MétaCan
Menu
Back to cohort
Record W2143890951 · doi:10.1093/rheumatology/kes175

Vaccination coverage in children with juvenile idiopathic arthritis followed at a paediatric tertiary care centre

2012· article· en· W2143890951 on OpenAlexaffabout
Michel Morin, Caroline Quach, Élise Fortin, Gaëlle Chédeville

Bibliographic record

VenueLara D. Veeken · 2012
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsMontreal Children's Hospital
Fundersnot available
KeywordsMedicineTertiary careJuvenileArthritisVaccinationPediatricsFamily medicineImmunology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the vaccination coverage rate of patients with JIA followed at a paediatric tertiary care centre and to determine the coverage rate for individual vaccines required as per the Quebec Immunization Protocol. METHODS: Consecutive JIA patients coming for their scheduled visit were included if they were between 2 and 18 years of age and if they had an available written immunization record. Descriptive statistics were used to evaluate the proportion of children with complete vaccination status according to the Quebec Immunization Protocol at 2.5, 10.5 years and at their last clinic visit. RESULTS: A total of 200 patients were included. Complete vaccination according to schedule was identified in only 52% of patients at 2.5 years, 68% at 10.5 years and 61% at their last clinic visit. The vaccination coverage rate for individual vaccines was good overall with the exception of low measles, mumps and rubella vaccine coverage at 2.5 years (58%). CONCLUSION: Despite overall good vaccination coverage rate for individual vaccines, only 61% of our cohort had a complete vaccination status at their last clinic visit. Measures to optimize vaccination coverage, such as catch-up vaccination, should be implemented when possible.

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)0.000
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.223
Teacher spread0.218 · 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".

Quick stats

Citations46
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueLara D. VeekenSame topicRheumatoid Arthritis Research and TherapiesFrench-language works237,207