The Impact of Real-Time Documentation of In-Hospital Medication Changes on Preventing Undocumented Discrepancies at Discharge and Improving Physician-Pharmacist Communication: A Retrospective Cohort Study and Survey.

Background: Transitional medication safety is crucial, as miscommunication about medication changes can lead to significant risks. Unclear or incomplete documentation during care transitions can result in outdated or incorrect medication lists at discharge, potentially causing medication errors, adverse drug events, and inadequate patient education. These issues are exacerbated by extended hospital stays and multiple care events, making accurate medication recall challenging at discharge. Objective: Thus, we aimed to investigate how real-time documentation of in-hospital medication changes prevents undocumented medication changes at discharge and improves physician-pharmacist communication. Methods: We conducted a retrospective cohort study in a tertiary hospital. Two pharmacists reviewed medical records of patients admitted to the acute medical unit from April to June 2020. In-hospital medication discrepancies were determined by comparing preadmission and hospitalization medication lists and it was verified whether the physician's intent of medication changes was clarified by documentation. By a documentation rate of medication changes of 100% and <100%, respectively, fully documented (FD) and partially documented (PD) groups were defined. Any undocumented medication changes at discharge were considered a "documentation error at discharge". Pharmacists' survey was conducted to assess the impact of appropriate documentation on the pharmacists. Results: After reviewing 400 medication records, patients were categorized into FD (61.3%) and PD (38.8%) groups. Documentation errors at discharge were significantly higher in the PD than in the FD group. Factors associated with documentation errors at discharge included belonging to the PD group, discharge from a non-hospitalist-managed ward, and having three or more intentional discrepancies. Pharmacists showed favorable attitudes towards physician's documentation. Conclusion: Appropriate documentation of in-hospital medication changes, facilitated by free-text communication, significantly decreased documentation errors at discharge. This analysis underlines the importance of communication between pharmacists and hospitalists in improving patient safety during transitions of care.

During transitions of care, communication failures among healthcare professionals can lead to medication errors. Therefore, effective sharing of information is essential, especially when intentional changes in prescription orders are made. Documenting medication changes facilitates real-time communication, potentially improving medication reconciliation and reducing discrepancies. However, inadequate documentation of medication changes is common in clinical practice. This retrospective cohort study underlines the importance of real-time documentation of in-hospital medication changes. There was a significant reduction in documentation errors at discharge in fully documented group, where real-time documentation of medication changes was more prevalent. Pharmacists showed favorable attitudes toward the physician's real-time documenting of medication changes because it provided valuable information on understanding the physician's intent and improving communication and also saved time for pharmacists. This study concludes that physicians' documentation on medication changes may reduce documentation errors at discharge, meaning that proper documentation of medication changes could enhance patient safety through effective communication.

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 of a multidisciplinary medication management program in nursing homes: protocol for a randomized controlled trial : Multidisciplinary medication management in nursing homes.

BACKGROUND: Polypharmacy and the use of potentially inappropriate medications are common among nursing home residents and are associated with negative outcomes. Although deprescribing has been proposed as a way to curtail these problems, the best way to implement multidisciplinary comprehensive medication review and deprescribing and its real impact in specific high-risk populations, such as nursing home residents, is still unclear. This multicenter randomized controlled clinical trial aims to assess the effects of a multidisciplinary mediation management program on medication use and health problems. METHODS: A total of 1,672 residents aged ≥ 65 years from 22 nursing homes in South Korea who meet the targeted criteria, such as the use of ≥ 10 medications, are eligible to participate. The experimental group will receive a comprehensive medication review, deprescription, and multidisciplinary case conference with the help of platform. Outcomes will be measured at baseline, at the end of the intervention, as well as at 3, 6, 9, and 12 months after the end of the intervention. The primary endpoints will be the rate of adverse drug events, number of potentially inappropriate medications/potentially inappropriate medication users/two or more central nervous system drug/ central nervous system drug users, delirium, emergency department visits, hospitalization, and falls. The secondary endpoint will be the number of medications taken and polypharmacy users. DISCUSSION: Our trial design is unique in that it aims to introduce a structured operationalized clinical program focused on reducing polypharmacy and potentially inappropriate medications in a nursing home setting with large samples. TRIAL REGISTRATION: Ethical approval was granted by the public institutional review board of the Ministry of Health and Welfare (2022-1092-009). The study is also registered with the Clinical Research Information Service (Identifier: KCT0008157, Development and evaluation of a multidisciplinary medication management program in long-term care facility residents Status: Approved First Submitted Date: 2023/01/18 Registered Date: 2023/02/03 Last Updated Date: 2023/01/18 (nih.go.kr) https://cris.nih.go.kr/ ), which includes all items from the World Health Organization Trial Registration Dataset.

Inconsistency in steroid use as antiemetics in clinical trial protocols involving immune checkpoint inhibitors combined with chemotherapy.

OBJECTIVES: This study aims to investigate the use of steroids as antiemetics in clinical trials involving immune checkpoint inhibitors with chemotherapy. METHODS: Focusing on phase III trials registered before August 2023, it evaluated the consistency of steroid use guidelines. RESULTS: Out of 3452 trials screened, 44 were selected for in-depth review. The findings indicate a considerable variation: 13 trials did not specify the use of antiemetics, while 31 provided criteria for antiemetics, with 13 conforming to local standards, six to international guidelines, and five allowing either. Seven trials recommended effective antiemetics without detailed criteria. This inconsistency led to a range of steroid dosages, with only 11 trials advocating for minimizing or avoiding steroids for antiemetic purposes. CONCLUSION: The research highlights the lack of uniformity in antiemetic steroid use in trials, reflecting diverse clinical practices and underscoring the need for further research to understand the implications on treatment outcomes.

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.

Contemporary Patterns and Underlying Causes of Vitrectomy in Pediatric and Adolescent Patients: A Nationwide, Population-Based Analysis.

PURPOSE: We determined the incidence, etiology, and longitudinal trends of vitreoretinal diseases necessitating pars plana vitrectomy (PPV) in the pediatric and adolescent population. DESIGN: Nationwide, population-based cohort study. METHODS: This study utilized data extracted from the Korean National Health Claims database spanning from 2009 to 2020. All pediatric and adolescent patients (under 20 years of age) who underwent PPV across the Korean population were included. The cumulative incidence of PPV was estimated from 2009 to 2020, with 2009 to 2011 as the washout period. The annual trends of PPV incidence, the proportion of each etiology, and comorbidity were estimated based on sex and specific age groups. RESULTS: In total, 1913 patients, including 83 infants, 746 pediatric patients, and 1084 adolescents, were newly identified as having undergone PPV surgery. The cumulative incidence of PPV surgery per 100,000 individuals was 21.42 (95% CI, 21.41-21.43). The rate of PPV was 2.4 times higher for males than females, and the rate of trauma as a comorbidity was also higher for males than females (13.1% vs 4.8%). Among males aged 5 years and older, the incidence of PPV nearly halved from 2011 to 2020. Among the primary etiologies, ROP had the highest rate (72%) in infants (under 1 year), while RD was most common (63%) in individuals aged 5 to 19 years. Myopia was present in 30.3% of patients, and atopic dermatitis was present in 31.8% of all patients. CONCLUSION: The primary etiologies underlying the need for PPV in the pediatric and adolescent populations vary by sex and age group. The incidence of PPV continues to decline in the adolescent population. Therefore, tailored patient education and age-specific etiological examination are recommended.

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.

Risk of non-thyroidal autoimmune diseases in patients with Graves' disease: a nationwide retrospective cohort study.

OBJECTIVE: Graves' disease (GD) is a major autoimmune thyroid disorder and associated with non-thyroidal autoimmune disease (NTAD). We aimed to investigate the risk of NTAD in patients with GD compared with age- and sex-matched controls and to evaluate whether the risk differs between individuals with or without Graves' ophthalmopathy (GO). METHODS: This was a retrospective cohort study using data from the Korean National Health Claims database. We included 77 401 patients with GD (2,310 with GO) and 77 401 age- and sex-matched controls. Risk of NTAD were compared between the entire cohort and within the GD cohort. RESULTS: During a mean follow-up period of 9 years, NTAD developed in 12 341 (16.1%) patients in the GD cohort. Risk for systemic lupus erythematosus (SLE) [adjusted hazard ratio (aHR):1.15, 95% confidence interval (CI): 1.02-1.29], vitiligo (aHR: 1.24, 95% CI: 1.10-1.40), and alopecia areata (aHR: 1.11, 95% CI: 1.10-1.40) were higher in the GD cohort than in the control cohort. In the GD cohort, risk for SLE (aHR: 1.60, 95% CI: 1.11-2.33), Sjogren's syndrome (aHR: 1.89, 95% CI: 1.30-2.74), and ankylosing spondylitis (aHR: 1.53, 95% CI: 1.08-2.17) were higher in the GO group than in the non-GO group. CONCLUSION: This study demonstrated an increased risk of SLE, vitiligo and alopecia areata in patient with GD. In the GD cohort, patients with GO had an increased risk of SLE, Sjogren's syndrome and ankylosing spondylitis. These findings suggest that importance of implementing a strategy for early detection of NTAD based on the presence of GO.

Increased risk of incident gout in patients with hyperthyroidism: a nationwide retrospective cohort study.

Previous studies have reported that thyroid dysfunction is associated with increased serum uric acid levels; however, the relationship between hyperthyroidism and incidence of clinical manifestations of gout has not been fully investigated. Therefore, this study aimed to longitudinally investigate the risk of gout in patients with hyperthyroidism. This nationwide retrospective cohort study used data from the Korean National Health Claims Database. We included 76,494 patients with hyperthyroidism and 76,542 age- and sex-matched controls. A Cox proportional hazard regression model was used to adjust for potential confounders and estimate the risk of incident gout in patients with hyperthyroidism. During a mean follow-up of 9 years, incident gout developed in 3,655 (4.8%) patients with hyperthyroidism and 3251 (4.2%) controls. Hyperthyroidism was significantly associated with increased risk of incident gout [adjusted hazard ratio (HR), 1.12; 95% confidence interval (CI) 1.07-1.18], independent of baseline metabolic profiles. The median time from the diagnosis of hyperthyroidism to the development of gout was 6 years. When stratified by age and sex, the risk of gout was still significant in the < 50-year age group (HR: 1.2, 95% CI 1.12-1.29) and males (HR: 1.21, 95% CI 1.12-1.30), but not in the older age group (> 50 years) and females. Hyperthyroidism is an important risk factor for incident gout, particularly in younger age groups (< 50 years) and males. Our results highlight the importance of continuous screening for gout in patients with hyperthyroidism.

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.

Increased Risk of Optic Neuritis in Patients With Fibromyalgia: Nationwide Population-Based Cohort Study in South Korea.

PURPOSE: To estimate the risk of incidence of optic neuritis and identify the high-risk group among patients with fibromyalgia (FM). DESIGN: Population-based cohort study. METHODS: A nationwide, population-based study was conducted using data from the Korean National Health Claims database from 2012 to 2021. This study included all the patients with FM from the entire South Korean population aged 20-79 years (FM group). Moreover, those with pain but not diagnosed with FM were considered as the non-FM group. A cohort was established by classifying it into the FM and non-FM groups during the recruitment period. A log-rank analysis was used to compare the risk of optic neuritis incidence between the FM group and non-FM group. Cox proportional hazards regression analysis was performed to calculate the adjusted hazard ratio (HR). The cohort was analyzed by stratifying according to age and sex. RESULTS: The FM and non-FM groups included 479,892 and 479,892 participants, respectively. The incidence rate of optic neuritis was 35.65/100,000 person-years in the FM group; the HR was significantly higher in the FM group than in the non-FM group (HR 2.11, 95% CI 1.84-2.41; P < .001). The mean interval between the onset of FM and incident optic neuritis was 2.4 ± 1.8 years. The risk increased significantly in men aged 60-79 years (HR 3.37, 95% CI 2.54-4.48) and in women aged 20-39 years (HR 2.07, 95% CI 1.38-3.22). CONCLUSION: We quantified the risk of optic neuritis through a long-term follow-up, which could contribute to understanding the pathophysiology and estimating the general health care burden associated with FM in a practical setting. Great attention should be paid to its risk in older men and younger women.

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.

Consultation-Based Deprescribing Service to Optimize Palliative Care for Terminal Cancer Patients.

(1) Background: A pharmacist-led deprescribing service previously developed within the Consultation-Based Palliative Care Team (CB-PCT) was implemented for terminal cancer patients. (2) Objective: To evaluate the clinical outcomes of the developed deprescribing service for terminal cancer patients in CB-PCT. (3) Methods: A retrospective analysis compared the active care (AC) group to the historical usual care (UC) group. The clinical outcomes included the deprescribing rate of preventive medications, the proportion of patients with one or more medication-related problems (MRPs) resolved upon discharge, and the clinical significance. The implementability of the service was also gauged by the acceptance rates of pharmacists' interventions. (4) Results: Preventive medications included lipid-lowering agents, gastroprotective agents, vitamins, antihypertensives, and antidiabetic agents. The AC group revealed a higher deprescribing rate (10.4% in the UC group vs. 29.6% in the AC group, p < 0.001). At discharge, more AC patients had one or more MRPs deprescribed (39.7% vs. 2.97% in UC, p < 0.001). The clinical significance consistently had a very significant rating (mean score of 2.96 out of 4). Acceptance rates were notably higher in the AC group (30.0% vs. 78.0%. p = 0.003). (5) Conclusions: The collaborative deprescribing service in CB-PCT effectively identified and deprescribed MRPs that are clinically significant and implementable in practice.

Adverse Drug Events Associated With Remdesivir in Real-World Hospitalized Patients With COVID-19, Including Vulnerable Populations: A Retrospective Multicenter Study.

BACKGROUND: Remdesivir is a US Food and Drug Administration-approved drug for coronavirus disease 2019 (COVID-19). Clinical trials were conducted under strictly controlled situations for a selected population, and their reported adverse events may not fully represent conditions in real-world patients. We aimed to estimate the incidence of adverse drug events (ADEs) associated with remdesivir in hospitalized patients with COVID-19, including vulnerable subpopulations, such as those with impaired renal or hepatic function and pregnant women. METHODS: This retrospective observational study included hospitalized patients with confirmed COVID-19 treated with remdesivir between January and December 2021 at ten hospitals. ADEs and severe ADEs (Common Toxicity Criteria for Adverse Events grade ≥ 3) were operationally defined and analyzed through laboratory investigations. The incidence of ADEs was compared with that of each matched control in subpopulations with renal or hepatic impairment and pregnant women. RESULTS: Among 2,140 patients, 1,416 (66.2%) and 295 (13.8%) experienced at least one ADE and severe ADE, respectively. The most frequent ADE was 'hepatic injury' (42.9%), followed by anemia (27.6%). The most common severe ADEs were 'hypokalemia' (5.3%), 'hepatic injury' (2.9%), and 'anemia' (3.6%). There was no significant difference in the incidence of ADEs in patients relative to their respective matched-control groups, including those with renal impairment (80.0% vs. control 71.8%, P = 0.063), hepatic impairment (70.4% vs. control 75.0%, P = 0.623) and pregnant women (78.6% vs. control 63.7%, P = 0.067). However, severe ADE incidence was significantly higher in patients with renal impairment (40.8% vs. 16.0%, P < 0.001). The most common severe ADEs in those were 'anemia' (15.3%), 'hypokalemia' (10.5%), and 'thrombocytopenia' (8.9%). There was no statistically significant difference in the incidence of severe ADEs in patients with hepatic impairment or in pregnancy (P = 0.230; P = 0.085). CONCLUSION: A significant proportion of patients with COVID-19 treated with remdesivir experienced ADEs and severe ADEs. Given the high incidence of severe ADEs, caution is required in patients with renal impairment. Further studies are needed to investigate ADEs in pregnant women and patients with hepatic impairment.

Machine learning-based prediction model for emergency department visits using prescription information in community-dwelling non-cancer older adults.

Older adults are more likely to require emergency department (ED) visits than others, which might be attributed to their medication use. Being able to predict the likelihood of an ED visit using prescription information and readily available data would be useful for primary care. This study aimed to predict the likelihood of ED visits using extensive medication variables generated according to explicit clinical criteria for elderly people and high-risk medication categories by applying machine learning (ML) methods. Patients aged ≥ 65 years were included, and ED visits were predicted with 146 variables, including demographic and comprehensive medication-related factors, using nationwide claims data. Among the eight ML models, the final model was developed using LightGBM, which showed the best performance. The final model incorporated 93 predictors, including six sociodemographic, 28 comorbidity, and 59 medication-related variables. The final model had an area under the receiver operating characteristic curve of 0.689 in the validation cohort. Approximately half of the top 20 strong predictors were medication-related variables. Here, an ED visit risk prediction model for older people was developed and validated using administrative data that can be easily applied in clinical settings to screen patients who are likely to visit an ED.

Characteristics of fatal occupational injuries in migrant workers in South Korea: A machine learning study.

Objective: Analysis of occupational injuries is essential for developing preventive strategies. However, few studies have evaluated severe occupational injuries in migrant workers from the perspective of gender. Therefore, using a new analytical method, this study was performed to identify gender-specific characteristics associated with fatal occupational injuries among migrant workers; the interactions between these factors, were also analyzed. In addition, we compared the utility of explainable artificial intelligence (XAI) using SHapley Additive exPlanations (SHAP) with logistic regression (LR) and discuss caveats regarding its use. Materials and methods: We analyzed national statistics for occupational injuries among migrant workers (n = 67,576) in South Korea between January 1, 2007, and September 30, 2018. We applied an extreme gradient boosting model and developed SHAP and LR models for comparison. Results: We found clear gender differences in fatal occupational injuries among migrant workers, with males in the same occupation having a higher risk of death than females. These gender differences suggest the need for gender-specific occupational injury prevention interventions for migrant workers to reduce the mortality rate. Occupation was a significant predictor of death among female migrant workers only, with care jobs having the highest fatality risk. The occupational fatality risk of female workers would not have been identified without the performance of detailed job-specific analyses stratified by gender. The major advantages of SHAP identified in the present study were the automatic identification and analysis of interactions, ability to determine the relative contributions of each feature, and high overall performance. The major caveat when using SHAP is that causality cannot be established. Conclusion: Detailed job-specific analyses stratified by gender, and interventions considering the gender of migrant workers, are necessary to reduce occupational fatality rates. The XAI approach should be considered as a complementary analytical method for epidemiological studies, as it overcomes the limitations of traditional statistical analyses.

Systemic evaluation of the risk of reoperations in pediatric populations with exotropia and esotropia: nested case-control study.

The study aimed to assess the risk of reoperations for strabismus in the pediatric population and to identify high-risk groups. This was a nationwide population-based study that used data from the Korean National Health Claims Database from 2008 to 2020. Two major cohorts were established based on initial strabismus: age-, sex-, and recruitment year-matched controls were randomly selected. Patients aged ≤ 9 years who underwent initial strabismus surgery for exotropia and esotropia were included, resulting in a total of 24,816 patients included to this study. The cumulative incidence of reoperations was 843 per 10,000 persons for exotropia, 1559 per 10,000 persons for esotropia. To assess the significant exposure factors, conditional logistic regression was performed to obtain odds ratio (OR) in each cohort. In patients with exotropia, the OR of reoperations was 4.26 times higher when the initial surgery is performed at younger age (earlier than 3-year-old) and 6.49 times higher when only one eye underwent than two eye. Similarly, in patients with esotropia, younger age (6.57 times) and unilateral surgery (7.20 times) were identified as common factors that increase the risk of reoperations. Based on the findings, special attention is recommended for patients younger than 3 years, especially those performed unilateral surgery as initial intervention in practical settings.

Potentially inappropriate medication use as predictors of hospitalization for residents in nursing home.

BACKGROUND: Hospitalization of nursing home (NH) residents impose a significant healthcare burden. However, there is still a lack of information regarding the risk of hospitalization from inappropriate prescribing in NH residents. We aimed to estimate the nationwide prevalence of potentially inappropriate medication (PIM) use among NH residents using the Korean tool and 2019 Beers criteria and to assess their associations with hospitalization or emergency department (ED) visits. METHODS: We included older adults aged 65 years or above who were admitted to NHs between July 2008 and December 2018 using national senior cohort database. The prevalence of PIM use based on the Korean medication review tool and Beers criteria on the date of admission to NH was estimated. And the adjusted hazard ratios (aHRs) of polypharmacy, numbers of PIM, each PIM category for hospitalization/ED visits within 30 days of admission to NH was calculated using Cox proportional hazard model to show the association. RESULTS: Among 20,306 NH residents, the average number of medications per person was 7.5 ± 4.7. A total of 89.3% and 67.9% of the NH residents had at least one PIM based on the Korean tool and 2019 Beers criteria, respectively. The risk of ED visits or hospitalization significantly increased with the number of PIMs based on the Korean tool (1-3: aHR = 1.24, CI 1.03-1.49; ≥4: aHR = 1.46, CI 1.20-1.79). Having four or more PIMs based on the Beers criteria increased the risk significantly (aHR = 1.30, CI 1.06-1.53) while using 1-3 PIMs was not significantly associated (aHR = 1.07, CI 0.97-1.19). Residents with any potential medication omission according to the Korean criteria, were at 23% higher risk of hospitalization or ED visits (aHR = 1.23, CI 1.07-1.40). CONCLUSIONS: This study demonstrated that PIMs, based on the Korean tool and Beers criteria, were prevalent among older adults living in NHs and the use of PIMs were associated with hospitalization or ED visits. The number of PIMs based on the Korean tool showed dose-response increase in the risk of hospitalization or ED visits.