ABSTRACT 255
Bibliographic record
Abstract
Background and aims: Severe shock may rapidly progress to multi-organ failure and death. Despite the lack of conclusive evidence for benefit and the potential for harm, pediatric intensive care physicians continue to report using steroids to treat this condition. Aims: We therefore sought to better understand the epidemiology of steroid use in this patient population. Methods: We conducted a one year, retrospective study of all patients with shock admitted to one of four Canadian PICUs in 2011. This study was approved by the IRB which waived the need for informed consent. Results: 364 patients were enrolled. Patients who received steroids had higher PRISM scores (13 vs 9, P< 0.0001) and were more likely to have received > 60 ml/kg of fluid (50.8% vs 32.9%, P=0.0008). Steroids were more likely to be used in patients with sepsis (50/94; P < 0.0001) and respiratory diseases (14/26; P = 0.05). There was an increase in the number of vasoactive agents used (2 vs 1; P = 0.0054) and the amount of fluid received (18.2 vs 9.0 ml; P = 0.0027) with steroid use after correcting for illness severity. There was no difference in the incidence of gastrointestinal bleeding, use of insulin infusions or positive cultures observed with the use of steroids. Conclusions: Clinicians commonly use steroids in children with fluid or vasoactive infusion dependant shock and these children appear to have worse outcomes but no increase in adverse events. A randomized controlled trial is necessary to determine the true effect of steroids on outcomes in pediatric shock.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.632 | 0.516 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".