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Record W3104241866 · doi:10.1017/ice.2020.1326

Sensitivity of midturbinate versus nasopharyngeal swabs for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

2020· article· en· W3104241866 on OpenAlexafffund
Alainna Jamal, Mohammad Mozafarihashjin, Eric A. Coomes, Sofia Anceva-Sami, Shiva Barati, Gloria Crowl, Amna Faheem, Lubna Farooqi, Christopher Kandel, Saman Khan, Angel X. Li, Henna Mistry, Aimee Paterson, Simon Plenderleith, Karren Prost, Susan M. Poutanen, Jeff Powis, Renée Schryer, Maureen Taylor, Lily Yip, Xi Zhong, Allison McGeer, Samira Mubareka

Bibliographic record

VenueInfection Control and Hospital Epidemiology · 2020
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreToronto East General HospitalSinai Health SystemUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsSalivaMedicineCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Polymerase chain reactionVirologyCoronavirusRespiratory systemInternal medicineBiologyGene

Abstract

fetched live from OpenAlex

To compare sensitivity of specimens for COVID-19 diagnosis, we tested 151 nasopharyngeal/midturbinate swab pairs from 117 COVID-19 inpatients using reverse-transcriptase polymerase chain reaction (RT-PCR). Sensitivity was 94% for nasopharyngeal and 75% for midturbinate swabs (P = .0001). In 88 nasopharyngeal/midturbinate pairs with matched saliva, sensitivity was 86% for nasopharyngeal swabs and 88% for combined midturbinate swabs/saliva.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.077
GPT teacher head0.343
Teacher spread0.266 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations27
Published2020
Admission routes2
Has abstractyes

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