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Liu P, Tian H, Gao L, Zhong T, Wang Y, Chen L. The predictive value of GLIM criteria on clinical outcomes and responses to nutritional support in patients with neurocritical illnesses. Sci Rep 2024; 14:15061. [PMID: 38956245 PMCID: PMC11219829 DOI: 10.1038/s41598-024-65994-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 06/26/2024] [Indexed: 07/04/2024] Open
Abstract
Neurocritically ill patients frequently exhibit coma, gastroparesis, and intense catabolism, leading to an increased risk of malnutrition. The Global Leadership Initiative on Malnutrition (GLIM) criteria for the diagnosis of malnutrition was created to achieve a consistent malnutrition diagnosis across diverse populations. This study aimed to validate the concurrent and predictive validity of GLIM criteria in patients with neurocritical illnesses. A total of 135 participants were followed from admission to the neurocritical unit (NCU) until discharge. Comparing GLIM criteria to the Subjective Global Assessment (SGA), sensitivity was 0.95 and specificity was 0.69. Predictive validity of GLIM criteria was assessed using a composite adverse clinical outcome, comprising mortality and various major complications. Adjusted hazard ratios for moderate and severe malnutrition were 2.86 (95% CI 1.45-5.67) and 3.88 (95% CI 1.51-9.94), respectively. Changes in indicators of nutritional status, including skeletal muscle mass and abdominal fat mass, within 7 days of admission were obtained for 61 participants to validate the predictive capability of the GLIM criteria for the patients' response of standardized nutritional support. The GLIM criteria have a statistically significant predictive validity on changes in rectus femoris muscle thickness and midarm muscle circumference. In conclusion, the GLIM criteria demonstrate high sensitivity for diagnosing malnutrition in neurocritically ill patients and exhibit good predictive validity.
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Affiliation(s)
- Peiqi Liu
- School of Nursing, Jilin University, No. 965 Xinjiang Street, Chang Chun, 130021, Jilin Province, China
| | - Huimin Tian
- School of Nursing, Jilin University, No. 965 Xinjiang Street, Chang Chun, 130021, Jilin Province, China
| | - Lan Gao
- Department of Neurology, The First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, 130021, Jilin Province, China
| | - Tangsheng Zhong
- School of Nursing, Jilin University, No. 965 Xinjiang Street, Chang Chun, 130021, Jilin Province, China
| | - Yujiao Wang
- Neurocritical Care Unit, Department of Neurology, The First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, 130021, Jilin Province, China.
| | - Li Chen
- School of Nursing, Jilin University, No. 965 Xinjiang Street, Chang Chun, 130021, Jilin Province, China.
- Department of Pharmacology, College of Basic Medical Sciences, Jilin University, Changchun, 130021, Jilin Province, China.
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Subramaniam A, Ling RR, Ridley EJ, Pilcher DV. The impact of body mass index on long-term survival after ICU admission due to COVID-19: A retrospective multicentre study. CRIT CARE RESUSC 2023; 25:182-192. [PMID: 38234325 PMCID: PMC10790021 DOI: 10.1016/j.ccrj.2023.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 10/18/2023] [Indexed: 01/19/2024]
Abstract
Objective The impact of obesity on long-term survival after intensive care unit (ICU) admission with severe coronavirus disease 2019 (COVID-19) is unclear. We aimed to quantify the impact of obesity on time to death up to two years in patients admitted to Australian and New Zealand ICUs. Design Retrospective multicentre study. Setting 92 ICUs between 1st January 2020 through to 31st December 2020 in New Zealand and 31st March 2022 in Australia with COVID-19, reported in the Australian and New Zealand Intensive Care Society adult patient database. Participants All patients with documented height and weight to estimate the body mass index (BMI) were included. Obesity was classified patients according to the World Health Organization recommendations. Interventions and main outcome measures The primary outcome was survival time up to two years after ICU admission. The effect of obesity on time to death was assessed using a Cox proportional hazards model. Confounders were acute illness severity, sex, frailty, hospital type and jurisdiction for all patients. Results We examined 2,931 patients; the median BMI was 30.2 (IQR 25.6-36.0) kg/m2. Patients with a BMI ≥30 kg/m2 were younger (median [IQR] age 57.7 [46.2-69.0] vs. 63.0 [50.0-73.6]; p < 0.001) than those with a BMI <30 kg/m2. Most patients (76.6%; 2,244/2,931) were discharged alive after ICU admission. The mortality at two years was highest for BMI categories <18.5 kg/m2 (35.4%) and 18.5-24.9 kg/m2 (31.1%), while lowest for BMI ≥40 kg/m2 (14.5%). After adjusting for confounders and with BMI 18.5-24.9 kg/m2 category as a reference, only the BMI ≥40 kg/m2 category patients had improved survival up to 2 years (hazard ratio = 0.51; 95%CI: 0.34-0.76). Conclusions The obesity paradox appears to exist beyond hospital discharge in critically ill patients with COVID-19 admitted in Australian and New Zealand ICUs. A BMI ≥40 kg/m2 was associated with a higher survival time of up to two years.
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Affiliation(s)
- Ashwin Subramaniam
- Department of Intensive Care, Peninsula Health, Frankston, Victoria, Australia
- Department of Intensive Care, Dandenong Hospital, Monash Health, Dandenong, Victoria, Australia
- Peninsula Clinical School, Monash University, Frankston, Victoria, Australia
- Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Ryan Ruiyang Ling
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Emma J. Ridley
- Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
- Department of Nutrition and Dietetics, Alfred Hospital, Melbourne, Victoria, Australia
| | - David V. Pilcher
- Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
- Department of Intensive Care, Alfred Hospital, Melbourne, Victoria, Australia
- Centre for Outcome and Resource Evaluation, Australian and New Zealand Intensive Care Society, Melbourne, Victoria, Australia
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Tóth B, Dénes Z, Németh M, Fazekas G. Changes in skeletal muscle mass index and fat mass index during rehabilitation for traumatic brain injury and stroke measured by bioelectrical impedance analysis. Int J Rehabil Res 2023; 46:264-269. [PMID: 37334827 DOI: 10.1097/mrr.0000000000000587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Although malnutrition may negatively impact the outcomes of rehabilitation and increase the cost of care, there are still no valid nutritional assessment methods appropriate for specific groups of patients undergoing rehabilitation. This study aimed to determine if a multifrequency bioelectrical impedance is suitable for monitoring the changes in body composition of brain-injured patients for whom individualized nutritional goals were set during rehabilitation. Fat mass index (FMI) and skeletal muscle mass index (SMMI) were examined by Seca mBCA515 or portable Seca mBCA525 device within 48 h of admission and before discharge in 11 traumatic brain injury (TBI) and 11 stroke patients with admission Nutritional Risk Screening 2002 scores ≥2. The changes in outcomes and plausible interactions were examined between the admission values and the values estimated for the 18th day (minimum length of stay in the sample) using a repeated measure mixed-sample analysis of covariance. In patients with low FMI at admission (mainly younger, TBI patients, with longer ICU stay), there was no change over time whereas, in those with high admission FMI (older, stroke patients, with shorter ICU stay), a decrease was observed (significant interaction F(1,19) = 9.224 P = 0.007 Part. η² = 0.327). The SMMI significantly increased over time (F(1,19) = 5.202 P = 0.034 Part. η² = 0.215) independently of gender, age, days spent in ICU and cause of brain injury. Our results suggest that bioelectrical impedance analysis is feasible and informative for monitoring the changes in body composition during rehabilitation, which also requires consideration of demographic and pre-rehabilitation characteristics.
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Affiliation(s)
- Babett Tóth
- Rehabilitation Department of Brain injuries, Department for Rehabilitation post Stroke, Department of Alimentation and Dietetics, National Institute of Locomotor Diseases and Disabilities/National Institute for Medical Rehabilitation
| | - Zoltán Dénes
- Rehabilitation Department of Brain injuries, Department for Rehabilitation post Stroke, Department of Alimentation and Dietetics, National Institute of Locomotor Diseases and Disabilities/National Institute for Medical Rehabilitation
- Department of Rehabilitation Medicine, Semmelweis University, Budapest
| | - Mariann Németh
- Rehabilitation Department of Brain injuries, Department for Rehabilitation post Stroke, Department of Alimentation and Dietetics, National Institute of Locomotor Diseases and Disabilities/National Institute for Medical Rehabilitation
- Department of Rehabilitation Medicine, Semmelweis University, Budapest
| | - Gábor Fazekas
- Rehabilitation Department of Brain injuries, Department for Rehabilitation post Stroke, Department of Alimentation and Dietetics, National Institute of Locomotor Diseases and Disabilities/National Institute for Medical Rehabilitation
- University of Szeged, Szeged, Hungary
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Besutti G, Pellegrini M, Ottone M, Bonelli E, Monelli F, Farì R, Milic J, Dolci G, Fasano T, Canovi S, Costi S, Fugazzaro S, Massari M, Ligabue G, Croci S, Salvarani C, Pattacini P, Guaraldi G, Giorgi Rossi P. Modifications of Chest CT Body Composition Parameters at Three and Six Months after Severe COVID-19 Pneumonia: A Retrospective Cohort Study. Nutrients 2022; 14:nu14183764. [PMID: 36145141 PMCID: PMC9501258 DOI: 10.3390/nu14183764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 09/08/2022] [Accepted: 09/10/2022] [Indexed: 11/16/2022] Open
Abstract
We aimed to describe body composition changes up to 6–7 months after severe COVID-19 and to evaluate their association with COVID-19 inflammatory burden, described by the integral of the C-reactive protein (CRP) curve. The pectoral muscle area (PMA) and density (PMD), liver-to-spleen (L/S) ratio, and total, visceral, and intermuscular adipose tissue areas (TAT, VAT, and IMAT) were measured at baseline (T0), 2–3 months (T1), and 6–7 months (T2) follow-up CT scans of severe COVID-19 pneumonia survivors. Among the 208 included patients (mean age 65.6 ± 11 years, 31.3% females), decreases in PMA [mean (95%CI) −1.11 (−1.72; −0.51) cm2] and in body fat areas were observed [−3.13 (−10.79; +4.52) cm2 for TAT], larger from T0 to T1 than from T1 to T2. PMD increased only from T1 to T2 [+3.07 (+2.08; +4.06) HU]. Mean decreases were more evident for VAT [−3.55 (−4.94; −2.17) cm2] and steatosis [L/S ratio increase +0.17 (+0.13; +0.20)] than for TAT. In multivariable models adjusted by age, sex, and baseline TAT, increasing the CRP interval was associated with greater PMA reductions, smaller PMD increases, and greater VAT and steatosis decreases, but it was not associated with TAT decreases. In conclusion, muscle loss and fat loss (more apparent in visceral compartments) continue until 6–7 months after COVID-19. The inflammatory burden is associated with skeletal muscle loss and visceral/liver fat loss.
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Affiliation(s)
- Giulia Besutti
- Radiology Unit, Department of Diagnostic Imaging and Laboratory Medicine, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
- Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, 41124 Modena, Italy
| | - Massimo Pellegrini
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41124 Modena, Italy
- Correspondence:
| | - Marta Ottone
- Epidemiology Unit, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Efrem Bonelli
- Radiology Unit, Department of Diagnostic Imaging and Laboratory Medicine, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
- Clinical Chemistry and Endocrinology Laboratory, Azienda USL-IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Filippo Monelli
- Radiology Unit, Department of Diagnostic Imaging and Laboratory Medicine, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
- Clinical and Experimental PhD Program, University of Reggio Emilia, 41124 Modena, Italy
| | - Roberto Farì
- Radiology Unit, Department of Diagnostic Imaging and Laboratory Medicine, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Jovana Milic
- Modena HIV Metabolic Clinic, University of Modena and Reggio Emilia, 41124 Modena, Italy
| | - Giovanni Dolci
- Modena HIV Metabolic Clinic, University of Modena and Reggio Emilia, 41124 Modena, Italy
| | - Tommaso Fasano
- Clinical Chemistry and Endocrinology Laboratory, Azienda USL-IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Simone Canovi
- Clinical Chemistry and Endocrinology Laboratory, Azienda USL-IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Stefania Costi
- Scientific Directorate Azienda USL-IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
- Department of Surgery, Medicine, Dentistry and Morphological Sciences with Interest in Transplant, Oncology and Regenerative Medicine, University of Modena and Reggio Emilia, 41124 Modena, Italy
| | - Stefania Fugazzaro
- Physical Medicine and Rehabilitation Unit, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Marco Massari
- Infectious Diseases Unit, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Guido Ligabue
- Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, 41124 Modena, Italy
| | - Stefania Croci
- Clinical Immunology, Allergy and Advanced Biotechnologies Unit, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Carlo Salvarani
- Department of Surgery, Medicine, Dentistry and Morphological Sciences with Interest in Transplant, Oncology and Regenerative Medicine, University of Modena and Reggio Emilia, 41124 Modena, Italy
- Rheumatology Unit, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Pierpaolo Pattacini
- Radiology Unit, Department of Diagnostic Imaging and Laboratory Medicine, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Giovanni Guaraldi
- Modena HIV Metabolic Clinic, University of Modena and Reggio Emilia, 41124 Modena, Italy
| | - Paolo Giorgi Rossi
- Epidemiology Unit, Azienda USL–IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
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