Drugs to Treat Neuroinflammation in Neurodegenerative Disorders.

Neuroinflammation is associated with disorders of the nervous system, and it is induced in response to many factors, including pathogen infection, brain injury, toxic substances, and autoimmune diseases. Astrocytes and microglia have critical roles in neuroinflammation. Microglia are innate immune cells in the central nervous system (CNS), which are activated in reaction to neuroinflammation-inducing factors. Astrocytes can have pro- or anti-inflammatory responses, which depend on the type of stimuli presented by the inflamed milieu. Microglia respond and propagate peripheral inflammatory signals within the CNS that cause low-grade inflammation in the brain. The resulting alteration in neuronal activities leads to physiological and behavioral impairment. Consequently, activation, synthesis, and discharge of various pro-inflammatory cytokines and growth factors occur. These events lead to many neurodegenerative conditions, such as Alzheimer's disease, Parkinson's disease, and multiple sclerosis discussed in this study. After understanding neuroinflammation mechanisms and the involvement of neurotransmitters, this study covers various drugs used to treat and manage these neurodegenerative illnesses. The study can be helpful in discovering new drug molecules for treating neurodegenerative disorders.

Proton Pump Inhibitors and Risk of Chronic Kidney Disease: Evidence from Observational Studies.

Previous epidemiological studies have raised the concern that the use of proton pump inhibitors (PPIs) is associated with an increased risk of kidney diseases. To date, no comprehensive meta-analysis has been conducted to assess the association between PPIs and the risk of chronic kidney disease (CKD). Therefore, we conducted a systematic review and meta-analysis to address the association between PPIs and CKD. The primary search was conducted in the most popular databases, such as PubMed, Scopus, and Web of Science. All observational studies evaluated the risk of CKD among PPI users, and non-users were considered for inclusion. Two reviewers conducted data extraction and assessed the risk of bias. Random-effect models were used to calculate pooled effect sizes. A total of 6,829,905 participants from 10 observational studies were included. Compared with non-PPI use, PPI use was significantly associated with an increased risk of CKD (RR 1.72, 95% CI: 1.02-2.87, p = 0.03). This updated meta-analysis showed that PPI was significantly associated with an increased risk of CKD. Association was observed in the same among moderate-quality studies. Until further randomized control trials (RCTs) and biological studies confirm these results, PPI therapy should not stop patients with gastroesophageal reflux disease (GERD). However, caution should be used when prescribing to patients with high-risk kidney disease.

Impact of gut-brain interaction in emerging neurological disorders.

The central nervous system (CNS) is a reservoir of immune privilege. Specialized immune glial cells are responsible for maintenance and defense against foreign invaders. The blood-brain barrier (BBB) prevents detrimental pathogens and potentially overreactive immune cells from entering the periphery. When the double-edged neuroinflammatory response is overloaded, it no longer has the protective function of promoting neuroregeneration. Notably, microbiota and its derivatives may emerge as pathogen-associated molecular patterns of brain pathology, causing microbiome-gut-brain axis dysregulation from the bottom-up. When dysbiosis of the gastrointestinal flora leads to subsequent alterations in BBB permeability, peripheral immune cells are recruited to the brain. This results in amplification of neuroinflammatory circuits in the brain, which eventually leads to specific neurological disorders. Aggressive treatment strategies for gastrointestinal disorders may protect against specific immune responses to gastrointestinal disorders, which can lead to potential protective effects in the CNS. Accordingly, this study investigated the mutual effects of microbiota and the gut-brain axis, which may provide targeting strategies for future disease treatment.

Association between systemic rheumatic diseases and dementia risk: A meta-analysis.

Background and aims: Epidemiological studies have been conducted on the relationship between systemic rheumatic diseases (SRDs) and dementia. Therefore, we focused on determining the extent of alliances bounded by SRDs, along with the risk of dementia. Materials and methods: Two independent reviewers assessed all studies retrieved from the PubMed, EMBASE, Scopus, and Web of Science databases between January 1, 2000 and November 30, 2021. Only observational studies that estimated the possibility of dementia in participants with SRD were considered. The random-effects model was applied to forecast pooled risk ratios (RRs) and 95% confidence intervals (CI). Heterogeneity among the studies was evaluated using the Q and I2 statistics. The quality of the included studies was assessed using the Newcastle-Ottawa Scale. Funnel plots were used to calculate the risk of bias. Results: Seventeen observational studies with 17,717,473 participants were recruited. Our findings showed that among the participants with SRDs, those with osteoarthritis, systemic lupus erythematosus, and Sjogren's syndrome were highly related to an elevated risk of dementia (pooled RR: 1.31; 95% CI: 1.15-1.49, p<0.001; pooled RR: 1.43; 95% CI: 1.19-1.73, p<0.001; and pooled RR: 1.26; 95% CI: 1.14-1.39, p<0.001, respectively). However, participants with rheumatoid arthritis (RA) were not associated with an increased risk of dementia (pooled RR: 0.98; 95% CI: 0.90-1.07, p<0.001). Conclusion: This systematic review and meta-analysis demonstrated an increased dementia risk among SRDs participants, except for RA.

Homogeneous Chronic Subdural Hematoma with Diverse Recurrent Possibilities.

Background: Evidence suggests that hyperdense (HD) chronic subdural hematomas (CSDHs) have a higher recurrence than hypodense (LD) chronic subdural hematomas. The value of mean hematoma density (MHD) has been proven to be associated with postoperative recurrence. The MHD levels in homogeneous CSDHs likely underestimate the risk of recurrence in HD homogeneous subtypes. Methods: This study investigated 42 consecutive CSDH cases between July 2010 and July 2014. The area of the hematoma was quantified to determine the MHD level using computer-based image analysis of preoperative brain CT scans. Results: In terms of the MHD distribution of the four types of CSDHs (homogeneous, laminar, separated, and trabecular), wide 95% CI (11.80-16.88) and high standard deviation (4.59) can be found in homogeneous types, reflecting a high variability in the MHD levels between cases (from low to high density). The categorization of homogeneous types into LD and HD (type five) displayed a minor standard deviation in the MHD levels for LD and HD subtypes (1.15, and 0.88, respectively). MHD values demonstrated concentrated distributions among the respective five types, compared to the four-type setting. Conclusions: In the current research, we provide a consideration that if LD and HD hematomas are separated from homogeneous CSDHs, the variability of the MHD quantification can potentially be reduced, thereby avoiding the possibility of undetected high-risk groups.

mHealth Research for Weight Loss, Physical Activity, and Sedentary Behavior: Bibliometric Analysis.

BACKGROUND: Research into mobile health (mHealth) technologies on weight loss, physical activity, and sedentary behavior has increased substantially over the last decade; however, no research has been published showing the research trend in this field. OBJECTIVE: The purpose of this study was to provide a dynamic and longitudinal bibliometric analysis of recent trends of mHealth research for weight loss, physical activity, and sedentary behavior. METHODS: A comprehensive search was conducted through Web of Science to retrieve all existing relevant documents published in English between January 1, 2010, and November 1, 2021. We developed appropriate research questions; based on the proven bibliometric approaches, a search strategy was formulated to screen the title for eligibility. Finally, we conducted bibliometric analyses to explore the growth rate of publications; publication patterns; and the most productive authors, institutions, and countries, and visualized the trends in the field using a keyword co-occurrence network. RESULTS: The initial search identified 8739 articles, of which 1035 were included in the analyses. Our findings show an exponential growth trend in the number of annual publications of mHealth technology research in these fields. JMIR mHealth and uHealth (n=214, 20.67%), Journal of Medical Internet Research (n=71, 6.86%), and BMC Public Health (n=36, 3.47%) were the top 3 journals, publishing higher numbers of articles. The United States remained the leading contributor in these areas (n=405, 39.13%), followed by Australia (n=154, 14.87%) and England (n=125, 12.07%). Among the universities, the University of Sydney (n=36, 3.47%) contributed the most mHealth technology research in these areas; however, Deakin University (n=25, 2.41%) and the National University of Singapore (n=23, 2.22%) were in the second and third positions, respectively. CONCLUSIONS: Although the number of papers published on mobile technologies for weight loss, physical activity, and sedentary behavior was initially low, there has been an overall increase in these areas in recent years. The findings of the study indicate that mobile apps and technologies have substantial potential to reduce weight, increase physical activity, and change sedentary behavior. Indeed, this study provides a useful overview of the publication trends and valuable guidance on future research directions and perspectives in this rapidly developing field.

Combination of Acupoints for Alzheimer's Disease: An Association Rule Analysis.

Background: Alzheimer's disease (AD) is an ongoing neurological degeneration characterized by amnesia and a decline in cognitive abilities. Hippocampal neurogenesis is the leading cause of AD. Mild cognitive impairment (MCI), a prodromal state of AD, is mainly due to the degradation of neuropsychiatric manifestations. Previous systematic reviews demonstrated that treatment with acupuncture with Chinese herbs is tolerable and effective in improving cognitive function in patients with AD. Our investigation aimed to discover the main acupoint combination for AD management based on a preceding systematic review and meta-analysis of randomized control trials (RCTs). Materials and Methods: Our investigation was executed using association rule analysis, which is a common data mining technique accessible within R. Our study elucidated acupoint locations as binary data from 15 of the included studies using the Apriori algorithm. Results: Thirty-two acupoints were selected from 15 RCTs. The 10 most frequent acupoints were selected. We inspected 503 association rules using the interpreted acupuncture data. The obtained results showed that {SP6, BI10} ≥ {HT7} and {HT7, BI10} ≥ {SP6} were the most associated rules in 15 RCTs. Conclusion: The combination of acupoints ({SP6, BI10} ≥ {HT7} and {HT7, BI10} ≥ {SP6}) can be acknowledged as a core combination for future acupuncture regimens of AD.

A Deep Learning Model to Predict Knee Osteoarthritis Based on Nonimage Longitudinal Medical Record.

PURPOSE: To develop deep learning model (Deep-KOA) that can predict the risk of knee osteoarthritis (KOA) within the next year by using the previous three years nonimage-based electronic medical record (EMR) data. PATIENTS AND METHODS: We randomly selected information of two million patients from the Taiwan National Health Insurance Research Database (NHIRD) from January 1, 1999 to December 31, 2013. During the study period, 132,594 patients were diagnosed with KOA, while 1,068,464 patients without KOA were chosen randomly as control. We constructed a feature matrix by using the three-year history of sequential diagnoses, drug prescriptions, age, and sex. Deep learning methods of convolutional neural network (CNN) and artificial neural network (ANN) were used together to develop a risk prediction model. We used the area under the receiver operating characteristic (AUROC), sensitivity, specificity, and precision to evaluate the performance of Deep-KOA. Then, we explored the important features using stepwise feature selection. RESULTS: This study included 132,594 KOA patients, 83,111 females (62.68%), 49,483 males (37.32%), mean age 64.2 years, and 1,068,464 non-KOA patients, 545,902 females (51.09%), 522,562 males (48.91%), mean age 51.00 years. The Deep-KOA achieved an overall AUROC, sensitivity, specificity, and precision of 0.97, 0.89, 0.93, and 0.80 respectively. The discriminative analysis of Deep-KOA showed important features from several diseases such as disorders of the eye and adnexa, acute respiratory infection, other metabolic and immunity disorders, and diseases of the musculoskeletal and connective tissue. Age and sex were not found as the most discriminative features, with AUROC of 0.9593 (-0.76% loss) and 0.9644 (-0.25% loss) respectively. Whereas medications including antacid, cough suppressant, and expectorants were identified as discriminative features. CONCLUSION: Deep-KOA was developed to predict the risk of KOA within one year earlier, which may provide clues for clinical decision support systems to target patients with high risk of KOA to get precision prevention program.

Metformin Use Is Associated with Decreased Mortality in COVID-19 Patients with Diabetes: Evidence from Retrospective Studies and Biological Mechanism.

BACKGROUND AND AIMS: The coronavirus disease 2019 (COVID-19) increases hyperinflammatory state, leading to acute lung damage, hyperglycemia, vascular endothelial damage, and a higher mortality rate. Metformin is a first-line treatment for type 2 diabetes and is known to have anti-inflammatory and immunosuppressive effects. Previous studies have shown that metformin use is associated with decreased risk of mortality among patients with COVID-19; however, the results are still inconclusive. This study investigated the association between metformin and the risk of mortality among diabetes patients with COVID-19. METHODS: Data were collected from online databases such as PubMed, EMBASE, Scopus, and Web of Science, and reference from the most relevant articles. The search and collection of relevant articles was carried out between 1 February 2020, and 20 June 2021. Two independent reviewers extracted information from selected studies. The random-effects model was used to estimate risk ratios (RRs), with a 95% confidence interval. RESULTS: A total of 16 studies met all inclusion criteria. Diabetes patients given metformin had a significantly reduced risk of mortality (RR, 0.65; 95% CI: 0.54-0.80, p < 0.001, heterogeneity I2 = 75.88, Q = 62.20, and τ2 = 0.06, p < 0.001) compared with those who were not given metformin. Subgroup analyses showed that the beneficial effect of metformin was higher in the patients from North America (RR, 0.43; 95% CI: 0.26-0.72, p = 0.001, heterogeneity I2 = 85.57, Q = 34.65, τ2 = 0.31) than in patients from Europe (RR, 0.67; 95% CI: 0.47-0.94, p = 0.02, heterogeneity I2 = 82.69, Q = 23.11, τ2 = 0.10) and Asia (RR, 0.90; 95% CI: 0.43-1.86, p = 0.78, heterogeneity I2 = 64.12, Q = 11.15, τ2 = 0.40). CONCLUSIONS: This meta-analysis shows evidence that supports the theory that the use of metformin is associated with a decreased risk of mortality among diabetes patients with COVID-19. Randomized control trials with a higher number of participants are warranted to assess the effectiveness of metformin for reducing the mortality of COVID-19 patients.

Anemia and the Risk of Cognitive Impairment: An Updated Systematic Review and Meta-Analysis.

BACKGROUND: Cognitive impairment is one of the most common, burdensome, and costly disorders in the elderly worldwide. The magnitude of the association between anemia and overall cognitive impairment (OCI) has not been established. OBJECTIVE: We aimed to update and expand previous evidence of the association between anemia and the risk of OCI. METHODS: We conducted an updated systematic review and meta-analysis. We searched electronic databases, including EMBASE, PubMed, and Web of Science for published observational studies and clinical trials between 1 January 1990 and 1 June 2020. We excluded articles that were in the form of a review, letter to editors, short reports, and studies with less than 50 participants. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed. We estimated summary risk ratios (RRs) with random effects. RESULTS: A total of 20 studies, involving 6558 OCI patients were included. Anemia was significantly associated with an increased risk of OCI (adjusted RR (aRR) 1.39 (95% CI, 1.25-1.55; p < 0.001)). In subgroup analysis, anemia was also associated with an increased risk of all-cause dementia (adjusted RR (aRR), 1.39 (95% CI, 1.23-1.56; p < 0.001)), Alzheimer's disease [aRR, 1.59 (95% CI, 1.18-2.13; p = 0.002)], and mild cognitive impairment (aRR, 1.36 (95% CI, 1.04-1.78; p = 0.02)). CONCLUSION: This updated meta-analysis shows that patients with anemia appear to have a nearly 1.39-fold risk of developing OCI than those without anemia. The magnitude of this risk underscores the importance of improving anemia patients' health outcomes, particularly in elderly patients.

Association between Anemia and Risk of Parkinson Disease.

METHODS: We systematically searched articles on electronic databases such as PubMed, Embase, Scopus, and Google Scholar between January 1, 2000 and July 30, 2020. Articles were independently evaluated by two authors. We included observational studies (case-control and cohort) and calculated the risk ratios (RRs) for associated with anemia and PD. Heterogeneity among the studies was assessed using the Q and I 2 statistic. We utilized the random-effect model to calculate the overall RR with 95% CI. RESULTS: A total of 342 articles were identified in the initial searches, and 7 full-text articles were evaluated for eligibility. Three articles were further excluded for prespecified reasons including insufficient data and duplications, and 4 articles were included in our systematic review and meta-analysis. A random effect model meta-analysis of all 4 studies showed no increased risk of PD in patients with anemia (N = 4, RRadjusted = 1.17 (95% CI: 0.94-1.45, p = 0.15). However, heterogeneity among the studies was significant (I 2 = 92.60, p = <0.0001). The pooled relative risk of PD in female patients with anemia was higher (N = 3, RRadjusted = 1.14 (95% CI: 0.83-1.57, p = 0.40) as compared to male patients with anemia (N = 3, RRadjusted = 1.09 (95% CI: 0.83-1.42, p = 0.51). CONCLUSION: This is the first meta-analysis that shows that anemia is associated with higher risk of PD when compared with patients without anemia. However, more studies are warranted to evaluate the risk of PD among patients with anemia.

Simulating Expansion of the Intracranial Space to Accommodate Brain Swelling after Decompressive Craniectomy: Volumetric Quantification in a 3D CAD Skull Model with Contour Elevation.

Background: Decompressive craniectomy (DC) can be used to augment intracranial space and halt brainstem compromise. However, a widely adopted recommendation for optimal surgical extent of the DC procedure is lacking. In the current study, we utilized three-dimensional (3D) computer-assisted design (CAD) skull models with defect contour elevation for quantitative assessment. Methods: DC was performed for 15 consecutive patients, and 3D CAD models of defective skulls with contour elevations (0-50 mm) were reconstructed using commercial software. Quantitative assessments were conducted in these CAD subjects to analyze the effects of volumetric augmentation when elevating the length of the contour and the skull defect size. The final positive results were mathematically verified using a computerized system for numerical integration with the rectangle method. Results: Defect areas of the skull CAD models ranged from 55.7-168.8 cm2, with a mean of 132.3 ± 29.7 cm2. As the contour was elevated outward for 6 mm or above, statistical significance was detected in the volume and the volume-increasing rate, when compared to the results obtained from the regular CAD model. The volume and the volume-increasing rate increased by 3.665 cm3, 0.285% (p < 0.001) per 1 mm of contour elevation), and 0.034% (p < 0.001) per 1 cm2 of increase of defect area, respectively. Moreover, a 1 mm elevation of the contour in Groups 2 (defect area 125-150 cm2) and 3 (defect area >150 cm2, as a proxy for an extremely large skull defect) was shown to augment the volume and the volume-increasing rate by 1.553 cm3, 0.101% (p < 0.001) and 1.126 cm3, 0.072% (p < 0.001), respectively, when compared to those in Group 1 (defect area <125 cm2). The volumetric augmentation achieved by contour elevation for an extremely large skull defect was smaller than that achieved for a large skull defect. Conclusions: The 3D CAD skull model contour elevation method can be effectively used to simulate the extent of a space-occupying swollen brain and to quantitatively assess the extent of brainstem protection in terms of volume augmentation and volume-increasing rate following DC. As the tangential diameter (representing the degree of DC) exceeded the plateau value, volumetric augmentation was attenuated. However, an increasing volumetric augmentation was detected before the plateau value was reached.

Deep Learning Classifier with Patient's Metadata of Dermoscopic Images in Malignant Melanoma Detection.

BACKGROUND: Incidence of skin cancer is one of the global burdens of malignancies that increase each year, with melanoma being the deadliest one. Imaging-based automated skin cancer detection still remains challenging owing to variability in the skin lesions and limited standard dataset availability. Recent research indicates the potential of deep convolutional neural networks (CNN) in predicting outcomes from simple as well as highly complicated images. However, its implementation requires high-class computational facility, that is not feasible in low resource and remote areas of health care. There is potential in combining image and patient's metadata, but the study is still lacking. OBJECTIVE: We want to develop malignant melanoma detection based on dermoscopic images and patient's metadata using an artificial intelligence (AI) model that will work on low-resource devices. METHODS: We used an open-access dermatology repository of International Skin Imaging Collaboration (ISIC) Archive dataset consist of 23,801 biopsy-proven dermoscopic images. We tested performance for binary classification malignant melanomas vs nonmalignant melanomas. From 1200 sample images, we split the data for training (72%), validation (18%), and testing (10%). We compared CNN with image data only (CNN model) vs CNN for image data combined with an artificial neural network (ANN) for patient's metadata (CNN+ANN model). RESULTS: The balanced accuracy for CNN+ANN model was higher (92.34%) than the CNN model (73.69%). Combination of the patient's metadata using ANN prevents the overfitting that occurs in the CNN model using dermoscopic images only. This small size (24 MB) of this model made it possible to run on a medium class computer without the need of cloud computing, suitable for deployment on devices with limited resources. CONCLUSION: The CNN+ANN model can increase the accuracy of classification in malignant melanoma detection even with limited data and is promising for development as a screening device in remote and low resources health care.

Do Orthopedic Surgeons or Neurosurgeons Detect More Hip Disorders in Patients with Hip-Spine Syndrome? A Nationwide Database Study.

Background: Disorders of the hip and lumbar spine can create similar patterns of pain and dysfunction. It is unknown whether all surgeons, regardless of orthopedic or neurosurgery training, investigate and diagnose concurrent hip and spine pathology at the same rate. Methods: Data were retrieved from Taiwan's National Health Insurance Research Database (NHIRD). Enrolled patients were stratified into hip and spine surgery at the same admission (Both), hip surgery before spine surgery (HS), or spine surgery before hip surgery (SH). The SH group was further subdivided based on whether spine surgery was performed by an orthopedic surgeon (OS) or neurosurgeon (NS), and differences in preoperative radiographic examinations and diagnoses were collected and analyzed. Results: In total, 1824 patients received lumbar spine surgery within 1 year before or after hip replacement surgery. Of these, 103 patients had spine and hip surgery in the same admission (Both), 1290 patients had spine surgery before hip surgery (SH), and 431 patients had hip surgery before spine surgery (HS). In the SH group, patients were categorized into spine surgery by orthopedic surgeons (OS) (n = 679) or neurosurgeons (NS) (n = 522). In the SH group, orthopedic surgeons investigated hip pathology with X-rays more often (52.6% vs. 38.1%, p < 0.001) and diagnosed more cases of hip disease (43.6% vs. 28.9%, p < 0.001) than neurosurgeons. Conclusions: Of patients in Taiwan's NHIRD who had concurrent surgical degenerative hip and lumbar spine disorders who had spine surgery before hip surgery, orthopedic surgeons obtained hip images and made hip-related diagnoses more frequently than did neurosurgeons.

Travel for mindfulness through Zen retreat experience: A case study at Donghua Zen Temple.

This study seeks to contribute knowledge of the Zen retreat experience unique to Buddhist tourism. The research setting is the Zen retreats found at the Donghua Zen Temple in China. This study examined feedback obtained from 520 tourists who stayed at Zen retreats. Zen retreat organizer insights were obtained through online discussions. This study identified four motivations for, and three outcomes of, staying at Zen retreats. Within the Zen retreat experience, this study clarified four themes in knowledge growth (mingxin), three themes in spiritual growth (jianxing), and two mechanisms to foster knowledge and spiritual growth. This study further proposed a figure demonstrating Zen practitioners' lifelong journey, and a figure categorizing tourists in Buddhist tourism into Zen tourism, Zen lifestyle, and Zen retreat by level of involvement.

Government and social trust vs. hotel response efficacy: A protection motivation perspective on hotel stay intention during the COVID-19 pandemic.

Based on protection motivation theory (PMT), this study conceptualizes a research framework to explain and examine customer intentions regarding hotel stays during the COVID-19 pandemic. Data were collected from 700 U.S. consumers via a crowdsourcing website in July 2020. Structural equation modeling was used to analyze the collected data for testing proposed hypotheses. The analytical results showed that the level of threat perceived by customers significantly reduced their intention to stay at a hotel. On the contrary, individual customer response efficacy significantly enhanced their intention to stay at a hotel. Additionally, both government and social trust, as well as hotel response efficacy, were found to significantly increase hotel stay intention by mediating the effects of threat perception and individual response efficacy. To the best of our knowledge, this study is one of the first attempts to apply PMT to explain customer hotel stay intentions during the COVID-19 pandemic.

Hotel employees' fun climate at work: Effects on work-family conflict and employee deep acting through a collectivistic perspective.

Although the importance of workplace fun in hospitality organizations has been emphasized by scholars, discussion of the mechanism of a workplace fun climate in collectivistic cultural contexts is still rare in current literature. Therefore, based on a collectivistic perspective, this study aims to examine the effects of a three-component fun climate at work (socializing with coworkers, celebrating at work, and global fun at work) on employee deep acting and work-family conflict. A total of 389 usable survey responses were collected from full-time hotel employees in China. The results of this study reveal that socializing with coworkers and celebrating at work enhance global fun at work. Moreover, global fun at work significantly reduces employees' work-family conflict and strengthens their deep acting at work. Findings of this study not only contribute to knowledge of understanding workplace fun climate in hospitality literature but also offer valuable practical implications to the hospitality industry.

Age, Period and Cohort Analysis of Rates of Emergency Department Visits Due to Pneumonia in Taiwan, 1998-2012.

BACKGROUND: Emergency room (ER) physicians need to face clinically suspected pneumonia patients in the front line of medical care and must do to give major medical interventions if patients show severity in pneumonia. METHODS: The data of pneumonia-related ER visit rates were categorized based on the International Classification of Disease (ICD) Codes (480-486) between 1998 and 2012. We use an age-period-cohort (APC) model to separate the pneumonia-related ER visit rates to identify the effects of age, time period, and cohort for a total of 1,813,588 patients. RESULTS: The age effect showed high risk for pediatric and elder populations. There is a significant increasing period effect, which increased from 1998 to 2012. The cohort effect tended to show an oscillation from 1913 to 1988 and the reverse in a recent cohort. Furthermore, the visit rate of pneumonia showed an increase from 1998 to 2012 for both genders. CONCLUSION: Age is a risk factor for pneumonia-related ER visits, especially for children and adolescents and older patients. Period and cohort effects were also found to increase the pneumonia visit rates. An APC model used to provide an advance clue for trend of pneumonia-related ER visit rates diversified.

Statins use and its impact in EGFR-TKIs resistance to prolong the survival of lung cancer patients: A Cancer registry cohort study in Taiwan.

Statins have been shown to be a beneficial treatment as chemotherapy and target therapy for lung cancer. This study aimed to investigate the effectiveness of statins in combination with epidermal growth factor receptor-tyrosine kinase inhibitor therapy for the resistance and mortality of lung cancer patients. A population-based cohort study was conducted using the Taiwan Cancer Registry database. From January 1, 2007, to December 31, 2012, in total 792 non-statins and 41 statins users who had undergone EGFR-TKIs treatment were included in this study. All patients were monitored until the event of death or when changed to another therapy. Kaplan-Meier estimators and Cox proportional hazards regression models were used to calculate overall survival. We found that the mortality was significantly lower in patients in the statins group compared with patients in the non-statins group (4-y cumulative mortality, 77.3%; 95% confidence interval (CI), 36.6%-81.4% vs. 85.5%; 95% CI, 78.5%-98%; P = .004). Statin use was associated with a reduced risk of death in patients the group who had tumor sizes <3 cm (hazard ratio [HR], 0.51, 95% CI, 0.29-0.89) and for patients in the group who had CCI scores <3 (HR, 0.6; 95% CI, 0.41-0.88; P = .009). In our study, statins were found to be associated with prolonged survival time in patients with lung cancer who were treated with EGFR-TKIs and played a synergistic anticancer role.

Girls' Empowerment and Adolescent Pregnancy: A Systematic Review.

Background: 21 million girls get pregnant every year. Many initiatives are empowering girls. Various studies have looked at girl empowerment, however, there is contradicting evidence, and even less literature from developing countries. Methods: We searched articles published between January 2000 to January 2019. We followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and registered our protocol on the International Prospective Register of Systematic Reviews PROSPERO (CRD42019117414). Nine articles were selected for review. Quality appraisal was done using separate tools for qualitative studies, cohort and cross-sectional studies and randomized control trials. Results: Eight studies included educational empowerment, four studies included community empowerment, three studies included economic empowerment, while two studies discussed policy empowerment. Three studies were of fair quality; two qualitative and one cross-sectional study were of high quality, while three studies had low quality. Discussion. Studies showed a favorable impact of girl empowerment on adolescent pregnancies and risky sexual behaviors. Education empowerment came through formal education or health systems such as in family planning clinics. Community empowerment was seen as crucial in girls' development, from interactions with parents to cultural practices. Economic empowerment was direct like cash transfer programs or indirect through benefits of economic growth. Policies such as contraceptive availability or compulsory school helped reduce pregnancies.