Evidence map›Paper›PMID 41675771›Full record

ArticleAnnals of medicine and surgery (2012)2026

From photosensitivity to autoimmunity: the role of AI metabolomics in PCT-celiac disease overlap.

S Tongpangkokla Ozukum, Kainat Wajahat, Muhammad Abdullah, Maliha Khalid, Aminath Waafira

Abstract readLetter
In one paragraph

Article in Annals of medicine and surgery (2012), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

S Tongpangkokla OzukumDepartment of Medicine, IMDH District Hospital College of Nursing, Nagaland.
Kainat WajahatDepartment of Medicine, Liaquat University of Medical and Health Sciences (LUMHS), Karachi, Pakistan.
Muhammad AbdullahShaheed Zulfiqar Ali Bhutto Medical University, Karachi, Pakistan.
Maliha KhalidDepartment of Medicine, Jinnah Sindh Medical University, Karachi, Pakistan.ORCID https://orcid.org/0009-0001-3413-2752
Aminath WaafiraSchool of Medicine, The Maldives National University, Malé, Maldives.ORCID https://orcid.org/0009-0000-3283-1982

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Porphyria cutanea tarda (PCT), caused by hepatic uroporphyrinogen decarboxylase deficiency, may rarely overlap with undiagnosed celiac disease (CD), complicating diagnosis due to shared hepatic and dermatologic features. Both conditions present with skin manifestations such as photosensitivity, blistering, or dermatitis herpetiformis-like lesions, often leading to misclassification. AI-driven metabolomics provides a novel strategy to identify metabolic biomarkers, predict CD with high accuracy through machine learning, and uncover hidden comorbidities in PCT patients. Despite challenges including limited datasets, bioinformatics demands, and regulatory barriers, integrating metabolomics with AI could enhance diagnostic precision and enable personalized management. Multidisciplinary collaboration is critical to translating these technologies into clinical practice for early detection and improved outcomes in PCT-CD overlap.

Indexed as

artificial intelligenceceliac diseasemetabolomicsporphyria cutanea tarda

Identifiers

PMID41675771
PMCPMC12889377

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.