PURPOSE: The purpose of this study was to determine the impact of uncertainty and uncertainty appraisal on quality of life (QoL) among prostate cancer patients after prostatectomy. METHODS: A descriptive correlational study was conducted with 117 participants at a hospital in S city from October 1 to December 31, 2016. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients and stepwise multiple regression using the IBM SPSS/WIN 21.0 program. RESULTS: According to a multiple regression model of the factors affecting QoL among prostate cancer patients after the operation, 61% of variance (F=13.92, p<.001) was explained by metastasis, recurrence, monthly income, uncertainty, uncertainty danger appraisal, and uncertainty opportunity appraisal. And the most influential factor in the QoL was uncertainty danger appraisal (β=-.37, p<.001). CONCLUSION: This study demonstrated that QoL was influenced by uncertainty, uncertainty appraisal and personal characteristics. Prostate cancer patients following prostatectomy should be provided with tailored training to improve their uncertainty opportunity appraisal. Also the educational program for reducing their uncertainty should be developed and provided to patients.
Humans ; Neoplasm Metastasis ; Prostate* ; Prostatectomy* ; Prostatic Neoplasms* ; Quality of Life* ; Recurrence ; Uncertainty*

BACKGROUND: Patients with cardiovascular risks are recommended to use statins and antiplatelet agents to prevent major cerebrocardiovascular events (MACCE). Antiplatelet agents also possess anti-inflammatory and antioxidant effects, in addition to their inhibitory activity on platelets. The differences in clinical outcomes in ischemic heart disease (IHD) based on the type of antiplatelet therapy combined with statin treatment were investigated in this study. METHODS: We conducted a retrospective cohort study using electronic medical records of IHD patients from January 2010 to December 2014 at Ajou University Hospital. Patients on combination therapy of antiplatelet drugs and statins were grouped based on antiplatelet drug types: clopidogrel, cilostazol, or sarpogrelate. Propensity score matching was applied to balance the baseline of the groups of clopidogrel vs. cilostazol and the groups of clopidogrel vs. sarpogrelate. The incidence and risk of MACCE as primary outcomes were assessed between the groups of antiplatelet drugs. RESULTS: Among the approximately 128,500 patients with IHD, 1,049 patients had taken a combination therapy of statin and antiplatelet agents. The cohorts of patients administered clopidogrel, cilostazol, or sarpogrelate were 906, 79, and 64, respectively. The incidence of MACCE was not significantly different among the cohorts (p=0.58), and there were no differences between clopidogrel vs. cilostazol (p=0.72) or clopidogrel vs. sarpogrelate (p=1.00) after propensity score matching. CONCLUSION There was no difference in the incidence of MACCE based on the type of antiplatelet drug (clopidogrel, cilostazol, or sarpogrelate) in combination with a statin in patients with IHD.

The purpose of this study was to investigate that the effect of dietary fatty acid composition on pro- and macro-glycogen utilization and resynthesis. The analyses were further extended for different muscle fibers (type I, type II, & type IIb ) as well as tissues (i.e., liver & heart ). Total one hundred sixty Sprague-Dawley rats were used, and rats were randomly allocated into four experimental groups :animals fed standard chow diet (n =40 ), animals fed saturated fatty acid diet (n =40 ), animals fed monounsaturated fatty acid (n =40 ), and animals fed polyunsaturated fatty acid (n =40 ). Animals in each groups were further divided into five subgroups :sacrificed at REST (n =8 ), sacrificed at immediately after 3 hr swim exercise (P-0HR, n =8 ), sacrificed at one hour after 3 hr swim exercise (P-1HR, n =8 ), sacrificed at four hour after 3 hr swim exercise (P-4HR, n =8 ), and sacrificed at twenty-four hour after 3 hr swim exercise (P-24HR, n =8 ). Soleus (type I ), red gastrocnemius (type IIa ), white gastrocnemius (type IIb ), liver, and heart were dissected out at appropriated time point from all animals, and were used for analyses of pro- & macro-glycogen concentrations. After 8 weeks of dietary interventions, there was no significant difference in body mass in any of dietary conditions (p >.05 ). After 3 hr swim exercise, blood lactate level was higher compared to resting conditions in all groups, but it was returned to resting value after 1 hr rest (p <.05 ). Free fatty acid concentration was higher in all high fat fed groups (regardless of fatty acid composition )than CHOW consumed group. At rest, pro- & macro-glycogen concentration was not different from any of experimental groups (p >.05 ). Regardless of forms of glycogen, the highest level was observed in liver (p <.01 ), and most cases of supercompensation after 3hr exercise observed in this study were occurred in CHOW fed tissues. Except heart muscle, all tissues used in this study showed that pro- and macro-glycogen concentration was significantly decreased after 3 hr exercise. Based on these results, two conclusions were made :first, there is no different level of glycogen content in various tissues regardless of types of fatty acids consumed and second, the highest mobilization rate would be demon-strated from CHOW fed animals compare to animals that consumed any kinds of fatty acid diet if prolonged exercise is applied.
Animals ; Diet ; Fatty Acids ; Glycogen ; Heart ; Lactic Acid ; Liver ; Muscle, Skeletal* ; Myocardium ; Rats* ; Rats, Sprague-Dawley

Objectives: The objective of this study was to develop and validate a multicenter-based, multi-model, time-series deep learning model for predicting drug-induced liver injury (DILI) in patients taking angiotensin receptor blockers (ARBs). The study leveraged a national-level multicenter approach, utilizing electronic health records (EHRs) from six hospitals in Korea. Methods: A retrospective cohort analysis was conducted using EHRs from six hospitals in Korea, comprising a total of 10,852 patients whose data were converted to the Common Data Model. The study assessed the incidence rate of DILI among patients taking ARBs and compared it to a control group. Temporal patterns of important variables were analyzed using an interpretable timeseries model. Results: The overall incidence rate of DILI among patients taking ARBs was found to be 1.09%. The incidence rates varied for each specific ARB drug and institution, with valsartan having the highest rate (1.24%) and olmesartan having the lowest rate (0.83%). The DILI prediction models showed varying performance, measured by the average area under the receiver operating characteristic curve, with telmisartan (0.93), losartan (0.92), and irbesartan (0.90) exhibiting higher classification performance. The aggregated attention scores from the models highlighted the importance of variables such as hematocrit, albumin, prothrombin time, and lymphocytes in predicting DILI. Conclusions Implementing a multicenter-based timeseries classification model provided evidence that could be valuable to clinicians regarding temporal patterns associated with DILI in ARB users. This information supports informed decisions regarding appropriate drug use and treatment strategies.

Objectives: The aim of this study was to characterize the benefits of converting Electronic Medical Records (EMRs) to a common data model (CDM) and to assess the potential of CDM-converted data to rapidly generate insights for benefit-risk assessments in post-market regulatory evaluation and decisions. Methods: EMRs from January 2013 to December 2016 were mapped onto the Observational Medical Outcomes Partnership-CDM (OMOP-CDM) schema. Vocabulary mappings were applied to convert source data values into OMOP-CDM-endorsed terminologies. Existing analytic codes used in a prior OMOP-CDM drug utilization study were modified to conduct an illustrative analysis of oral anticoagulants used for atrial fibrillation in Singapore and South Korea, resembling a typical benefit-risk assessment. A novel visualization is proposed to represent the comparative effectiveness, safety and utilization of the drugs. Results: Over 90% of records were mapped onto the OMOP-CDM. The CDM data structures and analytic code templates simplified the querying of data for the analysis. In total, 2,419 patients from Singapore and South Korea fulfilled the study criteria, the majority of whom were warfarin users. After 3 months of follow-up, differences in cumulative incidence of bleeding and thromboembolic events were observable via the proposed visualization, surfacing insights as to the agent of preference in a given clinical setting, which may meaningfully inform regulatory decision-making. Conclusions While the structure of the OMOP-CDM and its accessory tools facilitate real-world data analysis, extending them to fulfil regulatory analytic purposes in the post-market setting, such as benefit-risk assessments, may require layering on additional analytic tools and visualization techniques.