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OBJECTIVES: To determine the efficacy of the 3-Minute Nutrition Screening (3-MinNS) tool in adults hospitalized for cardiovascular diseases. METHODS: In this descriptive cross-sectional study of 759 cardiovascular disease patients in Erciyes University Cardiology Clinic, anthropometric measurements and some routine biochemical parameters were recorded, and nutrition screening tools were used to determine malnutrition status. The power of 3-MinNS to detect malnutrition in cardiovascular diseases patients was calculated. RESULTS: There was a strong positive correlation between 3-MinNS and Nutrition Risk Screening-2002 (NRS-2002) (r=0.719, p<0.001). A moderate agreement was found between 3-MinNS and NRS-2002 (κ=0.496, p<0.001). The sensitivity, specificity, and AUC of 3-MinNS were 79.1%, 75.0%, and 0.851, respectively, and it was determined to be a moderately effective nutrition screening tool that can be used to identify malnutrition in patients with cardiovascular diseases. CONCLUSION: The 3-MinNS is a moderately effective nutrition screening tool that can be administered within the first 24 hours of hospitalization in patients with cardiovascular diseases.

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BACKGROUND: Nutrition screening on admission is critically important to systematically identify patients with undernutrition given the known relationship with deleterious clinical outcomes. Limited data exist regarding optimal processes and criteria for pediatric nutrition screening. Therefore, we sought to characterize nutrition screening practices in pediatric hospitals. METHODS: A total of 365 inpatient pediatric hospitals in the United States were identified, eligible, and contacted. Eligible hospitals included general pediatric hospitals, adult hospitals with pediatric units, and specialty pediatric hospitals. One respondent at each eligible hospital was asked to complete a 33-question survey of admission nutrition screening practices. RESULTS: Of 268 survey respondents, 37% represented pediatric units in adult hospitals, 35% general pediatric hospitals, and 28% pediatric specialty or psychiatric hospitals. A total of 98.5% endorsed the existence of a screening process on admission. Anthropometrics (eg, body mass index z score, 84%) and nutrition status (eg, change in intake, 67%) were the most common screening criteria applied. A nutrition screening instrument was used in 37% of institutions, and only 31% of institutions reported using pediatric-specific screening instruments. Pediatric units within adult hospitals were 1.38 times more likely to use a screening instrument validated in any population. Barriers to nutrition screening included the lack of a standard screening procedure and insufficient staff to conduct screening. Fifty-four percent of respondents reported a desire to change their hospital's nutrition screening process. CONCLUSION: Most pediatric hospitals screen for nutrition risk on admission. However, methods and criteria varied widely across pediatric hospitals, highlighting the importance of standardized best practices.

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Individuals receiving hemodialysis are at increased risk of malnutrition; however, regular diagnosis of malnutrition using subjective global assessment (SGA) is time-consuming. This study aimed to determine whether the Canadian Nutrition Screening Tool (CNST) or the Geriatric Nutrition Risk Index (GNRI) screening tools could accurately identify hemodialysis patients at risk for malnutrition. A retrospective medical chart review was conducted for in-centre day shift hemodialysis patients (n = 95) to obtain the results of the SGA assessment and the CNST screener and to calculate the GNRI score. Sensitivity and specificity analyses showed only a fair agreement between the SGA and CNST (sensitivity = 20%; specificity 96%; κ = .210 (95% CI, -0.015 to .435), p < .05) and between the SGA and GNRI (sensitivity = 35%; specificity = 88%; κ = .248 (95% CI, .017 to .479), p < .05). There was no significant statistical difference between the accuracy of either tool in identifying patients at risk of malnutrition (p = .50). The CNST and GNRI do not accurately screen for risk of malnutrition in the hemodialysis population; therefore, further studies are needed to determine an effective malnutrition screening tool in this population.

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Objectives: To evaluate the under-nutrition risk of children admitted to hospitals using a validated tool. METHODS: The cross-sectional study was conducted from September 2017 to June 2018 in the paediatrics wards of a tertiary referral paediatric government hospital, a tertiary teaching hospital and a government district hospital in Malaysia. The sample comprised paediatric patients aged 2-12 years within 24-72 hours of hospital admission. Data was collected using the 3-Minute Nutrition Screening-Paediatrics tool. Data was analysed using SPSS 20. RESULTS: Of the 341 patients screened, 284(83.3%) were included; 170(59.9%) boys and 114(40.1%) girls. The overall median age was 4.85 years (interquartile range: 4.33 years). The median length of hospital stay was 3 days (interquartile range: 3 days). There were 72(25.4%) participants at high under-nutrition risk, with the highest proportion being at the district government hospital 31(33%). Among those with high risk, 5.4% subjects had severe acute malnutrition, 9.7% had severe chronic malnutrition, and 11.1% had severe thinness. Conclusion: The 3-Minute Nutrition Screening-Paediatrics scale was found to be effective as a nutrition screening tool for hospitalised children in Malaysia.

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BACKGROUND: Malnutrition is present in 20-50% of hospital patients but its recognition is often neither timely nor complete. The Global Leadership Initiative on Malnutrition (GLIM) aims to improve this, but its successful implementation may be compromised by its dependence on (a choice of) prior screening tools and difficulties in consistent assessment of muscle mass. AIMS: To explore different approaches to screening and muscle assessment in GLIM and to offer simpler choices for its more widespread application. METHODS: (1) Data from 300 consenting in-patients provided Nutritional Risk Screening (NRS-2002), Malnutrition Universal Screening Tool (MUST), and Subjective Global Assessment (SGA) scores. GLIM scoring was preceded by NRS-2002 or MUST (using threshold scores of 1 or 2 for MUST), or no prior screening. The results of GLIM scoring preceded by different screening approaches were compared with those of SGA. (2) The literature on mid-upper arm circumference (MUAC) and calf circumference (CC) as simple, non-invasive, objective methods of muscle assessment methods was reviewed (3) The cumulative times taken to obtain GLIM scores were measured and corrected for the different screening strategies. RESULTS: (1) Participants' mean age was 60 years, 157 (52%) were female and mean BMI was 27.8 kg/m2. In comparison with SGA, GLIM with no prior screening had the highest sensitivity (65%) and negative predictive value (NPV) (76%), but the lowest specificity (90%) and positive predictive value (PPV) (84%). The equivalent figures for GLIM with prior MUST "1" were 62%, 75%, 93% and 88%; with prior NRS-2002, 55%∗, 73%, 98%∗ and 95%∗; and with prior MUST "2", 44%∗, 69%∗, 98%∗, 95%∗. The area under an ROC curve was the highest (0.78) when GLIM was performed without screening or with prior MUST "1". (2) Being less affected by oedema and gender differences than calf circumference, MUAC could serve as a standard globally accessible muscle mass assessment method which can be supplemented by technical approaches if available and deemed necessary. (3) The overall per-capita time requirement of GLIM was 240-245 s without prior screening, and was increased by 2-3% with prior MUST "1", by 27-29% with prior NRS-2002 and decreased by 8-9% with prior MUST "2". CONCLUSIONS: Preceding GLIM by screening can decrease its sensitivity and increase overall time utilisation; "gold standard" muscle assessment is not globally accessible. Our results therefore support considering using GLIM as a combined screening and assessment tool, with MUAC as the method of muscle assessment which can be supplemented by technical approaches if available and deemed necessary. This could potentially both simplify the use of GLIM and improve the early detection of malnutrition. ∗Indicates statistically significant difference from use of GLIM without prior screening.

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The presence and impact of malnutrition in adult hospitalized patients has been well documented by a significant body of literature. However, current malnutrition care practices often vary widely and frequently lack standardization. The Global Malnutrition Composite Score (GMCS), the first nutrition-related electronic clinical quality measure, is intended to evaluate the quality of malnutrition care provided to inpatient adults. This measure aims to aid in standardizing malnutrition care through performance measurement. The four components of the measure (nutrition screening, nutrition assessment, malnutrition diagnosis, and nutrition care plans) follow the well-established Nutrition Care Process and encourage the use of standardized terminology. Facilities with high-performance scores on the GMCS are likely to experience improved outcomes associated with high-quality malnutrition care.

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AIMS AND OBJECTIVES: To assess the prevalence of malnutrition in hospitalised adult patients, and to evaluate the accuracy of the most commonly used nutritional screening tools for identifying individuals at risk of malnutrition. METHODS: A prospective cross-sectional study was conducted on a total of 248 hospitalised patients in internal medicine wards (mean age: 75.2 years; 39.5% females). Nutritional screening was performed within 48 h of admission using the following tools: Malnutrition Universal Screening Tool (MUST), Nutrition Risk Screening Tool (NRS-2002), Malnutrition Screening Tool (MST), Short Nutritional Assessment Questionnaire (SNAQ), and Mini Nutritional Assessment Short Form (MNA-SF). The criteria of the European Society for Clinical Nutrition and Metabolism (ESPEN) were used as the gold standard for defining malnutrition. Patients were also evaluated using the Subjective Global Assessment (SGA) and the Global Leadership Initiative on Malnutrition (GLIM) criteria. Accuracy was determined by examining sensitivity, specificity, and positive and negative predictive values, and diagnostic agreement was determined by calculation of Cohen's kappa (κ). The study is reported as per the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. RESULTS: The ESPEN criteria classified 20.2% of the hospitalised patients as malnourished. Overall, the MUST had the highest sensitivity (80.0%), specificity (74.7%) and positive predictive value (44.4%). For the subgroup of patients aged >65 years, the MNA-SF had high sensitivity (94.4%) but low specificity (39.0%). Based on Cohen's κ, the SGA and GLIM criteria showed low agreement with the ESPEN criteria. CONCLUSION: The MUST was the most accurate nutritional screening tool, through the MST is more easily applied in many clinical settings. A comprehensive assessment of malnutrition that considers muscle mass is crucial for the reliable diagnosis of malnutrition. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: The present findings underscore the importance of accurate assessment of the malnutrition status of hospitalised patients and the need for a reliable screening tool. No patient or public contribution.

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Malnutrition risk screening is crucial to identify at-risk patients in hospitals; however, screening rates can be suboptimal. This study evaluated the feasibility, acceptability, and potential cost-effectiveness of patient-led, technology-assisted malnutrition risk screening. A prospective multi-methods study was conducted in a 750-bed public hospital in Australia. Patients were recruited from seven wards and asked to complete an electronic version of the Malnutrition Screening Tool (e-MST) on bedside computer screens. Data were collected on feasibility, acceptability, and cost. Feasibility data were compared to pre-determined criteria on recruitment (≥50% recruitment rate) and e-MST completion (≥75% completion rate). Quantitative acceptability (survey) data were analyzed descriptively. Patient interview data were analyzed thematically. The economic evaluation was from the perspective of the health service using a decision tree analytic model. Both feasibility criteria were met; the recruitment rate was 78% and all 121 participants (52% male, median age 59 [IQR 48-69] years) completed the e-MST. Patient acceptability was high. Patient-led e-MST was modeled to save $3.23 AUD per patient and yield 6.5 more true malnutrition cases (per 121 patients) with an incremental cost saving per additional malnutrition case of 0.50 AUD. Patient-led, technology-assisted malnutrition risk screening was found to be feasible, acceptable to patients, and cost-effective (higher malnutrition yield and less costly) compared to current practice at this hospital.

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BACKGROUND: The emergency department (ED) is the most frequent access route to the hospital. Nutrition risk (NR) screening allows the early identification of patients at risk of malnutrition. This study aimed to evaluate the feasibility and predictive validity of five different tools in EDs: Nutritional Risk Screening 2002 (NRS-2002), Nutritional Risk Emergency 2017 (NRE-2017), Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT), Malnutrition Universal Screening (MUST), and Malnutrition Screening Tool (MST). METHODS: Patients with scores ≥3 according to the NRS-2002, ≥1.5 according to the NRE-2017, and ≥2 according to the MUST, RFH-NPT, or MST were classified with NR. Prolonged length of stay (LOS) and 1-year mortality were evaluated. RESULTS: 431 patients were evaluated (57.31 ± 15.6 years of age; 54.4% women) in a public hospital in southern Brazil. The prevalence of NR was: 35% according to the NRS-2002, 43% according to the MST, 45% according to the NRE-2017 and MUST, and 49% according to the RFH-NPT. Patients with NR, had a greater risk of prolonged LOS (P < 0.001). The presence of NR was associated with an increased risk of 1-year mortality according to the NRS-2002 (hazard ratio [HR]: 4.04; 95% CI, 2.513-6.503), MST (HR: 2.60; 95% CI, 1.701-3.996), NRE-2017 (HR: 4.82; 95% CI, 2.753-8.443), MUST (HR: 4.00; 95% CI, 2.385-6.710), and RFH-NPT (HR: 5.43; 95% CI, 2.984-9.907). CONCLUSIONS: NRE-2017 does not require objective data and presented predictive validity for all outcomes assessed, regardless of the severity of the disease, and thus appears to be the most appropriate tool for carrying out NR screening in the ED.

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Malnutrition is prevalent among surgical candidates and associated with adverse outcomes. Despite being potentially modifiable, malnutrition risk screening is not a standard preoperative practice. We conducted a cross-sectional survey to understand healthcare professionals' (HCPs) opinions and barriers regarding screening and treatment of malnutrition. HCPs working with adult surgical patients in Canada were invited to complete an online survey. Barriers to preoperative malnutrition screening were assessed using the Capability Opportunity Motivation-Behaviour model. Quantitative data were analyzed using descriptive statistics and qualitative data were analyzed using summative content analysis. Of the 225 HCPs surveyed (n = 111 dietitians, n = 72 physicians, n = 42 allied HCPs), 96%-100% agreed that preoperative malnutrition is a modifiable risk factor associated with worse surgical outcomes and is a treatment priority. Yet, 65% (n = 142/220; dietitians: 88% vs. physicians: 40%) reported screening for malnutrition, which mostly occured in the postoperative period (n = 117) by dietitians (n = 94). Just 42% (48/113) of non-dietitian respondents referred positively screened patients to a dietitian for further assessment and treatment. The most prevalent barriers for malnutrition screening were related to opportunity, including availability of resources (57%, n = 121/212), time (40%, n = 84/212) and support from others (38%, n = 80/212). In conclusion, there is a gap between opinion and practice among surgical HCPs pertaining to malnutrition. Although HCPs agreed malnutrition is a surgical priority, the opportunity to screen for nutrition risk was a great barrier.

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Nutrition screening is the first step in most acute care pediatric nutrition care pathways. However, there is a lack of understanding of patient and families' perception of nutrition screening in pediatric populations. The objective of this study was to explore the potential perceptions, feelings, and opinions of families if pediatric nutrition screening were to be completed during hospital admission. Nine members of the Family Advisory Council at the Alberta Children's Hospital participated in a focus group to discuss questions around nutrition screening practices, malnutrition, and the pediatric nutrition screening tool. Transcripts were analyzed using MAXQDA and thematic analysis using the Braun and Clarke methodology. Two major themes emerged: screening may raise sensitive emotions and understanding the purpose of nutrition screening and the questions. Participants agreed discussions around growth and nutrition are vital to comprehensive medical care; however, the timing and approach of nutrition screening can lead to anxiety and feelings of judgement. A lack of understanding of the purpose of screening, next steps, and benefit to the individual patient could limit acceptance of nutrition screening. The findings of this study can inform training and education of healthcare professionals involved in nutrition screening.

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The assessment of nutrition status, sarcopenia, and frailty holds significant relevance in the context of adult transplantation, as these factors are associated with an unfavorable prognosis; thus, transplant candidates must undergo a full nutrition assessment. Screening tools may be used to prioritize patients, this can be done using the Nutrition Risk Screening 2002 or Royal Free Hospital-Nutritional Prioritizing Tool. Subsequently, a thorough nutrition-focused physical examination should be conducted to evaluate clinical signs of nutrition deficiencies, fat and muscle loss, and fluid overload; dietary history and current intake must also be assessed. Apart from physical examination, specific testing for sarcopenia and frailty are recommended. For sarcopenia assessment, specifically for muscle quantification, the gold standard is the cross-sectional measurement of the muscle at L3 obtained from a computed tomography scan or magnetic resonance imaging; dual-energy x-ray absorptiometry is also a good tool especially when appendicular skeletal muscle index is calculated. Other more readily available options include phase angle from bioelectrical impedance or bioimpedance spectroscopy. In the sarcopenia assessment, muscle function evaluation is required, handgrip strength stands as the primary test for this purpose; this test is also part of the subjective global assessment and is included in some frailty scores. Finally, for frailty assessment, the Short Physical Performance Battery is useful for evaluating physical frailty, and for a multidimensional evaluation, the Fried frailty phenotype can be used. Specifically for liver transplant candidates, the use of Liver Frailty Index is recommended.

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BACKGROUND: Ambulatory cancer patients are at high risk of malnutrition. Multiple nutrition screening and assessment tools are used in the outpatient setting. This study aimed to evaluate the efficacy of different nutrition screening tools as the first step of the Global Leadership Initiative on Malnutrition (GLIM) framework in Chinese ambulatory cancer patients. METHODS: A cross-sectional study was conducted in a tertiary hospital in China. Malnutrition diagnoses made by the GLIM framework using Malnutrition Screening Tool, Malnutrition Universal Screening Tool, Nutritional Risk Screening 2002, or short-form of Patient-Gernerated Subjective Global Assessment (PG-SGA) as the first step were compared with PG-SGA separately. RESULTS: Of the 562 included patients, 31.0% were diagnosed with malnutrition (PG-SGA: B + C), and 12.6% were diagnosed with severe malnutrition (PG-SGA: C). As the screening tool in the first step of the GLIM framework, the short form of PG-SGA (PG-SGA SF) with a cutoff value of ≥2 performed best in diagnosing malnutrition, with good sensitivity (SE) (80.5% [73.6-85.9]) and specificity (SP) (98.4% [96.5-99.4]) and substantial accordance (κ = 0.826), whereas PG-SGA SF with a cutoff value of ≥4 performed best in diagnosing severe malnutrition, with fair SE (62.0% [49.6-73.0]), good SP (96.7% [94.6-98.1]) and moderate accordance (κ = 0.629). CONCLUSION: Using PG-SGA as the standard, the GLIM framework using PG-SGA SF as the screening tool has good accordance with the PG-SGA regardless of severity grading. PG-SGA SF can be used as a valid screening tool in the GLIM framework.

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BACKGROUND: For children with cystic fibrosis (CF), achieving and maintaining optimal growth by the age of 2 years is critical for future health outcomes. A standardized nutrition screening is needed to identify growth problems, enable timely interventions, and improve nutritional outcomes for children (0 to 2 years) with CF. The purpose of this study was to develop a nutrition screening tool for children (0 to 2 years) with CF to identify nutrition risk at every clinical encounter. METHODS: A retrospective cross-sectional study was used to develop a nutrition screening tool to determine if nutrition interventions needed to change (at-risk) or continue (not at-risk). Retrospective data for pertinent nutrition factors were collected for 99 children attending an accredited CF clinic. The nutrition factors were compared to a dietitian assessment. A stepwise discriminant analysis determined weight-for-age (WFA) and weight-for-length (WFL) z-scores were significant. Then anthropometric data and corresponding dietitian assessment results were collected for children with CF attending two other accredited CF clinics (n = 29, n = 30). Discriminant analysis was used to determine sensitivity and specificity of the nutrition factors and to create a nutrition screening tool equation. RESULTS: The nutrition screening model that included WFA z-score, LFA z-score, WFL z-score, and weight change velocity adequacy determined nutrition risk the best. The sensitivity was 89.7 %, specificity 83.2 %, NPV 93.3 %, and PPV 75.4 % for this model. CONCLUSION: The nutrition screening tool equation developed in this study standardizes the process to identify children (0 to 2 years) with CF at nutrition risk. Further validation is needed.

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Severe food selectivity places children at risk for nutrient deficiencies and long-term medical complications, if unaddressed. However, poor nutrition in highly selective eaters is often overlooked when considering other behavioral or medical concerns. Additionally, studies regarding food selectivity are sparse and limited to children with developmental delays. This study further investigates the nutritional deficiencies and growth characteristics of children with severe food selectivity to assist pediatricians in the earlier identification of patients for nutrition screening. A retrospective chart review was completed for 13 patients admitted to a pediatric feeding program solely for table-textured food selectivity. Nutrition and anthropometric data from the medical record were analyzed. All patients were determined to be following an age-appropriate growth curve but had multiple micronutrient deficiencies. Additionally, 6 children were typically developing outside of the feeding context. Results suggest that children with food selectivity may require more intensive and earlier nutrition screening beyond their growth patterns.

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OBJECTIVE: The purpose of this study was to investigate dietetic resources and current nutrition screening, assessment, and intervention practices in pediatric oncology centers in Aotearoa, New Zealand. METHODS: A national survey of the two specialist treatment centers and 14 shared care centers that provide care to childhood cancer patients in Aotearoa, New Zealand, was conducted. RESULTS: The two specialist treatment centers in Aotearoa, New Zealand, were the only centers with a dedicated dietetic oncology full-time equivalent resource; this full-time equivalent resource was devoted to inpatient care. Only 5 shared care centers (44%) had access to general pediatric dietetic support. Dietetic cover for outpatients or day-stay patients and use of standardized nutrition screening and assessment tools were limited. Weight and height were commonly measured, but there was inconsistency in the frequency and recording of measurements. Nutrition interventions, including nutrition education, oral nutrition support, enteral nutrition, and intravenous nutrition, were available within all centers but criteria for initiating support varied. Common barriers to providing nutrition interventions included staff resourcing and ad hoc referral pathways. Awareness of the relevance and clinical benefit of nutrition in pediatric oncology was low. Suggestions to improve nutrition screening, assessment, and intervention within Aotearoa, New Zealand, included the creation of standardized screening and referral criteria. CONCLUSIONS: Resource limitations and lack of nutritional screening and assessment prevent adequate nutritional intervention for children with cancer in Aotearoa, New Zealand. Akin to other high-income countries, there is a need to harmonize the management of nutritional challenges in children with cancer. This study provides a first step in establishing an evidence base to help support efforts to address this need in Aotearoa, New Zealand.

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CONTEXT: Conflicting predictions of malnutrition for the long-term prognosis of coronary artery disease (CAD) exist. OBJECTIVE: This study aimed to investigate the relationship between malnutrition and long-term prognosis of patients with CAD. DATA SOURCES: Four databases were searched for articles from February 11, 1936, to September 10, 2022. DATA EXTRACTION: Cohort studies adjusting for multiple cardiovascular risk factors with data on CAD and malnutrition were included. Malnutrition was measured and defined by different nutritional evaluation tools. The hazard ratios (HRs) and confidence intervals (CIs) for all-cause mortality and major adverse cardiovascular events (MACEs) were synthesized. Subgroup analyses were performed based on study design, assessment tools, ethnicity/race, follow-up, sample size, and types of CAD. Meta-regression was used to compare whether the effect sizes of the 2 subgroups were statistically significant. DATA ANALYSIS: A total of 30 cohort studies were included, totaling 81 361 participants with CAD. Nutritional evaluation tools, including the Geriatric Nutritional Risk Index (GNRI), Controlling Nutritional Status (CONUT), Nutritional Risk Screening 2002, Mini-Nutritional Assessment, and Prognostic Nutritional Index, were used. Malnutrition increased all-cause mortality (HR = 1.72; 95% CI: 1.53, 1.93) and MACEs (HR = 1.47; 95% CI: 1.35, 1.60) in patients with CAD. Subgroup analysis revealed the results were consistent across study design, ethnicity/race, follow-up, sample size, and types of CAD. Subgroup analyses and meta-regression revealed that malnutrition was associated with a higher risk of all-cause mortality (HR = 2.26; 95% CI: 1.91, 2.68) and MACEs (HR = 2.28; 95% CI: 1.69, 3.08) in patients with stable CAD than those with other types of CAD. Meta-regression revealed that the GNRI (HR = 2.20; 95% CI: 1.65, 2.93) was more effective than CONUT (HR = 1.47; 95% CI: 1.21, 1.78) in predicting all-cause mortality. CONCLUSION: Malnutrition independently increased all-cause mortality by 72% and MACEs by 47% in patients with CAD, especially with stable CAD. The GNRI is a more effective nutritional evaluation tool than CONUT in predicting all-cause mortality.

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BACKGROUND: Chimeric antigen receptor T (CAR-T) cell therapy is a novel therapy demonstrating durable remissions in patients with refractory or relapsing non-Hodgkin's B-cell lymphoma. Maintaining a patient's nutritional status has been demonstrated to improve outcomes in cancer treatment. However, no studies have investigated how CAR-T therapy affects nutritional status, nor compared its impact with other cancer treatments for this patient group. The primary aim of the present study was to investigate the effect of CAR-T therapy on the prevalence of nutrition impact symptoms (NIS) and nutritional status within 30 days post-treatment of patients with lymphoma compared to a conditioning regimen for autologous haematopoetic stem cell transplant (carmustine/BCNU, Etoposide, cytarabine/Ara-C, Melphalan [BEAM] auto-haematopoetic stem cell transplant [HSCT]). METHODS: Clinical notes of patients with lymphoma who underwent either CAR-T therapy or BEAM auto-HSCT between 2018 and 2021 were reviewed. Data extracted included body weight measurements and NIS, including decreased appetite, nausea, vomiting, diarrhoea, constipation, mucositis, cytokine release syndrome (CRS) and neurotoxicity at baseline and 30 ± 7 days post-treatment. RESULTS: In total, 129 adults with lymphoma (n = 88 CAR-T vs. n = 41 BEAM) were included. Nutritional status was assessed in both groups at baseline prior to treatment. Mean absolute weight change was significantly different between groups (3.05 kg in CAR-T, -5.9 kg in BEAM, p ≤ 0.001). This was also significant when weight loss was categorised into percentage weight loss (p = 0.01). CAR-T patients experienced a significantly lower prevalence of decreased appetite (52.3% vs. 97.6%) nausea (25% vs. 78%,) vomiting (10.2% vs. 53.7%), diarrhoea (43.2% vs. 96.7%) and mucositis (5.7% vs. 75.6%) combined across all levels of severity compared to BEAM chemotherapy (all p ≤ 0.01). CRS and neurotoxicity, which are specific side effects of CAR-T therapy, were moderately positively associated with weight loss. CONCLUSIONS: Weight loss, percentage weight loss and NIS were significantly reduced in CAR-T compared to BEAM treatment. However, patients who experienced neurotoxicity during treatment did have significant weight loss.

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Our primary study objectives were to (i) determine the proportion of children admitted to the Pediatric Intensive Care Unit (PICU) with malnutrition diagnoses, (ii) compare healthcare utilization by malnourished and non-malnourished PICU patients, and (iii) examine the impact of implementing malnutrition screening and coding practices at a major academic urban tertiary care medical center. Using patient records, we conducted a retrospective analysis of 4106 children admitted to the PICU for severe illnesses between 2011 and 2019. Patients were identified as malnourished if records showed an ICD-9 or ICD-10 code for malnutrition. We compared malnourished and non-malnourished patients by age, admitting diagnoses, number of comorbid conditions, and clinical outcomes (length of stay, hospital readmission). About 1 of every 5 PICU-admitted patients (783/4106) had a malnutrition diagnosis. Patients with malnutrition were younger (mean age 6.2 vs. 6.9 years, p < 0.01) and had more comorbid conditions (14.3 vs. 7.9, p < 0.01) than those without. Malnourished patients had longer hospital stays (26.1 vs. 10.0 days, p < 0.01) and higher 30-day readmission rates (10% vs. 7%, p = 0.03). Implementation of malnutrition screening and coding practices was associated with an increase in malnutrition diagnosis. In this study of children admitted to the PICU, malnourished patients had more comorbid diagnoses and used more healthcare resources (prolonged hospitalizations and higher 30-day readmission rates), leading to higher healthcare costs. Such findings underscore the need for policies, training, and programs emphasizing identification and treatment of malnutrition at hospitals caring for critically ill children.

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Malnutrition in critically ill patients is closely linked with clinical outcomes. During acute inflammatory states, nutrition cannot reverse the loss of body cell mass completely. Studies on nutritional screening and strategy considering metabolic changes have not yet been conducted. We aimed to identify nutrition strategies using the modified Nutrition Risk in the Critically ill (mNUTIRC) score. Nutrition support data, laboratory nutrition indicators, and prognosis indices were prospectively collected on the 2nd and 7th day after admission. It was to identify the effect of the changes on the metabolic status and critical target of nutrition intervention. To discriminate the high-risk group of malnutrition, receiver operating characteristic curves were plotted. Risk factors associated with 28 day-mortality were evaluated using multivariable Cox proportional hazards regression. A total of 490 and 266 patients were analyzed on the 2nd and 7th day, respectively. Only the mNUTRIC score showed significant differences in nutritional risk stratification. The use of vasopressors, hypoprotein supply (<1.0 g/kg/day), high mNUTRIC score, and hypoalbuminemia (<2.5 mg/dL) in the recovery phase were strongly associated with a 28-day mortality. The implementation of the mNUTRIC score and protein supply in the post-acute phase is critical to improve 28-day mortality in critically ill patients.

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