As the rate of discovery of drug-resistant Helicobacter pylori cases increases worldwide, the relevant societies have updated their guidelines for primary eradication regimens. A promising strategy against drug-resistant H. pylori is tailored therapy based on the results of an antibiotic susceptibility test; however, it is difficult to apply this strategy to all cases. Although culture-based antibiotic susceptibility tests can assess resistance to any antimicrobial agent, their greatest disadvantage is the time required to draw a conclusion. In contrast, molecular-based methods, such as polymerase chain reaction, can rapidly determine the presence of resistance, although a single test can only test for one type of antimicrobial agent. Additionally, the limited availability of facilities for molecular-based methods has hindered their widespread use. Therefore, low-cost, minimally invasive, simple, and effective primary regimens are needed. Several studies have compared the efficacy of the latest primary eradication regimens against that of tailored therapies, and their results have shaped guidelines. This article reviews the latest research on empirical and tailored treatments for H. pylori infections. Evidence for the superiority of tailored therapy over empirical therapy is still limited and varies by region and treatment regimen. A network meta-analysis comparing different empirical treatment regimens showed that vonoprazan triple therapy provides a superior eradication effect. Recently, favorable results towards vonoprazan dual therapy have been reported, as it reached eradication levels similar to those of vonoprazan triple therapy. Both vonoprazan dual therapy and tailored therapy based on antibiotic susceptibility tests could contribute to future treatment strategies.

BACKGROUND AND PURPOSE: Valproate is used as a prophylactic drug for migraine, but it is not be effective in all patients. We used medical records to investigate which clinical factors affected the response to valproate in patients with migraine as an original headache, and established a scoring system for predicting the clinical response to prophylactic therapy. METHODS: We investigated clinical factors from the medical records of 95 consistent responders (CRs) and 24 inconsistent responders (IRs) to valproate. RESULTS: Multivariate stepwise logistic regression analysis revealed that a history of hyperlipidemia and hay fever and the complication of depression or other psychiatric disorder were significant factors that independently contributed to a negative response, with odds ratios of 6.024 [no vs. yes; 95% confidence interval (CI)=1.616–22.222], 2.825 (no vs. yes; 95% CI=1.046–7.634), and 2.825 (no vs. yes; 95% CI=1.052–7.576), respectively. A predictive index (PI) of the clinical response to valproate in patients with migraine was calculated using the regression coefficients of these three factors as an integer, and the index was significantly higher for IRs than for CRs (1.46±1.10 vs. 0.69±0.74, mean±SD, p<0.001). CONCLUSIONS: The obtained PI may represent an appropriate scoring system for predicting the responses in these patients.
Depression ; Headache ; Humans ; Hyperlipidemias ; Logistic Models ; Medical Records ; Migraine Disorders* ; Odds Ratio ; Rhinitis, Allergic, Seasonal ; Risk Factors ; Valproic Acid*

Colonoscopy plays an important role in reducing the incidence and mortality of colorectal cancer by detecting adenomas and other precancerous lesions. Image-enhanced endoscopy (IEE) increases lesion visibility by enhancing the microstructure, blood vessels, and mucosal surface color, resulting in the detection of colorectal lesions. In recent years, various IEE techniques have been used in clinical practice, each with its unique characteristics. Numerous studies have reported the effectiveness of IEE in the detection of colorectal lesions. IEEs can be divided into two broad categories according to the nature of the image: images constructed using narrowband wavelength light, such as narrowband imaging and blue laser imaging/blue light imaging, or color images based on white light, such as linked color imaging, texture and color enhancement imaging, and i-scan. Conversely, artificial intelligence (AI) systems, such as computer-aided diagnosis systems, have recently been developed to assist endoscopists in detecting colorectal lesions during colonoscopy. To better understand the features of each IEE, this review presents the effectiveness of each type of IEE and their combination with AI for colorectal lesion detection by referencing the latest research data.