Extrahepatic Malignancies Are the Leading Cause of Death in Patients with Chronic Hepatitis B without Cirrhosis: A Large Population-Based Cohort Study

(1) Background: Accurate statistics on the causes of death in patients with chronic hepatitis B (CHB) are lacking. We investigated mortality rates and causes of death over time. (2) Methods: Data on patients newly diagnosed with CHB from 2007 to 2010 (cohort 1, n = 223,424) and 2012 to 2015 (cohort 2, n = 177,966) were retrieved from the Korean National Health Insurance Service. Mortality data were obtained from Statistics Korea. The causes of death were classified as liver-related (hepatic decompensation or hepatocellular carcinoma [HCC]) or extrahepatic (cardiovascular-related, cerebrovascular-related, or extrahepatic malignancy-related). (3) Results: Over a 10-year follow-up period of 223,424 patients (cohort 1) with CHB, the overall mortality was 1.54 per 100 person-years. The mortality associated with HCC was the highest (0.65 per 100 person-years), followed by mortality related to extrahepatic malignancies (0.26 per 100 person-years), and cardio/cerebrovascular diseases (0.18 per 100 person-years). In the non-cirrhotic CHB (87.4%), 70% (11,198/15,996) of patients died due to non-liver-related causes over ten years. The 10-year overall mortality was 0.86 per 100 person-years. Among these, mortality due to extrahepatic malignancies had the highest rate (0.23 per 100 person-years), followed by mortality related to HCC (0.20 per 100 person-years), and cardio/cerebrovascular diseases (0.16 per 100 person-years). The 5-year mortality associated with extrahepatic malignancies increased from 0.36 per 100 person-years (cohort 1) to 0.40 per 100 person-years (cohort 2). (4) Conclusions: Mortality related to HCC decreased, whereas mortality related to extrahepatic malignancies increased in the antiviral era. Extrahepatic malignancies were the leading cause of death among patients with CHB without cirrhosis.

Feasibility of Applying the OMOP Common Data Model to Traditional Eastern Asian Medicine Dataset

To evaluate the feasibility of applying the Observational Medical Outcome Partnership (OMOP) Common Data Model (CDM) to databases of traditional East Asian medicine (TEAM), we composed a TEAM dataset and transformed it to the OMOP CDM. We found that some important TEAM information entities could not be transformed to the OMOP CDM (version 6.0) data fields. We suggest to develop data fields and guideline for transforming TEAM data to the OMOP CDM.

Smoking Increases the Risk of Hepatocellular Carcinoma and Cardiovascular Disease in Patients with Metabolic-Associated Fatty Liver Disease

The association of smoking with hepatocellular carcinoma (HCC) or cardiovascular disease (CVD) has been reported, but the study of its relationship with metabolic-associated fatty liver disease (MAFLD) is limited. We aimed to investigate the effect of smoking on the incidence of HCC or CVD in MAFLD patients. Using the Korean nationwide health screening database, we analyzed subjects between 2001 and 2015. A total of 283,088 subjects including 110,863 MAFLD patients and 172,225 controls were analyzed. Smoking status was divided by non-smoker, ex-smoker, or current smoker. In the follow-up period, a total of 2903 (1.0%) subjects developed HCC, and the MAFLD group (1723, 1.6%) had a significantly higher incidence than the control group (1180, 0.7%). In the MAFLD group, current smokers showed significantly higher risk of HCC compared to non-smokers (adjusted HR 1.24, 95% CI 1.08-1.41), whereas the control group did not (adjusted HR 1.07, 95% CI 0.89-1.30). A total of 18,984 (6.7%) patients developed CVD, and the incidence was significantly higher in the MAFLD group (8688, 7.8%) than in the control group (10,296, 6.0%), similar to HCC. The risk of CVD in current smokers increased by 22% compared to non-smokers in the MAFLD group (adjusted HR 1.22, 95% CI 1.15-1.30) and by 21% (adjusted HR 1.21, 95% CI 1.13-1.29) in the control group. Based on sex stratification, men showed increased incidence of both HCC and CVD by smoking, whereas women had only increased risk of CVD. Smoking significantly increases the incidence of HCC and CVD in MAFLD patients; thus, it is highly recommended to quit smoking completely in the population with MAFLD.

Residual risks of comorbidities after parathyroidectomy in a nationwide cohort of patients with primary hyperparathyroidism

PURPOSE

Primary hyperparathyroidism (PHPT) is a common endocrine disorder with increasing incidence, while epidemiologic data in Asian population has been lacking. Therefore, we aimed to identify the incidence, prognosis, and prognostic factors of PHPT patients who underwent parathyroidectomy in Korea.

METHODS

In this retrospective nationwide cohort, patients with PHPT were defined as those with diagnostic codes of PHPT and procedural codes for parathyroidectomy, excluding chronic renal failure or secondary hyperparathyroidism based on National Health Insurance Services database in Korea in 2002-2018. Main primary outcomes were all-cause mortality, cardiovascular, and cerebrovascular events.

RESULTS

A total of 5561 patients were diagnosed with PHPT and had parathyroidectomy. The mean age was 54.5 years, and 71.8% were women. The age-standardized incidence was 10.1/100,000 person-year in 2018, rising from 1.7/100,000 person-year in 2002. During a mean of 5.9 years, history of cardiovascular disease, mood disorder, and genitourinary stone had increased risks of mortality with hazard ratios (HRs) of 1.59 (95% confidence interval [CI] 1.10-2.29), 1.43 (CI 1.14-1.80), and 1.40 (CI 1.09-1.80), respectively. History of hypertension, cerebrovascular disease, diabetes mellitus, and mood disorder were risk factors for cardiovascular events with HRs of 1.42 (CI 1.22-1.66), 1.29 (CI 1.05-1.58), 1.22 (CI 1.07-1.40), and 1.14 (CI 1.00-1.29), respectively. Mood disorder was a significant risk factor for cerebrovascular events (HR 1.30, CI 1.11-1.52).

CONCLUSION

The incidence of PHPT patients who underwent parathyroidectomy has been rising in Korea as reported in other countries. Patients with complications, especially mood disorder, had increased cardiovascular and cerebrovascular events and mortality risks.

Herbal medicine for the treatment of chronic rhinosinusitis: A systematic review and meta-analysis

Objectives: Chronic rhinosinusitis (CRS) is a disease with a high prevalence and a high socioeconomic burden. This study aimed to conduct a comprehensive systematic review to update the evidence on the use of herbal medicine (HM) for CRS treatment.

Methods: A total of 14 electronic databases for randomized controlled trials (RCTs) evaluating the effects of HM on the treatment of CRS were searched for articles published before July 2021. The primary outcome was CRS severity post-treatment, measured with the Visual Analogue Scale (VAS) and Total Effective Rate (TER). The risk of bias of the included studies and the quality of evidence of the main findings were assessed using the Cochrane Collaboration’s risk of bias tool and the Grading of Recommendations, Assessment, Development, and Evaluations tool.

Results: A total of 80 RCTs were included. Compared to placebo, HM significantly improved CRS severity as measured by TER and VAS. When HM was compared with conventional treatment (CT) as monotherapy or adjuvant therapy, CRS severity measured by TER and VAS, quality of life, Lund-Kennedy endoscopy score, Lund-Mackay computed tomography score, and nasal mucociliary function were significantly improved in the HM group. No serious adverse events associated with HM were reported. The risk of bias was generally unclear, and the quality of evidence ranged from moderate to low.

Conclusion: This review found some limited clinical evidence that HM or HM combined with CT may be more effective and safer than CT alone in treating CRS. However, the methodological quality of the included studies was generally low, and the quality of the evidence needs to be improved.

Antifungal activity of streptavidin C1 and C2 against pathogens causing Fusarium wilt

Fusarium wilt is caused by the soil-inhabiting fungus Fusarium oxysporum ff. spp. and is one of the most devastating plant diseases, resulting in losses and decreasing the quality and safety of agricultural crops. We recently reported the structures and biochemical properties of two biotin-binding proteins, streptavidin C1 and C2 (isolated from Streptomyces cinnamonensis strain KPP02129). In the present study, the potential of the biotin-binding proteins as antifungal agent for Fusarium wilt pathogens was investigated using recombinant streptavidin C1 and C2. The minimum inhibitory concentration of streptavidin C2 was found to be 16 µg ml^-1 for inhibiting the mycelial growth of F. oxysporum f.sp. cucumerinum and F. oxysporum f.sp. lycopersici, while that of streptavidin C1 was found to be 64 µg ml^-1 . Compared with the nontreated control soil, the population density of F. oxysporum f.sp. lycopersici in the soil was reduced to 49·5% and 39·6% on treatment with streptavidin C1 (500 µg ml^-1 ) and C2 (500 µg ml^-1 ), respectively. A greenhouse experiment revealed that Fusarium wilt of tomato plants was completely inhibited on soil drenching using a 50-ml culture filtrate of the streptavidin-producing strain KPP02129.

Epidemiology and Comorbidity of Adrenal Cushing Syndrome: A Nationwide Cohort Study

CONTEXT

Adrenal Cushing syndrome (CS) is a major subtype of CS and has a high surgical cure rate. However, only a few studies have investigated the epidemiology and long-term outcomes of adrenal CS.

OBJECTIVE

We aimed to investigate the nationwide epidemiology, long-term prognosis, and postoperative glucocorticoid replacement therapies of adrenal CS in Korea.

DESIGN

Retrospective cohort study.

SETTING

A nationwide claim database.

PATIENTS

Adrenal CS patients who were defined as having undergone adrenalectomy, a diagnosis code of CS, and not having pituitary gland surgery.

MAIN OUTCOME MEASURES

Crude incidence and age-standardized incidence rates, long-term mortality, comorbidities diagnosed preoperatively or developed postoperatively, and the pattern of postoperative glucocorticoid replacement therapy.

RESULTS

From 2002 to 2017, there were a total of 1199 new adrenal CS patients, including 72 patients with adrenocortical carcinoma (malignant adrenal CS), in Korea. The crude and age-standardized incidence rates were 1.51 and 1.27 per million person-years, respectively. The overall standardized mortality ratio was 3.0 (95% confidence interval [CI], 2.4-3.7) for benign adrenal CS and 13.1 (95% CI, 7.6-18.6) for malignant adrenal CS. Adrenal CS patients had a high risk of having coronary artery disease, stroke, metabolic diseases, and depression. A similar proportion of patients were diagnosed with these comorbidities both preoperatively and postoperatively, suggesting a significant residual risk even after adrenalectomy. The median time of postoperative glucocorticoid replacement therapy was 10.1 months, and the major types of glucocorticoids used were prednisolone (66.6%) and hydrocortisone (22.4%).

CONCLUSIONS

Adrenal CS is associated with multiple comorbidities even after treatment, which necessitates meticulous postoperative care.

Liquid crystal filter based tunable transmitter for 25Gps wavelength division multiplexing-passive optical network fronthaul

A novel tunable transmitter structure based on liquid crystal filter, to the best of our knowledge, is presented. The structure is designed for application to 5G fronthaul and supports 25 Gbps dense wavelength division multiplexing (WDM) transmission and tunable range of 35 nm. The design takes into account easy change of operation band over coarse WDM grid. Prototype samples are developed to test feasibility of the design.

Association between use of benzodiazepines and occurrence of acute angle-closure glaucoma in the elderly: A population-based study

OBJECTIVE

Because benzodiazepines (BZDs) can affect pupillae muscles, their use could be a risk factor for acute angle-closure glaucoma (AACG), which is an ophthalmic emergency. However, there is no research evidence for the association between BZDs and AACG, except two case reports. We aimed to investigate whether BZDs increase the risk of AACG in a geriatric population.

METHODS

We performed a case-control study using a geriatric cohort from the National Health Insurance database (2002-2013) in Korea. Case subjects (n = 1117) were patients diagnosed with AACG. Controls, people who have not been diagnosed with AACG, were randomly matched with the case according to age, sex, and index year (n = 4468). To examine the risk of BZD use for AACG, we performed conditional logistic regression analyses with potential confounders including comorbidities and concomitant medication.

RESULTS

The use of BZD within 30 days was not significantly associated with AACG risk (adjusted odds ratio [aOR] = 1.14, 95% confidence interval [CI] = 0.94-1.37). Further analyses showed that, compared with non-use of BZD, new BZD use had a significantly increased risk for the development of AACG (aOR = 1.62, 95% CI = 1.09-2.37). The risk was higher in the new BZD users exposed within 7 days (aOR = 3.09, 95% CI = 1.58-5.88).

CONCLUSION

We found that BZDs increase the risk of AACG at the beginning of its use among the Korean elderly. Clinicians should monitor visual disturbance in the elderly during the early period after prescription of BZD.

The Effects of Natural Daylight on Length of Hospital Stay

BACKGROUND AND PURPOSE

While providing medical services, hospitals generate many data about patients. Such medical data could contribute to better treatments once their associations or patterns have been identified. With properly analyzed medical data, traditional knowledge at an individual level could be further extended to broader populations. This comprehensive study was performed to demonstrate the effectiveness of light using medical data accumulated over 15 years.

METHODS

Patients who were admitted to the window or door side of a six-bedded room were included. Patients admitted to the emergency room and elderly people aged >80 years were excluded. Patients' length of stay was compared per what bed they were in (excluding middle beds). A multiple regression analysis was performed with patients admitted to the window or door side to determine whether the window affected their hospital stay. In addition, a multiple regression analysis was performed after adjusting for confounders by 1:1 matching between the two groups (ie, age, sex, and admitting department).

RESULTS

Participants were 38 788 patients with a bed near the window and 46 233 patients with a bed near the door. Results revealed that patients' length of stay was shorter for those near the window compared with those near the door, which was also true after group matching (33 921 participants in each group).

CONCLUSIONS

Clinical trials that test evidence-based designs of physical environments in wards or hospital rooms are usually difficult to perform. As an alternative strategy, using accumulated electronic medical data, we assessed this key element of hospital design.

Standard-based comprehensive detection of adverse drug reaction signals from nursing statements and laboratory results in electronic health records

Objective. We propose 2 Medical Dictionary for Regulatory Activities–enabled pharmacovigilance algorithms, MetaLAB and MetaNurse, powered by a per-year meta-analysis technique and improved subject sampling strategy.

Matrials and methods. This study developed 2 novel algorithms, MetaLAB for laboratory abnormalities and MetaNurse for standard nursing statements, as significantly improved versions of our previous electronic health record (EHR)–based pharmacovigilance method, called CLEAR. Adverse drug reaction (ADR) signals from 117 laboratory abnormalities and 1357 standard nursing statements for all precautionary drugs (n  = 101) were comprehensively detected and validated against SIDER (Side Effect Resource) by MetaLAB and MetaNurse against 11 817 and 76 457 drug-ADR pairs, respectively.

Results. We demonstrate that MetaLAB (area under the curve, AUC = 0.61 ± 0.18) outperformed CLEAR (AUC = 0.55 ± 0.06) when we applied the same 470 drug-event pairs as the gold standard, as in our previous research. Receiver operating characteristic curves for 101 precautionary terms in the Medical Dictionary for Regulatory Activities Preferred Terms were obtained for MetaLAB and MetaNurse (0.69 ± 0.11; 0.62 ± 0.07), which complemented each other in terms of ADR signal coverage. Novel ADR signals discovered by MetaLAB and MetaNurse were successfully validated against spontaneous reports in the US Food and Drug Administration Adverse Event Reporting System database.

Discussion. The present study demonstrates the symbiosis of laboratory test results and nursing statements for ADR signal detection in terms of their system organ class coverage and performance profiles.

Conclusion. Systematic discovery and evaluation of the wide spectrum of ADR signals using standard-based observational electronic health record data across many institutions will affect drug development and use, as well as postmarketing surveillance and regulation.

Analysis of the number of enlarged pores according to site, age, and sex

BACKGROUND

Increasing the number of enlarged pores causes cosmetic problems. The difference in the number of enlarged pores according to facial site, age, and sex is unclear.

OBJECTIVE

To analyze the distribution of the number of enlarged pores according to facial site, age, and sex.

METHODS AND MATERIALS

We analyzed the number of the enlarged pores and the percentage of wrinkles in the nose, forehead, and cheek from 434 polarized images. The measurement results were analyzed according to site, age, and sex. Relationship between enlarged pore counts and wrinkle severity was also analyzed. The study was conducted by using DermaVision,™ which can take cross-polarization, parallel polarization, and ultraviolet light images.

RESULTS

The enlarged pores of the nose and forehead were more prominent than in the cheeks. Pore counts were increased with age, and the increment was significant between the 30's and 40's. There was no significant difference by gender. Enlarged pore counts were related to wrinkle severity.

CONCLUSIONS

The number of enlarged pores differs depending on body site and increased with age. The enlarged pore counts correlate with wrinkle severity and the correlation varies depending on the body site.

Conversion and Data Quality Assessment of Electronic Health Record Data at a Korean Tertiary Teaching Hospital to a Common Data Model for Distributed Network Research

OBJECTIVES

A distributed research network (DRN) has the advantages of improved statistical power, and it can reveal more significant relationships by increasing sample size. However, differences in data structure constitute a major barrier to integrating data among DRN partners. We describe our experience converting Electronic Health Records (EHR) to the Observational Health Data Sciences and Informatics (OHDSI) Common Data Model (CDM).

METHODS

We transformed the EHR of a hospital into Observational Medical Outcomes Partnership (OMOP) CDM ver. 4.0 used in OHDSI. All EHR codes were mapped and converted into the standard vocabulary of the CDM. All data required by the CDM were extracted, transformed, and loaded (ETL) into the CDM structure. To validate and improve the quality of the transformed dataset, the open-source data characterization program ACHILLES was run on the converted data.

RESULTS

Patient, drug, condition, procedure, and visit data from 2.07 million patients who visited the subject hospital from July 1994 to November 2014 were transformed into the CDM. The transformed dataset was named the AUSOM. ACHILLES revealed 36 errors and 13 warnings in the AUSOM. We reviewed and corrected 28 errors. The summarized results of the AUSOM processed with ACHILLES are available at http://ami.ajou.ac.kr:8080/.

CONCLUSIONS

We successfully converted our EHRs to a CDM and were able to participate as a data partner in an international DRN. Converting local records in this manner will provide various opportunities for researchers and data holders.

New Alert Override Codes for the Drug Utilization Review System Derived from Outpatient Prescription Data from a Tertiary Teaching Hospital in Korea

Objectives

This paper proposes new alert override reason codes that are improvements on existing Drug Utilization Review (DUR) codes based on an analysis of DUR alert override cases in a tertiary medical institution.

Methods

Data were obtained from a tertiary teaching hospital covering the period from April 1, 2012 to January 15, 2013. We analyzed cases in which doctors had used the 11 overlapping prescription codes provided by the Health Insurance Review and Assessment Service (HIRA) or had provided free-text reasons.

Results

We identified 27,955 alert override cases. Among these, 7,772 (27.8%) utilized the HIRA codes, and 20,183 (72.2%) utilized free-text reasons. According to the free-text content analysis, 8,646 cases (42.8%) could be classified using the 11 HIRA codes, and 11,537 (57.2%) could not. In the unclassifiable cases, we identified the need for codes for "prescription relating to operation" and "emergency situations." Two overlapping prescription codes required removal because they were not used. Codes A, C, F, H, I, and J (for drug non-administration cases) explained surrounding situations in too much detail, making differentiation between them difficult. These 6 codes were merged into code J4: "patient was not taking/will not take the medications involved in the DDI." Of the 11 HIRA codes, 6 were merged into a single code, 2 were removed, and 2 were added, yielding 6 alert override codes. We could codify 23,550 (84.2%) alert override cases using these codes.

Conclusions

These new codes will facilitate the use of the drug–drug interactions alert override in the current DUR system. For further study, an appropriate evaluation should be conducted with prescribing clinicians.

A normalization method for combination of laboratory test results from different electronic healthcare databases in a distributed research network

PURPOSE

Distributed research networks (DRNs) afford statistical power by integrating observational data from multiple partners for retrospective studies. However, laboratory test results across care sites are derived using different assays from varying patient populations, making it difficult to simply combine data for analysis. Additionally, existing normalization methods are not suitable for retrospective studies. We normalized laboratory results from different data sources by adjusting for heterogeneous clinico-epidemiologic characteristics of the data and called this the subgroup-adjusted normalization (SAN) method.

METHODS

Subgroup-adjusted normalization renders the means and standard deviations of distributions identical under population structure-adjusted conditions. To evaluate its performance, we compared SAN with existing methods for simulated and real datasets consisting of blood urea nitrogen, serum creatinine, hematocrit, hemoglobin, serum potassium, and total bilirubin. Various clinico-epidemiologic characteristics can be applied together in SAN. For simplicity of comparison, age and gender were used to adjust population heterogeneity in this study.

RESULTS

In simulations, SAN had the lowest standardized difference in means (SDM) and Kolmogorov-Smirnov values for all tests (p < 0.05). In a real dataset, SAN had the lowest SDM and Kolmogorov-Smirnov values for blood urea nitrogen, hematocrit, hemoglobin, and serum potassium, and the lowest SDM for serum creatinine (p < 0.05).

CONCLUSION

Subgroup-adjusted normalization performed better than normalization using other methods. The SAN method is applicable in a DRN environment and should facilitate analysis of data integrated across DRN partners for retrospective observational studies.

A quantitative method for assessment of prescribing patterns using electronic health records

Background

Most available quality indicators for hospitals are represented by simple ratios or proportions, and are limited to specific events. A generalized method that can be applied to diverse clinical events has not been developed. The aim of this study was to develop a simple method of evaluating physicians' prescription patterns for diverse events and their level of awareness of clinical practice guidelines.

Methods and Findings

We developed a quantitative method called Prescription pattern Around Clinical Event (PACE), which is applicable to electronic health records (EHRs). Three discrete prescription patterns (intervention, maintenance, and discontinuation) were determined based on the prescription change index (PCI), which was calculated by means of the increase or decrease in the prescription rate after a clinical event. Hyperkalemia and Clostridium difficile-associated diarrhea (CDAD) were used as example cases. We calculated the PCIs of 10 drugs related to hyperkalemia, categorized them into prescription patterns, and then compared the resulting prescription patterns with the known standards for hyperkalemia treatment. The hyperkalemia knowledge of physicians was estimated using a questionnaire and compared to the prescription pattern. Prescriptions for CDAD were also determined and compared to clinical knowledge. Clinical data of 1698, 348, and 1288 patients were collected from EHR data. The physicians prescribing behaviors for hyperkalemia and CDAD were concordant with the standard knowledge. Prescription patterns were well correlated with individual physicians' knowledge of hyperkalemia (κ = 0.714). Prescribing behaviors according to event severity or clinical condition were plotted as a simple summary graph.

Conclusion

The algorithm successfully assessed the prescribing patterns from the EHR data. The prescription patterns were well correlated with physicians' knowledge. We expect that this algorithm will enable quantification of prescribers' adherence to clinical guidelines and be used to facilitate improved prescribing practices.

Airway management using a supraglottic airway device without endotracheal intubation for positive ventilation of anaesthetized rats

Endotracheal intubation is often necessary for positive pressure ventilation of rats during open thoracic surgery. Since endotracheal intubation in rats is technically difficult and is associated with numerous complications, many techniques using various devices have been described in the scientific literature. In this study, we compared the effectiveness of airway management of a home-made supraglottic airway device (SAD), which is cheap to fabricate and easy to place with that of an endotracheal intubation tube in enflurane-anaesthetized rats. Twenty male Sprague-Dawley rats (200-300 g) were randomly assigned to two equal groups for positive pressure mechanical ventilation using either the SAD or an endotracheal intubation tube. The carotid artery of each rat was cannulated for continuous blood pressure measurements and obtaining blood samples for determination of oxygen tension, carbon dioxide tension, and blood acidity before, during and after SAD placement or endotracheal intubation. Proper placement of the SAD was confirmed by observing chest wall movements that coincided with the operation of the mechanical ventilator. No complications and adverse events were encountered in the rats in which the SAD was placed, during SAD placement and immediate removal, during their mechanical ventilation through the SAD, and one week after SAD removal. From the results of blood gas analyses, we conclude that anaesthetized rats can be successfully ventilated using an SAD for open thoracic surgery.

Monitoring physicians' prescription patterns on electronic health record: the prescription pattern around clinical event (PACE) algorithm

Electronic health records (EHRs) have gained attention as a valuable data source for medical research, as its adoption rate continues to rise. However, no method for the monitoring of physicians' prescription patterns has been established. Since EHR maintain all prescription data as well as clinical events that occur during the care of patients, we hypothesized that a physician's prescription pattern can be monitored from EHR. In this study, we developed a novel algorithm named PACE, Prescription pattern Around Clinical Event. This algorithm analyzes distribution of the prescription of specific drugs around the time of a clinical event. In the proof of concept study, prescription changes with regard to hyperkalemia were well represented by the algorithm, and the observed patterns well correlated with the physician's knowledge on hyperkalemia (Cohen's kappa, 0.457-0.653). We expect that this algorithm can be used to monitor the guideline adherence of physicians.

Comparison of hyperkalemic risk in hospitalized patients treated with different angiotensin receptor blockers: a retrospective cohort study using a Korean clinical research database

BACKGROUND AND AIM

Clinical use of angiotensin II type 1 receptor antagonists (angiotensin receptor blockers [ARBs]) is associated with hyperkalemia as an adverse drug reaction. Although it has significant clinical implications, the incidence and relative risks of hyperkalemia with various ARBs have not yet been fully evaluated. The purpose of this study was to determine the risk of hyperkalemic events in hospitalized patients treated with different ARBs and to compare the risk among them.

METHODS

We constructed a retrospective cohort composed of hospitalized adult patients who took ARBs in a single tertiary teaching hospital between April 2004 and March 2010. We estimated the incidence of hyperkalemia (serum potassium level >5.5 mEq/L) with various ARBs, and then compared the risk between them using a multivariate Cox proportional hazard model based on age, sex, Charlson co-morbidity score, baseline serum potassium, underlying diseases, and concomitant drugs.

RESULTS

We identified 6992 evaluable intervals from 5449 patients treated with one of the seven ARBs during hospitalization over the 71-month study period with 2521.6 patient-months. We found 381 hyperkalemic events (5.4%) during the study period and an overall event rate of 15.1/100 patient-months. Moderate to fatal hyperkalemia was relatively rare (>6.0 mEq/L, 2.1% [moderate]; >6.5 mEq/L, 0.9% [severe]; >7.0 mEq/L, 0.3% [fatal]). After adjustment for covariates, telmisartan showed a lower risk of hyperkalemia (hazard ratio 0.67; 95% confidence interval 0.51, 0.89) compared with all other ARBs.

CONCLUSION

The risk of hyperkalemic events in hospitalized patients treated with different ARBs was defined. Telmisartan showed a relatively lower hyperkalemic risk profile in hospitalized patients compared with other ARBs.

Construction of an open-access QT database for detecting the proarrhythmia potential of marketed drugs: ECG-ViEW

Information about the QT interval from surface electrocardiograms (ECGs) is essential for surveillance of the proarrhythmia potential of marketed drugs. However, ECG records obtained in daily practice cannot be easily used for this purpose without labor-intensive manual effort. This study was aimed at constructing an open-access QT database, the Electrocardiogram Vigilance with Electronic Data Warehouse (ECG-ViEW). This longitudinal observational database contains 710,369 measurements of QT and associated clinical data from 371,401 patients. The de-identified database is freely available at http://www.ecgview.org.

Development of novel breast cancer recurrence prediction model using support vector machine

Purpose

The prediction of breast cancer recurrence is a crucial factor for successful treatment and follow-up planning. The principal objective of this study was to construct a novel prognostic model based on support vector machine (SVM) for the prediction of breast cancer recurrence within 5 years after breast cancer surgery in the Korean population, and to compare the predictive performance of the model with the previously established models.

Methods

Data on 679 patients, who underwent breast cancer surgery between 1994 and 2002, were collected retrospectively from a Korean tertiary teaching hospital. The following variables were selected as independent variables for the prognostic model, by using the established medical knowledge and univariate analysis: histological grade, tumor size, number of metastatic lymph node, estrogen receptor, lymphovascular invasion, local invasion of tumor, and number of tumors. Three prediction algorithms, with each using SVM, artificial neural network and Cox-proportional hazard regression model, were constructed and compared with one another. The resultant and most effective model based on SVM was compared with previously established prognostic models, which included Adjuvant! Online, Nottingham prognostic index (NPI), and St. Gallen guidelines.

Results

The SVM-based prediction model, named 'breast cancer recurrence prediction based on SVM (BCRSVM),' proposed herein outperformed other prognostic models (area under the curve=0.85, 0.71, 0.70, respectively for the BCRSVM, Adjuvant! Online, and NPI). The BCRSVM evidenced substantially high sensitivity (0.89), specificity (0.73), positive predictive values (0.75), and negative predictive values (0.89).

Conclusion

As the selected prognostic factors can be easily obtained in clinical practice, the proposed model might prove useful in the prediction of breast cancer recurrence. The prediction model is freely available in the website (http://ami.ajou.ac.kr/bcr/).

A novel algorithm for detection of adverse drug reaction signals using a hospital electronic medical record database

PURPOSE

Quantitative analytic methods are being increasingly used in postmarketing surveillance. However, currently existing methods are limited to spontaneous reporting data and are inapplicable to hospital electronic medical record (EMR) data. The principal objectives of this study were to propose a novel algorithm for detecting the signals of adverse drug reactions using EMR data focused on laboratory abnormalities after treatment with medication, and to evaluate the potential use of this method as a signal detection tool.

METHODS

We developed an algorithm referred to as the Comparison on Extreme Laboratory Test results, which takes an extreme representative value pair according to the types of laboratory abnormalities on the basis of each patient's medication point. We used 10 years' EMR data from a tertiary teaching hospital, containing 32,033,710 prescriptions and 115,241,147 laboratory tests for 530,829 individual patients. Ten drugs were selected randomly for analysis, and 51 laboratory values were matched. The sensitivity, specificity, positive predictive value, and negative predictive value of the algorithm were calculated.

RESULTS

The mean number of detected laboratory abnormality signals for each drug was 27 (±7.5). The sensitivity, specificity, positive predictive value, and negative predictive value of the algorithm were 64-100%, 22-76%, 22-75%, and 54-100%, respectively.

CONCLUSION

The results of this study demonstrated that the Comparison on Extreme Laboratory Test results algorithm described herein was extremely effective in detecting the signals characteristic of adverse drug reactions. This algorithm can be regarded as a useful signal detection tool, which can be routinely applied to EMR data.