Flat Pattern Peaks of Tacrolimus Absorption and Associated Pharmacogenomic Variants in Kidney Transplantation Recipients

Background@#Tacrolimus is the most commonly used immunosuppressive drug in solid organ transplantation. After administering a conventional twice-daily dose of tacrolimus, peak levels were achieved within the first 1.5 to 2 hours. A group of patients showed different early absorption phase of tacrolimus after kidney transplantation. @*Methods@#Trough(C0 ) and 1.5-hour blood levels (C1.5 ) of tacrolimus were measured in 95 kidney transplantation recipients. Patients with a C1.5 /C0 1.5 were defined as those having flat pattern peaks and as controls, respectively. Transplantation outcomes were compared between the groups. Whole exome sequencing was performed to investigate the genetic susceptibility to flat pattern peaks. @*Results@#Twenty-eight patients showed flat pattern peaks. The mean C1.5 /C0 values were 1.13 ± 0.22 and 3.78 ± 1.25 in the flat pattern peak and control groups, respectively. In multivariate analysis, flat pattern peak was an independent risk factor for biopsy-proven acute rejection (BPAR) and/or borderline change (P = 0.014). Patients having flat pattern peaks showed significantly lower post-transplant 36-month estimated glomerular filtration rate (P = 0.001). Two single nucleotide variants in ABCB1 genes, rs1922242 and rs2235035, were associated with flat pattern peaks (P = 0.019 and P = 0.027, respectively). @*Conclusion@#Both of C1.5 and C0should be measured to distinguish the patients showing unique initial absorption. A C1.5 /C0 ratio lower than 1.5 was associated with an increased risk of BPAR and/or borderline change. Single nucleotide variants s in ABCB1 gene might influence the flat pattern peaks of tacrolimus absorption.

ANNO: A General Annotation Tool for Bilingual Clinical Note Information Extraction / 대한의료정보학회지

Objectives@#This study was conducted to develop a generalizable annotation tool for bilingual complex clinical text annotation, which led to the design and development of a clinical text annotation tool, ANNO. @*Methods@#We designed ANNO to enable human annotators to support the annotation of information in clinical documents efficiently and accurately. First, annotations for different classes (word or phrase types) can be tagged according to the type of word using the dictionary function. In addition, it is possible to evaluate and reconcile differences by comparing annotation results between human annotators. Moreover, if the regular expression set for each class is updated during annotation, it is automatically reflected in the new document. The regular expression set created by human annotators is designed such that a word tagged once is automatically labeled in new documents. @*Results@#Because ANNO is a Docker-based web application, users can use it freely without being subjected to dependency issues. Human annotators can share their annotation markups as regular expression sets with a dictionary structure, and they can cross-check their annotated corpora with each other. The dictionary-based regular expression sharing function, cross-check function for each annotator, and standardized input (Microsoft Excel) and output (extensible markup language [XML]) formats are the main features of ANNO. @*Conclusions@#With the growing need for massively annotated clinical data to support the development of machine learning models, we expect ANNO to be helpful to many researchers.

Different Seasonal Variations of Potassium in Hemodialysis Patients with High Longitudinal Potassium Levels: A Multicenter Cohort Study Using DialysisNet

Purpose@#To determine seasonal variations in serum potassium levels among hemodialysis patients. @*Materials and Methods@#This was a multicenter cohort study of patients whounderwent hemodialysis and were registered in DialysisNet at our four associated general hospitals between January and December 2016. Month-to-month potassium variability was quantified as SD/√{n/(n-1)}, and a non-hierarchical method was used to cluster groups according to potassium trajectories. Seasonal variations in potassium levels were analyzed using a cosinor analysis. @*Results@#The analysis was performed on 279 patients with a mean potassium level of 5.08±0.58 mmol/L. After clustering, 52.3% (n=146) of patients were included in the moderate group (K+ , 4.6±0.4 mmol/L) and 47.7% (n=133) in the high group (K+ , 5.6±0.4 mmol/L). The mean potassium level peaked in January in the moderate group (4.83±0.74 mmol/L) and in August in the high group (5.51±0.70 mmol/L). In the high potassium group, potassium levels were significantly higher in summer than in autumn (p<0.001) and spring (p=0.007). Month-to-month potassium variability was greater in the high group than in the moderate group (0.59±0.19 mmol/L vs. 0.52±0.21 mmol/L, respectively, p=0.012). Compared to patients in the first quartile of potassium variability (≤0.395 mmol/L), those with higher variability (2nd–4th quartiles) were 2.8–4.2 fold more likely to be in the high potassium group. @*Conclusion@#Different seasonal patterns of serum potassium were identified in the moderate and high potassium groups, with potassium levels being significantly higher in the summer season in the high potassium group and in winter for the moderate potassium group.

Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach

BACKGROUND@#Human leukocyte antigen (HLA) typing is important for transplant patients to prevent a severe mismatch reaction, and the result can also support the diagnosis of various disease or prediction of drug side effects. However, such secondary applications of HLA typing results are limited because they are typically provided in free-text format or PDFs on electronic medical records. We here propose a method to convert HLA genotype information stored in an unstructured format into a reusable structured format by extracting serotype/allele information.@*METHODS@#We queried HLA typing reports from the clinical data warehouse of Seoul National University Hospital (SUPPREME) from 2000 to 2018 as a rule-development data set (64,024 reports) and from the most recent year (6,181 reports) as a test set. We used a rule-based natural language approach using a Python regex function to extract the 1) number of patients in the report, 2) clinical characteristics such as indication of the HLA testing, and 3) precise HLA genotypes. The performance of the rules and codes was evaluated by comparison between the extracted results from the test set and a validation set generated by manual curation.@*RESULTS@#Among 11,287 reports for development set and 1,107 for the test set describing HLA typing for a single patient, iterative rule generation developed 124 extracting rules and 8 cleaning rules for HLA genotypes. Application of these rules extracted HLA genotypes with 0.892–0.999 precision and 0.795–0.998 recall for the five HLA genes. The precision and recall of the extracting rules for the number of patients in a report were 0.997 and 0.994 and those for the clinical variable extraction were 0.997 and 0.992, respectively. All extracted HLA alleles and serotypes were transformed according to formal HLA nomenclature by the cleaning rules.@*CONCLUSION@#The rule-based HLA genotype extraction method shows reliable accuracy. We believe that there are significant number of patients who takes profit when this under-used genetic information will be return to them.

Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach

BACKGROUND: Human leukocyte antigen (HLA) typing is important for transplant patients to prevent a severe mismatch reaction, and the result can also support the diagnosis of various disease or prediction of drug side effects. However, such secondary applications of HLA typing results are limited because they are typically provided in free-text format or PDFs on electronic medical records. We here propose a method to convert HLA genotype information stored in an unstructured format into a reusable structured format by extracting serotype/allele information.METHODS: We queried HLA typing reports from the clinical data warehouse of Seoul National University Hospital (SUPPREME) from 2000 to 2018 as a rule-development data set (64,024 reports) and from the most recent year (6,181 reports) as a test set. We used a rule-based natural language approach using a Python regex function to extract the 1) number of patients in the report, 2) clinical characteristics such as indication of the HLA testing, and 3) precise HLA genotypes. The performance of the rules and codes was evaluated by comparison between the extracted results from the test set and a validation set generated by manual curation.RESULTS: Among 11,287 reports for development set and 1,107 for the test set describing HLA typing for a single patient, iterative rule generation developed 124 extracting rules and 8 cleaning rules for HLA genotypes. Application of these rules extracted HLA genotypes with 0.892–0.999 precision and 0.795–0.998 recall for the five HLA genes. The precision and recall of the extracting rules for the number of patients in a report were 0.997 and 0.994 and those for the clinical variable extraction were 0.997 and 0.992, respectively. All extracted HLA alleles and serotypes were transformed according to formal HLA nomenclature by the cleaning rules.CONCLUSION: The rule-based HLA genotype extraction method shows reliable accuracy. We believe that there are significant number of patients who takes profit when this under-used genetic information will be return to them.

Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach

BACKGROUND@#Human leukocyte antigen (HLA) typing is important for transplant patients to prevent a severe mismatch reaction, and the result can also support the diagnosis of various disease or prediction of drug side effects. However, such secondary applications of HLA typing results are limited because they are typically provided in free-text format or PDFs on electronic medical records. We here propose a method to convert HLA genotype information stored in an unstructured format into a reusable structured format by extracting serotype/allele information.@*METHODS@#We queried HLA typing reports from the clinical data warehouse of Seoul National University Hospital (SUPPREME) from 2000 to 2018 as a rule-development data set (64,024 reports) and from the most recent year (6,181 reports) as a test set. We used a rule-based natural language approach using a Python regex function to extract the 1) number of patients in the report, 2) clinical characteristics such as indication of the HLA testing, and 3) precise HLA genotypes. The performance of the rules and codes was evaluated by comparison between the extracted results from the test set and a validation set generated by manual curation.@*RESULTS@#Among 11,287 reports for development set and 1,107 for the test set describing HLA typing for a single patient, iterative rule generation developed 124 extracting rules and 8 cleaning rules for HLA genotypes. Application of these rules extracted HLA genotypes with 0.892–0.999 precision and 0.795–0.998 recall for the five HLA genes. The precision and recall of the extracting rules for the number of patients in a report were 0.997 and 0.994 and those for the clinical variable extraction were 0.997 and 0.992, respectively. All extracted HLA alleles and serotypes were transformed according to formal HLA nomenclature by the cleaning rules.@*CONCLUSION@#The rule-based HLA genotype extraction method shows reliable accuracy. We believe that there are significant number of patients who takes profit when this under-used genetic information will be return to them.

Current Clinical Status of Telehealth in Korea: Categories, Scientific Basis, and Obstacles / 대한의료정보학회지

OBJECTIVES: Through telehealth, medical services have expanded beyond spatial boundaries and are now available in living spaces outside of hospitals. It can also contribute to patient medical knowledge improvement because patients can access their hospital records and data from home. However, concepts of telehealth are rather vague in Korea. METHODS: We refer to several clinical reports to determine the current clinical status of and obstacles to telehealth in Korea. RESULTS: Patients' health conditions are now reported regularly to doctors remotely, and patients can receive varied assistance. Self-improvement based on minute details that are beyond medical staff's reach is another possible benefit that may be realized with the help of a variety of medical equipment (sensors). The feasibility, clinical effect, and cost-benefit of telehealth have been verified by scientific evidence. CONCLUSIONS: Patients will be able to improve their treatment adherence by receiving help from various professionals, such as doctors, nurses, nutritionists, and sports therapists. This means that the actual treatment time per patient will increase as well. Ultimately, this will increase the quality of patients' self-administration of care to impede disease progression and prevent complications.

Correlation between Drug Market Withdrawals and Socioeconomic, Health, and Welfare Indicators Worldwide

The relationship between the number of withdrawn/restricted drugs and socioeconomic, health, and welfare indicators were investigated in a comprehensive review of drug regulation information in the United Nations (UN) countries. A total of of 362 drugs were withdrawn and 248 were restricted during 1950-2010, corresponding to rates of 12.02+/-13.07 and 5.77+/-8.69 (mean+/-SD), respectively, among 94 UN countries. A socioeconomic, health, and welfare analysis was performed for 33 OECD countries for which data were available regarding withdrawn/restricted drugs. The gross domestic product (GDP) per capita, GDP per hour worked, health expenditure per GDP, and elderly population rate were positively correlated with the numbers of withdrawn and restricted drugs (P<0.05), while the out-of-pocket health expenditure payment rate was negatively correlated. The number of restricted drugs was also correlated with the rate of drug-related deaths (P<0.05). The World Bank data cross-validated the findings of 33 OECD countries. The lists of withdrawn/restricted drugs showed markedly poor international agreement between them (Fleiss's kappa=-0.114). Twenty-seven drugs that had been withdrawn internationally by manufacturers are still available in some countries. The wide variation in the numbers of drug withdrawals and restrictions among countries indicates the need to improve drug surveillance systems and regulatory communication networks.

Annotation of Genes Having Candidate Somatic Mutations in Acute Myeloid Leukemia with Whole-Exome Sequencing Using Concept Lattice Analysis

In cancer genome studies, the annotation of newly detected oncogene/tumor suppressor gene candidates is a challenging process. We propose using concept lattice analysis for the annotation and interpretation of genes having candidate somatic mutations in whole-exome sequencing in acute myeloid leukemia (AML). We selected 45 highly mutated genes with whole-exome sequencing in 10 normal matched samples of the AML-M2 subtype. To evaluate these genes, we performed concept lattice analysis and annotated these genes with existing knowledge databases.

ERRATUM: Acknowledgments Correction. Annotation of Genes Having Candidate Somatic Mutations in Acute Myeloid Leukemia with Whole-Exome Sequencing Using Concept Lattice Analysis

The funding acknowledgment in this article was partially omitted as published.

Clinical Characteristics of Patients with Medically Unexplained Chronic Widespread Pain: A Primary Care Center Study / 가정의학회지

BACKGROUND: Chronic widespread pain (CWP) is known as a common symptom of several organic and psychological disorders. Although medically unexplained CWP (MUE) has lots of clinical distress symptoms, there were no distinct symptoms or signs. Therefore, we conducted this study to investigate clinical distress symptoms of MUE distinct from those of medically explained CWP (ME). METHODS: One hundred nine patients with CWP were enrolled in the study. We classified the study subjects into three groups depending on their medical problems associated with CWP: organic group (ORG), psychological group (PSY), and MUE. All subjects were asked to fill out self-report questionnaires consisting of clinical distress scales including the Korean version of the Fibromyalgia Impact Questionnaire (FIQ-K), fatigue scale, depression scale, and stress scale. And physicians examined 18 tender points over their entire body of the subjects. RESULTS: MUE patients had higher FIQ-K and fatigue severity scores than ORG patients (all P < 0.05). The average number of tender points were 11.33 in MUE patients, 6.48 in ORG patients and 5.02 in PSY patients and statistically significant (P < 0.0001). There were no statistically different factors between MUE and PSY patients with exception for the number of tender points. Depressive symptom was the highest in PSY patients but not statistically different from MUE patients. CONCLUSION: MUE patients had higher physical impairments, fatigue severity and more number of tender points than ORG patients, but had no different clinical characteristics from PSY patients except for the number of tender points.

Patterns of Complementary and Alternative Medicine Therapies in Patients with Chronic Fatigue or Pain / 가정의학회지

BACKGROUND: It is well-known that patients with chronic fatigue or frequent pain seek complementary and alternative medicine therapies (CAT) in Western countries. We conducted this study to determine the pattern of CAT use and the factors related to CAT use in patients with chronic fatigue or pain in Korea. METHODS: This was a cross-sectional study. The participants (n = 143) with chronic fatigue or pain completed a self-reported questionnaire including demographic characteristics and lifestyle as well as disease-related and CAT-related items. RESULTS: The frequency of CAT use was 51.0& and 39.2& over the past 10 years and 1 year, respectively. The most common type of CAT used was herbal medicine. The therapeutic effects of the CAT were similar to physicians' prescriptions. CAT were most often used in combination with conventional medicine rather than alone. More than 70.0& of subjects did not consult their physicians for the use of CAT. The duration of illness, severity of fatigue and pain was signifi cantly related to the use of CAT. CONCLUSION: Many patients with chronic fatigue or pain use CAT. Most of these patients do not consult their physicians regarding CAT use.