Associations between depression, nutrition, and outcomes among individuals with coronary artery disease

Looking for a Novel Vegan Protein Supplement from Faba Bean, Lupine, and Soybean: a Dietary and Industrial Standpoint

Global population growth poses a threat to sustainable development. Meanwhile, the use of plant proteins as healthy and sustainable alternatives to animal proteins needs further research. Therefore, this investigation was designed to study the nutritive, structural, and thermal properties of isolated protein fractions from different legumes, i.e., faba bean (FPI), soybean (SPI), and lupine (LPI). As a prospective plant-based protein powder, an equal mixture (MPI) of the three prior legume samples was formulated to study its properties compared to each sole sample. The alkaline extraction and isoelectric precipitation (AE-IP) technique was used for protein isolation. Results showed that all protein isolates had reasonable levels of protein with maximum protein content in SPI (96.15%). The MPI sample, however, came out on top in terms of amino acid profile followed by FBI. Compared to SPI and LPI, it had the highest isoleucine content and higher methionine, valine, leucine, phenylalanine, and lysine. Moreover, MPI showed a median particle charge (-37.1 mV) compared to FPI, SPI, and LPI samples. MPI sample peak showed resistance to heat denaturation at a temperature greater than 200 °C when the DSC test was conducted. With respect to its rheological characteristics, it outperformed the other three protein isolates and exhibited the highest values of storage modulus G' and loss modulus G". Consequently, our study suggests that pulse-derived protein isolate mixture can be used as a unique type of nutritious dietary protein supplement. It could be a good nutritional alternative to proteins derived from animals.

Integrating social determinants of health in medical education: a bibliometric analysis study

OBJECTIVES

Social determinants of health (SDH) are the prevalent enablers of health among populations, and integrating them in medical education will advance clinical care by integrating social and economic risk data into medical diagnosis and treatment. Despite the numerous publications on SDH and medical education, the publication trends are not known. The study aims to analyse publication trends in integrating SDH into medical education and the corresponding thematic areas.

STUDY DESIGN

This was a bibliometric analysis study.

METHODS

Bibliometric was used. Data from Scopus databases from January 2006 to June 2023 were retrieved with no language restriction. VOSviewer software was used for analysis. Bibliographic coupling was used to identify the clusters of published literature on the integration of SDH into medical education, followed by the analysis of annual distribution and growth trends, authors and co-author relationships and collaborations.

RESULTS

A total of 1047 articles were retrieved. The annual research publication exhibited a swift surge in the studies conducted during the reviewed period. Five clusters of information were derived: relating to curriculum development, community engagement and service-learning, stakeholder collaborations, development of assessment methods and tools for SDH, and the impact of integrating SDH into medical education.

CONCLUSION

Bibliometric analysis has revealed a growing trend in the field of integrating SDH into medical education, and the study has highlighted the research impact through bibliographic coupling by identifying the five thematic areas. This study lays a foundation for advancing knowledge on what has been published and possible areas for improvement in the integration of SDH into medical education.

Prognostic impact of malnutrition in patients with coronary artery disease: a systematic review and meta-analysis

CONTEXT

Conflicting predictions of malnutrition for the long-term prognosis of coronary artery disease (CAD) exist.

OBJECTIVE

This study aimed to investigate the relationship between malnutrition and long-term prognosis of patients with CAD.

DATA SOURCES

Four databases were searched for articles from February 11, 1936, to September 10, 2022.

DATA EXTRACTION

Cohort studies adjusting for multiple cardiovascular risk factors with data on CAD and malnutrition were included. Malnutrition was measured and defined by different nutritional evaluation tools. The hazard ratios (HRs) and confidence intervals (CIs) for all-cause mortality and major adverse cardiovascular events (MACEs) were synthesized. Subgroup analyses were performed based on study design, assessment tools, ethnicity/race, follow-up, sample size, and types of CAD. Meta-regression was used to compare whether the effect sizes of the 2 subgroups were statistically significant.

DATA ANALYSIS

A total of 30 cohort studies were included, totaling 81 361 participants with CAD. Nutritional evaluation tools, including the Geriatric Nutritional Risk Index (GNRI), Controlling Nutritional Status (CONUT), Nutritional Risk Screening 2002, Mini-Nutritional Assessment, and Prognostic Nutritional Index, were used. Malnutrition increased all-cause mortality (HR = 1.72; 95% CI: 1.53, 1.93) and MACEs (HR = 1.47; 95% CI: 1.35, 1.60) in patients with CAD. Subgroup analysis revealed the results were consistent across study design, ethnicity/race, follow-up, sample size, and types of CAD. Subgroup analyses and meta-regression revealed that malnutrition was associated with a higher risk of all-cause mortality (HR = 2.26; 95% CI: 1.91, 2.68) and MACEs (HR = 2.28; 95% CI: 1.69, 3.08) in patients with stable CAD than those with other types of CAD. Meta-regression revealed that the GNRI (HR = 2.20; 95% CI: 1.65, 2.93) was more effective than CONUT (HR = 1.47; 95% CI: 1.21, 1.78) in predicting all-cause mortality.

CONCLUSION

Malnutrition independently increased all-cause mortality by 72% and MACEs by 47% in patients with CAD, especially with stable CAD. The GNRI is a more effective nutritional evaluation tool than CONUT in predicting all-cause mortality.

Prognostic nutritional index and prognosis of patients with coronary artery disease: A systematic review and meta-analysis

Background

This review assessed if prognostic nutritional index (PNI) can predict mortality and major adverse cardiac events (MACE) in coronary artery disease (CAD) patients.

Methods

PubMed, Web of Science, Scopus, and Embase were searched up to 1st November 2022 for all types of studies reporting adjusted associations between PNI and mortality or MACE in CAD patients. A random-effect meta-analysis was conducted for PNI as categorical or continuous variable. Subgroup analysis were conducted for multiple confounders.

Results

Fifteen studies with 22,521 patients were included. Meta-analysis found that low PNI was a significant predictor of mortality in CAD patients as compared to those with high PNI (HR: 1.67 95% CI: 1.39, 2.00 I2 = 95% p < 0.00001). Increasing PNI scores were also associated with lower mortality (HR: 0.94 95% CI: 0.91, 0.97 I2 = 89% p = 0.0003). Meta-analysis demonstrated that patients with low PNI had significantly higher incidence of MACE (HR: 1.57 95% CI: 1.08, 2.28 I2 = 94% p = 0.02) and increasing PNI was associated with lower incidence of MACE (HR: 0.84 95% CI: 0.72, 0.92 I2 = 97% p = 0.0007). Subgroup analyses showed mixed results.

Conclusion

Malnutrition assessed by PNI can independently predict mortality and MACE in CAD patients. Variable PNI cut-offs and high inter-study heterogeneity are major limitations while interpreting the results. Further research focusing on specific groups of CAD and taking into account different cut-offs of PNI are needed to provide better evidence.

Systematic Review Registration

No CRD42022365913 https://www.crd.york.ac.uk/prospero/.

Association of Controlling Nutritional Status Score With Adverse Outcomes in Patients With Coronary Artery Disease: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis sought to examine the association between the controlling nutritional status (CONUT) score and adverse outcomes in patients with coronary artery disease (CAD). PubMed and Embase databases were searched for eligible studies from their inceptions to December 12, 2021 to identify studies investigating the association of the CONUT score with major adverse cardiovascular events (MACEs) and all-cause mortality in CAD patients. Twelve studies (36,198 CAD) patients satisfied the criteria. Comparison of the high with low CONUT score, the pooled multivariate adjusted risk ratios (RR) was 1.78 (95% confidence intervals [CI] 1.36-2.32) for MACEs and 1.45 (95% CI 1.27-1.66) for all-cause mortality, respectively. When compared with patients with normal nutrition, malnourished (defined by the CONUT score ≥2) patients conferred a 52% increased risk of MACEs. Additionally, per point CONUT score increment was associated with 15% and 11% higher risk of MACEs and all-cause mortality, respectively. Higher CONUT score independently predicts the MACEs all-cause mortality in CAD patients. Estimation of nutritional status using the CONUT score could be helpful for improving risk classification of CAD.

Underestimated prognostic value of depression in patients with obstructive coronary artery disease

OBJECTIVE

The aim of this study was to explore the different predictive values of depression among patients with different cardiac systolic function levels.

METHODS

Four hundred eighty-three consecutive patients with obstructive coronary artery disease (CAD) were included the depressive state was assessed using the Chinese version of the Patient Health Questionnaire 9 (PHQ-9). Depression was defined as have depressive symptoms with a PHQ-9 score ≥5. The level of cardiac systolic function was classified as left ventricular ejection fraction (LVEF) ≥50 and <50%.

RESULTS

Over a median of 26.2 months, 421 patients completed the follow-up and experienced 101 major adverse cardiovascular events (MACEs), 45 non-cardiac rehospitalizations, and 17 deaths. Predictors for clinical outcomes in patients with different cardiac systolic function levels were not the same. For participants with preserved LVEF, depression was associated with increased risks for cardiovascular events and composite outcomes. However, when focusing the whole population, predictive values of depression for MACEs, non-cardiac rehospitalizations, and composite endpoints all dropped. Receiver operating characteristic (ROC) analyses further confirmed that depression was the one of the main predictors for all clinical outcomes. With the combination of other simple features, area under curve (AUC) could reach 0.64-0.67.

CONCLUSIONS

Inconsistent with the general impression, depression is found to have a closer linkage with clinical outcomes in CAD patients with preserved LVEF rather than in those with decreased LVEF. These findings appeal for more attention on CAD patients with depressive symptoms and comparatively normal LVEF. Including psychological factors may be a good attempt when constructing risk prediction models.

Phenolic Acids as Antidepressant Agents

Depression is a psychiatric disorder affecting the lives of patients and their families worldwide. It is an important pathophysiology; however, the molecular pathways involved are not well understood. Pharmacological treatment may promote side effects or be ineffective. Consequently, efforts have been made to understand the molecular pathways in depressive patients and prevent their symptoms. In this context, animal models have suggested phytochemicals from medicinal plants, especially phenolic acids, as alternative treatments. These bioactive molecules are known for their antioxidant and antiinflammatory activities. They occur in some fruits, vegetables, and herbal plants. This review focused on phenolic acids and extracts from medicinal plants and their effects on depressive symptoms, as well as the molecular interactions and pathways implicated in these effects. Results from preclinical trials indicate the potential of phenolic acids to reduce depressive-like behaviour by regulating factors associated with oxidative stress, neuroinflammation, autophagy, and deregulation of the hypothalamic-pituitary-adrenal axis, stimulating monoaminergic neurotransmission and neurogenesis, and modulating intestinal microbiota.

Lycopene: A Natural Arsenal in the War against Oxidative Stress and Cardiovascular Diseases

Lycopene is a bioactive red pigment found in plants, especially in red fruits and vegetables, including tomato, pink guava, papaya, pink grapefruit, and watermelon. Several research reports have advocated its positive impact on human health and physiology. For humans, lycopene is an essential substance obtained from dietary sources to fulfil the body requirements. The production of reactive oxygen species (ROS) causing oxidative stress and downstream complications include one of the major health concerns worldwide. In recent years, oxidative stress and its counter strategies have attracted biomedical research in order to manage the emerging health issues. Lycopene has been reported to directly interact with ROS, which can help to prevent chronic diseases, including diabetes and neurodegenerative and cardiovascular diseases. In this context, the present review article was written to provide an accumulative account of protective and ameliorative effects of lycopene on coronary artery disease (CAD) and hypertension, which are the leading causes of death worldwide. Lycopene is a potent antioxidant that fights ROS and, subsequently, complications. It reduces blood pressure via inhibiting the angiotensin-converting enzyme and regulating nitrous oxide bioavailability. It plays an important role in lowering of LDL (low-density lipoproteins) and improving HDL (high-density lipoproteins) levels to minimize atherosclerosis, which protects the onset of coronary artery disease and hypertension. Various studies have advocated that lycopene exhibited a combating competence in the treatment of these diseases. Owing to all the antioxidant, anti-diabetic, and anti-hypertensive properties, lycopene provides a potential nutraceutical with a protective and curing ability against coronary artery disease and hypertension.

A web-based novel prediction model for predicting depression in elderly patients with coronary heart disease: A multicenter retrospective, propensity-score matched study

BACKGROUND

Depression is associated with an increased risk of death in patients with coronary heart disease (CHD). This study aimed to explore the factors influencing depression in elderly patients with CHD and to construct a prediction model for early identification of depression in this patient population.

MATERIALS AND METHODS

We used propensity-score matching to identify 1,065 CHD patients aged ≥65 years from four hospitals in Chongqing between January 2015 and December 2021. The patients were divided into a training set (n = 880) and an external validation set (n = 185). Univariate logistic regression, multivariate logistic regression, and least absolute shrinkage and selection operator regression were used to determine the factors influencing depression. A nomogram based on the multivariate logistic regression model was constructed using the selected influencing factors. The discrimination, calibration, and clinical utility of the nomogram were assessed by the area under the curve (AUC) of the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA) and clinical impact curve (CIC), respectively.

RESULTS

The predictive factors in the multivariate model included the lymphocyte percentage and the blood urea nitrogen and low-density lipoprotein cholesterol levels. The AUC values of the nomogram in the training and external validation sets were 0.762 (95% CI = 0.722-0.803) and 0.679 (95% CI = 0.572-0.786), respectively. The calibration curves indicated that the nomogram had strong calibration. DCA and CIC indicated that the nomogram can be used as an effective tool in clinical practice. For the convenience of clinicians, we used the nomogram to develop a web-based calculator tool (https://cytjt007.shinyapps.io/dynnomapp_depression/).

CONCLUSION

Reductions in the lymphocyte percentage and blood urea nitrogen and low-density lipoprotein cholesterol levels were reliable predictors of depression in elderly patients with CHD. The nomogram that we developed can help clinicians assess the risk of depression in elderly patients with CHD.

Associations Among Depression, Hemoglobin A1c Level, and Prognosis in Patients With Coronary Artery Disease: A Prospective Study

BACKGROUND

Depression is ubiquitous in patients with coronary artery disease (CAD). The relationship between depression and hemoglobin A1c (HbA1c) is controversial. The combined effect of high HbA1c and depression on prognosis is unclear, especially in non-diabetic CAD patients. We sought to explore these associations.

METHODS

558 CAD patients were included in this prospective study. Patients were grouped by HbA1c levels and the status of clinical depression. The average follow-up period was about 2.2 years, and Cox proportional hazards models were used to compare the differences of prognosis in all the groups.

RESULTS

Clinical depression had no associations with HbA1c in all CAD patients (P for Pearson correlation = 0.74). In the all four groups, compared to group 1 (patients without clinical depression and low HbA1c), group 3 (without clinical depression and high HbA1c) had a higher risk of MACE (adjusted hazard ratio [aHR], 1.97; 95% confidence interval [CI], 1.2-3.25) and composite events (aHR, 1.67; 95% CI, 1.09-2.053). Group 4 (patients with clinical depression and high HbA1c) had higher HRs for MACE (aHR, 2.9; 95%CI, 1.32-6.38) and composite events (aHR, 2.12; 95% CI, 1.06-4.25). In CAD patients without diabetes, patients with clinical depression and high HbA1c had a higher risk of MACE (HR, 2.71; 95% CI, 1.02-7.19), non-cardiac readmission (HR,3.48; 95% CI, 1.26-9.57) and composite events (HR,2.44; 95% CI, 1.08-5.53) than those with no clinical depression and low HbA1c. In patients with comorbidities of depression and diabetes, patients with depression and high HbA1c more likely to experienced non-cardiac readmissions (HR, 4.49; 95% CI, 1.31-15.38) than patients with no depression and low HbA1c only. In all the above analysis, p-values for interaction between clinical depression and HbA1c were not statistically significant.

CONCLUSIONS

The presence of both depression and high HbA1c lead to a worse prognosis in CAD patients than one risk factor alone, no matter with or without the comorbidity of diabetes in these CAD patients. For patients with CAD and depression, lower HbA1c may be required.

Associations between Depression, Nutritional Status and Mediterranean Diet in Dalmatian Kidney Transplant Recipients

Depression has been addressed as a predictor of worse outcomes in kidney transplant recipients (KTRs). Nutritional status plays a great role in treatment of this population. The Mediterranean diet (MeDi) has been associated with lower levels of depressive symptoms. The aim of this cross-sectional study was to determine the rate of depression and its correlations to nutritional status and dietary habits according to the MeDi in Dalmatian KTRs. We included 115 KTRs, and data about body composition and anthropometric, laboratory and clinical parameters were obtained for each study participant. The Beck Depression Inventory-II (BDI-II) questionnaire was used to assess depressive symptoms and the Mediterranean Diet Serving Score (MDSS) was used to assess adherence to the MeDi. We found the presence of depressive symptoms in 21.73% of the Dalmatian KTRs. BDI-II score was reciprocally associated with fat mass, trunk visceral fat, anthropometric parameters of obesity, triglyceride levels and olive oil consumption. Inverse associations were found between BDI-II score and skeletal muscle mass, handgrip strength, MCV, hemoglobin levels and consumption of fish and white meat, as suggested by the MeDi. Our results showed the interconnections between nutritional status, dietary habits and depression in Dalmatian KTRs.

Coronary Heart Disease and Depression or Anxiety: A Bibliometric Analysis

This study aimed to conduct a bibliometric analysis of published studies on the association between coronary heart disease (CHD) and depression or anxiety. The study also aimed to identify leading authors, institutions, and countries to determine research hotspots and obtain some hints from the speculated future frontiers. Publications about CHD and depression or anxiety between 2004 and 2020 were collected from the Web of Science Core Collection (WOSCC) database. Bibliographic information, such as authorship, country, citation frequency, and interactive visualization, was generated using VOSviewer1.6.16 and CiteSpace5.6.R5. In total, 8,073 articles were identified in the WOSCC database. The United States (2,953 publications), Duke University and Harvard University (214 publications), Psychosomatic Medicine (297 publications), and Denollet Johan. (99 publications) were the most productive country, institutions, journal, and author, respectively. The three hotspots of the research were “The relationship between depression and CHD,” “depression and myocardial infarction,” and “The characteristic of women suffering depression after MI.” The four future research frontiers are predicted to be “treating depression in CHD patients with multimorbidity,” “psychometric properties of instruments for assessing depression and anxiety in CHD patients,” “depression or anxiety in post-PCI patients,” and “other mental diseases in CHD patients.” Bibliometric analysis of the association between CHD and depressive disorders might identify new directions for future research.

Impact of Germination on the Microstructural and Physicochemical Properties of Different Legume Types

The microstructural and physicochemical compositions of bean (Phaseolus vulgaris), lentil (Lens culinaris Merr.), soybean (Glycine max L.), chickpea (Cicer aretinium L.) and lupine (Lupinus albus) were investigated over 2 and 4 days of germination. Different changes were noticed during microscopic observations (Stereo Microscope, SEM) of the legume seeds subjected to germination, mostly related to the breakages of the seed structure. The germination caused the increase in protein content for bean, lentil, and chickpea and of ash content for lentil, soybean and chickpea. Germination increased the availability of sodium, magnesium, iron, zinc and also the acidity for all legume types. The content of fat decreased for lentil, chickpea, and lupine, whereas the content of carbohydrates and pH decreased for all legume types during the four-day germination period. Fourier transform infrared spectroscopic (FT-IR) spectra show that the compositions of germinated seeds were different from the control and varied depending on the type of legume. The multivariate analysis of the data shows close associations between chickpea, lentil, and bean and between lupine and soybean samples during the germination process. Significant negative correlations were obtained between carbohydrate contents and protein, fat and ash at the 0.01 level.