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Record W4317895500 · doi:10.1370/afm.21.s1.3998

Patterns of High vs. Standard Dose Flu Vaccinations in Canadian Primary Care: A Baseline Cohort Pilot Study

2023· article· en· W4317895500 on OpenAlexaboutno aff
Rebecca Theal, Rachael Morkem, David G. Barber, John T. Queenan, Lorne Kinsella

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVaccinationCohortComorbidityContext (archaeology)Logistic regressionPopulationCohort studyDemographyPediatricsInternal medicineEnvironmental healthImmunology

Abstract

fetched live from OpenAlex

Context: The high dose flu vaccination is newly available to Canadians and recommended for adults aged 65 years and older. Describing patterns of flu vaccination in Canadian primary care using electronic medical records (EMR) is challenging. However, we have established that by using a combination of the ATC code and the lot number of the product administered, we can differentiate between high and standard dose flu vaccination using routinely collected structured EMR data. Objectives: 1) Construct a baseline cohort of patients who received a flu vaccine during the 2018-2019 and 2019-2020 flu seasons. 2) Describe age, SES and comorbidity related patterns of standard vs. high dose flu vaccination. Design: Baseline cohort pilot study Dataset: Data from the Eastern Ontario Network (EON), a repository of EMR data drawn from primary care practices in south-eastern Ontario. Population Studied: Patients aged 65 and older who received a flu vaccination in a primary care setting during the 2018-2019 and/or 2019-2020 flu seasons (June 1 2018-May 31 2020). Outcome Measures: Flu vaccinations were determined by ATC code (J07BB). All patients who were vaccinated with a high dose lot number product were classified as “high dose”, all others were classified as “standard dose”. Logistic regression was used to describe odds of high vs standard dose flu vaccinations related to age, sex, location, socioeconomic status, and comorbidity. Results: Baseline cohorts of patients aged 65 and older who received flu vaccinations during the 2018-2019 (n=19,037) and 2019-2020 (n=18,908) flu seasons were constructed. Over one-third of patients 65 and older received a high dose flu vaccination in the 2018-2019 (36.6%) and 2019-2020 (35.4%) flu seasons. Both cohorts (2019-2019 vs 2019-2020) were also similar in age (75.8±7.6 vs. 75.9±7.6 years old), sex (54.6% vs. 54.2% female), and location (65.2% vs 64.2% live in an urban setting). Age was the strongest predictor of having received a high dose flu vaccine for both cohorts. Patients aged 85 years and older were 1.44x (95% CI 1.29-162; 2018-2019) and 1.86x (95% CI 1.65-2.08; 2019-2020) more likely to have received a high dose flu vaccine compared to patients aged 65 to 69. Conclusion: Overall, Canadian primary care EMR data was effectively used to compare patterns of high and standard dose flu vaccinations in patients aged 65+. Future work will describe patterns of subsequent respiratory infections stratified by flu vaccine dose.

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)0.006
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 score0.035
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.005
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.030
GPT teacher head0.334
Teacher spread0.304 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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