Blood glucose and prognosis in children with presumed severe malaria: is there a threshold for ‘hypoglycaemia’?
Bibliographic record
Abstract
OBJECTIVES: Hypoglycaemia (glucose <2.2 mmol/l) is a defining feature of severe malaria, but the significance of other levels of blood glucose has not previously been studied in children with severe malaria. METHODS: A prospective study of 437 consecutive children with presumed severe malaria was conducted in Mali. We defined hypoglycaemia as <2.2 mmol/l, low glycaemia as 2.2-4.4 mmol/l and hyperglycaemia as >8.3 mmol/l. Associations between glycaemia and case fatality were analysed for 418 children using logistic regression models and a receiver operator curve (ROC). RESULTS: There was a significant difference between blood glucose levels in children who died (median 4.6 mmol/l) and survivors (median 7.6 mmol/l, P < 0.001). Case fatality declined from 61.5% of the hypoglycaemic children to 46.2% of those with low glycaemia, 13.4% of those with normal glycaemia and 7.6% of those with hyperglycaemia (P < 0.001). Logistic regression showed an adjusted odds ratio (AOR) of 0.75 (0.64-0.88) for case fatality per 1 mmol/l increase in baseline blood glucose. Compared to a normal blood glucose, hypoglycaemia and low glycaemia both significantly increased the odds of death (AOR 11.87, 2.10-67.00; and 5.21, 1.86-14.63, respectively), whereas hyperglycaemia reduced the odds of death (AOR 0.34, 0.13-0.91). The ROC [area under the curve at 0.753 (95% CI 0.684-0.820)] indicated that glycaemia had a moderate predictive value for death and identified an optimal threshold at glycaemia <6.1 mmol/l, (sensitivity 64.5% and specificity 75.1%). CONCLUSIONS: If there is a threshold of blood glucose which defines a worse prognosis, it is at a higher level than the current definition of 2.2 mmol/l.
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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 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".