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Development of an electronic medical record-based algorithm to identify patients with Stevens-Johnson syndrome and toxic epidermal necrolysis in Japan.

ABSTRACT: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN), severe drug reactions, are often misdiagnosed due to their rarity and lack of information on differential diagnosis. The objective of the study was to develop an electronic medical record (EMR)-based algorithm to identify patients with SJS/TEN for future application in database studies. From the EMRs of a university hospital, two dermatologists identified all 13 patients with SJS/TEN seen at the Department of Dermatology as the case group. Another 1472 patients who visited the Department of Dermatology were identified using the ICD-10 codes for diseases requiring differentiation from SJS/TEN. One hundred of these patients were then randomly sampled as controls. Based on clinical guidelines for SJS/TEN and the experience of the dermatologists, we tested 128 algorithms based on the use of ICD-10 codes, clinical courses for SJS/TEN, medical encounters for mucocutaneous lesions from SJS/TEN, and items to exclude paraneoplastic pemphigus. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic odds ratio (DOR) of each algorithm were calculated, and the optimal algorithm was defined as that with high PPV and maximal sensitivity and specificity. One algorithm, consisting of a combination of clinical course for SJS/TEN, medical encounters for mucocutaneous lesions from SJS/TEN, and items to exclude paraneoplastic pemphigus, but not ICD-10 codes, showed a sensitivity of 76.9%, specificity of 99.0%, PPV of 40.5%, NPV of 99.8%, and DOR of 330.00. We developed a potentially optimized algorithm for identifying SJS/TEN based on clinical practice records. The almost perfect specificity of this algorithm will prevent bias in estimating relative risks of SJS/TEN in database studies. Considering the small sample size, this algorithm should be further tested in different settings.

SUBMITTER: Fukasawa T

PROVIDER: S-EPMC6692049 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Development of an electronic medical record-based algorithm to identify patients with Stevens-Johnson syndrome and toxic epidermal necrolysis in Japan.

Fukasawa Toshiki T Takahashi Hayato H Kameyama Norin N Fukuda Risa R Furuhata Shihori S Tanemura Nanae N Amagai Masayuki M Urushihara Hisashi H

PloS one 20190813 8

Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN), severe drug reactions, are often misdiagnosed due to their rarity and lack of information on differential diagnosis. The objective of the study was to develop an electronic medical record (EMR)-based algorithm to identify patients with SJS/TEN for future application in database studies. From the EMRs of a university hospital, two dermatologists identified all 13 patients with SJS/TEN seen at the Department of Dermatology as the ...[more]

PMID: 31408480

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Project description:BackgroundStevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are two of the most severe dermatologic emergencies. Although pregnant women comprise a subset of individuals at risk for SJS and TEN development, little is known with regard to outcomes and treatment.ObjectiveThis study aimed to conduct a systematic review to characterize the risk factors, outcomes, and treatment of SJS and TEN in pregnant patients and newborns.MethodsA primary literature search was conducted using PubMed in September 2019, using the following search terms entered in separate pairs: pregnant or pregnancy and stevens-johnson or SJS or toxic epidermal necrolysis. Reviews, studies in a language other than English, and articles not including pregnant patients were excluded.ResultsTwenty-six articles were included for review, including a total of 177 patients. The average maternal age for a reaction was 29.9 years, gestational age was 24.9 weeks, and time to reaction after drug initiation was 27.5 days. Approximately 85% of pregnant women in this review were infected with HIV. The most common causative medications were antiretroviral therapy (90% of all cases), antibiotics (3%), and gestational drugs (2%). Of the 94 cases in which outcome data were available, the survival rates of pregnant women and newborns after delivery were 98% and 96%, respectively. Withdrawal of the offending agent and supportive care was often sufficient for treatment, but antibiotics, steroids, and intravenous immunoglobulin were implemented in some cases. Complications included preterm labor, vaginal stenosis, and vaginal adhesions.ConclusionGiven the predominance of studies focusing on the subset of pregnant patients who are infected with HIV, SJS and TEN is most commonly reported in young patients after antiretroviral therapy, primarily nevirapine. Overall mortality is lower than that of the general population, but similar to the expected mortality rates of younger adults. Early recognition and withdrawal of the offending agent is essential to mitigate the distinct consequences of these conditions in the pregnant population.

Dataset Information

Development of an electronic medical record-based algorithm to identify patients with Stevens-Johnson syndrome and toxic epidermal necrolysis in Japan.

Publications

Development of an electronic medical record-based algorithm to identify patients with Stevens-Johnson syndrome and toxic epidermal necrolysis in Japan.

Similar Datasets

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