Bacterial Sepsis in Brazilian Children: A Trend Analysis from 1992 to 2006
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to determine the epidemiology of hospitalized pediatric sepsis in Brazil (1992-2006) and to compare mortality caused by sepsis to that caused by other major childhood diseases. METHODS AND FINDINGS: We performed a retrospective descriptive study of hospital admissions using a government database of all hospital affiliated with the Brazilian health system. We studied all hospitalizations in children from 28 days through 19 years with diagnosis of bacterial sepsis defined by the criteria of the International Classification of Diseases (ICD), (Appendix S1). Based on the data studied from 1992 through 2006, the pediatric hospital mortality rate was 1.23% and there were 556,073 pediatric admissions with bacterial sepsis with a mean mortality rate of 19.9%. There was a case reduction of 67% over 1992-2006 (p<0.001); however, the mortality rate remained unchanged (from 1992-1996, 20.5%; and from 2002-2006, 19.7%). Sepsis-hospital mortality rate was substantially higher than pneumonia (0.5%), HIV (3.3%), diarrhea (0.3%), undernutrition (2.3%), malaria (0.2%) and measles (0.7%). The human development index (HDI) and mortality rates (MR) by region were: North region 0.76 and 21.7%; Northeast region 0.72 and 27.1%; Central-West 0.81 and 23.5%; South region 0.83 and 12.2% and Southeast region 0.82 and 14.8%, respectively. CONCLUSIONS: We concluded that sepsis remains an important health problem in children in Brazil. The institution of universal primary care programs has been associated with substantially reduced sepsis incidence and therefore deaths; however, hospital mortality rates in children with sepsis remain unchanged. Implementation of additional health initiatives to reduce sepsis mortality in hospitalized patients could have great impact on childhood mortality rates in Brazil.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".