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Metabolic syndrome (MetS) is associated with decreased renal function and chronic kidney disease (CKD). To date, no research regarding the sixteen possible constellations resulting in the diagnosis of MetS has been elucidated. The purpose of this study is to report renal function in sixteen metabolic constellations grouped into four metabolic clusters. Individuals (n = 2767, representing 86,652,073 individuals) from the 2013–2018 National Health and Nutrition Examination Surveys who met the criteria for MetS were included. Sixteen possible constellations of three or more risk factors were analyzed for renal function. Four metabolic clusters representing MetS with hyperglycemia (Cluster I), MetS with hypertension (Cluster II), MetS with hyperglycemia and hypertension (Cluster III), or MetS with normoglycemia and normotension (Cluster IV) were assessed for renal function and CKD status. Cluster III had the highest odds of CKD (OR = 2.57, 95% CL = 1.79, 3.68). Clusters II and III had the lowest renal function and were not different from one another (87.82 and 87.28 mL/min/1.73 m2, p = 0.71). The constellation with the lowest renal function consisted of hypertension, high triglycerides, and a large waist circumference (82.86 mL/min/1.73 m2), whereas the constellation with the highest renal function consisted of hyperglycemia, low HDL, and a large waist circumference (107.46 mL/min/1.73 m2). The sixteen constellations of MetS do not have the same effects on renal function. More research is needed to understand the relationship between the various iterations of MetS and renal function.

Rising rates of metabolic syndrome, obesity, and mortality from chronic kidney disease (CKD) have prompted further investigation into the association between metabolic phenotypes and CKD. Purpose: To report the frequency of strictly defined metabolic phenotypes, renal function within each phenotype, and individual risk factors associated with reduced renal function. We utilized the 2013–2018 National Health and Nutrition Examination Surveys (NHANES) and complex survey sample weighting techniques to represent 220 million non-institutionalized U.S. civilians. Metabolic health was defined as having zero of the risk factors defined by the National Cholesterol Education Program with the exception of obesity, which was defined as BMI ³ 30 kg/m2 in non-Asians and BMI ³ 25 kg/m2 in Asians. The metabolically healthy normal (MUN) phenotype comprised the highest proportion of the population (38.40%), whereas the metabolically healthy obese (MHO) was the smallest (5.59%). Compared to the MHN reference group, renal function was lowest in the strictly defined MUN (B = −9.60, p &lt, 0.001) and highest in the MHO (B = 2.50, p &gt, 0.05), and this persisted when an increased number of risk factors were used to define metabolic syndrome. Systolic blood pressure had the strongest correlation with overall eGFR (r = −0.25, p &lt, 0.001), and individuals with low HDL had higher renal function compared to the overall sample. The MUN phenotype had the greatest association with poor renal function. While the MHO had higher renal function, this may be due to a transient state caused by renal hyperfiltration. Further research should be done to investigate the association between dyslipidemia and CKD.

Objective: Dietary guidelines from the Kidney Disease Outcomes Quality Initiative (KDOQI) and the United States Department of Agriculture (USDA) are advised to individuals with mid-spectrum (stages G3a and G3b) chronic kidney disease (CKD), yet typical diets in individuals with CKD remain understudied. The purpose of this study is to assess the self-reported dietary pattern of subjects with diagnosed mid-spectrum CKD and compare the normal dietary intakes to the KDOQI and USDA recommendations. Methods: A cross-sectional analysis of 20 participants with mid-spectrum CKD (n = 6 male [M]; n = 14 female [F]) was conducted to assess subjects’ self-reported dietary intakes for an average of 5 days. Micro and macronutrient analyses were compared to the KDOQI and USDA guidelines by sex to assess nutrition, and an exploratory stepwise multiple linear regression model was used to identify predictors of poor renal function;p-values were considered significant at the α = 0.05 level. Results: All subjects met the recommended caloric intake, but the average consumptions of protein (F = 0.86 ± 0.29g/kg body weight/day, M = 1.18 ± 0.45g/kg body weight/day), saturated fat (F = 12.17 ± 2.28%, M = 13.86 ± 1.20%), and sodium (F = 3.78 ± 2.51g, M = 4.21 ± 0.39g) were high (p < 0.05 for all). The average fiber intakewas low (F = 13.64 ± 4.09g, M = 14.82 ± 7.28g) as well as folate, vitamins D and K, zinc, and calcium intakes compared with the recommendations (p < 0.05 for all). The only significant contributor to higher renal function in the exploratory regression analysis was male sex (p = 0.035).

The purpose of this study is to determine if renal function varies by metabolic phenotype. A total of 9599 patients from a large Federally Qualified Health Center (FQHC) were included in the analysis. Metabolic health was classified as the absence of metabolic abnormalities defined by the National Cholesterol Education Program Adult Treatment Panel III criteria, excluding waist circumference. Obesity was defined as body mass index &gt, 30 kg/m2 and renal health as an estimated glomerular filtration rate (eGFR) &gt, 60 mL/min/1.732. Linear and logistic regressions were used to analyze the data. The metabolically healthy overweight (MHO) phenotype had the highest eGFR (104.86 ± 28.76 mL/min/1.72m2) and lowest unadjusted odds of chronic kidney disease (CKD) (OR = 0.46, 95%CI = 0.168, 1.267, p = 0.133), while the metabolically unhealthy normal weight (MUN) phenotype demonstrated the lowest eGFR (91.34 ± 33.28 mL/min/1.72m2) and the highest unadjusted odds of CKD (OR = 3.63, p &lt, 0.0001). After controlling for age, sex, and smoking status, the metabolically unhealthy obese (MUO) (OR = 1.80, 95%CI = 1.08, 3.00, p = 0.024) was the only phenotype with significantly higher odds of CKD as compared to the reference. We demonstrate that the metabolically unhealthy phenotypes have the highest odds of CKD compared to metabolically healthy individuals.

BackgroundThe use of tranexamic acid (TXA) has become increasingly prevalent for hemorrhage prevention in military trauma patients due to its known survival benefits. There is concern of increased venous thromboembolism (VTE) subsequent to receiving TXA. The purpose of this retrospective study was to determine the rate of VTE in severely injured military personnel during Operation Enduring Freedom (2009–2014).MethodsAn analysis of 859 military trauma patients from the 2009–2014 Department of Defense Trauma Registry included subjects with an injury severity score (ISS) >10 and a massive transfusion (MT) (>10 units of blood products in the first 24 hours). Outcomes included a documented VTE (eg, deep vein thrombosis (DVT) or pulmonary embolism (PE)) during the patient’s hospital course. Comparison between those who did/did not receive TXA was analyzed using three separate multiple regression analyses using listwise deletion, systematic replacement and multiple imputation.ResultsSubjects (n=620) met inclusion criteria with 27% (n=169) having a documented VTE. A total of 30% that received TXA had a documented VTE, 26% that did not receive TXA had a documented VTE and 43% (n=264, n=620) of the sample did not have TXA documented as either given or not given. Multiple regression analyses using listwise deletion and systematic replacement of the TXA variable demonstrated no difference in odds of VTE, whereas the multiple imputation analysis demonstrated a 3% increased odds of VTE, a9.4% increased odds of PE and 8.1% decreased odds of DVT with TXA administration.DiscussionTXA use with an ISS >10 and MT resuscitation had a 3% increased odds of VTE and an increased odds of PE, whereas the odds of DVT were found to be decreased after multiple imputation analysis. Further research on the long-term risks and benefits of TXA usage in the military population is recommended.Level of evidenceIV—therapeutic.

Novel approaches to ameliorating chronic kidney disease (CKD) are warranted as most patients are undiagnosed until they begin displaying symptoms of kidney failure. There is increasing evidence that a whole food plant-based (WFPB) diet may offer benefits that slow the progression of CKD, decrease the incidence cardiovascular disease, decrease rates of diabetes and obesity, and reduce inflammation and cholesterol, which in turn can delay kidney failure and the initiation of dialysis. While animal-based protein ingestion promotes an acidic environment, inflammation and renal hyperfiltration, study authors report plant-based protein can be alkaline-producing and anti-inflammatory and can contain renoprotective properties. Although there may be benefits to adopting a WFPB diet, macronutrient and micronutrient content should be carefully considered and adjusted to avoid malnutrition in CKD patients. Further research needs to be done in order to establish the biological plausibility and feasibility of a WFPB in individuals with diagnosed CKD.

The metabolically unhealthy normal weight (MUN) and metabolically healthy obese (MHO) phenotypes are abnormal metabolic states. The purpose of this study was to report the frequency of the strictly defined MHO and MUN phenotypes and the association between metabolic phenotype and 10-year Framingham cardiovascular disease (CVD) risk score using a sample taken from the 2015-2016 National Health and Nutrition Examination Survey.A cross-sectional sample of 2,316 participants age 18-79 years with complete metabolic health information were selected from the 2015-2016 dataset and included in the present analysis. Metabolic health was defined as the absence of all metabolic abnormalities as outlined by the National Cholesterol Education Program Adult Treatment Panel III criteria, excluding waist circumference. Obesity was defined as body mass index ≥30 kg/mFrequency of the MHO phenotype was 5.5% and the MUN was 44.3%. After adjustment for all covariates, Framingham CVD risk score was higher in the MUN (b = 1.74,p 0.001) and metabolically unhealthy obese (b = 3.32,p 0.001) phenotypes that used BMI to define obesity, and the MHO phenotype had a slight protective effect (b = -2.25,p 0.001) when waist circumference was used as the measure of obesity.Metabolically unhealthy phenotypes had higher CVD risk, while the MHO phenotype was not at any greater risk than the metabolically healthy normal weight.