Malnutrition significantly hampers wound healing processes. This study aimed to compare the effectiveness of the Global Leadership Initiative on Malnutrition (GLIM) and Subjective Global Assessment (SGA) in diagnosing malnutrition and predicting wound healing in patients with diabetic foot ulcers (DFU). GLIM criteria were evaluated for sensitivity (SE), specificity (SP), positive predictive value, negative predictive value and kappa (κ) against SGA as the reference. Modified Poisson regression model and the DeLong test investigated the association between malnutrition and non-healing ulcers over 6 months. This retrospective cohort study included 398 patients with DFU, with a mean age of 66·3 ± 11·9 years. According to SGA and GLIM criteria, malnutrition rates were 50·8 % and 42·7 %, respectively. GLIM criteria showed a SE of 67·3 % (95 % CI 60·4 %, 73·7 %) and SP of 82·7 % (95 % CI 76·6 %, 87·7 %) in identifying malnutrition, with a positive predictive value of 80·0 % and a negative predictive value of 71·1 % (κ = 0·50) compared with SGA. Multivariate analysis demonstrated that malnutrition, as assessed by SGA, was an independent risk factor for non-healing (relative risk (RR) 1·84, 95 % CI 1·45, 2·34), whereas GLIM criteria were associated with poorer ulcer healing in patients with estimated glomerular filtration rate ≥ 60 ml/min/1·73m2 (RR: 1·46, 95 % CI 1·10, 1·94). SGA demonstrated a superior area under the receiver\'s operating characteristic curve for predicting non-healing compared with GLIM criteria (0·70 (0·65-0·75) v. 0·63 (0·58-0·65), P < 0·01). These findings suggest that both nutritional assessment tools effectively identify patients with DFU at increased risk, with SGA showing superior performance in predicting non-healing ulcers.

Malnutrition is a critical issue among older inpatients, yet limited large-scale research related to this issue has been conducted in China. This study aimed to examine the nutritional status and support of older inpatients in China, assess the associations between disease categories and malnutrition on admission, and explore effective nutritional intervention.
A total of 24,139 older participants from the China Nutrition Fundamental Data 2020 Project were included. Malnutrition was measured by the Global Leadership Initiative on Malnutrition criteria. Adjusted odds ratios (aORs) were calculated using logistic analysis.
The overall frequency of malnutrition on admission was 18.9%. Participants with infections were more likely to have malnutrition (aOR = 1.929, 95% CI 1.486-2.504). Risks that were also noted for malnutrition included neoplasms (aOR = 1.822, 95% CI 1.697-1.957), hemic and lymphatic diseases (aOR = 1.671, 95% CI 1.361-2.051), nervous system diseases (aOR = 1.222, 95% CI 1.126-1.326), respiratory diseases (aOR = 1.613, 95% CI 1.490-1.746), and digestive system diseases (aOR = 1.462, 95% CI 1.357-1.577). Further, 32.26% inpatients with malnutrition during hospitalization didn\'t receive nutritional support. Oral nutrition supplements, enteral tube feeding, and parenteral nutrition were associated with stable or improved nutritional status.
Older inpatients were at a high risk for malnutrition but did not receive adequate nutritional intervention. More resources and attention need to be devoted to the nutritional status of older inpatients and targeted nutritional support.

Malnutrition and subsequent alterations in body composition (BC), particularly sarcopenia, are common but not yet elucidated in patients with inflammatory bowel disease (IBD); we aimed to detail the changes in BC and the characteristics of co-occurrence of malnutrition and sarcopenia in IBD patients and to investigate its effect on quality of life.
This study was a multicentre, prospective, observational study involving four tertiary referral hospitals in China. The following data were collected from consecutive IBD inpatients: demographic information, medical history, recent weight change, handgrip strength (HGS) and BC parameters by bioelectrical impedance analysis (BIA). Nutritional assessments were performed through stepwise screening (Nutritional Risk Screening 2002) and diagnosis (World Health Organization-related body mass index [BMI], subjective global assessment, European Society for Clinical Nutrition and Metabolism 2015 and Global Leadership Initiative on Malnutrition [GLIM] criteria). The quality of life was assessed by the Inflammatory Bowel Disease Questionnaire. IBD patients were compared with 1:1 sex-, age- and BMI-matched healthy controls (MHC).
A total of 238 IBD patients (177 Crohn\'s disease [CD] and 61 ulcerative colitis [UC]), 68.5% male, with a mean age of 38.5 ± 14.0 years and a mean BMI of 19.8 ± 3.5 kg/m2 , were recruited. Compared with MHC (n = 122), IBD patients showed significant deterioration in BC and physical function, characterized by muscle depletion (appendicular skeletal muscle mass index [ASMI], 8.0 ± 1.3 vs. 6.7 ± 1.2 kg/m2 , Δ% -15.0% [-22.0%, -10.0%], P < 0.001) and fat accumulation (visceral fat area, 32.9 ± 22.6 vs. 66.5 ± 35.8, Δ% 110.0% [35.0%, 201.0%], P < 0.001). The prevalence of GLIM-defined malnutrition and sarcopenia in IBD patients was 60.1% and 25.2%, respectively. The nutritional status of patients with CD was worse than that of patients with UC. The activity phase of IBD significantly and negatively affected BC, while the lesion location did not. The co-occurrence of sarcopenia and malnutrition was not optimistic; 16.4-21.8% of patients suffer from sarcopenia and malnutrition based on different criteria at the same time, which was accompanied by a reduction in quality of life. HGS was correlated with various BC parameters (body cell mass, r = 0.76; ASMI, r = 0.70; fat-free mass, r = 0.73, all P < 0.001).
GLIM-defined malnutrition and sarcopenia were prevalent in IBD patients and kept a high rate of co-occurrence, which was accompanied with impaired quality of life. The alteration of BC in IBD patients was characterized by muscle depletion and fat accumulation. The strong correlation between HGS and BIA-derived BC suggested its hopeful evaluation in nutritional status and sarcopenia in IBD patients.

暂无摘要。

This study aimed to assess malnutrition using the Global Leadership Initiative on Malnutrition (GLIM) criteria and Subjective Global Assessment (SGA) at baseline and determine the GLIM criteria that best predicted unplanned hospitalization in outpatients with unintentional weight loss (UWL).
We performed a retrospective cohort study of 257 adult outpatients with UWL. The GLIM criteria and SGA agreement were reported using the Cohen kappa coefficient. Kaplan-Meier survival curves and adjusted Cox regression analyses were used for survival data. Logistic regression was used for the other correlation analysis.
This study collected data from 257 patients for 2 years. Based on the GLIM criteria and SGA, malnutrition prevalence was 79.0% and 72.0%, respectively (κ = 0.728, P < 0.001). Using the SGA as a standard, GLIM had a sensitivity of 97.8%, a specificity of 69.4%, a positive predictive value of 89.2%, and a negative predictive value of 92.6%. Malnutrition was associated with higher rates of unplanned hospital admission independent of other prognostic factors (GLIM: hazard ratio [HR]=2.85, 95% CI=1.22-6.68; SGA: HR=2.07, 95% CI=1.13-3.79). Of the five GLIM criteria-related diagnostic combinations, disease burden or inflammation was the most important to predict unplanned hospital admission in multivariable analysis (HR=3.27, 95% CI=2.03-5.28).
There was good agreement between the GLIM criteria and the SGA. GLIM-defined malnutrition, as well as all five GLIM criteria-related diagnosis combinations, had the potential to predict unplanned hospital admissions in outpatients with UWL within 2 years.

Older patients are at an increased risk of malnutrition due to many factors related to poor clinical outcomes.
This study aims to develop an assisted diagnosis model using machine learning (ML) for identifying older patients with malnutrition and providing the focus of individualized treatment.
We reanalyzed a multicenter, observational cohort study including 2660 older patients. Baseline malnutrition was defined using the global leadership initiative on malnutrition (GLIM) criteria, and the study population was randomly divided into a derivation group (2128/2660, 80%) and a validation group (532/2660, 20%). We applied 5 ML algorithms and further explored the relationship between features and the risk of malnutrition by using the Shapley additive explanations visualization method.
The proposed ML models were capable to identify older patients with malnutrition. In the external validation cohort, the top 3 models by the area under the receiver operating characteristic curve were light gradient boosting machine (92.1%), extreme gradient boosting (91.9%), and the random forest model (91.5%). Additionally, the analysis of the importance of features revealed that BMI, weight loss, and calf circumference were the strongest predictors to affect GLIM. A BMI of below 21 kg/m2 was associated with a higher risk of GLIM in older people.
We developed ML models for assisting diagnosis of malnutrition based on the GLIM criteria. The cutoff values of laboratory tests generated by Shapley additive explanations could provide references for the identification of malnutrition.
Chinese Clinical Trial Registry ChiCTR-EPC-14005253; https://www.chictr.org.cn/showproj.aspx?proj=9542.

UNASSIGNED: Recently, some cohorts have looked into the use of Global Leadership Initiative on Malnutrition (GLIM) criteria in cancer patients. The objective of the current meta-analysis was to determine its utility in predicting clinical and survival outcomes for cancer patients.
UNASSIGNED: Searching and screening literature from PubMed, Web of Science and Embase until September 13, 2022 was performed by two researchers independently. According to the exclusion and inclusion criteria, articles reporting the impact of malnutrition diagnosed by GLIM on long-term survival and clinical outcomes were included. Data of interest were also extracted from the included papers. The stability of the pooled results was evaluated using sensitivity analysis. With the aid of subgroup analysis, heterogeneity was revealed. To assess publication bias, Egger\'s and Begg\'s tests were conducted. The influence of publication bias on the pooling risk estimate was examined using a trim-and-fill analysis.
UNASSIGNED: 15 studies that qualified for our study were identified. Pooled hazard ratio (HR) from both multivariate and univariate regression analysis showed a worse overall survival in GLIM-defined malnourished cancer patients than those in well-nourished status. Meanwhile, disease-free survival was also poorer in malnourished patients. Moreover, pooled odds ratio (OR) demonstrated that malnourished cancer patients were more likely to develop overall postoperative complications, complications ≥ Clavien-Dindo grade IIa and complications ≥ Clavien-Dindo grade IIIa. Two articles reported negative relation between GLIM-defined malnutrition and 30-day readmission/mortality.
UNASSIGNED: GLIM-defined malnutrition possesses value in predicting poorer survival and clinical outcomes for cancer patients.
UNASSIGNED: [https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=321094], identifier [CRD42022321094].

The Global Leadership Initiative on Malnutrition (GLIM) was convened by several of the major global clinical nutrition societies. This tool used the phenotypic and etiologic criteria to diagnose the malnutrition in adults. This meta-analysis aimed to examine the association between malnutrition defined by the GLIM and survival outcomes in patients with cancer.
Two independent authors comprehensively searched the articles indexed in PubMed, Web of Science, Embase databases until June 25, 2022. Only cohort studies evaluating the association of malnutrition defined by the GLIM with survival outcomes in cancer patients were included. The fully adjusted hazard ratio (HR) with 95% confidence intervals (CI) was pooled for the malnutrition versus the those without.
Twelve article reporting on 11 studies including 6799 cancer patients were identified. Four articles were grouped to have moderate risk of bias and 8 articles were deemed to have a low risk of bias. The prevalence of malnutrition defined by the GLIM ranged from 11.9% to 87.9%. Meta-analysis indicated that malnutrition defined by the GLIM was associated with poor overall survival (HR 1.90; 95% CI 1.58-2.29) and disease-free survival (HR 1.51; 95% CI 1.27-1.79), respectively. Subgroup analysis showed that the pooled HR was 1.49 (95% CI 1.32-1.68) for moderate malnutrition and 1.68 (95% CI 1.42-1.99) for severe malnutrition.
Malnutrition defined by the GLIM is significantly associated with reduced overall survival and disease-free survival in patients with cancer. Detection of nutritional status using GLIM has potential to improve survival stratification in these patients.

The present study aimed to investigate the prognostic value of the preoperative fat-free mass index (FFMI) for postoperative outcomes in patients undergoing esophagogastric cancer surgery and to explore the role of the FFMI in the Global Leadership Initiative on Malnutrition (GLIM) criteria.
This multicenter retrospective observational study took place in four teaching tertiary hospitals in China from September 2015 to June 2018. Malnutrition was diagnosed following the GLIM criteria. The evaluation of muscle mass (ie, the FFMI) as one of the constituents contained in the GLIM consensus was measured by bioelectrical impedance analysis. According to their FFMI per the GLIM criteria, patients with esophagogastric cancer were divided into a normal-FFMI group and a low-FFMI group. The observation indicators were postoperative complications, length of stay, wound healing time, postoperative antibiotic time, and nutritional status in the two groups.
Of the 205 total patients with esophagogastric cancer, 76 (37.1%) were diagnosed with malnutrition. The normal-FFMI group had a significantly lower rate of postoperative complications (43 [33.3%] of 129 patients versus 37 [48.7%] of 76 patients; P = 0.038) and a shorter postoperative length of stay (12.6 ± 3.1 d versus 14.3 ± 3.2 d; P = 0.034), postoperative antibiotic time (5.3 ± 2.9 d versus 6.4 ± 2.1 d; P = 0.031), and wound healing time (10.9 ± 2.5 d versus 11.9 ± 3.1 d; P = 0.005) compared with the low-FFMI group. There were no significant differences between the groups in rates of other clinical outcomes. The body mass index (BMI) and FFMI were generally consistent in the diagnosis of malnutrition based on GLIM criteria (kappa, 0.464; P < 0.001). The linear correlation between BMI and FFMI (correlation coefficient, 0.659; P < 0.001) was moderate in patients with esophagogastric cancer who were at nutritional risk.
The FFMI has an important role in the diagnosis of malnutrition using the GLIM criteria. In this study, a decreased preoperative FFMI was closely associated with postoperative complications in patients with esophagogastric cancer.

The Global Leadership Initiative on Malnutrition (GLIM) has achieved a consensus for the diagnosis of malnutrition in recent years. This study aims to determine the prognostic effect of the GLIM after cardiac surgery. A total of 603 patients in the training cohort and 258 patients in the validation cohort were enrolled in this study. Perioperative characteristics and follow-up data were collected. A nomogram based on independent prognostic predictors was developed for survival prediction. In total, 114 (18.9%) and 48 (18.6%) patients were defined as being malnourished according to the GLIM criteria in the two cohorts, respectively. Multivariate regression analysis showed that GLIM-defined malnutrition was an independent risk factor of total complication (OR 1.661, 95% CI: 1.063-2.594) and overall survival (HR 2.339, 95% CI: 1.504-3.637). The c-index was 0.72 (95% CI: 0.66-0.79) and AUC were 0.800, 0.798, and 0.780 for 1-, 2-, and 3-year survival prediction, respectively. The calibration curves of the nomogram fit well. In conclusion, GLIM criteria can efficiently identify malnutrition and has a prognostic effect on clinical outcomes after cardiac surgery. GLIM-based nomogram has favorable performance in survival prediction.