Objective: Inherited hyperbilirubinemia is almost a Gilbert’s syndrome, which is fluctuated by infection, stress, and fasting. The diagnosis of Gilbert’s syndrome using the bilirubin level of one sample is unclear. I examined the prevalence of inherited jaundice in Japanese by 10-year follow up.

Methods: The participants were 772 men and 1,039 women without liver dysfunction and anemia who visited the Kouseiren Takaoka Health Care Center in 2010. The participants were followed up for 10 years. The minimum and maximum levels and fluctuation range of total bilirubin in 10 years were calculated. The participants were divided into the < 1.0 mg/dL and > 1.1 mg/dL groups, according to the maximum total bilirubin level.

Results: In the < 1.0 mg/dL group, the mean total bilirubin levels were 0.66 ± 0.13mg/dL and 0.65 ± 0.13mg/dL in men and women, respectively, with no significant difference. The mean fluctuation ranges of total bilirubin were 0.33 ± 0.19mg/dL and 0.24 ± 0.17mg/dL in men and women, respectively, with a significant difference (p<0.001). The prevalence of hyperbilirubinemia with > 1.1 mg/dL max total bilirubin level were 42.1% and 24.5% in men and women, respectively. The fluctuation bilirubin levels of hyperbilirubinemia were 0.2 to 3.4mg/dL in men and 0.3 to 2.6 mg/dL in women.

Conclusions: Assuming that the upper limit of the normal total bilirubin level was 1.0 mg/dL, the prevalence of inherited jaundice was thought to be higher than those in previous studies.

Objective: We investigated whether coronary artery calcification can be assessed by non-electrocardiogram (ECG) synchronous computed tomography (CT) imaging.

Methods: Of the 246 patients who permitted to have coronary artery calcification assessed in conjunction with CT scanning, conventional scanning with ECG synchronization and non-ECG synchronized helical scanning were performed. The coronary artery calcification index (CACS) was calculated by the Agatston method and compared between the two groups.

Results: In the conventional scan group, the correlation coefficients of 78 patients with CACS ≥1, 29 patients with CACS ≥65, 20 patients with CACS ≥100, and 6 patients with CACS ≥400 were 0.923, 0.950, 0.919, and 0.943, respectively, showing a strong positive correlation (p<0.01). There were 10 patients that had a CACS of 0 in the helical scan despite a CACS result of ≥1 in the conventional scan. The mean CACS of the 10 patients was 8.6 ± 7.9, which was <65. If the conventional scan group had a positive CACS of ≥1, the sensitivity and specificity of the helical scan group were 87% and 100%, respectively. The positive and negative predictive values were 100% and 94%, respectively.

Conclusion: The results suggest that non-ECG synchronized CT imaging is useful in detecting cases of coronary artery calcification with a CACS result of ≥65.

Objective: Cardiac dysfunction and valvular heart diseases progress slowly. Early detection of these diseases is challenging for non-cardiologists. Therefore, we developed an artificial intelligence (AI) model for Japanese to simultaneously detect cardiac dysfunction and valvular diseases using a 12-lead electrocardiogram (ECG) and recommend examination such as echocardiograms.

Methods: We conducted a retrospective cohort study, and enrolled 30,467 adult patients, who were exposed to both 12-lead ECG and echocardiography between 2006 and 2021. These patients included 945 medical checkup examinees (3.1%). We developed a model that can speculate decreased left ventricular ejection fraction (LVEF) <40% and/or moderate to severe valvular heart diseases from ECGs.

Results: The model achieved high specificity for estimating reduced LVEF (sensitivity 74.1%, specificity 95.3%), aortic stenosis (sensitivity 18.9%, specificity 95.2%) and aortic (sensitivity 36%, specificity 95.2%), mitral (sensitivity 35.6%, specificity 95.2%), and tricuspid valve regurgitation (sensitivity 39.4%, specificity 94.6%) by the ECG. If a patient has at least one of these statuses, the patient needs to receive echocardiography. The AI could determine the necessity of echocardiography by ECG (sensitivity 44.7%, specificity 92.9%).

Conclusions: AI-based 12-lead ECG analysis can be used in patient selection for precise examination, including an echocardiogram, without any expert consultation or professional ECG interpretation.

Objective: In February 2018, after the assignment of full-time public health nurses, the Center established a system for health guidance after health examinations and continuous follow-up in writing and by telephonic conversation. In this paper, we will discuss our efforts in fundus examination, which is one of our main focuses, and report on its effectiveness.

Methods: The patients who underwent physical examinations from April 2017 to July 2019 were divided into three groups: before the start of follow-up, after the start of follow-up, and after the enhancement (a document with content specific to findings after four months for subjects with a judgment requiring detailed examination and treatment [hereinafter referred to as “D judgment”] on the fundus examination day). We calculated, compared, and examined the D judgment rate and ophthalmologic consultation rate of each group.

Results: The ophthalmology consultation rate improved to 64.2% after the start of follow-up and to 73.2% after enhanced follow-up for optic nerve papillary depression, which accounts for a high percentage of fundus findings. In addition, the rate of ophthalmological examinations after 4 to 8 months has been improved by strengthening the follow-up after the physical examination.

Conclusion: Enclosing a leaflet on optic nerve papillary depression significantly increased the rate of ophthalmological consultation among patients with depression. In order to improve and maintain the uptake rate, it is necessary to provide continuous follow-up from the day of medical check-up.

Objective: Until now, the facility has conducted sleep apnea syndrome (SAS) screening tests using a pulse oximeter and sleep recorder; however, the number of devices was limited. To increase the number of examinations, improve the accuracy of examinations, and collect many potential patients with SAS, we outsourced from 2019 and changed to examinations using a simple polysomnography (simplified PSG) device, and compared and examined the results before and after introduction.

Methods: In FY2018, the rate of patients requiring further investigation based on the results and the number of patients with SAS underwent tests using pulse oximeters and sleep recorders managed at the facility. In FY2019, the tests were outsourced and a simple PSG was used to compare the number of SAS tests performed.

Results: The number of tests performed was more than that if doubled, increasing from 36 to 77. The percentage of test results requiring further investigation increased from 31% to 55%, percentage of replies from healthcare providers increased from 18% to 64%, and number of patients with SAS increased from 2 to 21.

Conclusion: Changing to the SAS screening test using a simple PSG device and eliminating the device limitations by outsourcing the test were effective in collecting many potential patients with SAS. By reviewing the test flow and following up after the test, we were able to connect many patients with SAS for treatment.