The mitral-aortic intervalvular fibrosa (MAIF) is a fibrous skeleton between the mitral and aortic valves. We describe a case of a pseudoaneurysm of MAIF (MAIFPsA) 3 months after an aortic valve replacement. A 75-year-old man had undergone aortic valve replacement using a bioprosthesis (SJM Trifecta 23 mm). He developed congestive heart failure 3 months after surgery. Trans-esophageal echocardiography and multi-detector computed tomography detected a MAIFPsA and severe paravalvular leakage. The patient underwent a new operation. After the aortic prosthesis was removed, an orifice of the pseudoaneurysm, which was composed of the anterior mitral leaflet and the aortic annulus, were revealed. The defect was repaired with a bovine pericardial patch, sutured to the anterior mitral leaflet and aortic annulus. A new bioprosthesis (Carpentier-Edwards PERIMOUNT 21 mm) was implanted in the supra-annular position. His postoperative course was uneventful.

Objective: The Pharmaceuticals and Medical Devices Agency (PMDA) discloses reports with accumulated side effect information in comma-separated value (CSV) format.  It is difficult to use the information in this type of text file because the amount of data is large and composed of multiple fields.  Therefore, we developed an application that presents the data in a way that is easier to read and understand.
Methods: The application can display the whole dataset, or the search results of certain medicines and side effects within the database in Microsoft Access 2013.  It exports data from search results into an Excel spreadsheet organized by medicine and side effect.
Results: This application makes it possible to understand statistics contained in the side effect dataset, such as the number of cases, the medicines, and the side effects themselves.  Moreover, the application allows the totaled search results for the medicines and the side effects to be graphed.  It also makes it possible to understand the sex and age distribution of patients, as well as the days elapsed before developing a side effect.
Conclusions: Recently, the importance of information concerning the safety of medicine has increased.  This system could facilitate the effective use of side effect information and the creation of medicine risk management plans in medical institutions.

Objective: The hospital is changing its formulary reference from paper-based to intranet.  There was concern that both paper-based and intranet versions of the formulary would be necessary.  Revising the paper-based hospital formulary each time package inserts are revised is difficult.  For your review we report on the creation of the iPhone® electronic formulary which enables rapid off-line formulary retrieval and easy updates while at the same time providing low cost service in a light device.
Methods: The CSV (Comma Separated Value) of the hospital formulary dictionary was made using a standard personal computer.  The CSV data file was converted using JAMES2DIC into a HTML file format.  Next, the converted HTML file is transformed into the EPWING (Electronic Publishing WING) format using EBStudio.  Finally, we forward the EPWING dictionary file from the personal computer to the iPhone®.  The retrieval becomes possible by using EBPocket for iOS of EPWING/electronic book viewer software for the iPhone®.  The number of items was assumed to be 29 items thought for a lot of inquiries to exist.
Results: We compared the paper-based formulary with the iPhone® electronic formulary.  As a result, the iPhone4® electronic formulary shortened the retrieval time, was smaller, lighter, and excellent at a lower price.
Conclusion: The iPhone4® electronic formulary enables the user to perform complex full-text searches and retrieve information at a much higher speed than is possible with paper based formularies.  It has the additional advantage of seamless integration and deployment of formulary additions or reference material revisions.  We believe we have successfully created a practical electronic formulary.

Objective: The feasibility of peri-orbital electrodes, which are not invasive and do not induce pain, as a supplemental electrode for detection of ictal discharges in medial temporal lobe epilepsy (MTLE) was examined. Methods: Patients with MTLE, who underwent video-EEG monitoring with simultaneous peri-orbital and sphenoidal electrodes and obtained good outcome following standard anterior temporal lobectomy, were subjects in this study. Initial ictal discharge amplitudes were compared between sphenoidal (Sp1/ 2), standard anterior temporal in 10-20 system (F7/ 8), peri-orbital (superior orbital lateral: SOL, inferior orbital medial: IOM), frontopolar (Fp1/ 2), frontal (F3/4) and ear (A1/ 2) electrodes. Results: A total of 34 consecutive seizures from 20 patients were analyzed, with a maximum amplitude observed at Sp1/2 (57.57±5.59), followed by F7/8 (54.89±5.59), SOL (50.97±5.59), IOM (46.95±5.59), A1/2 (45.07±5.69), Fp1/2 (44.78±5.62), and F3/4 (37.75±5.66) (mean±standard error, μV). There was no statistical difference between Sp1/2, F7/8, SOL, and IOM values. When the sphenoidal electrode was omitted, 13 seizures (13/34, 38.2%) resulted in the highest amplitude at peri-orbital electrodes and 10 seizures (10/ 34, 29.4%) at F7/8. Conclusions: Peri-orbital electrodes could detect ictal discharges in MTLE as well as sphenoidal and standard anterior temporal electrodes in 10-20 system and are useful for supplemental recording for detecting ictal epileptiform discharges in MTLE.

A 66-year-old man was under observation as an outpatient for moderate aortic regurgitation and distal aortic arch aneurysm since 2005. He underwent surgery for gradual expansion of the distal aortic arch aneurysm. Preoperative enhanced computed tomography (CT) revealed a fusiform-type aortic aneurysm with a maximum short diameter of 63 mm. The aneurysm extended from the left subclavian artery to the descending aorta, 67 mm ahead. Based on the preoperative CT, a 150-mm open stent graft (OSG) was selected because of an adequate landing zone when inserted from the proximal site of the left subclavian artery. A 33-mm diameter graft was selected with a diameter 10% larger than that of the aorta at the landing zone. Moreover, the preoperative rapid plasma reagin (RPR) test was positive at 5.5 RU, and the fixed Treponema pallidum latex agglutination (TPLA) test was positive at 4,670 TU. He had undergone treatment for syphilis, and we concluded that the patient harbored antibodies after syphilis treatment. In the operating room, median sternotomy was performed. Cardiopulmonary bypass (CPB) was instated with bilateral axillary artery return, and superior vena cave (SVC) -inferior vena cave (IVC) venous drainage was placed. The aortic wall was strongly adherent to the surrounding tissue, similar to that observed in the aortitis syndrome. We performed aortic valve replacement during the systemic cooling. Under hypothermic circulatory arrest at 25°C with selective cerebral perfusion, the aorta was cut between the left common carotid artery and left subclavian artery. From this site, OSG was inserted to the level of the aortic valve. Total arch replacement was performed with a 30-mm bypass graft. Pathological findings indicated infiltration of lymphocytes and plasma cells around the feeding artery in the aortic aneurysm wall, and the aortic media wall showed fibrillation. Based on the intraoperative and postoperative pathologic findings, we diagnosed the patient with syphilitic aortic aneurysm, and started oral administration of amoxicillin 1,500 mg per day for 3 months. He was discharged on the 13th postoperative day without paraplegia, vocal cord paralysis, or other complications. Although syphilitic aortic aneurysm is rarely seen, it must always be considered as one of the causes of aortic aneurysm.

Objective: Currently, limited information is available on the milk transfer properties of drugs when consumed by lactating women. Therefore, we aim to construct a prediction model of milk transfer of drugs using machine learning methods.Methods: We obtained data from Hale’s Medications & Mothers’ Milk (MMM) and SciFinder®, and then constructed the datasets. The physicochemical and pharmacokinetic data were used as feature variables with M/P ratio ≥ 1 and M/P ratio < 1 as the objective variables, classified into two groups as the classification of milk transferability. In this study, analyses were conducted using machine learning methods: logistic regression, linear support vector machine (linear SVM), kernel method support vector machine (kernel SVM), random forest, and k-nearest neighbor classification. The results were compared to those obtained with the linear regression equation of Yamauchi et al. from a previous study. The analysis was performed using scikit-learn (version 0.24.2) with python (version 3.8.10).Results: Model construction and validation were performed on the training data comprising 159 drugs. The results revealed that the random forest had the highest accuracy, area under the receiver operating characteristic curve (AUC), and F value. Additionally, the results with test data A and B (n = 36, 31), which were not used for training, showed that both F value and accuracy for the random forest and the kernel method SVM exceeded those with the linear regression equation of Yamauchi et al. Conclusion: We were able to construct a predictive model of milk transferability with relatively high performance using a machine learning method capable of nonlinear separation. The predictive model in this study can be applied to drugs with unknown M/P ratios for providing a new source of information on milk transfer.