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Record W23320603

My journey through the lives of patients with coeliac disease.

2015· article· en· W23320603 on OpenAlexaboutno aff
Pankaj Vohra

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicCeliac Disease Research and Management
Canadian institutionsnot available
Fundersnot available
KeywordsCoeliac diseaseMedicineFailure to thriveDiseasePediatricsIrritable bowel syndromeInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

I never read about coeliac disease during my MBBS or MD days. It probably did not exist or even if it did, we never made a diagnosis often enough for it to be considered an important condition. However, it became clear in the 1990s that coeliac disease was not restricted to Europe—the so-called world capital of coeliac disease— but was prevalent in the USA, Canada and many other countries, at rates similar to those found in Europe. Then came the realization that children and adults living in the wheat-eating belt of northern India were suffering from the same condition and the prevalence rates here were almost the same. It was in 1999–2000 when I started my practice in paediatric gastroenterology in Delhi, having completed my Fellowship from Mount Sinai Medical Center, New York. There, too, the diagnosis of coeliac disease was relatively rare at that time—most children with anaemia and diarrhoea had inflammatory bowel disease. As a result of an increase in awareness, coeliac disease is being diagnosed more often, though it is sometimes confused with Crohn disease. Most of the patients I initially saw in Delhi had a history of recurrent non-bloody diarrhoea. These children had stunted growth, distended abdomens, were irritable and often had haemoglobin levels of 3–5 g/dl. Almost all these patients had received several courses of antibiotics and at least one course of antitubercular treatment, and had a label of ‘Failure to thrive’. Convincing the parents to let the child undergo an endoscopy and a biopsy was a challenging task (and still is, though definitely less). Getting good serological reports was also not easy. At that time, the serological test available for coeliac disease was anti-gliadin antibody. This test was known to yield high false-positive and false-negative results. Some laboratories had started doing the anti-endomysial antibody—a test that used the immunofluorescence technique and was inherently difficult to read. One reference laboratory set up by a Malaysian group was sending samples to Australia for assessment of tissue transglutaminase antibody—probably the best bet, but the most expensive. However, the diagnosis was relatively easy once considered, as the biopsy changes were those of severe disease. And if there was any doubt about the diagnosis, it vanished when the child was put on a gluten-free diet and his/ her condition improved virtually every week. The challenge at the time was to explain the disease to the parents and grandparents and convince them of the need to put the child on a gluten-free diet. There was limited knowledge of this condition and there were hardly any suppliers of gluten-free food. No commercial outlets were available. We recommended going back to the basics of Indian diets, which have a large variety of naturally available gluten-free food. The good thing was that those days, not many readymade products were available and people did not have much disposable income either—this meant that children mostly ate home-cooked food and rarely had pizzas and burgers. The children may have been too young to realize how sick they were, but their parents did, and they went from doctor to doctor till a diagnosis was made. A good number of these children with coeliac disease continue to stay on a gluten-free diet because they have been told how sick they were before the diagnosis. Several of these patients continue to follow-up with me and it is a pleasure to see many of them grow into young healthy adults. Among the very sick children I described above, there were some with other forms of coeliac disease. For example, there was a child with only anaemia, a child who had severe constipation and was thought to have Hirschprung disease, a child with chronic liver disease progressing to liver failure, a child with type 1 diabetes who refused to grow despite good control of his blood sugar level, and a child of short stature. Over the next 5 years or so, the number of children being diagnosed with coeliac disease increased exponentially. An increasing number of paediatric gastroenterologists gave talks on the subject and more doctors became aware of the disease. Daylong conferences were organized on coeliac disease and no conference on the diseases of children was complete without a session on this condition. Articles appeared in the lay press. As a result, there was a gradual change in the patient population that came to visit me. Children with fewer symptoms started to come for a diagnosis. Endoscopy was more widely available and became more acceptable. Serology became better, cheaper and more accurate, and was now locally available. Most importantly, a number of gluten-free food outlets sprang up, mostly from homes which had children diagnosed with the condition. Rarely did I see patients with haemoglobin levels of 3 g/dl. Also, I came across many children with coeliac disease without a gastrointestinal

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0150.010
Scholarly communication0.0130.016
Open science0.0020.017
Research integrity0.0060.030
Insufficient payload (model declined to judge)0.0100.003

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.

Opus teacher head0.044
GPT teacher head0.274
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2015
Admission routes1
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