Association between markers of glucose metabolism and the presence of glaucoma^*

<p>*Conducted in people not taking diabetes medications.</p>†<p>Adjusted for age, gender, and ethnicity.</p>‡<p>Further adjusted for smoking, physical activity, alcohol intake, education, and BMI.</p><p>Association between markers of glucose metabolism and the presence of glaucoma^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112460#nt112" target="_blank">*</a>}</p

Prevalence of glucose metabolism abnormalities by glaucoma status.^*

<p>*Data are percentages or means (SEs).</p>†<p>P value for homogeneity of means or proportions comparing participants with to those without glaucoma.</p><p>Prevalence of glucose metabolism abnormalities by glaucoma status.^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112460#nt104" target="_blank">*</a>}</p

Odds ratio and 95% CIs for the presence of glaucoma.

†<p>Adjusted for age, gender, and ethnicity.</p>‡<p>Further adjusted for smoking, physical activity, alcohol intake, education, and BMI.</p><p>*Diabetes defined as self-report, HbA1c ≥6.5%, fasting glucose ≥126 mg/dL, or taking diabetic medications.Pre-diabetes defined as self-report, HbA1c ≥5.7% to <6.5%, or fasting glucose ≥100 mg/dL to <126 mg/dL.</p>§<p>Diabetes defined as self-report, HbA1c ≥6.5%, or taking diabetic medications. Pre-diabetes defined as self-report or HbA1c ≥5.7% to <6.5%.</p>†<p>Diabetes defined as self-report, fasting glucose ≥126 mg/dL or taking diabetic medications. Pre-diabetes defined as self-report or fasting glucose ≥100 mg/dL to <126 mg/dL.</p>||<p>Values are based on the subsample of participants not taking insulin or medication for diabetes.</p><p>Odds ratio and 95% CIs for the presence of glaucoma.</p

Association between Personality Traits and Sleep Quality in Young Korean Women

<div><p>Personality is a trait that affects behavior and lifestyle, and sleep quality is an important component of a healthy life. We analyzed the association between personality traits and sleep quality in a cross-section of 1,406 young women (from 18 to 40 years of age) who were not reporting clinically meaningful depression symptoms. Surveys were carried out from December 2011 to February 2012, using the Revised NEO Personality Inventory and the Pittsburgh Sleep Quality Index (PSQI). All analyses were adjusted for demographic and behavioral variables. We considered beta weights, structure coefficients, unique effects, and common effects when evaluating the importance of sleep quality predictors in multiple linear regression models. Neuroticism was the most important contributor to PSQI global scores in the multiple regression models. By contrast, despite being strongly correlated with sleep quality, conscientiousness had a near-zero beta weight in linear regression models, because most variance was shared with other personality traits. However, conscientiousness was the most noteworthy predictor of poor sleep quality status (PSQI≥6) in logistic regression models and individuals high in conscientiousness were least likely to have poor sleep quality, which is consistent with an OR of 0.813, with conscientiousness being protective against poor sleep quality. Personality may be a factor in poor sleep quality and should be considered in sleep interventions targeting young women.</p></div

Long-term survival by etiology.

<p>The median survival was significantly longer in HCV-related HCC patients than in HBV-related HCC patients. (2.17 vs. 1.34 years, <i>P</i><0.01).</p

Additional file 1: of Obesity associates with vasomotor symptoms in postmenopause but with physical symptoms in perimenopause: a cross-sectional study

Flow chart of the subjects. (PPTX 36 kb

Survival by etiology.

<p>Abbreviation: HBV, hepatitis B virus; HCV, hepatitis C virus. HR, hazard ratio. Model 1  =  crude hazard ratio, Model 2  =  adjusted for age, gender, Model 3  =  Model 2 + Child-Pugh class and AJCC/mUICC stage, Model 4  =  Model 3 + initial treatment modality.</p><p>Survival by etiology.</p

The age-specific incidence rates of hepatocellular carcinoma (HCC) by the etiology (A), by gender in HBV-related HCC (B) and by gender in HCV-related HCC (C).

<p>The annual incidence rates of HBV-related HCC peaked in the 50–59 age group, while the annual incidence rates of HCV-related HCC kept gradually increasing until age ≥70 s. Similar trend was observed after stratified by gender, although the peak mean annual incidence rates was observed in the 50–59 in men and in the 60–69 in women in HBV-related HCC (B). Diamonds (♦) and triangles (▴) represent for HBV and HCV-related HCC in (A), men and women in (B) and (C), respectively.</p

Adjusted difference in the survival between hepatitis B virus and hepatitis C virus related hepatocellular carcinoma by subgroup.

<p>Abbreviation: HBV, hepatitis B virus; HCV, hepatitis C virus; CI, confidence interval; NR, not reached. In each adjusted model, hepatitis B was used as reference for hepatitis C and following variables were adjusted: age, gender, Child-Pugh class, AJCC/mUICC stage, and initial treatment modality.</p><p>Adjusted difference in the survival between hepatitis B virus and hepatitis C virus related hepatocellular carcinoma by subgroup.</p

Characteristics of study population.

<p>Abbreviation: HBV, hepatitis B virus; HCV, hepatitis C virus; S.D, standard deviation; INR, international normalized ratio; AJCC/mUICC, American Joint Committee on Cancer/International Union Against Cancer; BCLC, Barcelona Clinic Liver Cancer; TACE, transarterial chemoembolization; TACI, transarterial chemoinfusion.</p><p>*These 3 patients received ¹⁶⁶holmium injection therapy. Values are expressed as mean ± standard deviation, median (quartile), or no (%).</p>†<p>BCLC stage and performance status was not collected at the time of data collection. Hence, BCLC stage was re-coded (staged) by authors with Child-Pugh class, tumor size, tumor number and presence of portal vein invasion and extrahepatic spread, without performance status.</p><p>Characteristics of study population.</p