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Tian L, Liu R, Zhou Z, Xu X, Feng S, Kushmaro A, Marks RS, Wang D, Sun Q. Probiotic Characteristics of Lactiplantibacillus Plantarum N-1 and Its Cholesterol-Lowering Effect in Hypercholesterolemic Rats. Probiotics Antimicrob Proteins 2022; 14:337-348. [PMID: 35064922 DOI: 10.1007/s12602-021-09886-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/04/2021] [Indexed: 11/28/2022]
Abstract
In this study, the probiotic potential and treatment effects of Lactiplantibacillus plantarum N-1 in hypercholesterolemic rats were investigated, and the possible regulatory mechanisms of lipid metabolism via short-chain fatty acids (SCFAs) and 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase were elucidated. The strain N-1 displayed probiotic properties of antioxidant capacity, adhesion to Caco-2 cells, susceptibility to antibiotics in vitro. The results in animal study showed that the total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) levels in serum and TC in liver declined significantly in both N-1 and simvastatin (Sta) treatment groups compared to the control (P < 0.05), and the extent of these decreases were similar between them. The expression of the HMG-CoA gene in the N-1 group was downregulated significantly by 31.18% compared to the control (P < 0.01), and the contents of butyrate and valerate in N-1 groups were significantly higher than those in both model and Sta group (P < 0.05). Thus, promoting the production of the intestinal SCFAs and inhibiting the expression of HMG-CoA reductase by L. plantarum N-1 may contribute to the improved lipid metabolism and thus lowering cholesterol level in rats. Our investigation indicated that L. plantarum N-1 has the potential to be developed into a functional food supplement for hypercholesterolemia treatment.
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Affiliation(s)
- Lei Tian
- Key Laboratory of Bio-Resource and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, Sichuan, People's Republic of China.,Department of Biotechnology Engineering, Faculty of Engineering Sciences, Avram and Stella Goldstein-Goren, Ben Gurion University of the Negev, 84105, Beer-Sheva, Israel
| | - Rongmei Liu
- Key Laboratory of Bio-Resource and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, Sichuan, People's Republic of China.,Key Laboratory of Sichuan Province for Dairy Nutrition and Function, New Hope Dairy Co., Ltd., Chengdu, China
| | - Zhiwei Zhou
- Key Laboratory of Bio-Resource and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, Sichuan, People's Republic of China
| | - Xiaofang Xu
- Key Laboratory of Bio-Resource and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, Sichuan, People's Republic of China
| | - Su Feng
- Key Laboratory of Bio-Resource and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, Sichuan, People's Republic of China
| | - Ariel Kushmaro
- Department of Biotechnology Engineering, Faculty of Engineering Sciences, Avram and Stella Goldstein-Goren, Ben Gurion University of the Negev, 84105, Beer-Sheva, Israel.,The Ilse Katz Centre for Meso and Nanoscale Science and Technology, Ben-Gurion University of the Negev, 84105, Beer-Sheva, Israel
| | - Robert S Marks
- Department of Biotechnology Engineering, Faculty of Engineering Sciences, Avram and Stella Goldstein-Goren, Ben Gurion University of the Negev, 84105, Beer-Sheva, Israel.,The Ilse Katz Centre for Meso and Nanoscale Science and Technology, Ben-Gurion University of the Negev, 84105, Beer-Sheva, Israel
| | - Dan Wang
- School of Bioscience and Technology, Chengdu Medical College, Chengdu, 610500, Sichuan, People's Republic of China.
| | - Qun Sun
- Key Laboratory of Bio-Resource and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, Sichuan, People's Republic of China.
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Shin SY, Kim HS. Data Pseudonymization in a Range That Does Not Affect Data Quality: Correlation with the Degree of Participation of Clinicians. J Korean Med Sci 2021; 36:e299. [PMID: 34783216 PMCID: PMC8593412 DOI: 10.3346/jkms.2021.36.e299] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 10/18/2021] [Indexed: 12/28/2022] Open
Abstract
Personal medical information is an essential resource for research; however, there are laws that regulate its use, and it typically has to be pseudonymized or anonymized. When data are anonymized, the quantity and quality of extractable information decrease significantly. From the perspective of a clinical researcher, a method of achieving pseudonymized data without degrading data quality while also preventing data loss is proposed herein. As the level of pseudonymization varies according to the research purpose, the pseudonymization method applied should be carefully chosen. Therefore, the active participation of clinicians is crucial to transform the data according to the research purpose. This can contribute to data security by simply transforming the data through secondary data processing. Case studies demonstrated that, compared with the initial baseline data, there was a clinically significant difference in the number of datapoints added with the participation of a clinician (from 267,979 to 280,127 points, P < 0.001). Thus, depending on the degree of clinician participation, data anonymization may not affect data quality and quantity, and proper data quality management along with data security are emphasized. Although the pseudonymization level and clinical use of data have a trade-off relationship, it is possible to create pseudonymized data while maintaining the data quality required for a given research purpose. Therefore, rather than relying solely on security guidelines, the active participation of clinicians is important.
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Affiliation(s)
- Soo-Yong Shin
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea
- Center for Research Resource Standardization, Samsung Medical Center, Seoul, Korea
| | - Hun-Sung Kim
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
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3
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Zhirov IV. [Decreasing cardiovascular morbidity: how to improve adherence to the treatment in the translational era]. TERAPEVT ARKH 2020; 92:49-53. [PMID: 33346431 DOI: 10.26442/00403660.2020.09.000835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 10/13/2020] [Indexed: 11/22/2022]
Abstract
Cardiovascular diseases are the main drivers of the morbidity and mortality in Russian Federation. We briefly discussed the poor adherence of the patients and outlined the solutions of this problem.
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Affiliation(s)
- I V Zhirov
- National Medical Research Center for Cardiology.,Russian Medical Academy of Continuous Professional Education
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4
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Lee J, Lee SH, Kim H, Lee SH, Cho JH, Lee H, Yim HW, Yoon KH, Kim HS, Kim JH. Low-density lipoprotein cholesterol reduction and target achievement after switching from statin monotherapy to statin/ezetimibe combination therapy: Real-world evidence. J Clin Pharm Ther 2020; 46:134-142. [PMID: 33026659 DOI: 10.1111/jcpt.13271] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2020] [Revised: 08/16/2020] [Accepted: 09/05/2020] [Indexed: 01/11/2023]
Abstract
WHAT IS KNOWN AND OBJECTIVES This study investigated the additional low-density lipoprotein cholesterol (LDL-C) reductions and target (LDL-C < 100 mg/dL) achievement rates in patients after switching from statin monotherapy to statin/ezetimibe combination therapy, in clinical practice. METHODS This retrospective study used data recovered from the electronic medical record systems of two tertiary care medical centres for patients treated between 2015 and 2017. Patients prescribed statin/ezetimibe combination therapy after switching from statin monotherapy were enrolled. The observed LDL-C reductions and the percentage of patients achieving LDL-C levels of <100 mg/dL, after 3 months of treatment, were assessed relative to baseline values. RESULTS AND DISCUSSION A total of 4252 patients with prescriptions for statin/ezetimibe combination therapy were enrolled. Changing from statin monotherapy to the combination therapy resulted in additional LDL-C level reductions of 31.0-41.0% (all intensity groups, P < .01). Similarly, 88.3-91.1% of the enrolled patients successfully achieved LDL-C levels of <100 mg/dL (all intensity groups, P < .01). A subgroup analysis of patients with baseline LDL-C levels ≥ 100 mg/dL showed that switching from moderate- or high-intensity statin monotherapy to a rosuvastatin/ezetimibe combination showed greater LDL-C reductions than did switching to an atorvastatin/ezetimibe combination, within the same statin intensity groups. WHAT IS NEW AND CONCLUSION The present study provides real-world evidence of the LDL-C reduction benefits associated with statin/ezetimibe combinations in the clinical practice setting. The results also demonstrate that if statin monotherapy does not effectively help patients reach their target LDL-C goals, changing to a statin/ezetimibe combination prescription may show enhanced LDL-C-lowering effects and improve the likelihood of achieving LDL-C targets, in real practice.
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Affiliation(s)
- Jeongmin Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Sue Hyun Lee
- Department of Biomedical Informatics, College of Medicine, Konyang University, Daejeon, Korea
| | - Hyunah Kim
- College of Pharmacy, Sookmyung Women's University, Seoul, Republic of Korea
| | - Seung-Hwan Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jae Hyoung Cho
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyunyong Lee
- Clinical Research Coordinating Center, Catholic Medical Center, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyeon Woo Yim
- Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kun-Ho Yoon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.,Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hun-Sung Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.,Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Ju Han Kim
- Division of Biomedical Informatics, Systems Biomedical Informatics Research Centre, Seoul National University College of Medicine, Seoul, Republic of Korea
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Achievement of the low-density lipoprotein cholesterol goal among patients with dyslipidemia in South Korea. PLoS One 2020; 15:e0228472. [PMID: 31999714 PMCID: PMC6992159 DOI: 10.1371/journal.pone.0228472] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Accepted: 01/16/2020] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND It is important to achieve the low-density lipoprotein cholesterol (LDL-C) goal recommended by clinical guidelines in managing the risk of cardiovascular (CV) events, however, the current management of LDL-C in actual clinical settings is suboptimal. We examined the LDL-C level among patients with dyslipidemia against the 2015 Korean guidelines, the crude rates of CV events based on LDL-C goal achievement, and the factors associated with LDL-C goal achievement. METHODS This was a retrospective cohort study using the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) database from 2006 to 2013. Patients who had a health examination with LDL-C measurement between January 1, 2007, and December 31, 2011 were identified. Patients were required to have at least one diagnosis of dyslipidemia during the 1 year before the index date, defined as the first date of LDL-C measurement. The 2015 Korean guidelines were used to measure LDL-C goal achievement based on the CV risk level. Crude CV event rates were calculated for total and individual CV events as the number of events divided by person-years (PYs) during the follow-up period. CV events included acute coronary syndrome, ischemic stroke, peripheral artery disease, CV death, and all-cause death. Factors associated with LDL-C goal achievement were assessed using logistic regression. RESULTS In the NHIS-HEALS database, 69,942 patients met the eligibility criteria: 36.7%, 22.5%, 20.1%, and 20.6% were among the very high-, high-, moderate-, and low-risk groups for the CV events, respectively, as defined by the 2015 Korean guidelines. Approximately half of the patients with dyslipidemia (47.6%) achieved their recommended LDL-C goal, but the achievement rates were substantially different across CV risk levels (17.6%, 47.2%, 66.9%, and 82.4% for very high-, high-, moderate-, and low-risk groups, respectively; P<0.0001). The crude event rate of total CV events during the follow-up period in the LDL-C goal non-achievers was higher than that in the LDL-C goal achievers (24.35/100 PYs vs. 11.93/100 PYs; P<0.0001). LDL-C goal achievement was significantly associated with patient characteristics, including age, sex, body mass index, lipid-modifying therapy, and CV risk level. CONCLUSIONS In South Korea, LDL-C goal achievement among patients with very high or high CV risk was suboptimal. Patients who did not achieve the goal showed a higher rate of CV events during the follow-up period than patients who achieved the goal. LDL-C management strategies should be highlighted in dyslipidemia patients who are less likely to achieve the goal, such as female, overweight or obese patients, patients not adherent to statin, or patients with very high or high CV risk.
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Kim HS, Lee SH, Kim TM, Kim JH. Developing a multi-center clinical data mart of ACEI and ARB for real-world evidence (RWE). Clin Hypertens 2018; 24:18. [PMID: 30564448 PMCID: PMC6295049 DOI: 10.1186/s40885-018-0103-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 11/12/2018] [Indexed: 11/30/2022] Open
Abstract
Background Randomized controlled trials can be expensive and time-consuming, leading to medical researchers utilizing real-world evidence (RWE) based on already-collected data. We aimed to conduct various RWE studies on angiotensin-converting enzyme inhibitors (ACEI) and angiotensin II receptor blocker (ARB), commonly used as first-line therapy for blood pressure, and to develop a multi-center clinical data mart (CDM) of ACEI/ARB for various clinical purposes. Methods Data from electronic medical records of St. Mary’s Hospital and the Seoul National University Hospital were collected. We obtained blood and urine test results of patients within the 30 days prior to their first prescription of ACEI or ARB, as well as the first date of diagnosis and presence of various chronic and cardiovascular diseases using the International Classification of Diseases-10 classification. One researcher managed data quality and collation for each hospital in order to facilitate patient anonymity. When results were unclear, the responsible investigator for each hospital attempted to resolve ambiguities by direct chart review. Results A total of 102,333 patients who were prescribed ACEI or ARB for the first time were included (21,481 ACEI, 80,551 ARB, and 301 both). Our ACEI/ARB-CDM included short-term studies (within 12 months) to observe changes in various blood or urinary laboratory test values after the initial prescription of ACEI or ARB and long-term studies to confirm the incidence of various diseases. Conclusion We established a CDM of RWE for ACEI/ARB prescription, which included various clinical studies. As we accumulate experience in this process, we expect that the use of RWE research will grow and develop.
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Affiliation(s)
- Hun-Sung Kim
- 1Department of Medical Informatics, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591 Republic of Korea.,2Department of Endocrinology and Metabolism, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sue Hyun Lee
- 3Division of Biomedical Informatics, Systems Biomedical Informatics Research Centre, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 110-799 Republic of Korea
| | - Tong Min Kim
- 1Department of Medical Informatics, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591 Republic of Korea
| | - Ju Han Kim
- 3Division of Biomedical Informatics, Systems Biomedical Informatics Research Centre, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 110-799 Republic of Korea
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7
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Lee J, Lee S. Comparative Effectiveness of Combination Therapy with Statins and Angiotensin-Converting Enzyme Inhibitors versus Angiotensin II Receptor Blockers in Patients with Coronary Heart Disease: A Nationwide Population-Based Cohort Study in Korea. Pharmacotherapy 2018; 38:1095-1105. [PMID: 30225928 DOI: 10.1002/phar.2181] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
STUDY OBJECTIVE Patients with coronary heart disease (CHD) frequently use the combination of a statin and renin-angiotensin-aldosterone system (RAAS) blocker, an angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II receptor blocker (ARB), to control lipid levels and blood pressure, respectively, and the use of ARBs is increasing in Korean patients. Few studies are available, however, that have compared combination therapy with statin-ACEIs versus statin-ARBs. The objective of this study was to evaluate whether ARBs are associated with a reduced risk of major adverse cardiovascular and cerebrovascular events (MACCEs) compared with ACEIs when used in combination with statins in patients with established CHD. DESIGN Population-based retrospective cohort study. DATA SOURCE Korean National Health Insurance Service-National Sample Cohort database. PATIENTS A total of 6577 adults who started statin-RAAS blocker combination therapy (1870 in the statin-ACEI cohort and 4707 in the statin-ARB cohort) after being diagnosed with CHD between January 2003 and December 2013 were included. Of these, 3676 propensity score-matched patients (1838 in the statin-ACEI cohort and 1838 in the statin-ARB cohort) were included in the final analyses. MEASUREMENTS AND MAIN RESULTS The primary outcome was MACCE (major adverse cardiovascular and cerebrovascular events), a composite of cardiovascular mortality, nonfatal myocardial infarction (MI), ischemic stroke, and revascularization. Incidences and incidence rates of MACCE were calculated to estimate the differences between the two cohorts. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated by using a Cox proportional hazard model. The incidence of MACCE was 19.9% and 14.7%, and incidence rates were 11.7 and 8.1 per 100 person-years in the statin-ACEI and statin-ARB cohorts, respectively. The risk of MACCE was significantly lower in the statin-ARB cohort (adjusted HR 0.69, 95% CI 0.59-0.81). CONCLUSION A MACCE was less likely to occur in patients who received a statin-ARB than in those who received a statin-ACEI. Similar trends were seen in cardiovascular mortality and the occurrence of recurrent MI but not stroke. The availability of statin-ARB fixed-dose combinations may have contributed to the improved outcomes in the statin-ARB cohort by reducing pill burden and improving medication adherence. Further research is warranted to validate our findings and to address whether a particular statin-ARB combination is more effective than other combinations.
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Affiliation(s)
- Jimin Lee
- College of Pharmacy, Ajou University, Suwon, South Korea
| | - Sukhyang Lee
- College of Pharmacy, Ajou University, Suwon, South Korea
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Kim HS, Lee S, Kim JH. Real-world Evidence versus Randomized Controlled Trial: Clinical Research Based on Electronic Medical Records. J Korean Med Sci 2018; 33:e213. [PMID: 30127705 PMCID: PMC6097073 DOI: 10.3346/jkms.2018.33.e213] [Citation(s) in RCA: 215] [Impact Index Per Article: 35.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 05/24/2018] [Indexed: 12/29/2022] Open
Abstract
Real-world evidence (RWE) and randomized control trial (RCT) data are considered mutually complementary. However, compared with RCT, the outcomes of RWE continue to be assigned lower credibility. It must be emphasized that RWE research is a real-world practice that does not need to be executed as RCT research for it to be reliable. The advantages and disadvantages of RWE must be discerned clearly, and then the proper protocol can be planned from the beginning of the research to secure as many samples as possible. Attention must be paid to privacy protection. Moreover, bias can be reduced meaningfully by reducing the number of dropouts through detailed and meticulous data quality management. RCT research, characterized as having the highest reliability, and RWE research, which reflects the actual clinical aspects, can have a mutually supplementary relationship. Indeed, once this is proven, the two could comprise the most powerful evidence-based research method in medicine.
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Affiliation(s)
- Hun-Sung Kim
- Department of Medical Informatics, The Catholic University of Korea College of Medicine, Seoul, Korea
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Korea
| | - Suehyun Lee
- Division of Biomedical Informatics, Systems Biomedical Informatics Research Center, Seoul National University College of Medicine, Seoul, Korea
| | - Ju Han Kim
- Division of Biomedical Informatics, Systems Biomedical Informatics Research Center, Seoul National University College of Medicine, Seoul, Korea
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Choi J, Kim Y, Kim HS, Choi IY, Yu H. Phenotyping of Korean patients with better-than-expected efficacy of moderate-intensity statins using tensor factorization. PLoS One 2018; 13:e0197518. [PMID: 29897980 PMCID: PMC5999101 DOI: 10.1371/journal.pone.0197518] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 05/03/2018] [Indexed: 11/18/2022] Open
Abstract
Several studies have been conducted to evaluate the efficacy of statins in Korean and Asian patients. However, most previous studies only observed the percent reduction in low-density lipoprotein cholesterol (LDL-C) and did not consider the effects of various patient conditions simultaneously, such as abnormal test results, patient demographics, and prescribed drugs before taking a statin. Moreover, the characteristics of the patients whose percent reduction in LDL-C was higher than expected were not provided. Therefore, in this study, we aimed to derive meaningful phenotypes by using tensor factorization to observe the characteristics of the patients whose percent reduction in LDL-C was higher than expected among patients taking moderate-intensity statins. In addition, we used the derived phenotypes to predict how much the LDL-C levels of new patients decreased. We consequently identified eight phenotypes that represented the characteristics of the patients whose percent reduction in LDL-C was higher than expected. Moreover, the latent representations of the derived phenotypes achieved prediction performance similar to that obtained using the raw data. These results demonstrate that the derived phenotypes and latent representations are useful tools for observing the characteristics of patients and predicting LDL-C levels. Additionally, our findings provide direction on how to conduct clinical studies in the future.
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Affiliation(s)
- Jingyun Choi
- Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea
| | - Yejin Kim
- Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea
| | - Hun-Sung Kim
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - In Young Choi
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hwanjo Yu
- Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea
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10
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Hong JY, Kim HS, Choi IY. Pilot Algorithm Designed to Help Early Detection of HMG-CoA Reductase Inhibitor-Induced Hepatotoxicity. Healthc Inform Res 2017; 23:199-207. [PMID: 28875055 PMCID: PMC5572524 DOI: 10.4258/hir.2017.23.3.199] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Revised: 07/02/2017] [Accepted: 07/02/2017] [Indexed: 02/05/2023] Open
Abstract
Objectives To enable early detection of adverse drug reactions (ADRs) in patients using HMG-CoA reductase inhibitors (statins), we developed an algorithm that automatically detects liver injury caused by statins from Electronic Medical Record (EMR) data. We verified the performance of our algorithm through manual ADR assessment and a direct chart review. Methods The subjects in this study were patients who had been prescribed a statin for the first time among outpatients in Seoul St. Mary's Hospital in Korea between January 2009 and December 2012. We extracted basic information about the patients, including laboratory information, underlying disease, diagnosis information, prescription information, and concomitant drugs. We developed an automatic ADR detection algorithm by using EMR data. We validated the results of the algorithm through a chart review. Results We developed the algorithm to assess ADR occurrences based on alanine transaminase (ALT) and alkaline phosphatase (ALP) levels. According to the proposed algorithm, any of these result options could be attained: ADR-free, little association, strong association, and weak association or indeterminable. The results of the ADR assessments obtained using the proposed algorithm showed that the data of 126 patients (1.4% of all 9,241 patients) included suspicious figures, thus indicating the possibility of an ADR. In the EMR chart review for verifying the algorithm, ADRs of 33 patients were not associated with statin use; therefore, the ADR occurrence rate was found to be 1.0% (93/9,241). Therefore, the positive predictive value was calculated to be 73.8% (93/126; 95% confidence interval, 69.2%–77.6%). No differences were observed between statin types (p = 0.472). Conclusions For early detection of statin-induced liver injury, we developed an automatic ADR assessment algorithm. We expect that algorithms that are more reliable can be developed if we conduct supplement clinical studies with a focus on adverse drug effects.
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Affiliation(s)
- Joo Young Hong
- Division of Biomedical Informatics, Systems Biomedical Informatics Research Centre, Seoul National University College of Medicine, Seoul, Korea.,Cipherome Inc., Seoul, Korea
| | - Hun-Sung Kim
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea.,Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - In Young Choi
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
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11
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Kim TM, Kim H, Jeong YJ, Baik SJ, Yang SJ, Lee SH, Cho JH, Lee H, Yim HW, Choi IY, Yoon KH, Kim HS. The differences in the incidence of diabetes mellitus and prediabetes according to the type of HMG-CoA reductase inhibitors prescribed in Korean patients. Pharmacoepidemiol Drug Saf 2017; 26:1156-1163. [PMID: 28556206 DOI: 10.1002/pds.4237] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Revised: 04/05/2017] [Accepted: 04/27/2017] [Indexed: 01/06/2023]
Abstract
BACKGROUND Very few studies conducted in Korea have investigated the relationship between statins and the incidence of diabetes. Therefore, we analyzed the progression from normal blood glucose to prediabetes and then to diabetes mellitus (DM) according to the type, intensity, and dose of statin prescribed. METHODS Data of patients who were first prescribed statins between 2009 and 2011 were extracted from electronic medical records. Patients with normal blood glucose or prediabetes were observed for 4 years after initiation of statin therapy. RESULTS A total of 2890 patients were included in our study and analyzed on the basis of the first statin they were prescribed. The incidence rate of DM in patients with prediabetes was 1.72 times that of patients with normal glucose levels (odds ratio = 1.72, 95% confidence interval = 1.41-2.10, P < .001). Regarding progression from normal blood glucose to prediabetes, the incidence rate of prediabetes was significantly lower in patients prescribed pitavastatin (odds ratio = 0.62, 95% confidence interval = 0.40-0.96, P = .031) compared to that in patients prescribed atorvastatin. Regarding the progression from normal blood glucose or prediabetes to DM, there were no significant differences among all statins. CONCLUSIONS Lower DM incidence in patients prescribed pitavastatin appears to be primarily because of the lower rate of progression from normal blood glucose to prediabetes. These findings indicate that avoiding statins because of DM risk is unjustified and that clinicians should prescribe statins from the appropriate potency group.
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Affiliation(s)
- Tong Min Kim
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyunah Kim
- College of Pharmacy, Sookmyung Women's University, Seoul, Republic of Korea
| | - Yoo Jin Jeong
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sun Jung Baik
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - So Jung Yang
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Seung-Hwan Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary''s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jae-Hyoung Cho
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary''s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyunyong Lee
- Clinical Research Coordinating Center, Catholic Medical Center, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyeon Woo Yim
- Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - In Young Choi
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kun-Ho Yoon
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.,Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary''s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hun-Sung Kim
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.,Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary''s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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12
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Kim HS, Kim H, Jeong YJ, Kim TM, Yang SJ, Baik SJ, Lee SH, Cho JH, Choi IY, Yoon KH. Development of Clinical Data Mart of HMG-CoA Reductase Inhibitor for Varied Clinical Research. Endocrinol Metab (Seoul) 2017; 32:90-98. [PMID: 28256114 PMCID: PMC5368128 DOI: 10.3803/enm.2017.32.1.90] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Revised: 01/02/2017] [Accepted: 01/06/2017] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND The increasing use of electronic medical record (EMR) systems for documenting clinical medical data has led to EMR data being increasingly accessed for clinical trials. In this study, a database of patients who were prescribed statins for the first time was developed using EMR data. A clinical data mart (CDM) was developed for cohort study researchers. METHODS Seoul St. Mary's Hospital implemented a clinical data warehouse (CDW) of data for ~2.8 million patients, 47 million prescription events, and laboratory results for 150 million cases. We developed a research database from a subset of the data on the basis of a study protocol. Data for patients who were prescribed a statin for the first time (between the period from January 1, 2009 to December 31, 2015), including personal data, laboratory data, diagnoses, and medications, were extracted. RESULTS We extracted initial clinical data of statin from a CDW that was established to support clinical studies; the data was refined through a data quality management process. Data for 21,368 patients who were prescribed statins for the first time were extracted. We extracted data every 3 months for a period of 1 year. A total of 17 different statins were extracted. It was found that statins were first prescribed by the endocrinology department in most cases (69%, 14,865/21,368). CONCLUSION Study researchers can use our CDM for statins. Our EMR data for statins is useful for investigating the effectiveness of treatments and exploring new information on statins. Using EMR is advantageous for compiling an adequate study cohort in a short period.
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Affiliation(s)
- Hun Sung Kim
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Hyunah Kim
- College of Pharmacy, Sookmyung Women's University, Seoul, Korea
| | - Yoo Jin Jeong
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Tong Min Kim
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - So Jung Yang
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Sun Jung Baik
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Seung Hwan Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jae Hyoung Cho
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - In Young Choi
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea.
| | - Kun Ho Yoon
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
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13
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Jeong YJ, Kim H, Baik SJ, Kim TM, Yang SJ, Lee SH, Cho JH, Lee H, Yim HW, Choi IY, Yoon KH, Kim HS. Analysis and comparison of the cost-effectiveness of statins according to the baseline low-density lipoprotein cholesterol level in Korea. J Clin Pharm Ther 2017; 42:292-300. [PMID: 28251662 DOI: 10.1111/jcpt.12512] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2016] [Accepted: 02/02/2017] [Indexed: 01/01/2023]
Abstract
WHAT IS KNOWN AND OBJECTIVE There are a few Korean studies on the economics of statins based on reduction in low-density lipoprotein cholesterol (LDL-C) data from other countries. This study aimed to analyse and compare the cost-effectiveness of statins according to the baseline LDL-C level in Korea. METHODS Between January 2009 and December 2015, the data of patients who were prescribed statins for the first time were extracted from electronic medical records. We performed a cost-effectiveness analysis (CEA) based on the LDL-C reduction rate (CEA-RR) and target achievement rate. RESULTS AND DISCUSSION Among high-intensity statins, the CEA-RR value of rosuvastatin (20 mg) was significantly lower than that of atorvastatin (40 mg) at all baseline LDL-C levels, except levels of 160-189 mg/dL. Additionally, at baseline LDL-C levels of 130-159 mg/dL, the CEA-RR value of rosuvastatin (20 mg) was three times lower than that of atorvastatin (40 mg) (9·1 ± 2·5 $/% vs. 31·7 ± 15·0 $/%, P < 0·001). Among moderate-to-low-intensity statins, rosuvastatin (5 mg) showed the lowest CEA-RR value (4·0 ± 0·6 $/%), and the value significantly increased for pitavastatin (2 mg) (8·0 ± 0·6 $/%), atorvastatin (10 mg) (9·5 ± 0·5 $/%), simvastatin (10·8 ± 1·1 $/%) and pravastatin (40 mg) (11·5 ± 0·9 $/%) in order (P < 0·0001). On changing from atorvastatin (10 mg) to atorvastatin (20 mg), the additional yearly cost was 16·0 and additional CEA-RR value was 2·74 $/%. On the other hand, on changing from atorvastatin (10 mg) to rosuvastatin (10 mg), the additional yearly cost was -16·3 and additional CEA-RR value was -1·8 $/%. WHAT IS NEW AND CONCLUSION We successfully compared the cost-effectiveness of statins according to the baseline LDL-C level in Korea. It is expected that our findings will help clinical decision-making with regard to statin prescription, and this will help reduce national medical expenditure.
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Affiliation(s)
- Y J Jeong
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - H Kim
- College of Pharmacy, Sookmyung Women's University, Seoul, Korea
| | - S J Baik
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - T M Kim
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - S J Yang
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - S-H Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - J-H Cho
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - H Lee
- Clinical Research Coordinating Center, Catholic Medical Center, The Catholic University of Korea, Seoul, Korea
| | - H W Yim
- Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - I Y Choi
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - K-H Yoon
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea.,Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - H-S Kim
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea.,Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
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Abstract
More than 13 million Americans are taking statin drugs in order to lower cholesterol levels and thereby avoid potential cardiovascular disease. Home healthcare clinicians are well suited to educate patients about this sometimes-controversial medication class. The purpose of this article is to describe the link between cholesterol and statins, and to provide an overview for healthcare providers including drug actions, indications, and possible adverse effects.
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Affiliation(s)
- Diana R Mager
- Diana R. Mager, DNP, RN-BC, is an Associate Professor, Fairfield University School of Nursing, Fairfield, Connecticut
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