Efficacy comparison of 7- and 14-day P-CAB based bismuth-containing quadruple regimen with PPI based bismuth-containing quadruple regimen for Helicobacter pylori infection: rationale and design of an open-label, multicenter, randomized controlled trial.

BACKGROUND: Owing to its strong acid inhibition, potassium-competitive acid blocker (P-CAB) based regimens for Helicobacter pylori (H. pylori) eradication are expected to offer clinical advantages over proton pump inhibitor (PPI) based regimens. This study aims to compare the efficacy and adverse effects of a 7-day and a 14-day P-CAB-based bismuth-containing quadruple regimen (PC-BMT) with those of a 14-day PPI-based bismuth-containing quadruple regimen (P-BMT) in patients with high clarithromycin resistance. METHODS: This randomized multicenter controlled clinical trial will be performed at five teaching hospitals in Korea. Patients with H. pylori infection who are naive to treatment will be randomized into one of three regimens: 7-day or 14-day PC-BMT (tegoprazan 50 mg BID, bismuth subcitrate 300 mg QID, metronidazole 500 mg TID, and tetracycline 500 mg QID) or 14-day P-BMT. The eradication rate, treatment-related adverse events, and drug compliance will be evaluated and compared among the three groups. Antibiotic resistance testing by culture will be conducted during the trial, and these data will be used to interpret the results. A total of 366 patients will be randomized to receive 7-day PC-BMT (n = 122), 14-day PC-BMT (n = 122), or 14-day P-BMT (n = 122). The H. pylori eradication rates in the PC-BMT and P-BMT groups will be compared using intention-to-treat and per-protocol analyses. DISCUSSION: This study will demonstrate that the 7-day or 14-day PC-BMT is well tolerated and achieve similar eradication rates to those of 14-day P-BMT. Additionally, the 7-day PC-BMT will show fewer treatment-related adverse effects and higher drug compliance, owing to its reduced treatment duration. TRIAL REGISTRATION: Korean Clinical Research Information Service registry, KCT0007444. Registered on 28 June 2022, https://cris.nih.go.kr/cris/index/index.do .

Allergy Wheal and Erythema Segmentation Using Attention U-Net.

The skin prick test (SPT) is a key tool for identifying sensitized allergens associated with immunoglobulin E-mediated allergic diseases such as asthma, allergic rhinitis, atopic dermatitis, urticaria, angioedema, and anaphylaxis. However, the SPT is labor-intensive and time-consuming due to the necessity of measuring the sizes of the erythema and wheals induced by allergens on the skin. In this study, we used an image preprocessing method and a deep learning model to segment wheals and erythema in SPT images captured by a smartphone camera. Subsequently, we assessed the deep learning model's performance by comparing the results with ground-truth data. Using contrast-limited adaptive histogram equalization (CLAHE), an image preprocessing technique designed to enhance image contrast, we augmented the chromatic contrast in 46 SPT images from 33 participants. We established a deep learning model for wheal and erythema segmentation using 144 and 150 training datasets, respectively. The wheal segmentation model achieved an accuracy of 0.9985, a sensitivity of 0.5621, a specificity of 0.9995, and a Dice similarity coefficient of 0.7079, whereas the erythema segmentation model achieved an accuracy of 0.9660, a sensitivity of 0.5787, a specificity of 0.97977, and a Dice similarity coefficient of 0.6636. The use of image preprocessing and deep learning technology in SPT is expected to have a significant positive impact on medical practice by ensuring the accurate segmentation of wheals and erythema, producing consistent evaluation results, and simplifying diagnostic processes.