Prevalence and associated factors of malnutrition in patients with Parkinson's disease using CONUT and GNRI

GLIM criteria-based identification of severe malnutrition and its relationship with the risk of mortality among older Chinese adults with arthritis or rheumatism

BACKGROUND

Malnutrition is a well-known risk factor for mortality among older adults. Arthritis and rheumatism are characterized by chronic inflammation and are also related to malnutrition as diagnosed using the Global Leadership Initiative on Malnutrition (GLIM) criteria. This study was thus developed to examine the associations linking malnutrition and all-cause death among older adults in China, employing the GLIM criteria to assess malnutrition.

METHODS

Two waves of the China Health and Retirement Longitudinal Study from 2013 and 2018 were used to conduct this study. Moderate malnutrition was defined as low BMI (< 18.5 and < 20 for individuals < 70 and 70 + years of age, respectively), an unintended 10-20% decrease in weight, or low muscle mass based on the sex-specific lowest 20% of the height-adjusted muscle mass as < 5.039 kg/m2 in women and < 6.866 kg/m2 in men. Severe malnutrition was defined as a > 20% unintended decrease in weight only or the combination of both low muscle mass and an unintended reduction of over 10% in weight. Associations between malnutrition and the risk of all-cause death were assessed through Cox regression analyses.

RESULTS

Overall, this study enrolled 1766 subjects 60 + years of age, of whom 57.36% (1033/1766) were female. Malnutrition was estimated to affect 418 (23.67%) of these individuals at baseline, with 21.06% and 2.60% affected by moderate and severe malnutrition, respectively. Over the 5-year follow-up, 189 of these individuals died. Covariate-adjusted Cox regression analyses confirmed a significant association between severe malnutrition and the risk of death in this cohort (HR = 2.196, 95%CI 1.125-4.286, P = 0.021).

CONCLUSIONS

Severe malnutrition, identified through screening based on the GLIM criteria, was associated with an increased risk of all-cause death among older Chinese adults with arthritis or rheumatism.

The efficacy of nutritional screening indexes in predicting the incidence of osteosarcopenia and major osteoporotic fracture in the elderly

INTRODUCTION

The effect of nutritional status on osteosarcopenia (OS) and major osteoporotic fracture (MOF) among the elderly is still unclear. So we aimed to compare the efficacy of the Mini-Nutrition Assessment-Short Form (MNA-sf), the Geriatric Nutritional Risk Index (GNRI) and Controlling Nutritional Status (CONUT) for predicting OS and MOF among the elderly.

MATERIALS AND METHODS

A total of 409 participants were enrolled in this prospective study. Blood biochemical indexes, nutritional status, and bone- and muscle-related examinations were assessed at initial visit to the outpatient. Participants were divided into 4 groups: (1) control; (2) osteopenia/osteoporosis; (3) sarcopenia; (4) osteosarcopenia, and then followed for 5 years, recording the occurrence time of MOF.

RESULTS

The frequency values of osteopenia/osteoporosis, sarcopenia, and OS, at baseline, were respectively 13.4, 16.1, and 12% among the study samples. Correlation analysis showed that nutritional status scores were associated with body mass index, handgrip strength, albumin, bone mineral density, and physical functions. According to multivariate models, poor nutritional status was significantly associated with a higher risk of OS and MOF (P < 0.05). Survival analysis showed that the MOF rate in malnutrition group was significantly higher than normal nutrition group (P < 0.05). The receiver operator characteristic curve shows that the value of MNA-sf to diagnose OS and MOF is greater (P < 0.05).

CONCLUSION

The poor nutritional status was associated with a higher risk of both OS and MOF. MNA-sf showed a superior diagnostic power for OS and MOF among the elderly. Early nutrition assessments and interventions may be key strategies to prevent OS and fractures.

Prognostic value of geriatric nutritional risk index in patients with amyotrophic lateral sclerosis

BACKGROUND

The geriatric nutritional risk index (GNRI) is a prognostic indicator for several diseases, meanwhile, nutrition and inflammation play important roles in the disease progression of amyotrophic lateral sclerosis (ALS). However, the association between the GNRI and ALS remains unknown.

METHODS

443 patients diagnosed with ALS were divided into two groups based on the GNRI levels. Associations between GNRI and survival time were analyzed using Kaplan-Meier curves and compared by the log-rank test. Univariate and multivariate analyses were used to assess their prognostic values for survival time. Spearman correlation analysis was used to evaluate the correlation coefficients between GNRI and other clinical variables.

RESULTS

No significant differences were found in diagnostic delay between the two groups. The onset age and disease progression rate (DPR) were significantly lower in high GNRI group while forced vital capacity (FVC), revised version of the ALS functional rating scale (ALSFRS-R), serum albumin and body mass index (BMI) were significantly lower in low GNRI group. Lower GNRI levels were linked with shorter ALS patients' survival time by Kaplan-Meier curves. The univariate and multivariate analysis identified the onset age, gender, onset site, diagnostic delay, DRP and GNRI as predictors of survival time in patients with ALS.

CONCLUSION

Nutritional status was closely corelated with ALS progression. The GNRI may be used as a potential prognostic indictor for ALS patients.

Comparative analysis of four nutritional scores predicting the incidence of MACE in older adults with acute coronary syndromes after PCI

To determine the most appropriate nutritional assessment tool for predicting the occurrence of major adverse cardiovascular events (MACE) within 1 year in elderly ACS patients undergoing PCI from four nutritional assessment tools including PNI, GNRI, CONUT, and BMI. Consecutive cases diagnosed with acute coronary syndrome (ACS) and underwent percutaneous coronary intervention (PCI) in the Department of Cardiovascular Medicine of the Air force characteristic medical center from 1 January 2020 to 1 April 2022 were retrospectively collected. The basic clinical characteristics and relevant test and examination indexes were collected uniformly, and the cases were divided into the MACE group (174 cases) and the non-MACE group (372 cases) according to whether a major adverse cardiovascular event (MACE) had occurred within 1 year. Predictive models were constructed to assess the nutritional status of patients with the Prognostic Nutritional Index (PNI), Geriatric Nutritional Risk Index (GNRI), Controlling nutritional status (CONUT) scores, and Body Mass Index (BMI), respectively, and to analyze their relationship with prognosis. The incremental value of the four nutritional assessment tools in predicting risk was compared using the Integrated Discriminant Improvement (IDI) and the net reclassification improvement (NRI). The predictive effect of each model on the occurrence of major adverse cardiovascular events (MACE) within 1 year in elderly ACS patients undergoing PCI was assessed using area under the ROC curve (AUC), calibration curves, decision analysis curves, and clinical impact curves; comparative analyses were performed. Among the four nutritional assessment tools, the area under the curve (AUC) was significantly higher for the PNI (AUC: 0.798, 95%CI 0.755-0.840 P < 0.001) and GNRI (AUC: 0.760, 95%CI 0.715-0.804 P < 0.001) than for the CONUT (AUC: 0.719,95%CI 0.673-0.765 P < 0.001) and BMI (AUC: 0.576, 95%CI 0.522-0.630 P < 0.001). The positive predictive value (PPV) of PNI: 67.67% was better than GNRI, CONUT, and BMI, and the negative predictive value (NPV): of 83.90% was better than CONUT and BMI and similar to the NPV of GNRI. The PNI, GNRI, and CONUT were compared with BMI, respectively. The PNI had the most significant improvement in the Integrated Discriminant Improvement Index (IDI) (IDI: 0.1732, P < 0.001); the PNI also had the most significant improvement in the Net Reclassification Index (NRI) (NRI: 0.8185, P < 0.001). In addition, of the four nutritional assessment tools used in this study, the PNI was more appropriate for predicting the occurrence of major adverse cardiovascular events (MACE) within 1 year in elderly ACS patients undergoing PCI.

Temporal Muscle Thickness Correlates with Sarcopenia in Parkinson’s Disease

Background: Sarcopenia is characterized by a progressive loss of muscle mass, strength, and function resulting in adverse health outcomes. Current assessment strategies are bothersome and means to simplify the diagnosis are an unmet medical need in Parkinson’s disease (PD). Objective: To evaluate temporal muscle thickness (TMT) obtained on routine cranial MRI as a surrogate marker of sarcopenia in PD patients. Methods: We correlated TMT from axial non-contrast-enhanced T1-weighted sequences of MRI close (±12 months) to an outpatient visit including sarcopenia (EWGSOP1, EWGSOP2, SARC-F), frailty (Fried’s criteria, clinical frailty scale), and disease characteristics of Parkinson’s patients (Hoehn and Yahr-scale, Movement Disorder Society-Unified Parkinson’s Disease Rating Scale, quality of life with the Parkinson’s Disease Questionnaire-8) assessments. Results: Cranial MRI was available in 32 patients with a mean age of 73.56±5.14 years, mean disease duration of 11.46±5.66 years, and median Hoehn and Yahr stage of 2.5. The mean TMT was 7.49±2.76 (7.15) mm. Mean TMT was significantly associated with sarcopenia (EWGSOP2, p = 0.018; EWGSOP1, p = 0.023) and frailty status (physical phenotype; p = 0.045). Moreover, there were significant moderate to strong correlations between TMT measurement and appendicular skeletal muscle mass index (r: 0.437, p = 0.012), as well as handgrip strength (r: 0.561, p <  0.001). Conclusion: Reduced TMT seems to be a promising surrogate marker for sarcopenia (EWGSOP2) and muscle strength in this pilot study in PD patients.

Association Between Poor Nutritional Status and Increased Risk for Subsequent Vertebral Fracture in Elderly People with Percutaneous Vertebroplasty

Background

The relationship between a poor nutritional state and the risk of fractures has not been investigated. This study aimed to investigate the ability of the Controlling Nutritional Status (CONUT) and Geriatric Nutritional Risk Index (GNRI) to predict the incidence of subsequent vertebral fracture (SVF) after percutaneous vertebroplasty (PVP).

Methods

A total of 307 women and 138 men over 50 years old who underwent PVP for osteoporotic vertebral compression fracture (OVCF) were included. Blood biochemical indexes, body mass index (BMI), bone mineral density (BMD), physical function, and muscle strength were measured at baseline. Cox regression analysis was used to determine whether nutritional state was an independent predictor for SVF.

Results

During follow-up, 35 (25.4%) men and 85 (27.7%) women suffered SVF. Patients with SVF had lower BMI, serum albumin levels, GNRI scores, grip strength, lumbar BMD, and Short-Physical Performance Battery (SPPB) scores and higher fall rates and CONUT scores (P < 0.05). Compared with normal nutrition, mild malnutrition was associated with higher risk for SVF (women: HR 2.37, p=0.001, men: HR 2.97, p=0.021 by GNRI; women: HR 2.36, p=0.005, men: HR 3.62, p=0.002 by CONUT) after adjusting for confounding factors. Those with moderate-severe malnutrition also had a higher risk of SVF. Kaplan-Meier analysis showed that poor nutrition state was significantly associated with lower SVF-free survival (P<0.05). The area under curve (AUC) for predicting SVF was 0.65 and 0.73 for the GNRI and 0.67 and 0.66 for the CONUT in men and women, respectively.

Conclusion

GNRI and CONUT are simple and effective tools for predicting SVF in patients undergoing PVP. Health management and nutrition supplement after PVP is a potentially effective prevention strategy against SVF.

The prevalence of undernutrition and associated factors in older obese patients

BACKGROUND

Both obesity and malnutrition are common health problems in older adults.

AIM

The aim of our study is to investigate the prevalence of undernutrition and related factors in older obese patients.

METHODS

1911 older outpatients who underwent comprehensive geriatric assessment were included in this cross-sectional study. Body mass index (BMI) was categorized as follows: 'Underweight' = BMI < 18.5, 'Normal weight' = 18.5 ≤ BMI < 25, 'Overweight' 25 ≤ BMI < 30, and 'Obesity' ≥ BMI 30. Mini-Nutritional Assessment scores > 23.5, 17-23.5, or < 17 were categorized as well-nourished, malnutrition risk, and malnutrition, respectively. Those who were not well-nourished were considered undernutrition.

RESULTS

Of 1911 patients, with a mean age of 77.34 ± 8.0 years, 931 (48.7%) were obese. Of whom 6.0% were malnourished and 26.3% were at risk of malnutrition. Age, females, widowed and those living with their children, the number of drugs used, and the presence of heart failure, Parkinson's disease, and dementia, decreased calf circumference and muscle strength were higher in obese patients with undernutrition than obese well-nourished patients (p < 0.05). After adjustment for the aforementioned factors, basic and instrumental activities of daily livings, and Tinetti scores were lower, and falls and Geriatric Depression Scale-15 scores were higher in those with undernutrition compared to those with well-nourished among older obese patients (p < 0.05).

CONCLUSIONS

Half of the older patients were obese and undernutrition was observed in one out of every three older obese patients. Undernutrition was associated with decreased functional capacity, impairment in balance and gait functions, falls, and depressed mood. Therefore, we recommend to screen older obese patients for nutritional status.

Lipid level alteration in human and cellular models of alpha synuclein mutations

Lipid profiles in biological fluids from patients with Parkinson's disease (PD) are increasingly investigated in search of biomarkers. However, the lipid profiles in genetic PD remain to be determined, a gap of knowledge of particular interest in PD associated with mutant α-synuclein (SNCA), given the known relationship between this protein and lipids. The objective of this research is to identify serum lipid composition from SNCA A53T mutation carriers and to compare these alterations to those found in cells and transgenic mice carrying the same genetic mutation. We conducted an unbiased lipidomic analysis of 530 lipid species from 34 lipid classes in serum of 30 participants with SNCA mutation with and without PD and 30 healthy controls. The primary analysis was done between 22 PD patients with SNCA+ (SNCA+/PD+) and 30 controls using machine-learning algorithms and traditional statistics. We also analyzed the lipid composition of human clonal-cell lines and tissue from transgenic mice overexpressing the same SNCA mutation. We identified specific lipid classes that best discriminate between SNCA+/PD+ patients and healthy controls and found certain lipid species, mainly from the glycerophosphatidylcholine and triradylglycerol classes, that are most contributory to this discrimination. Most of these alterations were also present in human derived cells and transgenic mice carrying the same mutation. Our combination of lipidomic and machine learning analyses revealed alterations in glycerophosphatidylcholine and triradylglycerol in sera from PD patients as well as cells and tissues expressing mutant α-Syn. Further investigations are needed to establish the pathogenic significance of these α-Syn-associated lipid changes.