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Abstract Background Hyperthyroidism is frequently under-recognized and leads to heart failure and mortality. Timely identification of high-risk patients is a prerequisite to effective antithyroid therapy. Since the heart is very sensitive to hyperthyroidism and its electrical signature can be demonstrated by electrocardiography, we developed an artificial intelligence model to detect hyperthyroidism by electrocardiography and examined its potential for outcome prediction. Methods The deep learning model was trained using a large dataset of 47,245 electrocardiograms from 33,246 patients at an academic medical center. Patients were included if electrocardiograms and measurements of serum thyroid-stimulating hormone were available that had been obtained within a three day period. Serum thyroid-stimulating hormone and free thyroxine were used to define overt and subclinical hyperthyroidism. We tested the model internally using 14,420 patients and externally using two additional test sets comprising 11,498 and 596 patients, respectively. Results The performance of the deep learning model achieves areas under the receiver operating characteristic curves (AUCs) of 0.725–0.761 for hyperthyroidism detection, AUCs of 0.867–0.876 for overt hyperthyroidism, and AUC of 0.631–0.701 for subclinical hyperthyroidism, superior to a traditional features-based machine learning model. Patients identified as hyperthyroidism-positive by the deep learning model have a significantly higher risk (1.97–2.94 fold) of all-cause mortality and new-onset heart failure compared to hyperthyroidism-negative patients. This cardiovascular disease stratification is particularly pronounced in subclinical hyperthyroidism, surpassing that observed in overt hyperthyroidism. Conclusions An innovative algorithm effectively identifies overt and subclinical hyperthyroidism and contributes to cardiovascular risk assessment.

Abstract Pioglitazone is an insulin resistance inhibitor widely used as monotherapy or combined with metformin or insulin in treating type 2 diabetes mellitus (T2DM). This study further investigated the relationship between pioglitazone use and the risk of developing Alzheimer's disease (AD) in patients newly diagnosed with T2DM, and examined the potential impact of insulin use on this association. Data were extracted from the National Health Insurance Research Database (NHIRD) of Taiwan. Our data exhibited that the risk of developing AD in the pioglitazone group was 1.584-fold (aHR = 1.584, 95% CI 1.203–1.967, p

Abstract Background Identifying candidates responsive to treatment is important in lupus nephritis (LN) at the renal flare (RF) because an effective treatment can lower the risk of progression to end-stage kidney disease. However, machine learning (ML)-based models that address this issue are lacking. Methods Transcriptomic profiles based on DNA microarray data were extracted from the GSE32591 and GSE112943 datasets. Comprehensive bioinformatics analyses were performed to identify disease-defining genes (DDGs). Peripheral blood samples (GSE81622, GSE99967, and GSE72326) were used to evaluate the effect of DDGs. Single-sample gene set enrichment analysis (ssGSEA) scores of the DDGs were calculated and correlated with specific immunology genes listed in the nCounter panel. GSE60681 and GSE69438 were used to examine the ability of the DDGs to discriminate LN from other renal diseases. K-means clustering was used to obtain the separate gene sets. The clustering results were extended to data derived using the nCounter technique. The least absolute shrinkage and selection operator (LASSO) algorithm was used to identify genes with high predictive value for treatment response after the first RF in each cluster. LASSO models with tenfold validation were built in GSE200306 and assessed by receiver operating characteristic (ROC) analysis with area under curve (AUC). The models were validated by using an independent dataset (GSE113342). Results Forty-five hub genes specific to LN were identified. Eight optimal disease-defining clusters (DDCs) were identified in this study. Th1 and Th2 cell differentiation pathway was significantly enriched in DDC-6. LCK in DDC-6, whose expression positively correlated with various subsets of T cell infiltrations, was found to be differentially expressed between responders and non-responders and was ranked high in regulatory network analysis. Based on DDC-6, the prediction model had the best performance (AUC: 0.75; 95% confidence interval: 0.44–1 in the testing set) and high precision (0.83), recall (0.71), and F1 score (0.77) in the validation dataset. Conclusions Our study demonstrates that incorporating knowledge of biological phenotypes into the ML model is feasible for evaluating treatment response after the first RF in LN. This knowledge-based incorporation improves the model's transparency and performance. In addition, LCK may serve as a biomarker for T-cell infiltration and a therapeutic target in LN.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has become a global pandemic since December 2019. Most of the patients are mild or asymptomatic and recovered well as those suffered from other respiratory viruses. SARS-CoV-2 infection is supposed to demonstrate more sequelae. Acute kidney injury (AKI) is common among COVID-19 patients and is associated with disease severity and outcomes. Only a few studies focused on a detailed analysis of kidney damage in asymptomatic or mildly symptomatic COVID-19 patients. Whether any minor viral infection is likely to exhibit similar minor effect on renal function as COVID-19 is still unclear, and the definite pathophysiology of viral invasion is not fully understood. Currently, the proposed mechanisms of AKI include direct effects of virus on kidney, dysregulated immune response, or as a result of multi-organs failure have been proposed. This study will discuss the difference between COVID-19 and other viruses, focusing on proposed mechanisms, biomarkers and whether it matters with clinical significance.

Abstract Trichomonas vaginalis infection is one of the most widespread sexually transmitted infections in the world. There are approximately 276 million cases worldwide. Most men remain undiagnosed and untreated because they are asymptomatic. The chronic inflammation induced by persistent infection may increase the risk of developing genitourinary cancers. In this study, we aimed to investigate the association between trichomoniasis and benign prostate hyperplasia (BPH), prostate cancer (PCa), and bladder cancer (BC) in Taiwan. We designed a case–control study by using the database of the National Health Insurance program in Taiwan. We used the International Classification of Diseases, 9th Revision classifications to classify all the medical conditions in the case and control groups. All odds ratios (ORs) and 95% confidence intervals (CIs) were analyzed using multivariable logistic regression to adjust for all comorbidities and variables. From 2000 to 2015, we enrolled a total of 62,544 individuals as the case group and 187,632 as the control group. Trichomoniasis exposure had a significant association with BPH and PCa (adjusted OR: BPH = 2.685, 95% CI = 1.233–4.286, P = 0.013; PCa = 5.801, 95% CI = 1.296–26.035, P = 0.016). The relative risk was much higher if patients had both trichomoniasis and depression (adjusted OR = 7.682, 95% CI = 5.730–9.451, P

BackgroundRare cases of de novo or relapsed kidney diseases associated with vaccination against coronavirus disease 2019 (COVID-19) have been increasingly reported. The aim of this study was to report the incidence, etiologies, and outcomes of acute kidney disease (AKD) following COVID-19 vaccination.MethodsThis retrospective study extracted cases from renal registry of a single medical center from 1 March 2021 to 30 April 2022, prior to the significant surge in cases of the Omicron variant of COVID-19 infection in Taiwan. Adult patients who developed AKD after COVID-19 vaccination were included. We utilized the Naranjo score as a causality assessment tool for adverse vaccination reactions and charts review by peer nephrologists to exclude other causes. The etiologies, characteristics, and outcomes of AKD were examined.ResultsTwenty-seven patients (aged 23 to 80 years) with AKD were identified from 1,897 vaccines (estimated rate of 13.6 per 1000 patient-years within the renal registry). A majority (77.8%) of vaccine received messenger RNA-based regimens. Their median (IQR) Naranjo score was 8 (6-9) points, while 14 of them (51.9%) had a definite probability (Naranjo score ≥ 9). The etiologies of AKD included glomerular disease (n = 16) consisting of seven IgA nephropathy, four anti-neutrophil cytoplasmic antibodies-associated glomerulonephritis (AAN), three membranous glomerulonephritis, two minimal change diseases, and chronic kidney disease (CKD) with acute deterioration (n = 11). Extra-renal manifestations were found in four patients. Over a median (IQR) follow-up period of 42 (36.5–49.5) weeks, six patients progressed to end-stage kidney disease (ESKD).ConclusionBesides glomerulonephritis (GN), the occurrence of AKD following COVID-19 vaccination may be more concerning in high-risk CKD patients receiving multiple doses. Patients with the development of de novo AAN, concurrent extra-renal manifestations, or pre-existing moderate to severe CKD may exhibit poorer kidney prognosis.

Concurrent severe rhabdomyolysis and acute liver damage are rarely reported in the setting of acute high-altitude illness (AHAI). We described a 53-year-old healthy mountain climber who experienced headache and dyspnea at the summit of Snow Mountain (Xueshan; 3,886 m above sea level) and presented to the emergency room with generalized malaise, diffuse muscle pain, and tea-colored urine. His consciousness was alert, and he had a blood pressure of 114/74 mmHg, heart rate of 66/min, and body temperature of 36.8°C. Myalgia of the bilateral lower limbs, diminished skin turgor, dry oral mucosa, and tea-colored urine were notable. Urinalysis showed positive occult blood without red blood cells. The most striking blood laboratory data included creatine kinase (CK) 33,765 IU/L, inappropriately high aspartate aminotransferase (AST) 2,882 IU/L and alanine aminotransferase (ALT) 2,259 IU/L (CK/AST ratio 11.7, CK/ALT ratio 14.9), creatinine 1.5 mg/dl, serum urea nitrogen (BUN) 26 mg/dl, total bilirubin 1.7 mg/dl, ammonia 147 μg/ml, lactate 2.5 mmol/L, and prothrombin time 17.8 s. The meticulous search for the underlying causes of acute liver injury was non-revealing. With volume repletion, mannitol use, and urine alkalization coupled with avoidance of nephrotoxic and hepatotoxic agents, his clinical features and laboratory abnormality completely resolved in 3 weeks. Despite rarity, severe rhabdomyolysis and/oracute liver injury as a potential life-threatening condition requiring urgent management may occur in high-altitude hypobaric hypoxia.

Cefazolin-induced neurotoxicity with the documented toxic concentration has not been reported in uremic patients on continuous ambulatory peritoneal dialysis (CAPD). We described an elderly female on CAPD for years presented with newly-onset status epilepticus. Her body weight was 60 kg. And she had received intraperitoneal ceftazidime and cefazolin 1.5 g once daily for her CAPD peritonitis 5 days earlier. She was disoriented but afebrile with normal blood pressure. Laboratory data showed WBC 18,480/uL, pH 6.93, HCO3- 8.5 mmol/L, free Ca2+ 3.5 mmol/L, and albumin 2.8 g/dL. Although antiepileptic drugs and hypocalcemia correction ceased the seizure, her consciousness remained semi-coma. Image studies of brain were unremarkable. Despite undetectable serum ceftazidime, her cefazolin trough level was 149.5 μg/mL. Emergent hemodialysis rapidly resolved her neurological features accompanied by a markedly declined serum cefazolin concentration (28.6 μg/mL). Higher intraperitoneal cefazolin dosing in patients on CAPD may cause drug-induced neurotoxicity with status epilepticus which could be rapidly corrected by hemodialysis.

Severe lactic acidosis, a mitochondrial toxicity caused by the recommended standard dosage of linezolid (LZD), may occur in patients with impaired renal function. We describe an adult male who underwent kidney transplantation with stably impaired renal function, severe dyspnea, and abdominal discomfort. He received a standard oral dose of LZD (600 mg twice daily) and azithromycin for three weeks with a reduced immunosuppressant dose due to pulmonary non-tuberculosis mycobacterial infection. He was alert and afebrile, with a blood pressure of 140/60 mmHg. Pertinent laboratory data showed: pH 7.12, PaCO2 13.6 mmHg; HCO3- 4.3 mmol/L and serum lactate 18.4 mmol/L. His trough serum LZD concentration reached toxic levels (21.4 μg/mL). With hemodialysis, his clinical symptoms improved, with a decline in serum LZD (9.8μg/mL) and lactate (3.2 mmol/L). Chronic standard dose LZD in patients with impaired renal function can lead to life-threatening lactic acidosis, especially in coexisting conditions that reduce LZD metabolism.

Abstract Background The decline of the incidence rate of tuberculosis in Taiwan has been partly attributed to the launch of the directly observed therapy short course (DOTS) program in 2006, followed by the DOTS-Plus in 2007. However, with the phasing out of the specialized tuberculosis care system and the declining incidence, clinical workers in Taiwan might become less familiar with the presentation of tuberculosis. Complementing the patient-pathway analysis with health system delay estimates, the objective of this study is twofold: to estimate the alignment between patient care initiation and the availability of prompt diagnostic and treatment services, and to identify the risk factors of delayed tuberculosis treatment. Methods The study population included all Taiwanese patients with incident tuberculosis in 2013. We (1) identified 11,507 incident tuberculosis patients from the 2013 National TB Registry, and (2) linked 10,932 Taiwanese from the registry to the 2012–2013 National Health Insurance Research Database. We assessed patient’s care-seeking pathways and associated the determinants of health system delay in a Cox model. Results The overall health system delay was 46 days. We found that 20.5 and 3.5% of 10,932 tuberculosis patients were diagnosed and treated respectively at the initial visit to seek care for TB-related symptoms. Risk factors related to the prolonged health system delay included female gender (adjusted HR = 0.921, 95% CI: 0.884, 0.960), age > =65 years (adjusted HR = 0.720, 95% CI: 0.692, 0.750), non-severe (chest X-ray without cavities) (adjusted HR =0.721, 95% CI 0.683–0.760), chronic respiratory diseases (adjusted HR = 0.544, 95% CI: 0.522, 0.566), living in long-term care facilities (adjusted HR = 0.580, 95% CI: 0.525,0.640), an initial visit at a primary care clinic (adjusted HR = 0.588, 95% CI: 0.565, 0.612), and living in southern Taiwan (adjusted HR = 0.887, 95% CI: 0.798, 0.987). Conclusions The low access to TB diagnostic and treatment services at the initial visit and the prolonged health system delay indicate inefficiency in the health care system. Strengthening training of physicians at public hospitals and health workers at nursing homes might improve the efficiency and timeliness of tuberculosis diagnosis and treatment in Taiwan.

The rare and severe adverse effects associated with coronavirus disease of 2019 (COVID-19) vaccination have been under-appreciated, resulting in many instances of inappropriate management. We describe the case of an elderly woman who developed anti-neutrophil cytoplasmic antibody-associated vasculitis with pulmonary renal syndrome approximately 3 weeks after the first dose of COVID-19 mRNA vaccination (Moderna). Her nasopharyngeal polymerase chain reaction test for the COVID-19 RNA virus was negative. Gross hematuria, heavy proteinuria, acute renal failure (serum creatinine up to 6.5 mg/dL), and hemoptysis coupled with a marked increase in serum anti-myeloperoxidase-O antibody were observed. Renal biopsy showed severe vasculitis with pauci-immune crescent glomerulonephritis. The pulmonary hemorrhage was resolved and renal function improved following combined plasma exchange and the administration of systemic steroids and anti-CD20 therapy. The early examination of urinalysis and renal function may be crucial for identifying glomerulonephritis and acute renal failure in susceptible patients after COVID-19 vaccination.

Introduction: End-stage kidney disease (ESKD) patients who need renal replacement therapy need to face a dialysis modality decision: the choice between hemodialysis (HD) and peritoneal dialysis (PD). Although the global differences in HD/PD penetration are affected by health-care policies, these two modalities may exert different effects on survival in patients with ESKD. Although Taiwan did not implicate PD as first policy, we still need to compare patients’ outcomes using two modalities in a nation-wise database to determine future patients’ care and health policies. Methods: We used the nationwide Taiwan Renal Registry Data System (TWRDS) database from 2005 to 2012 and included 52,900 patients (48,371 on HD and 4529 on PD) to determine all-cause and cardiovascular mortality among ESKD patients. Results: Age-matched survival probability from all-cause mortality was significantly lower in patients on PD than in those on HD (p < 0.05). The adjusted hazard ratios of 3-year and 5-year all-cause and cardiovascular mortality were significantly higher in PD compared with HD. The presence of comorbid conditions including myocardial infarction, coronary artery disease (CAD), diabetes mellitus (DM), hypoalbuminemia, hyperferritinemia and hypophosphatemia was related with significantly higher all-cause and CV mortality in PD patients. No significant difference was noted among younger patients

Activation of the Nod-like receptor 3 (NLRP3) inflammasome is important for activation of innate immune responses, but improper and excessive activation can cause inflammatory disease. We previously showed that glycolysis, a metabolic pathway that converts glucose into pyruvate, is essential for NLRP3 inflammasome activation in macrophages. Here, we investigated the role of metabolic pathways downstream glycolysis – lactic acid fermentation and pyruvate oxidation—in activation of the NLRP3 inflammasome. Using pharmacological or genetic approaches, we show that decreasing lactic acid fermentation by inhibiting lactate dehydrogenase reduced caspase-1 activation and IL-1β maturation in response to various NLRP3 inflammasome agonists such as nigericin, ATP, monosodium urate (MSU) crystals, or alum, indicating that lactic acid fermentation is required for NLRP3 inflammasome activation. Inhibition of lactate dehydrogenase with GSK2837808A reduced lactate production and activity of the NLRP3 inflammasome regulator, phosphorylated protein kinase R (PKR), but did not reduce the common trigger of NLRP3 inflammasome, potassium efflux, or reactive oxygen species (ROS) production. By contrast, decreasing the activity of pyruvate oxidation by depletion of either mitochondrial pyruvate carrier 2 (MPC2) or pyruvate dehydrogenase E1 subunit alpha 1 (PDHA1) enhanced NLRP3 inflammasome activation, suggesting that inhibition of mitochondrial pyruvate transport enhanced lactic acid fermentation. Moreover, treatment with GSK2837808A reduced MSU-mediated peritonitis in mice, a disease model used for studying the consequences of NLRP3 inflammasome activation. Our results suggest that lactic acid fermentation is important for NLRP3 inflammasome activation, while pyruvate oxidation is not. Thus, reprograming pyruvate metabolism in mitochondria and in the cytoplasm should be considered as a novel strategy for the treatment of NLRP3 inflammasome-associated diseases.

Introduction Patients with tuberculosis (TB) often experience difficulties in accessing diagnosis and treatment. Patient pathway analysis identifies mismatches between TB patient care-seeking patterns and service coverage, but to date, studies have only employed cross-sectional aggregate data.Methods We developed an algorithmic approach to analyse and interpret patient-level routine data on healthcare use and to construct patients’ pathways from initial care-seeking to treatment outcome. We applied this to patients with TB in a simple random sample of one million patients’ records in the Taiwan National Health Insurance database. We analysed heterogeneity in pathway patterns, delays, service coverage and patient flows between different health system levels.Results We constructed 7255 pathways for 6258 patients. Patients most commonly initially sought care at the primary clinic level, where the capacity for diagnosing TB patients was 12%, before eventually initiating treatment at higher levels. Patient pathways are extremely heterogeneous prior to diagnosis, with the 10% most complex pathways accounting for 48% of all clinical encounters, and 55% of those pathways yet to initiate treatment after a year. Extended consideration of alternative diagnoses was more common for patients aged 65 years or older and for patients with chronic lung disease.Conclusion Our study demonstrates that longitudinal analysis of routine individual-level healthcare data can be used to generate a detailed picture of TB care-seeking pathways. This allows an understanding of several temporal aspects of care pathways, including lead times to care and the variability in patient pathways.

Introduction: Dengue has been endemic to Pakistan in the last two decades. There was a massive outbreak in the Swat valley in 2013. Here we demonstrate the spatio-temporal clustering and diffusion patterns of the dengue outbreak. Methods: Dengue case data were acquired from the hospital records in the Swat district of Pakistan. Ring maps visualize the distribution and diffusion of the number of cases and incidence of dengue at the level of the union council. We applied space-time scan statistics to identify spatio-temporal clusters. Ordinary least squares and geographically weighted regression models were used to evaluate the impact of elevation, population density, and distance to the river. Results: The results show that dengue distribution is not random, but clustered in space and time in the Swat district. Males constituted 68% of the cases while females accounted for about 32%. A majority of the cases (>55%) were younger than 40 years of age. The southern part was a major hotspot affected by the dengue outbreak in 2013. There are two space-time clusters in the spatio-temporal analysis. GWR and OLS show that population density is a significant explanatory variable for the dengue outbreak, while GWR exhibits better performance in terms of ‘R2 = 0.49 and AICc = 700’. Conclusion: Dengue fever is clustered in the southern part of the Swat district. This region is relatively urban in character, with most of the population of the district residing here. There is a need to strengthen the surveillance system for reporting dengue cases in order to respond to future outbreaks in a robust way. Keywords: Dengue, Swat, Pakistan, Spatio-temporal, Clusters, Diffusion

Guanylate binding protein 5 (GBP5) is the interferon (IFN)-inducible subfamily of guanosine triphosphatases (GTPases) and is involved in pathogen defense. However, the role played by GBP5 in cancer development, especially in oral squamous cell carcinoma (OSCC), is still unknown. Herein, next-generation sequencing analysis showed that the gene expression levels of GBP5 were significantly higher in OSCC tissues compared with those found in corresponding tumor adjacent normal tissues (CTAN) from two pairs of OSCC patients. Higher gene expression levels of GBP5 were also found in tumor tissues of 23 buccal mucosal squamous cell carcinoma (BMSCC)/14 tongue squamous cell carcinoma (TSCC) patients and 30 oral cancer patients from The Cancer Genome Atlas (TCGA) database compared with those in CTAN tissues. Immunohistochemical results showed that protein expression levels of GBP5 were also higher in the tumor tissues of 353 OSCC patients including 117 BMSCC, 187 TSCC, and 49 lip squamous cell carcinoma patients. Moreover, TCGA database analysis indicated that high gene expression levels of GBP5 were associated with poor overall survival in oral cancer patients with moderate/poor cell differentiation, and associated with poor disease-free survival in oral cancer patients with moderate/poor cell differentiation and lymph node metastasis. Furthermore, GBP5-knockdowned cells exhibited decreased cell growth, arrest at G1 phase, and decreased invasion/migration. The gene expression of markers for epithelial−mesenchymal transition and cancer stemness was also reduced in GBP5-silenced oral cancer cells. Taken together, GBP5 might be a potential biomarker and therapeutic target for OSCC patients, especially for those with poor cell differentiation and lymph node metastasis.

Abstract Background Cases of dengue fever have increased in areas of Southeast Asia in recent years. Taiwan hit a record-high 42,856 cases in 2015, with the majority in southern Tainan and Kaohsiung Cities. Leveraging spatial statistics and geo-visualization techniques, we aim to design an online analytical tool for local public health workers to prospectively identify ongoing hot spots of dengue fever weekly at the village level. Methods A total of 57,516 confirmed cases of dengue fever in 2014 and 2015 were obtained from the Taiwan Centers for Disease Control (TCDC). Incorporating demographic information as covariates with cumulative cases (365 days) in a discrete Poisson model, we iteratively applied space–time scan statistics by SaTScan software to detect the currently active cluster of dengue fever (reported as relative risk) in each village of Tainan and Kaohsiung every week. A village with a relative risk >1 and p value

To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-spatial tool (GeoMasker) intended to mask the residential locations of patients or cases in a geographic information system (GIS). To elucidate the effects of geo-masking parameters, we applied 2010 dengue epidemic data from Taiwan testing the tool’s performance in an empirical situation. The similarity of pre- and post-spatial patterns was measured by D statistics under a 95% confidence interval. In the empirical study, different magnitudes of anonymisation (estimated Kanonymity ≥10 and 100) were achieved and different degrees of agreement on the pre- and post-patterns were evaluated. The application is beneficial for public health workers and researchers when processing data with individuals’ spatial information.

Ambulance response times and resuscitation efforts are critical predictors of the survival rate after out-of-hospital cardiac arrests (OHCA). On the other hand, rural-urban differences in the OHCA survival rates are an important public health issue.We retrospectively reviewed the January 2011-December 2013 OHCA registry data of Kaohsiung City, Taiwan. With particular focus on geospatial variables, we aimed to unveil risk factors predicting the overall OHCA survival until hospital admission. Spatial analysis, network analysis, and the Kriging method by using geographic information systems were applied to analyze spatial variations and calculate the transport distance. Logistic regression was used to identify the risk factors for OHCA survival.Among the 4,957 patients, the overall OHCA survival to hospital admission was 16.5%. In the multivariate analysis, female sex (adjusted odds ratio:, AOR, 1.24 [1.06-1.45]), events in public areas (AOR: 1.30 [1.05-1.61]), exposure to automated external defibrillator (AED) shock (AOR: 1.70 [1.30-2.23]), use of laryngeal mask airway (LMA) (AOR: 1.35 [1.16-1.58]), non-trauma patients (AOR: 1.41 [1.04-1.90]), ambulance bypassed the closest hospital (AOR: 1.28 [1.07-1.53]), and OHCA within the high population density areas (AOR: 1.89 [1.55-2.32]) were positively associated with improved OHCA survival. By contrast, a prolonged total emergency medical services (EMS) time interval was negatively associated with OHCA survival (AOR: 0.98 [0.96-0.99]).Resuscitative efforts, such as AED or LMA use, and a short total EMS time interval improved OHCA outcomes in emergency departments. The spatial heterogeneity of emergency medical resources between rural and urban areas might affect survival rate.

Ambient vibration measurements of a cable-stayed bridge in Taiwan were first conducted to identify its dominant modal parameters with a reliable stochastic subspace identification algorithm recently developed. A finite element model is then constructed based on the identified frequencies and shape vectors of four vertically bending, one torsional, and one horizontally bending modes. This model is also updated by adjusting the girder-pier connection with the addition of a rotational spring to reflect the actual conditions and its accuracy is demonstrated with less than 1% of error for the first two vertically bending modes. As a solid application for probing the environmental effects in structural health monitoring, the vibration measurements of 24 hours were further conducted and combined with the well calibrated model to investigate the controlling factor for its variation in modal frequencies. It is found that the frequencies of the first two vertically bending modes are closely correlated to the root-mean-square velocity representing the traffic excitation intensity. Moreover, it is shown with the updated model that the daily variations in the frequencies of the first two vertically bending modes can be reasonably simulated by modifying the coefficient of the rotational spring merely in a limited range. [ABSTRACT FROM AUTHOR]