Pediatric Sepsis and Septic Shock Management in Resource-Limited Settings
Bibliographic record
Abstract
This chapter provides recommendations on the management of pediatric sepsis in intensive care units (ICUs) in resource-limited settings. Rapidly identification of severe sepsis through a combination of danger signs of end-organ dysfunction or impaired circulation is vital to improve outcome. Better scoring systems for risk stratification tailored for resource-poor settings are needed. Rapid vascular access is critical, and we suggest that in children with septic shock, the placement of an intraosseous line should be considered for vascular access rapidly after an attempt for intravenous access fails. We recommend a careful and individualized approach to fluid administration. For children with severe acute malnutrition without signs of severe shock, we suggest careful administration of intravenous fluids at an initial rate of 10–15 mL/kg/h (no fluid boluses). For well-nourished children who show signs of severely impaired circulation, we suggest careful administration of 10–15 mL/kg of crystalloids over 30–60 min. We recommend incorporation of protocols for timely antibiotic administration, oxygen and respiratory support, and fluid management. We recommend blood transfusion in children with severe anemia and malaria only if there are signs such as respiratory distress or shock or with a hemoglobin concentration below 4 g/dL, requiring rapid transfusion. Children in resource-limited settings with severe respiratory distress and hypoxemia from sepsis could benefit from bubble continuous positive airway pressure (CPAP). Finally, we recommend using a tidal volume of 5–8 mL/kg predicted body weight in all mechanically ventilated children with sepsis-induced lung injury.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".