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This study, bases on both the attribution theory and trust repair theory, and explores the effects of attribution and government intervention in the trust repair process, willingness to reconcile and one’s intention to share during the COVID-19 pandemic. Questionnaires are distributed online, and 799 responses are collected, as based on convenience sampling. Partial least squares structural equation modeling is used to conduct analysis. Results show that controllability, stability, affective repair, functional repair, and informational repair have a positive and significant effect on individuals’ willingness to reconcile, but the locus of causality does not have a significant effect. Willingness to reconcile has a positive effect on individuals’ intention to share. Based on these findings, it is recommended that governments develop appropriate strategies to repair peoples’ levels of trust and eliminate the chance of any major crisis event recurrence. Moreover, the findings further confirm that governments and public sector organizations can use the attribution theory and trust repair strategies to affect positive change.

Abstract Background In patients with chronic obstructive pulmonary disease (COPD) and acute respiratory failure, approximately 10% of them are considered to be at high risk for prolonged mechanical ventilation (PMV, > 21 days). PMV have been identified as independent predictors of unfavorable outcomes. Our previous study revealed that patients aged 70 years older and COPD severity were at a significantly higher risk for PMV. We aimed to analyze the impact of comorbidities and their associated risks in patients with COPD who require PMV. Methods The data used in this study was collected from Kaohsiung Medical University Hospital Research Database. The COPD subjects were the patients first diagnosed COPD (index date) between January 1, 2012 and December 31, 2020. The exclusion criteria were the patients with age less than 40 years, PMV before the index date or incomplete records. COPD and non-COPD patients, matched controls were used by applying the propensity score matching method. Results There are 3,744 eligible patients with COPD in the study group. The study group had a rate of 1.6% (60 cases) patients with PMV. The adjusted HR of PMV was 2.21 (95% CI 1.44–3.40; P

Abstract Large‐area graphene is typically synthesized on rolled‐annealed copper foils, which require transferring to other substrates for applications. This study examines large‐area graphene growth on electrodeposited (ED) copper foils—used in lithium‐ion batteries and printed circuit boards—via plasma‐enhanced chemical vapor deposition (PECVD). It reveals that, for a set plasma power, a minimum growth time ensures full graphene coverage, leading to monolayer and then multilayer graphene, showing PECVD growth on ED copper is not self‐limited. The process also beneficially modifies the ED copper substrate, like removing the surface zinc layer and changing copper grain size and orientation, thus improving graphene growth. Additionally, the study includes high‐frequency scattering parameter (S‐parameter) measurements in a coplanar waveguide (CPW) system. This involves graphene on a sapphire substrate with a silver electrode. The S‐parameter data indicate that the CPW with graphene shows reduced insertion losses in high‐frequency circuits compared to those without graphene. This underscores graphene's role in reducing insertion losses between metallic and dielectric layers in high‐frequency settings, offering valuable insights for industrial and technological applications.

Objectives: Long-acting bronchodilators are important treatments for chronic obstructive pulmonary disease (COPD) and adequate medication adherence decreases COPD exacerbations, especially in reducing the hazard of influenza infection. Therefore, the study aim was to evaluate adherence of long-acting bronchodilator treatment and the risk of influenza in patients with COPD. Methods: This retrospective nested case-control study included patients with newly diagnosed COPD from 2012 to 2018. Cases with influenza infection were defined and matched to 2 randomly selected controls. The influenza infection date was the index date. Conditional logistic regressions were used to estimate odds ratios of influenza from proportion of days covered (PDC) of long-acting bronchodilators measured in one year before the index date. Adherence was divided into high adherence (PDC ≥80 %) and low adherence (PDC

Abstract Background This study examines incidence, mortality, medical expenditure and prescription patterns for asthma on a national scale, particularly in Asian countries for asthma is limited. Our aim is to investigate incidence, mortality, prescription patterns and provide a comprehensive overview of healthcare utilization trends for asthma from 2009 to 2018. Methods We included patients diagnosed with asthma between 2009 and 2018. We excluded patients with missing demographic data. Our analysis covered comorbidities, including diabetes mellitus, hypertension, allergic rhinitis, eczema, atopic dermatitis, coronary artery disease, congestive heart failure, chronic kidney disease, chronic hepatitis, stroke, and cancer. Investigated medications comprised oral and intravenous steroids, short-acting beta-agonists, inhaled corticosteroids (ICS), combinations of ICS and long-acting beta-agonists, long-acting muscarinic antagonists, and leukotriene receptor antagonists montelukast. We also assessed the number of outpatient visits, emergency visits, and hospitalizations per year, as well as the average length of hospitalization and average medical costs. Results The study included a final count of 88,244 subjects from 1,998,311 randomly selected samples between 2000 and 2019. Over the past decade, there was a gradual decline in newly diagnosed asthma patients per year, from 10,140 to 6,487. The mean age annually increased from 47.59 in 2009 to 53.41 in 2018. Over 55% of the patients were female. Eczema was diagnosed in over 55% of the patients. Around 90% of the patients used oral steroids, with a peak of 97.29% in 2018, while the usage of ICS varied between 86.20% and 91.75%. Intravenous steroids use rose from 40.94% in 2009 to 54.14% in 2018. The average annual hospital stay ranged from 9 to 12 days, with a maximum of 12.26 days in 2013. Lastly, the average medical expenses per year ranged from New Taiwan dollars 5558 to 7921. Conclusions In summary, both asthma incidence and all-cause mortality rates decreased in Taiwan from 2009 to 2018. Further analysis of medical expenses in patients with asthma who required multiple hospitalizations annually revealed an increase in outpatient and emergency visits and hospitalizations, along with longer hospital stays and higher medical costs.

Abstract Objective The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning’s potential to predict ED dispositions, thus leading to promising substantial benefits. This study’s objective is to create a predictive model for ED patient dispositions by employing ensemble learning. It harnesses diverse data types, including structured and unstructured information gathered during ED visits to address the evolving needs of localized healthcare systems. Methods In this cross-sectional study, 80,073 ED patient records were amassed from a major southern Taiwan hospital in 2018–2019. An ensemble model incorporated structured (demographics, vital signs) and pre-processed unstructured data (chief complaints, preliminary diagnoses) using bag-of-words (BOW) and term frequency-inverse document frequency (TF-IDF). Two random forest base-learners for structured and unstructured data were employed and then complemented by a multi-layer perceptron meta-learner. Results The ensemble model demonstrates strong predictive performance for ED dispositions, achieving an area under the receiver operating characteristic curve of 0.94. The models based on unstructured data encoded with BOW and TF-IDF yield similar performance results. Among the structured features, the top five most crucial factors are age, pulse rate, systolic blood pressure, temperature, and acuity level. In contrast, the top five most important unstructured features are pneumonia, fracture, failure, suspect, and sepsis. Conclusions Findings indicate that utilizing ensemble learning with a blend of structured and unstructured data proves to be a predictive method for determining ED dispositions.

Abstract Background Chronic obstructive pulmonary disease (COPD) is a preventable and treatable chronic condition characterized by progressive, partially reversible airflow obstruction. Osteoporosis represents a significant comorbidity in individuals with COPD. However, the incidence and prevalence of osteoporosis among the COPD population remain unclear in Taiwan. Therefore, our objective is to investigate the incidence and prevalence of osteoporosis in patients with COPD. Methods In this cross-sectional study, we enrolled a COPD population retrieved from the Taiwan National Health Insurance Research Database (NHIRD) spanning the years 2003 to 2016. Osteoporosis patients were identified using diagnosis codes. The study included newly diagnosed COPD patients from 2003 to 2016. The case group comprised patients who developed osteoporosis or osteoporotic fractures after their COPD diagnosis. We calculated the prevalence and incidence of osteoporosis in individuals with COPD and conducted trend tests. Results A total of 1,297,579 COPD patients were identified during the period from 2003 to 2016, with 275,233 of them in the osteoporosis group. The average prevalence of osteoporosis among individuals with COPD was 21.21% from 2003 to 2016 in Taiwan. The number of osteoporosis cases increased from 6,727 in 2003 to 24,184 in 2016. The prevalence of osteoporosis among COPD patients increased from 3.62% in 2003 to 18.72% in 2016. The number of osteoporosis cases among individuals with COPD continued to rise over the years, reaching its highest point in 2016 with 24,184 new cases. The incidence of osteoporosis fluctuated during the study period but generally remained around 3,000 cases per 100,000 person-years. Notably, there was a significant upward trend in incidence from 2003 to 2006, after which the trend stabilized and remained relatively constant. Conclusions Our study highlights an increase in both the prevalence and incidence of osteoporosis in individuals with COPD. Given the significant medical, economic, and social implications associated with osteoporosis, a comprehensive and robust assessment of its healthcare burden can offer valuable insights for healthcare system planning and policymaking.

Background Chronic airway diseases have been associated with an increased risk of tuberculosis (TB); however, data in patients with bronchiectasis is limited. Statins have been shown to exhibit anti-inflammatory effects by modulating the inflammatory response. This study investigated whether statin treatment could reduce the risk of TB in patients with bronchiectasis.Methods We conducted a retrospective cohort study using a nationwide population database of patients with bronchiectasis who did or did not receive statin treatment. The defined daily dose (DDD) of statin, current or past statin user and statin exposure time were measured for the impact of statin use. The primary outcome was the incidence of new-onset TB. Considering of potential immortal time bias due to stain exposure time, Cox regression models with time-dependent covariates were employed to estimate HRs with 95% CIs for TB incidence among patients with bronchiectasis.Results Patients with bronchiectasis receiving statin treatment had a decreased risk of TB. After adjusting for age, sex, income, comorbidities and Charlson Comorbidity Index, statin users had a 0.59-fold lower risk of TB incidence compared with non-statin users (95% CI 0.40 to 0.88; p=0.0087). Additionally, compared with non-statin users, statin treatment was a protective factor against TB in users with a cumulative DDD greater than 180 per year, with an HR of 0.32 (95% CI 0.12 to 0.87; p=0.0255).Conclusions Statin treatment demonstrated a dose-dependent protective effect and was associated with a reduced risk of TB in patients with bronchiectasis. These findings suggest that statins may play a role in lowering TB risk by modulating airway inflammation in this patient population.

ObjectiveAs patient life expectancy has increased and people are living longer than before, the rate of mechanical ventilation among elderly patients in the intensive care unit has increased. Older patients who receive mechanical ventilation and have multiple comorbidities are more likely to have a do not resuscitate order than are younger patients with fewer comorbidities. The aim of our study was to describe the patient characteristics and predictive factors of do not resuscitate orders during hospitalization among elderly patients who received ventilation in the intensive care unit.MethodsThis was a retrospective review of the electronic medical records of patients in the intensive care unit of a teaching hospital in southern Taiwan. We enrolled patients admitted to the general intensive care unit from January 1, 2018, to September 31, 2020, and patients older than 80 years who experienced respiratory failure, were intubated and received mechanical ventilation. We analyzed patient demographics, disease severity during hospitalization and comorbidities. If a patient had multiple admissions to the intensive care unit, only the first admission was recorded.ResultsOf the 305 patients over 80 years of age with respiratory failure who were intubated and placed on a ventilator, 66 were excluded because of incomplete data, and 13 were excluded because they had already signed a do not resuscitate order prior to admission to the hospital. Ultimately, 226 patients were included in this study. A higher acute physiology and chronic health evaluation II score (>30) was also associated with an increased likelihood of a do not resuscitate order (odds ratio (OR) = 3.85, 95% CI = 1.09–13.62, p = 0.0362). Patients who had acute kidney injury or cerebrovascular accident were more likely to have a do not resuscitate order (OR = 2.74, 95% CI = 1.03–7.28, p = 0.0428 and OR = 7.32, 95% CI = 2.02–26.49, p = 0.0024, respectively).ConclusionOur study showed that older age, greater disease severity, and certain critical interventions were associated with a greater propensity for do not resuscitate orders, which is crucial for understanding patient preferences and guiding end-of-life care discussions. These findings highlight the importance of clinical severity and specific health events in predicting end-of-life care preferences in older patient groups.

Pancreatic islet transplantation is one of the clinical options for certain types of diabetes. However, difficulty in maintaining islets prior to transplantation limits the clinical expansion of islet transplantations. Our study introduces a dynamic culture platform developed specifically for primary human islets by mimicking the physiological microenvironment, including tissue fluidics and extracellular matrix support. We engineered the dynamic culture system by incorporating our distinctive microwell-patterned porous collagen scaffolds for loading isolated human islets, enabling vertical medium flow through the scaffolds. The dynamic culture system featured four 12 mm diameter islet culture chambers, each capable of accommodating 500 islet equivalents (IEQ) per chamber. This configuration calculates > five-fold higher seeding density than the conventional islet culture in flasks prior to the clinical transplantations (442 vs 86 IEQ/cm 2 ). We tested our culture platform with three separate batches of human islets isolated from deceased donors for an extended period of 2 weeks, exceeding the limits of conventional culture methods for preserving islet quality. Static cultures served as controls. The computational simulation revealed that the dynamic culture reduced the islet volume exposed to the lethal hypoxia (< 10 mmHg) to ~1/3 of the static culture. Dynamic culture ameliorated the morphological islet degradation in long-term culture and maintained islet viability, with reduced expressions of hypoxia markers. Furthermore, dynamic culture maintained the islet metabolism and insulin-secreting function over static culture in a long-term culture. Collectively, the physiological microenvironment-mimetic culture platform supported the viability and quality of isolated human islets at high-seeding density. Such a platform has a high potential for broad applications in cell therapies and tissue engineering, including extended islet culture prior to clinical islet transplantations and extended culture of stem cell-derived islets for maturation.

Patients with chronic obstructive pulmonary disease (COPD) had higher risk of atrial fibrillation (AF). The treatment of AF includes medicines to control heart rate and reduce the risk of stroke, and procedures such as cardioversion to restore normal heart rhythm. To reduce the stroke, patients with AF may prescribe some type of antithrombotic medication (such as warfarin, one of the new non-vitamin K antagonist oral anticoagulants [NOACs] – dabigitran, apixaban, rivoraxaban, or edoxaban) or maybe aspirin. The aim of our study was to exam the prescription pattern in patients with COPD and AF. We selected COPD population in Taiwan older than 40 years and less than 90 years old with an COPD diagnosis at least two outpatient claims or at least one inpatient claim coded and also need at least one prescription of bronchodilators. We followed this COPD cohort until they have AF and their prescription pattern. We included 267,740 patients with COPD who meet the inclusion and exclusion criteria and 6,582 patients concomitant with COPD and AF. The mean age was 75 years, and about 77% of the patients were older than 70 years. Three-fourths of patients with COPD were male. The common comorbidities were hypertension (17.58%), diabetes (7.47%), ischemic heart disease (4.66%), and dyslipidemia (3.68%). we found that most patients received aspirin which accounting for 31%, followed by coumadin (8.22%) and clopidogrel. Prescribing NOAC within 30 days after AF diagnosis was low in patients with COPD and the percentage of NOAC usage was also lower than warfarin.

Background: We investigated the impacts of the standard treatment durations of and adherence to standard anti-tuberculous therapy (ATT) on recurrence after the successful completion of tuberculosis (TB) treatment. Methods: We recruited patients with TB who had received treatment for six or nine months from the 2008–2017 databases of the Taiwanese National Health Insurance Research Database. Treatment duration and adherence to standard ATT were analyzed for their impacts on recurrence within two years. Complete adherence to standard ATT was defined as daily use of ethambutol, isoniazid, pyrazinamide, and rifampin for the first two months, and daily use of isoniazid and rifampin for the first six months. Results: A total of 33,298 TB patients with new-onset TB were identified and classified into two groups by treatment duration: six months (n = 25,849, 77.63%) and nine months (n = 7449). Sex and age distributions varied between the groups. Treatment duration did not affect TB recurrence within two years (adjusted hazard ratio (AHR): 1.18, 95% confidence interval (C.I.) [0.96–1.44], p = 0.1156). Multivariable logistic regression showed that incomplete adherence to standard anti-tuberculous therapy (80–89% and 90–99% standard anti-TB therapy, AHR: 1.57, 95% C.I. [1.26–1.95], and 1.63, 95% C.I. [1.26–2.06], respectively, p

Background: Type 2 diabetes mellitus (DM) is a risk factor for mycobacterial pulmonary infections (MPI), including tuberculosis (TB) and nontuberculous mycobacterial lung disease (NTM-LD). Dipeptidyl peptidase IV inhibitor (DPP4i), a common DM medication, has an immune-modulation effect that raises concerns about developing MPI. However, there is scarce research on the topic. Methods: This retrospective study was conducted in a tertiary-referral center in Taiwan from 2009 to 2016. Patients with type 2 DM who were receiving any DM medication were enrolled. TB and NTM-LD were defined by microbiological criteria. We analyzed the risk of MPI in DPP4i users using Cox proportional hazard regression with adjusted inverse probability of treatment weighting. Results: A total of 9963 patients were included. Among them, 3931 were classified as DPP4i users, and 6032 patients were DPP4i nonusers. DPP4i users had no increase in incidences of MPI (604 vs. 768 per 100,000 person-years, p = 0.776), NTM-LD (174 vs. 255 per 100,000 person-years, p = 0.228), and TB (542 vs. 449 per 100,000 person-years, p = 0.663) relative to those of DPP4i nonusers. After adjustment, the adjusted hazard ratios for MPI (aHR: 1.07, 95% CI: 0.79–1.45), TB (aHR: 1.15, 95% CI: 0.81–1.64) and NTM-LD (aHR: 0.85, 95% CI: 0.49–1.47) were not significantly increased relative to those of nonusers. The subgroup analysis also showed that DPP4i use did not increase the risk of MPI in different DM severities and comorbidities. Conclusions: According to our large cohort study, DPP4i use is safe for patients with type 2 DM and might not increase the risk of MPI.

Abstract An awareness of antecedents of acceptance of digital contact tracing (DCT) can enable healthcare authorities to design appropriate strategies for fighting COVID-19 or other infectious diseases that may emerge in the future. However, mixed results about these antecedents are frequently reported. Most prior DCT acceptance review studies lack statistical synthesis of their results. This study aims to undertake a systematic review and meta-analysis of antecedents of DCT acceptance and investigate potential moderators of these antecedents. By searching multiple databases and filtering studies by using both inclusion and exclusion criteria, 76 and 25 studies were included for systematic review and meta-analysis, respectively. Random-effects models were chosen to estimate meta-analysis results since Q, I 2 , and H index signified some degree of heterogeneity. Fail-safe N was used to assess publication bias. Most DCT acceptance studies have focused on DCT related factors. Included antecedents are all significant predictors of DCT acceptance except for privacy concerns and fear of COVID-19. Subgroup analysis showed that individualism/collectivism moderate the relationships between norms/privacy concerns and intention to use DCT. Based on the results, the mean effect size of antecedents of DCT acceptance and the potential moderators may be more clearly identified. Appropriate strategies for boosting the DCT acceptance rate can be proposed accordingly.

Summary: In this research, we aimed to harness machine learning to predict the imminent risk of acute exacerbation in chronic obstructive pulmonary disease (AECOPD) patients. Utilizing retrospective data from electronic medical records of two Taiwanese hospitals, we identified 26 critical features. To predict 3- and 6-month AECOPD occurrences, we deployed five distinct machine learning algorithms alongside ensemble learning. The 3-month risk prediction was best realized by the XGBoost model, achieving an AUC of 0.795, whereas the XGBoost was superior for the 6-month prediction with an AUC of 0.813. We conducted an explainability analysis and found that the episode of AECOPD, mMRC score, CAT score, respiratory rate, and the use of inhaled corticosteroids were the most impactful features. Notably, our approach surpassed predictions that relied solely on CAT or mMRC scores. Accordingly, we designed an interactive prediction system that provides physicians with a practical tool to predict near-term AECOPD risk in outpatients.

Background: A growing population of individuals diagnosed with idiopathic pulmonary fibrosis (IPF) are receiving treatment with nintedanib and pirfenidone. The aim of our study was to assess the incidence of drug-induced liver injury (DILI) associated with the use of pirfenidone and nintedanib in patients with IPF in Taiwan.Methods: We collected a cohort of adult patients diagnosed with IPF between 2017 and 2020. The research outcomes involved assessing the incidence of DILI in patients treated with nintedanib or pirfenidone. Poisson regression analysis was employed to estimate incidence rates, with and without adjustments for covariates, to calculate and present both unadjusted and adjusted incidence rate ratios (IRRs).Results: The risk of DILI was greater in patients who received nintedanib than in those who received pirfenidone during the 1-year follow-up. Patients treated with nintedanib exhibited a heightened risk of DILI based on inpatient diagnoses using specific codes after adjusting for variables such as gender, age group, comorbidities and concomitant medications, with an adjusted incidence rate ratio (aIRR) of 3.62 (95% confidence interval (CI) 1.11–11.78). Similarly, the risk of DILI was elevated in patients treated with nintedanib according to a per-protocol Poisson regression analysis of outcomes identified from inpatient diagnoses using specific codes. This was observed after adjusting for variables including gender, age group, comorbidities, and concomitant medications, with an aIRR of 3.60 (95% CI 1.11–11.72).Conclusion: Data from postmarketing surveillance in Taiwan indicate that patients who received nintedanib have a greater risk of DILI than do those who received pirfenidone.

Abstract Background With rising incidence of skin cancer and relatively increased mortality rates, an improved diagnosis of such a potentially fatal disease is of vital importance. Although frequently curable, it nevertheless places a considerable burden upon healthcare systems. Among the various types of skin cancers, non-melanoma skin cancer is most prevalent. Despite such prevalence and its associated cost, scant proof concerning the diagnostic accuracy via Artificial Intelligence (AI) for non-melanoma skin cancer exists. This study meta-analyzes the diagnostic test accuracy of AI used to diagnose non-melanoma forms of skin cancer, and it identifies potential covariates that account for heterogeneity between extant studies. Methods Various electronic databases (Scopus, PubMed, ScienceDirect, SpringerLink, and Dimensions) were examined to discern eligible studies beginning from March 2022. Those AI studies predictive of non-melanoma skin cancer were included. Summary estimates of sensitivity, specificity, and area under receiver operating characteristic curves were used to evaluate diagnostic accuracy. The revised Quality Assessment of Diagnostic Studies served to assess any risk of bias. Results A literature search produced 39 eligible articles for meta-analysis. The summary sensitivity, specificity, and area under receiver operating characteristic curve of AI for diagnosing non-melanoma skin cancer was 0.78, 0.98, & 0.97, respectively. Skin cancer typology, data sources, cross validation, ensemble models, types of techniques, pre-trained models, and image augmentation became significant covariates accounting for heterogeneity in terms of both sensitivity and/or specificity. Conclusions Meta-analysis results revealed that AI is predictive of non-melanoma with an acceptable performance, but sensitivity may become improved. Further, ensemble models and pre-trained models are employable to improve true positive rating.

Atrial fibrillation (AF) commonly occurs in approximately 2% of cancer patients, and the incidence of AF among cancer patients is greater than in the general population. This observational study presented the incidence risk of AF among cancer patients, including specific cancer types, using a population database. The Taiwan Cancer Registry was used to identify cancer patients between 2008 and 2017. The diagnosis of AF was based on the International Classification of Diseases codes (ICD-9-CM: 427.31 or ICD-10-CM: I48.0, I48.1, I48.2, and I48.91) in Taiwan national health insurance research datasets. The incidence of developing AF in the cancer population was calculated as the number of new-onset AF cases per person-year of follow-up during the study period. The overall incidence of AF among cancer patients was 50.99 per 100,000 person-years. Patients aged older than 65 years and males had higher AF incidence rates. Lung cancer males and esophageal cancer females showed the highest AF incidence risk (185.02 and 150.30 per 100,000 person-years, respectively). Our findings identified esophageal, lung, and gallbladder cancers as the top three cancers associated with a higher incidence of AF. Careful monitoring and management of patients with these cancers are crucial for early detection and intervention of AF.

Fireflies produce light through luciferase-catalyzed reactions involving luciferin, oxygen, and adenosine triphosphate, distinct from other luminescent organisms. This unique feature has revolutionized molecular biology and physiology, serving as a valuable tool for cellular research. Luciferase-based bioluminescent imaging enabled the creation of transgenic animals, such as Firefly Rats. Firefly Rats, created in 2006, ubiquitously express luciferase and have become a critical asset in scientific investigations. These rats have significantly contributed to transplantation and tissue engineering studies. Their low immunogenicity reduces graft rejection risk, making them ideal for long-term tracking of organ/tissue/cellular engraftments. Importantly, in the islet transplantation setting, the ubiquitous luciferase expression in these rats does not alter islet morphology or function, ensuring accurate assessments of engrafted islets. Firefly Rats have illuminated the path of transplantation research worldwide for over a decade and continue accelerating scientific advancements in many fields.

Background: Surgical patients with aortic dissection often require multiple antihypertensive drugs to control blood pressure. However, the prescription pattern and effectiveness of antihypertensive drugs for these patients are unclear. We aimed to investigate the prescription pattern and effectiveness of different classes of antihypertensive drugs in surgical patients with aortic dissection.Methods: Newly diagnosed aortic dissection patients who underwent surgery, aged >20 years, from 1 January 2012 to 31 December 2017 were identified. Patients with missing data, in-hospital mortality, aortic aneurysms, or congenital connective tissue disorders, such as Marfan syndrome, were excluded. Prescription patterns of antihypertensive drugs were identified from medical records of outpatient visits within 90 days after discharge. Antihypertensive drugs were classified into four classes: 1) β-blockers, 2) calcium channel blockers (CCBs), 3) renin–angiotensin system, and 4) other antihypertensive drugs. Patients were classified according to the number of classes of antihypertensive drugs as follows: 1) class 0, no exposure to antihypertensive drugs; 2) class 1, antihypertensive drugs of the same class; 3) class 2, antihypertensive drugs of two classes; 4) class 3, antihypertensive drugs of three classes; or 5) class 4, antihypertensive drugs of four classes. The primary composite outcomes included rehospitalization associated with aortic dissection, death due to aortic dissection, and all-cause mortality.Results: Most patients were prescribed two (28.87%) or three classes (28.01%) of antihypertensive drugs. In class 1, β-blockers were most commonly used (8.79%), followed by CCBs (5.95%). In class 2, β-blockers+CCB (10.66%) and CCB+RAS (5.18%) were the most common drug combinations. In class 3, β-blockers + CCB+RAS (14.84%) was the most prescribed combination. Class 0 had a significantly higher hazard of the composite outcome (HR, 2.1; CI, 1.46–3.02; p < 0.001) and all-cause mortality (HR, 2.34; CI, 1.56–3.51; p < 0.001) than class 1. There were no significant differences in hazards for rehospitalization associated with aortic dissection among classes.Conclusion: Among operated patients with type A aortic dissection, no specific type of antihypertensive drug was associated with a better outcome, whereas among those with type B aortic dissection, the use of β-blockers and CCBs was related to a significantly lower risk of the composite outcome.

Bronchiectasis is a common comorbidity in chronic obstructive pulmonary disease (COPD). There are limited data regarding the incidence of bronchiectasis in COPD. The purpose of the study was to use a nationwide database to evaluate the incidence of bronchiectasis in COPD in Taiwan. We used a cohort of 2,000,000 individuals followed from 2005 to 2018. Patients with COPD diagnosed between January 1, 2011, and December 31, 2017, were selected, and those with bronchiectasis before COPD were excluded. In total, 134,366 patients with COPD were enrolled, and propensity score matching was used to ensure homogeneity of baseline characteristics between the COPD and non-COPD groups. The incidence rate of bronchiectasis was higher in the COPD group than in the non-COPD group (87.83 vs 69.80 per 10,000 person-years). The adjusted hazard ratio (1.9; 95% confidence interval 1.75–2.05; P < 0.001) of bronchiectasis indicated that the risk of bronchiectasis was 1.9 times higher for patients with COPD than for patients without COPD. In the COPD group, the age-stratified incidence rates of bronchiectasis increased with age (55.01, 80.92, 101.52, and 105.23 for 40–49, 50–59, 60–69, and over 70 years, respectively). The incidence of bronchiectasis was higher in patients with COPD than in the general population, the risk of bronchiectasis increased with age in COPD, and post-tuberculosis status was an important risk factor for bronchiectasis.

ObjectivesWe assessed the efficacies of various corticosteroid treatments for preventing postexubation stridor and reintubation in mechanically ventilated adults with planned extubation.MethodsWe searched the Pubmed, Embase, the Cochrane databases and ClinicalTrial.gov registration for articles published through September 29, 2022. Only randomized controlled trials (RCTs) that compared the clinical efficacies of systemic corticosteroids and other therapeutics for preventing postextubation stridor and reintubation were included. The primary outcome was postextubation stridor and the secondary outcome was reintubation.ResultsThe 11 assessed RCTs reported 4 nodes: methylprednisolone, dexamethasone, hydrocortisone, and placebo, which yielded 3 possible pairs for comparing the risks of post extubation stridor and 3 possible pairs for comparing the risks of reintubation. The risk of postextubation stridor was significantly lower in dexamethasone- and methylprednisolone-treated patients than in placebo-treated patients (dexamethasone: OR = 0.39; 95% CI = 0.22–0.70; methylprednisolone: OR = 0.22; 95% CI = 0.11–0.41). The risk of postextubation stridor was significantly lower in methylprednisolone-treated patients than in hydrocortisone-treated: OR = 0.24; 95% CI = 0.08–0.67) and dexamethasone-treated patients: OR = 0.55; 95% CI = 0.24–1.26). The risk of reintubation was significantly lower in dexamethasone- and methylprednisolone-treated patients than in placebo-treated patients: (dexamethasone: OR = 0.34; 95% CI = 0.13–0.85; methylprednisolone: OR = 0.42; 95% CI = 0.25–0.70). Cluster analysis showed that dexamethasone- and methylprednisolone-treated patients had the lowest risks of stridor and reintubation. Subgroup analyses of patients with positive cuff-leak tests showed similar results.ConclusionsMethylprednisolone and dexamethasone were the most effective agents against postextubation stridor and reintubation.

In this report, we introduce a 1D photonic crystal (PhC) nanocavity with waveguide-like strain amplifiers within a soft polydimethylsiloxane substrate, presenting it as a potential candidate for highly sensitive pressure and position optical sensors. Due to its substantial optical wavelength response to uniform pressure, laser emission from this nanocavity enables the detection of a minimum applied uniform pressure of 1.6‰ in experiments. Based on this feature, we further studied and elucidated the distinct behaviors in wavelength shifts when applying localized pressure at various positions relative to the PhC nanocavity. In experiments, by mapping wavelength shifts of the PhC nanolaser under localized pressure applied using a micro-tip at different positions, we demonstrate the nanocavity’s capability to detect minute position differences, with position-dependent minimum resolutions ranging from tens to hundreds of micrometers. Furthermore, we also propose and validate the feasibility of employing the strain amplifier as an effective waveguide for extracting the sensing signal from the nanocavity. This approach achieves a 64% unidirectional coupling efficiency for leading out the sensing signal to a specific strain amplifier. We believe these findings pave the way for creating a highly sensitive position-sensing module that can accurately identify localized pressure in a planar space.

The global incidence of early-onset colorectal cancer (EO-CRC) is increasing. Although the mortality rate is relatively stable, some comorbidities have been associated with a higher mortality rate. This study estimated the mortality risk in patients with EO-CRC with various comorbidities using real-world data to identify the high-risk group using Cox proportional regression for overall and cancer-specific mortality. The incidence rate of EO-CRC significantly increased from 6.04 per 100,000 population in 2007 to 12.97 per 100,000 population in 2017. The five-year overall mortality rate was 101.50 per 1000 person year and the cancer-specific mortality rate was 94.12 per 1000 person year. Patients with cerebrovascular disease (CVD) had a higher mortality risk (hazard ratio (HR): 1.68; 95% confidence interval (CI): 1.25-2.28; p=0.0007). After subgroup analyses based on age, sex, clinical stage, and treatment type, patients with CVD had a higher overall mortality risk compared to non-CVD patients, except for patients undergoing surgery and chemotherapy. Patients with chronic kidney disease had a higher mortality risk in the early clinical stages (HR: 2.31; 95% CI: 1.08-4.96; p=0.0138). Patients who underwent radiotherapy had a higher overall mortality risk (HR: 1.38; 95% CI: 1.04-1.85; p=0.0285) than those without liver disease. Identifying specific comorbidity mortality risks in patients with EO-CRC allows for risk stratification when screening target groups and may lower disease mortality.

BackgroundLung cancer is one of the leading causes of cancer death worldwide, and tuberculosis (TB) is a common pre-existing disease. However, there is scarce literature studying the mortality risk in patients with prior TB and subsequent lung cancer.MethodsWe recruited lung cancer patients from the Taiwan Cancer Registry from 2011 to 2015 and classified them into two groups according to presence or absence of prior TB. We then matched them in a ratio of 1:4 using the exact matching approach. The mortality risk within 3 years after diagnosis of lung cancer was analyzed and compared between these two groups.ResultsDuring the study period, 43,472 patients with lung cancer were recruited, and of these, 1,211 (2.79%) patients had prior TB. After matching, this cohort included 5,935 patients with lung cancer in two groups: patients with prior TB before lung cancer (n = 1,187) and those without (n = 4,748). After controlling for demographic factors and comorbidities, the patients with prior TB had increased adjusted hazard ratios of 1.13 (95% CI: 1.04–1.23) and 1.11 (1.02–1.21) for all-cause and cancer-specific 3-year mortality, respectively, compared to the lung cancer patients without prior TB. Duration between TB and lung cancer (3 years) had no differences for mortality risk.ConclusionIn the present study, 2.79% patients with lung cancer had prior TB, which was associated with higher 3-year mortality after they developed lung cancer. The mortality risk with prior TB did not decrease even if >3 years passed before diagnosis of lung cancer.

The emerging challenges of global health constantly puts forward new requirements for cultivating medical talents. From the perspective of great health, the First Affiliated Hospital of Sun Yat-sen University aims at cultivating top-notch and innovative medical talents for the future. Since 2018, the hospital has been inheriting and innovating the model of training medical elites and has explored and implemented the clinical postdoctoral program. This program relies on the platform of progressive medical training of the relatively mature 'college system' initiated by our hospital. By regrouping the high-quality interdisciplinary faculty team, the platform optimizes the 'outcome-based' advanced training system and builds effective evaluation and the assessment system, to comprehensively strengthen clinical postdoctoral trainees' abilities of clinical and scientific research and teaching. The program provides reference for the cultivation of high-level medical elites.

Background: Lung cancer patients are high-risk for active tuberculosis (TB); however, fragility and drug-drug interaction might lead to TB treatment interruption. TB treatment incompletion occurrence and predictors among lung cancer patients remain unclear. Methods: We recruited lung cancer patients with new-onset TB from Taiwan Cancer Registry and Taiwanese National Health Insurance 2007–2015 databases. TB treatment incompletion was the identified primary outcome, and associated risk factors were analyzed. Results: A total of 1155 lung cancer patients with new-onset TB were identified and classified as treatment incompletion (n=706, 61.13%) or completion (n=449). Gender and age distribution was similar in both groups. Under multivariable logistic regression, advanced cancer (stage III and IV) and no first-line TB drugs use were independent factors for treatment incompletion; but older age was not significant. For patients surviving >1 year since TB diagnosis, independent factors for treatment incompletion included no first-line TB drugs use (except pyrazinamide) and absence of hypertension. Cancer stage had borderline significance. Conclusions: TB treatment incompletion occurred in 61.13% of lung cancer patients. Clinicians should carefully titrate anti-TB medications and monitor side effects in lung cancer patients, especially those with treatment incompletion risk factors, to avoid treatment interruption due to fragility and/or drug intolerance.

Abstract Pulmonary function testing (PFT) allows for quantitative analysis of lung function. However, as a result of the coronavirus disease 2019 (COVID-19) pandemic, a majority of international medical societies have postponed PFTs in an effort to mitigate disease transmission, complicating the continuity of care in high-risk patients diagnosed with COVID-19 or preexisting lung pathologies. Here, we describe the development of a non-contact wearable pulmonary sensor for pulmonary waveform analysis, pulmonary volume quantification, and crude thoracic imaging using the eddy current (EC) phenomenon. Statistical regression analysis is performed to confirm the predictive validity of the sensor, and all data are continuously and digitally stored with a sampling rate of 6,660 samples/second. Wearable pulmonary function sensors may facilitate rapid point-of-care monitoring for high-risk individuals, especially during the COVID-19 pandemic, and easily interface with patient hospital records or telehealth services.

Abstract Existing paradigms for stroke diagnosis typically involve computed tomography (CT) imaging to classify ischemic versus hemorrhagic stroke variants, as treatment for these subtypes varies widely. Delays in diagnosis and transport of unstable patients may worsen neurological status. To address these issues, we describe the development of a rapid, portable, and accurate eddy current damping (ECD) stroke sensor. Copper wire was wound to create large (11.4 cm), medium (4.5 cm), and small (1.5 cm) solenoid coils with varying diameters, with each connected to an inductance-to-digital converter. Eight human participants were recruited between December 15, 2019 and March 15, 2020, including two hemorrhagic stroke, two ischemic stroke, one subarachnoid hemorrhage, and three control participants. Observers were blinded to lesion type and location. A head cap with 8 horizontal scanning paths was placed on the patient. The sensor was tangentially rotated across each row on the patient’s head circumferentially. Consent, positioning, and scanning with the sensor took roughly 15 min from start to end for each participant and all scanning took place at the patient bedside. The ECD sensor accurately classified and imaged each of the varying stroke types in each patient. The sensor additionally detected ischemic and hemorrhagic lesions located deep inside the brain, and its range is selectively tunable during sensor design and fabrication.

Abstract After traumatic brain injury (TBI), an inflammatory response in the brain might affect the immune system. The risk of pulmonary infection reportedly increases in patients with TBI. We aimed to evaluate the risk of tuberculosis (TB) in patients with TBI in Taiwan. All participants were selected from the intensive care unit (ICU). Patients with TBI were defined as patients in ICU with intracranial injury, and comparison cohort were patients in ICU without TBI diagnosis. There was a significant difference in TB risk between the patients with TBI and the comparison cohort according to age and the Charlson’s comorbidity index (CCI) score. Thus, we divided patients based on CCI into three groups for further analysis: mild (CCI = 0), moderate (CCI = 1/2), severe (CCI > 2). Mild-CCI group had a lower TB incidence rate (0.74%) and longer time to TB development (median: 2.43) than the other two groups. Moderate-CCI group had 1.52-fold increased risk of TB infection (p

Background: Colorectal cancer is one of the leading cancers worldwide. This study aimed to investigate the mortality differences between 2 primary tumor locations, the proximal/distal colon and rectosigmoid junction (RSJ)/rectum, after adjusting for comorbidities. Methods: The Taiwan Cancer Registry linked with Taiwan’s National Health Insurance Research Database was used to estimate the 5-year mortality rate among patients with colorectal cancer. A total of 73 769 individuals were enrolled in the study, which included 44 234 patients with proximal and distal colon cancers and 29 535 patients with RSJ and rectal cancers. Potential mortality risk was calculated using Cox regression analysis. Results: The mortality rates due to the location of the cancer in the proximal/distal colon and RSJ/rectum were 45.27% and 42.20%, respectively. After adjustment for age, sex, comorbidities, and clinical stages, the proximal/distal colon had a 1.03-fold higher 5-year overall mortality rate than RSJ/rectal cancer (95% confidence interval = 1.00–1.05). Proximal and distal colon cancers had a worse prognosis and survival than RSJ and rectal colon cancers in women and older patients (⩾70 years). Comorbidities had different effects on mortality in the proximal/distal colon and RSJ/rectum. Conclusions: Tumor location is associated with the prognosis of patients with colorectal cancer. It is important to treat patients beyond their cancer treatment, and to manage their comorbidities.

Abstract. We explored the relationship between asthma and early menarche in a representative sample of Korean adolescents. Web-based self-reported data collected from 2006 to 2015 by the Korean Youth Risk Behavior Web-based Survey were used. Menarche status was divided into “early” (

In an effort to help organizations understand consumers, our study deconstructs task–technology fit into two segments: ideal task–technology fit and individual use context–technology fit. Users’ continuous use of cloud-based bookstores is studied through survey methodology to collect consumer experience data related to the use of such cloud-based bookstores. In total, 185 samples were collected. Analytical results demonstrated that both ideal task–technology fit and individual use context–technology fit were significantly associated with the confirmation of users’ expectations as related to cloud-based bookstores. Expectation confirmation and ideal task–technology fit also have a significant link to users’ perceived usefulness and satisfaction, respectively. Furthermore, perceived usefulness significantly predicts satisfaction. Finally, perceived usefulness and satisfaction are also significantly associated with a users’ continuous use of cloud-based bookstores. As a result of this study’s findings, system administrators may foster suitable strategies for an improvement of users’ continuous use of cloud-based bookstores.

Rheumatoid arthritis (RA) can lead to various pulmonary manifestations. Evidence shows the possible association between RA and pleural empyema.

Abstract Background Coronary artery disease is common in patients with end-stage renal disease (ESRD). Patients with ESRD are a high-risk group for cardiac surgery and have increased morbidity and mortality. Most studies comparing ESRD patients receiving coronary artery bypass grafting (CABG) or percutaneous coronary intervention have found that the long-term survival is good in ESRD patients after CABG. The aim of our study was to compare ESRD patients who underwent CABG with the general population who underwent CABG, in terms of prognosis and hospital costs. Methods This study analyzed data from the National Health Insurance Research Database in Taiwan for patients who were diagnosed with ESRD and received CABG (ICD-9-CM codes 585 or 586) between January 1, 2004, and December 31, 2009. The ESRD patients included in this study all received catastrophic illness cards with the major illness listed as ESRD from the Ministry of Health and Welfare in Taiwan. The control subjects were randomly selected patients without ESRD after propensity score matching with ESRD patients according to age, gender, and comorbidities at a 2:1 ratio from the same dataset. Results A total of 48 ESRD patients received CABG, and their mean age was 62.04 ± 10.04 years. Of these patients, 29.2% were aged ≥70 years, and 66.7% were male. ESRD patients had marginally higher intensive care unit (ICU) stays (11.06 vs 7.24 days) and significantly higher ICU costs (28,750 vs 17,990 New Taiwan Dollars (NTD)) than non-ESRD patients. Similarly, ESRD patients had significantly higher surgical costs (565,200 vs. 421,890 NTD), a higher perioperative mortality proportion (10.4% vs 2.1%) and a higher postoperative mortality proportion (33.3% vs 11.5%) than non-ESRD patients. Conclusions After CABG, ESRD patients had a higher risk of mortality than non-ESRD patients, and ICU and surgery costs were also higher among the ESRD patients than among patients without ESRD.

Abstract. By evaluating S100 calcium binding protein A9 (S100A9) and Klebs von den Lungen-6 (KL-6) expression in patients with 4 common interstitial lung diseases (ILDs), we aimed to investigate whether S100A9 or KL-6 can be of any value in the differential diagnosis of these ILDs and simultaneously signal the disease progression. We collected the data of patients diagnosed with the 4 ILDs and underwent fiber-optic bronchoscopy and BAL in the First Affiliated Hospital, China Medical University from January 2012 to December 2020. The data related to BGA, C-reactive protein, pulmonary function test, total number and fraction of cells, T lymphocyte subsets in bronchoalveolar lavage fluid (BALF), and the expression of S100A9 and KL-6 in BALF and serum were collected. We analyzed, whether S100A9 or KL-6 could serve as a biomarker for differential diagnosis between the 4 common ILDs; whether the levels of S100A9 and KL-6 correlated with each other; whether they were correlated with other clinical parameters and disease severity. This study included 98 patients, 37 patients with idiopathic pulmonary fibrosis (IPF), 12 with hypersensitivity pneumonitis, 13 with connective tissue disease-associated ILD, and 36 with sarcoidosis (SAR): stage I (18), stage II (9), stage III (5), and stage IV (4). The expression of KL-6 in BALF was significantly higher in IPF patients than other 3 groups (all P-value .05). The levels of S100A9 in BALF of IPF patients was positively and significantly correlated with KL-6 expression and the percentage of neutrophils in BALF (P-value

Background: Tuberculosis (TB) is one of the leading causes of death worldwide and a major cause of ill health. Without treatment, the mortality rate of TB is approximately 50%; with treatment, most patients with TB can be cured. However, anti-TB drug treatments may result in many adverse effects. Therefore, it is important to detect and predict these adverse effects early. Our study aimed to build models using an artificial intelligence/machine learning approach to predict acute hepatitis, acute respiratory failure, and mortality after TB treatment. Materials and Methods: Adult patients (age ≥ 20 years) who had a TB diagnosis and received treatment from January 2004 to December 2021 were enrolled in the present study. Thirty-six feature variables were used to develop the predictive models with AI. The data were randomly stratified into a training dataset for model building (70%) and a testing dataset for model validation (30%). These algorithms included XGBoost, random forest, MLP, light GBM, logistic regression, and SVM. Results: A total of 2248 TB patients in Chi Mei Medical Center were included in the study; 71.7% were males, and the other 28.3% were females. The mean age was 67.7 ± 16.4 years. The results showed that our models using the six AI algorithms all had a high area under the receiver operating characteristic curve (AUC) in predicting acute hepatitis, respiratory failure, and mortality, and the AUCs ranged from 0.920 to 0.766, 0.884 to 0.797, and 0.834 to 0.737, respectively. Conclusions: Our AI models were good predictors and can provide clinicians with a valuable tool to detect the adverse prognosis in TB patients early.

Background: Overactive bladder (OAB) syndrome is defined as urinary urgency, with or without urge incontinence in the absence of an underlying pathological or metabolic cause. Treatment for OAB involves anti-muscarinic agents and beta 3-adrenoceptor agonists. As a previous study showed that treatment may increase the risk of urinary tract infection (UTI), we conducted a nationwide, population-based, retrospective study to assess UTI risk associated with OAB medication adherence, and different types of OAB medication.Methods: The source of data was medical records from National Health Insurance Research Database (NHIRD). Patients who were diagnosed with OAB in outpatient records from January 1, 2014 to December 31, 2016 were included. Outpatient visits included an attendance at primary care or the emergency department. The index date was the first prescription medication for OAB treatment after diagnosis. The targeted population was those diagnosed with OAB, and targeted drugs were anti-muscarinic agent (including flavoxate, oxybutynin, propiverine, solifenacin, tolterodine, and trospium) and mirabegron. Adherence was assessed based on the proportion of days covered in 12 months among mirabegron and anti-muscarinic agents. A multivariate Cox proportional-hazards model was used to compare the risk of UTI with OAB medication adherence, and different types of OAB medication.Results: There were 39,975 outpatients diagnosed with OAB in the database from 2014 to 2016. Excluding those younger than 20 years old and for whom the information was incomplete in the database, 21,869 patients were included in the final OAB cohort. Overall, risk of UTI was not influenced by the targeted drugs or adherence during the follow-up period, regardless of UTI history or sex.Conclusion: OAB is a common problem in Taiwan. After 12 months of follow-up, there was no difference between anticholinergic medications and beta-3 agonists, nor between high and low adherence in the risk of UTI.

Abstract Background This study explored the possible antecedents that will motivate hospital employees’ compliance with privacy policy related to electronic medical records (EMR) from a deterrence perspective. Further, we also investigated the moderating effect of computer monitoring on relationships among the antecedents and the level of hospital employees’ compliance intention. Methods Data was collected from a large Taiwanese medical center using survey methodology. A total of 303 responses was analyzed via hierarchical regression analysis. Results The results revealed that sanction severity and sanction certainty significantly predict hospital employees’ compliance intention, respectively. Further, our study found external computer monitoring significantly moderates the relationship between sanction certainty and compliance intention. Conclusions Based on our findings, the study suggests that healthcare facilities should take proactive countermeasures, such as computer monitoring, to better protect the privacy of EMR in addition to stated privacy policy. However, the extent of computer monitoring should be kept to minimum requirements as stated by relevant regulations.

Abstract Background Androgen deprivation therapy (ADT) in the treatment of prostate cancer may be associated with an increased risk of thromboembolic disease. The aim of our study was to investigate the association of ADT in the treatment of prostate cancer with ischemic stroke risk. Methods We identified individuals older than 20 years of age who were newly diagnosed with prostate cancer between January 1, 2005, and December 31, 2012. Patients who experienced ischemic stroke or transient ischemic stroke before the index date were excluded. Patients who received at least one prescription for ADT within 6 months were defined as the ADT user group. Patients who did not receive at least one prescription for ADT within 6 months were defined as the ADT nonuser group. The patients were followed until the first occurrence of one of the primary outcome measures (ischemic stroke or death) or until December 31, 2013. The primary composite outcome was the time to any cause of death or ischemic stroke. Results There was no significant difference in the primary composite outcomes in the prostate cancer patients between the ADT user and nonuser groups. Prostate cancer patients who received ADT had a higher mortality rate than those who were not treated with ADT, and the adjusted hazard ratio was 1.907 (95% confidence interval: 1.278–2.844; P = 0.0016) after adjusting for age, comorbidities and comedication use. Conclusion ADT in the treatment of prostate cancer may not be associated with an increased risk of ischemic stroke. The differences in thromboembolic effects in cardiovascular disease and ischemic stroke secondary to ADT should be further discussed and evaluated prospectively.

Abstract Background Coronary artery aneurysm (CAA) is a rare disease, and there are limited data on prescribing patterns for CAA. The aim of our study was to investigate prescribing patterns for CAA in Taiwan via the National Health Insurance Research Database (NHIRD). Methods We included all CAA patients in Taiwan from 2005 to 2011. Data from 1 year before and after the CAA diagnosis were used to analyze examinations, comorbidities and prescribing patterns. Results A total of 1397 patients diagnosed with CAA were enrolled in our study. Most pediatric patients with CAA were diagnosed with Kawasaki disease (95.7%). In pediatric CAA patients, the utilization rates of aspirin and gamma globulins were 82.9 and 53.6%, respectively, after CAA diagnosis. Among the antithrombotic agents, aspirin was used most commonly, followed by dipyridamole (16.9%), heparin (5.8%) and warfarin (4.6%). In adult CAA patients, common comorbidities included hypertension (63.4%), hyperlipidemia (39.6%), and diabetes mellitus (26.1%). Coronary atherosclerosis was identified in 72.5% of adult patients after CAA diagnosis. Antithrombotic agents, particularly aspirin, clopidogrel and heparin, were prescribed more frequently after CAA diagnosis. Among the prescribed medications, aspirin (75.8%), β-blockers (48.3%), statins (47.6%), metformin (14.4%), sulfonylureas (14.4%) and isosorbide mononitrate (32.9%) were frequently observed in each category. Conclusions Kawasaki disease was the main cause of CAA in pediatric patients, and coronary artery disease was the most common comorbidity in adult CAA patients. The most commonly used antithrombic agent after CAA diagnosis was aspirin in both adult and pediatric patients.

Abstract Background Medications are frequently used for treating schizophrenia, however, anti-psychotic drug use is known to lead to cases of pneumonia. The purpose of our study is to build a model for predicting hospital-acquired pneumonia among schizophrenic patients by adopting machine learning techniques. Methods Data related to a total of 185 schizophrenic in-patients at a Taiwanese district mental hospital diagnosed with pneumonia between 2013 ~ 2018 were gathered. Eleven predictors, including gender, age, clozapine use, drug-drug interaction, dosage, duration of medication, coughing, change of leukocyte count, change of neutrophil count, change of blood sugar level, change of body weight, were used to predict the onset of pneumonia. Seven machine learning algorithms, including classification and regression tree, decision tree, k-nearest neighbors, naïve Bayes, random forest, support vector machine, and logistic regression were utilized to build predictive models used in this study. Accuracy, area under receiver operating characteristic curve, sensitivity, specificity, and kappa were used to measure overall model performance. Results Among the seven adopted machine learning algorithms, random forest and decision tree exhibited the optimal predictive accuracy versus the remaining algorithms. Further, six most important risk factors, including, dosage, clozapine use, duration of medication, change of neutrophil count, change of leukocyte count, and drug-drug interaction, were also identified. Conclusions Although schizophrenic patients remain susceptible to the threat of pneumonia whenever treated with anti-psychotic drugs, our predictive model may serve as a useful support tool for physicians treating such patients.

Information security has come to the forefront as an organizational priority since information systems are considered as some of the most important assets for achieving competitive advantages. Despite huge capital expenditures devoted to information security, the occurrence of security breaches is still very much on the rise. More studies are thus required to inform organizations with a better insight on how to adequately promote information security. To address this issue, this study investigates important factors influencing hospital staff’s adherence to Information Security Policy (ISP). Deterrence theory is adopted as the theoretical underpinning, in which punishment severity and punishment certainty are recognized as the most significant predictors of ISP adherence. Further, this study attempts to identify the antecedents of punishment severity and punishment certainty by drawing from upper echelon theory and well-acknowledged international standards of IS security practices. A survey approach was used to collect 299 valid responses from a large Taiwanese healthcare system, and hypotheses were tested by applying partial least squares-based structural equation modeling. Our empirical results show that Security Education, Training, and Awareness (SETA) programs, combined with internal auditing effectiveness are significant predictors of punishment severity and punishment certainty, while top management support is not. Further, punishment severity and punishment certainty are significant predictors of hospital staff’s ISP adherence intention. Our study highlights the importance of SETA programs and internal auditing for reinforcing hospital staff’s perceptions on punishment concerning ISP violation, hospitals can thus propose better internal strategies to improve their staff’s ISP compliance intention accordingly.

Background: Patients with chronic obstructive pulmonary disease (COPD) are at risk for pulmonary hypertension (PH). The aim of our study was to investigate the benefit of statins for PH in patients with COPD.Methods: The study enrolled 23 million individuals from Taiwan’s population database from January 1, 2002, to December 31, 2017. COPD patients who met the inclusion criteria were enrolled, and patients with lung cancer, less than one year of observation, specific drug therapy for PH and lung transplantation were excluded.Results: A total of 643,131 COPD patients were included in the study, and only 12,308 patients developed PH during follow-up. Based on the inclusion and exclusion criteria, 8,577 PH patients were included in the cohort of patients with PH related to COPD for analysis. According to the definition of statin exposure, the final study population had 1,487 statin users and 7,090 statin non-users. The statin user group had a lower mortality related to PH than the non-user group (3.87 vs. 5.55 per 100 person-years, p < 0.001). The mortality rate for PH in the multivariate analysis (aHR = 0.78, 95% CI = 0.62–0.98, p = 0.046) was significantly lower for statin users than for non-users.Conclusion: Statins seem to benefit patients with PH and COPD.

Purpose: Many comorbidities, including depression, anxiety, and insomnia, occur in patients with chronic obstructive pulmonary disease (COPD). These patients may be prescribed benzodiazepines (BZDs). However, there are some concerns that benzodiazepines increase the risk of drug overdose, hypercapnic respiratory failure, acute exacerbation and increased mortality. The aim of our study was to evaluate the drug safety of BZDs in patients with COPD.Methods: We used the National Health Insurance Research database in Taiwan from 2002 to 2016 to perform a retrospective cohort study. We enrolled patients who were exposed to the first prescription of BZDs, non-BZDs or a combination (mix user) after COPD diagnosis. We performed 1:1:1 propensity score matching in three groups. The outcomes were COPD with acute exacerbation and all-cause mortality. Poisson regression analysis was performed to evaluate the incidence rate ratios for the outcomes in the groups.Results: After propensity score matching, there were 2,856 patients in each group. After adjusting for confounding factors, we found that compared to BZD users, non-BZD and mix users had nonsignificant differences in outpatient management of acute exacerbations, hospitalization management of acute exacerbations, emergency department management of acute exacerbations and all-cause mortality. BZD and mix groups showed significantly increased admission for acute exacerbation of COPD compared with that of the nonuser group, with IRRs of 2.52 (95% CI, 1.52–4.18; p = 0.0004) and 2.63 (95% CI, 1.57–4.40; p = 0.0002), respectively.Conclusion: BZD, non-BZD, and mix users showed increased COPD-related respiratory events compared to nonusers in Asian subjects.

Background Numerous studies have utilized machine-learning techniques to predict the early onset of type 2 diabetes mellitus. However, fewer studies have been conducted to predict an appropriate diagnosis code for the type 2 diabetes mellitus condition. Further, ensemble techniques such as bagging and boosting have likewise been utilized to an even lesser extent. The present study aims to identify appropriate diagnosis codes for type 2 diabetes mellitus patients by means of building a multi-class prediction model which is both parsimonious and possessing minimum features. In addition, the importance of features for predicting diagnose code is provided. Methods This study included 149 patients who have contracted type 2 diabetes mellitus. The sample was collected from a large hospital in Taiwan from November, 2017 to May, 2018. Machine learning algorithms including instance-based, decision trees, deep neural network, and ensemble algorithms were all used to build the predictive models utilized in this study. Average accuracy, area under receiver operating characteristic curve, Matthew correlation coefficient, macro-precision, recall, weighted average of precision and recall, and model process time were subsequently used to assess the performance of the built models. Information gain and gain ratio were used in order to demonstrate feature importance. Results The results showed that most algorithms, except for deep neural network, performed well in terms of all performance indices regardless of either the training or testing dataset that were used. Ten features and their importance to determine the diagnosis code of type 2 diabetes mellitus were identified. Our proposed predictive model can be further developed into a clinical diagnosis support system or integrated into existing healthcare information systems. Both methods of application can effectively support physicians whenever they are diagnosing type 2 diabetes mellitus patients in order to foster better patient-care planning.