The association between sleep duration, quality, and nonalcoholic fatty liver disease: A cross-sectional study.

Sleep can affect nonalcoholic fatty liver disease (NAFLD). We investigated the association between sleep duration, sleep quality, and NAFLD. From January to December 2018, 1,073 patients (age: 37.94 ± 10.88, Body Mass Index (BMI): 22.85 ± 3.27) were enrolled. Pittsburgh Sleep Quality Index Questionnaire and Munich Chronotype Questionnaire were used to assess sleep duration, quality, and habits. Ultrasonography was used to diagnose NAFLD. Multivariate logistic regression models were used to calculate the odds ratio (OR) and 95% confidence interval (CI) of the risk of NAFLD by different types of sleep duration and sleep quality. No significant differences in sleep time, sleep quality, and sleep habits between the NAFLD and the non-NAFLD groups were observed (P > 0.05). There was no correlation between sleep duration and NAFLD in the whole cohort. After adjusting for age, exercise, fasting plasma glucose, and BMI, the group with long sleep duration showed a decreased risk of NAFLD in men (OR = 0.01, 95% CI: 0.001-0.27, P = 0.032). However, in all four adjusted models, no correlation between sleep duration, quality, and NAFLD was found in women. In conclusion, sleep duration was significantly and negatively associated with NAFLD in men but not women. Prospective studies are required to confirm this association.

Sex-specific differences in the associations of metabolic syndrome or components with gallstone disease in Chinese euthyroid population.

In euthyroid population, it is uncertain whether there is sex-specific difference in the associations of metabolic syndrome (MetS) or its components with gallstone disease (GSD); in general population, MetS increases the risk of GSD. This was a cross-sectional study to investigate the sex-specific difference in the prevalence of MetS according to GSD status and the associations of MetS or its components with GSD in Chinese euthyroid population. The total prevalence of GSD was 8.1% (6.5% in men and 11.0% in women, with a significant difference (p < 0.001)). The total presence of MetS was 10.7% (12.1% in men and 8.2% in women,with a significant difference (p = 0.001)). The age-adjusted odds ratio of MetS for GSD was 2.775 in men (p < 0.001), 2.543 in women (p = 0.007) and 2.503 in the oveall samples (p < 0.001). Univariate analysis revealed that fasting plasma glucose (FPG), high-density lipoprotein cholesterol (HDL-C) and thyroid-stimulating hormone (TSH) were associated with the prevalence of GSD. After adjustment for age, multivariate logistic regression analysis demonstrated that above three parameters were still significantly associated with the risk of GSD in general population; FPG and HDL-C but not TSH levels were significantly associated with the risk of GSD in men; and FPG and TSH levels but not HDL-C in women. Our study demonstrated that in euthyroid population, MetS appeared to be strongly associated with GSD regardless of sex, and FPG and TSH were two independent risk factors for GSD in men, while FPG and HDL-C in women.

Gene co-expression analysis identifies modules related to insufficient sleep in humans.

BACKGROUND: Insufficient sleep and circadian rhythm disruption may cause cancer, obesity, cardiovascular disease, and cognitive impairment. The underlying mechanisms need to be elucidated. METHOD: Weighted gene co-expression network analysis (WGCNA) was used to identify co-expressed modules. Connectivity Map tool was used to identify candidate drugs based on top connected genes. R ptestg package was utilized to detected module rhythmicity alteration. A hypergeometric test was used to test the enrichment of insomnia SNP signals in modules. Google Scholar was used to validate the modules and hub genes by literature. RESULTS: We identified a total of 45 co-expressed modules. These modules were stable and preserved. Eight modules were correlated with sleep restriction duration. Module rhythmicity was disrupted in sleep restriction subjects. Hub genes that involve in insufficient sleep also play important roles in sleep disorders. Insomnia GWAS signals were enriched in six modules. Finally, eight drugs associated with sleep disorders were identified. CONCLUSION: Systems biology method was used to identify sleep-related modules, hub genes, and candidate drugs. Module rhythmicity was altered in sleep insufficient subjects. Thiamphenicol, lisuride, timolol, and piretanide are novel candidates for sleep disorders.

Exploration of the risk factors of essential hypertension with hyperhomocysteinemia: A hospital-based study and nomogram analysis.

OBJECTIVES: To explore the risk factors of essential hypertension with hyperhomocysteinemia (H-type hypertension) and design a nomogram to predict this risk. METHODS: A hospital-based study was conducted on 1,712 individuals, including 282 patients with H-type hypertension, 105 patients with simple hypertension, 645 individuals with hyperhomocysteinemia, and 680 healthy controls. Logistic regression and nomogram models were applied to evaluate the risk factors. RESULTS: Logistic regression showed that advanced age, male sex, high body mass index (BMI), high total cholesterol levels, high glucose levels, and high creatinine levels were risk factors of H-type hypertension in the healthy population and were integrated into the nomogram model. Advanced age, male sex, high BMI, high total cholesterol levels, and high glucose levels were shown to be risk factors of H-type hypertension in the hyperhomocysteinemia population. Male sex and high creatinine levels were shown to be risk factors of H-type hypertension in the hypertension population. Nomogram analysis showed that the total factor score ranged from 106 to 206, and the corresponding risk rate ranged from 0.05 to 0.95. CONCLUSIONS: Men are more likely to have H-type hypertension, and advanced age, high BMI, high total cholesterol levels, and high glucose levels are risk factors of H-type hypertension in healthy and hyperhomocysteinemia populations. Furthermore, high creatinine level is a risk factor of H-type hypertension in healthy and hypertension populations. Nomogram models may be used to intuitively evaluate H-type hypertension risk and provide a basis for personalized interventions.

Exploration of the risk factors of essential hypertension with hyperhomocysteinemia: A hospital-based study and nomogram analysis

OBJECTIVES: To explore the risk factors of essential hypertension with hyperhomocysteinemia (H-type hypertension) and design a nomogram to predict this risk. METHODS: A hospital-based study was conducted on 1,712 individuals, including 282 patients with H-type hypertension, 105 patients with simple hypertension, 645 individuals with hyperhomocysteinemia, and 680 healthy controls. Logistic regression and nomogram models were applied to evaluate the risk factors. RESULTS: Logistic regression showed that advanced age, male sex, high body mass index (BMI), high total cholesterol levels, high glucose levels, and high creatinine levels were risk factors of H-type hypertension in the healthy population and were integrated into the nomogram model. Advanced age, male sex, high BMI, high total cholesterol levels, and high glucose levels were shown to be risk factors of H-type hypertension in the hyperhomocysteinemia population. Male sex and high creatinine levels were shown to be risk factors of H-type hypertension in the hypertension population. Nomogram analysis showed that the total factor score ranged from 106 to 206, and the corresponding risk rate ranged from 0.05 to 0.95. CONCLUSIONS: Men are more likely to have H-type hypertension, and advanced age, high BMI, high total cholesterol levels, and high glucose levels are risk factors of H-type hypertension in healthy and hyperhomocysteinemia populations. Furthermore, high creatinine level is a risk factor of H-type hypertension in healthy and hypertension populations. Nomogram models may be used to intuitively evaluate H-type hypertension risk and provide a basis for personalized interventions.

Sex differences in subclinical hypothyroidism and associations with metabolic risk factors: a health examination-based study in mainland China.

BACKGROUND: The association between subclinical hypothyroidism (SCH) and metabolic risk factors in the general health examination-based population has been widely explored. However, the results have been inconclusive. Additionally, the sex differences in the prevalence of SCH and the association of SCH with metabolic risk factors remain unknown. METHODS: We conducted this cross-sectional study using data from health examination-based participants between June 2016 and April 2018 in our health examination centre. Sex differences SCH and the association of SCH with metabolic risk factors were explored. RESULTS: The total prevalence of SCH was 3.40% among the 5319 included participants, and 4.90% among the 2306 female participants, which was much higher than the prevalence of 2.26% among the 3013 male participants (p < 0.05). In males, the difference between participants younger than 60 and aged 60 or older was not significant (p = 0.104); while in females, the difference between participants younger than 40 and participants aged 40 or older was statistically significant (p = 0.023). Multivariate logistic regression analysis demonstrated that age (OR = 0.568, p = 0.004), body-mass index (BMI) (OR = 5.029, p < 0.001) and systolic/diastolic blood pressure (SBP/DBP) (OR = 5.243, p < 0.001) were independent predictors of SCH in females, but no metabolic risk factor was significantly associated with SCH in males. Further analysis revealed that the prevalence was much higher in participants with one or two metabolic risk factors than in those with no above metabolic risk factors regardless of age (p < 0.01). CONCLUSIONS: Our study demonstrates that high BMI and/or high blood pressure are associated with SCH in female participants, and the prevalence of SCH among women with one or two metabolic risk factors ranges from 7.69-14.81%, which indicates that in such a population, serum concentrations of TSH and FT4 may be routinely screened in mainland China. Certainly, prospective, large-scale studies with long follow-up period are still necessary to further verify our results.

Association between body mass index and fatty liver risk: A dose-response analysis.

Body mass index (BMI) is associated with fatty liver risk, however, the dose-response relationship between continuous BMI changes and fatty liver risk has not been clearly defined. In this study, a cross-sectional study was conducted and a total of 3202 individuals were included. Unconditional logistic regression and restricted cubic spline model were used to analyze the dose-response association of BMI with fatty liver risk. After adjusting for confounding factors (age, gender, hypertension, total cholesterol, triglycerides, glucose, high-density lipoprotein, low-density lipoprotein, uric acid, homocysteine, creatinine, aspartate aminotransferase and alanine transaminase), overweight (OR = 3.55, 95% CI: 2.49-5.06, P = 2.79 × 10-12), obesity (OR = 7.59, 95% CI: 4.91-11.71, P = 6.56 × 10-20) were significantly related to fatty liver risk. Stratified by gender (male/female), age (<50 years/≥50 years), prevalence of hypertension (yes/no), the above association was still significant (P = 0.004 or lower). In dose-response analysis, BMI was statistically significantly associated with fatty liver risk in a nonlinear fashion (approximately J-shaped fashion, Pnonlinearity = 1.71 × 10-4 or lower) in the total population and all subgroups mentioned above. Findings from this dose-response analysis suggest that higher BMI (overweight/obesity) is an independent, dose-dependent risk factor for fatty liver, and prevention of fatty liver focusing on continuous changes in BMI should be noted.

Effects of acute normovolemic hemodilution on perioperative coagulation and fibrinolysis in elderly patients undergoing hepatic carcinectomy.

OBJECTIVE: To observe the effects of acute normovolemic hemodilution (ANH) on coagulation function and fibrinolysis in elderly patients undergoing hepatic carcinectomy. METHODS: Thirty elderly patients (aged 60-70 years) with liver cancer (American Society of Anesthesiologists physical status I-II) scheduled for hepatic carcinectomy from February 2007 to February 2008 were randomly divided into ANH group (n = 15) and control group (n = 15). After tracheal intubation, patients in ANH group and control group were infused with 6% hydroxyethyl starch (HES) (130/0.4), and basic liquid containing 6% HES and routine Ringer's solution, respectively. In all the studied patients, blood samples were drawn at five different time points: before anesthesia induction (T1), 30 minutes after ANH (T2), 1 hour after start of operation (T3), immediately after operation (T4), and 24 hours after operation (T5). Then coagulation function, soluble fibrin monomer complex (SFMC), prothrombin fragment (F1+2), and platelet membrane glycoprotein (activated GPIIb/GPIIIa and P-selectin) were measured. RESULTS: The perioperative blood loss was not significantly different between the two groups (P > 0.05). The volume of allogeneic blood transfusion in ANH group was significantly smaller than that in control group (350.5 +/- 70.7 mL vs. 457.8 +/- 181.3 mL, P < 0.01). Compared with the data of T1, prothrombin time (PT) and activated partial thromboplastin time in both groups prolonged significantly after T3 (P < 0.05), but still within normal range. There were no significant changes in thrombin time and D-dimer between the two groups and between different time points in each group (all P > 0.05). SFMC and F1 + 2 increased in both groups, but without statistical significance. P-selectin expression on the platelet surface of ANH group was significantly lowered at T2 and T3 compared with the level at T1 (P < 0.05). Compared with control group, P-selectin was significantly lower in ANH group at T2-T5 (all P < 0.05). CONCLUSIONS: In elderly patients undergoing resection of liver cancer, ANH may not hamper fibrinolysis and coagulation function. It could therefore be safe to largely reduce allogeneic blood transfusion.