Malnutrition in patients with coronary artery disease: Prevalence and mortality in a 46,485 Chinese cohort study

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.

Ischemic cardio-cerebrovascular disease and all-cause mortality in Chinese elderly patients: a propensity-score matching study

BACKGROUND

Ischemic cardio-cerebrovascular disease is the leading cause of mortality worldwide. However, studies focusing on elderly and very elderly patients are scarce. Hence, our study aimed to characterize and investigate the long-term prognostic implications of ischemic cardio-cerebrovascular diseases in elderly Chinese patients.

METHODS

This retrospective cohort study included 1026 patients aged ≥ 65 years who were categorized into the mono ischemic cardio-cerebrovascular disease (MICCD) (either coronary artery disease or ischemic stroke/transient ischemic attack) (n = 912) and the comorbidity of ischemic cardio-cerebrovascular disease (CICCD) (diagnosed with both coronary artery disease and ischemic stroke/transient ischemic attack at admission) (n = 114). The primary outcome was all-cause death. The mortality risk was evaluated using the Cox proportional hazards risk model with multiple adjustments by conventional and propensity-score-based approaches.

RESULTS

Of the 2494 consecutive elderly patients admitted to the hospital, 1026 (median age 83 years [interquartile range]: 76.5-86.4; 94.4% men) met the inclusion criteria. Patients with CICCD consisted mostly of very elderly (79.2% vs. 66.1%, P < 0.001) individuals with a higher burden of comorbidities. Over a median follow-up of 10.4 years, 398 (38.8%) all-cause deaths were identified. Compared with the MICCD group, the CICCD group exhibited a higher adjusted hazard ratio (HR) (95% confidential interval, CI) of 1.71 (1.32-2.39) for long-term mortality after adjusting for potential confounders. The sensitivity analysis results remained robust. After inverse probability of treatment weighting (IPTW) modeling, the CICCD group displayed an even worse mortality risk (IPTW-adjusted HR: 2.07; 95% CI 1.47-2.90). In addition, anemia (adjusted HR: 1.48; 95% CI 1.16-1.89) and malnutrition (adjusted HR: 1.43; 95% CI 1.15-1.78) are also independent risk factors for all-cause mortality among elderly and very elderly patients.

CONCLUSIONS

Our results thus suggest that elderly patients with ischemic cardio-cerebrovascular disease and anemia or malnutrition may have higher mortality, which may be predicted upon admission. These findings, however, warrant further investigation.

Prevalence of Metabolic Syndrome Based on Activity Type and Dietary Habits in Extremely Low-Income Individuals

A high prevalence of metabolic syndrome (MS) and cardiovascular disease among low-income individuals has often been reported. However, there is still a lack of research on the relationship between basic livelihood security (BLS) and MS. This study investigated the prevalence of MS according to activity type, dietary habits, and the nutrient intake characteristics of individuals receiving BLS. Data from 14,803 men and 20,299 women were analyzed to assess the association between receiving BLS and MS. The associations between MS and various factors were analyzed separately in men and women by logistic regression analysis. In this cohort, 5.9% of men and 6.8% of women received BLS; of these, 46.9% and 47.7% had MS, respectively. High caloric intake, low-frequency breakfast consumption, and no nutritional education were associated with MS in both men and women. Among those with a low-frequency walking habit and strength training activity type, MS increased by 1.58 and 1.57 times in men and by 1.47 and 2.16 times in women, respectively. Men who were sedentary for 8 h or more had an increased risk of MS, but there was no association between these in women. BLS nutritional intake characteristics were high in carbohydrates and fat and low in dietary fiber and vitamin C (p < 0.05). In conclusion, establishing a healthy eating pattern through nutritional education and increasing walking and strength training may reduce the risk of MS.

Machine learning-based coronary artery calcium score predicted from clinical variables as a prognostic indicator in patients referred for invasive coronary angiography

OBJECTIVES

Utilising readily available clinical variables, we aimed to develop and validate a novel machine learning (ML) model to predict severe coronary calcification, and further assessed its prognostic significance.

METHODS

This retrospective study enrolled patients who underwent coronary CT angiography and subsequent invasive coronary angiography. Multiple ML algorithms were used to train the models for predicting severe coronary calcification (cardiac CT-measured coronary artery calcium [CT-CAC] score ≥ 400). The ML-based CAC (ML-CAC) score derived from the ML predictive probability was stratified into quartiles for prognostic analysis. The primary endpoint was a composite of all-cause death, nonfatal myocardial infarction, or nonfatal stroke.

RESULTS

Overall, 5785 patients were divided into training (80%) and test sets (20%). For clinical practicability, we selected the nine-feature support vector machine model with good and satisfactory performance regarding both discrimination and calibration based on five repetitions of the 10-fold cross-validation in the training set (mean AUC = 0.715, Brier score = 0.202), and based on the test in the test set (AUC = 0.753, Brier score = 0.191). In the test set cohort (n = 1137), the primary endpoint was observed in 50 (4.4%) patients during a median 2.8 years' follow-up. The ML-CAC system was significantly associated with an increased risk of the primary endpoint (adjusted hazard ratio for trend 2.26, 95% CI 1.35-3.79, p = 0.002). There was no significant difference in the prognostic value between the ML-CAC and CT-CAC systems (C-index, 0.67 vs. 0.69; p = 0.618).

CONCLUSION

ML-CAC score predicted from clinical variables can serve as a novel prognostic indicator in patients referred for invasive coronary angiography.

CLINICAL RELEVANCE STATEMENT

In patients referred for invasive coronary angiography who have not undergone preoperative CT-measured coronary artery calcium scoring, machine learning-based coronary artery calcium score assessment can serve as an alternative for predicting the prognosis.

KEY POINTS

• The coronary artery calcium (CAC) score, a solid prognostic indicator, can be predicted using non-CT methods. • We developed a machine learning (ML)-CAC model utilising nine clinical variables to predict severe coronary calcification. • The ML-CAC system offers significant prognostic value in patients referred for invasive coronary angiography.

Retrospective study for correlation analysis of nutritional status with osteoporosis, sarcopenia and cognitive impairment in elderly patients with coronary heart disease

Coronary heart disease (CHD) is an abbreviation of coronary atherosclerotic heart disease, which remains challenging for diagnosis and treatment. Current study aims to explore the correlation between geriatric nutritional risk index (GNRI) and osteoporosis, sarcopenia, cognitive dysfunction in elderly patients with CHD, and to analyze the clinical diagnostic value of GNRI in the above complications. A total of 92 elderly patients with CHD treated in Suzhou Ninth People's Hospital from January 2020 to October 2023 were retrospectively collected as the experimental group, and 68 non-CHD subjects matched for sex and age in the same period of physical examination were randomly selected as the control group. Osteoporosis, sarcopenia and cognitive dysfunction were analyzed in all patients, and the correlation between GNRI and these indices in different populations was analyzed by Spearman's rank correlation. The diagnostic efficacy of GNRI in osteoporosis, sarcopenia, and cognitive impairment was analyzed by ROC curves. There was no significant difference in age, sex distribution, body mass index (BMI) and serum biological indexes between the elderly patients with CHD and the control group (all P > 0.05). Correlation analysis showed that GNRI level was positively correlated with bone mineral content (BMC), bone mineral density (BMD) T value and osteocalcin (OCN) (All r > 0, P < 0.05). In addition, GNRI levels were positively correlated with skeletal muscle mass (ASMI), grip strength and calf circumference (CC) (All r > 0, P < 0.05). However, there was no significant correlation between GNRI levels and cognitive dysfunction-related indicators (P > 0.05). In the elderly and elderly with CHD, the diagnostic AUC of GNRI was 0.875 and 0.862 in osteoporosis, and 0.912 and 0.932 in sarcopenia, respectively. The level of GNRI is significantly correlated with osteoporosis and sarcopenia. GNRI level, as an auxiliary diagnostic tool in elderly patients with CHD, exerts important clinical significance for early detection of the risk of complications, such as osteoporosis and sarcopenia.

Prevalence and prognostic value of malnutrition in patients with acute coronary syndrome and chronic kidney disease

Background

Malnutrition is a rising global health issue associated with unfavorable outcomes of a variety of disorders. Currently, the prevalence and prognostic significance of malnutrition to patients with acute coronary syndrome (ACS) and chronic kidney disease (CKD) remained largely unclear.

Methods

A total of 705 patients diagnosed with ACS and CKD in the First Affiliated Hospital of Wenzhou Medical University between 2013 and 2021 were included in this retrospective cohort study. Malnutrition was assessed by the Controlling Nutritional Status (CONUT), the Geriatric Nutritional Risk Index (GNRI), and the Prognostic Nutritional Index (PNI), respectively. The relationships between malnutrition and all-cause mortality and major cardiovascular events (MACEs) were analyzed.

Results

During a median follow-up of 31 months, 153 (21.7%) patients died, and 165 (23.4%) had MACEs. The prevalence of malnutrition was 29.8, 80.6, and 89.8% for the PNI, CONUT, and GNRI, respectively. All the malnutrition indexes were correlated with each other (r = 0.77 between GNRI and PNI, r = -0.72 between GNRI and CONUT, and r = -0.88 between PNI and CONUT, all p < 0.001). Compared with normal nutrition, malnutrition was independently associated with an increased risk for all-cause mortality (adjusted hazard ratio for moderate and severe degrees of malnutrition, respectively: 7.23 [95% confidence interval (CI): 2.69 to 19.49] and 17.56 [95% CI: 5.61 to 55.09] for the CONUT score, 2.18 [95% CI: 0.93 to 5.13] and 3.16 [95% CI: 1.28 to 7.79] for the GNRI, and 2.52 [95% CI: 1.62 to 3.94] and 3.46 [95% CI: 2.28 to 5.25] for the PNI score. p values were lower than 0.05 for all nutritional indexes, except for moderate GNRI p value = 0.075). As for MACEs, similar results were observed in the CONUT and PNI. All the risk scores could improve the predictive ability of the Global Registry of Acute Coronary Events (GRACE) risk score for both all-cause mortality and MACEs.

Conclusion

Malnutrition was common in patients with ACS and CKD regardless of the screening tools used, and was independently associated with all-cause mortality and MACEs. Malnutrition scores could facilitate risk stratification and prognosis assessment.

Effects of obesity on short-term mortality in patients with acute heart failure under different nutritional status

BACKGROUND

Increased body mass index (BMI) is associated with better survival in patients with acute heart failure (AHF), which is a paradoxical phenomenon. However, it is unclear whether different nutritional status affects this association.

METHODS

1325 patients with AHF from the Medical Information Mart for Intensive Care III database were retrospectively included. Nutritional status was assessed by serum albumin (SA) and prognostic nutritional index (PNI). Patients were divided into High-SA (≥ 3.5 g/dL) and Low-SA groups (< 3.5 g/dL), and they also were divided into High-PNI (≥ 38) and Low-PNI groups (< 38). Propensity-score matching (PSM) was used to control for the effect of baseline confounding factors, multifactor regression model was adopted to assess the association of nutritional status, BMI, and outcomes in AHF patients.

RESULTS

Of the 1325 patients (mean age 72.4 ± 13.1 years), 52.1% (n = 690) were male, 13.1% (n = 173) died in hospital and 23.5% (n = 311) died within 90 days. Before PSM, after adjusting for potential confounders, in the High-SA population, compared with the under/normal BMI group, overweight and obesity were negatively correlated with 90-day mortality, with adjusted hazard ratios (HR) of 0.47, 95% confidence interval (CI) (0.30-0.74), P = 0.001; HR 0.45, 95%CI (0.28-0.72), P = 0.001, respectively. However, this correlation was much attenuated in the Low-SA group (overweight BMI: HR 1.06, 95%CI 0.75-1.50, P = 0.744; obese BMI: HR 0.86, 95%CI 0.59-1.24, P = 0.413). After PSM, those who were overweight or obese in the High-SA group had a 50-58% reduction in 90-day risk of death, while the protective effect disappeared in the Low-SA group (HR 1.09, 95% CI 0.70-1.71; HR 1.02, 95%CI 0.66 - 0.59). Similarly, results were similar in analyses using PNI as a nutritional assessment criterion.

CONCLUSION

Overweight or Obesity was associated with lower short-term mortality in well-nourished AHF patients, whereas this association was significantly attenuated or even disappeared in malnourished patients. Therefore, further research is needed for weight loss recommendations for malnourished obese patients with AHF.

The Effect of Prognostic Nutritional Index on Infection in Acute Ischemic Stroke Patients

Objectives: Malnutrition is frequently seen in stroke patients. Malnutrition worsens the prognosis and increases the mortality rate in acute ischemic stroke patients. Malnutrition is a significant factor not only in the initiation of infection but also in its progression. The prognostic nutritional index (PNI) is a new index that evaluates the nutrition and inflammatory status. This study aims to investigate the relationship between PNI and stroke-related infection (SRI) development during hospitalization in patients with acute ischemic stroke. Materials and Methods: Acute ischemic stroke was the primary diagnosis for 158 patients who were admitted to the neurology intensive care unit. Patients' demographic, clinical, and laboratory parameters were recorded. PNI was calculated according to the formula given below. PNI: 10 × serum albumin (g/dL) + 0.005 × total lymphocyte count (mm³). PNI > 380 normal, PNI: 350-380 moderate malnutrition risk, PNI < 350 severe malnutrition risk. Results: A total of 158 patients with acute ischemic stroke were included in the study. There were 70 male and 88 female patients, whereas the mean age of the patients was 67.79 ± 14.0 years. Nosocomial infection developed in 34 (21%) of the patients. Compared to high PNI scores, patients with low PNI scores were generally older, and the National Institutes of Health Stroke Scale (NIHSS) score, atrial fibrillation, infection, mortality rate, and hospitalization rates were all significantly higher. Conclusions: In this study, we discovered that patients with poor PNI had a considerably increased rate of infection development. It is vital to evaluate the nutritional status of patients with acute ischemic stroke during hospitalization.

Association of prognostic nutritional index level and diabetes status with the prognosis of coronary artery disease: a cohort study

BACKGROUND

Malnutrition and inflammation are associated with adverse clinical outcomes in patients with diabetes or coronary artery disease (CAD). Prognostic nutritional index (PNI) is a comprehensive and simple indicator reflecting nutritional condition and immunological status. Whether there is a crosstalk between nutritional-immunological status and diabetes status for the impact on the prognosis of coronary artery disease (CAD) is unclear.

METHODS

A total of 9429 consecutive CAD patients undergoing percutaneous coronary intervention were grouped by diabetes status [diabetes (DM) and non-diabetes (non-DM)] and preprocedural PNI level [high PNI (H-PNI) and low PNI (L-PNI)] categorized by the statistically optimal cut-off value of 48.49. The primary endpoint was all-cause death.

RESULTS

During a median follow-up of 5.1 years (interquartile range: 5.0-5.1 years), 366 patients died. Compared with the non-DM/H-PNI group, the DM/L-PNI group yielded the highest risk of all-cause death (adjusted hazard ratio: 2.65, 95% confidence interval: 1.97-3.56, p < 0.001), followed by the non-DM/L-PNI group (adjusted hazard ratio: 1.44, 95% confidence interval: 1.05-1.98, p = 0.026), while DM/H-PNI was not associated with the risk of all-cause death. The negative effect of L-PNI on all-cause death was significantly stronger in diabetic patients than in nondiabetic patients (p for interaction = 0.037). Preprocedural PNI category significantly improved the Global Registry of Acute Coronary Events (GRACE) risk score for predicting all-cause death in patients with acute coronary syndrome, especially in those with diabetes.

CONCLUSIONS

CAD patients with diabetes and L-PNI experienced the worst prognosis. The presence of diabetes amplifies the negative effect of L-PNI on all-cause death. Poor nutritional-immunological status outweighs diabetes in increasing the risk of all-cause death in CAD patients. Preprocedural PNI can serve as an assessment tool for nutritional and inflammatory risk and an independent prognostic factor in CAD patients, especially in those with diabetes.

Prognostic Potential of the Controlling Nutritional Status (CONUT) Score in Predicting All-Cause Mortality and Major Adverse Cardiovascular Events in Patients With Coronary Artery Disease: A Meta-Analysis

Background

As defined by the Controlling Nutrition Status (CONUT) score, the prognostic significance of nutritional status has attracted attention in patients with cardiovascular disease. This meta-analysis aimed to determine the importance of CONUT score for prediction of all-cause mortality and major adverse cardiovascular events (MACE) in adult patients with coronary artery disease (CAD).

Methods

Observational studies conducted to evaluate the association of CONUT score with adverse clinical outcomes in patients with CAD were included. We searched MEDLINE, Embase, Scopus, Cochrane library, Google scholar, medRxiv pre-print as well as Science Direct search engine for studies published from the inception of each database until March 21, 2022. Studies reporting the utility of CONUT score in prediction of all-cause mortality and MACE among patients with CAD were eligible. Predictive potential of the CONUT score were summarized by pooling the multivariable adjusted hazard ratio (aHR) with 95% CI for the malnourished vs. normal nutritional status or per point CONUT score increase.

Results

Of 2,547 screened citation, nine observational studies involving 81,257 patients with CAD were analyzed. Malnutrition defined by the CONUT score was associated with significantly increased risk of all-cause mortality when compared with the normal nutritional state (aHR for mild, moderate, and severe malnutrition, respectively: (1.21 [95% CI: 1.15–1.27], I² = 0%), (1.53 [95% CI: 1.26–1.84], I² = 84%), and (2.24 [95% CI: 1.57–3.19], I² = 77%). Similarly, moderate (aHR 1.71 [95% CI: 1.44–2.03], I² = 0%) and severe (aHR 2.66 [95% CI: 1.82–3.89], I² = 0%) malnutrition was associated with a significantly higher risk of MACE compared with the normal nutritional state. Additionally, per point increase in the CONUT score was correlated with 20 and 23% additional risk of all-cause mortality and MACE, respectively.

Conclusion

As defined by the CONUT score, malnutrition is an independent predictor of all-cause mortality and MACE in CAD patients. Nutritional assessment with CONUT score could allow clinicians to identify patients with CAD at high risk for adverse clinical outcomes.