Utilization of tetanus and diphtheria serology tests in Alberta, Canada: Patterns and implications
Bibliographic record
Abstract
BACKGROUND: Tetanus and diphtheria (Td) antibody titers can be measured to assess for seroprotection from immunization, though this is not routinely indicated. There are limited population level data on the utilization of these tests and their results. METHODS: This is a population level retrospective study based on laboratory data collected from patients who underwent Td antibody testing. Td IgG titer requests from May 1, 2023, to December 31, 2024, were extracted from the provincial health information system of Alberta, Canada. Td anti-toxin test requests, geometric mean titers, and vaccination status of patients who underwent testing were analyzed. Individuals with multiple tests were assessed for changes in antibody levels, and the proportion of tested individuals who were vaccinated within the past 10 years was calculated. Geometric mean titers were interpreted in relation to established thresholds for long-term protective immunity. RESULTS: A total of 2,550 patients underwent testing for tetanus (n = 2,349) and diphtheria (n = 2,093) anti-toxin antibody levels. Geometric mean titers varied widely across physician specialties, with pediatrics and Immunology showing higher proportions of recent vaccinations and higher geometric mean titers, while general practice and nephrology had lower values. Nearly 40% of diphtheria test orders in patients immunized within the past 10 years were requested by general practice (n = 336). In contrast, less than 20% of tests were ordered by nephrology (n = 153), pediatrics (n = 95), and pharmacy (n = 12). CONCLUSION: Over half the tests were requested by general practice. Our study highlighted variability in vaccination patterns and immune responses across specialties. While antibody testing is useful for assessing protection, a considerable number of tests were performed in individuals likely to be protected by recent vaccination, pointing to inefficiencies and unnecessary healthcare spending. These findings underscore the importance of aligning test ordering practices with immunization history to optimize resource use, avoid redundant testing, support diagnostic stewardship, and inform more cost-effective public health strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".