OBJECTIVE: To explore the risk factors for poor prognosis in sepsis-associated acute kidney injury (SA-AKI) and establish a nomogram predictive model. METHODS: The clinical data of patients with SA-AKI admitted to the department of critical care medicine of Shandong Provincial Hospital Affiliated to Shandong First Medical University from January 2019 to September 2022 were retrospectively analyzed, including demographic information, worst values of blood cell counts and biochemical indicators within 24 hours of SA-AKI diagnosis, whether the patient received renal replacement therapy (RRT), mechanical ventilation, vasopressor therapy during hospitalization, acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA), fibrinogen-to-albumin ratio (FAR) within 24 hours of diagnosis, acute kidney injury (AKI) staging, total length of hospital stay, length of intensive care unit (ICU) stay, and others. According to the 28-day outcome, the patients were divided into survival group and death group, and the indicators between the two groups were compared. Univariate and multivariate Logistic regression analyses were used to screen for risk factors associated with mortality in SA-AKI patients. A nomogram predictive model for SA-AKI prognosis was constructed based on the identified risk factors. Receiver operator characteristic curve (ROC curve) and calibration plots were generated to evaluate the predictive value of the nomogram model for SA-AKI prognosis. RESULTS: A total of 113 SA-AKI patients were included, with 67 in the survival group and 46 in the death group. The 28-day mortality among SA-AKI patients was 40.7%. The comparison between the two groups showed that there were statistically significant differences in age ≥ 65 years, AKI stage, mechanical ventilation, vasopressors, RRT, length of ICU stay, and laboratory indicators cystatin C (Cys C), fibrinogen (Fib), and FAR. Multivariate Logistic regression analysis showed that age ≥ 65 years [odds ratio (OR) = 7.967, 95% confidence interval (95%CI) was 1.803-35.203, P = 0.006], cystatin C (OR = 7.202, 95%CI was 1.756-29.534, P = 0.006), FAR (OR = 2.444, 95%CI was 1.506-3.968, P < 0.001), and RRT (OR = 7.639, 95%CI was 1.391-41.951, P = 0.019) were independent risk factors for mortality in SA-AKI patients. ROC curve analysis showed that the area under the ROC curve (AUC) for age ≥ 65 years, cystatin C, FAR, and RRT in predicting SA-AKI patient mortality were 0.713, 0.856, 0.911, and 0.701, respectively. A nomogram predictive model for SA-AKI patient prognosis was constructed based on age ≥ 65 years, cystatin C, FAR, and RRT, with an AUC of 0.967 (95%CI was 0.932-1.000) according to ROC curve analysis. The calibration plot indicated good consistency between predicted and actual probabilities. CONCLUSIONS Age ≥ 65 years, cystatin C, FAR, and RRT are independent risk factors for mortality in SA-AKI patients. The nomogram predictive model based on these four factors can accurately predict SA-AKI patient prognosis, helping physicians adjust treatment strategies in a timely manner and improve patient outcomes.
Humans ; Aged ; Cystatin C ; Retrospective Studies ; Intensive Care Units ; Sepsis/diagnosis* ; Acute Kidney Injury/therapy* ; Prognosis ; ROC Curve ; Fibrinogen

OBJECTIVE: To investigate the association between the glucose-to-lymphocyte ratio (GLR) and prognosis of patients with sepsis-associated acute kidney injury (SA-AKI). METHODS: Based on the Medical Information Mart for Intensive Care-IV (MIMIC-IV), SA-AKI patients aged ≥ 18 years were selected. According to the tertiles of GLR, the patients were divided into GLR1 group (GLR ≤ 4.97×10^-9 mmol), GLR2 group (4.97×10^-9 mmol < GLR < 9.75×10^-9 mmol) and GLR3 group (GLR ≥ 9.75×10^-9 mmol). Patients with SA-AKI were divided into survival group and death group according to whether they survived 28 days after admission. The patient's gender, age, vital signs, laboratory test results, comorbidities, sequential organ failure assessment (SOFA), acute physiology score III (APS III) score and treatment measures were extracted from the database. Kaplan-Meier survival analysis was used to make the survival curves of patients with SA-AKI at 28 days, 90 days, 180 days and 1 year. Multivariate Logistic regression analysis model was used to explore the independent risk factors of 28-day mortality in patients with SA-AKI. Receiver operator characteristic curve (ROC curve) was used to analyze the predictive efficacy of GLR for the prognosis of patients with SA-AKI. RESULTS: A total of 1 524 patients with SA-AKI were included, with a median age of 68.28 (58.96, 77.24) years old, including 612 females (40.16%) and 912 males (59.84%). There were 507 patients in the GLR1 group, 509 patients in the GLR2 group and 508 patients in the GLR3 group. There were 1 181 patients in the 28-day survival group and 343 patients in the death group. Grouping according to GLR tertiles showed that with the increase of GLR, the 28-day, 90-day, 180-day and 1-year mortality of SA-AKI patients gradually increased (28-day mortality were 11.64%, 22.00%, 33.86%, respectively; 90-day mortality were 15.98%, 26.72%, 40.55%, respectively; 180-day mortality were 17.16%, 28.29% and 41.73%, and the 1-year mortality were 17.95%, 29.27% and 42.72%, respectively, all P < 0.01). According to 28-day survival status, the GLR of the death group was significantly higher than that of the survival group [×10^-9 mmol: 9.81 (5.75, 20.01) vs. 6.44 (3.64, 10.78), P < 0.01]. Multivariate Logistic regression analysis showed that GLR was an independent risk factor for 28-day mortality in patients with SA-AKI [when GLR was used as a continuous variable: odds ratio (OR) = 1.065, 95% confidence interval (95%CI) was 1.045-1.085, P < 0.001; when GLR was used as a categorical variable, compared with GLR1 group: GLR2 group OR = 1.782, 95%CI was 1.200-2.647, P = 0.004; GLR3 group OR = 2.727, 95%CI was 1.857-4.005, P < 0.001]. ROC curve analysis showed that the area under the ROC curve (AUC) of GLR for predicting 28-day mortality in patients with SA-AKI was 0.674, when the optimal cut-off value was 8.769×10^-9 mmol, the sensitivity was 57.1% and the specificity was 67.1%. The predictive performance was improved when GLR was combined with APS III score and SOFA score, and the AUC was 0.806, the sensitivity was 74.6% and the specificity was 71.4%. CONCLUSIONS GLR is an independent risk factor of 28-day mortality in patients with SA-AKI, and high GLR is associated with poor prognosis in patients with SA-AKI.
Male ; Female ; Humans ; Blood Glucose ; Glucose ; ROC Curve ; Prognosis ; Sepsis/diagnosis* ; Acute Kidney Injury ; Retrospective Studies ; Intensive Care Units

INTRODUCTION: Creatinine has limitations in identifying and predicting acute kidney injury (AKI). Our study examined the utility of neutrophil gelatinase-associated lipocalin (NGAL) in predicting AKI in patients presenting to the emergency department (ED), and in predicting the need for renal replacement therapy (RRT), occurrence of major adverse cardiac events (MACE) and all-cause mortality at three months post visit. METHODS: This is a single-centre prospective cohort study conducted at Singapore General Hospital (SGH). Patients presenting to SGH ED from July 2011 to August 2012 were recruited. They were aged ≥21 years, with an estimated glomerular filtration rate <60 mL/min/1.73 m², and had congestive cardiac failure, systemic inflammatory response syndrome or required hospital admission. AKI was diagnosed by researchers blinded to experimental measurements. Serum NGAL was measured as a point-of-care test. RESULTS: A total of 784 patients were enrolled, of whom 107 (13.6%) had AKI. Mean serum NGAL levels were raised (P < 0.001) in patients with AKI (670.0 ± 431.9 ng/dL) compared with patients without AKI (490.3 ± 391.6 ng/dL). The sensitivity and specificity of NGAL levels >490 ng/dL for AKI were 59% (95% confidence interval [CI] 49%-68%) and 65% (95% CI 61%-68%), respectively. Need for RRT increased 21% per 100 ng/dL increase in NGAL (P < 0.001), whereas odds of death in three months increased 10% per 100 ng/dL increase in NGAL (P = 0.028). No clear relationship was observed between NGAL levels and MACE. CONCLUSION Serum NGAL identifies AKI and predicts three-month mortality.
Humans ; Lipocalin-2 ; Prospective Studies ; Lipocalins ; Proto-Oncogene Proteins ; Acute-Phase Proteins ; Biomarkers ; Acute Kidney Injury/diagnosis* ; Emergency Service, Hospital ; Predictive Value of Tests

Objective: To investigate the changes of high density lipoprotein cholesterol (HDL-C) in sepsis patients and its early predictive value for secondary acute kidney injury (AKI) in such patients. Methods: A retrospective case series study was conducted. From June 2019 to June 2021, 232 sepsis patients who met the inclusion criteria were admitted to the Second Hospital of Hebei Medical University, including 126 males and 106 females, aged 24 to 71 years. According to whether complicating secondary AKI, the patients were divided into non-AKI group (n=158) and AKI group (n=74). Data of patients between the two groups were compared and statistically analyzed with independent sample t test or chi-square test, including the sex, age, body mass index (BMI), body temperature, heart rate, primary infection site, combined underlying diseases, acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) score and sepsis-related organ failure assessment (SOFA) score at admission, and the serum levels of C-reactive protein (CRP), procalcitonin, creatinine, cystatin C, and HDL-C measured at diagnosis of sepsis. The multivariate logistic regression analysis was performed on the indicators with statistically significant differences between the two groups to screen the independent risk factors for developing secondary AKI in 232 sepsis patients, and the joint prediction model was established based on the independent risk factors. The receiver operating characteristic (ROC) curve of the independent risk factors and the joint prediction model predicting secondary AKI in 232 sepsis patients were drawn, and the area under the curve (AUC), the optimal threshold, and the sensitivity and specificity under the optimal threshold were calculated. The quality of the above-mentioned AUC was compared by Delong test, and the sensitivity and specificity under the optimal threshold were compared using chi-square test. Results: The sex, age, BMI, body temperature, heart rate, primary infection site, combined underlying diseases, and CRP level of patients between the two groups were similar (P>0.05). The procalcitonin, creatinine, cystatin C, and scores of APACHE Ⅱ and SOFA of patients in AKI group were all significantly higher than those in non-AKI group (with t values of -3.21, -16.14, -12.75, -11.13, and -12.88 respectively, P<0.01), while the HDL-C level of patients in AKI group was significantly lower than that in non-AKI group (t=6.33, P<0.01). Multivariate logistic regression analysis showed that creatinine, cystatin C, and HDL-C were the independent risk factors for secondary AKI in 232 sepsis patients (with odds ratios of 2.45, 1.68, and 2.12, respectively, 95% confidence intervals of 1.38-15.35, 1.06-3.86, and 0.86-2.56, respectively, P<0.01). The AUCs of ROC curves of creatinine, cystatin C, HDL-C, and the joint prediction model for predicting secondary AKI in 232 sepsis patients were 0.69, 0.79, 0.89, and 0.93, respectively (with 95% confidence intervals of 0.61-0.76, 0.72-0.85, 0.84-0.92, and 0.89-0.96, respectively, P values all below 0.01); the optimal threshold were 389.53 μmol/L, 1.56 mg/L, 0.63 mmol/L, and 0.48, respectively; the sensitivity under the optimal threshold were 76.6%, 81.4%, 89.7%, and 95.5%, respectively; the specificity under the optimal threshold values were 78.6%, 86.7%, 88.6%, and 96.6%, respectively. The AUC quality of cystatin C was significantly better than that of creatinine (z=2.34, P<0.05), the AUC quality and sensitivity and specificity under the optimal threshold of HDL-C were all significantly better than those of cystatin C (z=3.33, with χ² values of 6.43 and 7.87, respectively, P<0.01) and creatinine (z=5.34, with χ² values of 6.32 and 6.41, respectively, P<0.01); the AUC quality and sensitivity and specificity under the optimal threshold of the joint prediction model were all significantly better than those of creatinine, cystatin C, and HDL-C (with z values of 6.18, 4.50, and 2.06, respectively, χ² values of 5.31, 7.23, 3.99, 6.56, 7.34, and 4.00, respectively, P<0.05 or P<0.01). Conclusions: HDL-C level in sepsis patients with secondary AKI is significantly lower than that in patients without secondary AKI. This is an independent risk factor for secondary AKI in sepsis patients with a diagnostic value being superior to that of creatinine and cystatin C. The combination of the aforementioned three indicators would have higher predicative valuable for secondary AKI in sepsis patients.
Acute Kidney Injury/etiology* ; Adult ; Aged ; Cholesterol, HDL ; Female ; Humans ; Male ; Middle Aged ; Prognosis ; ROC Curve ; Retrospective Studies ; Sepsis/diagnosis* ; Young Adult

PURPOSE: To investigate the clinical value of urine interleukin-18 (IL-8), neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1) for the early diagnosis of acute kidney injury (AKI) in patients with ureteroscopic lithotripsy (URL) related urosepsis. METHODS: A retrospective study was carried out in 157 patients with urosepsis after URL. The patients were divided into AKI group and non-AKI group according to the Kidigo guideline and urine IL-8, NGAL and KIM-1 levels were detected by enzyme-linked immunosorbent assay at 0, 4, 12, 24 and 48 h after the surgery. Receiver operating characteristic curve (ROC) was used to evaluate the diagnostic value of these three biomarkers for postoperative AKI. RESULTS: The level of urine IL-8, NGAL and KIM-1 in AKI group was significantly higher than that in non-AKI group at 4, 12, 24 and 48 h (p < 0.01). The ROC analysis showed the combined detection of urine IL-8, NGAL and KIM-1 at 12 h had a larger area under curve (AUC) than a single marker (0.997, 95% CI: 0.991-0.998), and the sensitivity and specificity were 98.2% and 96.7%, respectively. Pearson correlation analysis showed that the levels of urine NGAL at 4, 12, 24 and 48 h in AKI patients were positively correlated with the levels of urine KIM-1 and IL-18 (p < 0.01). CONCLUSION AKI could be quickly recognized by the elevated level of urine IL-8, NGAL and KIM-1 in patients with URL-related urosepsis. Combined detection of the three urine biomarkers at 12 h after surgery had a better diagnostic performance, which may be an important reference for the early diagnosis of AKI.
Acute Kidney Injury/etiology* ; Biomarkers ; Early Diagnosis ; Hepatitis A Virus Cellular Receptor 1 ; Humans ; Interleukin-18 ; Interleukin-8 ; Lipocalin-2 ; Lithotripsy ; Retrospective Studies ; Ureteroscopy

Few studies have described the key features and prognostic roles of lung microbiota in patients with severe community-acquired pneumonia (SCAP). We prospectively enrolled consecutive SCAP patients admitted to ICU. Bronchoscopy was performed at bedside within 48 h of ICU admission, and 16S rRNA gene sequencing was applied to the collected bronchoalveolar lavage fluid. The primary outcome was clinical improvements defined as a decrease of 2 categories and above on a 7-category ordinal scale within 14 days following bronchoscopy. Sixty-seven patients were included. Multivariable permutational multivariate analysis of variance found that positive bacteria lab test results had the strongest independent association with lung microbiota (R² = 0.033; P = 0.018), followed by acute kidney injury (AKI; R² = 0.032; P = 0.011) and plasma MIP-1β level (R² = 0.027; P = 0.044). Random forest identified that the families Prevotellaceae, Moraxellaceae, and Staphylococcaceae were the biomarkers related to the positive bacteria lab test results. Multivariable Cox regression showed that the increase in α-diversity and the abundance of the families Prevotellaceae and Actinomycetaceae were associated with clinical improvements. The positive bacteria lab test results, AKI, and plasma MIP-1β level were associated with patients' lung microbiota composition on ICU admission. The families Prevotellaceae and Actinomycetaceae on admission predicted clinical improvements.
Acute Kidney Injury/complications* ; Bacteria/classification* ; Chemokine CCL4/blood* ; Community-Acquired Infections/microbiology* ; Humans ; Lung ; Microbiota/genetics* ; Pneumonia, Bacterial/diagnosis* ; Prognosis ; RNA, Ribosomal, 16S/genetics*

To maintain homeostasis of the cardiovascular system, the heart and kidney act bidirectionally. Therefore, acute or chronic dysfunction of one organ can cause dysfunction in the other. This phenomenon is characterized as cardiorenal syndrome (CRS). Concurrent dysfunction of the heart and kidney adversely affects one another and eventually worsens patient outcomes through a vicious cycle. Although a CRS classification system has been proposed, the underlying pathophysiology is multifactorial and clinical access continues to be difficult. Although several therapies, including agents that target the renin-angiotensin-aldosterone system, have been utilized, there is not enough evidence to demonstrate their effectiveness for CRS. Thus, more effort should be made to optimize the diagnosis and treatment strategies for CRS patients. This review will introduce CRS as it is currently understood, discuss the pathophysiology, and examine management strategies.
Acute Kidney Injury ; Cardio-Renal Syndrome ; Cardiovascular System ; Classification ; Diagnosis ; Heart ; Heart Failure ; Homeostasis ; Humans ; Kidney ; Renal Insufficiency, Chronic ; Renin-Angiotensin System

OBJECTIVE: To explore the predicting performance of renal resistive index (RRI), semi quantitative power Doppler ultrasound (PDU) score and serum cystatin C (Cys C) for acute kidney injury (AKI) in patients with cardiac failure or sepsis. METHODS: A prospective, observational study was conducted. Critically ill patients with acute cardiac failure or sepsis admitted to the emergency intensive care unit (ICU) of Cangzhou Central Hospital from January 1st to December 31st in 2018 were enrolled. In addition to the demographic data, serum Cys C, RRI, and PDU score were measured within 6 hours after admission to ICU. Renal function was assessed on day 5 according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Patients who proceeded to AKI stage 2 or 3 within 5 days from admission were defined as the AKI 2-3 group; other patients were classified into the AKI 0-1 group. The differences of each index were compared in all patients, cardiac failure patients and sepsis patients between the two groups. Multivariate binary Logistic regression was carried out to identify the independent risk predictors of AKI 2-3. Receiver operator characteristic (ROC) curves were plotted to examine the values of Cys C, RRI, PDU score, and RRI+PDU in predicting AKI 2-3. RESULTS: Thirty-seven patients with cardiac failure (11 with no AKI, 10 with AKI stage 1, 3 with AKI stage 2, and 13 with AKI stage 3) and 26 patients with sepsis (8 with no AKI, 2 with AKI stage 1, 7 with AKI stage 2, and 9 with AKI stage 3) were recruited. In all patients as well as the subgroup of cardiac failure, compared with the AKI 0-1 group, acute physiology and chronic health evaluation II (APACHE II) score, sequential organ failure assessment (SOFA) score, rate of continuous renal replacement therapy (CRRT), 28-day mortality, serum creatinine (SCr), Cys C and RRI were higher in AKI 2-3 group, and urine output, PDU score were lower; in the subgroup of sepsis, rate of CRRT, SCr, and Cys C were higher in AKI 2-3 group, and urine output was lower. Multivariate Logistic regression analysis found that Cys C and PDU score were independent risk factors for AKI 2-3 in all patients [Cys C: odds ratio (OR) = 11.294, 95% confidence interval (95%CI) was 2.801-45.541, P = 0.001; PDU score: OR = 0.187, 95%CI was 0.056-0.627, P = 0.007]; RRI and PDU score were independent risk factors for AKI 2-3 in patients with cardiac failure [RRI (×10): OR = 6.172, 95%CI was 0.883-43.153, P = 0.067; PDU score: OR = 0.063, 95%CI was 0.007-0.584, P = 0.015]; Cys C was the independent risk factor for AKI 2-3 in patients with sepsis (OR = 22.830, 95%CI was 1.345-387.623, P = 0.030). It was shown by ROC curve analysis that: in the subgroup of cardiac failure, the predictive values of RRI, PDU score and Cys C were well [area under the curve (AUC) and 95%CI was 0.839 (0.673-0.942), 0.894 (0.749-0.971), 0.777 (0.610-0.897), all P < 0.01]. RRI+PDU performed best in predicting AKI (AUC = 0.956, 95%CI was 0.825-0.997, P < 0.01), and the predictive value was higher than Cys C [AUC (95%CI): 0.956 (0.825-0.997) vs. 0.777 (0.610-0.897), P = 0.034]. In the subgroup of sepsis, the predictive value of Cys C was well (AUC = 0.913, 95%CI was 0.735-0.987, P < 0.01), however, the predictive value of RRI, PDU, RRI+PDU were poor. CONCLUSIONS RRI and PDU score effectively predict AKI stage 2 or 3 in cardiac failure patients, but not in patients with sepsis. The predictive values of Cys C for AKI are similar in patients with cardiac failure or sepsis.
Acute Kidney Injury/diagnosis* ; Cystatin C/metabolism* ; Heart Failure ; Humans ; Intensive Care Units ; Prognosis ; Prospective Studies ; ROC Curve ; Sepsis ; Ultrasonography

OBJECTIVE: To explore the value of serum microRNA-494 (miR-494) expression in predicting the prognosis of acute renal injury (AKI) after cardiac surgery in children. METHODS: 116 children with AKI after cardiopulmonary bypass for congenital heart disease admitted to Sanya People's Hospital from January 2016 to March 2019 were enrolled. The expression of miR-494 in serum was detected by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), and the levels of serum neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1) were detected by enzyme linked immunosorbent assay (ELISA) of all the children. The children were divided into survival group and death group according to 28-day survival. Serum levels of miR-494, NGAL and KIM-1 were measured in two groups. Multivariate Logistic regression was used to analyze the risk factors of death in children with AKI after cardiac surgery. The receiver operating characteristic (ROC) curve analysis of serum levels of miR-494, NGAL and KIM-1 in predicting prognosis of children with AKI after cardiac surgery was performed. Pearson correlation analysis was used to analyze the correlation between serum levels of miR-494 and NGAL, KIM-1. RESULTS: After cardiopulmonary bypass in 116 children with AKI, 27 cases died and 89 cases survived during the 28-day observation. Compared with the survival group, the proportion of cyanosis in the death group was significantly increased, the proportion of blood perfusion was significantly decreased, the time of cardiopulmonary bypass and postoperative mechanical ventilation were significantly prolonged, and the blood glucose level was significantly increased after operation. There was no significant difference in other general data. The serum levels of miR-494, NGAL and KIM-1 in the death group were significantly higher than those in the survival group [miR-494 (2^-ΔΔCt): 3.75±1.28 vs. 1.48±0.71, NGAL (mg/L): 583.60±52.72 vs. 320.52±31.84, KIM-1 (g/L): 30.53±6.38 vs. 17.40±3.72, all P < 0.01]. Multivariate Logistic regression analysis showed cyanosis [odds ratio (OR) = 1.716, 95% confidence interval (95%CI) was 1.184-2.982, P = 0.039], postoperative blood glucose (OR = 1.925, 95%CI was 1.262-3.387, P = 0.005), serum miR-494 (OR = 2.527, 95%CI was 1.706-5.148, P < 0.001), NGAL (OR = 2.473, 95%CI was 1.620-4.935, P < 0.001) and KIM-1 (OR = 1.805, 95%CI was 1.213-3.106, P < 0.001) were independent risk factors for death in children with AKI after cardiac surgery. ROC curve analysis showed the area under the curve (AUC) to predict the death of children with postoperative AKI was 0.868, 0.857 and 0.819 respectively, AUC of serum miR-494, NGAL and KIM-1 levels combination to predict the death of children with postoperative AKI was the largest (0.964, 95%CI was 0.908-0.997), with a high sensitivity and specificity of 97.0% and 91.8%. The correlation analysis showed the expression level of serum miR-494 was positively correlated with NGAL and KIM-1 in the death group (r₁ = 0.902, r₂ = 0.873, both P < 0.01). CONCLUSIONS Serum levels of miR-494 increased significantly in children with AKI after cardiac surgery, which is an independent risk factor for death in children with AKI after cardiac surgery, and the combination of NGAL and KIM-1 levels had a high value in predicting the prognosis of children with AKI after cardiac surgery.
Acute Kidney Injury/diagnosis* ; Acute-Phase Proteins ; Biomarkers ; Cardiac Surgical Procedures ; Child ; Humans ; Lipocalin-2 ; MicroRNAs/blood* ; Predictive Value of Tests ; Prognosis ; Proto-Oncogene Proteins

Dramatic advances in the care of patients with cancer have led to significant improvement in outcomes and survival. However, renal manifestations of the underlying cancer as well as the effects of anti-neoplastic therapies leave patients with significant morbidity and chronic kidney disease risks. The most common renal manifestations associated with cancer include acute kidney injury (AKI) in the setting of multiple myeloma, tumor lysis syndrome, post-hematopoietic stem cell therapy, and AKI associated with chemotherapy. Knowledge of specific risk factors, modification of risk and careful attention to rapid AKI diagnosis are critical for improving outcomes.
Acute Kidney Injury ; Diagnosis ; Drug Therapy ; Humans ; Multiple Myeloma ; Renal Insufficiency, Chronic ; Risk Factors ; Stem Cells ; Tumor Lysis Syndrome