Clinical Implications of Estimating Glomerular Filtration Rate with Different Equations in Heart Failure Patients with Preserved Ejection Fraction.

INTRODUCTION: The prognostic values of estimated glomerular filtration rate (eGFR) calculated by different formulas have not been adequately compared in patients with heart failure with preserved ejection fraction (HFpEF). AIM: We compared the predictive values of serum creatinine-based eGFRs calculated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation, Modification of Diet in Renal Disease Study (MDRD) formula, and full-age-spectrum creatinine (FAS Cr) equation in 1751 HFpEF patients. METHODS: The area under the receiver-operating characteristic curve (AUC), integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were employed. RESULTS: eGFR values were lowest calculated with FAS Cr equation (p < 0.001). When patients were classified into 4 subgroups (eGFR ≥ 90, 89-60, 59-30, and  < 30 ml/min/1.73 m2) or only 2 subgroups (≥ 60 or  < 60 ml/min/1.73 m2), the 3 formulas correlated significantly, with the best correlation found between the MDRD and CKD-EPI formulas (kappa = 0.871 and 0.963, respectively). The 3 formulas conveyed independent prognostic information. After adjusting for potential cofounders, risk prediction for all-cause mortality was more accurate (p = 0.001) using the CKD-EPI equation than MDRD formula as assessed by AUC. Compared with MDRD formula, CKD-EPI equation exhibited superior predictive ability assessed by IDI and NRI of 0.32% (p < 0.001)/10.4% (p = 0.010) for primary endpoint and 0.37% (p = 0.010)/10.8% (p = 0.010) for HF hospitalization. The risk prediction for deterioration of renal function was more accurate (p ≤ 0.040) using the CKD-EPI equation than FAS Cr equation as assessed by AUC, IDI, and NRI. CONCLUSION: The CKD-EPI formula might be the preferred creatinine-based equation in clinical risk stratification in HFpEF patients.

RACK1 promotes autophagy via the PERK signaling pathway to protect against traumatic brain injury in rats.

AIMS: Neuronal cell death is a primary factor that determines the outcome after traumatic brain injury (TBI). We previously revealed the importance of receptor for activated C kinase (RACK1), a multifunctional scaffold protein, in maintaining neuronal survival after TBI, but the specific mechanism remains unclear. The aim of this study was to explore the mechanism underlying RACK1-mediated neuroprotection in TBI. METHODS: TBI model was established using controlled cortical impact injury in Sprague-Dawley rats. Genetic intervention and pharmacological inhibition of RACK1 and PERK-autophagy signaling were administrated by intracerebroventricular injection. Western blotting, coimmunoprecipitation, transmission electron microscopy, real-time PCR, immunofluorescence, TUNEL staining, Nissl staining, neurobehavioral tests, and contusion volume assessment were performed. RESULTS: Endogenous RACK1 was upregulated and correlated with autophagy induction after TBI. RACK1 knockdown markedly inhibited TBI-induced autophagy, whereas RACK1 overexpression exerted the opposite effects. Moreover, RACK1 overexpression ameliorated neuronal apoptosis, neurological deficits, and cortical tissue loss after TBI, and these effects were abrogated by the autophagy inhibitor 3-methyladenine or siRNAs targeting Beclin1 and Atg5. Mechanistically, RACK1 interacted with PERK and activated PERK signaling. Pharmacological and genetic inhibition of the PERK pathway abolished RACK1-induced autophagy after TBI. CONCLUSION: Our findings indicate that RACK1 protected against TBI-induced neuronal damage partly through autophagy induction by regulating the PERK signaling pathway.