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Kawasaki disease (KD) is a form of systemic vasculitis that primarily affects children under the age of 5 years old. Antibiotics are often prescribed for KD patients even before a diagnosis is made due to their prolonged fever and elevated inflammatory markers. Therefore, the purpose of this study was to investigate the impact of antibiotics usage on the disease outcome of KD. We carried out a retrospective chart review of children between 2005 and 2017 for initial immunoglobulin (IVIG) treatment of KD. KD children with initial IVIG treatment more than 10 days after the onset of symptoms were excluded. In total, 280 children were eligible for this study, among which 209 had been treated with antibiotic(s) and 71 had not been. The IVIG resistance rates were 5.6% (4/71), 8.9% (10/112), and 21.6% (21/97) in non-users, single-drug users, and multiple-drug users, respectively (r = 0.205, p = 0.003). The IVIG resistance rate of the multiple antibiotics drug users in KD patients was significantly higher than the other two groups. Furthermore, the likelihood of IVIG resistance was found to increase with elevated C-reactive protein (CRP) values (1.010/unit, p < 0.001) but not with total white blood cell (WBC) count (p = 0.466). The probability of IVIG resistance increases with elevated CRP values and the use of multiple IV antibiotics, thus indicating that physicians should be prudent in administering multiple IV antibiotics when treating assumed infections in KD children. [ABSTRACT FROM AUTHOR]

Background: Mobile health apps have emerged as useful tools for patients and clinicians alike, sharing health information or assisting in clinical decision-making. Prostate cancer (PCa) risk calculator mobile apps have been introduced to assess risks of PCa and high-grade PCa (Gleason score ≥7). The Rotterdam Prostate Cancer Risk Calculator and Coral-Prostate Cancer Nomogram Calculator apps were developed from the 2 most-studied PCa risk calculators, the European Randomized Study of Screening for Prostate Cancer (ERSPC) and the North American Prostate Cancer Prevention Trial (PCPT) risk calculators, respectively. A systematic review has indicated that the Rotterdam and Coral apps perform best during the prebiopsy stage. However, the epidemiology of PCa varies among different populations, and therefore, the applicability of these apps in a Taiwanese population needs to be evaluated. This study is the first to validate the PCa risk calculator apps with both biopsy and prostatectomy cohorts in Taiwan.Objective: The study's objective is to validate the PCa risk calculator apps using a Taiwanese cohort of patients. Additionally, we aim to utilize postprostatectomy pathology outcomes to assess the accuracy of both apps with regard to high-grade PCa.Methods: All male patients who had undergone transrectal ultrasound prostate biopsies in a single Taiwanese tertiary medical center from 2012 to 2018 were identified retrospectively. The probabilities of PCa and high-grade PCa were calculated utilizing the Rotterdam and Coral apps, and compared with biopsy and prostatectomy results. Calibration was graphically evaluated with the Hosmer-Lemeshow goodness-of-fit test. Discrimination was analyzed utilizing the area under the receiver operating characteristic curve (AUC). Decision curve analysis was performed for clinical utility.Results: Of 1134 patients, 246 (21.7%) were diagnosed with PCa; of these 246 patients, 155 (63%) had high-grade PCa, according to the biopsy results. After confirmation with prostatectomy pathological outcomes, 47.2% (25/53) of patients were upgraded to high-grade PCa, and 1.2% (1/84) of patients were downgraded to low-grade PCa. Only the Rotterdam app demonstrated good calibration for detecting high-grade PCa in the biopsy cohort. The discriminative ability for both PCa (AUC: 0.779 vs 0.687; DeLong's method: P<.001) and high-grade PCa (AUC: 0.862 vs 0.758; P<.001) was significantly better for the Rotterdam app. In the prostatectomy cohort, there was no significant difference between both apps (AUC: 0.857 vs 0.777; P=.128).Conclusions: The Rotterdam and Coral apps can be applied to the Taiwanese cohort with accuracy. The Rotterdam app outperformed the Coral app in the prediction of PCa and high-grade PCa. Despite the small size of the prostatectomy cohort, both apps, to some extent, demonstrated the predictive capacity for true high-grade PCa, confirmed by the whole prostate specimen. Following our external validation, the Rotterdam app might be a good alternative to help detect PCa and high-grade PCa for Taiwanese men. [ABSTRACT FROM AUTHOR]