septic Shock—Do We Prevent Death?

2017· article· en· W2749930327 on OpenAlexaff
Gabriel Altit, Myriam Vigny-Pau, Keith J. Barrington, Véronique Dorval, Anie Lapointe

Bibliographic record

VenueAmerican Journal of Perinatology · 2017
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineSeptic shockInotropeGestational ageSepsisNecrotizing enterocolitisHemodynamicsHazard ratioShock (circulatory)AnesthesiaBacteremiaRetrospective cohort studyInternal medicinePregnancyConfidence interval

Abstract

fetched live from OpenAlex

Objective The aim was to compare survival of patients with septic shock receiving or not hydrocortisone (HC) and to analyze the hemodynamic response to HC. Study Design It is a retrospective study of 62 premature neonates with septic shock (confirmed bacteremia) and/or necrotizing enterocolitis (NEC) stage 2 and above receiving inotropes with or without HC. We analyzed survival and hemodynamic response to HC. Results Thirty-nine (63%) premature neonates received HC and were compared with 23 (37%) who only received inotropes. Vasoactive index score (VAI) decreased and blood pressure, urine output, and oxygen requirements improved significantly following HC. Despite receiving more inotropes (VAI of 33 [20–53] vs 10 [8–20], p < 0.001), being more premature (26 ± 2 vs 27 ± 2 weeks, p = 0.02) and more frequently having NEC (64 vs 26%, p = 0.004), patients who received HC had similar survival from septic episode (death: 22% vs 41%, p = 0.12). However, patients receiving HC during their sepsis were less likely to survive at their 1-year postmenstrual age follow-up when accounted for gestational age (GA) at birth and duration of inotropes (hazard ratio 6.08 p = 0.01). Conclusion HC was used in infants with increased inotropic support. HC during septic shock was associated with similar survival from episode, but with decreased survival at 1-year postmenstrual age.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.055
GPT teacher head0.367
Teacher spread0.312 · 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

Citations14
Published2017
Admission routes1
Has abstractyes

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