Corticosteroid Therapy in Neonatal Septic Shock—Do We Prevent Death?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".