Novel Equations for Estimating Lean Body Mass in Peritoneal Dialysis Patients

Dong, Jie; Li, Yanjun; Xu, Rong; Yang, Zhikai; Zheng, Yan

doi:10.3747/pdi.2013.00246

Cited by 7 publications

(6 citation statements)

References 36 publications

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“…As a result, there might have been some difference between the estimated value and the actual value of LMI. However, LBM estimation with our previously developed equations has been verified as a precise method with a very small bias compared with dual-energy X-ray absorptiometry [39], a commonly recognized standard examination. Another limitation was the observational design of the study, we therefore cannot exclude the possibility that unrecognized factors confounded the observed associations between exposure, i.e., HGS or LMI, and mortality.…”

Section: Discussionmentioning

confidence: 90%

“…HGS evaluated in the dominant arm was used to develop the prediction equation. Lean body mass (LBM) was calculated using the following formulas for CKD stage 3–5 patients derived by us: LBM (kg) = (1 if male; 0 if female) × 4.72 + height (cm) × 0.28 + weight (kg) × 0.27 + HGS (N) × 0.02—dialysis duration (months) × 0.04—26.84 [ 39 ]. As compared with the gold standard, dual-energy X-ray absorptiometry, LBM estimated from this equation has shown small bias and better accuracy than LBM from creatinine kinetics and anthropometry methods.…”

Section: Methodsmentioning

confidence: 99%

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The cut-off values of handgrip strength and lean mass index for sarcopenia among patients on peritoneal dialysis

Yang

et al. 2020

Nutr Metab (Lond)

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Background Sarcopenia is common and contributes to a high risk of mortality among general population. There is no consensus regarding the cut-off values for sarcopenia in terms of mortality among chronic kidney disease patients. This study aimed to explore and validate cut-off points of handgrip strength (HGS) and lean mass index (LMI) for estimating the risk of mortality in peritoneal dialysis (PD) patients. Methods This single-center prospective cohort study enrolled 1089 incident PD patients between October 2002 and July 2019. All patients were followed until death, transfer to hemodialysis, receiving renal transplantation or the end date of study (December 2019). All participants were randomly sampled to development cohort (70% participants) and validation cohort (30% participants), matched by gender and diabetes. Lean body mass was calculated by using the equation published by our center. Cubic spline regression analysis was used to examine the relationship between HGS or LMI values and mortality, and explore the cut-off points after adjusting for age, diabetes, cardiovascular disease and serum albumin in the development cohort. The derived cut-off values were verified by the agreement rate for predicting mortality and then compared with cut-off values from various clinical guidelines in the validation cohort. Results All 1089 patients were followed up with the median of 36.0 (18.0, 71.0) months. In the development cohort, cut-off points for predicting the higher mortality were derived as 24.5 kg and 14 kg of HGS for males and females, 16.7 kg/m2 and 13.8 kg/m2 of LMI for males and females respectively. In the validation cohort, these cut-off values significantly predicted worse outcomes, with HR 1.96 (1.35, 2.84) of HGS and HR 1.76 (1.26, 2.47) of LMI for all-cause mortality after multivariate adjustment. The newly derived cut-off points of HGS have numerically higher prognostic values in all-cause mortality compared with those from current clinical guidelines, and agreement rates of HGS were 65.2 versus 62.5–64.6 respectively. Conclusions The derived cut-off values of HGS and LMI have sufficient and better prognostic value in predicting all-cause mortality in PD patients compared with the cut-off values in the existing guidelines. These cut-off values are only validated in a single population, thus limiting the generalizability.

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Section: Discussionmentioning

confidence: 90%

Section: Methodsmentioning

confidence: 99%

The cut-off values of handgrip strength and lean mass index for sarcopenia among patients on peritoneal dialysis

Yang

et al. 2020

Nutr Metab (Lond)

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“…However, this method can be insensitive since it is associated with a substantial interobserver error and the volume state [7]. Equations based on the MAMC and handgrip strength have been favorably correlated with muscle mass [38].…”

Section: Dietary Intakementioning

confidence: 99%

Diagnosis, Prevention, and Treatment of Protein-Energy Wasting in Peritoneal Dialysis

Yanowsky-Escatell¹,

Pazarín-Villaseñor²,

Andrade‐Sierra³

et al. 2018

Evolving Strategies in Peritoneal Dialysis

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Protein-energy wasting (PEW) is highly prevalent in peritoneal dialysis (PD) patients and is associated with mortality. Reduced protein and energy intake, comorbidity conditions, endocrine disorders, increased inflammatory cytokines, uremic toxins, metabolic acidosis, oxidative stress, nutrient losses into dialysate, continuous absorption of glucose from PD solutions, abdominal fullness induced by the dialysate, and peritonitis contribute to PEW. Assessment of nutritional status for the detection and management of PEW includes the PEW definition criteria, subjective global assessment (SGA), malnutrition-inflammation score (MIS), and geriatric nutritional risk index (GNRI). Diverse factors can affect nutritional and metabolic status in these patients so multiple strategies may be required to prevent or reverse PEW. Preventive measures include continuous nutritional counseling, optimizing dietary nutrient intake, and managing comorbidities. To treat PEW, the following may be used: administration of oral, intraperitoneal, enteral, or parenteral nutritional supplementation and adjunct therapies such as anabolic agents, appetite stimulants, antiinflammatory interventions, and exercise. Diagnosis, prevention, and treatment of PEW in PD patients may favorably impact the prognosis and course of the disease.

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“…Loss of skeletal muscle mass may impede insulin-mediated glucose disposal and exacerbate obesity-related IR [ 9 , 10 ]. Lean body mass can be estimated by equations based on the mid-arm muscle circumference (MAMC) and hand grip strength (HGS) [ 11 ], and the MAMC can represent muscle mass because of its association with dual-energy X-ray absorptiometry (DEXA) [ 12 ]. According to Atkins et al , the MAMC was initially positively correlated with HOMA-IR.…”

Section: Introductionmentioning

confidence: 99%

Mid-arm muscle circumference as a surrogate in predicting insulin resistance in non-obese elderly individuals

et al. 2017

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The homeostatic model assessment of insulin resistance (HOMA-IR) was used to measure the degree of insulin resistance (IR). Previous literature revealed that mid-arm muscle circumference (MAMC) is one of the anthropometric indicators for nutritional status and the relationship between MAMC and HOMA-IR remains uncertain in the obese and non-obese elderly individuals. The present study included 5,607 participants aged between 60 to 84 years old, using data from the 1999 to 2006 National Health and Nutrition Examination Survey (NHANES). To further explore the association between HOMA-IR and MAMC in the obese and non-obese elderly population using multivariate Cox regression analyses, we divided the participants into obese (BMI ≥ 30 kg/m2) group and non-obese (19 ≤ BMI < 30 kg/m2) group in this study; each group was then divided into quartiles based on their MAMC levels. A positive association was noted between the MAMC and HOMA-IR in all of the designed models initially. After adjusting for multiple covariates, a higher level of the MAMC was significantly associated with elevated HOMA-IR (P < 0.05) in the non-obesity group, which was not the case in the obesity group. Additionally, subjects in the higher quartiles of MAMC tended to have higher HOMA-IR with a significant association (P for trend = 0.003 in model 1; P for trend < 0.001 in model 2, 3, and 4). These results demonstrated that the MAMC can be an auxiliary indicator of HOMA-IR in non-obese elderly individuals and may have substantial additional value in screening for IR if well extrapolated.

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Novel Equations for Estimating Lean Body Mass in Peritoneal Dialysis Patients

Cited by 7 publications

References 36 publications

The cut-off values of handgrip strength and lean mass index for sarcopenia among patients on peritoneal dialysis

The cut-off values of handgrip strength and lean mass index for sarcopenia among patients on peritoneal dialysis

Diagnosis, Prevention, and Treatment of Protein-Energy Wasting in Peritoneal Dialysis

Mid-arm muscle circumference as a surrogate in predicting insulin resistance in non-obese elderly individuals

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