THE INTELLECTUAL STRUCTURE OF ELECTRONIC RECORDS MANAGEMENT

A number of countries have launched projects with a particular emphasis on using information technologies (IT) to provide electronic information and services to citizens and businesses. Through various IT, tremendous amount of electronic records in government agencies are created. These records and archives are the basis of knowledge management. Electronic records management (ERM) is a fast growing field throughout the last decades. Theoretical foundations for ERM have remained obscure from the research community. To map the intellectual structure of ERM research, this study identifies the high-impact articles as well as the correlations among these scholar publications. In this study, co-citation, co-word, association rule and cluster analysis techniques are used to investigate the intellectual pillars of the ERM literature. This study exposes researchers to a new way of profiling knowledge networks and their relationships the area of ERM, thereby helping academia and practitioners better understand contemporary studies. The results of the mapping can help identify the research direction of ERM research, provide a valuable tool for researchers to access ERM literature, and acts as an exemplary model for future researches

Neurological Complications in Young Infants With Acute Bacterial Meningitis

We aimed to evaluate the occurrence, treatment, and outcomes of neurological complications after bacterial meningitis in young infants. A case series study from a retrospective cohort from two tertiary-level medical centers in Taiwan between 2007 and 2016 was conducted. Eighty-five young infants aged < 90 days with bacterial meningitis were identified. 25 (29.4%) were born at preterm. Group B Streptococcus (GBS) and Escherichia coli caused 74.1% of identified cases. Despite the majority (90.6%) initially received microbiologically appropriate antibiotics, 65 (76.5%) had experienced at least one neurological complication identified at a median of 6 days (range: 1–173) after onset of bacterial meningitis. The most common neurological complication was seizure (58.8%), followed by subdural effusion (47.1%), ventriculomegaly (41.2%), subdural empyema (21.2%), hydrocephalus (18.8%), ventriculitis (15.3%), periventricular leukomalacia (11.8%), and encephalomalacia (10.6%). Nine patients (10.6%) died (including 4 had critical discharge on request) and 29/76 (38.2%) of the survivors had major neurological sequelae at discharge. Nighteen (22.4%) received surgical intervention due to these complications. After multivariate logistic regression, initial seizure (adjusted odds ratio [aOR]: 4.76, 95% confidence interval [CI]: 1.7–13.0, P = 0.002) and septic shock (aOR: 6.04; 95% CI: 1.35–27.0, P = 0.019) were independent predictors for final unfavorable outcomes.Conclusions: Neurological complications and sequelae are common in young infants after bacterial meningitis. Patients presented with early seizure or septic shock can be an early predictor of final unfavorable outcomes and require close monitoring. Further research regarding how to improve clinical management and outcomes is warranted

3D Geometry of the Chelungpu Thrust System in Central Taiwan: Its Implications for Active Tectonics

This study is aimed at constructing a 3D subsurface geometry of the Chelungpu thrust and its associated structures, as well as examining the implications of the studies results for active tectonics in the area. Nine balanced cross-sections were constructed across the foothills belt in the study area to delineate the subsurface geometry of the major thrusts in the foreland of the fold-and-thrust belt

Genetic polymorphisms in glutathione S-transferase (GST) superfamily and risk of arsenic-induced urothelial carcinoma in residents of southwestern Taiwan

<p>Abstract</p> <p>Background</p> <p>Arsenic exposure is an important public health issue worldwide. Dose-response relationship between arsenic exposure and risk of urothelial carcinoma (UC) is consistently observed. Inorganic arsenic is methylated to form the metabolites monomethylarsonic acid and dimethylarsinic acid while ingested. Variations in capacity of xenobiotic detoxification and arsenic methylation might explain individual variation in susceptibility to arsenic-induced cancers.</p> <p>Methods</p> <p>To estimate individual susceptibility to arsenic-induced UC, 764 DNA specimens from our long-term follow-up cohort in Southwestern Taiwan were used and the genetic polymorphisms in GSTM1, GSTT1, GSTP1 and arsenic methylation enzymes including GSTO1 and GSTO2 were genotyped.</p> <p>Results</p> <p>The GSTT1 null was marginally associated with increased urothelial carcinoma (UC) risk (HR, 1.91, 95% CI, 1.00-3.65), while the association was not observed for other GSTs. Among the subjects with cumulative arsenic exposure (CAE) ≥ 20 mg/L*year, the GSTT1 null genotype conferred a significantly increased cancer risk (RR, 3.25, 95% CI, 1.20-8.80). The gene-environment interaction between the GSTT1 and high arsenic exposure with respect to cancer risk was statistically significant (multiplicative model, <it>p </it>= 0.0151) and etiologic fraction was as high as 0.86 (95% CI, 0.51-1.22). The genetic effects of GSTO1/GSTO2 were largely confined to high arsenic level (CAE ≥ 20). Diplotype analysis showed that among subjects exposed to high levels of arsenic, the AGG/AGG variant of GSTO1 Ala140Asp, GSTO2 5'UTR (-183)A/G, and GSTO2 Asn142Asp was associated with an increased cancer risk (HRs, 4.91, 95% CI, 1.02-23.74) when compared to the all-wildtype reference, respectively.</p> <p>Conclusions</p> <p>The GSTs do not play a critical role in arsenic-induced urothelial carcinogenesis. The genetic effects of GSTT1 and GSTO1 on arsenic-induced urothelial carcinogenesis are largely confined to very high exposure level.</p

Roles of cysteines Cys115 and Cys201 in the assembly and thermostability of grouper betanodavirus particles

The virus-like particle (VLP) assembled from capsid subunits of the dragon grouper nervous necrosis virus (DGNNV) is very similar to its native T = 3 virion. In order to investigate the effects of four cysteine residues in the capsid polypeptide on the assembly/dissociation pathways of DGNNV virions, we recombinantly cloned mutant VLPs by mutating each cysteine to destroy the specific disulfide linkage as compared with thiol reduction to destroy all S–S bonds. The mutant VLPs of C187A and C331A mutations were similar to wild-type VLPs (WT-VLPs); hence, the effects of Cys187 and Cys331 on the particle formation and thermostability were presumably negligible. Electron microscopy showed that either C115A or C201A mutation disrupted de novo VLP formation significantly. As shown in micrographs and thermal decay curves, β-mercaptoethanol-treated WT-VLPs remained intact, merely resulting in lower tolerance to thermal disruption than native WT-VLPs. This thiol reduction broke disulfide linkages inside the pre-fabricated VLPs, but it did not disrupt the appearance of icosahedrons. Small dissociated capsomers from EGTA-treated VLPs were able to reassemble back to icosahedrons in the presence of calcium ions, but additional treatment with β-mercaptoethanol during EGTA dissociation resulted in inability of the capsomers to reassemble into the icosahedral form. These results indicated that Cys115 and Cys201 were essential for capsid formation of DGNNV icosahedron structure in de novo assembly and reassembly pathways, as well as for the thermal stability of pre-fabricated particles

Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care

ObjectiveTo implement an all-day online artificial intelligence (AI)-assisted detection of ST-elevation myocardial infarction (STEMI) by prehospital 12-lead electrocardiograms (ECGs) to facilitate patient triage for timely reperfusion therapy.MethodsThe proposed AI model combines a convolutional neural network and long short-term memory (CNN-LSTM) to predict STEMI on prehospital 12-lead ECGs obtained from mini-12-lead ECG devices equipped in ambulance vehicles in Central Taiwan. Emergency medical technicians (EMTs) from the 14 AI-implemented fire stations performed the on-site 12-lead ECG examinations using the mini portable device. The 12-lead ECG signals were transmitted to the AI center of China Medical University Hospital to classify the recordings as “STEMI” or “Not STEMI”. In 11 non-AI fire stations, the ECG data were transmitted to a secure network and read by available on-line emergency physicians. The response time was defined as the time interval between the ECG transmission and ECG interpretation feedback.ResultsBetween July 17, 2021, and March 26, 2022, the AI model classified 362 prehospital 12-lead ECGs obtained from 275 consecutive patients who had called the 119 dispatch centers of fire stations in Central Taiwan for symptoms of chest pain or shortness of breath. The AI's response time to the EMTs in ambulance vehicles was 37.2 ± 11.3 s, which was shorter than the online physicians' response time from 11 other fire stations with no AI implementation (113.2 ± 369.4 s, P &lt; 0.001) after analyzing another set of 335 prehospital 12-lead ECGs. The evaluation metrics including accuracy, precision, specificity, recall, area under the receiver operating characteristic curve, and F1 score to assess the overall AI performance in the remote detection of STEMI were 0.992, 0.889, 0.994, 0.941, 0.997, and 0.914, respectively. During the study period, the AI model promptly identified 10 STEMI patients who underwent primary percutaneous coronary intervention (PPCI) with a median contact-to-door time of 18.5 (IQR: 16–20.8) minutes.ConclusionImplementation of an all-day real-time AI-assisted remote detection of STEMI on prehospital 12-lead ECGs in the field is feasible with a high diagnostic accuracy rate. This approach may help minimize preventable delays in contact-to-treatment times for STEMI patients who require PPCI

A proposed prognostic 7-day survival formula for patients with terminal cancer

<p>Abstract</p> <p>Background</p> <p>The ability to identify patients for hospice care results in better end-of-life care. To develop a validated prognostic scale for 7-day survival prediction, a prospective observational cohort study was made of patients with terminal cancer.</p> <p>Methods</p> <p>Patient data gathered within 24 hours of hospital admission included demographics, clinical signs and symptoms and their severity, laboratory test results, and subsequent survival data. Of 727 patients enrolled, data from 374 (training group) was used to develop a prognostic tool, with the other 353 serving as the validation group.</p> <p>Results</p> <p>Five predictors identified by multivariate logistic regression analysis included patient's cognitive status, edema, ECOG performance status, BUN and respiratory rate. A formula of the predictor model based on those five predictors was constructed. When probability was >0.2, death within 7 days was predicted in the training group and validation group, with sensitivity of 80.9% and 71.0%, specificity of 65.9% and 57.7%, positive predictive value of 42.6% and 26.8%, and negative predictive value (NPV) of 91.7% and 90.1%, respectively.</p> <p>Conclusion</p> <p>This predictor model showed a relatively high sensitivity and NPV for predicting 7-day survival among terminal cancer patients, and could increase patient satisfaction by improving end-of-life care.</p

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities