Serum albumin (ALB) has traditionally been regarded as a marker of nutritional status. However, recent studies suggest its changes are closely linked to inflammation, metabolic dysregulation, and disease severity, limiting its role as a sole indicator of nutritional status. Yet, clinical practice continues to rely on ALB to monitor nutritional interventions, with a paucity of high-quality evidence on its dynamic associations with clinical outcomes. This study aimed to investigate the comprehensive associations of ALB dynamics with inflammation, nutritional status, and clinical outcomes in hospitalized patients, providing evidence to optimize clinical management. This secondary analysis utilized data from a prospective observational cohort study conducted in 34 tertiary hospitals across China between June and September 2014. A total of 2959 patients hospitalized for 7–30 days with complete data were included. Standardized protocols were used to collect demographics, nutritional indices (Nutritional Risk Screening 2002, Subjective Global Assessment), hematology, biochemistry results, and clinical outcomes (complications, length of stay, costs). Subgroup analyses were performed based on inflammatory status changes, nutritional therapy administration, department type, baseline nutritional status, and advanced age. Receiver operating characteristic curves identified cutoff values for infection-related complications. Correlation analyses and multivariable linear regression models determined independent predictors of ALB changes. Among 2959 patients, 1894 (64.0%) experienced a decrease in ALB during hospitalization, which significantly impacted primary outcomes, including prolonged length of stay, increased hospitalization costs, and higher complication rates. Significant ALB decline was also strongly associated with worsened nutritional status, weight loss at discharge, exacerbated gastrointestinal symptoms, functional impairments, and edema (P < 0.001 for all). Compared to binary categorization (increase vs. decrease), the magnitude of ALB change demonstrated a stronger correlation with infection-related complications across all subgroups. Subgroup-specific cutoff values stratified patients into high- and low-risk groups, with significant differences in infection-related complication rates (P < 0.05), aiding early identification and intervention. Independent predictors of ALB decline included advanced age, surgical status, lower baseline handgrip strength and its change during hospitalization, higher baseline ALB and globulin levels, baseline Prognostic Nutritional Index, baseline inflammatory status and its exacerbation, elevated platelet-to-lymphocyte ratio, and intensive care unit admission. Dynamic changes in ALB serve as a critical indicator of inflammation–nutrition interplay, with its reduction effectively predicting infection-related complications, clinical outcomes, and nutritional deterioration. This is particularly valuable in older adults, inflammatory-variable, surgical, and non-malnourished patients. The conventional view of ALB as a pure nutritional marker requires revision. Joint monitoring with inflammatory biomarkers and multidisciplinary interventions targeting high-risk populations are recommended.

The controlling nutritional status (CONUT) score assesses nutritional status and is associated with short- and long-term prognoses in some diseases, but the significance of the CONUT score for the prediction of in-hospital mortality in older adults is unknown. The purpose was to determine the importance of the CONUT score for the prediction of in-hospital mortality, short-term complications, length of hospital stay, and hospital costs in older adults. Our retrospective cohort study analyzed data from 11,795 older adult patients from two multicenter cohort studies. We performed receiver operating characteristic curve analysis using in-hospital mortality as the endpoint and determined the appropriate CONUT score cut-off by the Youden index. The patients were divided into two high and low groups according to the CONUT cut-off value, and the differences in clinical characteristics and in-hospital clinical outcomes between the two groups were compared. We compared the accuracy of the CONUT score and other nutrition-related tools in predicting in-hospital mortality by calculating the area under the receiver operating characteristic curve and performed univariate and multivariate analyses of predictors of in-hospital mortality. Among all the patients, 178 (1.5%) patients experienced in-hospital death. The optimal cut-off values was 5.5 for the CONUT score. The high CONUT group had a higher incidence of short-term complications and prolonged hospital stay than the low CONUT group (CONUT score <6), but hospital costs were not significantly higher. The CONUT score had the highest predictive ability for in-hospital mortality among the five nutrition-related parameters compared. Multivariate analysis showed that a high CONUT score (CONUT score ≥ 6) was an independent predictor of in-hospital mortality. In conclusion, the present study demonstrated that the CONUT score could be used to predict in-hospital mortality in older adults.

Background: Malnutrition is prevalent among patients with cancer. The Global Leadership Initiative on Malnutrition (GLIM) released new universal criteria for diagnosing malnutrition in 2019. The objectives of this study were to assess the prevalence of malnutrition in patients with cancer using the GLIM criteria, explore the correlation between the GLIM criteria, and clinical outcomes, and compare the GLIM criteria with subjective global assessment (SGA).Methods: This retrospective analysis was conducted on 2,388 patients with cancer enrolled in a multicenter study. Nutritional risk was screened using the Nutritional Risk Screening-2002, and the nutritional status was assessed using SGA and GLIM criteria. Chi-square analysis and Wilcoxon rank sum test, stratified by age 65 years, were used to evaluate the effect of GLIM-defined malnutrition on clinical outcomes. Logistic regression analysis was used to analyze the nutritional status and complications, and the interrater reliability was measured using a kappa test.Results: The prevalence of malnutrition defined by the GLIM criteria was 38.9% (929/2,388). GLIM-defined malnutrition was significantly associated with in-hospital mortality (P = 0.001) and length of hospital stays (P = 0.001). Multivariate logistic regression analysis showed GLIM-defined malnutrition significantly increased complications (odds ratio [OR] 1.716, 95% CI 1.227–2.400, P = 0.002). The GLIM criteria had a “moderate agreement” (kappa = 0.426) compared with the SGA.Conclusions: The prevalence of malnutrition in hospitalized patients with cancer is high, and malnourishment in patients with cancer is associated with poorer clinical outcomes. The use of the GLIM criteria in assessing the nutritional status of inpatients with cancer is recommended and can be used as the basis for nutritional interventions.

Background & AIMS To compare the association of geriatric nutritional risk index (GNRI) and controlling nutritional status (CONUT) scores with malnutrition, and to study their association with clinical outcomes in older adult cancer patients. Methods This retrospective analysis was conducted on 854 older adult cancer patients collected from 34 hospitals in 18 cities in China between June and September 2014. Anthropometric and hematological examination results at admission were collected, and subjective global assessment was used. Clinical outcomes, such as complications, length of hospital stays, and hospital costs, were recorded. Receiver operating characteristic curves were used to evaluate the accuracy of the two nutritional assessment tools for malnutrition. The association between GNRI and CONUT score and clinical outcomes was analyzed using the chi-square test, t-test, or rank sum test. Results Among 854 patients with cancer, the prevalence of malnutrition was 42.7%. Compared with subjective global assessment, the GNRI had a significantly higher accuracy than the CONUT score in predicting malnutrition (area under the curve 0.704, 95% confidence interval, 0.658–0.750, P < 0.001). The GNRI was significantly associated with the occurrence of complications (χ2 = 4.985, P = 0.026), and low GNRI (≤98) was associated with a longer length of hospital stay (t = −2.179, P = 0.030). Conclusions The GNRI may be used to assess malnutrition in older adult cancer patients and can predict poor clinical outcomes in these patients.