Background and Aims Currently, there are calculation tools that predict the risk of fractures (fx), one of which is the Fracture Risk Assessment Tool (FRAX®). Patients with advanced chronic kidney disease (CKD) have a higher risk of fx than the general population and it is an independent factor for fx. However, this tool does not consider the presence or absence of CKD, where alterations in bone mineral metabolism have important clinical consequences and their prevention should be the objective of CKD control. The aim of our study is to evaluate the FRAX® tool in patients with advanced CKD and to analyze possible relationships with parameters of bone mineral metabolism. Method Observational, descriptive, retrospective study of a series of cases of patients with advanced chronic kidney disease in our center, where demographic data, FRAX® calculation, personal history of Diabetes Mellitus, etiology of CKD, personal history of fx, measurement of bone mineral densitometry by dual energy X-ray absorptiometry (DXA), estimated glomerular filtration rate (CKD-EPI), levels of serum calcium and phosphorus, vitamin D 1. 25 levels, Parathyroid hormone (PTH), fibroblast growth factor 23 (FGF-23), use of phosphorus chelating treatment and vitamin D were collected. Descriptive results of continuous variables are expressed as mean and standard deviation or median and interquartile range (IQR) according to their distribution. For categorical data, frequency and percentage are reported. To analyze the impact of the variables on the event to be studied, a univariate and multivariate Cox regression model was used. Results 59 patients with advanced CKD with DXA performed within one year of the FRAX® analysis were analyzed. The median age was 66 years (IQR 22). 59.3% were male. 35.6% had a personal history of diabetes mellitus. The most frequent etiology of CKD was unknown etiology (18.6%), followed by vascular (16.9%). History of some type of fx:13.6% (3.6% vertebral). Estimated glomerular filtration rate CKD-EPI: 20.7 ml/min/1,73 m2 (IQR 7.5). 16.9% had osteoporosis of the femoral neck and 22% of the spine. DXA decreased in femoral neck 78% and in spine 59.3%. Low risk of major osteoporotic fracture according to FRAX® of 76.3% and 64.3% (without and with DXA) and elevated risk of major osteoporotic fracture according to FRAX® 5.1% and 8.5% (without and with DXA). Risk of hip fracture 25.4% and 30.5% (without and with DXA). These data are summarized in Figure 1 and Figure 2. In the multivariate analysis there is no relationship between bone mineral metabolism parameters and DXA. The results showed a negative correlation between glomerular filtration rate CKD-EPI and FRAX® hip (HR -1.7; 95% CI 1.46-9.6 p = 0.027) which would suggest an association between loss of renal function and loss of DXA. Patients with diabetes mellitus have a higher risk of fx (HR 3.7; 95% CI 1.46-9.6 p = 0.009). Conclusion In patients with advanced CKD, FRAX® index identifies patients at high fracture risk for whom active treatment for osteoporosis should be instituted. In patients with advanced chronic kidney disease, FRAX® underestimates those patients with decreased bone mass and elevated risk of osteoporosis. We did not find any association with biochemical parameters of bone mineral metabolism which could guide us in anticipating the treatment of osteoporosis. The loss of renal function accelerates the loss of bone mass, so we believe that the introduction of this variable is necessary in the equation, especially in this profile of patients.
Background and Aims Elderly patients with Advanced Chronic Kidney Disease (ACKD) present high cardiovascular comorbidity and increased mortality risk. The CKD-G4+ risk calculator was developed by Grams specifically for the population with CKD G4 and analyzes the risk of requiring kidney replacement therapy (KRT), cardiovascular events and death. Ours aims was validation of the Grams score as a prognostic tool in patients with CKD G4 aged over 65 years old in our hospital area. Method Descriptive and retrospective non-randomized study of a cohort of patients older than 65 years with CKD G4 attending for the first time for consultation during 2016 and 2017. Follow-up for 4 years or first clinical event defined as need for KRT, eGFR < = 8 ml/min/1.72 m2 or death. Demographic and clinical data were collected for Grams model risk calculation (age, sex, CKD-EPI eGFR, urine albumin/creatinine ratio (CAC), systolic blood pressure (SBP), diabetes, smoking, cardiovascular history, non-fatal cardiovascular event (CHF, AMI, stroke) and death). SPSS statistical analysis. Results Of 663 patients who started follow-up in ACKD consultations in our hospital area between 2016 and 2017, 303 patients who met inclusion criteria were analyzed, 31 were excluded due to loss to follow-up. The clinical characteristics of the studied population are collected in Table 1. The results are collected in Table 2, they include predicted and observed incidences of death, KRT onset and cardiovascular events in 2 and 4 years from the first visit. Predictors used in this study included Grams calculator risk scores at 2 and 4 years (Grams-2 and Grams-4,respectively) for any KRT, cardiovascular events, and death. Conclusion In our cohort of patients with G4 ACKD older than 65 years old, the Grams score provides good discrimination to significantly predict the onset of KRT and cardiovascular events. The risk of death was moderately accurate and should be taken into account for care planning. Further external validation studies are required.
Background and Aims In patients with Advanced Chronic Kidney Disease (ACKD) stage G4 it is necessary to use prognostic tools to predict the need for Kidney Replacement Therapy (KRT), especially in elderly patients, the most used is the Kidney Failure Risk Equation (KFRE). The Grams Score (GS) predicts the risk of KRT, cardiovascular events and mortality, providing better prediction for the choice of KRT modality but requires more parameters in its equation. Ours objective was compare both KFRE and GS prognostic equations to validate which one better predicts the onset of KRT. Method Descriptive, retrospective study of a cohort of patients older than 65 years with G4 CKD attending for the first time in 2016–2017. Follow-up for 5 years or first clinical event defined as need for KRT (including Conservative Renal Treatment with GFR = <8 ml/min/1.72m2) or death. Variables needed to calculate KFRE and GS were collected, as well as events occurred. Results 271 patients who met the inclusion criteria were analyzed. The clinical characteristics are shown in Table 1. The Grams model showed good discrimination for initiating KRT at 2 and 4 years, AUC 0.84 [95%CI 0.77-0.91] and AUC 0.81 [95%CI 0.75-0.87], respectively. The ROC curves presented by both equations showed good discrimination, AUC 0.82 [95%CI 0.74-0.91] and AUC 0.80 [95%CI 0.74-0.87].When comparing the need for 2-year KRT with both equations, we observed both ROC curves were similar (p = 0.356). Table 2 shows results from logistic regression analysis. For the 2-year KRT event by Grams, patients with a score > = 17.85% were 11.53 [95%CI 5.16-27.78] times more likely to initiate KRT. However, compared to KFRE with a score > = 20.77%, they had 17.53 [95%CI 7.59-40.47] times higher probability of KRT (both p<0.001). When we compared both equations in multivariate analysis only the KFRE was significant (ODR 0.217 (95%CI 0.87-0.54). Conclusion In our population, both prognostic equations showed good discrimination to program initiation of KRT. However, the GS could underestimate this need while the KFRE seems to discriminate it better.
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