Objective To assess the relationship between the change in fluid overload at 48 h after initiation of continuous renal replacement therapy (CRRT) and 28-day mortality in critically ill patients with acute kidney injury (AKI). Methods A retrospective cohort study was performed using data from the MIMIC-IV database from 2008 to 2019. Patients who received CRRT for AKI for more than 24 h within 14 d of admission to the intensive care unit were included. The exposure variable was the proportion of change of fluid overload (ΔFO%, defined as the difference between body weight normalized fluid input and output) at 48 h after CRRT initiation, and the endpoint was 28-day mortality. Generalized additive linear regression models and logistic regression models were used to determine the relationship between the exposure and endpoint. Results A total of 911 patients were included in the study, with a median (lower quartile, upper quartile) ΔFO% of −3.27% (−6.03%, 0.01%) and a 28-day mortality of 40.1%. Generalized additive linear regression model showed that the ΔFO% at 48 h after CRRT initiation was associated with a J-shaped curve with 28-day mortality. After adjusting for other variables, as compared with the second quartile of ΔFO% group, the first quartile group [odds ratio (OR)=1.23, 95% confidence interval (CI) (0.81, 1.87), P=0.338] was not associated with higher risk of 28-day mortality, while the third quartile group [OR=1.54, 95%CI (1.01, 2.35), P=0.046] and the fourth quartile group [OR=2.05, 95%CI (1.32, 3.18), P=0.001] were significantly associated with higher risk of 28-day mortality. There was no significant relationship between ΔFO% groups and 28-day mortality in the first 24-hour after CRRT initiation (P>0.05), but there was a linear relationship between ΔFO% and 28-day mortality in the second 24-hour after CRRT initiation, the larger the ΔFO%, the higher the mortality rate [OR=1.10, 95%CI (1.04 1.16), P<0.001 for per 1% increase]. ConclusionIn critically ill patients with AKI, the ΔFO% greater than −3.27% within 48 h after CRRT initiation is independently associated with an increased risk of 28-day mortality, and the goals of CRRT fluid management may be dynamical.
Objective To observate the influencing factors on circuit life during continuous renal replacement therapy (CRRT) with regional citrate anticoagulation (RCA), so as to provide data support for further optimization of RCA anticoagulation strategy. MethodsPatients who underwent CRRT with RCA in West China Hospital of Sichuan University between March 2021 and April 2022 were retrospectively selected. Analyze the basic information of patients and the impact of relevant indicators before or within 12 hours of treatment on the circuit life. Results A total of 116 patients were included. Among the included patients, a total of 225 cases were treated with CRRT for 11 051.7 hours, the median circuit life was 57.0 (25.4, 72.0) h. 142 cases (63.1%) were terminated due to coagulation, the median circuit life was 30.3 (20.5, 52.8) h. The results of multivariate Cox regression analysis showed that pH value [hazard ratio (HR)=0.002, 95% confidence interval (CI) (0.0001, 0.127), P=0.003], the maximam postfilter ionized calcium [HR=0.039, 95%CI (0.004, 0.437), P=0.008], blood flow [HR=1.051, 95%CI (1.027, 1.075), P<0.001] and catheter dysfunction [HR=5.701, 95%CI (3.777, 8.605), P<0.001] were the four influential factors affected circuit life. Kaplan Meier survival curve showed that RCA had the best effect when the postfilter ionized calcium was in the range of 0.25 ~ 0.35 mmol/L. Conclusions During CRRT treatment of RCA, pH value, postfilter ionized calcium, blood flow and catheter function are the independent influencing factors of circuit life. The above parameters should be carefully monitored and optimized in the treatment process to minimize the risk of coagulation, prolong the circuit life and maintain the continuty of CRRT treatment. The postfilter ionized calcium was recommended to be maitained at 0.25-0.35mmol/L, pH value maintained above 7.38, blood flow no more than 145 mL/min and catheter maitained patency to ensure the adequate anticoagulation.
Continuous renal replacement therapy (CRRT) originated from intermittent hemodialysis. Over the past 40 years, its application scope has gradually expanded from the initial treatment of kidney diseases alone to the support of multi-organ functions. As a safe, adequate, and flexible therapeutic modality, CRRT has become one of the main means of treating critically ill patients. Continuous innovation in technology, biomaterials and other technologies provides important driving force for the sustainable development of CRRT. This paper reviews the technological innovation and development of CRRT devices. With continuous technological updates and iteration, CRRT can better adapt to clinical needs. Biofeedback, portability, and intelligence are several directions of the development of CRRT, which can provide more accurate and personalized treatment for critically ill patients in different scenarios.
Objective To estimate the cost of continuous renal replacement therapy (CRRT) in public hospitals and analyze the main influencing factors of the cost, in order to provide evidence for the optimal application of CRRT technology. Methods In March 2021, activity-based costing was used to estimate and analyze the cost of CRRT, the data of which were collected from 5 hospitals in Jiangsu, Zhejiang, Henan, Sichuan and Xinjiang, and single factor sensitivity analysis was used to find the main influencing factors of the cost. Results The hourly treatment costs of CRRT in the 5 hospitals ranged from 265.30 to 474.44 yuan, with an average of 376.81 yuan. The costs of manpower and filters accounted for the top two largest proportions, the manpower cost of continuous veno-venous hemofiltration and continuous veno-venous hemodiafiltration accounted for 22.90% and 21.51%, respectively, and the filters cost of the two types of CRRT accounted for 15.07% and 17.73%, respectively. The unit cost and cost composition varied greatly between hospitals. There were four factors affecting the unit cost, namely clinical operation, efficiency, price and patient, among which clinical operation difference was the primary factor leading to cost difference. Conclusions The application cost of CRRT technology varies greatly among hospitals, and there are many factors affecting the cost. Public hospitals face great pressure in cost control. It is necessary to strengthen the internal control operation management of public hospitals, establish CRRT clinical operation standards, and improve the quality of medical services in public hospitals.
Currently, there is a lack of guidelines and consensuses on hospital infection prevention and control for continuous renal replacement therapy (CRRT) at home and aboard. Given that in-hospital infection control for CRRT differs from that for intermittent hemodialysis, the Nephrology Brunch of Sichuan International Medical Exchange & Promotion Association, in collaboration with West China Hospital of Sichuan University, has established an expert consensus group for CRRT hospital infection prevention and control. The group conducted systematic retrieval, data analysis, and expert consultation on the thematic content, and developed five topics: occupational protection for CRRT healthcare personnel, CRRT catheter-related infections, collection of CRRT blood/waste specimens, disinfection of CRRT machines, and utilization and disposal of CRRT consumables and waste. The aim is to standardize clinical practices, prevent nosocomial infections, and enhance awareness among healthcare personnel regarding infection prevention and control in CRRT settings.
In continuous renal replacement therapy (CRRT), the combination of medicine and engineering is propelling advancements in therapeutic technology. By enhancing the biocompatibility and specific adsorption capabilities of the blood adsorption materials, the therapeutic efficacy of CRRT is augmented, leading to a reduction in adverse reactions for patients. Moreover, the application of big data and artificial intelligence in CRRT is continually being developed. Utilizing intelligent devices, data analysis, and machine learning, the initiation, monitoring, and formulation of CRRT treatment plans are optimized, providing clinical patients with more efficient and secure therapeutic options, thereby further improving clinical outcomes.
ObjectiveTo investigate the risk factors of death in patients undergoing continuous renal replacement therapy (CRRT) after cardiac surgery. MethodsWe retrospectively analyzed records of 66 adult patients without history of chronic renal failure suffering acute kidney injury (AKI) following cardiac surgery and undergoing CRRT in our hospital between July 2007 and June 2014. There were 38 males and 28 females with mean age of 59.11±12.62 years. They were divided into a survival group and a non-survival group according to prognosis at discharge. All perioperative data were collected and analyzed by univariate analysis and multivariate logistic regression analysis. ResultsIn sixty-six adult patients, eighteen patients survived with a mortality rate of 72.7%. Through univariate analysis and multivariate logistic regression, risk factors of death in the post-operative AKI patients requiring CRRT included hypotension on postoperative day 1 (B=2.897, OR=18.127, P=0.001), duration of oliguria until hemofiltration (B=0.168, OR=1.183, P=0.024), and blood platelet on postoperative day 1 (B=-0.026, OR=0.974, P=0.001). ConclusionHypotension on postoperative day 1 (POD1) is the predominant risk factor of death in patients requiring CRRT after cardiac surgery, while blood platelet on POD1 is a protective factor. If CRRT is required, the sooner the better.
Continuous renal replacement therapy (CRRT) is a term of blood purification technique that can continuously remove the body's solute and water for 24 hours without any interruption throughout each day. It has several advantages such as hemodynamic stability, accurate capacity control, stable internal environment, and inflammatory regulation, which is especially suitable for patients with severe hemodynamic instability. In clinical practice, critically ill patients treated with CRRT are often associated with different types of acidosis, including metabolic acidosis, lactic acidosis, citrate acidosis, ketoacidosis and hypercapnic acidosis. Different types of acidosis can be treated in different ways. This paper reviews the CRRT for special types of acidosis.
Continuous renal replacement therapy (CRRT) is one of the important therapeutic techniques for critically ill patients. In recent years, the field of artificial intelligence has developed rapidly and has been widely applied in manufacturing, automotive, and even daily life. The development and application of artificial intelligence in the medical field are also advancing rapidly, and artificial intelligence radiographic imaging result judgment, pathological result judgment, patient prognosis prediction are gradually being used in clinical practice. The development of artificial intelligence in the field of CRRT has also made rapid progress. Therefore, this article will elaborate on the current application status of artificial intelligence in CRRT, as well as its future prospects in CRRT, so as to provide a reference for understanding the application of artificial intelligence in CRRT.
Continuous renal replacement therapy (CRRT) is one of the major treatments for critically ill patients. With the development of information technology, the informatization and artificial intelligent of CRRT has received wide attention, which has promoted the optimization of CRRT in terms of workflow, teaching method as well as scientific research. Benefiting from the big data generated, artificial intelligence is expected to be applied in the precision treatment, quality control, timing of intervention, as well as prognosis assessment in severe AKI, so as to ultimately improve the therapeutic effect of CRRT among critically ill patients. This paper summarizes the information construction of CRRT and the research progress of artificial intelligence, which can be used as a reference for practitioners in kidney disease, critical medicine, emergency medicine and other related fields.