Prevalence of Hypogammaglobulinemia in the Indigenous Population with Bronchiectasis in Manitoba
Bibliographic record
Abstract
Bronchiectasis is a obstructive lung disease characterized by irreversible dilation of airways, inflammation, chronic lower airway infection, and destruction of bronchial walls. An often overlooked condition that contributes to bronchiectasis development is hypogammaglobulinemia. Thus, quantification of immunoglobulin should be measured when evaluating bronchiectasis patients. Bronchiectasis is highly prevalent in Manitoba’s Indigenous population; this is likely due to high rates of tuberculosis. Despite this, Indigenous patients are underrepresented at the Clinical Immunology Clinic at the Health Sciences Center. The goal of this study was to evaluate if immunoglobulin levels are being tested in Indigenous patients with bronchiectasis and identify gaps in care provided to Indigenous patients with bronchiectasis in Manitoba. This was a retrospective chart review; comparison was between two groups of age and sex-matched patients with bronchiectasis in Manitoba, one of non-Indigenous patients and one Indigenous as determined from Accuro EMR used at HSC outpatient clinics. Quantitative immunoglobulins were reviewed and the frequency of hypogammaglobulinemia in the two groups were compared. Of the 145 patients identified in the chart review, approximately 55% had immunoglobulin results available. Although the true prevalence of hypogammaglobulinemia in Indigenous Manitobans with bronchiectasis could not be determined, statistical analysis revealed social and medical factors that affected the likelihood of a participant having immunoglobulin levels tested. Area of residence and tuberculosis status were found to be significant predictors of antibody testing. The findings of this study can be used to further our understanding of hypogammaglobulinemia prevalence in bronchiectasis patients as well as improve treatment of the disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".