Machine learning models to identify low adherence to influenza vaccination among Korean adults with cardiovascular disease.

BACKGROUND: Annual influenza vaccination is an important public health measure to prevent influenza infections and is strongly recommended for cardiovascular disease (CVD) patients, especially in the current coronavirus disease 2019 (COVID-19) pandemic. The aim of this study is to develop a machine learning model to identify Korean adult CVD patients with low adherence to influenza vaccination METHODS: Adults with CVD (n = 815) from a nationally representative dataset of the Fifth Korea National Health and Nutrition Examination Survey (KNHANES V) were analyzed. Among these adults, 500 (61.4%) had answered "yes" to whether they had received seasonal influenza vaccinations in the past 12 months. The classification process was performed using the logistic regression (LR), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB) machine learning techniques. Because the Ministry of Health and Welfare in Korea offers free influenza immunization for the elderly, separate models were developed for the < 65 and ≥ 65 age groups. RESULTS: The accuracy of machine learning models using 16 variables as predictors of low influenza vaccination adherence was compared; for the ≥ 65 age group, XGB (84.7%) and RF (84.7%) have the best accuracies, followed by LR (82.7%) and SVM (77.6%). For the < 65 age group, SVM has the best accuracy (68.4%), followed by RF (64.9%), LR (63.2%), and XGB (61.4%). CONCLUSIONS: The machine leaning models show comparable performance in classifying adult CVD patients with low adherence to influenza vaccination.

The clinical characteristics of Anisakis allergy in Korea.

Anisakidae larvae can cause anisakiasis when ingested by humans. Although several groups have reported a gastrointestinal Anisakis allergy among people in Spain and Japan, our report is the first to summarize the clinical features of 10 Anisakis allergy cases in Korea. We enrolled 10 Korean patients (6 men and 4 women) who complained of aggravated allergic symptoms after ingesting raw fish or seafood. Sensitization to Anisakis was confirmed by detecting serum specific IgE to Anisakis simplex. The most common manifestation of anisakiasis was urticaria (100%), followed by abdominal pain (30%) and anaphylaxis (30%). All patients presenting with these symptoms also exhibited high serum specific IgE (0.45 to 100 kU/L) to A. simplex. Nine patients (90%) exhibited atopy and increased total serum IgE levels. The fish species suspected of carrying the Anisakis parasite were flatfish (40%), congers (40%), squid (30%), whelk (10%), and tuna (10%). Anisakis simplex should be considered as a possible causative food allergen in adult patients presenting with urticaria, angioedema, and anaphylaxis following the consumption of raw fish or seafood.

The antichromatin antibodies can be useful as a diagnostic tool and disease activity marker of systemic lupus erythematosus in Koreans.

We have investigated the clinical utility of antichromatin antibodies for the diagnosis of SLE and as a marker of disease activity in Korean SLE patients. Blood samples were collected from SLE patients, lupus syndrome patients having only two or three of ACR classification criteria for SLE and normal controls. The level of antichromatin antibody was measured by enzyme linked immunosorbent assay and expressed as arbitrary unit. The antichromatin antibody levels of the SLE and lupus syndrome patients were higher than NC. The antichromatin antibody levels were significant higher in SLE patients with arthritis. A significant correlation was found between the level of antichromatin antibodies and each of anti-dsDNA antibody, leukopenia, complement and SLEDAI. The change of antichromatin antibody levels showed a positive correlation with the change of SLEDAI in serial samples. These data suggest that the antichromatin antibodies appear to be a useful laboratory test that can help in the diagnosis and assessment of SLE.