Factors associated with cerebral edema in children under 5 years of age admitted in an intensive care unit and their outcome
Bibliographic record
Abstract
OBJECTIVE: We aimed to evaluate risk factors and outcome of cerebral edema in children with diarrhea. METHODS: In this retrospective chart analysis, data of all diarrheal children under 5 years of age having convulsion and admitted in intensive care unit were retrieved from an electronic medical record system of Dhaka Hospital of International Centre for Diarrhoeal Disease Research, Bangladesh, from 1st January 2011 to 31st December 2016. Comparison of clinical and laboratory characteristics was made between children with (cases = 22) and without cerebral edema (controls = 66). RESULTS: Cases more often had a fatal outcome than controls (36% vs 8%, p = 0.003). In logistic regression analysis, after adjusting for potential confounders, the cases were independently associated with respiratory distress (odds ratio = 5.5, confidence interval = 1.55-19.62, p = 0.008), severe sepsis (odds ratio = 4.6, confidence interval = 1.24-16.77, p = 0.022), and severe malnutrition (odds ratio = 0.16, confidence interval = 0.04-0.74, p = 0.019). A rapid drop (>0.5 mmol/L per hour) in serum sodium did not have any impact on developing cerebral edema (p = 0.090). CONCLUSION: Identification of simple clinical predictors may help in the early treatment of cerebral edema that may further help in reducing deaths in such children especially in resource-poor settings. However, further research with prospective design is needed to consolidate our observation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".