MétaCan
Menu
Back to cohort
Record W2327105202 · doi:10.1093/ofid/ofu052.977

1431Comparison of two multiplex PCR techniques for the study of respiratory viruses in Mexican children with pneumonia

2014· article· en· W2327105202 on OpenAlexaboutno aff
Alejandra Pamela González-Rodríguez, Miguel Leonardo García León, C Aranda, Irma López Martínez, Teresa Hernandez Andrade, Jesús Gaitán Meza, Daniel E. Noyola, Alberto Villaseñor Sierra, Gerardo Martínez Aguilar, Luis Fernando Perez Gonzalez, Oscar Alberto Newton-Sánchez, Veronica Firo Reyes, Carlos Nicolas Del Rio Almendarez, José Ignacio Santos Preciado, Rosa María Wong‐Chew

Bibliographic record

VenueOpen Forum Infectious Diseases · 2014
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePneumoniaVirologyPathogenic organismRespiratory systemMultiplex polymerase chain reactionMultiplexMicrobiologyIntensive care medicinePediatricsInternal medicinePolymerase chain reactionBioinformaticsBiologyGeneticsGene

Abstract

fetched live from OpenAlex

Background. Respiratory tract infections are the main cause of morbidity and mortality worldwide. Diagnostic methods have evolved through time and now there are techniques available to detect multiple viruses in one sample. The aims of the study were to identify respiratory viruses in nasal washings from children younger than 5 years old admitted with pneumonia at 6 hospitals from 6 cities in Mexico and to perform a diagnostic test evaluation between 2 multiplex PCR techniques for the detection of respiratory viruses. Methods. 310 nasal washings from children younger than 5 years old with clinical and/or radiological diagnosis of pneumonia were included. Nucleic acid was extracted, and amplified by two methods: xTAG RVP (Luminex Molecular Diagnostics, Toronto, Canada) and Anyplex II RV16 (Seegene, Seoul, Corea). The respiratory viruses detected were: RSV A and B, INF A and B, PIV1, 2, 3 and 4, AdV, MpV, CoV OC43, 229E and NL63, RV A/B/C, EV and HBoV1/2/3/4. The gold standard was a construct (the same result with both techniques, and those with discrepancies were sequenced). Virus frequencies, sensitivity, specificity, positive predictive value and negative predictive value were calculated. Results. The viruses detected were in order of frequency: 43.1% RSV A, 22.9% RV/EV, 7.2% ADV, 6.5% INF A, 3.9% MpV, 2.9% HBoV, 2.6% PIV 3, 2.3% RSV B, 2.3% PIV 4, 2.3% CoV NL63, 1.9% PIV 1, 1.3% PIV 2, 0.9% INF B, 0.9% CoV OC43, 0.6% CoV 229E and 0.3% CoV HKUI. Overall Anyplex II RV16 had a higher sensitivity (90% vs 78.9%) and specificity (97.4% vs 59.4%) compared to xTAG RVP. Anyplex II RV 16 was more sensitive in detecting AdV (100% vs 52.2%), INF A (83.3% vs 53.3%), RSV A (97.8% vs 69.9%) and CoV OC45/HUK1 (100% vs 50%) compared to xTAG RVP, respectively. xTAG RVP was more sensitive in detecting PIV (95% vs 80%), RSV B (80% vs 71.4%), RV/EV (86.9% vs 83.1%) and MpV (90% vs 83.3%) compared to Anyplex II RV 16, respectively. Conclusion. The 3 most frequent pathogens detected in children with pneumonia were RSV, RV and PIV (1/2/3/4). Overall, Anyplex II RV16 had a higher sensitivity and specificity than xTAG RVP for the diagnosis of multiple respiratory viruses. Although, xTAX RVP is more sensitive to detect PIV, RSV B, RV and MpV. Disclosures. R. M. Wong Chew, Seegene: Grant Investigator, Research grant

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.051
GPT teacher head0.396
Teacher spread0.345 · 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 designBench or experimental
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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueOpen Forum Infectious DiseasesSame topicRespiratory viral infections researchFrench-language works237,207