The potential threshold for dietary energy intake (DEI) that might prevent protein-energy wasting (PEW) in chronic kidney disease (CKD) is uncertain. The subjects were non-dialysis CKD patients aged ≥ 14 years who were hospitalised from September 2019 to July 2022. PEW was measured by subjective global assessment. DEI and dietary protein intake (DPI) were obtained by 3-d diet recalls. Patients were divided into adequate DEI group and inadequate DEI group according to DEI ≥ 30 or < 30 kcal/kg/d. Logistic regression analysis and restricted cubic spline were used in this study. We enrolled 409 patients, with 53·8 % had hypertension and 18·6 % had diabetes. The DEI and DPI were 27·63 (sd 5·79) kcal/kg/d and 1·00 (0·90, 1·20) g/kg/d, respectively. 69·2 % of participants are in the inadequate DEI group. Malnutrition occurred in 18·6 % of patients. Comparing with patients in the adequate DEI group, those in the inadequate DEI group had significantly lower total lymphocyte count, serum cholesterol and LDL-cholesterol and a higher prevalence of PEW. For every 1 kcal/kg/d increase in DEI, the incidence of PEW was reduced by 12·0 % (OR: 0·880, 95 % CI: 0·830, 0·933, P < 0·001). There was a nonlinear curve relationship between DEI and PEW (overall P < 0·001), and DEI ≥ 27·6 kcal/kg/d may have a preventive effect on PEW in CKD. Low DPI was also significantly associated with malnutrition, but not when DEI was adequate. Decreased energy intake may be a more important factor of PEW in CKD than protein intake.

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.

In this study, we aimed to examine the relationship between energy-adjusted dietary inflammatory index (E-DII) and a comprehensive profile of malnutrition in Iranian haemodialysis (HD) patients. In this cross-sectional study, 291 participants on HD for at least 6 months before enrollment were included. The current dietary intakes of participants were assessed using a 4-d diet diary-assisted recall, including 2 non-dialysis days and 2 dialysis days to calculate E-DII. To determine the malnutrition status of HD patients, BMI, subjective global assessment (SGA), dialysis malnutrition score (DMS) and malnutrition inflammation score (MIS) were used. Overall, 291 HD patients comprised our study population. After controlling for potential confounders, E-DII was associated with a higher risk of malnutrition, as evidenced by SGA (OR = 2·23; 95 % CI: 1·11, 4·49), DMS (OR = 2·31; 95 % CI: 1·16, 4·60) and MIS (OR = 2·50; 95 % CI: 1·28, 4·88). No significant association was detected between E-DII and BMI either before (OR = 1·78; 95 % CI: 0·83, 3·81) or after adjustment for possible confounders (OR = 1·43; 95 % CI: 0·58, 3·54). This study showed that E-DII was significantly associated with reliable malnutrition markers including SGA, DMS and MIS in HD patients. However, further longitudinal studies are warranted to infer a cause-and-effect relationship between DII and malnutrition.

Identifying nutritional deficits and implementing appropriate interventions in patients requiring vascular surgery is challenging due to the paucity of appropriate screening and assessment tools in this group. This retrospective study aimed to determine the validity of the Global Leadership Initiative on Malnutrition (GLIM) in identifying protein–energy malnutrition (PEM) in inpatients admitted to a vascular surgery unit, using the PG-SGA as the comparator. Diagnostic accuracy and consistency were determined between the GLIM and the Patient-Generated Subjective Global Assessment (PG-SGA) global rating. The GLIM determination was made retrospectively using the relevant parameters collected at baseline in the original study. Two hundred and twenty-four (70·1 % male) participants were included. The prevalence of PEM was 28·6 % on GLIM and 17 % via the PG-SGA. Compared with the PG-SGA, the GLIM achieved sensitivity of 73·7 % and specificity of 80·6 %; however positive predictive value was 43·7 % indicating that the GLIM over-diagnosed malnutrition compared with the PG-SGA. Kappa reached 0·427 indicating moderate diagnostic consistency. Due to the absence of an ideal instrument and the complexity of malnutrition often seen in this group which extends beyond PEM to significant micronutrient deficiencies, further work is required to determine the most appropriate instrument in this patient group, and how micronutrient status can also be included in the overall assessment given the critical role of micronutrients in this group.

We aimed to investigate the relationship between the neutrophil to lymphocyte ratio (NLR) and nutritional parameters in chronic kidney disease (CKD) patients. In this cross-sectional study, 187 non-dialysis CKD patients were enrolled. Daily dietary energy intake (DEI) and daily dietary protein intake (DPI) were assessed by 3-d dietary records. Protein-energy wasting (PEW) was defined as Subjective Global Assessment (SGA) class B and C. Spearman correlation analysis, logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed. The median NLR was 2·51 (1·83, 3·83). Patients with CKD stage 5 had the highest NLR level. A total of 19·3 % (n 36) of patients suffered from PEW. The NLR was positively correlated with SGA and serum P, and the NLR was negatively correlated with BMI, waist and hip circumference, triceps skinfold thickness, mid-arm muscle circumference, DPI and Hb. Multivariate logistic regression analysis adjusted for DPI, DEI, serum creatinine, blood urea nitrogen, uric acid and Hb showed that a high NLR was an independent risk factor for PEW (OR = 1·393, 95 % CI 1·078, 1·800, P = 0·011). ROC analysis showed that an NLR ≥ 2·62 had the ability to identify PEW among CKD patients, with a sensitivity of 77·8 %, a specificity of 62·3 % and an AUC of 0·71 (95 % CI 0·63, 0·81, P < 0·001). The NLR was closely associated with nutritional status. NLR may be an indicator of PEW in CKD patients.

The prevalence of malnutrition is high among oncology patients in Northern China. Malnutrition is related to the longer hospital stay, and it can be used to predict the prognostic outcome of patients. This work focused on investigating the relationship of nutritional condition with the length of hospital stay (LOS) in Northern Chinese patients with lung adenocarcinoma (LUAD). The Patient-Generated Subjective Global Assessment (PG-SGA), Nutritional Risk Screening 2002 (NRS 2002) score, recent weight loss and BMI were assessed in a probabilistic sample of 389 LUAD patients without epidermal growth factor receptor (EGFR) mutations. This study collected the demographic and clinical features of patients in a prospective manner. Then, we examined the association of nutritional status with LOS among the population developing LUAD. According to the PG-SGA, 63 (16·3 %), 174 (44·7 %) and 78 (20·1 %) patients were at risk for undernutrition, moderate undernutrition and severe undernutrition, respectively. Nutritional risk was found in 141 (36·2 %) patients based on the NRS 2002. The average LOS for tumour patients in Northern China was 12·5 d. At admission, a risk of undernutrition or undernutrition according to the PG-SGA (P < 0·001), NRS 2002 (P < 0·001) and latest weight loss (P < 0·001) predicted the longer LOS. LOS was related to nutritional status and hospitalisation expenses (P < 0·001). LUAD patients who stayed in the ICU had a poorer nutritional status and a longer LOS (P < 0·001). In Northern Chinese patients with LUAD, a risk for undernutrition evaluated by the PG-SGA, the NRS 2002 and recent weight loss, but not BMI, could predict a longer LOS.

Health-related quality of life (HRQoL) is severely impaired in persons receiving dialysis. Malnutrition has been associated with some measures of poor HRQoL in cross-sectional analyses in dialysis populations, but no studies have assessed the impact of malnutrition and dietary intake on change in multiple measures of HRQoL over time. We investigated the most important determinants of poor HRQoL and the predictors of change in HRQoL over time using several measures of HRQoL. We enrolled 119 haemodialysis and thirty-one peritoneal dialysis patients in this prospective study. Nutritional assessments (Subjective Global Assessment (SGA), anthropometry and 24-h dietary recalls) and HRQoL questionnaires (Short Form-36 (SF-36) mental (MCS) and physical component scores (PCS) and European QoL-5 Dimensions (EQ5D) health state (HSS) and visual analogue scores (VAS)) were performed at baseline, 6 and 12 months. Mean age was 64 (14) years. Malnutrition was present in 37 % of the population. At baseline, malnutrition assessed by SGA was the only factor independently (and negatively) associated with all four measures of HRQoL. No single factor was independently associated with decrease in all measures of HRQoL over 1 year. However, prevalence/development of malnutrition over 1 year was an independent predictor of 1-year decrease in EQ5D HSS, and 1-year decrease in fat intake independently predicted the 1-year decline in SF-36 MCS and PCS, and EQ5D VAS. These findings strengthen the importance of monitoring for malnutrition and providing nutritional advice to all persons on dialysis. Future studies are needed to evaluate the impact of nutritional interventions on HRQoL and other long-term outcomes.

Nutritional status (NS) monitoring is an essential step of the nutrition care process. To assess changes in NS throughout hospitalisation and its ability to predict clinical outcomes, a prospective cohort study with patients over 18 years of age was conducted. The Subjective Global Assessment (SGA) was performed within 48 h of admission and 7 d later. For each patient, decline in NS was assessed by two different methods: changes in SGA category and severe weight loss alone (≥2 % during the first week of hospitalisation). Patients were followed up until discharge to assess length of hospital stay (LOS) and in-hospital mortality and contacted 6 months post-discharge to assess hospital readmission and death. Out of the 601 patients assessed at admission, 299 remained hospitalised for at least 7 d; of those, 16·1 % had a decline in SGA category and 22·8 % had severe weight loss alone. In multivariable analysis, decline in SGA category was associated with 2-fold (95 % CI 1·06, 4·21) increased odds of prolonged LOS and 3·6 (95 % CI 1·05, 12·26) increased odds of hospital readmission at 6 months. Severe weight loss alone was associated with 2·5-increased odds (95 % CI 1·40, 4·64) of prolonged LOS. In conclusion, deterioration of NS was more often identified by severe weight loss than by decline in SGA category. While both methods were associated with prolonged LOS, only changes in the SGA predicted hospital readmission. These findings reinforce the importance of nutritional monitoring and provide guidance for further research to prevent short-term NS deterioration from being left undetected.

Malnutrition risk screening in cirrhotic patients is crucial, as poor nutritional status negatively affects disease prognosis and survival. Given that a variety of malnutrition screening tools is usually used in routine clinical practice, the effectiveness of eight screening tools in detecting malnutrition risk in cirrhotic patients was sought. A total of 170 patients (57·1 % male, 59·4 (sd 10·5) years, 50·6 % decompensated ones) with cirrhosis of various aetiologies were enrolled. Nutritional screening was performed using the Malnutrition Universal Screening Tool, Nutritional Risk Index, Malnutrition Screening Tool, Nutritional Risk Screening (NRS-2002), Birmingham Nutritional Risk Score, Short Nutritional Assessment Questionnaire, Royal Free Hospital Nutritional Prioritizing Tool (RFH-NPT) and Liver Disease Undernutrition Screening Tool (LDUST). Malnutrition diagnosis was defined using the Subjective Global Assessment (SGA). Data on 1-year survival were available for 145 patients. The prevalence of malnutrition risk varied according to the screening tools used, with a range of 13·5–54·1 %. RFH-NPT and LDUST were the most accurate in detecting malnutrition (AUC = 0·885 and 0·892, respectively) with a high sensitivity (97·4 and 94·9 %, respectively) and fair specificity (73·3 and 58 %, respectively). Malnutrition according to SGA was an independent prognostic factor of within 1-year mortality (relative risk was 2·17 (95 % CI 1·0, 4·7), P = 0·049) after adjustment for sex, age, disease aetiology and Model for End-stage Liver Disease score, whereas nutrition risk according to RFH-NPT, LDUST and NRS-2002 showed no association. RFH-NPT and LDUST were the only screening tools that proved to be accurate in detecting malnutrition in cirrhotic patients.

Malnutrition is a frequent feature in Crohn’s disease (CD), affects patient outcome and must be recognised. For chronic inflammatory diseases, recent guidelines recommend the development of combined malnutrition and inflammation risk scores. We aimed to design and evaluate a new screening tool that combines both malnutrition and inflammation parameters that might help predict clinical outcome. In a prospective cohort study, we examined fifty-five patients with CD in remission (Crohn’s disease activity index (CDAI) <200) at 0 and 6 months. We assessed disease activity (CDAI, Harvey–Bradshaw index), inflammation (C-reactive protein (CRP), faecal calprotectin (FC)), malnutrition (BMI, subjective global assessment (SGA), serum albumin, handgrip strength), body composition (bioelectrical impedance analysis) and administered the newly developed ‘Malnutrition Inflammation Risk Tool’ (MIRT; containing BMI, unintentional weight loss over 3 months and CRP). All parameters were evaluated regarding their ability to predict disease outcome prospectively at 6 months. At baseline, more than one-third of patients showed elevated inflammatory markers despite clinical remission (36·4 % CRP ≥5 mg/l, 41·5 % FC ≥100 µg/g). Prevalence of malnutrition at baseline according to BMI, SGA and serum albumin was 2–16 %. At 6 months, MIRT significantly predicted outcome in numerous nutritional and clinical parameters (SGA, CD-related flares, hospitalisations and surgeries). In contrast, SGA, handgrip strength, BMI, albumin and body composition had no influence on the clinical course. The newly developed MIRT was found to reliably predict clinical outcome in CD patients. This screening tool might be used to facilitate clinical decision making, including treatment of both inflammation and malnutrition in order to prevent complications.

Despite the significant impact of malnutrition in hospitalised patients, it is often not identified by clinical staff in daily practice. To improve nutritional support in hospitals, standardised routine nutritional screening is essential. The Graz Malnutrition Screening (GMS) tool was developed for the purpose of malnutrition risk screening in a large hospital setting involving different departments. It was the aim of the present study to validate the GMS against Nutritional Risk Screening (NRS) and Mini Nutritional Assessment-short form (MNA-sf) in a randomised blinded manner. A total of 404 randomly selected patients admitted to the internal, surgical and orthopaedic wards of the University Hospital Graz were screened in a blinded manner by different raters. Concurrent validity was determined by comparing the GMS with the NRS and in older patients (70+ years) with the MNA-sf additionally. According to GMS, 31·9 or 28·5 % of the admitted patients were categorised as at ‘risk of malnutrition’ (depending on the rater). According to the reference standard of NRS, 24·5 % of the patients suffered from malnutrition. Pearson’s r values of 0·78 compared with the NRS and 0·84 compared with the MNA showed strong positive correlations. Results of accuracy (0·85), sensitivity (0·94), specificity (0·77), positive predictive value (0·76) and negative predictive value (0·95) of GMS were also very high. Cohen’s κ for internal consistency of the GMS was 0·82. GMS proves to be a valid and reliable instrument for the detection of malnutrition in adult patients in acute-care hospitals.

This prospective cohort study was conducted in eighteen Canadian hospitals with the aim of examining factors associated with nutritional decline in medical and surgical patients. Nutritional decline was defined based on subjective global assessment (SGA) performed at admission and discharge. Data were collected on demographics, medical information, food intake and patients’ satisfaction with nutrition care and meals during hospitalisation; 424 long-stay (≥7 d) patients were included; 38 % of them had surgery; 51 % were malnourished at admission (SGA B or C); 37 % had in-hospital changes in SGA; 19·6 % deteriorated (14·6 % from SGA A to B/C and 5 % from SGA B to C); 17·4 % improved (10·6 % from SGA B to A, 6·8 % from SGA C to B/A); and 63·0 % patients were stable (34·4 % were SGA A, 21·3 % SGA B, 7·3 % SGA C). One SGA C patient had weight loss ≥5 %, likely due to fluid loss and was designated as stable. A subset of 364 patients with admission SGA A and B was included in the multiple logistic regression models to determine factors associated with nutritional decline. After controlling for SGA at admission and the presence of a surgical procedure, lower admission BMI, cancer, two or more diagnostic categories, new in-hospital infection, reduced food intake, dissatisfaction with food quality and illness affecting food intake were factors significantly associated with nutritional decline in medical patients. For surgical patients, only male sex was associated with nutritional decline. Factors associated with nutritional decline are different in medical and surgical patients. Identifying these factors may assist nutritional care.

The calculation of body composition using bioelectrical impedance analysis in sick and hospitalized patients is hampered due to altered hydration state. We wanted to investigate how disease-related malnutrition assessed by the Subjective Global Assessment (SGA) is reflected in the bioelectrical impedance vector analysis. Patients with benign gastrointestinal disease (n 242) were entered in the study. Nutritional status was assessed by SGA. Arm muscle and fat area were estimated by anthropometry, muscle function was determined by hand grip strength. Whole body impedance measurements were made at 50 kHz. Ninety-eight patients were considered well nourished (SGA A), ninety-four were classified moderately malnourished (SGA B) and fifty patients were classified severely malnourished (SGA C) according to the SGA. The mean vector was significantly displaced between SGA C and SGA A and B, showing comparable resistance with a significantly reduced reactance, indicating comparable hydration but loss of dielectrical mass of soft tissues. This distinctive vector migration was not seen when studying the patients grouped according to BMI. In conclusion, disease-related malnutrition as assessed by the SGA is associated with a distinctive bioelectrical vector migration, implying that abnormal tissue structure and not reduced body mass only occurs in disease-related malnutrition. These disturbances are not seen in underweight according to BMI. Bioelectrical impedance vector analysis appears to be an attractive tool to identify disease-related malnutrition and to monitor nutritional intervention.