Medication-related incidents in acute care hospitals among different age groups: An analysis of national patient safety report data.

PURPOSE: This study aimed to perform a nationwide analysis of medication errors (MEs) from hospitals using national reporting system data and to compare the ME patterns among different age groups. METHODS: We analyzed medication-related incidents in acute care hospitals reported to the Korean Patient Safety Reporting and Learning System (KOPS), which is a patient safety reporting system, from July 2016 to December 2020. The stages of the medication use process, type of errors, medication class involved in MEs, and degree of harm were analyzed. RESULTS: Among a total of 5071 medication-related incidents, 37.7% (1911 cases) were incidents that caused patient harm and 1.2% caused long-term, permanent, and fatal harm. The proportion of medication-related incidents that resulted in harm was the highest among the <1-year-old age group (67 cases, 51.5%), followed by the elderly (≥ 65 years) (828 cases, 40.9%). The cases leading to patient death were most frequently reported in patients aged ≥65 years. Medication-related incidents occurred mainly in the administration stage (2954 cases, 58.3%), and wrong dose was the most frequently reported ME type. The most prevalent medication class occurring in the 20-64-year age group (256 cases, 11.7%) was 'antibacterials for systemic use', whereas 'contrast media' (236 cases, 11.6%) and 'blood substitutes and perfusion solutions' (98 cases, 19.3%) were the most prevalent drug classes in the ≥65- and <20-year-old age groups, respectively. CONCLUSIONS: It is necessary to establish guidelines for the prevention of medication-related incidents according to the medication use process and patient age group.

Real-world incidence and risk factors of bortezomib-related cardiovascular adverse events in patients with multiple myeloma.

BACKGROUND: Although most studies on the cardiovascular toxicity of proteasome inhibitors have focused on carfilzomib, the risk of cardiotoxicity associated with bortezomib remains controversial. This study aimed to evaluate the incidence and risk factors of cardiovascular adverse events (CVAEs) associated with bortezomib in patients with multiple myeloma in a real-world setting. METHODS: This cross-sectional study included patients who were treated with bortezomib at a tertiary hospital in South Korea. CVAEs, defined as hypertension, arrhythmia, heart failure, myocardial infarction, pulmonary arterial hypertension, angina, and venous thromboembolism, were detected using cardiac markers, ECG, echocardiography, medications, or documentation by clinicians. The patients were observed for at least 6 months and up to 2 years after starting bortezomib administration. RESULTS: Among the 395 patients, 20.8% experienced CVAEs of any grade, and 14.7% experienced severe adverse events. The median onset time for any CVAE was 101.5 days (IQR, 42-182 days), and new-onset/worsened hypertension was the most prevalent CVAE. The risk of CVAEs increased in patients with a body mass index lower than 18.5 (adjusted HR (aHR) 3.50, 95% confidence interval (CI) 1.05-11.72), light chain (1.80, 1.04-3.13), and IgD (4.63, 1.06-20.20) as the multiple myeloma subtype, baseline stroke (4.52, 1.59-12.80), and hypertension (1.99, 1.23-3.23). However, CVAEs did not significantly affect the 2-year overall survival and progression-free survival. CONCLUSION: Approximately 15% of the Korean patients treated with bortezomib experienced severe CVAEs. Thus, patients, especially those with identified risk factors, should be closely monitored for CVAE symptoms during bortezomib treatment.

Development and validation of a medication-based risk prediction model for acute kidney injury in older outpatients.

BACKGROUND: Older adults are at an increased risk of acute kidney injury (AKI), particularly in community settings, often due to medications. Effective prevention hinges on identifying high-risk patients, yet existing models for predicting AKI risk in older outpatients are scarce, particularly those incorporating medication variables. We aimed to develop an AKI risk prediction model that included medication-related variables for older outpatients. METHODS: We constructed a cohort of 2,272,257 outpatients aged ≥65 years using a national claims database. This cohort was split into a development (70%) and validation (30%) groups. Our primary goal was to identify newly diagnosed AKI within one month of cohort entry in an outpatient context. We screened 170 variables and developed a risk prediction model using logistic regression. RESULTS: The final model integrated 12 variables: 2 demographic, 4 comorbid, and 6 medication-related. It showed good performance with acceptable calibration. In the validation cohort, the area under the receiver operating characteristic curve value was 0.720 (95% confidence interval, 0.692-0.748). Sensitivity and specificity were 69.9% and 61.9%, respectively. Notably, the model identified high-risk patients as having a 27-fold increased AKI risk compared with low-risk individuals. CONCLUSION: We have developed a new AKI risk prediction model for older outpatients, incorporating critical medication-related variables with good discrimination. This tool may be useful in identifying and targeting patients who may require interventions to prevent AKI in an outpatient setting.

Development of a claims-based risk-scoring model to predict emergency department visits in older patients receiving anti-neoplastic therapy.

This study developed and validated a risk-scoring model, with a particular emphasis on medication-related factors, to predict emergency department (ED) visits among older Korean adults (aged 65 and older) undergoing anti-neoplastic therapy. Utilizing national claims data, we constructed two cohorts: the development cohort (2016-2018) with 34,642 patients and validation cohort (2019) with 10,902 patients. The model included a comprehensive set of predictors: demographics, cancer type, comorbid conditions, ED visit history, and medication use variables. We employed the least absolute shrinkage and selection operator (LASSO) regression to refine and select the most relevant predictors. Out of 120 predictor variables, 12 were integral to the final model, including seven related to medication use. The model demonstrated acceptable predictive performance in the validation cohort with a C-statistic of 0.76 (95% CI 0.74-0.77), indicating reasonable calibration. This risk-scoring model, after further clinical validation, has the potential to assist healthcare providers in the effective management and care of older patients receiving anti-neoplastic therapy.

Development and validation of a predictive model for persistent opioid use in new opioid analgesic users via a nationwide claims database.

BACKGROUND: Chronic opioid use is associated with problematic opioid use, such as opioid abuse. It is important to develop a prediction model for safe opioid use. In this study, we aimed to develop and validate a risk score model for chronic opioid use in opioid-naïve, noncancer patients, using data from a nationwide database. METHODS: Data from the National Health Insurance Claims Database in the Republic of Korea from 2016 to 2018 were used, and adult, noncancer patients who were started on non-injectable opioid analgesics (NIOAs) were included. The risk score model was developed using the ß coefficient of each variable in the multivariable logistic regression analysis. RESULTS: Overall, 676,676 noncancer patients were started on NIOAs, of which 65,877 (9.7%) were prescribed NIOAs chronically. Age, baseline healthcare utilization, comorbidities, co-medications, and pattern of first NIOA prescription were identified as risk factors for chronic opioid use. The c-static for the performance of our risk score model was 0.754 (95% confidence interval, 0.750-0.758). CONCLUSION: To our knowledge, this is the first tool that can predict chronic opioid use in the Korean population. The model can help physicians examine the risk of chronic opioid use by patients who are started on NIOA.

Development of machine learning algorithms for scaling-up antibiotic stewardship.

BACKGROUND: Antibiotic stewardship programs (ASP) aim to reduce inappropriate use of antibiotics, but their labor-intensive nature impedes their wide adoption. The present study introduces explainable machine learning (ML) models designed to prioritize inpatients who would benefit most from stewardship interventions. METHODS: A cohort of inpatients who received systemic antibiotics and were monitored by a multidisciplinary ASP team at a tertiary hospital in the Republic of Korea was assembled. Data encompassing over 130,000 patient-days and comprising more than 160 features from multiple domains, including prescription records, laboratory, microbiology results, and patient conditions was collected.Outcome labels were generated using medication administration history: discontinuation, switching from intravenous to oral medication (IV to PO), and early or late de-escalation. The models were trained using Extreme Gradient Boosting (XGB) and light Gradient Boosting Machine (LGBM), with SHapley Additive exPlanations (SHAP) analysis used to explain the model's predictions. RESULTS: The models demonstrated strong discrimination when evaluated on a hold-out test set(AUROC - IV to PO: 0.81, Early de-escalation: 0.78, Late de-escalation: 0.72, Discontinue: 0.80). The models identified 41%, 16%, 22%, and 17% more cases requiring discontinuation, IV to PO, early and late de-escalation, respectively, compared to the conventional length of therapy strategy, given that the same number of patients were reviewed by the ASP team. The SHAP results explain how each model makes their predictions, highlighting a unique set of important features that are well-aligned with the clinical intuitions of the ASP team. CONCLUSIONS: The models are expected to improve the efficiency of ASP activities by prioritizing cases that would benefit from different types of ASP interventions along with detailed explanations.

Development and validation of a machine learning-based fall-related injury risk prediction model using nationwide claims database in Korean community-dwelling older population.

BACKGROUND: Falls impact over 25% of older adults annually, making fall prevention a critical public health focus. We aimed to develop and validate a machine learning-based prediction model for serious fall-related injuries (FRIs) among community-dwelling older adults, incorporating various medication factors. METHODS: Utilizing annual national patient sample data, we segmented outpatient older adults without FRIs in the preceding three months into development and validation cohorts based on data from 2018 and 2019, respectively. The outcome of interest was serious FRIs, which we defined operationally as incidents necessitating an emergency department visit or hospital admission, identified by the diagnostic codes of injuries that are likely associated with falls. We developed four machine-learning models (light gradient boosting machine, Catboost, eXtreme Gradient Boosting, and Random forest), along with a logistic regression model as a reference. RESULTS: In both cohorts, FRIs leading to hospitalization/emergency department visits occurred in approximately 2% of patients. After selecting features from initial set of 187, we retained 26, with 15 of them being medication-related. Catboost emerged as the top model, with area under the receiver operating characteristic of 0.700, along with sensitivity and specificity rates around 65%. The high-risk group showed more than threefold greater risk of FRIs than the low-risk group, and model interpretations aligned with clinical intuition. CONCLUSION: We developed and validated an explainable machine-learning model for predicting serious FRIs in community-dwelling older adults. With prospective validation, this model could facilitate targeted fall prevention strategies in primary care or community-pharmacy settings.

Study Protocol for the Evaluation of Multidisciplinary Medication Reconciliation Service in Adult Patients Undergoing Thoracic and Cardiovascular Surgery (The MERITS Study): A Single-Center Controlled before-and-after Study.

Medication reconciliation (MR), which is widely implemented worldwide, aims to improve patient safety to reduce the medication errors during care transition. Despite its widespread use, MR has not yet been implemented in the Republic of Korea, and its effectiveness has not been studied. We aimed to evaluate the impact of a multidisciplinary MR service in older patients undergoing thoracic and cardiovascular surgery. This is a single-center, prospective, controlled, before-and-after study of adult patients taking at least one chronic oral medication. Depending on the period of each patient's participation, they will be allocated to an intervention group or control group. Patients in the intervention group will receive multidisciplinary MR, and those in the control group will receive usual care. The primary outcome is to assess the impact of the MR service on medication discrepancies between the best possible medication history and medication orders at care transition. Secondary outcomes include the incidence rate of medication discrepancies at each transition, the discrepancy rate between the sources of information, the impact of MR on medication appropriateness index score, drug-related problems, 30-day mortality, the emergency department visit rate, readmission rate after discharge, the rate and acceptability of pharmacists' intervention during hospitalization, and patients' satisfaction.

Risk Factors for Emergency Department Presentations after the Initiation of Opioid Analgesics in Non-Cancer Patients in Korea: A Nationwide Study.

Background and Objectives: Opioid use in Korea is lower than in other developed countries. However, recent studies have reported an increase in opioid prescriptions and the number of chronic opioid users. The current status of adverse events (AEs) associated with opioid analgesics in Korea is unclear. This nested case-control study aimed to evaluate the influence of opioid analgesic use patterns on all emergency department (ED) visits and opioid-related ED visits after opioid analgesic initiation using the national claims database. Materials and Methods: Adult non-cancer patients who initiated non-injectable opioid analgesics (NIOA) between January 2017 and June 2018 were included. We defined the case group as patients who visited the ED within six months of opioid initiation, and the control group was selected in a 1:1 ratio using an exact matching method. Results: A total of 97,735 patients (13.58%) visited the ED within six months of NIOA initiation. Nearly 32% of cases were linked to opioid-related AEs. The most frequent AEs were falls and fractures (61.27%). After adjusting for covariates, opioid initiation at the ED was associated with all-cause or opioid-related ED visits (adjusted odds ratio (aOR) = 3.19, 95% confidence interval (CI) = 3.09-3.29; aOR = 3.82, 95% CI = 3.62-4.04, respectively). Chronic NIOA use was associated with all-cause and opioid-related ED visits (aOR = 1.32, 95% CI = 1.23-1.40; aOR = 1.56, 95% CI = 1.39-1.76, respectively). Conclusion: This study found that 13% of non-cancer patients visited the ED within six months of NIOA initiation. In addition, the NIOA use pattern was significantly associated with all-cause and opioid-related ED visits.

Derivation and validation of a risk prediction score for nonsteroidal anti-inflammatory drug-related serious gastrointestinal complications in the elderly.

AIMS: Few studies have quantified the impact of risk factors on GI complications in elderly nonsteroidal anti-inflammatory drug (NSAID) users. This study aimed to develop and validate a risk prediction score for severe GI complications to identify high-risk elderly patients using NSAID. METHODS: We used the following two Korean claims datasets: customized data with an enrolment period 2016-2017 for model development, and the sample data in 2019 for external validation. We conducted a nested case-control study for model development and validation. NSAID users were identified as the elderly (≥65 years) who received NSAIDs for more than 30 days. Serious GI complications were defined as hospitalizations or emergency department visits, with a main diagnosis of GI bleeding or perforation. We applied the logistic least absolute shrinkage and selection operator (LASSO) regression model for variable selection and model fitting. RESULTS: We identified 8176 cases and 81 760 controls with a 1:10 matched follow-up period in the derivation cohort. In the external validation cohort, we identified 372 cases from 254 551 patients. The risk predictors were high-dose NSAIDs, nonselective NSAID, complicated GI ulcer history, male sex, concomitant gastroprotective agents, relevant co-medications, severe renal disease and cirrhosis. Area under the receiver operating characteristic curve was 0.79 (95% confidence interval, 0.77-0.81) in the external validation dataset. CONCLUSIONS: The prediction model may be a useful tool for reducing the risk of serious GI complications by identifying high-risk elderly patients.

Analysis of Medication Errors Reported by Community Pharmacists in the Republic of Korea: A Cross-Sectional Study.

Background and objectives: We aimed to describe medication-related incidents or medication errors (MEs) reported by community pharmacists and analyze the prevalent medications involved. Materials and Methods: We extracted ME reports from databases comprising patient safety incidents reported to the Korean Pharmaceutical Association between January 2013 and June 2021. Medications were analyzed according to the second (therapeutic subgroup) and fifth (chemical substance) levels of the Anatomical Therapeutic Chemical classification. Results: A total of 9046 MEs were identified, most of which were near miss reports (88.3%). Among the errors that reached the patients (521 cases), harmful incidents accounted for 76.8%. Most MEs occurred during prescription (89.5%), while harmful MEs occurred mainly during dispensing (73.3%). In the prescription step, wrong drugs (44.8%), dosing errors (27.0%), and wrong durations (14.0%) were common. Anti-inflammatory and anti-rheumatic products (M01), drugs for acid-related disorders (A02), and antihistamines for systemic use (R06) were the most frequently reported medication classes involved. Harmful incidents were most common for dosing errors (31.0%) and wrong drugs (26.8%) and were common with warfarin, levothyroxine, and glimepiride. Conclusions: The MEs reported by community pharmacists were mainly prescribing errors, most of which were rectified before reaching patients. The prevalent medications involved in harmful errors include anti-diabetic, anti-thrombotic, and anti-inflammatory agents.

Trends in potentially inappropriate opioid prescribing and associated risk factors among Korean noncancer patients prescribed non-injectable opioid analgesics.

Introduction: The aim of this study was to investigate trends in the prevalence of potentially inappropriate opioid prescribing (PIOP) and identify potential risk factors among Korean noncancer patients. Methods: We conducted a cross-sectional study of annual national patient sample data from the Korean Health Insurance Review and Assessment Service (HIRA-NPS) for the period 2012-2018. Noncancer patients who were prescribed non-injectable opioid analgesics (NIOAs) at least once were included. The proportion of patients with at least one PIOP in terms of concurrent use of benzodiazepines or gabapentinoids, substance use disorder, treatment duration, and dosage was evaluated. Multivariable logistic regression was performed to identify the risk factors associated with PIOP. Results: Of the 9,772,503 noncancer patients, 1,583,444 (16.2%) were prescribed NIOAs at least once. Among them, 15.7% were exposed to PIOP, and the prevalence was much higher (31.6%) in the elderly group (age: ⩾65 years). The prevalence of PIOP increased 1.1-fold over 7 years (14.8-16.8%) among the total NIOA users and was more pronounced in non-tramadol NIOA users (a 1.5-fold increase, from 13.2% to 19.4%). Multivariable logistic regression indicated that older age, beneficiaries of medical aid or national meritorious service, exposure to polypharmacy, psychological disorder, chronic pain indication, and concomitant sedative use were independently associated with higher odds of PIOP. Discussion and Conclusion: We found that the prevalence of PIOP was 15.7% among Korean noncancer patients, and it increased over the 7-year study period. This increasing trend is alarming because it was more drastic with non-tramadol NIOAs compared with that with tramadol. Several patient-level risk factors associated with PIOP would be useful in targeted management strategies for the safe use of opioids. Plain Language Summary: Potentially inappropriate opioid prescribing and related risk factors among noncancer patients prescribed non-injectable opioids in Korea In Korea, the prevalence of non-injectable opioid analgesic (NIOA) use in noncancer patients steadily increased from 15.3% in 2012 to 17.1% in 2018.Also, the prevalence of potentially inappropriate opioid prescribing (PIOP) increased from 14.8% in 2012 to 16.8% in 2018.The following factors were associated with a markedly increased risk of PIOP: age, beneficiaries of medical aid or national meritorious service, polypharmacy, psychological disorder, chronic pain, and concomitant medications.

Development and validation of a risk-score model for opioid overdose using a national claims database.

Opioid overdose can be serious adverse effects of opioid analgesics. Thus, several strategies to mitigate risk and reduce the harm of opioid overdose have been developed. However, despite a marked increase in opioid analgesic consumption in Korea, there have been no tools predicting the risk of opioid overdose in the Korean population. Using the national claims database of the Korean population, we identified patients who were incidentally prescribed non-injectable opioid analgesic (NIOA) at least once from 2017 to 2018 (N = 1,752,380). Among them, 866 cases of opioid overdose occurred, and per case, four controls were selected. Patients were randomly allocated to the development (80%) and validation (20%) cohort. Thirteen predictive variables were selected via logistic regression modelling, and a risk-score was assigned for each predictor. Our model showed good performance with c-statistics of 0.84 in the validation cohort. The developed risk score model is the first tool to identify high-risk patients for opioid overdose in Korea. It is expected to be applicable in the clinical setting and useful as a national level surveillance tool due to the easily calculable and identifiable predictors available from the claims database.

Rebamipide as a Potential Alternative Gastroprotective Agent to Proton Pump Inhibitor in Elderly Chronic Nonsteroidal Anti-Inflammatory Drug Users without Risk Factors.

Purpose: The use of proton pump inhibitors (PPI) is recommended to prevent nonsteroidal anti-inflammatory drug (NSAID)-induced gastrointestinal (GI) complications. The incidence of several adverse effects during the long-term use of PPI prompts the search for other alternatives. Limited studies have evaluated the efficacy of rebamipide, a widely used mucoprotective drug, as a gastroprotective agent (GPA) compared to PPI, focusing on the elderly chronic NSAID users, nor with GI risk stratification. We aimed to determine the population who would get benefit from the use of rebamipide as an alternative to PPI to prevent traditional nonsteroidal anti-inflammatory drug (tNSAID)-associated GI complications. Patients and Methods: We identified 41,889 and 35,708 elderly chronic tNSAID users with PPI and rebamipide co-therapy, respectively, from the national claims database. Outcome was defined as hospitalization or emergency department visits due to serious GI complications. Propensity score-matched cohorts were constructed and compared within risk strata. Results: In high and moderate risk groups with two risk factors, rebamipide showed a higher risk of serious GI complication compared to PPI (aHR 2.63, 95% CI 1.24-5.59 and aHR 2.42, 95% CI 1.21-4.83, respectively). However, in elderly patients without risk factors, there was no significant difference in the risk of serious GI complications between PPI and rebamipide (aHR 0.69, 95% CI 0.27-1.76). Conclusion: This study suggested that rebamipide can be considered as an alternative to PPI in elderly chronic tNSAID users without risk factors. However, elderly patients with other risk factors should use PPI rather than rebamipide. Therefore, the presence of GI risk factors needs to be evaluated in elderly chronic tNSAID users to prescribe the most suitable GPA in clinical practice.

Impact of Preventive Strategies on Gastrointestinal Complications in Elderly Patients on Concomitant Use of Oral Anticoagulants and Nonsteroidal Anti-Inflammatory Drugs: A Nationwide Cohort Study.

INTRODUCTION: Despite growing evidence showing an increased risk of concomitant use of nonsteroidal anti-inflammatory drugs (NSAIDs) and anticoagulants, few studies have investigated whether proton pump inhibitors can prevent gastrointestinal (GI) complications in patients receiving both NSAIDs and anticoagulants. OBJECTIVE: We aimed to evaluate the risk of serious GI complications and the impact of GI preventive strategies on the concomitant use of NSAIDs and anticoagulants. METHODS: Our nationwide cohort study using Korea's claims data included elderly patients (aged ≥ 65 years) who started anticoagulants and NSAIDs from 2016 to 2017. The outcome was serious GI complications defined as hospitalization or emergency department visits with GI bleeding or perforation. A Cox regression analysis was performed using time-dependent variables and propensity score matching. RESULTS: In total, 92,379 patients were identified. Compared with non-prophylaxis, proton pump inhibitors and selective cyclooxygenase-2 inhibitors were associated with a 64% [adjusted hazard ratio, 0.36 (95% confidence interval 0.25-0.53)] and 74% [adjusted hazard ratio, 0.26 (95% confidence interval 0.19-0.36)] lower risk of serious GI complications, respectively. Cyclooxygenase-2 inhibitor use was not different from the use of non-selective NSAIDs with proton pump inhibitors for the prevention of serious GI complications. H2-receptor antagonists did not reduce the risk of serious GI complications compared with non-prophylaxis during concomitant non-selective NSAID and anticoagulant therapy. CONCLUSIONS: Proton pump inhibitors or cyclooxygenase-2 inhibitors used as GI preventive strategies did not completely eliminate but lowered the risk of serious GI complications among elderly patients receiving both NSAIDs and anticoagulants.

Risk factors of chronic opioid use after surgical procedures in noncancer patients: A nationwide case-control study.

BACKGROUND: Surgery is an indication for opioid prescription in noncancer patients, and chronic use of opioids is associated with overdose and abuse. OBJECTIVES: We aimed to evaluate the prevalence and risk factors associated with chronic opioid use (COU) following surgery among noncancer patients. DESIGN: A nationwide case-control study. SETTING: Retrospective analysis of the annual national patient sample data from 2012 to 2018 in South Korea. PATIENTS: Adults without cancer who had undergone surgery and received noninjectable opioids during hospital stay. MAIN OUTCOME MEASURES: COU during 3 months following surgery. RESULTS: A total of 15 543 participants were included, and the prevalence overall and in opioid-naïve users was 8.1 and 5.7%, respectively. Prior exposure patterns of opioids [intermittent user, adjusted odds ratio (aOR) 2.35; 95% CI, 2.00 to 2.77, and continuous user, aOR 8.58; 95% CI, 6.54 to 11.24] and concomitant use of benzodiazepine (in continuous user, aOR 18.60; 95% CI 11.70 to 29.55) were strongly associated with COU compared with naïve users. Morphine milligram equivalent, type of opioid strength at discharge and prescription of nonopioid analgesics at discharge were also associated with COU. Compared with minor surgery, knee (aOR 1.49; 95% CI 1.17 to 1.89), spine (aOR 1.65; 95% CI 1.33 to 2.06) and shoulder (aOR 2.54; 95% CI 1.97 to 3.27) procedures showed a significantly positive association with COU. Sensitivity analysis in opioid-naïve patients showed similar results. CONCLUSION: About 8.1% of noncancer patients who had undergone surgery and were prescribed noninjectable opioids became chronic opioid users in Korea. Identified risk factors could be used to derive strategies for safe opioid use in noncancer patients in the future.

Age- and sex-specific risk of urogenital infections in patients with type 2 diabetes treated with sodium-glucose co-transporter 2 inhibitors: A population-based self-controlled case-series study.

This study aimed to investigate the age- and sex-specific risk of urogenital infections in patients with type 2 diabetes mellitus (T2DM) treated with sodium-glucose co-transporter 2 (SGLT2) inhibitors. A self-controlled case series was conducted using annual national patient sample datasets from 2016 and 2017. Patients who were treated with SGLT2 inhibitors and who received antimicrobials for urogenital infections were included in the study. The incidence rate ratio (IRR) of urogenital infections during SGLT2 inhibitor exposure were compared with those in the non-exposure period. A total of 2,949 patients were included in the analysis, and 71.2% of the patients were women aged ≥ 50 years. Stratified analysis by age and sex showed that only women ≥ 50 years showed a significant increase in the risk of urinary tract infections (UTIs) (IRR 1.25, 95% CI 1.14-1.37) and genital infections (IRR 1.44, 95% CI 1.28-1.62). The highest risk of UTI risk was observed 8-14 days after initiating SGLT2 inhibitor therapy (IRR 1.49, 95% CI 1.07-2.08), and after 15-28 days for genital infections (IRR 2.11, 95% CI 1.66-2.67) in women ≥ 50. SGLT2 inhibitors increase the risk of urogenital infections in T2DM patients, especially in women aged ≥ 50 years. Monitoring of urogenital infections in women aged ≥ 50 years, especially during the first month after starting SGLT2 inhibitors, is recommended.

Interrupted Time Series Analysis of Changes in Zolpidem Use Due to Media Broadcasts.

Media has become a major source of information on health and plays a role in the decision-making process on health topics. We aimed to evaluate the association between zolpidem use and media broadcasts that reported the suicide risk. We obtained the data of adult outpatients who have been prescribed zolpidem or other hypnotics from the National Patient Sample database (2015-2017). We evaluated the change in zolpidem or other hypnotic prescription trends based on the prescription rate and average daily prescribed dose before and after July 2016, using interrupted time series analysis. A total of 129,787 adult patients had at least one zolpidem prescription in 3 years. The prescription rate of zolpidem after the broadcast decreased significantly by 0.178% (95% confidence interval (CI): -0.214, -0.142), whereas that of other hypnotic users did not differ from that before the broadcast (-0.020%, 95% CI: -0.088, 0.047). However, the trends in the prescription rate before and after the broadcast did not differ for zolpidem and other hypnotics. Broadcasting medication safety through major public media could have an effect on medication use. After broadcasting about the suicide risk of zolpidem, its overall prescription rate decreased immediately, but the trend was not changed.