Leistungsknick, Thoraxschmerz und Polyserositis bei einem 35-jährigen Patienten mit antikonvulsiver Therapie

Wittchen, Frank; Spencker, Sebastian; Zinke, Sandra; Çoban, Neslihan; Schultheiss, H.‐P.; Witzenbichler, Bernhard

doi:10.1007/s00108-005-1504-8

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…This was only surpassed by the case described by Wittchen et al . in which the clinical signs appeared 20 years after starting CBZ treatment (29). Differentiating them at clinical level is made easier in that some of the most relevant facts in idiopathic SLE, such as renal, neurological, and severe hematological involvement, are rare in DILE (2).…”

Section: Discussionmentioning

confidence: 99%

Carbamazepine-induced systemic lupus erythematosus: A case-based review

Álvarez-Lario¹,

Bártulos-Iglesias²,

Colazo-Burlato³

et al. 2019

Eur J Rheumatol

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A case of carbamazepine-induced systemic lupus erythematosus (CBZ-DILE) is presented, along with a literature review, with the aim to define the clinical and serological characteristics of this group, and compare them with systemic lupus erythematosus (SLE) triggered by other drugs (DILE). A 31-year-old woman presented with a 6-month history of hand arthritis and nasal ulcers. She had been diagnosed with epilepsy at 12 years of age and had continued treatment with carbamazepine (CBZ) for the past 18 years with excellent clinical control. Laboratory data revealed antinuclear antibodies (ANA) positive to a titer of 1/1280, and positive anti-nucleosome antibodies. The patients’ clinical symptoms disappeared after the CBZ discontinuation and did not reappear during the 1-year follow-up period. A search was made in the PubMed/Medline database of the (CBZ-DILE) published cases. A total of 26 cases of CBZ-DILE were found in the search. CBZ-DILE cases are characterized by variable latency periods that often last for years and are not related to the dose of CBZ. Most frequent clinical findings of CBZ-DILE in patients are arthralgia/arthritis, mucocutaneous manifestations, constitutional symptoms, and pleuritis or pericarditis. The renal involvement has not been reported in CBZ-DILE. Antihistone antibodies were observed less frequently, and anti-dsDNA antibodies were observed more frequently than in the “classic” DILE. The ANA remained positive in over 60% of cases during the follow-up after withdrawal. The CBZ-DILE has significant clinical and laboratory manifestations that distinguish it from classic DILE or idiopathic SLE.

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Section: Discussionmentioning

confidence: 99%

Carbamazepine-induced systemic lupus erythematosus: A case-based review

Álvarez-Lario¹,

Bártulos-Iglesias²,

Colazo-Burlato³

et al. 2019

Eur J Rheumatol

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Predicting drug–disease associations through layer attention graph convolutional network

Huang

Zhao

et al. 2020

Briefings in Bioinformatics

232

102

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Background: Determining drug–disease associations is an integral part in the process of drug development. However, the identification of drug–disease associations through wet experiments is costly and inefficient. Hence, the development of efficient and high-accuracy computational methods for predicting drug–disease associations is of great significance. Results: In this paper, we propose a novel computational method named as layer attention graph convolutional network (LAGCN) for the drug–disease association prediction. Specifically, LAGCN first integrates the known drug–disease associations, drug–drug similarities and disease–disease similarities into a heterogeneous network, and applies the graph convolution operation to the network to learn the embeddings of drugs and diseases. Second, LAGCN combines the embeddings from multiple graph convolution layers using an attention mechanism. Third, the unobserved drug–disease associations are scored based on the integrated embeddings. Evaluated by 5-fold cross-validations, LAGCN achieves an area under the precision–recall curve of 0.3168 and an area under the receiver–operating characteristic curve of 0.8750, which are better than the results of existing state-of-the-art prediction methods and baseline methods. The case study shows that LAGCN can discover novel associations that are not curated in our dataset. Conclusion: LAGCN is a useful tool for predicting drug–disease associations. This study reveals that embeddings from different convolution layers can reflect the proximities of different orders, and combining the embeddings by the attention mechanism can improve the prediction performances.

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Leistungsknick, Thoraxschmerz und Polyserositis bei einem 35-jährigen Patienten mit antikonvulsiver Therapie

Cited by 2 publications

References 11 publications

Carbamazepine-induced systemic lupus erythematosus: A case-based review

Carbamazepine-induced systemic lupus erythematosus: A case-based review

Predicting drug–disease associations through layer attention graph convolutional network

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