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Record W2888794634 · doi:10.14745/ccdr.v40i07a02

Summary of recommendations for the diagnosis and treatment of malaria by the Committee to Advise on Tropical Medicine and Travel (CATMAT)

2014· article· en· W2888794634 on OpenAlexafffundvenueabout
Andrea K. Boggild, Jason Brophy, Paul Charlebois, Maryanne Crockett, J Geduld, Wayne Ghesquière, Paul McDonald, Pierre Plourde, Peter Teitelbaum, Martin Tepper, Steven R. Schofield

Bibliographic record

VenueCanada Communicable Disease Report · 2014
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsPublic Health Agency of CanadaHealth CanadaUniversity of ManitobaChildren's Hospital Research Institute of ManitobaCanadian Armed ForcesUniversity Health NetworkToronto General HospitalManitoba HealthUniversity of VictoriaChildren's Hospital of Eastern Ontario
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsMalariaMedicineContext (archaeology)Gold standard (test)Intensive care medicineParasitemiaPublic healthEnvironmental healthMedical emergencyFamily medicinePathologyGeographyPlasmodium falciparumInternal medicine

Abstract

fetched live from OpenAlex

Background: On behalf of the Public Health Agency of Canada, the Committee to Advise on Tropical Medicine and Travel (CATMAT) developed the Canadian Recommendations for the Prevention and Treatment of Malaria Among International Travellers 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.Severe or complicated malaria requires admission to hospital for regular monitoring of respiratory rate and pattern, coma score, and glucose and urine output, especially if the patient is unconscious.In high levels of parasitemia, exchange transfusion may be beneficial to remove infected red blood cells and toxic mediators from the circulation, and reduce the parasite load.Because of the elevated risk of severe or complicated malaria, those with a diagnosis of Plasmodium falciparum malaria should also be admitted to hospital or receive initial treatment in an observation unit.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.393
Threshold uncertainty score0.790

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0060.005
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0070.002
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0330.012

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.

Opus teacher head0.038
GPT teacher head0.312
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations14
Published2014
Admission routes4
Has abstractyes

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