In 1983, Helicobacter pylori (Hp) was discovered and has revolutionized the concept of upper gastrointestinal diseases, including gastric cancer (GC). Hp screening is considered important in preventive medicine, such as the comprehensive health check-up system. It should be used effectively after understanding the advantages and disadvantages of each Hp testing method. Additionally, eradication therapy should be performed jointly with insurance treatment to reduce the risk of GC. Moreover, endoscopy-based surveillance is desirable based on the understanding of the characteristics of diseases and GCs caused by Hp infection status. For future reference, I have summarized our findings by reviewing the 40-year history of Hp study, treatment, and screening. Over the past 40 years in Japan, the Hp infection rate has declined rapidly, and eradication therapy has become widespread. The proportion of Hp cases in the comprehensive health check-up system has become extremely low, and the disease spectrum has changed; thus, it is important to respond to this change.

  The attitude of verifying facts without being compelled by preconceptions is required in preventive medicine.

Objective: Temporal subtraction for chest radiographs facilitates the detection of lesions by subtracting past images and is expected to avoid false negatives for lung cancer. However, there is a potential concern regarding increases in false positives due to artifacts, which have not been studied extensively. Therefore, this study investigated whether temporal subtraction for chest radiography images increased the rate of false positives.

Method: To match the backgrounds before and after the introduction of temporal subtraction, we only included screening chest radiography participants who had had their images interpreted by the same radiologist and who had matching propensity scores when adjusted for age, sex, smoking history, frontal-only or frontal-lateral imaging method, and whether the participant had previously undergone chest radiography at our institution. We used a non-inferiority test to investigate whether the patients’ positive results increased after the introduction of temporal subtraction. Moreover, the lung cancer detection rate was also evaluated although the sample size was small.

Results: A total of 5,860 participants were enrolled in each group (before and after temporal subtraction introduction), and the backgrounds of both groups were matched. The positive results before and after temporal subtraction introduction were 1.3% (74/5,860) and 1.1% (63/5,860), respectively. The 95% confidence interval for the difference in proportions was −0.6% to 0.2%, and the upper limit was below the non-inferiority margin. Lung cancer detection rates were 0.017% (1/5,860) and 0.034% (2/5,860), respectively.

Conclusion: Temporal subtraction for chest radiography did not increase the rate of false positives. Therefore, it is useful for lung cancer screening.

Objective: A bifascicular block (BFB) is a preclinical stage of a complete atrioventricular block and is frequently accompanied by structural and/or ischemic heart disease; therefore, a BFB is usually associated with a high mortality risk. However, patients with chronic BFB frequently present without any history of cardiac events during medical checkups. We investigated the prevalence and characteristics of BFBs.

Methods: We investigated 41,303 individuals who underwent electrocardiography at the JA Kanagawa Medical Checkup Center during 2021. We defined BFB as a complete right bundle branch block accompanied by a left anterior or posterior hemiblock.

Results: We identified 110 patients with BFB, of whom 82.0% were men. The overall prevalence was 0.27%, with prevalence of 0.40% in men and 0.11% in women. Patients’ median age was 65 years, and disease duration was three or more years. Only three cardiac events were observed during this period. Twelve patients (11.0%) had underlying heart disease; five had structural heart disease (5.0%), two had ischemic heart disease (2.0%), two had progressive cardiac conduction defects (2.0%), and three had arrhythmias (3.0%).

Conclusions: The prevalence of BFBs was 0.27% in the general population. However, most patients denied a history of cardiac events, and only 11.0% of patients had underlying heart disease. These findings are inconsistent with those reported by previous studies that included data obtained from hospitalized patients.

Objective: It has been recognized that there is a relationship between insulin resistance and lifestyle-related diseases. Therefore, this study aimed to examine the correlation between fasting immunoreactive insulin (F-IRI) and various examination levels in a medical checkup.

Methods: A total of 2,716 examinees in 8,504 cases with documented F-IRI levels were examined. Among these, medical checkup for 25,530 cases was carried out from 2016 to 2019.

Results: Body mass index, body fat percentage, waist circumference, diastolic blood pressure, fasting plasma glucose, homeostatic model assessment for insulin resistance, non-high-density lipoprotein cholesterol (n-HDL-C), HDL-C, triglyceride, aspartate aminotransferase, and alanine aminotransferase levels showed a significant correlation with F-IRI levels. We divided the examinees into four groups using the cluster analysis of the k-means method. The F-IRI levels progressed accordingly from the first group to the third group. The waist circumference of the third group was 94.8 ± 6.3 cm in men and 92.3 ± 8.3 cm in women. JMP pro ver. 14 for Windows was used for statistical analysis.

Conclusions: Our study demonstrates a significant correlation between F-IRI levels and various examination levels in a medical checkup. The cluster analysis results show that the third group is the target group, where specific health guidance should be performed.

Objective: In recent years, many studies have been conducted on the diagnosis of diseases from hair component analysis. However, most reports are based on raw data of disease patients and healthy donors, and have determined significant differences using Student’s t-test. There are few reports using machine learning for data analysis. Therefore, the objective of this study was to examine the possibility of diagnosis by candidates of disease markers from hair using machine learning.

Methods: Hair samples were obtained from patients with any of six diseases, namely diabetes, hypertension, androgenetic alopecia, depression, Alzheimer’s dementia, and cerebral infarction, and from healthy donors who have not been diagnosed with these diseases. The hair components, including minerals, free amino acids, and steroid hormones, were analyzed. Using random forest, a machine learning algorithm, we constructed a model to discriminate between healthy donors and each disease. In the constructed model, candidate disease marker components were extracted based on this analysis.

Results: By using machine learning to predict the presence of disease from the components of hair, the minerals Li, I, and P were cited as important factors for discriminating healthy donors from subjects with diseases. Regarding free amino acids, Cys, cysteic acid, Glu, His, Lys, Met, and Ser were cited as important factors. Steroid hormones, excluding progesterone, were also cited as important factors.

Conclusions: Our results indicate that machine learning is a meaningful analysis method for narrowing down on important components in the study of disease prediction using hair. In the future, by further increasing the number of cases and conducting component analysis using hair, it is expected that machine learning analysis will lead to the identification of disease markers.

Objective: Generally, potential carriers of viral hepatitis (VH) are expected to develop life-threatening liver-related events, such as hepatocellular carcinoma. Although VH screening at medical checkup facilities is a possible way to detect undiagnosed carriers in Japan, introducing such screening in these facilities has progressed poorly. In this study, we investigated the predictive index for VH and aimed not only to improve VH screening rates but also develop an early and effective screening test to detect VH markers (VHM)-positive examinees.

Methods: Data from examinees who received VH screening at our facilities in 2018 were analyzed. Statistical analysis was performed to examine differences in various clinical data, including non-invasive hepatic fibrosis scoring systems, between examinees who tested positive for VHM and those who did not.

Results: A high fibrosis-4 (FIB-4) index (≥1.30) value, a non-invasive hepatic fibrosis scoring system, was an independent predictor of VHM-positive examinees (p=0.004). In the subgroup analysis, a high FIB-4 index value of ≥1.30 was also an independent predictor for HBs antigens-positive examinees (p=0.004), but was not a significant predictor for HCV antibodies-positive examinees.

Conclusions: A high FIB-4 index value of ≥1.30 is a promising predictive index for examinees who tested positive for VHM, especially HBs antigens. Applying this index may improve VH screening rates and afford early and effective screening opportunities to identify VHM-positive examinees.