Performance of Point-of-Care Diagnostics for Glucose, Lactate, and Hemoglobin in the Management of Severe Malaria in a Resource-Constrained Hospital in Uganda
Bibliographic record
Abstract
Severe malaria is frequently managed without access to laboratory testing. We report on the performance of point-of-care tests used to guide the management of a cohort of 179 children with severe malaria in a resource-limited Ugandan hospital. Correlation coefficients between paired measurements for glucose (i-STAT and One Touch Ultra), lactate (i-STAT and Lactate Scout), and hemoglobin (Hb; laboratory and i-STAT) were 0.86, 0.85, and 0.73, respectively. The OneTouch Ultra glucometer readings deviated systematically from the i-STAT values by +1.7 mmol/L. Lactate Scout values were systematically higher than i-STAT by +0.86 mmol/L. Lactate measurements from either device predicted subsequent mortality. Hb estimation by the i-STAT instrument was unbiased, with upper and lower limits of agreement of -34 and +34 g/L, and it was 91% sensitive and 89% specific for the diagnosis of severe anemia (Hb < 50 g/L). New commercially available bedside diagnostic tools, although imperfect, may expedite clinical decision-making in the management of critically ill children in resource-constrained settings.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".