Malaria in Malawi: inside a research autopsy study of pediatric cerebral malaria.
Bibliographic record
Abstract
CONTEXT: Malaria is still a major cause of death in sub-Saharan Africa. OBJECTIVES: To describe my participation as a pathologist in a research autopsy study in Malawi and to examine retinal pathologic findings in cerebral malaria and correlate them with those in the brain. To describe the challenges of conducting a research study in sub-Saharan Africa and the personal and scientific benefits resulting from this. DESIGN: Children with coma are admitted to the pediatric research ward, classified according to the clinical definition of severe malaria or another cause of coma, evaluated, and treated systematically. The eyes are examined by indirect ophthalmoscopy after dilatation. If a child dies and permission is given, a standardized autopsy is carried out. The patients' condition is then reclassified pathologically. RESULTS: Ninety autopsies have been completed, with the cause of death confirmed as cerebral malaria in 64 cases (71.1%). These patients showed heavy parasite sequestration and often extravascular pathologic findings in the brain, retina, gastrointestinal tract, and subcutaneous fat. Clinical and pathologic findings in the retina correlated with those in the brain, and ophthalmoscopy has become a useful tool in the diagnosis and prognosis of children with cerebral malaria. Twenty-eight percent of patients clinically classified as having cerebral malaria showed another cause of death and no malarial pathologic process or retinopathy. CONCLUSIONS: The human, financial, and transportation resources and organization required for this autopsy project are substantial. The scientific benefits are now becoming evident after sufficient autopsies have been completed for detailed comparisons. Personal benefits include the opportunity to work and travel in an African setting and to develop collaborations world-wide.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".