A162 PHYSICIAN DIAGNOSES AND SELF-DIAGNOSIS OF PATIENTS WITH CELIAC DISEASE IN THE INTERNET ERA
Bibliographic record
Abstract
Celiac disease (CD) is an immune condition defined by intestinal inflammation in response to gluten. Manifestations of CD are variable and diagnostic delays are common. With growing public awareness of CD, many individuals are turning to resources such as the Internet, family and friends for health information. In a population of newly diagnosed CD subjects, identify: 1. Alternate diagnoses prior to CD diagnosis 2. Resources used to self-diagnose CD 3. The role of the Internet in directing the diagnosis of CD Between July 2014 and February 2017, adults with positive TTG and/or EMA antibodies and Marsh III histology were prospectively enrolled in the Manitoba CD Cohort. The initial study visit (within 6 weeks of initiating a gluten-free diet) included an optional online survey with items related to symptoms, use of health information sources and diagnoses given prior to CD. Among 99 subjects who completed the survey, median symptom duration was 3 years (IQR 1–10) prediagnosis and 1 year (IQR 0.25–3) prior to seeking health care evaluation. The most common symptoms at diagnosis were gas (58%), urgency (45%) and difficulty concentrating (35%). Many subjects (35%) were given a diagnosis other than CD for their symptoms, most commonly IBS or a psychological diagnosis (Table 1). The Internet and family doctor were considered the most important sources used to identify a diagnosis. About 80% of subjects who were Internet users (n=93) used the Internet to research their symptoms. The most accessed Internet sites were the Canadian Celiac Association (n=55), Mayo clinic (n=52) and WebMD (n=39). One quarter (n=18) made a self-diagnosis based on their search, with 7 concluding that CD was the most likely diagnosis. As a result of their Internet search, 66% talked to a friend, 54% saw their family doctor, and 43% changed their diet. Doctors visits were used to ask for a TTG (31%), discuss what was found on the Internet (27%) and/or ask for a gastroenterology referral (24%). Many doctors and patients attribute symptoms of CD to alternate conditions, which may contribute to diagnostic delays. Many individuals diagnosed with CD used the Internet to research their symptoms thereby initiating the CD evaluation. More work is needed to raise awareness about CD screening. Diagnoses for CD symptoms None
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".