Correlates of metabolic syndrome in patients with depression: A study from north-western India

Nebhinani, Naresh; Sharma, Praveen; Suthar, Navratan; Pareek, V.; Kunwar, Deep; Purohit, Priyanka; Purohit, Purvi

doi:10.1016/j.dsx.2020.10.013

Cited by 7 publications

(3 citation statements)

References 27 publications

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“…Reportedly, the catecholamine levels were signi cantly higher in depression patients compared with control patients, indicating that depression could lead to the abnormal increase of sympathetic nervous activity and the disorder of autonomous nervous system [25,26] . Moreover, the dysregulated hypothalamus-pituitaryadrenal axis and renin-angiotensin-aldosterone system also belonged to the important pathophysiological change in depression [27][28][29] . Importantly, lifestyle-related changes and behavioral mechanisms (e.g., smoking, obesity, alcohol abuse, physical inactivity, and medication nonadherence) for depression patients could serve as the predominant risk factors for AF development [30][31][32] .…”

Section: Discussionmentioning

confidence: 99%

Major depression disorder may have no causality on the atrial fibrillation risk: Evidence from the Mendelian randomization study

Li,

Wu,

Geng

et al. 2023

Preprint

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Background: Accumulated studies have indicated that depression was significantly associated with the atrial fibrillation (AF) risk. However, the causal effect of major depressive disorder (MDD) on the risk of AF was elusive. Methods: We performed a two-sample Mendelian randomization (MR) analysis using two genetic instrument tools for MDD to assess the potential causal effect of MDD on the AF risk, including a training dataset (37 single-nucleotide polymorphisms (SNPs) significantly associated with MDD) and a validation dataset (11 SNPs robustly associated with MDD). Inverse-variance weighted method (IVW), weighted median method, MR-Egger, MR-Pleiotropy REsidual Sum and Outlier (MR-PRESSO) test, pleiotropy test, and leave-one-out sensitivity analysis were performed for MR analyses. Results: We first performed MR analysis for a training data using multiple data processing steps, including removing SNPs related with AF risk factors, removing one outlier with MR-PRESSO, and tighten instrument P value threshold. The final MR estimates suggested that MDD had no causality on AF incidence (IVW method, OR = 1.04, 95%CI = 0.79–1.36, P value = 0.785; weighted median, OR = 1.15, 95%CI = 0.90–1.46, P value = 0.268; MR-Egger, OR = 1.00, 95%CI = 0.35–2.85, P value = 0.999). Moreover, a consistent result was displayed in MR estimates using a validation data. Pleiotropy test and leave-one-out sensitivity analysis revealed that our results were robust. Conclusions: Our MR analysis suggested that MDD may have no causality on the AF risk.

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Section: Discussionmentioning

confidence: 99%

Major depression disorder may have no causality on the atrial fibrillation risk: Evidence from the Mendelian randomization study

Li,

Wu,

Geng

et al. 2023

Preprint

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“…These cytokines act on the brain, resulting in symptoms of depression in susceptible populations, 54,55 and lead to systemic inflammation. The involvement of the HPA axis indicates that depression is often accompanied by hypertension, metabolic syndrome, and obesity, [56][57][58] which aggravate oxidative stress and inflammation in the body. Systemic inflammation increases the risk of AF by changing the electrophysiology (calcium flowing), conduction, and structural substrates of the atrium.…”

Section: Atrial Fibrillationmentioning

confidence: 99%

Confounding by Indication in Studies of Selective Serotonin Reuptake Inhibitors

Lee

Chang

2022

Psychiatry Investig

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Selective serotonin reuptake inhibitors (SSRIs) are used worldwide as the first-line pharmacological treatment for depression. Although SSRI use can increase the risk of suicide, fractures, and infertility, the nature of these relationships is controversial. This review reports confounding by indication and confounding by severity for SSRI side effects in previously published observational studies. The PubMed and Google Scholar databases were searched for English-language articles published from 2005 to 2022. SSRIs are often prescribed for depressive symptoms, and depression is associated with an increased risk of side effects. Therefore, confounding by indication, whereby patients are selected for a particular treatment depending on their diagnosis or severity of illness, may lead to erroneous treatment conclusions, resulting in an adverse outcome. The side effects of SSRIs that can be considered due to confounding by indication or severity include suicide, fractures, infertility, atrial fibrillation, stroke, autism spectrum disorder, and congenital malformation. When prescribing SSRIs for depression, physicians must consider confounding by indication and severity in the management of side effects. In addition, medication discontinuation should be carefully considered when side effects occur during the treatment.

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“…Age and modern lifestyle can lead to increased health problems for humans. Factors like depression, workloads requiring a person to sit frequently for a long period, immobility by body systems, and unhealthy diets may trigger a series of health problems, including central obesity, increased blood sugar levels, blood pressure, and cholesterol increased triglycerides [1]. These health problems, which may occur simultaneously, are known as Metabolic Syndrome (MetS).…”

Section: Introductionmentioning

confidence: 99%

Selection of Aggregation Function in Fuzzy Inference System for Metabolic Syndrome

Kusumadewi¹,

Rosita²,

Wahyuni³

2022

Int. J. Adv. Sci. Eng. Inf. Technol.

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Metabolic syndrome (MetS) has long-term, very detrimental effects, including chronic kidney disease, cardiovascular disease, stroke, and diabetes mellitus. Therefore, early detection of MetS is very important. Numerous global health organizations have made some Metabolic Syndrome (MetS) diagnosis criteria, but they are still mostly in a dichotomous form. On the other hand, a continuous MetS risk score has been proven to be more sensitive and with less risk of error. This study aims to build a Fuzzy Inference System (FIS) model. MetS diagnostic criteria issued by NCEP-APT III are used as a reference for generating rules. This model uses max, probor, and additive functions to obtain membership values as a result of rules aggregation in seven steps: 1) Identification of variables; 2) Determination of fuzzy sets and their membership functions; 3) Knowledge base generation; 4) Implementation of the implication functions; 5) Fuzzy rules aggregation; 6) Defuzzification; 7) Performance testing of the model and selecting the best aggregation function. The findings show the max function as the most suitable function for the aggregation process with an accuracy, sensitivity, specificity, and precision value of 100% according to the measurement results with NCEP-ATP III. A continuous risk score between 0% and 99.99% is considered a non-high risk, whereas a score of 100% indicates a high risk. This function also has an ideal risk value distribution according to the neighborhood level of the NCEP-ATP III diagnostic criteria.

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Correlates of metabolic syndrome in patients with depression: A study from north-western India

Cited by 7 publications

References 27 publications

Major depression disorder may have no causality on the atrial fibrillation risk: Evidence from the Mendelian randomization study

Major depression disorder may have no causality on the atrial fibrillation risk: Evidence from the Mendelian randomization study

Confounding by Indication in Studies of Selective Serotonin Reuptake Inhibitors

Selection of Aggregation Function in Fuzzy Inference System for Metabolic Syndrome

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