Aetiology of anaphylaxis in patients referred to an immunology clinic in Colombo, Sri Lanka
Bibliographic record
Abstract
BACKGROUND: The aetiology of anaphylaxis differs according to types of foods consumed, fauna and foliage and cultural practices. Although the aetiology of anaphylaxis in Western countries are well known, the causes in South Asian countries have not been reported. We sought to determine the causes of anaphylaxis in patients referred to an immunology clinic in Colombo, Sri Lanka. METHODS: 238 episodes of anaphylaxis were reviewed in 188 patients who were referred and skin prick tests and in vitro tests (ImmunoCap) were carried out to assess the presence of allergen specific IgE. Clinical features and severity of anaphylaxis was also recorded along with treatment received. RESULTS: Anaphylaxis to food either following direct exposure 90/238 (37.5%) or after exercise in the form of food dependent exercise induced anaphylaxis 29/238 (12.2%) was the predominant cause of anaphylaxis. Allergy to cow's milk and red meat, after immediate exposure, accounted for 66/238 (27.7%) of instances of all episodes of anaphylaxis and 66/90 (73.33%) of anaphylaxis due to food. Vaccines accounted for 28/238 (11.8%) of instances of anaphylaxis, especially among children. Of those who developed anaphylaxis to the MMR (n = 14), 71.4% of them had specific IgE to cow's milk and 35.7% of them had specific IgE to beef. Of those who developed anaphylaxis to insect stings, 27/42 of these episodes occurred following stings of ants (family Formicidae). The predominant cause of anaphylaxis changed with the age, with food allergy being the most frequent trigger of anaphylaxis in childhood, while drug allergy and idiopathic anaphylaxis being more frequent after 30 years of age. CONCLUSIONS: In this cohort, anaphylaxis to red meat appears to be the predominant cause of food induced anaphylaxis and presence of beef specific IgE and cow's milk, appears to be a predisposing factor for vaccine induced anaphylaxis.
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 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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".