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Trends in Asymptomatic Nasopharyngeal Streptococcus pneumoniae Carriage with qPCR and Culture Analysis

2022· article· en· W4306937573 on OpenAlexafffundabout
Julie‐Anne Lemay, Leah J. Ricketson, James D. Kellner

Bibliographic record

VenueMicroorganisms · 2022
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersPfizer CanadaAlberta Precision LaboratoriesPfizer
KeywordsCarriageStreptococcus pneumoniaeMedicineSerotypeSiblingAsymptomaticPediatricsImmunologyInternal medicineMicrobiologyBiologyPathologyAntibioticsPsychology

Abstract

fetched live from OpenAlex

We previously reported trends in pneumococcal nasopharyngeal carriage in the post-PCV13 era as detected by conventional culture methods. Our current aim is to assess if there are fundamental differences in the clinical and demographic features of children who have pneumococcal carriage detected by qPCR compared with culture analysis. The CASPER team conducted point-prevalence surveys in 2016 in healthy children in Calgary to determine trends in overall and serotype-specific pneumococcal nasopharyngeal carriage. Being 18 months of age (p = 0.009), having at least one sibling under 2 years of age (p = 0.04), having only sibling(s) over 2 years of age (p = 0.001), and childcare attendance (p = 0.005) were associated with carriage by qPCR methods only. Having only sibling(s) older than 2 years of age was associated with carriage detected by both qPCR and culture methods (p = 0.001). No clinical factors were associated with carriage detected by both qPCR and culture compared to qPCR methods only. Both analyses are suitable methods to detect carriage; however, qPCR analysis is more sensitive and more cost-effective. As there are no fundamental differences in the children that have pneumococcal nasopharyngeal carriage detectable by qPCR methods compared to conventional culture methods, molecular analysis may be a preferable option for future carriage studies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.244
Teacher spread0.237 · 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.

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

Citations2
Published2022
Admission routes3
Has abstractyes

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