UNASSIGNED: Nutritional problems are considered one of the main complications of hemodialysis, and the geriatric nutritional risk index (GNRI) is a new instrument for assessing geriatric nutritional status. The present study sought to evaluate the relationship between the GNRI and quality of life (QOL) among elderly hemodialysis patients.
UNASSIGNED: In the present analytical cross-sectional study, 110 hemodialysis individuals were selected by applying a simple random sampling method, among whom 57 and 53 were males and females, respectively (mean: 70.3±6.93 years). Demographic characteristics, GNRI, and QOL status were determined. The data were analyzed using SPSS 20 software and descriptive statistics, Pearson\'s correlation, ANOVA, independent sample t-tests, and multiple linear regression analysis.
UNASSIGNED: The mean GNRI and mean total QOL were respectively obtained 93.903±11.067 and 20.95 ± 4.89. Among females, a significant direct relationship was observed between GNRI and total QOL (P = 0.010, r = 0.352), autonomy (P = 0.004, r = 0.389), and pleasure (P = 0.015, r = 0.333), while GNRI was not directly and significantly related to QOL in males (P = 0.161, r = 0.188).
UNASSIGNED: Due to the presence of a significant association between Geriatric GNRI and QOL among elderly hemodialysis patients, particularly among females, highlighting the importance of addressing nutritional status in optimizing well-being.

UNASSIGNED: To investigate the associations between the geriatric nutritional risk index (GNRI) with cognitive functions among U.S. older adults. (Patients were classified into two nutrition risk groups based on the GNRI).
UNASSIGNED: Our analysis utilized data from the cross-sectional National Health and Nutrition Examination Survey (NHANES) conducted between 2011 and 2014. Cognitive function was measured using CERAD test, AFT and DSST. Composite z-scores were obtained by summing test-specific z-scores of the above three cognitive tests and were used to assess the global cognitive function. We employed weighted logistic regression models to evaluate the associations between GNRI and nutritional status (low and high GNRI) with cognitive function among older participants. The non-linear relationship was described using fitted smoothed curves and threshold effect analyses. Subgroup analysis and interaction tests were also conducted.
UNASSIGNED: This study included 2,592 older participants aged 60 years and older. After adjusting for confounding variables, the GNRI was positively associated with AFT (β = 0.05, 95% CI 0.005-0.096, p-value = 0.0285), DSST (β = 0.192, 95% CI 0.078-0.305, p-value = 0.0010) and the composite z-scores (β = 0.027, 95% CI 0.010-0.044, p-value = 0.0024). The results also showed that the high-GNRI group was significantly associated with AFT (β = 0.922, 95% CI 0.166-1.677, p-value = 0.0169), DSST (β = 2.791, 95% CI 0.884-4.698, p-value = 0.0042) and composite z-scores (β = 0.405, 95% CI 0.115-0.695, p-value = 0.0062) likewise had significant positive correlations, using the low-GNRI group as a reference. In addition, inflection points with CERAD and composite z-scores were found at GNRI of 108.016, and 105.371, respectively. Specifically, on the left side of the inflection point GNRI levels were positively correlated with CERAD and composite z-scores (CERAD β = 0.087, 95% CI 0.024-0.150, p-value = 0.0070; composite z-scores β = 0.065, 95% CI 0.040-0.091, p-value <0.0001), while on the right side of the inflection point were significantly negatively associated (CERAD β = -0.295, 95% CI -0.529 to -0.062, p-value = 0.0133, composite z-scores β = -0.050, 95% CI -0.091 to -0.008, p-value = 0.0184).
UNASSIGNED: Lower GNRI was associated with poorer performance in several cognitive domains. Additionally, there was a non-linear positive association between GNRI and cognitive function in normal nutritional states, for excessive GNRI may cause cognitive decline.

UNASSIGNED: The management of nutritional risk has garnered significant attention in individuals diagnosed with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) due to the high prevalence of malnutrition and its correlation with unfavorable outcomes. While numerous rating scales exist to assist in assessment for both clinical and research purposes, there is considerable variability in the selection of scales based on the characteristics of the study participants and the study design. The objective of this study was to examine the efficacy of the Geriatric Nutritional Risk Index (GNRI) and Prognostic Nutritional Index (PNI) in identifying malnutrition and predicting prognosis in elderly AECOPD patients.
UNASSIGNED: From January 2022 to December 2022, a consecutive inclusion of elderly AECOPD patients admitted to the First Affiliated Hospital of Zhengzhou University was conducted. Diagnosing malnutrition in patients using PNI and GNRI, comparing the results with the diagnostic outcomes based on the Global Leadership Initiative on Malnutrition (GLIM) criteria through Receiver Operating Characteristic curves. Logistic regression analysis was employed to assess the risks associated with length of stay (LOS), hospitalization costs, and Charlson Comorbidity Index (CCI) based on GLIM, GNRI, or PNI.
UNASSIGNED: A total of 839 elderly AECOPD patients were investigated in the study. The GNRI and PNI demonstrated a sensitivity of 89.5 and 74.1%, specificity of 77.2 and 66.4%, and an area under the curve of 0.834 and 0.702, respectively. The identification of high malnutrition-risk cases using the GLIM, GNRI and PNI were associated with a significant increase in the risk of LOS over 7 days [odds ratio (95% CI) for GLIM, GNRI, PNI: 1.376 (1.033-1.833); 1.405 (1.070-1.846); 1.875 (1.425-2.468)] and higher hospitalization expenses [OR (95% CI) for GLIM, GNRI: 1.498 (1.080-2.080); 1.510 (1.097-2.079)], but not with the CCI.
UNASSIGNED: According to our study, it is possible to use GNRI and PNI as alternatives to GLIM in the context of AECOPD, which makes it easier to identify malnutrition. The utilization of GNRI and PNI as alternatives to GLIM in the context of AECOPD enables the identification of malnutrition. The presence of malnourished individuals experiencing AECOPD is correlated with higher probabilities of extended hospital stays and escalated in-hospital expenses.

BACKGROUND: Malnutrition is common in older atrial fibrillation (AF) patients and results in poor clinical outcomes. The Geriatric Nutritional Risk Index (GNRI) is a straightforward method for evaluating nutritional health. However, its prognostic value in AF patients is unclear. This research focused on examining the correlation between GNRI and overall mortality in Chinese individuals with AF.
METHODS: We performed a multicenter retrospective study at four Chinese hospitals involving patients diagnosed with AF between January 2019 and August 2023. Using GNRI, nutritional status was evaluated, classifying patients into three categories. Multivariable logistic regression and restricted cubic spline analysis assess the relationship between GNRI and mortality, with exploratory subgroup analyses investigating potential effect modifiers.
RESULTS: The study included 4,878 AF patients with a median follow-up of 19 months. The mean age was 71 (63-78), and the mean GNRI was 102 (95-108). Malnutrition was identified in 1,776 patients (36.41%). During the study, 419 (8.59%) deaths occurred. After controlling for confounders, moderate to severe malnutrition was linked to an increased risk of all-cause mortality compared to no malnutrition (odds ratio 1.50; 95% CI, 1.17-1.94). The relationship between GNRI and mortality risk was approximately linear, with consistent associations across subgroups.
CONCLUSIONS: Malnutrition, as assessed by GNRI, is prevalent among Chinese AF patients and is independently linked to higher all-cause mortality risk.

UNASSIGNED: Despite previous literature exploring the factors influencing lower urinary tract symptoms (LUTS), few studies have examined the relationship between nutritional status and LUTS.
UNASSIGNED: The objective of this research was to evaluate the relationship between LUTS and Geriatric Nutritional Risk Index (GNRI) in middle-aged and older men.
UNASSIGNED: We included 2,607 men in the NHANES 2005-2006 and 2007-2008 cycles for cross-sectional analysis. We screened for LUTS based on four specific questions on the relevant questionnaire. We calculated GNRI according to the relevant calculation formula and included other covariates. Multivariate logistic analysis using GNRI as the principal independent variable and adjusting for other covariates were used to determine the association with LUTS, nocturia, and daytime LUTS.
UNASSIGNED: According to the responses to the questionnaire, out of 2,607 eligible participants, 471 had LUTS, 906 had nocturia, and 819 had daytime LUTS. In the unadjusted regression model, LUTS (OR = 0.93, 95% CI = 0.91-0.96, p < 0.001), nocturia (OR = 0.90, 95% CI = 0.88-0.93, p < 0.001), and daytime LUTS (OR = 0.96, 95% CI = 0.94-0.99, p = 0.002) were significantly negatively associated with GNRI. After adjustment by adding covariates, LUTS (OR = 0.97,95% CI =0.94-0.99, p = 0.026) and nocturia (OR = 0.94, 95% CI =0.91-0.93, p < 0.001) were significantly negatively associated with GNRI.
UNASSIGNED: Low GNRI was associated with the development of LUTS. In the prevention and treatment of LUTS, urologists should consider the impact of nutritional status on LUTS, and interventions for nutritional status may prevent and improve LUTS.

UNASSIGNED: Geriatric Nutritional Risk Index (GNRI) is a new and simple index recently introduced to assess nutritional status, and its predictive value for clinical outcomes has been demonstrated in patients with chronic kidney disease. However, the association between the GNRI and prognosis has not been evaluated so far in patients with acute kidney injury (AKI), especially in those receiving continuous renal replacement therapy (CRRT).
UNASSIGNED: A total of 1096 patients with severe AKI initiating CRRT were identified for inclusion in this retrospective observational study. Patients were divided into three groups according to GNRI tertiles, with tertile 1 as the reference. The outcomes of interest were the 28- and 90-days of all-cause mortality. The associations between GNRI and clinical outcomes were estimated using multivariate Cox proportional hazards model analysis.
UNASSIGNED: The overall mortality rates at 28- and 90-days were 61.6% (675/1096) and 71.5% (784/1096), respectively. After adjusting for multiple confounding factors, GNRI was identified as an independent prognostic factor for 28-days all-cause mortality (HR, 0.582; 95% CI, 0.467-0.727; p < .001 for tertile 3 vs. tertile 1) as well as 90-days all-cause mortality (HR, 0.540; 95% CI, 0.440-0.661; p < .001 for tertile 3 vs. tertile 1). The observed inverse associations were robust across subgroup analysis, and were more pronounced in elderly patients over 65 years of age. Finally, incorporating GNRI in a model with established risk factors might significantly improve its predictive power for the short-term death.
UNASSIGNED: GNRI is considered to be a useful prognostic factor in patients with severe AKI initiating CRRT, especially in elderly patients.

BACKGROUND: Recent studies show that malnutrition increases all-cause mortality by 1.11 times and cardiovascular mortality by 2.60 times. Similarly, metabolic syndrome raises overall mortality by 40% and cardiovascular mortality by 37%. This research assesses the Nutritional Metabolic Risk Index (NMRI) for predicting these mortality risks.
METHODS: We analyzed data from 14,209 participants in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, where the NMRI was calculated based on the ratio of GNRI to TyG-WHtR. The relationship between NMRI and mortality was investigated using Kaplan-Meier methods and Cox regression models, with restricted cubic splines (RCS) employed to examine non-linear associations. The predictive capabilities of NMRI, GNRI, and TyG-WHtR for mortality were assessed using receiver operating characteristic curve (ROC) curve analysis.
RESULTS: Over a median follow-up period of 89 months, there were 1358 all-cause deaths and 345 cardiovascular deaths recorded. Cox regression analysis indicated that each unit increase in NMRI was associated with an 8% reduction in all-cause mortality risk and a 15% reduction in cardiovascular mortality risk. RCS analysis found a nonlinear negative correlation between NMRI and both all-cause and cardiovascular mortality. NMRI demonstrated superior predictive accuracy for all-cause mortality (AUC: 0.696, 95% CI: 0.682-0.710) and cardiovascular mortality (AUC: 0.713, 95% CI: 0.689-0.737) compared to GNRI and TyG-WHtR (P < 0.05).
CONCLUSIONS: The NMRI is inversely associated with the risk of all-cause and cardiovascular mortality in American adults.

UNASSIGNED: Malnutrition adversely affects prognosis in various medical conditions, but its implications in older adults with Chronic Obstructive Pulmonary Disease (COPD) in the ICU are underexplored. The geriatric nutritional risk index (GNRI) is a novel tool for assessing malnutrition risk. This study investigates the association between GNRI and 90-day mortality in this population.
UNASSIGNED: We selected older adults with COPD admitted to the ICU from Medical Information Mart for Intensive Care (MIMIC)-IV 2.2 database. A total of 666 patients were categorized into four groups based on their GNRI score: normal nutrition (>98), mild malnutrition (92-98), moderate malnutrition (82-91), and severe malnutrition (≤81) groups. We employed a restricted cubic spline (RCS) analysis to assess the presence of a curved relationship between them and to investigate any potential threshold saturation effect.
UNASSIGNED: In multivariate Cox regression analyses, compared with individuals had normal nutrition (GNRI in Q4 >98), the adjusted HR values for GNRI in Q3 (92-98), Q2 (82-91), and Q1 (≤81) were 1.81 (95% CI: 1.27-2.58, p=0.001), 1.23 (95% CI: 0.84-1.79, p=0.296), 2.27 (95% CI: 1.57-3.29, p<0.001), respectively. The relationship between GNRI and 90-day mortality demonstrates an L-shaped curve (p=0.016), with an approximate inflection point at 101.5.
UNASSIGNED: These findings imply that GNRI is a useful prognostic tool in older adults with COPD in the ICU. An L-shaped relationship was observed between GNRI and 90-day mortality in these patients.

BACKGROUND: The measurement of triceps skinfold (TSF) thickness serves as a noninvasive metric for evaluating subcutaneous fat distribution. Despite its clinical utility, the TSF thickness trajectories and their correlation with overall mortality have not been thoroughly investigated.
OBJECTIVE: To explore TSF thickness trajectories of Chinese adults and to examine their associations with all-cause mortality.
METHODS: This study encompassed a cohort of 14747 adults sourced from the China Health and Nutrition Survey. Latent class trajectory modeling was employed to identify distinct trajectories of TSF thickness. Subjects were classified into subgroups reflective of their respective TSF thickness trajectory. We utilized multivariate Cox regression analyses and mediation examinations to explore the link between TSF thickness trajectory and overall mortality, including contributory factors.
RESULTS: Upon adjustment for multiple confounding factors, we discerned that males in the \'Class 2: Thin-stable\' and \'Class 3: Thin-moderate\' TSF thickness trajectories exhibited a markedly reduced risk of mortality from all causes in comparison to the \'Class 1: Extremely thin\' subgroup. In the mediation analyses, the Geriatric Nutritional Risk Index was found to be a partial intermediary in the relationship between TSF thickness trajectories and mortality. For females, a lower TSF thickness pattern was significantly predictive of elevated all-cause mortality risk exclusively within the non-elderly cohort.
CONCLUSIONS: In males and non-elderly females, lower TSF thickness trajectories are significantly predictive of heightened mortality risk, independent of single-point TSF thickness, body mass index, and waist circumference.

BACKGROUND: It is reported that reduced physical activity and malnutrition may trigger pneumonia, and the utilisation of the geriatric nutritional risk index (GNRI) upon admission to long-term nursing care can enable the implementation of accurate and timely rehabilitation and nutritional support, which may, in turn, minimise pneumonia incidence. However, to date, there is no reported association between GNRI and pneumonia among stable schizophrenic patients.
METHODS: This is a retrospective investigation. We enrolled 434 hospitalised subjects aged ≥50 years, who were diagnosed with stable schizophrenia between January 2017 and June 2022. Baseline nutritional status information during the stable stage of schizophrenia was evaluated using body mass index, serum albumin, and GNRI. In addition, pneumonia-based information, including diagnosis and treatment, was retrospectively obtained within 1 year. To examine the potential association between nutrition indicators and pneumonia risk among stable schizophrenia patients, we employed a logistic regression analysis.
RESULTS: The pneumonia incidence among all stable schizophrenia patients was 10.14%, and there were no statistically significant difference between sexes (male vs. female, 10.63% vs. 9.44%, P = 0.687). Based on the univariate analysis of nutrition indicators and pneumonia, female patients exhibited a strong correlation between serum albumin and pneumonia (P = 0.022). Furthermore, we adjusted for potential influencing factors of pneumonia infection, and confirmed that only serum albumin was linked to pneumonia risk in female stable schizophrenia patients (odds ratio = 0.854, 95% CI: 0.749-0.975, P = 0.02).
CONCLUSIONS: Based on our analysis, serum albumin was strongly correlated with pneumonia risk in female stable schizophrenia patients.