Prediction of 5-year mortality risk by malnutrition according to the GLIM format using seven pragmatic approaches to define the criterion of loss of muscle mass

Malnutrition as a prognostic factor for 2-year mortality in hospitalized patients in Norway: A matched cohort study

BACKGROUND

Risk of malnutrition and malnutrition have been previously associated with increased risk of mortality. It remains unclear, however, whether the severity of malnutrition differentiates in association with all-cause mortality. The aim was to assess the association between being at risk of malnutrition or being diagnosed with malnutrition according to the diagnostic assessment of the Global Leadership Initiative on Malnutrition (GLIM) with all-cause mortality during a 2-year follow-up in hospitalized patients.

METHODS

A matched cohort study was conducted in hospitalized patients (excluding cancer, intensive care, and transmissible infections) at a university hospital in Bergen, Norway. All patients underwent nutrition screening with the Nutritional Risk Screening 2002 and a further nutrition assessment using the GLIM criteria. All-cause mortality was estimated from the Norwegian death registry after 2 years, and risk factors were calculated by Cox regression analysis.

RESULTS

Among 326 patients included, 55 patients died within 2 years (17% mortality rate). Risk of malnutrition was associated with increased all-cause mortality, which disappeared after adjustment for age and sex. Malnutrition was associated with an increased risk of all-cause mortality at 2 years also after adjustment for age and sex and, additionally, for further comorbidities (hazard ratio = 2.50; 95% CI, 1.41-4.42). When analyzed separately only severe malnutrition was associated with mortality (hazard ratio = 2.73; 95% CI, 1.44-5.15).

CONCLUSION

The findings highlight a strong association between inpatients with severe malnutrition, defined by the GLIM criteria, and an increased risk of all-cause mortality within a 2-year follow-up.

The Global Leadership Initiative on Malnutrition criteria for diagnosis of malnutrition and outcomes prediction in emergency abdominal surgery

OBJECTIVES

Malnutrition has adverse postoperative outcomes, especially in emergency surgery. Among the numerous tools for nutritional assessment, this study aims to investigate malnutrition diagnosed by Global Leadership Initiative on Malnutrition criteria and the Global Leadership Initiative on Malnutrition predictive value for outcomes after emergency abdominal surgery.

METHODS

This was a prospective observational study. Among the 468 patients undergoing emergency abdominal surgery admitted to a department of emergency surgery from June 2020 to December 2021, 53 patients were not eligible for enrollment, and 19 patients had missing data. Thus, the final number of participants was 396. Muscle mass was evaluated by skeletal muscle index at the third lumbar vertebra on computed tomography scans, and the lower quartile was defined as the threshold of muscle mass reduction. The associations of Global Leadership Initiative on Malnutrition, Global Leadership Initiative on Malnutrition (muscle mass reduction excluded), and skeletal muscle index with in-hospital mortality, postoperative complications, and postoperative stay were evaluated using χ2. In addition, confounding factors were screened, regression models were established, and the Global Leadership Initiative on Malnutrition predictive value was analyzed for clinical outcome. Ethical approval was obtained from the appropriate department.

RESULTS

Malnutrition was observed in 19.9% of the total 396 patients based on the Global Leadership Initiative on Malnutrition and in 12.4% on the Global Leadership Initiative on Malnutrition (muscle mass reduction excluded). Sarcopenia by skeletal muscle index was found in 24.7% of patients. Univariate analysis indicated that in-hospital mortality, postoperative complications, infective complication rate, and postoperative hospital stay were significantly higher in malnourished and sarcopenic patients. Multivariate analysis found that malnutrition diagnosed by the Global Leadership Initiative on Malnutrition was predictive for complications, infective complications, and postoperative stay (total postoperative complications: odds ratio = 3.620; 95% CI, 1.635-8.015; P = 0.002; infective complications: odds ratio = 3.127; 95% CI, 1.194-8.192; P = 0.020; and postoperative stay: regression coefficient = 2.622; P = 0.022). The Global Leadership Initiative on Malnutrition (muscle mass reduction excluded) identified postoperative complications and postoperative stay (total postoperative complications: odds ratio = 3.364; 95% CI, 1.247-9.075; P = 0.017 and postoperative stay: regression coefficient = 3.547; P = 0.009). Sarcopenia by skeletal muscle index was a risk factor for postoperative complications (odds ratio = 3.366; 95% CI, 1.587-7.140; P = 0.002).

CONCLUSION

The Global Leadership Initiative on Malnutrition and Global Leadership Initiative on Malnutritison (muscle mass reduction excluded) had predictive value for adverse clinical outcomes due to malnutrition in patients undergoing emergency abdominal surgery.

3D Convolutional Deep Learning for Nonlinear Estimation of Body Composition from Whole-Body Morphology

Total and regional body composition are strongly correlated with metabolic syndrome and have been estimated non-invasively from 3D optical scans using linear parameterizations of body shape and linear regression models. Prior works produced accurate and precise predictions on many, but not all, body composition targets relative to the reference dual X-Ray absorptiometry (DXA) measurement. Here, we report the effects of replacing linear models with nonlinear parameterization and regression models on the precision and accuracy of body composition estimation in a novel application of deep 3D convolutional graph networks to human body composition modeling. We assembled an ensemble dataset of 4286 topologically standardized 3D optical scans from four different human body shape databases, DFAUST, CAESAR, Shape Up! Adults, and Shape Up! Kids and trained a parameterized shape model using a graph convolutional 3D autoencoder (3DAE) in lieu of linear PCA. We trained a nonlinear Gaussian process regression (GPR) on the 3DAE parameter space to predict body composition via correlations to paired DXA reference measurements from the Shape Up! scan subset. We tested our model on a set of 424 randomly withheld test meshes and compared the effects of nonlinear computation against prior linear models. Nonlinear GPR produced up to 20% reduction in prediction error and up to 30% increase in precision over linear regression for both sexes in 10 tested body composition variables. Deep shape features produced 6-8% reduction in prediction error over linear PCA features for males only and a 4-14% reduction in precision error for both sexes. Our best performing nonlinear model predicting body composition from deep features outperformed prior work using linear methods on all tested body composition prediction metrics in both precision and accuracy. All coefficients of determination (R2) for all predicted variables were above 0.86. We show that GPR is a more precise and accurate method for modeling body composition mappings from body shape features than linear regression. Deep 3D features learned by a graph convolutional autoencoder only improved male body composition accuracy but improved precision in both sexes. Our work achieved lower estimation RMSEs than all previous work on 10 metrics of body composition.

Anthropometric measures and physical examination could be used to assess phenotypic GLIM (Global leadership initiative on malnutrition) criteria in heart failure patients

BACKGROUND AND AIMS

The assessment of muscle mass using technology-based methods is less commonly performed when applying the Global Leadership Initiative on Malnutrition (GLIM) criteria due to the lack of skilled clinical nutrition practitioners and/or equipment. Based on the predictive validity of poor health outcomes and feasibility in clinical practice, this study aimed to analyze whether the measurement of calf circumference (CC), mid-upper arm circumference (MAC), and the physical examination could be used as substitutes for muscle mass assessment, as well as handgrip strength (HGS) used as a substitution when applying the GLIM criteria in hospitalized HF patients.

METHODS AND RESULTS

From June 2022 to January 2023, a single-center prospective study including 216 patients was performed. Additionally, covariates were identified by a directed acyclic graph. The multivariate logistic regression analysis was also used to analyze and compare the association between poor health outcomes and malnutrition (based on 5 types of GLIM criteria). Cohen-kappa coefficient and TELOS-feasibility score were calculated. The prevalence of malnutrition ranged from 35.2% to 42.6%, depending on the tool used. After adjusting for covariates, malnutrition assessed using CC, MAC, or physical examination within the GLIM criteria was independently associated with poor clinical outcomes (90-day HF-related readmission or all-cause mortality and prolonged hospital stay) but not with HGS.

CONCLUSION

CC, MAC and results from physical examination but not HGS may serve as a substitutive metric of muscle mass contained in the GLIM criteria to diagnose malnutrition and predict poor clinical outcomes among HF patients.

REGISTRATION NUMBER

This study was registered at Chinese Clinical Trial Registry. (ChiCTR2200057876) on 20 Mar. 2022.

Nutritional indicators' performance in malnutrition diagnosis of hospitalized elderly patients

BACKGROUND

Several nutritional diagnosis methods and their relationship with clinical outcomes have been described. This study investigated malnutrition in hospitalized elderly patients (HEP) using different nutritional indicators and determined criteria to identify malnutrition and explore the variables that discriminate the risk of malnutrition.

METHOD

Cross-sectional study with 500 HEP; different methods of nutritional diagnosis, their relationship with clinical outcomes and criteria for defining malnutrition were investigated. The GLIM criteria for the diagnosis of malnutrition was applied in this study. In the statistical analysis, the Chi-square test, Fisher's exact test, Mann-Whitney test, univariate and multiple logistic regression and the ROC curve were used.

RESULTS

Patients aged 65-79 years, at nutritional risk or with malnutrition, had longer hospital stays (p = 0.0099; OR = 1.047; 95% CI = 1.011; 1.084) and lower body mass index (BMI) (p < 0.0001; OR = 0.867 (1153)); 95% CI = 0.813; 0.924 (1085; 1225). Patients aged ≥80 years had a lower BMI (p = 0.0053; OR = 0.779 (1284); 95% CI = 0.653; 0.928 (1078; 1531)). Accuracy was significant in both age groups for BMI (p < 0.0001; 65-79 years and p = 0.001; ≥80 years); for the lymphocyte count (p = 0.0167; 65-79 years and p = 0.0028; ≥80 years), and for the calf circumference (CC) (p < 0.0001; 65-79 years and p = 0.001; ≥80 years). Using the GLIM criteria, 27.78% of patients were considered malnourished. CC showed good accuracy, good specificity, but low sensitivity while BMI was more accurate to detect malnutrition in both age groups.

CONCLUSION

CC showed good accuracy, good specificity, but low sensitivity to detect malnutrition. BMI was more accurate in both age groups to detect malnutrition.

Cross-sectional assessment of body composition and detection of malnutrition risk in participants with low body mass index and eating disorders using 3D optical surface scans

BACKGROUND

New recommendations for the assessment of malnutrition and sarcopenia include body composition, specifically reduced muscle mass. Three-dimensional optical imaging (3DO) is a validated, accessible, and affordable alternative to dual X-ray absorptiometry (DXA).

OBJECTIVE

Identify strengths and weaknesses of 3DO for identification of malnutrition in participants with low body mass index (BMI) and eating disorders.

DESIGN

Participants were enrolled in the cross-sectional Shape Up! Adults and Kids studies of body shape, metabolic risk, and functional assessment and had BMI of <20 kg/m2 in adults or <85% of median BMI (mBMI) in children and adolescents. A subset was referred for eating disorders evaluation. Anthropometrics, scans, strength testing, and questionnaires were completed in clinical research centers. Lin's Concordance Correlation Coefficient (CCC) assessed agreement between 3DO and DXA; multivariate linear regression analysis examined associations between weight history and body composition.

RESULTS

Among 95 participants, mean ± SD BMI was 18.3 ± 1.4 kg/m2 in adult women (N = 56), 19.0 ± 0.6 in men (N = 14), and 84.2% ± 4.1% mBMI in children (N = 25). Concordance was excellent for fat-free mass (FFM, CCC = 0.97) and strong for appendicular lean mass (ALM, CCC = 0.86) and fat mass (FM, CCC = 0.87). By DXA, 80% of adults met the low FFM index criterion for malnutrition, and 44% met low ALM for sarcopenia; 52% of children and adolescents were <-2 z-score for FM. 3DO identified 95% of these cases. In the subset, greater weight loss predicted lower FFM, FM, and ALM by both methods; a greater percentage of weight regained predicted a higher percentage of body fat.

CONCLUSIONS

3DO can accurately estimate body composition in participants with low BMI and identify criteria for malnutrition and sarcopenia. In a subset, 3DO detected changes in body composition expected with weight loss and regain secondary to eating disorders. These findings support the utility of 3DO for body composition assessment in patients with low BMI, including those with eating disorders. This trial was registered at clinicaltrials.gov as NCT03637855.

Intrinsic capacity and risk of death: Focus on the impact of using different diagnostic criteria for the nutritional domain

OBJECTIVE

We aimed to estimate the ability of intrinsic capacity (IC) to predict death in community-dwelling older people using different diagnostic criteria to define the nutritional domain.

METHODS

Participants from the Belgian SarcoPhAge cohort were followed from 2013 to the present. Four IC domains were assessed at baseline (data on the sensorial domain were not collected), and considered unsatisfactory below some specific thresholds. The nutritional domain was considered unsatisfactory if baseline malnutrition was present, defined by: 1) MNA-SF ≤11 points; 2) seven versions of the GLIM criteria, varying by the technique used to identify a reduced muscle mass; or 3) the combination of MNA-SF ≤11 points + GLIM criteria. The association between baseline unsatisfactory IC and 9-year mortality was calculated using the odds ratio (OR) adjusted for cofounders.

RESULTS

Among the 534 participants (73.5 ± 6.2 years old; 60.3 % women at baseline), 157 (29.4 %) were dead after 9.3 ± 0.3 years of follow-up. Patients with baseline unsatisfactory IC in the locomotor domain (adjusted OR = 2.31 [95%CI 1.38-3.86]) or psychological domain (adjusted OR = 1.78 [1.12-2.83]) were at higher mortality risk. Regarding malnutrition, unsatisfactory IC in the nutrition domain was strongly associated with a higher mortality risk, whatever the criteria used to identify a reduced muscle mass. The highest association with mortality was found in participants with a baseline unsatisfactory nutritional domain defined by the combination of MNA-SF + GLIM criteria (adjusted OR = 3.27 [95%CI 1.72-6.23]).

CONCLUSIONS

Presenting any unsatisfactory IC at baseline was associated with a higher 9-year mortality risk in community-dwelling older people. The sequential incorporation of MNA-SF and GLIM criteria as the IC nutritional domain would be helpful to guide public health actions towards healthy ageing.

Machine Learning-Based Prediction of Complications and Prolonged Hospitalization with the GLIM Criteria Combinations Containing Calf Circumference in Elderly Asian Patients

BACKGROUND AND AIMS

Malnutrition is widely present and influences the prognosis of elderly inpatients, so it is helpful to be able to identify it with a convenient method. However, in the widely accepted criteria for malnutrition, the Global Leadership Initiative on Malnutrition (GLIM), a lot of metrics can be used to define the phenotypic and etiological criteria. To identify muscle mass reduction, anthropometric parameters such as calf circumference (CC) and hand grip strength (HGS) are preferable to other expensive methods in many situations because they are easy and inexpensive to measure, but their applicability needs to be verified in specific clinical scenarios. This study aims to verify the value of CC- and HGS-identified muscle loss in diagnosing malnutrition and predicting in-hospital complications (IHC) and prolonged length of hospital stay (PLOS) in elderly inpatients using machine learning methods.

METHODS

A sample of 7122 elderly inpatients who were enrolled in a previous multicenter cohort study in China were screened for eligibility for the current study and were then retrospectively diagnosed for malnutrition using 33 GLIM criteria that differ in their combinations of phenotypic and etiological criteria, in which CC or CC+HGS were used to identify muscle mass reduction. The diagnostic consistency with the subjective global assessment (SGA) criteria at admission was evaluated according to Kappa coefficients. The association and the predictive value of the GLIM-defined malnutrition with 30-day IHC and PLOS were evaluated with logistic regression and randomized forest models.

RESULTS

In total, 2526 inpatients (average age 74.63 ± 7.12 years) were enrolled in the current study. The prevalence of malnutrition identified by the 33 criteria combinations ranged from 3.3% to 27.2%. The main IHCs was infectious complications (2.5%). The Kappa coefficients ranged from 0.130 to 0.866. Logistic regression revealed that malnutrition was identified by 31 GLIM criteria combinations that were significantly associated with 30-day IHC, and 22 were significantly associated with PLOS. Random forest prediction revealed that GLIM 15 (unconscious weight loss + muscle mass reduction, combined with disease burden/inflammation) performs best in predicting IHC; GLIM 30 (unconscious weight loss + muscle mass reduction + BMI reduction, combined with disease burden/inflammation) performs best in predicting PLOS. Importantly, CC alone performs better than CC+HGS in the criteria combinations for predicting adverse clinical outcomes.

CONCLUSION

Muscle mass reduction defined by a reduced CC performs well in the GLIM criteria combinations for diagnosing malnutrition and predicting IHC and PLOS in elderly Asian inpatients. The applicability of other anthropometric parameters in these applications needs to be further explored.

Machine learning models to predict outcomes at 30-days using Global Leadership Initiative on Malnutrition combinations with and without muscle mass in people with cancer

BACKGROUND

Equipment to assess muscle mass is not available in all health services. Yet we have limited understanding of whether applying the Global Leadership Initiative on Malnutrition (GLIM) criteria without an assessment of muscle mass affects the ability to predict adverse outcomes. This study used machine learning to determine which combinations of GLIM phenotypic and etiologic criteria are most important for the prediction of 30-day mortality and unplanned admission using combinations including and excluding low muscle mass.

METHODS

In a cohort of 2801 participants from two cancer malnutrition point prevalence studies, we applied the GLIM criteria with and without muscle mass. Phenotypic criteria were assessed using ≥5% unintentional weight loss, body mass index, subjective assessment of muscle stores from the PG-SGA. Aetiologic criteria included self-reported reduced food intake and inflammation (metastatic disease). Machine learning approaches were applied to predict 30-day mortality and unplanned admission using models with and without muscle mass.

RESULTS

Participants with missing data were excluded, leaving 2494 for analysis [49.6% male, mean (SD) age: 62.3 (14.2) years]. Malnutrition prevalence was 19.5% and 17.5% when muscle mass was included and excluded, respectively. However, 48 (10%) of malnourished participants were missed if muscle mass was excluded. For the nine GLIM combinations that excluded low muscle mass the most important combinations to predict mortality were (1) weight loss and inflammation and (2) weight loss and reduced food intake. Machine learning metrics were similar in models excluding or including muscle mass to predict mortality (average accuracy: 84% vs. 88%; average sensitivity: 41% vs. 38%; average specificity: 85% vs. 89%). Weight loss and reduced food intake was the most important combination to predict unplanned hospital admission. Machine learning metrics were almost identical in models excluding or including muscle mass to predict unplanned hospital admission, with small differences observed only if reported to one decimal place (average accuracy: 77% vs. 77%; average sensitivity: 29% vs. 29%; average specificity: 84% vs. 84%).

CONCLUSIONS

Our results indicate predictive ability is maintained, although the ability to identify all malnourished patients is compromised, when muscle mass is excluded from the GLIM diagnosis. This has important implications for assessment in health services where equipment to assess muscle mass is not available. Our findings support the robustness of the GLIM approach and an ability to apply some flexibility in excluding certain phenotypic or aetiologic components if necessary, although some cases will be missed.

Validity of the Global Leadership Initiative on Malnutrition criteria using calf circumference in the prediction of in-hospital mortality in older surgical patients: A secondary analysis of a cohort study

BACKGROUND

Malnutrition is a prevalent condition among older patients and is associated with worse clinical outcomes. Methods such as the Subjective Global Assessment (SGA), the Mini Nutritional Assessment Long Form (MNA-LF), and the Global Leadership Initiative on Malnutrition (GLIM) diagnose malnutrition early. This study aimed to evaluate the performance and validity of these instruments to predict the length of hospital stay (LOS) and in-hospital mortality in older surgical patients.

METHODS

This prospective cohort study was performed in hospitalized older surgical patients. In the first 48 h of admission, general data were collected, and patients were evaluated by SGA, MNA-LF, and GLIM using calf circumference (CC) and mid-upper arm circumference (MUAC) as phenotypic criteria for nutrition diagnoses. Accuracy tests and regression analysis adjusted for sex, type of surgery, and the Charlson Comorbidity Index adjusted for age were performed to assess the criterion validity of instruments to predict LOS and mortality.

RESULTS

A total of 214 patients (age 75.4 ± 6.6 years, 57.3% men, and 71.1% admitted to elective surgery) were evaluated. Malnutrition was diagnosed in 39.7% (SGA), 63% (MNA-LF), 41.6% (GLIMCC ), and 32.1% (GLIMMUAC ) of patients. GLIMCC had the best accuracy (AUC = 0.70; 95% CI, 0.63-0.79) and sensitivity (95.8%) to predict in-hospital mortality. In the adjusted analysis, malnutrition, according to SGA, MNA-LF, and GLIMCC , increased the risk of in-hospital mortality by 3.12 (95% CI, 1.08-11.34), 4.51 (95% CI, 1.29-17.61), and 4.83 (95% CI, 1.52-15.22), respectively.

CONCLUSION

GLIMCC had the best performance and satisfactory criterion validity to predict in-hospital mortality in older surgical patients.

Evaluation of Nutritional Status and the Impact of Nutritional Treatment in Patients with Pancreatic Cancer

Patients with pancreatic cancer who develop irreversible cancer cachexia have a life expectancy of less than 3 months. Therefore, it is extremely important to evaluate the patient's nutritional status as early as possible and to implement an appropriate nutritional intervention in order to reduce the risk of further weight loss and/or muscle loss, which affect the outcomes of cancer treatment and the correct nutritional treatment in patients with pancreatic cancer. A literature review was performed by using the PubMed and Cochrane quick search methodology. The main purpose of this review was to present the current approach to nutritional treatment in pancreatic cancer. The review included publications, most of which concerned clinical nutrition as part of the phase of treatment of patients with pancreatic cancer, nutritional and metabolic disorders in pancreatic cancer, and the period after pancreatic resection. Some of the publications concerned various nutritional interventions in patients with pancreatic cancer undergoing chemotherapy or surgical treatment (nutritional support before surgery, after surgery, or during palliative treatment). There is an unmet need for integrated nutritional therapy as a key part of the comprehensive care process for PC patients. Nutritional counseling is the first line of nutritional treatment for malnourished cancer patients, but pancreatic enzyme replacement therapy also constitutes the cornerstone of nutritional treatment for relieving symptoms of indigestion and maintaining or improving nutritional status.

Association between Malnutrition Assessed by the Global Leadership Initiative on Malnutrition Criteria and Mortality in Older People: A Scoping Review

The Global Leadership Initiative on Malnutrition (GLIM) criteria were introduced in 2018 for the diagnosis of malnutrition in adults. This review was aimed at gathering the evidence about the association between malnutrition according to the GLIM criteria and mortality in older people, an emerging and clinically meaningful topic in the implementation of the GLIM criteria in geriatric healthcare settings. This scoping review considered meta-analyses, systematic reviews, cohort studies, and cross-sectional studies published in PubMed, Scopus, and the Cochrane Database for Systematic Reviews from the development of the GLIM criteria in 2018 to January 2023. Seventeen articles (15 cohort and 2 cross-sectional studies) were included. The association between GLIM criteria and mortality had been assessed in hospitalized (11 over the 17 articles) and community-dwelling older populations, and those in nursing homes. The review found a strong association between malnutrition according to GLIM criteria and mortality in hospitalized (1.2-fold to 7-fold higher mortality) and community-dwelling older people (1.6-fold to 4-fold higher mortality). These findings highlight the prognostic value of the GLIM criteria and support strategies towards the implementation of malnutrition evaluation according to the GLIM, in order to optimize comprehensive geriatric assessment and provide older people with the highest quality of nutritional care. Studies in nursing home populations were very scarce and may be urgently required.

Comparison of nutritional risk screening with NRS2002 and the GLIM diagnostic criteria for malnutrition in hospitalized patients

Nutritional risk screening, to identify patients at risk of malnutrition, is the first step in the prevention and treatment of malnutrition in hospitalized patients, and should be followed by a thorough nutritional assessment resulting in a diagnosis of malnutrition and subsequent treatment. In 2019, a consensus on criteria has been suggested for the diagnosis of malnutrition by the Global Leadership Initiative for Malnutrition (GLIM). This study investigates the diagnosis of malnutrition in hospitalized patients using nutritional risk screening and the diagnostic assessment suggested by GLIM. Hospitalized patients (excluding cancer, intensive care, and transmissible infections) who underwent nutritional risk screening (by NRS2002) were included. Nutritional risk screening was followed by anthropometric measurements including measurement of muscle mass, assessment of dietary intake and measurement of serum C-reactive protein (CRP) for inflammation in all patients. Malnutrition was diagnosed according to the GLIM-criteria. In total, 328 patients (median age 71 years, 47% women, median length of stay 7 days) were included. Nutritional risk screening identified 143 patients as at risk of malnutrition, while GLIM criteria led to a diagnosis of malnutrition in 114 patients. Of these 114 patients, 77 were also identified as at risk of malnutrition by NRS2002, while 37 patients were not identified by NRS2002. Malnutrition was evident in fewer patients than at risk of malnutrition, as expected. However, a number of patients were malnourished who were not identified by the screening procedure. More studies should investigate the importance of inflammation and reduced muscle mass, which is the main difference between nutritional risk screening and GLIM diagnostic assessment.

Orthostatic hypotension is associated with malnutrition diagnosed by GLIM in elderly hypertensive patients

Background

Orthostatic Hypotension (OH) and malnutrition, are common health problems in elderly hypertensive patients. This study aimed to analyze the relationship between malnutrition and OH in elderly hypertensive patients.

Methods

This is a cross-sectional single-center study. All participants underwent a Comprehensive Geriatric Assessment (CGA), in which malnutrition was defined according to the Global Leadership Initiative on Malnutrition (GLIM) criteria based on four different methods of diagnosing muscle mass loss. Furthermore, the accuracy of these methods was verified by Receiver Operating Characteristic (ROC) analysis. Univariate and multivariate logistic regression analyses were used to identify risk factors for OH in elderly hypertensive patients.

Results

For GLIM criteria, when Fat-Free Mass Index (FFMI) was the gold standard for muscle mass loss, the Area Under ROC Curve (AUC) values for Upper Arm Circumference (UAC), Calf Circumference (CC), and Hand Grip Strength (HGS) were 0.784, 0.805, and 0.832, with moderate accuracy in diagnosing malnutrition. Multivariate analysis showed that females, Diabetes Mellitus (DM), diuretics, and malnutrition diagnosed by GLIM-UAC were risk factors for OH in elderly hypertensive patients.

Conclusion

Prompt detection of malnutrition in the elderly and attention to changes in UAC may be critical. Similarly, we should strengthen medication and disease management in elderly hypertensive patients.

Malnutrition via GLIM Criteria in General Surgery Patients

Purpose: The purposes are to determine malnutrition in elective general surgery patients via GLIM criteria, compare GLIM criteria with NRS2002 and to determine the effect of malnutrition on Length of Stay (LoS). Materials and Methods: Malnutrition was detected with NRS2002 and GLIM. GLIM was evaluated in two different ways as 1-NRS2002 (first four questions) was used as a preliminary malnutrition screening tool for GLIM and 2-All patients were evaluated with GLIM without a preliminary assessment. Reduced muscle mass in GLIM, was assessed using different anthropometric measurements and cut-off points. In total, 10 different GLIM models were constituted. Data were collected within 48 hours of admission. Agreement between malnutrition tools was determined via Kappa. Logistic regression models were established to present the effect of malnutrition on long LoS. p

Prevalence of Malnutrition Assessed by the GLIM Criteria and Association with Activities of Daily Living in Older Residents in an Integrated Facility for Medical and Long-Term Care

Malnutrition is associated with poor functional outcomes in residents in long-term care facilities. The integrated facility for medical and long-term care (IFMLC) is a new Japanese long-term care facility where medical services can be provided. This study aimed to investigate the prevalence of malnutrition diagnosed based on the Global Leadership Initiative on Malnutrition (GLIM) criteria and its association with activities of daily living (ADL) in older residents in IFMLC. In this cross-sectional study of older residents, we diagnosed mild and severe malnutrition using the GLIM criteria and assessed ADLs using the Barthel index (BI). Multivariate regression analysis was used to investigate the relationship between BI score and GLIM-defined malnutrition. A total of 117 older residents (84 women; median age, 88 years) were analyzed in this study. The prevalence values of mild and severe malnutrition were 29% and 18%, respectively. Multivariate analyses for the BI score after adjusting for potential confounders showed that mild and severe malnutrition were independently associated with BI score (B = −6.113, p < 0.046; B = −8.411, p = 0.015, respectively). GLIM-defined malnutrition is negatively associated with ADLs in older residents in IFMLC.

Development and Validation of Cutoff Value for Reduced Muscle Mass for GLIM Criteria in Patients with Gastrointestinal and Hepatobiliary-Pancreatic Cancers

The Global Leadership Initiative on Malnutrition (GLIM) criteria recommends using race- and sex-adjusted cutoff values for reduced muscle mass (RMM), but the only cutoff values available for Asians are the skeletal muscle mass index (SMI) established by the Asian Working Group for Sarcopenia (AWGS). This retrospective study aimed to develop and validate cutoff values for the fat-free mass index (FFMI) and arm circumference (AC) of Asians, and to investigate the association between GLIM malnutrition and prognosis. A total of 660 patients with primary gastrointestinal (GI) and hepatobiliary–pancreatic (HBP) cancers who underwent their first resection surgery were recruited and randomly divided into development and validation groups. The FFMI and AC cutoff values were calculated by receiver operating characteristic curve analysis for the AWGS SMI as the gold standard. The cutoff values for each RMM were used to diagnose malnutrition on the basis of GLIM criteria, and the survival rates were compared. The optimal FFMI cutoff values for RMM were 17 kg/m² for men and 15 kg/m² for women, and for AC were 27 cm for men and 25 cm for women. In the validation group, the accuracy of the FFMI and AC cutoff values to discriminate RMM were 85.2% and 68.8%, respectively. Using any of the three measures of RMM, overall survival rates were significantly lower in the GLIM malnutrition group. In conclusion, the cutoff values for the FFMI and AC in this study could discriminate RMM, and GLIM malnutrition using these cutoff values was associated with decreased survival.

Calf Circumference and All-Cause Mortality: A Systematic Review and Meta-Analysis Based on Trend Estimation Approaches

OBJECTIVES

To perform a systematic review and meta-analysis and quantify the associations of total mortality with calf circumference (CC) in adults 18 years and older via combining various analyses based on empirical dichotomic CC, continuous CC, and dose-response CC.

METHODS

We conducted a systematic search of relevant studies in PubMed, EMBASE, Cochrane Library, and Web of Science published through April 12, 2022. This systematic review includes longitudinal observational studies reporting the relationships of total mortality with CC. We calculated the pooled relative risk (RR) and 95% confidence interval (CI) of total mortality with CC per 1 cm for each study and combined the values using standard meta-analysis approaches. Newcastle-Ottawa scale (NOS), Grading of Recommendations, Assessment, Development and Evaluations approach (GRADE), and the Instrument for assessing the Credibility of Effect Modification Analyses (ICEMAN) were assessed for meta-analyses.

RESULTS

Our analysis included a total of 37 cohort studies involving 62,736 participants, across which moderate heterogeneity was observed (I2=75.7%, P<0.001), but no publication bias was found. Study quality scores ranged from 6 to 9 (mean 7.7), with only three studies awarded a score of 6 (fair quality). We observed an inverse trend between total death risk and CC per 1 cm increase (RR, 0.95, 95% CI, 0.94-0.96; P<0.001; GRADE quality=high). Only a very slight difference was found among residents of nursing homes (6.9% mortality risk reduction per one cm CC increase), community-dwellers (5.4%), and those living in hospitals (4.8%), respectively (P for meta-regression=0.617). Low credible subgroup difference was found based on the ICEMAN tool.

CONCLUSIONS

Calf circumference is a valid anthropometric measure for mortality risk prediction in a community, nursing home, or hospital.

Intrinsic Capacity Defined Using Four Domains and Mortality Risk: A 5-Year Follow-Up of the SarcoPhAge Cohort

OBJECTIVES

The concept of 'intrinsic capacity' (IC) offers a new way to approach another concept, that of 'healthy aging'. The first objective of the present study was to assess the ability of the construct of 'intrinsic capacity' to predict death. The second objective was to assess whether deteriorations in intrinsic capacity, measured over 1 and 2 years, are predictive of death.

DESIGN

The present analysis was based on a prospective cohort study.

SETTING

Community-dwelling participants.

PARTICIPANTS

The study recruited older adults aged 65 years and older.

MEASUREMENTS

Intrinsic capacity (IC) encompasses five domains: sensorial (not evaluated here), cognition (Mini-Mental State Examination), nutrition (Mini-Nutritional Assessment), mobility (Short Physical Performance Battery), and psychological (Geriatric Depression Scale). Each domain was considered satisfactory when its assessment, for an individual, was above the threshold defined by the initial validation of the domain assessment tool. To explore the relationship between IC and mortality risk, a Cox model was applied. The predictive value of the dynamic aspects (i.e., changes over 1 year and 2 years) was investigated using the following categorization of IC: stable, deteriorated, improved.

RESULTS

The sample was composed of 481 volunteers aged 73.4±6.12 years (60.1% women). Two satisfactory IC domains appeared to be significantly associated with reduced mortality risk: the satisfactory mobility domain (adjusted HR=0.45 [0.26-0.79]) and the satisfactory psychological domain (adjusted HR = 0.56 [1.04-3.09]). When considering intrinsic capacity as a whole construct, using a composite Z-score, we noticed that the risk of death was decreased by 49% for an increase of 1 standard deviation in IC. Changes in intrinsic capacity in the mobility and psychological domains led to an increased risk of death (from 2.74 to 4.18-fold).

CONCLUSION

The concept of intrinsic capacity seems highly relevant in order to assess older adults' health and well-being. This concept should be considered for integration into clinical practice.

Comparison of the GLIM, ESPEN and ICD-10 Criteria to Diagnose Malnutrition and Predict 30-Day Outcomes: An Observational Study in an Oncology Population

The Global Leadership Initiative on Malnutrition (GLIM) criteria are consensus criteria for the diagnosis of malnutrition. This study aimed to investigate and compare the prevalence of malnutrition using the GLIM, European Society for Clinical Nutrition and Metabolism (ESPEN) and International Statistical Classification of Diseases version 10 (ICD-10) criteria; compare the level of agreement between these criteria; and identify the predictive validity of each set of criteria with respect to 30-day outcomes in a large cancer cohort. GLIM, ESPEN and ICD-10 were applied to determine the prevalence of malnutrition in 2794 participants from two cancer malnutrition point prevalence studies. Agreement between the criteria was analysed using the Cohen’s Kappa statistic. Binary logistic regression models were used to determine the ability of each set of criteria to predict 30-day mortality and unplanned admission or readmission. GLIM, ESPEN and ICD-10 criteria identified 23.0%, 5.5% and 12.6% of the cohort as malnourished, respectively. Slight-to-fair agreement was reported between the criteria. All three criteria were predictive of mortality, but only the GLIM and ICD-10 criteria were predictive of unplanned admission or readmission at 30 days. The GLIM criteria identified the highest prevalence of malnutrition and had the greatest predictive ability for mortality and unplanned admission or readmission in an oncology population.

Sarcopenia, Malnutrition, and Cachexia: Adapting Definitions and Terminology of Nutritional Disorders in Older People with Cancer

The recent publication of the revised Consensus on definition and diagnosis of sarcopenia (EWGSOP2) and the Global Leadership Initiative on Malnutrition (GLIM) criteria changed the approach to research on sarcopenia and malnutrition. Whilst sarcopenia is a nutrition-related disease, malnutrition and cachexia are nutritional disorders sharing the common feature of low fat-free mass. However, they have differential characteristics and etiologies, as well as specific therapeutic approaches. Applying the current definitions in clinical practice is still a challenge for health professionals and the potential for misdiagnosis is high. This is of special concern in the subgroup of older people with cancer, in which sarcopenia, malnutrition, and cancer cachexia are highly prevalent and can overlap or occur separately. The purpose of this review is to provide an updated overview of the latest research and consensus definitions of sarcopenia, malnutrition, and cachexia and to discuss their implications for clinical practice in older patients with cancer. The overall aim is to improve the quality of nutritional care in light of the latest findings.