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Sarcopenic Obesity in Chronic Kidney Disease: Challenges in Diagnosis using Different Diagnostic Criteria.

ABSTRACT: Obesity and muscle impairment (low muscle mass or strength) are present in chronic kidney disease (CKD) and associated to worse prognosis. However, the various existing definitions for these conditions make the diagnosis variable. The aim of the study was to evaluate the agreement between diagnostic criteria for sarcopenic obesity and its components in CKD. Two hundred and sixty seven patients with CKD were included in the study. We assessed body composition by dual energy X-ray absorptiometry (DXA) and muscle function by handgrip strength (HGS); adiposity by BMI, waist circumference (WC), fat mass index (FMI), and percentage of fat mass (%FM). Diagnosis of muscle impairment was made by HGS, appendicular lean mass (ALM) and index (ALMI); obesity by BMI, WC, FMI and %FM, and sarcopenic obesity was diagnosed by concomitant presence of muscle impairment and obesity. Prevalence of muscle impairment varied from 11 to 50%, higher when low muscle mass criteria was used. Prevalence of obesity varied from 26 to 62%, higher when WC and %FM criteria was used. Prevalence of sarcopenic obesity varied from 2 to 23%. Women were more affected by sarcopenic obesity. Muscle impairment and sarcopenic obesity were more prevalent among patients on hemodialysis and obesity among non-dialysis-dependent and kidney transplant patients. The agreement was poor between muscle mass and strength criteria; substantial between FMI, BMI, and %FM and only fair between WC and the others measures; for sarcopenic obesity, varied from poor to almost perfect. Significant differences were found among the various diagnostic criteria that are used in the diagnosis of sarcopenic obesity.

SUBMITTER: Bellafronte NT

PROVIDER: S-EPMC8562051 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionLoss of skeletal muscle mass and function (sarcopenia) is common in individuals with obesity due to metabolic changes associated with a sedentary lifestyle, adipose tissue derangements, comorbidities (acute and chronic diseases) and during the ageing process. Co-existence of excess adiposity and low muscle mass/function is referred to as sarcopenic obesity (SO), a condition increasingly recognized for its clinical and functional features that negatively influence important patient-centred outcomes. Effective prevention and treatment strategies for SO are urgently needed, but efforts are hampered by the lack of a universally established SO definition and diagnostic criteria. Resulting inconsistencies in the literature also negatively affect the ability to define prevalence as well as clinical relevance of SO for negative health outcomes.Aims and methodsThe European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) launched an initiative to reach expert consensus on a definition and diagnostic criteria for SO. The jointly appointed international expert panel proposes that SO is defined as the co-existence of excess adiposity and low muscle mass/function. The diagnosis of SO should be considered in at-risk individuals who screen positive for a co-occurring elevated body mass index or waist circumference, and markers of low skeletal muscle mass and function (risk factors, clinical symptoms, or validated questionnaires). Diagnostic procedures should initially include assessment of skeletal muscle function, followed by assessment of body composition where presence of excess adiposity and low skeletal muscle mass or related body compartments confirm the diagnosis of SO. Individuals with SO should be further stratified into stage I in the absence of clinical complications or stage II if cases are associated with complications linked to altered body composition or skeletal muscle dysfunction.ConclusionsESPEN and EASO, as well as the expert international panel, advocate that the proposed SO definition and diagnostic criteria be implemented into routine clinical practice. The panel also encourages prospective studies in addition to secondary analysis of existing data sets, to study the predictive value, treatment efficacy and clinical impact of this SO definition.

Project description:INTRODUCTION: Recently, the Kidney Disease: Improving Global Outcomes (KDIGO) proposed a new definition and classification of acute kidney injury (AKI) on the basis of the RIFLE (Risk, Injury, Failure, Loss of kidney function, and End-stage renal failure) and AKIN (Acute Kidney Injury Network) criteria, but comparisons of the three criteria in critically ill patients are rare. METHODS: We prospectively analyzed a clinical database of 3,107 adult patients who were consecutively admitted to one of 30 intensive care units of 28 tertiary hospitals in Beijing from 1 March to 31 August 2012. AKI was defined by the RIFLE, AKIN, and KDIGO criteria. Receiver operating curves were used to compare the predictive ability for mortality, and logistic regression analysis was used for the calculation of odds ratios and 95% confidence intervals. RESULTS: The rates of incidence of AKI using the RIFLE, AKIN, and KDIGO criteria were 46.9%, 38.4%, and 51%, respectively. KDIGO identified more patients than did RIFLE (51% versus 46.9%, P?=?0.001) and AKIN (51% versus 38.4%, P <0.001). Compared with patients without AKI, in-hospital mortality was significantly higher for those diagnosed as AKI by using the RIFLE (27.8% versus 7%, P <0.001), AKIN (32.2% versus 7.1%, P <0.001), and KDIGO (27.4% versus 5.6%, P <0.001) criteria, respectively. There was no difference in AKI-related mortality between RIFLE and KDIGO (27.8% versus 27.4%, P?=?0.815), but there was significant difference between AKIN and KDIGO (32.2% versus 27.4%, P?=?0.006). The areas under the receiver operator characteristic curve for in-hospital mortality were 0.738 (P <0.001) for RIFLE, 0.746 (P <0.001) for AKIN, and 0.757 (P <0.001) for KDIGO. KDIGO was more predictive than RIFLE for in-hospital mortality (P <0.001), but there was no difference between KDIGO and AKIN (P?=?0.12). CONCLUSIONS: A higher incidence of AKI was diagnosed according to KDIGO criteria. Patients diagnosed as AKI had a significantly higher in-hospital mortality than non-AKI patients, no matter which criteria were used. Compared with the RIFLE criteria, KDIGO was more predictive for in-hospital mortality, but there was no significant difference between AKIN and KDIGO.

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Sarcopenic Obesity in Chronic Kidney Disease: Challenges in Diagnosis using Different Diagnostic Criteria.

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