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Age Influences the emm Type Distribution of Pediatric Group A Streptococcal Pharyngeal Isolates

2005· article· en· W2014043601 on OpenAlexaboutno aff
Preeti Jaggi, Robert R. Tanz, Bernard Beall, Stanford T. Shulman

Bibliographic record

VenueThe Pediatric Infectious Disease Journal · 2005
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPharyngitisPharynxBiologyAge groupsGroup AStreptococcusVeterinary medicineMedicineDemographyInternal medicineBacteriaGeneticsAnatomy

Abstract

fetched live from OpenAlex

BACKGROUND: emm types 12, 1, 28, 3, 4, 2 and 6 (in that order) are the types most commonly associated with uncomplicated group A streptococcal (GAS) pharyngitis in the United States, together accounting for approximately 78% of isolates. OBJECTIVE: To determine whether the distribution of common pharyngeal group A streptococcal GAS types differs at various ages throughout childhood. STUDY DESIGN: We emm typed 3356 GAS isolates collected from the United States and Canada during 3 streptococcal seasons (2000-2003). Variations in prevalence by age for the 7 most prevalent emm types and the "uncommon" category (all types accounting for <5% of the total number of isolates) were analyzed and assessed for significance by chi2. RESULTS: The proportion of uncommon isolates increased significantly with increasing age from 18% in group 1 to 37% in group 4 (P = 0.001). We found a significant decrease in the proportion of the common pharyngeal emm types, specifically emm 12 and emm 4 type isolates, with increasing age (P = 0.001 and P = 0.003, respectively); there was no significant decline in the prevalence of other common pharyngeal types (emm 1, 2, 3, 6 and 28) with increasing age. CONCLUSION: Age-related changes in emm type distribution of pharyngeal GAS are present in childhood; these changes may reflect acquisition of immunity to more common types as a consequence of exposure early in life, but this remains to be demonstrated.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.286
Teacher spread0.270 · 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

Citations21
Published2005
Admission routes1
Has abstractyes

Explore more

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