Lipid ratios and appropriate cut off values for prediction of diabetes: a cohort of Iranian men and women

<p>Abstract</p> <p>Background</p> <p>Dyslipidemia is a risk factor for incident type 2 diabetes; however, no study has specifically assessed the lipid ratios (i.e. total cholesterol (TC)/high density lipoprotein cholesterol (HDL-C) and triglyceride (TG)/HDL-C) as predictors of diabetes. We aimed to compare the independent association between the different lipid measures with incident diabetes over a median follow up of 6.4 years in Iranian men and women.</p> <p>Method</p> <p>The study population consisted of 5201 non diabetic (men = 2173, women = 3028) subjects, aged ≥20 years. The risk factor adjusted odds ratios (ORs) for diabetes were calculated for every 1 standard deviation (SD) change in TC, log-transformed TG, HDL-C, non-HDL-C, TC/HDL-C and log-transformed TG/HDL-C using multivariate logistic regression analysis. Receiver operator characteristic (ROC) curve analysis was used to define the points of the maximum sum of sensitivity and specificity (MAXss) of each lipid measure as a predictor of diabetes.</p> <p>Result</p> <p>We found 366 (146 men and 220 women) new diabetes cases during follow-up. The risk-factor-adjusted ORs for a 1 SD increase in TG, TC/HDL-C and TG/HDL-C were 1.23, 1.27 and 1.25 in men; the corresponding risks in females were 1.36, 1.14, 1.39 respectively (all p < 0.05, except TC/HDL-C in females which was marginally significant, p = 0.07). A 1 SD increase of HDL-C only in women decreased the risk of diabetes by 25% [0.75(0.64-0.89)]. In both genders, there was no difference in the discriminatory power of different lipid measures to predict incident diabetes in the risk factor adjusted models (ROC ≈ 82%). TG cutoff values of 1.98 and 1.66 mmol/l; TG/HDL-C cutoff values of 4.7 and 3.7, in men and women, respectively, TC/HDL-C cutoff value of 5.3 in both genders and HDL-C cutoff value of 1.18 mmol/l in women yielded the MAXss for defining the incidence of diabetes.</p> <p>Conclusion</p> <p>TC/HDL-C and TG/HDL-C showed similar performance for diabetes prediction in men population however; among women TG/HDL-C highlighted higher risk than did TC/HDL-C, although there was no difference in discriminatory power. Importantly, HDL-C had a protective effect for incident diabetes only among women.</p

Prevalence, awareness, treatment, and control of type 2 diabetes mellitus among the adult residents of tehran: Tehran Cohort Study.

BACKGROUND The prevalence of type 2 diabetes mellitus has increased in the past decades. We investigated the prevalence of diabetes and its awareness, treatment, and control among adult residents of Tehran. METHODS We used the recruitment phase data of the Tehran Cohort study, enrolling a random sample of adult residents of Tehran aged ≥35 years. Diabetes was defined as self-report, current use of glucose-lowering medications, and/or fasting plasma glucose (FPG) ≥126mg/dl. Impaired fasting glucose (IFG) was defined as an FPG of 100-125mg/dl. Awareness was defined as diabetes self-report, treatment as receiving glucose-lowering medications, and glycemic control as FPG <126mg/dl. The age- and sex-weighted estimates were calculated using the 2016 national census. Logistic regression models were used to determine the factors associated with diabetes awareness, treatment, and control. RESULTS A total of 8151 participants were included. Age- and sex-weighted prevalence of diabetes mellitus and IFG were 16.7% (95% CI: 15.1-18.4) and 25.1% (95% CI: 23.1-27.1), respectively. Diabetes was more prevalent in the eastern and central districts of Tehran. Advanced age (OR per 1-year increase: 1.026, 95% CI: 1.021-1.030), male sex (OR: 1.716, 95% CI: 1.543-1.909), higher BMI levels (OR for BMI ≥35 vs. <20 kg/m2: 4.852, 95% CI: 3.365-6.998), pre-existing hypertension (OR: 1.552, 95% CI: 1.378-1.747), dyslipidemia (OR: 1.692, 95% CI: 1.521-1.883), and chronic kidney disease (OR: 1.650, 95% CI: 1.019-2.673) were associated with an increased odds of diabetes mellitus. On the contrary, diabetes mellitus was less likely in current tobacco (OR: 0.872, 95% CI: 0.765-0.994) and alcohol users (OR: 0.836, 95% CI: 0.703-0.994) compared to non-users. Among diabetic individuals, 82.8% were aware of their condition, 71.9% received treatment, and 31.7% of treated patients had adequate glycemic control. Advanced age and pre-existing comorbidities, including hypertension and dyslipidemia, were associated with higher diabetes awareness and treatment. Furthermore, advanced age, higher levels of education, and female sex were determinants of better glycemic control among treated diabetic participants. CONCLUSION There is a high prevalence of diabetes and IFG among adult residents of Tehran. Additionally, more than two-thirds of treated diabetics living in Tehran remain uncontrolled

Modeling of cerebellar transcranial electrical stimulation effects on hand tremor in Parkinson’s disease

IntroductionParkinson’s disease (PD) is a neurodegenerative disorder with different motor and neurocognitive symptoms. Tremor is a well-known symptom of this disease. Increasing evidence suggested that the cerebellum may substantially contribute to tremors as a clinical symptom of PD. However, the theoretical foundations behind these observations are not yet fully understood.MethodsIn this study, a computational model is proposed to consider the role of the cerebellum and to show the effectiveness of cerebellar transcranial alternating current stimulation (tACS) on the rest tremor in participants with PD. The proposed model consists of the cortex, cerebellum, spinal circuit-muscular system (SC-MS), and basal ganglia blocks as the most critical parts of the brain, which are involved in generating rest tremors. The cortex, cerebellum, and SC-MS blocks were modeled using Van der Pol oscillators that interacted through synchronization procedures. Basal ganglia are considered as a regulator of the coupling weights defined between oscillators. In order to evaluate the global behavior of the model, we applied tACS on the cerebellum of fifteen PD patients for 15 min at each patient’s peak frequency of their rest tremors. A tri-axial accelerometer recorded rest tremors before, during, and after the tACS.Results and DiscussionThe simulation of the model provides a suggestion for the possible role of the cerebellum on rest tremors and how cerebellar tACS can affect these tremors. Results of human experiments also showed that the online and offline effects of cerebellar tACS could lead to the reduction of rest tremors significantly by about %76 and %68, respectively. Our findings suggest that the cerebellar tACS could serve as a reliable, therapeutic technique to suppress the PD tremor

Does the implementation of a Quality Improvement Care Bundle reduce the incidence of acute kidney injury in patients undergoing emergency laparotomy?

Previous work has demonstrated a survival improvement following the introduction of an enhanced recovery protocol in patients undergoing emergency laparotomy (the emergency laparotomy pathway quality improvement care (ELPQuiC) bundle). Implementation of this bundle increased the use of intra-operative goal directed fluid therapy and ICU admission, both evidence-based strategies recommended to improve kidney outcomes. The aim of this study was to determine if the observed mortality benefit could be explained by a difference in the incidence of AKI pre- and post-implementation of the protocol.This article is freely available via Open Access. Click on the Publisher URL to access the full-text via the publisher's site

Population-based incidence of Type 2 diabetes and its associated risk factors: results from a six-year cohort study in Iran

<p>Abstract</p> <p>Background</p> <p>The Middle East is estimated to have the largest increase in prevalence of diabetes by 2030; yet there is lack of published data on the incidence of Type 2 diabetes in this region. This study aimed to estimate Type 2 diabetes incidence and its associated risk factors in an Iranian urban population.</p> <p>Methods</p> <p>Among 3307 non-diabetics ≥ 20 years (mean age 42 ± 13 years, 42% males), glucose tolerance test was performed at baseline in 1999–2001 and at two consecutive phases in 2001–2005 and 2005–2008. Diabetes and glucose tolerance status were defined according to the ADA 1997 criteria. Logistic regression was used to determine the independent variables associated with incident diabetes and their odds ratios (OR).</p> <p>Results</p> <p>After median follow-up of 6 years, 237 new cases of diabetes were ascertained corresponding to an age and sex standardized cumulative incidence of 6.4% (95%CI: 5.6–7.2) and incidence rate of 10.6 (9.2–12.1) per 1000 person years. Besides classical diabetes risk factors, female sex and low education level significantly increased risk of diabetes in age adjusted models. In full model, the independent predictors were age [OR, 95%CI: 1.2 (1.1–1.3)], family history of diabetes [1.8 (1.3–2.5)], body mass index ≥ 30 kg/m²[2.3 (1.5–3.6)], abdominal obesity [1.9 (1.4–2.6)], high triglyceride [1.4 (1.1–1.9)], Isolated impaired fasting glucose (IFG) [7.4 (3.6–15.0)], Isolated impaired glucose tolerance (IGT) [5.9 (4.2–8.4)] and combined IFG and IGT [42.2 (23.8–74.9)].</p> <p>Conclusion</p> <p>More than 1% of the Iranian urban population older than 20 years develops Type 2 diabetes each year. Combination of IFG and IGT was the strongest predictor of incident diabetes among the modifiable risk factors.</p

Novel reliable model by integrating the adaptive neuro-fuzzy inference systems with wavelet transform and firefly algorithms for rainfall forecasting in the north of Iran

Abstract Rainfall is perhaps the most important source of drinking and agriculture water for the inhabitants of different parts of the world, particularly in arid and semi-arid area like Iran. Hence, the simulation of this hydrological phenomenon is crucial. The current research attempts to reproduce the long-term monthly precipitation of Ardabil, Iran, during 44 years from 1976 to 2020 for the first time via a hybrid fuzzy technique. For developing this model (WANFIS-FA), adaptive neuro-fuzzy inference system (ANFIS), firefly algorithm and wavelet transform were integrated. Firstly, the impacting lags of time series data were recognized by using the autocorrelation function and 14 WANFIS-FA models were defined using them. Then, the results of WANFIS-FA models were evaluated and the best WANFIS-FA model and the most influencing lags were found. For example, the variance accounted for index (VAF), correlation coefficient (R) and Nash–Sutcliffe coefficient (NSC) values for the superior WANFIS-FA model were computed to be 98.082, 0.990 and 0.980, respectively. In addition, the lags (t − 1), (t − 2), (t − 3) and (t − 12) were the most effective ones. Next, different members of the mother wavelet were tested and finally demy was selected as an optimal wavelet. Also, the analysis of the outcomes of the hybrid models demonstrated that the wavelet transform meaningfully enhanced the efficiency of the neuro-fuzzy model. Finally, the efficiency of WANFIS-FA was compared with ANFIS, WANFIS and ANFIS-FA, which displayed that WANFIS-FA performed better

Discrimination between Obstructive Coronary Artery Disease and Cardiac Syndrome X in Women with Typical Angina and Positive Exercise Test; Utility of Cardiovascular Risk Calculators

Introduction: Nearly 40% of women with typical angina and a positive exercise tolerance test (ETT) have normal or near normal coronary angiography (CAG) labeled as cardiac syndrome X (CSX). Objective: We performed this study to evaluate the power of common cardiovascular risk calculators to distinguish patients with CSX from those with coronary artery disease (CAD). Methods: 559 women participated in the study. Three risk scores, including (1) newly pooled cohort equation of American College of Cardiology/American Heart Association (ACC/AHA) to predict 10 years risk of first atherosclerotic cardiovascular hard event (ASCVD), (2) Framingham risk score (FRS) for the prediction of 10 years coronary heart disease, and (3) the SCORE tool to estimate 10-year risk of cardiovascular mortality (SCORE), were applied. Results: CAD was diagnosed in 51.5% of the patients. 11.6% of the population had ASCVD &lt; 2.5%, and only 13.8% of these patients had CAD on their CAG. By choosing FRS, 14.4% of patients had FRS &lt; 7.5%, and only 11.3% of these patients had recorded CAD on CAG, while the rest of the patients were diagnosed as CSX. Using the SCORE model, 13.8% of patients had the least value (&lt;0.5%) in whom the prevalence of CAD was 19.9%. The area under receiver operating characteristic curve (AUROC) to discriminate CSX from CAD was calculated for each scoring system, being 0.750 for ASCVD, 0.745 for FRS, and 0.728 for SCORE (p value for all AUROCs &lt; 0.001). The Hosmer&ndash;Lemeshow chi squares (df, p value) for calibration were 8.787 (8, 0.361), 11.125 (8, 0.195), and 10.618 (8, 0.224) for ASCVD, FRS, and SCORE, respectively. Conclusions: Patients who have ASCVD &lt; 2.5% or FRS &lt; 7.5% may be appropriate cases for noninvasive imaging (Such as coronary CT angiography). CAG is indicated for patients with ASCVD &ge; 7.5% and FRS &ge; 15%, whereas the patients with intermediate risk need comprehensive patient&ndash;physician shared decision-making