Elderly depression symptoms was the only factor significantly associating with poor sleep quality after adjustment. Higher level of physical activity was associated with better sleep quality in univariate analysis but not in multivariate analysis, which considered the factor of elderly depression symptoms in the elderly. The role of physical activity in late life potentially influence sleep quality but may have less significance compared with depression. Therefore, we suggest the need for more future research to investigate the relationship between elderly people's sleep and physical activity.

BackgroundsInternet addiction (IA) has become a major public health issue worldwide and is closely linked to psychiatric disorders and suicide. The present study aimed to investigate the prevalence of IA and its associated psychosocial and psychopathological determinants among internet users across different age groups.MethodsThe study was a cross-sectional survey initiated by the Taiwan Suicide Prevention Center. The participants were recruited from the general public who responded to the online questionnaire. They completed a series of self-reported measures, including Chen Internet Addiction Scale-revised (CIAS-R), Five-item Brief Symptom Rating Scale (BSRS-5), Maudsley Personality Inventory (MPI), and questions about suicide and internet use habits.ResultsWe enrolled 1100 respondents with a preponderance of female subjects (85.8%). Based on an optimal cutoff for CIAS-R (67/68), the prevalence rate of IA was 10.6%. People with higher scores of CIAS-R were characterized as: male, single, students, high neuroticism, life impairment due to internet use, time for internet use, online gaming, presence of psychiatric morbidity, recent suicide ideation and past suicide attempts. Multiple regression on IA showed that age, gender, neuroticism, life impairment, internet use time, and BSRS-5 score accounted for 31% of variance for CIAS-R score. Further, logistic regression showed that neuroticism, life impairment and internet use time were three main predictors for IA. Compared to those without IA, the internet addicts had higher rates of psychiatric morbidity (65.0%), suicide ideation in a week (47.0%), lifetime suicide attempts (23.1%), and suicide attempt in a year (5.1%).ConclusionNeurotic personality traits, psychopathology, time for internet use and its subsequent life impairment were important predictors for IA. Individuals with IA may have higher rates of psychiatric morbidity and suicide risks. The findings provide important information for further investigation and prevention of IA.

The transcriptional network of the SRY (sex determining region Y)-box 17 (SOX17) and the prognostic impact of SOX17 protein expression in human cancers remain largely unclear. In this study, we evaluated the prognostic effect of low SOX17 protein expression and its dysregulation of transcriptional network in esophageal squamous cell carcinoma (ESCC). Low SOX17 protein expression was found in 47.4% (73 of 154) of ESCC patients with predicted poor prognosis. Re-expression of SOX17 in ESCC cells caused reduced foci formation, cell motility, decreased ESCC xenograft growth and metastasis in animals. Knockdown of SOX17 increased foci formation in ESCC and normal esophageal cells. Notably, 489 significantly differential genes involved in cell growth and motility controls were identified by expression array upon SOX17 overexpression and 47 genes contained putative SRY element in their promoters. Using quantitative chromatin immunoprecipitation-PCR and promoter activity assays, we confirmed that MACC1, MALAT1, NBN, NFAT5, CSNK1A1, FN1 and SERBP1 genes were suppressed by SOX17 via the SRY binding-mediated transcriptional regulation. Overexpression of FN1 and MACC1 abolished SOX17-mediated migration and invasion suppression. The inverse correlation between SOX17 and FN1 protein expression in ESCC clinical samples further strengthened our conclusion that FN1 is a transcriptional repression target gene of SOX17. This study provides compelling clinical evidence that low SOX17 protein expression is a prognostic biomarker and novel cell and animal data of SOX17-mediated suppression of ESCC metastasis. We establish the first transcriptional network and identify new suppressive downstream genes of SOX17 which can be potential therapeutic targets for ESCC.

BackgroundHigh smoking prevalence is a major public health concern for people with mental disorders. Improved monitoring could be facilitated through electronic health record (EHR) databases. We evaluated whether EHR information held in structured fields might be usefully supplemented by open-text information. The prevalence and correlates of EHR-derived current smoking in people with severe mental illness were also investigated.MethodsAll cases had been referred to a secondary mental health service between 2008-2011 and received a diagnosis of schizophreniform or bipolar disorder. The study focused on those aged over 15 years who had received active care from the mental health service for at least a year (N=1,555). The ‘CRIS-IE-Smoking’ application used General Architecture for Text Engineering (GATE) natural language processing software to extract smoking status information from open-text fields. A combination of CRIS-IE-Smoking with data from structured fields was evaluated for coverage and the prevalence and demographic correlates of current smoking were analysed.ResultsProportions of patients with recorded smoking status increased from 11.6% to 64.0% through supplementing structured fields with CRIS-IE-Smoking data. The prevalence of current smoking was 59.6% in these 995 cases for whom this information was available. After adjustment, younger age (below 65 years), male sex, and non-cohabiting status were associated with current smoking status.ConclusionsA natural language processing application substantially improved routine EHR data on smoking status above structured fields alone and could thus be helpful in improving monitoring of this lifestyle behaviour. However, limited information on smoking status remained a challenge.

Acute kidney injury (AKI) is associated with higher hospital mortality. However, the relationship between geriatric AKI and in-hospital complications is unclear. We prospectively enrolled elderly patients (≥65 years) from general medical wards of National Taiwan University Hospital, part of whom presented AKI at admission. We recorded subsequent in-hospital complications, including catastrophic events, incident gastrointestinal bleeding, hospital-associated infections, and new-onset electrolyte imbalances. Regression analyses were utilized to assess the associations between in-hospital complications and the initial AKI severity. A total of 163 elderly were recruited, with 39% presenting AKI (stage 1: 52%, stage 2: 23%, stage 3: 25%). The incidence of any in-hospital complication was significantly higher in the AKI group than in the non-AKI group (91% vs. 68%, p < 0.01). Multiple regression analyses indicated that elderly patients presenting with AKI had significantly higher risk of developing any complication (Odds ratio [OR] = 3.51, p = 0.01) and new-onset electrolyte imbalance (OR = 7.1, p < 0.01), and a trend toward more hospital-associated infections (OR = 1.99, p = 0.08). The risk of developing complications increased with higher AKI stage. In summary, our results indicate that initial AKI at admission in geriatric patients significantly increased the risk of in-hospital complications.

BackgroundMolecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear.ResultsWe developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy.ConclusionsWe propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

Neutrophil to lymphocyte ratio (NLR) is an easy measurable laboratory marker used to evaluate systemic inflammation. Elevated NLR is associated with poor survival and increased morbidity in cancer and cardiovascular disease. However, the usefulness of NLR to predict morbidity and mortality in a hospital setting for patients with multiple chronic conditions has not been previously examined. In this study, we investigate the association between NLR and mortality in multimorbid medical inpatients. Two hundred thirty medical in-patients with chronic conditions were selected from a single academic medical center in Taiwan. Retrospective NLRs were calculated from routine full blood counts previously obtained during the initial hospital admission and at the time of discharge. Self-rated health (using a single-item question), medical disorders, depressive symptoms, and medical service utilization over a 1-year period were included in the analyses. Mortality outcomes were ascertained by reviewing electronic medical records and follow-up. The mortality rate at 2-year follow-up was 23%. Depression (odds ratio [OR] 1.9 [95% CI 1.0–3.7]), poor self-rated health (OR 2.1 [95% CI 1.1–3.9]), being hospitalized 2 or more times in the previous year (OR 2.3 [95% CI 1.2–4.6]), metastatic cancer (OR 4.7 [95% CI 2.3–9.7]), and chronic liver disease (OR 4.3 [95% CI 1.5–12.1]) were associated with 2-year mortality. The median (interquartile range) NLR at admission and discharge were 4.47 (2.4–8.7) and 3.65 (2.1–6.5), respectively. Two-year mortality rates were higher in patients with an elevated NLR at admission (NLR <3 = 15.5%, NLR >3 = 27.6%) and discharge (NLR < 3 = 14.7%, NLR >3 = 29.1%). Multivariate logistic regression demonstrated that an elevated NLR >3.0 at admission (OR 2.3 [95% CI 1.0–5.2]) and discharge (OR 2.3 [95% CI 1.1–5.0]) were associated with mortality independent of baseline age, sex, education, metastatic cancer, liver disease, depression, and previous hospitalization. Increased NLR is associated with mortality among medical inpatients with multiple chronic conditions. NLR may provide added value to predict both risk of mortality for the inpatients with chronic conditions, in addition to allowing predictions of likely hospital service needs such as re-admissions that are associated with long-term mortality.

Polypharmacy is common in the elderly due to multimorbidity and interventions. However, the temporal association between polypharmacy and renal outcomes is rarely addressed and recognized. We investigated the association between cardiovascular (CV) polypharmacy and the risk of acute kidney injury (AKI) in elderly patients.We used the Taiwan National Health Insurance PharmaCloud system to investigate the relationship between cumulative CV medications in the 3 months before admission and risk of AKI in the elderly at their admission to general medical wards in a single center. Community-dwelling elderly patients (>60 years) were prospectively enrolled and classified according to the number of preadmission CV medications. CV polypharmacy was defined as use of 2 or more CV medications.We enrolled 152 patients, 48% with AKI (based upon Kidney Disease Improving Global Outcomes [KDIGO] classification) and 64% with CV polypharmacy. The incidence of AKI was higher in patients taking more CV medications (0 drugs: 33%; 1 drug: 50%; 2 drugs: 57%; 3 or more drugs: 60%; P = 0.05) before admission. Patients with higher KDIGO grades also took more preadmission CV medications (P = 0.04). Multiple regression analysis showed that patients who used 1 or more CV medications before admission had increased risk of AKI at admission (1 drug: odds ratio [OR] = 1.63, P = 0.2; 2 drugs: OR = 4.74, P = 0.03; 3 or more drugs: OR = 5.92, P = 0.02), and that CV polypharmacy is associated with higher risk of AKI (OR 2.58; P = 0.02). Each additional CV medication increased the risk for AKI by 30%.We found that elderly patients taking more CV medications are associated with risk of adverse renal events. Further study to evaluate whether interventions that reduce polypharmacy could reduce the incidence of geriatric AKI is urgently needed.