Corticosteroid use in neonatal hypotension: A survey of Canadian neonatologists
Bibliographic record
Abstract
OBJECTIVE: To assess prescribing practices and perspectives regarding the use of corticosteroids in the management of neonatal hypotension. METHODS: Cross-sectional questionnaire-based electronic survey of neonatologists (n = 206) practicing at tertiary neonatal intensive care units across 30 academic centres in Canada. RESULTS: The overall response rate was 33% (72/206), with a completion rate was 94%. Most (48/72, 64%) worked in a unit that covered both inborn and outborn infants, and 53% (37/70) worked in units with >100 very low birth weight infants admitted annually. Among the 72 respondents, 39% use a loading dose, of whom most (57%) use 2 mg/kg. Dosing ranges were variable, most using either 0.5 mg/kg or 1 mg/kg, q6h. Among the 56% (40/72) of neonatologists who reported measuring cortisol before initiation of hydrocortisone, cut-offs for initiation of hydrocortisone varied from <100 to <500 nmol/L, most of whom (48%) used <100 nmol/L. Of 71 respondents, 92% (65) indicated that a randomized control trial examining the use of corticosteroids in neonatal hypotension is needed, of whom 52% (37) indicated that the intervention group should receiving hydrocortisone after one vasopressor/inotrope. CONCLUSIONS: This survey provides insight into the prescribing practices of tertiary neonatologists with regards to the use of corticosteroids in neonatal hypotension. While corticosteroids are frequently prescribed, there is variability in the indication, dosing, and duration of corticosteroid use. The findings from this survey can be used to inform further research, including a clinical trial, regarding the practice in the management of neonatal hypotension.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".