Summary of recommendations for the diagnosis and treatment of malaria by the Committee to Advise on Tropical Medicine and Travel (CATMAT)
Bibliographic record
Abstract
BACKGROUND: for Canadian health care providers who are preparing patients for travel to malaria-endemic areas and treating travellers who have returned ill. These recommendations aim to achieve appropriate diagnosis and management of malaria, a disease that is still uncommon in Canada. OBJECTIVE: To provide recommendations on the appropriate diagnosis and treatment of malaria. METHODS: CATMAT reviewed all major sources of information on malaria diagnosis and treatment, as well as recent research and national and international epidemiological data, to tailor guidelines to the Canadian context. The evidence-based medicine recommendations were developed with associated rating scales for the strength and quality of the evidence. RECOMMENDATIONS: Malarial management depends on rapid identification of the disease, as well as identification of the malaria species and level of parasitemia. Microscopic identification of blood samples is both rapid and accurate but can be done only by trained laboratory technicians. Rapid diagnostic tests are widely available, are simple to use and do not require specialized laboratory equipment or training; however, they do not provide the level of parasitemia and do require verification. Polymerase chain reaction (PCR), although still limited in availability, is emerging as the gold standard for high sensitivity and specificity in identifying the species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".