Diagnosing atopic dermatitis in infancy: Questionnaire reports vs criteria‐based assessment
Bibliographic record
Abstract
BACKGROUND: Persisting atopic dermatitis (AD) is known to be associated with more serious allergic diseases at later ages; however, making an accurate diagnosis during infancy is challenging. We assessed the diagnostic performance of questionnaire-based AD measures with criteria-based in-person clinical assessments at age 1 year and evaluated the ability of these diagnostic methods to predict asthma, allergic rhinitis and food allergies at age 5 years. METHODS: Data relate to 3014 children participating in the Canadian Healthy Infant Longitudinal Development (CHILD) Study who were directly observed in a clinical assessment by an experienced healthcare professional using the UK Working Party criteria. The majority (2221; 73.7%) of these children also provided multiple other methods of AD ascertainment: a parent reporting a characteristic rash on a questionnaire, a parent reporting the diagnosis provided by an external physician and a combination of these two reports. RESULTS: Relative to the direct clinical assessment, the area under the Receiver Operating Characteristic curve for a parental report of a characteristic rash, reported physician diagnosis and a combination of both were, respectively, 0.60, 0.69 and 0.70. The strongest predictor of asthma at 5 years was AD determined by criteria-based in-person clinical assessment followed by the combination of parental and physician report. CONCLUSIONS: These findings suggest that questionnaire data cannot accurately substitute for assessment by experienced healthcare professionals using validated criteria for diagnosis of atopic dermatitis. Combining the parental report with diagnosis by a family physician might sometimes be appropriate (eg to avoid costs of a clinical assessment).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".