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To investigate the association of sarcopenia index (SI) [(serum creatinine/serum cystatin C) × 100] with mortality, nutritional risk/malnutrition and sarcopenia among hospitalized older adults. A prospective analysis was performed in 758 hospitalized older adults. Anthropometric measures and biochemical parameters were carried out for each patient. Sarcopenia was defined according to the Asian Working Group for Sarcopenia (AWGS) 2019 algorithm. Nutritional risk/malnutrition was defined according to the European Society of Clinical Nutrition and Metabolism (ESPEN) criteria. The logistic regression analysis was employed for the analysis of correlation between the SI and other variables. Cox regression analysis was employed to analyze correlation between the SI and mortality. A total of 758 participants agreed to participate in this study (589 men and 169 women; mean age: 85.6±6.1 years). The median of the follow-up period was 212 days. A total of 112 patients died. A high SI (per 1-SD was 22.1) was independently associated with all-cause mortality (HR per 1-SD = 0.61, 95% CI: 0.47-0.79), nutritional risk/malnutrition (OR per 1-SD = 0.38, 95% CI: 0.29-0.49) and sarcopenia (OR per 1-SD = 0.58, 95% CI: 0.45-0.74). High SI was positively correlated with albumin (r = 0.32, < 0.001), hemoglobin (r = 0.24, < 0.001), body mass index (BMI) (r = 0.12, = 0.001), waist circumference (WC) (r = 0.08, = 0.046), calf circumference (CC) (r = 0.45, < 0.001), hand grip strength (HGS) (r = 0.52, < 0.001) and negatively correlated with triglyceride glucose (TyG) (r = -0.11, = 0.007). The SI based on serum cystatin C and creatinine is associated with long-term mortality, nutritional risk/malnutrition and sarcopenia in hospitalized older Chinese patients.

Background Nutritional risk is prevalent in various diseases, but its association with contrast-induced acute kidney injury (CI-AKI) remains unclear. This study aimed to explore this association in patients undergoing coronary angiography (CAG). Methods In this retrospective cross-sectional study, 4386 patients undergoing CAG were enrolled. Nutritional risks were estimated by nutritional risk screening 2002 (NRS-2002), controlling nutritional status (CONUT), prognostic nutritional index (PNI), and geriatric nutritional risk index (GNRI), respectively. CI-AKI was determined by the elevation of serum creatinine (Scr). Multivariable logistic regression analyses and receiver operator characteristic (ROC) analyses were conducted. Subgroup analyses were performed according to age (< 70/≥70 years), gender (male/female), percutaneous coronary intervention (with/without), and estimated glomerular filtration rate (< 60/≥60 ml/min/1.73m 2 ). Results Overall, 787 (17.9%) patients were diagnosed with CI-AKI. The median score of NRS-2002, CONUT, PNI, and GNRI was 1.0, 3.0, 45.8, and 98.6, respectively. Nutritional risk was proven to be associated with CI-AKI when four different nutritional tools were employed, including NRS-2002 ([3–7 vs. 0]: odds ratio [95% confidence interval], OR [95%CI] = 4.026 [2.732 to 5.932], P  < 0.001), CONUT ([6–12 vs. 0–1]: OR [95%CI] = 2.230 [1.586 to 3.136], P  < 0.001), PNI ([< 38 vs. ≥52]: OR [95%CI] = 2.349 [1.529 to 3.610], P  < 0.001), and GNRI ([< 90 vs. ≥104]: OR [95%CI] = 1.822 [1.229 to 2.702], P  = 0.003). This is consistent when subgroup analyses were performed. Furthermore, nutritional scores were proved to be accurate in predicting CI-AKI (area under ROC curve: NRS-2002, 0.625; CONUT, 0.609; PNI, 0.629; and GNRI, 0.603). Conclusions Nutritional risks (high scores of NRS-2002 and CONUT; low scores of PNI and GNRI) were associated with CI-AKI in patients undergoing CAG.

Objective Patient nutritional status is an independent and crucial prognostic predictor; however, it is often overlooked in clinical practice. This study aimed to evaluate the value of three nutritional risk screening tools—Geriatric Nutritional Risk Index, Prognostic Nutritional Index, and Nutritional Risk Screening 2002—in predicting postoperative prognosis and recurrence in patients with chronic subdural hematoma. Method According to the inclusion and exclusion criteria, a total of 153 patients with chronic subdural hematoma who were hospitalized and underwent surgical treatment at our hospital between December 2017 and October 2022 were retrospectively enrolled. General clinical data and laboratory test results were collected. The Nutritional Risk Screening 2002, Geriatric Nutritional Risk Index, and Prognostic Nutritional Index scores were assessed. Based on the modified Rankin scale scores, patients were divided into poor prognosis (score ≥3) and good prognosis (score <3) groups. According to the presence or absence of recurrence within 6 months of surgery, patients were classified into recurrence and nonrecurrence groups. General clinical data, laboratory results, and scores of three nutritional risk screening tools were evaluated. Receiver operating characteristic curves were plotted, and multivariate logistic regression analysis was performed. Results Among the 153 patients, 13 (8.5%) had a poor prognosis. Compared with the good prognosis group, patients in the poor prognosis group were older, had higher fibrinogen levels, and had lower serum albumin and hemoglobin levels (p < 0.05). In total, 33 (21.6%) patients experienced recurrence. Compared with the nonrecurrence group, patients in the recurrence group had a higher percentage of monocytes (p < 0.05) and lower body mass index, serum albumin levels, and hemoglobin levels (p < 0.05). In the poor prognosis group, the rates of nutritional risk determined using the Geriatric Nutritional Risk Index, Prognostic Nutritional Index, and Nutritional Risk Screening 2002 were 46.2%, 69.2%, and 92.3%, respectively, which were significantly higher than those in the good prognosis group (p < 0.05). In the recurrence group, the nutritional risk rates determined using the abovementioned three tools were 42.4%, 51.5%, and 78.8%, respectively, all significantly higher than those in the nonrecurrence group (p < 0.05). Receiver operating characteristic curve analysis indicated that the Geriatric Nutritional Risk Index, Prognostic Nutritional Index, and Nutritional Risk Screening 2002 are predictive markers for both surgical prognosis and postoperative recurrence of chronic subdural hematoma. Moreover, multivariate logistic regression analysis identified the three tools as risk factors for poor prognosis and recurrence after surgery for chronic subdural hematoma (p < 0.05). Conclusion Three nutritional risk screening tools—the Geriatric Nutritional Risk Index, Prognostic Nutritional Index, and Nutritional Risk Screening 2002—were independently associated with both poor prognosis and recurrence of chronic subdural hematoma. Among them, the Geriatric Nutritional Risk Index showed the highest specificity in predicting poor prognosis, while the Nutritional Risk Screening 2002 demonstrated the highest specificity in predicting postoperative recurrence.

Background Nutritional risk assessment indices impact disease prognosis, yet their prognostic roles in preoperative digestive system tumor (DST) patients remain unclear. Methods In this study, the Controlling Nutritional Status (CONUT) score, the Nutritional Risk Index (NRI) and the Prognostic Nutritional Index (PNI) before surgery were applied to 17, 338 patients with 10 kinds of newly diagnosed DSTs. The distribution of nutritional risk and its correlation with mortality were examined in this study through the utilization of three nutritional risk assessment indices. Results The study encompassed 17,338 cases of DSTs, comprising 7,644 cases of gastric cancer, 5,542 cases of esophageal cancer, 2,826 cases of pancreatic cancer, 570 cases of gastroesophageal junction cancer, 185 cases of liver cancer, and minimal instances of five other tumor types, each numbering approximately 100. According to the 3 nutritional risk assessment indices, CONUT, NRI and PNI, nutrition risk was common in patients with DSTs (79.24% with CONUT, 38.91% with NRI, 3.13% with PNI), and even in patients with normal or high BMI. In gastric cancer, in addition to age, stage, presence of metastasis, and tumor tissue type, three nutritional risk assessment indices could effectively stratify the prognosis based on nutritional status. CONUT was valuable for predicting the prognosis of intrahepatic cholangiocarcinoma, whereas NRI was significant in Esophageal Cancer and Pancreatic Cancer. Conclusions Nutritional risk was common among DSTs patients and was strongly associated with increased mortality in GC according to CONUT, NRI and PNI Stratification. More attention should be paid to nutritional risk assessment indices to improve prognosis, and prospective clinical trials were needed to evaluate the efficacy of nutritional interventions in GC patients. However, the utility of these three nutritional risk assessment indices in other DSTs was limited.

The geriatric nutritional risk index (GNRI) and modified creatinine index (mCI) are surrogate markers of protein-energy wasting in patients receiving hemodialysis. We aimed to examine whether a combined evaluation of these indices improved mortality prediction in this population. We retrospectively investigated 263 hemodialysis patients divided into two groups, using 91.2 and 20.16 mg/kg/day as cut-off values of GNRI and mCI, respectively. The resultant four groups were reshuffled into four subgroups defined using combinations of cut-off values of both indices and were followed up. During the follow-up period (median: 3.1 years), 103 patients died (46/103, cardiovascular causes). Lower GNRI and lower mCI were independently associated with all-cause mortality (adjusted hazard ratio (aHR) 4.96, 95% confidence intervals (CI) 3.10–7.94, and aHR 1.92, 95% CI 1.22–3.02, respectively). The aHR value for the lower GNRI and lower mCI group vs. the higher GNRI and higher mCI group was 7.95 (95% CI 4.38–14.43). Further, the addition of GNRI and mCI to the baseline risk assessment model significantly improved the C-index of all-cause mortality (0.801 to 0.835, p = 0.025). The simultaneous evaluation of GNRI and mCI could be clinically useful to stratify the risk of mortality and to improve the predictability of mortality in patients on hemodialysis.

Malnutrition prevails among patients with heart failure (HF), increasing the likelihood of functional decline. We assessed the predictive value of the Hemoglobin-Geriatric Nutritional Risk Index (H-GNRI)—combining hemoglobin and the Geriatric Nutritional Risk Index (GNRI)—on prognosis in older patients with HF. We used the JMDC multicenter database to examine the potential associations between malnutrition risk and other outcome measures. The patients were categorized as low- (H-GNRI score = 2), intermediate- (H-GNRI score = 1), or high-risk (H-GNRI score = 0) based on their H-GNRI scores. The primary outcome measure was the Barthel Index (BI) gain; the secondary outcomes included the BI at discharge, the BI efficiency, length of hospital stay, in-hospital mortality, discharge to home or a nursing home, and hospitalization-associated disability. We analyzed 3532 patients, with 244 being low-risk, 952 being intermediate-risk, and 2336 being high-risk patients. The high-risk group of patients had significantly lower BI values at discharge, lower BI gains, reduced BI efficiency values, and prolonged hospital stays compared to those in the low-risk group. The high-risk patients also had higher in-hospital mortality rates, lower rates of discharge to home or a nursing home, and greater incidences of a hospitalization-associated disability in comparison to the low-risk group. The H-GNRI may serve as a valuable tool for determining prognoses for patients with HF.

Background Emergence delirium (ED) is a common complication in elderly surgical patients. While nutritional risk is prevalent, its relationship with ED remains unclear. This study evaluated the association between preoperative nutritional risk, assessed by the objective Geriatric Nutritional Risk Index (GNRI), and ED in elderly patients undergoing non-cardiac surgery. Methods This secondary analysis of a prospective observational study included patients aged 65–90 years undergoing elective non-cardiac surgery. Preoperative nutritional risk was assessed using GNRI calculated from serum albumin and body weight. Nutritional risk was defined as GNRI ≤ 98. The primary outcome was ED assessed by the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) in the Post-Anesthesia Care Unit. Multivariable logistic regression was used to identify independent risk factors. Results Of 915 patients, 20.0% (183/915) were at nutritional risk based on GNRI. The incidence of ED was significantly higher in the nutritional risk group compared to the non-nutritional-risk group (49.7% vs. 33.9%, P  < 0.001). After adjusting for confounders, nutritional risk assessed by GNRI was identified as an independent risk factor for ED (OR 1.80, 95% CI 1.25–2.59, P  = 0.002) and was associated with prolonged postoperative hospital stay (HR 0.83, P  = 0.026). No significant independent association was found between nutritional risk and postoperative delirium or non-delirium complications. Conclusions Preoperative nutritional risk identified by the objective GNRI is independently associated with an increased risk of emergence delirium and prolonged hospitalization in elderly patients. GNRI serves as a valuable, specific screening tool for risk stratification in this population. Clinical trial registrations Chinese Clinical Trial Registry (chictr.org.cn, ChiCTR-OOC-17012734, September 19, 2017)

Aim: This study aimed to investigate how sarcopenia and nutritional risk influence all-cause mortality among older individuals with type 2 diabetes mellitus. Methods: In view of the presence of sarcopenia, defined according to the Asian Working Group for Sarcopenia (AWGS) criteria, and nutritional risk, as determined by the Geriatric Nutritional Risk Index (GNRI), a total of 396 participants were divided into four distinct groups (group 1: no nutritional risk and no sarcopenia, n = 306; group 2: nutritional risk and no sarcopenia, n = 32; group 3: no nutritional risk and sarcopenia, n = 36; and group 4: nutritional risk and sarcopenia, n = 22). Mortality risk was assessed through time-to-event analysis using Cox regression. Results: Throughout the 86-month median follow-up, 31 participants died. Compared to group 1, hazard ratios (HRs) for mortality of groups 2, 3, and 4 were 9.08 (95% confidence interval (95% CI), 2.44–33.8), 9.08 (95% CI: 2.44–33.8), and 14.0 (95% CI: 4.62–42.4), respectively. The risk of death was significantly higher in groups 2, 3, and 4 compared to group 1. Additionally, group 4 had a significantly higher risk of death than group 3. However, no significant difference in mortality risk was observed between groups 3 and 4 when compared to group 2. Conclusions: Coexistence of nutritional risk and sarcopenia was linked to an increased risk of mortality across older individuals with type 2 diabetes mellitus. There was no significant difference in mortality between individuals presenting or not presenting with sarcopenia within the nutritional risk group; therefore, greater attention should be directed toward malnutrition.

Previous studies have reported a close relationship between nutritional and functional domains, but evidence in long-term care residents is still limited. We evaluated the relationship between nutritional risk and functional status and the association of these two domains with mortality in newly institutionalised elderly. In the present multi-centric prospective cohort study, involving 346 long-term care resident elderly, nutritional risk and functional status were determined upon admission by the Geriatric Nutritional Risk Index (GNRI) and the Barthel Index (BI), respectively. The prevalence of high (GNRI < 92) and low (GNRI 92–98) nutritional risk were 36·1 and 30·6 %, respectively. At multivariable linear regression, functional status was independently associated with age (P= 0·045), arm muscle area (P= 0·048), the number of co-morbidities (P= 0·027) and mainly with the GNRI (P< 0·001). During a median follow-up of 4·7 years (25th–75th percentile 3·7–6·2), 230 (66·5 %) subjects died. In the risk analysis, based on the variables collected at baseline, both high (hazard ratio (HR) 1·86, 95 % CI 1·32, 2·63; P< 0·001) and low nutritional risk (HR 1·52, 95 % CI 1·08, 2·14; P= 0·016) were associated with all-cause mortality. Participants at high nutritional risk (GNRI < 92) also showed an increased rate of cardiovascular mortality (HR 1·93, 95 % CI 1·28, 2·91; P< 0·001). No association with outcome was found for the BI. Upon admission, nutritional risk was an independent predictor of functional status and mortality in institutionalised elderly. Present data support the concept that the nutritional domain is more relevant than functional status to the outcome of newly institutionalised elderly.

Controversies exist as to the suitability of various nutrition screening tools for various age groups, the incorporation of age and age-related criteria into some tools, and the procedures associated with tool selection. Reviews of the literature and national and local datasets were used to identify the types of screening tools available for different age groups, the origins of age-related criteria, and the value of tool selection procedures based on predicting clinical outcomes. Nutrition screening can be undertaken in fetuses, children, and adults over narrow or wide age ranges, for diagnostic or prognostic purposes, with or without nutritional interventions. Certain tools can establish malnutrition risk without using any nutritional criteria, whereas others can do so only with nutritional criteria. The incorporation of age and age-specific body mass index criteria into adult screening tools can influence the prevalence and age distribution of malnutrition, but no justification is usually provided for their use. In several circumstances, age alone can predict mortality and length of hospital stay much better than screening tools. We identified various methodologic problems in nutrition screening tool selection. A comparison of nutrition screening tools designed for different age groups and different purposes can be problematic. Age and screening tools incorporating risk factors that are non-modifiable or generally weakly modifiable by nutritional support (e.g., age, disease severity) may predict outcomes of disease, but they are not necessarily suitable for predicting outcomes of nutritional support. To contextualize the findings, a framework for screening tool selection is suggested that takes into account a matrix of needs.