Pollen allergen skin test and specific IgE reactivity among Filipinos: a community-based study
Bibliographic record
Abstract
Abstract Background Despite the clinical importance of pollen allergens among Filipinos, few studies delve into the sensitization profiles of Filipinos against pollen allergens. This study determined the sensitization profile of Filipinos to pollen using skin prick test (SPT) and pollen-specific ELISA. Methods Pollen from fifteen selected plant sources was collected and extracted for use in sensitization tests. Volunteers were interviewed for their clinical history prior to blood sampling and SPT. The blood samples collected were assessed using Enzyme-Linked Immunosorbent Assay (ELISA). Results The best panel of pollen allergens for the skin prick test was Mangifera indica (64%), Acacia auriculiformis (28%), Mimosa spp. (25%) Amaranthus spinosus (22%), Lantana camara (20%), Pilea microphylla (16%) and Dichanthium aristatum (15%). Young adults had more sensitizations to pollen than among early childhood and elderly. There were more allergic subjects that have rhinitis (61%) than asthma (42%) and atopic dermatitis (35%). Pollen-specific IgE levels show low percent reactivity as compared to the skin test with Cocos nucifera obtaining the highest IgE reactivity (21%). Conclusions Pollen allergens from both arboreal and herbaceous plants used in this study yielded positive reactivities for both skin tests and specific IgE tests.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".