Cardiac cysticercosis and neurocysticercosis in sudden and unexpected community deaths in Lusaka, Zambia: a descriptive medico-legal post-mortem examination study
Bibliographic record
Abstract
BACKGROUND: Cysticercosis is a World Health Organization designated neglected human zoonosis worldwide. Data on cardiac cysticercosis and its contribution to sudden and unexpected community deaths are scarce and require study. METHODS: A study was performed of cysticercosis-related deaths and other incidental cases of cysticercosis seen at forensic post-mortem examination over a period of 12 months, in individuals who died suddenly and unexpectedly in the community in Lusaka, Zambia. Whole-body post-mortem examinations were performed according to standard operating procedures for post-mortem examinations. Representative samples were obtained from all body organs and subjected to histopathological examination. Information was obtained on circumstances surrounding the death. Data were collated on patient demographics, history, co-morbidities, pathological gross and microscopic findings, and forensic autopsy cause(s) of death. The available literature on cardiac cysticercosis was also reviewed. RESULTS: Nine cases of cysticercosis were identified. Eight of the nine cases had cardiac cysticercosis. There was no prior history of cysticercosis before death. All were male, aged between 28 and 56 years, and from high population density and low socioeconomic communities. There was no community case clustering identified. CONCLUSIONS: Cardiac cysticercosis and neurocysticercosis are important incidental findings in sudden and unexpected deaths in the community and can easily be missed antemortem. More investment in forensic autopsy services is required to define the undiagnosed burden of deaths due to treatable communicable diseases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".