Objective: To attain optimal blood concentration rapidly, it is needed to perform initial dose setting appropriately when vancomycin (VCM) used.  In order to design initial dose settings of VCM more currently, we compared the predictive performance of two types of VCM therapeutic drug monitoring (TDM) analysis software retrospectively.
Method: We utilized two TDM analysis software, SHIONOGI-VCM-TDM ver.2009 (VCM-TDM) and “Vancomycin MEEK TDM analysis software Ver. 2.0” (MEEK), based on patient’s background. 112 patients who received VCM and performed TDM were analyzed during the period from October 2011 through September 2012 and compared the actual trough level with the predictive trough level.  The predictive performance was evaluated by calculating ME (mean prediction error), MAE (mean absolute prediction error), and RMSE (root mean squared error).  Age, gender, and a renal function were evaluated as patient’s background.
Results: VCM-TDM gave good predictive performance for patients overall.  When classified patient’s background complexly (sex, age, and renal function), as for male patients, VCM-TDM showed good predictive performance except for the group over 65 years old and CCr over 85 mL/min.  For female patients, the difference of predictive performance was not accepted by all groups.
Conclusion: These results suggest, for male patients, we should use VCM-TDM for initial dose settings except for the group over 65 years old and over CCr 85 mL/min.  For the other patients, we consider that both of software can be used.  These new findings seem to contribute to proper dosage settings of VCM.

Objective: It is very important that, to avoid, pharmacists-check medication being taken by patient.  In the Hokkaido University Hospital we used commercial drug identification software at the start of outpatient prescription identification duty and reported the outcome.  Furthermore, we filled in another hand-written check sheet with the drug’s name, whether or not it is used in our hospital, alternative drugs, and the dosage and administration.  Because of the risk of drugs being entered by mistake, we built a database for drug identification and distinguished the outpatient’s prescriptions.  With this system it is possible integrate identification reports and check sheet using one style, automatically.  We also to smoothly rationalize duties by planning correct communication between the medical staff.  At the same time, we analyzed the case that was able to intervene in reasonable use of medical supplies with a past identification report as a result of pharmacists distinguishing outpatient prescriptions.
Design and Methods: This system was constructed using Microsoft® Access, which is a general-purpose database software.  Also, the medical supply database that we used for this system uses “Drugs in Japan Ethical Drugs DB (supervised by Drugs in Japan Forum)” published by JIHO Co., Ltd.
Results: By using this system, we were able to reduce the time required to identify the drugs and make the report.  The result of a questionnaire carried out on doctors and a nurses and medical staff revealed that more than 90% of the respondents claimed, “the report is easy to refer.”  Likewise, we analyzed a report of the previous year and recognized that medical staff could not find the inappropriate use of prescriptions for outpatients in about 17.5%.
Conclusion: This system improved the efficiency of outpatient prescriptions practices, and it became clear that it could be used convincingly as a tool to share appropriate drug information between medical staff and pharmacists, more precisely.  In addition, feedback from medical staff suggested that it might prevent the risk of problems surrounding outpatient prescriptions, from the viewpoint of the pharmacist.

Magnetic resonance imaging (MRI) for diagnostic evaluation of the breast was performed in 61 patients who visted the Breast Clinic of our hospital and were suspected to have malignant tumors by physical examination and mammography between January and December 1999. In 58 patients undergoing histological diagnostic tests (8 with benignancy and 50 with breast cancer), we compared the imaging characteristics and the time-signal intensity curves acquired by dynamic imaging between benign and malignant lesions, and evaluated the usefulness of analyzing enhancement patterns on contrast MRI. Contrast MRI revealed strong tumor enhancement in all patients; the mean time required for the signal intensity to reach a peak was about 7 min in patients with benign tumors and about 2 min in those with breast cancer. Peripheral ring enhancement was observed in 40 of the 50 patients with breast cancer (80.0%), while such enhancement was not noted in any of the patients with benign tumors.
Although diagnosis of breast disease by imaging has primarily relied on mammography and ultrasonography, the pattern of contrast enhancement on dynamic MRI also appears to be useful for determining the treatment method of breast tumors.

Objective: Hematological toxicity, including neutropenia and thrombocytopenia, is a typical side effect of ganciclovir (GCV). We previously developed a risk-prediction model for GCV-induced neutropenia using decision tree (DT) analysis. By employing the DT model, which is a flowchart-like framework, users can predict the combination of factors that may increase neutropenia risk. However, a risk-prediction model for thrombocytopenia has not been established. Here, we aimed to identify the risk factors associated with GCV-induced thrombocytopenia and construct risk-prediction models.Method: We retrospectively evaluated the medical records of 386 patients who received GCV between April 2008 and March 2018 at Hokkaido University Hospital. Thrombocytopenia is defined as a decrease in the platelet count (PLT) to ＜50,000 cells/mm3 and to a ＜75% decrease. Risk factors of thrombocytopenia were extracted from the medical records using a multiple logistic regression analysis. Moreover, we employed chi-squared automatic interaction detection (CHAID) and classification and regression tree (CRT) algorithms to develop the DT models. The accuracies of the established models were evaluated to assess their reliability.Results: Thrombocytopenia occurred in 47 (12.2%) patients. In the multiple logistic regression analysis, data of patients with white blood cells ＜7,000 cells/mm3,PLT＜101,000 cells/mm3 and total bilirubin ≥ 0.8 mg/dL were extracted. Two risk-prediction models were constructed, and patients were divided into six and seven subgroups. In both algorithms, data on hematopoietic stem cell transplantations, PLT ＜101,000 cells/mm3, serum albumin ＜ 2.8 g/dL, total bilirubin ≥ 0.8 mg/dL, and residence in intensive care unit were extracted. The predictive accuracy of both the CHAID algorithm and the logistic regression models was 87.8% and that of the CRT algorithm was 88.3%, indicating they were reliable.Conclusion: We successfully identified the factors associated with GCV-induced thrombocytopenia and constructed useful flowchartlike risk-prediction models.

Purpose: This study aimed to analyze the terminal care attitudes of healthcare members engaged in palliative care and the factors associated with these attitudes. Methods: We conducted a survey for healthcare members engaging in palliative care including oncologists and palliative care doctors using the Japanese version of the Frommelt Attitudes Toward Care of the Dying (FATCOD B-J), a scale that measures the attitude of medical stuff toward the care of dying patients. Results: A total of 223 (response rate=42.2%) responses were obtained and analyzed. Multiple regression analysis using the FATCOD B-J total score as the objective variable showed that 30s had lower partial regression coefficients than 40s (−3.8). Higher “satisfaction from work” and “interest in palliative care” were associated with greater partial regression coefficients (+5.7, +6.2). Conclusion: A sense of satisfaction and interest in palliative care may be important to cultivate terminal care attitudes among health care providers involved in palliative care.