scholarly journals Clinical Features and Outcomes of Acute Kidney Injury in Patients Infected with COVID-19 in Xiangyang, China

2020 ◽  
pp. 1-7
Author(s):  
Hai Yuan ◽  
Jingjing Liu ◽  
Zhao Gao ◽  
Fengqi Hu

<b><i>Background:</i></b> In December 2019, pneumonia associated with COVID-19 has spread from Wuhan to other areas in China. In the present study, we aimed to further clarify the clinical features and outcomes of acute kidney injury (AKI) in patients infected with COVID-19 in Xiangyang, Hubei, China. <b><i>Methods:</i></b> All confirmed cases of COVID-19 with AKI in Xiangyang Central Hospital from January 22 to May 31, 2020, were included in this retrospective study. Data of epidemiological, clinical, laboratory, radiological tests, treatment, complication, and outcomes were collected and analyzed. Patients were divided into intensive care unit (ICU) group and isolation ward (non-ICU) group. <b><i>Results:</i></b> Of the total patients, 33.3% in the non-ICU group and 85.7% in the ICU group had chronic diseases. In addition, 85.7% of patients in the ICU group died. The most common symptoms were fever, cough, and fatigue. The lymphocyte count in the ICU group was significantly reduced compared with the non-ICU group. The chest computed tomography (CT) images appeared showed multiple mottles and ground-glass opacity. Strip shadow could be found in chest CT images of some recovered patients. All patients received antiviral treatment. Most patients in the ICU group were given methylprednisolone, immunoglobulin, antibiotics, and mechanical ventilation and 35.7% of patients in the ICU group received continuous renal replacement therapy. <b><i>Conclusions:</i></b> Elderly with chronic comorbidities were more susceptible to COVID-19, showing a higher mortality rate due to multiple organ damage, and 35.7% of patients with AKI in ICU received renal replacement therapy. Moreover, part of the cured patients might need additional time to recover for poor lung function.

2016 ◽  
Vol 19 (3) ◽  
pp. 123 ◽  
Author(s):  
Orhan Findik ◽  
Ufuk Aydin ◽  
Ozgur Baris ◽  
Hakan Parlar ◽  
Gokcen Atilboz Alagoz ◽  
...  

<strong>Background:</strong> Acute kidney injury is a common complication of cardiac surgery that increases morbidity and mortality. The aim of the present study is to analyze the association of preoperative serum albumin levels with acute kidney injury and the requirement of renal replacement therapy after isolated coronary artery bypass graft surgery (CABG).<br /><strong>Methods:</strong> We retrospectively reviewed the prospectively collected data of 530 adult patients who underwent isolated CABG surgery with normal renal function. The perioperative clinical data of the patients included demographic data, laboratory data, length of stay, in-hospital complications and mortality. The patient population was divided into two groups: group I patients with preoperative serum albumin levels &lt;3.5 mg/dL; and group II pateints with preoperative serum albumin levels ≥3.5 mg/dL.<br /><strong>Results:</strong> There were 413 patients in group I and 117 patients in group II. Postoperative acute kidney injury (AKI) occured in 33 patients (28.2%) in group I and in 79 patients (19.1%) in group II. Renal replacement therapy was required in 17 patients (3.2%) (8 patients from group I; 9 patients from group II; P = .018). 30-day mortality occurred in 18 patients (3.4%) (10 patients from group I; 8 patients from group II; P = .037). Fourteen of these patients required renal replacement therapy. Logistic regression analysis revealing the presence of lower serum albumin levels preoperatively was shown to be associated with increased incidence of postoperative AKI (OR: 1.661; 95% CI: 1.037-2.661; <br />P = .035). Logistic regression analysis also revealed that DM (OR: 3.325; 95% CI: 2.162-5.114; P = .000) was another independent risk factor for AKI after isolated CABG. <br /><strong>Conclusion:</strong> Low preoperative serum albumin levels result in severe acute kidney injury and increase the rate of renal replacement therapy and mortality after isolated CABG.


2018 ◽  
Vol 51 (2) ◽  
pp. 141-148
Author(s):  
Shigeo Negi ◽  
Daisuke Koreeda ◽  
Masaki Higashiura ◽  
Takuro Yano ◽  
Sou Kobayashi ◽  
...  

2021 ◽  
pp. 1-7
Author(s):  
Pattharawin Pattharanitima ◽  
Akhil Vaid ◽  
Suraj K. Jaladanki ◽  
Ishan Paranjpe ◽  
Ross O’Hagan ◽  
...  

Background/Aims: Acute kidney injury (AKI) in critically ill patients is common, and continuous renal replacement therapy (CRRT) is a preferred mode of renal replacement therapy (RRT) in hemodynamically unstable patients. Prediction of clinical outcomes in patients on CRRT is challenging. We utilized several approaches to predict RRT-free survival (RRTFS) in critically ill patients with AKI requiring CRRT. Methods: We used the Medical Information Mart for Intensive Care (MIMIC-III) database to identify patients ≥18 years old with AKI on CRRT, after excluding patients who had ESRD on chronic dialysis, and kidney transplantation. We defined RRTFS as patients who were discharged alive and did not require RRT ≥7 days prior to hospital discharge. We utilized all available biomedical data up to CRRT initiation. We evaluated 7 approaches, including logistic regression (LR), random forest (RF), support vector machine (SVM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), multilayer perceptron (MLP), and MLP with long short-term memory (MLP + LSTM). We evaluated model performance by using area under the receiver operating characteristic (AUROC) curves. Results: Out of 684 patients with AKI on CRRT, 205 (30%) patients had RRTFS. The median age of patients was 63 years and their median Simplified Acute Physiology Score (SAPS) II was 67 (interquartile range 52–84). The MLP + LSTM showed the highest AUROC (95% CI) of 0.70 (0.67–0.73), followed by MLP 0.59 (0.54–0.64), LR 0.57 (0.52–0.62), SVM 0.51 (0.46–0.56), AdaBoost 0.51 (0.46–0.55), RF 0.44 (0.39–0.48), and XGBoost 0.43 (CI 0.38–0.47). Conclusions: A MLP + LSTM model outperformed other approaches for predicting RRTFS. Performance could be further improved by incorporating other data types.


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