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Record W2309900818 · doi:10.1093/cid/ciw032

Streptococcal Infections and Varicella

2016· letter· en· W2309900818 on OpenAlexaff
R. W. Allard, Pierre A. Pilon

Bibliographic record

VenueClinical Infectious Diseases · 2016
Typeletter
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsMedicineChickenpoxVirologySTREPTOCOCCAL INFECTIONSImmunologyMicrobiologyVirus

Abstract

fetched live from OpenAlex

To the Editor—Frère et al [1] recently reported the effects of a universal varicella immunization program on admissions to a pediatric hospital for invasive group A streptococcal infections (IGASI). We wish to draw readers’ attention to 2 points concerning this study, hoping to help interpret its results. The first point is that the quantities the authors call “rates of IGASI per 1000 hospital admissions” are in fact proportions of admissions due to IGASI. As such, they are as dependent on changes in numbers of hospitalizations for any other cause as they are on hospitalizations for IGASI. Only true population-based hospitalization rates, with person-time denominators, would generally be independent of each other. The reservation expressed in the last sentence of the article is therefore not supported by the results reported: the varicella immunization program could have decreased the hospitalization rate for IGASI; we simply do not know, based on these proportions, if it did. The second, related point is that it is not meaningful that the difference between the proportions of admissions due to IGASI before and after the implementation of the varicella immunization program was not statistically significant, because the study had a very low power for detecting as statistically significant a difference in proportions of the size observed. After the denominators had been retrieved by a rule of three, one calculator [2] estimated that the study had a power of 6%, another [3] a power of 7%. A statistical power of about 80%, with a significance threshold of 0.05, is the usual target, giving a 20% risk of failing to detect as statistically significant a true difference in effect of the size judged important (type II error). Here the risk of a type II error is about 93%. These reservations bear only on the epidemiologic findings of the study and not on the clinical finding that the number of pediatric patients admitted each year to the study hospital for varicella-associated IGASI decreased from a yearly mean of 3.4 (24 in 7 years) before the implementation of the varicella immunization program to 0.9 (7 in 8 years) afterward. Testing the significance of the apparently large difference between these 2 means is a very straightforward matter, given the corresponding sample sizes and variances. The authors’ data on varicella-related IGASI suggest that the decrease is significant. Confirming this with absolute numbers instead of proportions would support the hypothesis of a population effect of the program in the absence of an alternate explanation, such as a decrease in the pediatric population served or a change in consultation patterns. Potential conflict of interest. Both authors: No reported conflicts. Both authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

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)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.036
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0360.025
Insufficient payload (model declined to judge)0.0110.005

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 head0.038
GPT teacher head0.369
Teacher spread0.330 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2016
Admission routes1
Has abstractno

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