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Record W6959582076 · doi:10.11575/prism/45804

Experience with a triplex arbovirus nucleic acid test (NAT) at a Canadian Public Health Laboratory

2021· other· en· W6959582076 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDengue feverChikungunyamyalgiaArbovirusZika virusDengue virusViremiaNucleic acid test

Abstract

fetched live from OpenAlex

Abstract Background Dengue, chikungunya and zika infections occur in tropical and subtropical regions of the world. We describe the utilization of an in-house nucleic acid test (NAT) targeting all three viruses for febrile returning travelers in Alberta, Canada. Methods NAT was performed until 40 days from symptom onset or exposure due to the prolonged duration of zika virus RNA detection. From Sept 1, 2017 to August 31, 2019, 2552 specimens from 1932 patients were tested. Results Approximately 2% of patients tested were NAT positive for dengue virus (n = 42), chikungunya virus (n = 4), and zika virus (n = 1). The majority presented with fever, myalgia and rash. Regions with the most frequent travel included SouthEast Asia (68.5%), South America (25%) and the Caribbean (6.5%). Ct values were stronger (~ 1.5 logs) for patients within 1–3 days following onset of clinical symptoms than those presenting later. Nineteen patients had urine and plasma submitted; 5 were positive for both specimens and 2 were positive only for dengue virus in the urine. Also, Ct values were lower for plasma when compared to the corresponding urine. RNA was detected until 10 days and 5 days post-exposure in plasma and urine respectively for dengue virus. Conclusions Owing to dengue viremia detected beyond the conventional 7 days and low levels of circulating zika virus globally, a cutoff of 14 days from symptom onset to NAT is sufficient to diagnose acute cases. Inclusion of a zoonotic history form that collects appropriate clinical history results in improved test utilization.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.551
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.001

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 head0.017
GPT teacher head0.207
Teacher spread0.190 · 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 teacher head, not a consensus.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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