Acute Kidney Injury in Patients Undergoing Total Hip Arthroplasty: A Systematic Review and Meta-Analysis

Abstract

Background: The number of total hip arthroplasties (THA) performed across the world is growing rapidly. We performed this meta-analysis to evaluate the incidence of acute kidney injury (AKI) in patients undergoing THA. Methods: A literature search was performed using MEDLINE, EMBASE and Cochrane Database from inception until July 2018 to identify studies assessing the incidence of AKI (using standard AKI definitions of RIFLE, AKIN, and KDIGO classifications) in patients undergoing THA. We applied a random-effects model to estimate the incidence of AKI. The protocol for this meta-analysis is registered with PROSPERO (no. CRD42018101928). Results: Seventeen cohort studies with a total of 24,158 patients undergoing THA were enrolled. Overall, the pooled estimated incidence rates of AKI and severe AKI requiring dialysis following THA were 6.3% (95% CI: 3.8%–10.2%) and 0.5% (95% CI: 0.1%–2.3%). Subgroup analysis based on the countries by continent was performed and demonstrated the pooled estimated incidence of AKI following THA of 9.2% (95% CI: 5.6%–14.8%) in Asia, 8.1% (95% CI: 4.9%–13.2%) in Australia, 7.4% (95% CI: 3.2%–16.3%) in Europe, and 2.8% (95% CI: 1.2%–17.0%) in North America. Meta-regression of all included studies showed significant negative correlation between incidence of AKI following THA and study year (slope = −0.37, p <0.001). There was no publication bias as assessed by the funnel plot and Egger’s regression asymmetry test with p = 0.13 for the incidence of AKI in patients undergoing THA. Conclusion: The overall estimated incidence rates of AKI and severe AKI requiring dialysis in patients undergoing THA are 6.3% and 0.5%, respectively. There has been potential improvement in AKI incidence for patients undergoing THA over time.

Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation

“…Those needs that are classified as unmet require provision of some ample spaces for the purpose of imagination in relation to leveraging the strength associated with big data, as well as relevant artificial intelligence (AI) to improve the overall status of patients with kidney diseases [25]. In this article, we discuss the big data concepts in nephrology, describe the potential use of AI in nephrology and transplantation, and also encourage researchers and clinicians to submit their invaluable research, including original clinical research studies [26][27][28][29][30], database studies from registries [31][32][33], meta-analyses [34][35][36][37][38][39][40][41][42][43][44], and artificial intelligence research [25,[45][46][47][48] in nephrology and transplantation. Table 1 demonstrates known and commonly used databases that have provided big data in nephrology and transplantation [49][50][51].…”

A Meta-Analysis of Acute Kidney Injury in Patients Undergoing Hip Fracture Surgery: Prevalence and Risk Factors

“…A previous meta-analysis showed that the overall estimated prevalence rates of AKI in patients undergoing total hip arthroplasties are 6.3%. 26 Obviously, the prevalence of AKI following total hip arthroplasties was lower than that in patients undergoing hip fracture surgery. Regardless of the fact that the exact causes for these differences were largely unclear, but surgical workers should attach more importance to the potential AKI in patients undergoing hip fracture surgery.…”

“…4,5 Worse still, it has been estimated that AKI results in a considerably mortality (1.7 million deaths per year) globally. 4,5 Notably, AKI is a common postoperative complication in patients undergoing surgical interventions for hip fracture, which closely correlated with prolonged hospital stay, various morbidity and increased mortality 6,7 Therefore, to adequately understand the landscape of prevalence and risk factors of AKI may largely help to improve outcomes of patients undergoing hip fracture surgery. Nevertheless, the reported prevalence of AKI associated with hip fracture surgery ranged widely from 5-60% currently.…”

Novel Biomarkers in Patients with Chronic Kidney Disease: An Analysis of Patients Enrolled in the GCKD-Study

“…In patients with chronic kidney disease (CKD), a high burden of cardiovascular diseases (CVD) is common, and an inverse correlation of renal function with the prevalence of coronary artery disease, congestive heart failure, and cerebrovascular disease is observed [1,50]. Moreover, the incidence of acute kidney injury has been steadily increasing in recent years, leading to higher healthcare costs and mortality and contributing to increasing prevalence rates of CKD [51,52]. With an increasing prevalence of CKD from variable causes, the number of patients with end-stage renal disease is on the rise [1,53].…”