COVID-19 Pandemic Risk Assessment: Systematic Review.

Background: The COVID-19 pandemic presents the possibility of future large-scale infectious disease outbreaks. In response, we conducted a systematic review of COVID-19 pandemic risk assessment to provide insights into countries' pandemic surveillance and preparedness for potential pandemic events in the post-COVID-19 era. Objective: We aim to systematically identify relevant articles and synthesize pandemic risk assessment findings to facilitate government officials and public health experts in crisis planning. Methods: This study followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and included over 620,000 records from the World Health Organization COVID-19 Research Database. Articles related to pandemic risk assessment were identified based on a set of inclusion and exclusion criteria. Relevant articles were characterized based on study location, variable types, data-visualization techniques, research objectives, and methodologies. Findings were presented using tables and charts. Results: Sixty-two articles satisfying both the inclusion and exclusion criteria were identified. Among the articles, 32.3% focused on local areas, while another 32.3% had a global coverage. Epidemic data were the most commonly used variables (74.2% of articles), with over half of them (51.6%) employing two or more variable types. The research objectives covered various aspects of the COVID-19 pandemic, with risk exposure assessment and identification of risk factors being the most common theme (35.5%). No dominant research methodology for risk assessment emerged from these articles. Conclusion: Our synthesized findings support proactive planning and development of prevention and control measures in anticipation of future public health threats.

Epidemiology of patients with lymphangioleiomyomatosis: A descriptive study using the national database of health insurance claims and specific health checkups of Japan.

BACKGROUND: Using patient registries or limited regional hospitalization data may result in underestimation of the incidence and prevalence of rare diseases. Therefore, we used the national administrative database to estimate the incidence and prevalence of lymphangioleiomyomatosis over six years (2014-2019) and describe changes in clinical practice and mortality. METHODS: We extracted data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan between January 2013 and December 2020. This database covers ≥99% of the population. We used the diagnostic code for lymphangioleiomyomatosis to estimate the incidence and prevalence from 2014 to 2019. Additionally, we examined the demographic characteristics, treatments, comorbidities, and mortality of the patients. RESULTS: In women, the incidence and prevalence of lymphangioleiomyomatosis in 2019 were approximately 3 per 1,000,000 person-years and 28.7 per 1,000,000 persons, respectively. While, in men, the incidence and prevalence of lymphangioleiomyomatosis were <0.2 per 1,000,000 person-years and 0.8 per 1,000,000 persons, respectively. From 2014 to 2019, the proportion of prescriptions of sirolimus and everolimus increased, while the use of home oxygen therapy, chest drainage, comorbid pneumothorax, and bloody phlegm decreased. The mortality rate remained stable at approximately 1%. CONCLUSIONS: The incidence and prevalence of lymphangioleiomyomatosis were higher in women than those reported previously. Although the incidence did not change during the 6-year period, the prevalence gradually increased. Moreover, lymphangioleiomyomatosis was observed to be rare in men. The practice of treating patients with lymphangioleiomyomatosis changed across the six years while mortality remained low, at approximately 1%.

A Novel Electronic Record System for Documentation and Efficient Workflow for Community Health Workers: Development and Usability Study.

BACKGROUND: The COVID-19 pandemic added to the decades of evidence that public health institutions are routinely stretched beyond their capacity. Community health workers (CHWs) can be a crucial extension of public health resources to address health inequities, but systems to document CHW efforts are often fragmented and prone to unneeded redundancy, errors, and inefficiency. OBJECTIVE: We sought to develop a more efficient data collection system for recording the wide range of community-based efforts performed by CHWs. METHODS: The Communities Organizing to Promote Equity (COPE) project is an initiative to address health disparities across Kansas, in part, through the deployment of CHWs. Our team iteratively designed and refined the features of a novel data collection system for CHWs. Pilot tests with CHWs occurred over several months to ensure that the functionality supported their daily use. Following implementation of the database, procedures were set to sustain the collection of feedback from CHWs, community partners, and organizations with similar systems to continually modify the database to meet the needs of users. A continuous quality improvement process was conducted monthly to evaluate CHW performance; feedback was exchanged at team and individual levels regarding the continuous quality improvement results and opportunities for improvement. Further, a 15-item feedback survey was distributed to all 33 COPE CHWs and supervisors for assessing the feasibility of database features, accessibility, and overall satisfaction. RESULTS: At launch, the database had 60 active users in 20 counties. Documented client interactions begin with needs assessments (modified versions of the Arizona Self-sufficiency Matrix and PRAPARE [Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences]) and continue with the longitudinal tracking of progress toward goals. A user-specific automated alerts-based dashboard displays clients needing follow-up and upcoming events. The database contains over 55,000 documented encounters across more than 5079 clients. Available resources from over 2500 community organizations have been documented. Survey data indicated that 84% (27/32) of the respondents considered the overall navigation of the database as very easy. The majority of the respondents indicated they were overall very satisfied (14/32, 44%) or satisfied (15/32, 48%) with the database. Open-ended responses indicated the database features, documentation of community organizations and visual confirmation of consent form and data storage on a Health Insurance Portability and Accountability Act-compliant record system, improved client engagement, enrollment processes, and identification of resources. CONCLUSIONS: Our database extends beyond conventional electronic medical records and provides flexibility for ever-changing needs. The COPE database provides real-world data on CHW accomplishments, thereby improving the uniformity of data collection to enhance monitoring and evaluation. This database can serve as a model for community-based documentation systems and be adapted for use in other community settings.

Safety assessment of cenobamate: real-world adverse event analysis from the FAERS database.

Objective: This study aims to analyze adverse drug events (ADEs) associated with cenobamate from the FAERS database, covering the third quarter of 2020 to the second quarter of 2023. Methods: Data related to cenobamate-associated ADEs from the third quarter of 2020 to the second quarter of 2023 were collected. After standardizing the data, various signal quantification techniques, including ROR, MHRA, BCPNN, and MGPS, were employed for analysis. Results: Among 2535 ADE reports where cenobamate was the primary suspected drug, 94 adverse reactions involving 11 different System Organ Class (SOC) categories were identified through the application of four signal quantification techniques. More specifically, neurological disorders and injuries resultant from complications are frequent adverse reactions associated with cenobamate. Conclusion: Our research findings align with established results, affirming the favorable safety profile of cenobamate. Effective prevention of adverse reactions induced by cenobamate can be achieved through the establishment of efficient blood concentration monitoring and dose adjustments.

Chinese herbal medicine decreases incidence of hepatocellular carcinoma in diabetes mellitus patients with regular insulin management.

BACKGROUND: Type 2 diabetes mellitus (DM) is an independent risk factor for hepatocellular carcinoma (HCC), while insulin is a potent mitogen. Identifying a new therapeutic modality for preventing insulin users from developing HCC is a critical goal for researchers. AIM: To investigate whether regular herbal medicine use can decrease HCC risk in DM patients with regular insulin control. METHODS: We used data acquired from the Taiwanese National Health Insurance research database between 2000 and 2017. We identified patients with DM who were prescribed insulin for > 3 months. The herb user group was further defined as patients prescribed herbal medication for DM for > 3 months per annum during follow-up. We matched the herb users to nonusers at a 1:3 ratio according to age, sex, comorbidities and index year by propensity score matching. We analyzed HCC incidence, HCC survival rates, and the herbal prescriptions involved. RESULTS: We initially enrolled 657144 DM patients with regular insulin use from 2000 to 2017. Among these, 46849 patients had used a herbal treatment for DM, and 140547 patients were included as the matched control group. The baseline variables were similar between the herb users and nonusers. DM patients with regular herb use had a 12% decreased risk of HCC compared with the control group [adjusted hazard ratio (aHR) = 0.88, 95%CI = 0.80-0.97]. The cumulative incidence of HCC in the herb users was significantly lower than that of the nonusers. Patients with a herb use of > 5 years cumulatively exhibited a protective effect against development of HCC (aHR = 0.82, P < 0.05). Of patients who developed HCC, herb users exhibited a longer survival time than nonusers (aHR = 0.78, P = 0.0001). Additionally, we report the top 10 herbs and formulas in prescriptions and summarize the potential pharmacological effects of the constituents. Our analysis indicated that Astragalus propinquus (Huang Qi) plus Salvia miltiorrhiza Bunge (Dan Shen), and Astragalus propinquus (Huang Qi) plus Trichosanthes kirilowii Maxim. (Tian Hua Fen) were the most frequent combination of single herbs. Meanwhile, Ji Sheng Shen Qi Wan plus Dan Shen was the most frequent combination of herbs and formulas. CONCLUSION: This large-scale retrospective cohort study reveals that herbal medicine may decrease HCC risk by 12% in DM patients with regular insulin use.

Disparities in Place of Death Among Malnourished Individuals in the United States.

BACKGROUND: Deficiencies or imbalances in a person's intake of nutrients are referred to as malnutrition. Malnutrition remains a significant public health concern in the United States, with potential consequences ranging from chronic disease to mortality. This study aims to assess the disparities in place of death due to malnutrition in the United States from 1999 to 2020, based on variables like age, gender, race, and location, utilizing the Centers for Disease Control and Prevention Information and Communication Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database. METHODOLOGY: Data regarding mortality due to malnutrition was extracted for the years 1999-2020 from the CDC WONDER database. Univariate regression analysis was performed to investigate disparities in the place of death based on variables. RESULTS: Between 1999 and 2020, a total of 1,03,962 malnutrition-related deaths were recorded, with 31,023 in home and hospice care, 68,173 in medical and nursing facilities, and 4,766 in other places. The odds of death due to malnutrition at home or hospice were highest for the 85+ age group, female gender, census region 4 (West), and Asian or Pacific Islander race. CONCLUSIONS: This study reveals a rising trend in mortality due to malnutrition in the United States, especially among certain demographic groups and in medical facilities and nursing homes. It emphasizes the need to understand the factors contributing to this increase in mortality rates. Future research should focus on these contributors to combat the rising burden of malnutrition-related mortality in the United States.

Changes in disease burden and treatment reality in patients with severe asthma.

BACKGROUND: Biologics are clinically available for patients with severe asthma, but changes in asthma control over time are unknown. We examined changes in disease burden and treatment in severe asthma patients. METHODS: This retrospective study used a Japanese health insurance database (Cross Fact) and included patients aged ≥16 years treated continuously with an inhaled corticosteroid (ICS) for a diagnosis of asthma in each calendar year from 2015 to 2019. Severe asthma was defined as annual use of high-dose ICS plus one or more asthma controller medications four or more times, oral corticosteroids for ≥183 days, or biologics for ≥16 weeks. Changes in asthma exacerbations, prescriptions, and laboratory testing were examined. RESULTS: Demographic characteristics were similar throughout the study. The number and proportion of patients with severe asthma among those with asthma increased (2724; 15.3% in 2015 vs 4485; 19.0% in 2019). The proportion of severe asthma patients with two or more asthma exacerbations decreased from 24.4% to 21.5%. Odds ratios (95% confidence interval) of ≥2 asthma exacerbations in each year compared with 2015 were 0.96 (0.85-1.08) in 2016 and 0.86 (0.76-0.97) in 2017, with significant reductions observed in subsequent years. Short-acting beta agonists and oral corticosteroid prescriptions for asthma exacerbations decreased and long-acting muscarinic antagonist and biologic prescriptions for maintenance treatment increased. CONCLUSIONS: This study showed improvements in disease burden and treatment in severe asthma patients. There remains an unmet medical need for patients with severe asthma, given the proportion who continue to have asthma exacerbations.

A summary of the U.S. Marine Recruit Assessment Program (RAP) procedures and survey from 2003 to 2021

The Recruit Assessment Program (RAP) is a cross-sectional, baseline survey of U.S. Marine recruits administered at Marine Corps Recruit Depot, San Diego. This report presents RAP study procedures and survey content that was administered to 229,015 participants between 2003 and 2021. Self-reported data were collected on recruit demographics, physical and mental health, adverse life experiences, lifestyle and risky behaviors, and substance use. In 2013, the survey was updated to remove questions with other linkable and reliable sources and those with low completion rates and low relevance to Marine health research; the removal of these items allowed for the addition of instrument measures for major depression, post-traumatic stress disorder, anger, and resilience with no significant change to overall survey length. Average completion rates are approximately 95%. Multiple studies have shown the utility of RAP data collected thus far as a robust data repository of pre-service health and behavioral measures.

Comparison of Healthcare Costs for Women with Treated Versus Untreated Vasomotor Symptoms Due to Menopause.

INTRODUCTION: The study objective was to estimate all-cause healthcare resource utilization (HCRU) and medical and pharmacy costs for women with treated versus untreated vasomotor symptoms (VMS) due to menopause. METHODS: A retrospective study was conducted using US claims data from Optum Research Database (study period: January 1, 2012-February 29, 2020). Women aged 40-63 years with a VMS diagnosis claim and ≥ 12 and ≥ 18 months of continuous enrollment during baseline and follow-up periods, respectively, were included. Women treated for VMS were propensity score matched 1:1 to untreated controls with VMS. Standardized differences (SDIFF) ≥ 10% were considered meaningful. A generalized linear model (gamma distribution, log link, robust standard errors) estimated the total cost of care ratio. Subgroup analyses of on- and off-label treatment costs were conducted. RESULTS: Of 117,582 women diagnosed with VMS, 20.5% initiated VMS treatment and 79.5% had no treatment. Treated women (n = 24,057) were matched to untreated VMS controls. There were no differences in HCRU at follow-up (SDIFF < 10%). Pharmacy ($487 vs $320, SDIFF 28.4%) and total ($1803 vs $1536, SDIFF 12.6%) costs were higher in the treated cohort. Total costs were 7% higher in the treated cohort (total cost ratio 1.07, 95% CI 1.05-1.10, P < 0.001). The on-label treatment pharmacy costs ($546 versus $315, SDIFF 38.6%) were higher in the treated cohort. Off-label treatment had higher medical costs ($1393 versus $1201, SDIFF 10.4%). CONCLUSIONS: Most women with VMS due to menopause were not treated within 6 months following diagnosis. While both on- and off-label treatment increased the total cost of care compared with untreated controls, those increases were modest in magnitude and should not impede treatment for women who report symptom improvement as a result of treatment.

The Longitudinal Association between Multiple Frailty Criteria and Depressive Symptomatology Five Years Later in Older Adults: A Decision Tree Modelling Approach.

Background: To examine the longitudinal association between frailty criteria and depression (DEP) in a large sample of older Europeans using decision tree models, and to examine complex relationships between frailty criteria and DEP symptomatology. Methods: Data come from waves six and eight of the Population Survey of Health, Ageing and Retirement in Europe. DEP was assessed using the EURO-D scale (wave 8) and frailty (wave 6). We included 27,122 people (56.9% women), aged 50 or over. Results: Women indicated a higher rate of DEP (29.0%), as well as a higher prevalence of pre-frailty (21.6%) and frailty (10.8%) than men. For both sexes, fatigue, weight loss, and slowness indicated an increased chance of DEP 5 years later. MPA (moderate physical activity) and grip strength were considered longitudinally protective factors for DEP. The highest prevalence of DEP symptomatology 5 years later was 50.3%, pointing to those with fatigue and slowness. Among women, the highest incidence of DEP was 66.8%, identified through fatigue, slowness, and low MPA. Conclusions: Strategies to reduce frailty and DEP in older European adults may include the creation of policies that encourage the promotion of physical capacity to reach MPA levels, as well as an improvement in muscular strength.

Cause-of-Death Determinants of Lifespan Inequality.

We propose a novel decomposition approach that breaks down the levels and trends of lifespan inequality as the sum of cause-of-death contributions. The suggested method shows whether the levels and changes in lifespan inequality are attributable to the levels and changes in (1) the extent of inequality in the cause-specific age-at-death distribution (the "Inequality" component), (2) the total share of deaths attributable to each cause (the "Proportion" component), or (3) the cause-specific mean age at death (the "Mean" component). This so-called Inequality-Proportion-Mean (or IPM) method is applied to 10 low-mortality countries in Europe. Our findings suggest that the most prevalent causes of death (in our setting, "circulatory system" and "neoplasms") do not necessarily contribute the most to overall levels of lifespan inequality. In fact, "perinatal and congenital" causes are the strongest drivers of lifespan inequality declines. The contribution of the IPM components to changes in lifespan inequality varies considerably across causes, genders, and countries. Among the three components, the Mean one explains the least lifespan inequality dynamics, suggesting that shifts in cause-specific mean ages at death alone contributed little to changes in lifespan inequality.

Medical Costs Associated with High/Moderate/Low Likelihood of Adult Growth Hormone Deficiency: A Healthcare Claims Database Analysis.

Purpose: Adult growth hormone deficiency (AGHD) is often underdiagnosed and undertreated, leading to costly comorbidities. Previously, we developed an algorithm to identify individuals in a commercially insured US population with high, moderate, or low likelihood of having AGHD. Here, we estimate and compare direct medical costs by likelihood level. Patients and Methods: Retrospective, observational analysis using the Truven Health MarketScan database to analyze direct medical costs relating to inpatient and outpatient claims, outpatient prescription claims, medication usage, clinical utilization records, and healthcare expenditures. Patients were categorized into groups based on algorithmically determined likelihoods of AGHD. Likelihood groups were further stratified by age and sex. Trajectories of annual costs (USD) by likelihood level were also investigated. Results: The study cohort comprised 135 million US adults (aged ≥18 years). Individuals ranked as high-likelihood AGHD had a greater burden of comorbid illness, including cardiovascular disease and diabetes, than those ranked moderate- or low-likelihood. Those in the high-likelihood group had greater mean total direct medical monthly costs ($1844.51 [95% confidence interval (CI): 1841.24;1847.78]) than those in the moderate- ($945.65 [95% CI: 945.26;946.04]) and low-likelihood groups ($459.10 [95% CI: 458.95;459.25]). Outpatient visits accounted for the majority of costs overall, although cost per visit was substantially lower than for inpatient services. Costs tended to increase with age and peaked around the time that individuals were assigned a level of AGHD likelihood. Total direct medical costs in individuals with a high likelihood of AGHD exceeded those for individuals with moderate or low likelihood. Conclusion: Understanding the trajectory of healthcare costs in AGHD may help rationalize allocation of healthcare resources.

Growth hormone is an important substance found in the body. Adult growth hormone deficiency (AGHD) is the reduced production of growth hormone unrelated to the normal reduction seen with aging. Untreated AGHD can result in the development of other conditions, known as comorbidities, which can be expensive to manage. Previously, 135 million privately insured people in the US, aged 18­64 years, were categorized into groups by their likelihood (high, medium, or low) of having AGHD. This study compared the estimated direct medical costs (eg hospital care and medication) across the different likelihood levels. People with a high likelihood of AGHD had more comorbidities than people with a medium/low likelihood, and an average total direct medical monthly cost of $1844.51, nearly twice as much as those with a medium likelihood ($945.65), and four times as much as those with a low likelihood ($459.10). These costs tended to increase with age, with the highest costs associated with people aged 50­59 years and 60­64 years. Outpatient costs (for treatments not requiring an overnight hospital stay) accounted for the greatest proportion of total medical costs, ahead of inpatient costs (for treatments requiring an overnight hospital stay) and medication costs. These findings suggest that diagnosing and treating AGHD earlier may help to reduce medical costs over time. Increased testing and treatment will cause an initial increase in the use of healthcare resources, but could improve overall cost effectiveness by reducing the long-term impact of the disease and avoiding unnecessary healthcare use.

Cracking a cancer code DNA methylation in epigenetic modification: an in-silico approach on efficacy assessment of Sri Lanka-oriented nutraceuticals.

DNA methyltransferase (DNMTs) are essential epigenetic modifiers that play a critical role in gene regulation. These enzymes add a methyl group to cytosine's 5'-carbon, specifically within CpG dinucleotides, using S-adenosyl-L-methionine. Abnormal overexpression of DNMTs can alter the gene expression patterns and contribute to cancer development in the human body. Therefore, the inhibition of DNMT is a promising therapeutic approach to cancer treatment. This study was aimed to identify potential nutraceutical inhibitors from the Sri Lanka Flora database using computational methods, which provided an atomic-level description of the drug binding site and examined the interactions between nutraceuticals and amino acids of the DNMT enzyme. A series of nutraceuticals from Sri Lanka-oriented plants were selected and evaluated to assess their inhibitory effects on DNMT using absorption, distribution, metabolism, excretion and toxicity analysis, virtual screening, molecular docking, molecular dynamics simulation and trajectory analysis. Azacitidine, a DNMT inhibitor approved by the US Food and Drug Administration, was selected as a reference inhibitor. The complexes with more negative binding energies were selected and further assessed for their potency. Seven molecules were identified from 200 nutraceuticals, demonstrating significantly negative binding energies against the DNMT enzyme. Various trajectory analyses were conducted to investigate the stability of the DNMT enzyme. The results indicated that petchicine (NP#0003), ouregidione (NP#0011) and azacitidine increased the stability of the DNMT enzyme. Consequently, these two nutraceuticals showed inhibitory efficacies similar to azacitidine, making them potential candidates for therapeutic interventions targeting DNMT enzyme-related cancers. Additional bioassay testing is recommended to confirm the efficacies of these nutraceuticals and explore their applicability in clinical treatments.Communicated by Ramaswamy H. Sarma.

Possibilities and limits of modelling of long-range economic consequences of air pollution - A case study.

Air pollution is the biggest environmental problem in modern societies, causing considerable health damage and requiring substantial financial resources for health care. The goal of the study is to demonstrate the adverse economic consequences of air pollution on example of a small, open Central European country, Hungary, and to provide quantified financial arguments for macroeconomic decision-making for the development of a long-term energy strategy. On the basis of the Cobb-Douglas production function and Solow-Swann model of dynamic economic systems a simple and robust model was constructed to estimate and predict economic losses, caused by the pollution. On base of results it is obvious, that on base of macroeconomic theory and combination of various, publicly available, quality-controlled statistical resources quantifiable models can be constructed to characterise the economic consequences of air pollution, but it should be taken into consideration, that the reliability of economic models considerably depends on their initial parameters and practical validity of assumptions, based on which the underlying economic theories were built. The most important economic burden of air pollution is caused by the loss of working-age population, resulting in a decrease of 4.1-9.4 % a year in Gross Domestic Product (GDP) in the next fifty years. The additional burden of health care costs amounts to 0.1 % of GDP. Reducing air pollution is not only a quality of life improvement but also an investment into the economic development. Notwithstanding of statistical biases it could be proven the importance of combination health economic and econometric methods in preparation of more efficient environmental-related socio-economic decisions.

Simultaneous assessment of stress hyperglycemia ratio and glycemic variability to predict mortality in patients with coronary artery disease: a retrospective cohort study from the MIMIC-IV database.

BACKGROUND: Stress hyperglycemia and glycemic variability (GV) can reflect dramatic increases and acute fluctuations in blood glucose, which are associated with adverse cardiovascular events. This study aimed to explore whether the combined assessment of the stress hyperglycemia ratio (SHR) and GV provides additional information for prognostic prediction in patients with coronary artery disease (CAD) hospitalized in the intensive care unit (ICU). METHODS: Patients diagnosed with CAD from the Medical Information Mart for Intensive Care-IV database (version 2.2) between 2008 and 2019 were retrospectively included in the analysis. The primary endpoint was 1-year mortality, and the secondary endpoint was in-hospital mortality. Levels of SHR and GV were stratified into tertiles, with the highest tertile classified as high and the lower two tertiles classified as low. The associations of SHR, GV, and their combination with mortality were determined by logistic and Cox regression analyses. RESULTS: A total of 2789 patients were included, with a mean age of 69.6 years, and 30.1% were female. Overall, 138 (4.9%) patients died in the hospital, and 404 (14.5%) patients died at 1 year. The combination of SHR and GV was superior to SHR (in-hospital mortality: 0.710 vs. 0.689, p = 0.012; 1-year mortality: 0.644 vs. 0.615, p = 0.007) and GV (in-hospital mortality: 0.710 vs. 0.632, p = 0.004; 1-year mortality: 0.644 vs. 0.603, p < 0.001) alone for predicting mortality in the receiver operating characteristic analysis. In addition, nondiabetic patients with high SHR levels and high GV were associated with the greatest risk of both in-hospital mortality (odds ratio [OR] = 10.831, 95% confidence interval [CI] 4.494-26.105) and 1-year mortality (hazard ratio [HR] = 5.830, 95% CI 3.175-10.702). However, in the diabetic population, the highest risk of in-hospital mortality (OR = 4.221, 95% CI 1.542-11.558) and 1-year mortality (HR = 2.013, 95% CI 1.224-3.311) was observed in patients with high SHR levels but low GV. CONCLUSIONS: The simultaneous evaluation of SHR and GV provides more information for risk stratification and prognostic prediction than SHR and GV alone, contributing to developing individualized strategies for glucose management in patients with CAD admitted to the ICU.

Characterizing Fit-for-Purpose Real-World Data: An Assessment of a Mother-Infant Linkage in the Japan Medical Data Center Claims Database.

Purpose: Observational postapproval safety studies are needed to inform medication safety during pregnancy. Real-world databases can be valuable for supporting such research, but fitness for regulatory purpose must first be vetted. Here, we demonstrate a fit-for-purpose assessment of the Japan Medical Data Center (JMDC) claims database for pregnancy safety regulatory decision-making. Patients and Methods: The Duke-Margolis framework considers a database's fitness for regulatory purpose based on relevancy (capacity to answer the research question based on variable availability and a sufficiently sized, representative population) and quality (ability to validly answer the research question based on data completeness and accuracy). To assess these considerations, we examined descriptive characteristics of infants and pregnancies among females ages 12-55 years in the JMDC between January 2005 and March 2022. Results: For relevancy, we determined that critical data fields (maternal medications, infant major congenital malformations, covariates) are available. Family identification codes permitted linkage of 385,295 total mother-infant pairs, 57% of which were continuously enrolled during pregnancy. The prevalence of specific congenital malformation subcategories and maternal medical conditions were representative of the general population, but preterm births were below expectations (3.6% versus 5.6%) in this population. For quality, our methods are expected to accurately identify the complete set of mothers and infants with a shared health insurance plan. However, validity of gestational age information was limited given the high proportion (60%) of missing live birth delivery codes coupled with suppression of infant birth dates and inaccessibility of disease codes with gestational week information. Conclusion: The JMDC may be well suited for descriptive studies of pregnant people in Japan (eg, comorbidities, medication usage). More work is needed to identify a method to assign pregnancy onset and delivery dates so that in utero medication exposure windows can be defined more precisely as needed for many regulatory postapproval pregnancy safety studies.

Advanced SQL-Database for bioenergy technologies - A catalogue for bio-resources, conversion technologies, energy carriers, and supply applications.

Bioenergy is a crucial element of the future energy system with wide range of applications in electricity, heat and transport. A major challenge for the analysis and optimisation of the bioenergy system is the degree of diversity and complexity compared to wind or solar energy. A coherent database for studying the role of bioenergy in the energy system needs to cover the different entities such as bio-resources, conversion procedures and process chains. Since there is no comprehensive data collection for bioenergy so far, we develop a SQLite database by merging several existing datasets and additional information. The resulting Bio-Energy Technology Database (BET.db) provides a consistent set of 141 feedstocks as well as energy carriers, 259 conversion technologies, and 134 energy supply concepts. The proof of concept within a bioenergy system modelling a wide range of technologies for the electricity, heat and transport sectors using the BENOPT model has been successful. By providing a one-stop-shop solution for techno-economic information about on the bioenergy nexus, this blind spot can be avoided for further investigations. The current stage of development is an intermediate prototype that will be developed into a more versatile and interactive web application later on.

Impact of National Public-Private Mix and Medical Expense Support Program for Control Tuberculosis in South Korea: An Interrupted Time Series Analysis.

Tuberculosis (TB) remains a major threat to global public health, various measures at national level have been implemented to control TB and no evidence with long-term effectiveness has yet been evaluated on TB control programs. We confirmed the long-term effectiveness of the TB control programs in reducing overall burden in South Korea using interrupted time series analysis. Along with the Public-Private Mix, our finding suggests that relieving the economic burden of people with TB may further complement in achieving the End TB strategy. For countries currently developing strategies for TB control, results may provide important insights in effective TB control.

Average daily glucocorticoid dose, number of prescription days, and cumulative dose in the initial 90 days of glucocorticoid therapy are associated with subsequent hip and clinical vertebral fracture risk: a retrospective cohort study using a nationwide health insurance claims database in Japan.

PURPOSE: Fracture risk assessment is recommended at three months after glucocorticoid (GC) therapy initiation. This study aimed to assess whether GC exposure in the initial 90 days of GC therapy is associated with subsequent hip and clinical vertebral fracture risk using the nationwide health insurance claims database of Japan (NDBJ). METHODS: Patients aged ≥ 50 years who were prescribed GC (≥ 70 mg prednisolone or equivalent; PSL) in the initial 90 days of GC therapy and were followed for hip and clinical vertebral fracture incidences for the subsequent 1080 days were selected from NDBJ. Associations of GC exposure with hip or clinical vertebral fracture risk were evaluated by Cox regression analysis adjusted for potential confounders. RESULTS: We selected 316,396 women and 299,871 men for the GC-exposed group and 43,164 women and 33,702 men for the reference group. Higher GC doses and longer prescription days in the initial 90 days of GC therapy were significantly and dose-dependently associated with increased fracture risk relative to the reference group. Patients receiving GC ≥ 5 mg PSL/day had a significantly increased fracture risk in the stratum of 30-59 days of GC prescription. In addition, female patients who received GC (≥ 1 and < 2.5 mg PSL/day) for 90 days in the initial 90 days of GC therapy had a significantly increased fracture risk. CONCLUSIONS: GC exposure in the initial 90 days of GC therapy was dose-dependently associated with hip and clinical vertebral fracture risk. GC may increase fracture risk with lower doses for shorter durations than previously reported. Fracture risk assessment three months after glucocorticoid (GC) therapy initiation is recommended. We found that GC exposure in the initial 90 days of GC therapy at lower daily doses for shorter durations than previously reported were significantly and dose-dependently associated with fracture risk using a nationwide health insurance claims database.

Validation of an international classification of disease, tenth revision, clinical modification (ICD-10-CM) algorithm in identifying severe hypoglycaemia events for real-world studies.

AIM: The transition to the ICD-10-CM coding system has reduced the utility of hypoglycaemia algorithms based on ICD-9-CM diagnosis codes in real-world studies of antidiabetic drugs. We mapped a validated ICD-9-CM hypoglycaemia algorithm to ICD-10-CM codes to create an ICD-10-CM hypoglycaemia algorithm and assessed its performance in identifying severe hypoglycaemia. MATERIALS AND METHODS: We assembled a cohort of Medicare patients with DM and linked electronic health record (EHR) data to the University of North Carolina Health System and identified candidate severe hypoglycaemia events from their Medicare claims using the ICD-10-CM hypoglycaemia algorithm. We confirmed severe hypoglycaemia by EHR review and computed a positive predictive value (PPV) of the algorithm to assess its performance. We refined the algorithm by removing poor performing codes (PPV ≤0.5) and computed a Cohen's κ statistic to evaluate the agreement of the EHR reviews. RESULTS: The algorithm identified 642 candidate severe hypoglycaemia events, and we confirmed 455 as true severe hypoglycaemia events, PPV of 0.709 (95% confidence interval: 0.672, 0.744). When we refined the algorithm, the PPV increased to 0.893 (0.862, 0.918) and missed <2.42% (<11) true severe hypoglycaemia events. Agreement between reviewers was high, κ = 0.93 (0.89, 0.97). CONCLUSIONS: We translated an ICD-9-CM hypoglycaemia algorithm to an ICD-10-CM version and found its performance was modest. The performance of the algorithm improved by removing poor performing codes at the trade-off of missing very few severe hypoglycaemia events. The algorithm has the potential to be used to identify severe hypoglycaemia in real-world studies of antidiabetic drugs.