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Record W3046958156 · doi:10.1016/j.cgh.2020.07.058

Reducing Read Time of Point-of-Care Test Does Not Affect Detection of Hepatitis C Virus and Reduces Need for Reflex RNA

2020· article· en· W3046958156 on OpenAlexaff
David Smookler, Aaron Vanderhoff, Mia J. Biondi, Jorge Valencia, Pablo Ryan, Joel Karkada, Rachel Hong, Erin Mandel, Martina Gjevori, Julia Casey, David Fletcher, Hemant Shah, Bettina E. Hansen, Camelia Capraru, Harry L.A. Janssen, Jeffrey V. Lazarus, Jordan J. Feld

Bibliographic record

VenueClinical Gastroenterology and Hepatology · 2020
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsMaple Leaf Medical ClinicToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersJanssen PharmaceuticalsInstituto de Salud Carlos IIIEuropean CommissionRocheAbbVieAbbott LaboratoriesMerckGlaxoSmithKlineEuropean Social FundGilead SciencesBoehringer Ingelheim
KeywordsMedicineViremiaCohortHepatitis C virusLogistic regressionPoint of careAntibodyHepatitis CTiterNucleic acid testPoint-of-care testingInternal medicineImmunologyVirologyVirusDiseasePathologyCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

BACKGROUND & AIMS: Global elimination of hepatitis C virus (HCV) will require increases in diagnosis. Point of care (POC) tests that detect antibodies against HCV can be useful for testing large and difficult to reach populations. The most accurate POC test requires a 20 min read time to identify antibody-positive samples. We investigated whether viremic patients could be identified using a shorter read time, to increase efficiency and reduce the need for reflex tests (a follow-up test for HCV RNA on the same specimen to confirm viremia). METHODS: Patients with past or current HCV infections provided samples at 2 clinics in Canada for evaluation by the OraQuick HCV Rapid antibody POC test. A community HCV-screening program in Madrid, Spain (real-world cohort) invited people to be tested for HCV with the same OraQuick test. Patients provided samples of whole blood, via finger prick. Fingerprick samples were tested immediately after collection. In the clinic cohort, photographs of the developing test were taken at 15 second intervals, and blinded readers recorded the time to positivity. In the real-world cohort, readers recorded the OraQuick result at 5 minutes, and each minute after, up to 10 minutes, and then again at 20 minutes; viremia was then evaluated using a POC HCV RNA test (GeneXpert HCV Viral Load Assay). Sera from viremic and non-viremic clinic patients were used to quantify antibody titers to investigate the relationship between the time of band appearance and antibody concentration. Fisher's exact test and exact logistic regression were used to determine factors associated with a positive result at 5 minutes. RESULTS: Blood from all viremic patients produced a positive result in the antibody POC test by 5 min. Median time to a positive result for 171 viremic patients was 2.6 min (range, 1.8-4.6 min), vs 4.1 min (range, 2.3-14.4 min) for 108 patients with resolved infection (P < .001). The 5-min threshold identified all viremic cases among 176 HCV antibody-positive patients in the real-world cohort, confirmed by testing for HCV RNA. In the pooled cohorts, antibody positivity at 5 min identified viremic patients with 100% sensitivity (95% CI, 98.4%-100%); the negative predictive value was 100% (95% CI, 94.9%-100%). The positive predictive value at 5 min was 62.0% (95% CI, 56.7%-67.0%) and therefore insufficient alone to detect viremia; an HCV RNA test would still be necessary to confirm active infection. CONCLUSIONS: The wait time for the OraQuick HCV Rapid antibody POC blood test can be reduced from 20 min to 5 min and continue to reliably identify patients with HCV infection. Shortening the test time could increase high-throughput screening, reduce loss to follow up, and reduce the need for reflex HCV RNA testing.

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)0.001
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.050
GPT teacher head0.374
Teacher spread0.324 · 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".

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Citations22
Published2020
Admission routes1
Has abstractno

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