Epidemiology of acute kidney injury and chronic kidney disease in the intensive care unit

Epidemiology, patterns of care and prognosis of acute kidney injury in critically ill patients: A multicenter study in Argentina (The EPIRA study)

BACKGROUND

Acute kidney injury (AKI) is associated with high morbidity and mortality rates in the intensive care unit (ICU). In low- and middle-income countries (LMICs), epidemiological information about this condition is still scarce. Our main objective was to characterize its epidemiology, prognosis, and its treatment.

METHODS

This multicenter prospective cohort study included 1466 patients from 35 ICUs during 6 months in Argentina in 2018. Risk factors and outcomes in patients with and without AKI, and between AKI on admission (AKIadm) and that developed during hospitalization (AKIhosp) were analyzed.

RESULTS

AKI occurred in 61.3% of patients (900/1466); 72.6% were AKIadm and 27.3% AKIhosp. Risk factors were age, BMI, arterial hypertension, cardiovascular diseases, diabetes, SOFA, APACHE II, dehydration, sepsis, vasopressor use, radiocontrast, diuresis/h and mechanical ventilation. Independent predictors for AKI were sepsis, diabetes, dehydration, vasopressors on admission, APACHE II and radiocontrast use. Renal replacement therapies (RRT) requirement in AKI patients was 14.8%. Hospital mortality in AKI vs. non-AKI was 38.7% and 23.3% (p < 0.001); and in AKIadm vs. AKIhosp, 41.2% and 37.8% (p = 0.53).

CONCLUSIONS

ICU-acquired AKI has high incidence, complications and mortality. Risk factors for AKI and RRT utilization were similar to those described in other epidemiological studies. AKIadm was more frequent than AKIhosp, but had equal prognosis.

Valoración de la seguridad del paciente en la práctica clínica de terapia renal sustitutiva en las unidades de vigilancia intensiva

Introducción: La seguridad del paciente en unidades de vigilancia intensiva, con terapia renal sustitutiva intermitente, está influenciada por diversos factores: los inherentes al paciente, humanos y técnicos. Objetivo: Identificar los factores de riesgo y principales incidencias presentes en la práctica clínica, que interfieren en la seguridad del paciente al que se le realiza terapia sustantiva renal intermitente. Material y Método: Estudio descriptivo y retrospectivo de 413 sesiones de terapia sustitutiva renal intermitente. Se obtuvieron datos demográficos, clínicos, complicaciones clínicas, técnicas, controles de monitores, medidas correctivas y factores de riesgo relacionados con las enfermeras mediante un cuestionario de experteza en diálisis. Resultados: 413 sesiones; (52,1%) hemodiálisis intermitente. Edad media 65 años; 78,7% sexo masculino; motivo de ingreso shock séptico (35,1%).Incidencias: error en la asignación de la modalidad (33,2%), pautas sin actualizar (30,5%), disfunción del acceso vascular (15,7%). Complicaciones clínicas: 47,6 en hemodiálisis intermitente, destacando hipotensión en 41,2%.Complicaciones técnicas en el 37,7% de las sesiones, coagulación total o parcial del circuito extracorpóreo (16,7%). Relacionados con el personal: falta de un programa estandarizado de formación (57,1%), variabilidad de personal (81%) y no asistencia a la capacitación programada (52,4%). Conclusión: La seguridad del paciente con terapia sustitución renal en unidades de vigilancia intensiva, es un proceso multifactorial: relacionados con aspectos no modificables (asociados al paciente), incidencias durante el procedimiento y complicaciones. Aunque no se produjeron efectos adversos mayores en la evolución clínica del paciente, éstos son considerados potenciales y algunos previsibles, controlables y evitables.

Valoración de la seguridad del paciente en la práctica clínica de terapia renal sustitutiva en las unidades de vigilancia intensiva

Introducción: La seguridad del paciente en unidades de vigilancia intensiva, con terapia renal sustitutiva intermitente, está influenciada por diversos factores: los inherentes al paciente, humanos y técnicos. Objetivo: Identificar los factores de riesgo y principales incidencias presentes en la práctica clínica, que interfieren en la seguridad del paciente al que se le realiza terapia sustantiva renal intermitente. Material y Método: Estudio descriptivo y retrospectivo de 413 sesiones de terapia sustitutiva renal intermitente. Se obtuvieron datos demográficos, clínicos, complicaciones clínicas, técnicas, controles de monitores, medidas correctivas y factores de riesgo relacionados con las enfermeras mediante un cuestionario de experteza en diálisis. Resultados: 413 sesiones; (52,1%) hemodiálisis intermitente. Edad media 65 años; 78,7% sexo masculino; motivo de ingreso shock séptico (35,1%).Incidencias: error en la asignación de la modalidad (33,2%), pautas sin actualizar (30,5%), disfunción del acceso vascular (15,7%). Complicaciones clínicas: 47,6 en hemodiálisis intermitente, destacando hipotensión en 41,2%.Complicaciones técnicas en el 37,7% de las sesiones, coagulación total o parcial del circuito extracorpóreo (16,7%). Relacionados con el personal: falta de un programa estandarizado de formación (57,1%), variabilidad de personal (81%) y no asistencia a la capacitación programada (52,4%). Conclusión: La seguridad del paciente con terapia sustitución renal en unidades de vigilancia intensiva, es un proceso multifactorial: relacionados con aspectos no modificables (asociados al paciente), incidencias durante el procedimiento y complicaciones. Aunque no se produjeron efectos adversos mayores en la evolución clínica del paciente, éstos son considerados potenciales y algunos previsibles, controlables y evitables.

SGLT2i reduces renal injury by improving mitochondrial metabolism and biogenesis

OBJECTIVES

Despite advances in treatment, an effective therapeutic strategy for acute kidney injury (AKI) is still lacking. Considering the widely reported clinical benefits of canagliflozin in the kidneys, we assessed the effects of canagliflozin on AKI.

METHODS

Lipopolysaccharide was used to induce AKI in the presence of canagliflozin.

RESULTS

Canagliflozin treatment reduced blood urea nitrogen and serum creatinine levels and improved the renal tubular structure in mice with lipopolysaccharide-induced septic AKI. Canagliflozin also suppressed the inflammatory response, oxidative stress and tubular cell death in the kidneys during septic AKI. In vitro, canagliflozin supplementation maintained mitochondrial function in lipopolysaccharide-treated HK-2 cells by restoring the mitochondrial membrane potential, inhibiting mitochondrial reactive oxygen species production and normalizing mitochondrial respiratory complex activity. In HK-2 cells, canagliflozin stimulated the adenosine monophosphate-activated protein kinase catalytic subunit alpha 1 (AMPKα1)/peroxisome proliferator-activated receptor-gamma coactivator 1 alpha (PGC1α)/nuclear respiratory factor 1 (NRF1) pathway, thus elevating the number of live and healthy mitochondria following lipopolysaccharide treatment. Inhibition of the AMPKα1/PGC1α/NRF1/mitochondrial biogenesis pathway abolished the protective effects of canagliflozin on renal cell mitochondria and tubular viability. Similarly, the protective effects of canagliflozin on kidney function and tubular structure were abrogated in AMPKα1-knockout mice.

CONCLUSIONS

Canagliflozin could be used to treat septic AKI by activating the AMPKα1/PGC1α/NRF1/mitochondrial biogenesis pathway.

Klotho restoration via ACE2 activation: A potential therapeutic strategy against acute kidney injury-diabetes comorbidity

Acute kidney injury (AKI) is a collection of clinical syndromes with persistent increases in morbidity and mortality rates. Hyperglycemia is a risk factor for AKI development. Renin-angiotensin-aldosterone system (RAS) disequilibrium and Klotho downregulation also play a pivotal role in the pathogenesis of AKI. Moreover, the relationship between Klotho and ACE2 (a component of non-conventional RAS) regulation in AKI remains an unexplored area of research. Hence, in this study, we investigated ACE2 and Klotho regulation in AKI using ischemic Wistar rats and NRK52E cells under normal and hyperglycemic conditions. Our findings suggested that hyperglycemia exacerbates renal ischemia-reperfusion injury (IRI)/hypoxia-reperfusion injury (HRI) induced AKI. Systemic and renal Klotho deficiency is a novel hallmark of AKI. Additionally, ACE2 is a protective component of the RAS, and its inhibition/deficiency leads to inflammation, apoptosis, Klotho downregulation, and thus AKI development. However, ACE2 activation resulted in the amelioration of AKI. Importantly, ACE2 plays an important role in Klotho upregulation, which might act as an intermediate for ACE2-mediated reno-protection. In conclusion, ACE2 activator i.e. DIZE restored endogenous ACE2-Ang-(1-7)-Klotho level, inhibited apoptosis and inflammation, and ameliorates IRI/HRI induced AKI under diabetic and non-diabetic conditions. Hence, in future, targeting ACE2-Ang-(1-7)-Klotho axis may prove a novel therapeutic strategy against AKI, where further preclinical and clinical investigations are required to verify the clinical potential of this finding.

Machine learning for the prediction of acute kidney injury in patients with sepsis

BACKGROUND

Acute kidney injury (AKI) is the most common and serious complication of sepsis, accompanied by high mortality and disease burden. The early prediction of AKI is critical for timely intervention and ultimately improves prognosis. This study aims to establish and validate predictive models based on novel machine learning (ML) algorithms for AKI in critically ill patients with sepsis.

METHODS

Data of patients with sepsis were extracted from the Medical Information Mart for Intensive Care III (MIMIC- III) database. Feature selection was performed using a Boruta algorithm. ML algorithms such as logistic regression (LR), k-nearest neighbors (KNN), support vector machine (SVM), decision tree, random forest, Extreme Gradient Boosting (XGBoost), and artificial neural network (ANN) were applied for model construction by utilizing tenfold cross-validation. The performances of these models were assessed in terms of discrimination, calibration, and clinical application. Moreover, the discrimination of ML-based models was compared with those of Sequential Organ Failure Assessment (SOFA) and the customized Simplified Acute Physiology Score (SAPS) II model.

RESULTS

A total of 3176 critically ill patients with sepsis were included for analysis, of which 2397 cases (75.5%) developed AKI during hospitalization. A total of 36 variables were selected for model construction. The models of LR, KNN, SVM, decision tree, random forest, ANN, XGBoost, SOFA and SAPS II score were established and obtained area under the receiver operating characteristic curves of 0.7365, 0.6637, 0.7353, 0.7492, 0.7787, 0.7547, 0.821, 0.6457 and 0.7015, respectively. The XGBoost model had the best predictive performance in terms of discrimination, calibration, and clinical application among all models.

CONCLUSION

The ML models can be reliable tools for predicting AKI in septic patients. The XGBoost model has the best predictive performance, which can be used to assist clinicians in identifying high-risk patients and implementing early interventions to reduce mortality.

Assessment of APACHE II Score to Predict ICU Outcomes of Patients with AKI: A Single Center Experience from Haryana, North India

Background

The acute physiology and chronic health evaluation (APACHE) II severity score has shown a good calibration and discriminatory value across a range of disease processes and remains the most widely used source of prognostic information on the risk for death in patients admitted to intensive care units (ICUs).

Objectives

To study APACHE II scores in patients of acute kidney injury (AKI) admitted in the ICU and to find its association with outcome.

Materials and methods

One hundred patients with AKI aged 18 years or above were admitted in the ICU, department of general medicine, of a tertiary care institute in Haryana, North India, from October 2019 to September 2020, were studied. Patients who had known causes of chronic kidney disease (CKD), on maintenance hemodialysis, and those who underwent renal replacement therapy (RRT) or nephrectomy were excluded. All required investigations were performed, and data were collected. The patients were followed till discharge or in-hospital mortality.

Results

The mean age of the patients was 55.92 ± 18.18 years. Male–female ratio was 1.5:1. Thirty-five percent of the admitted patients had an in-hospital mortality. Sepsis (47%) was the most common cause of AKI, and 83% of the patients had underlying comorbid conditions. The mean APACHE II score of the expired patients on admission, i.e., 24.80 ± 13.65, was found to be significantly higher compared to the mean APACHE II score (17.25 ± 10.12) of the discharged patients (p-value <0.001). APACHE II score was found to have 57.14% sensitivity, 86.15% specificity, 69% PPV, 78.9% NPV, and 76% diagnostic accuracy to predict mortality among the AKI patients.

Conclusion

APACHE II scoring system has a good discrimination and calibration when applied to ICU-admitted AKI patients and is a good predictor of prognosis in them.

How to cite this article

Patel P, Gupta S, Patel H, Bashar MDA. Assessment of APACHE II Score to Predict ICU Outcomes of Patients with AKI: A Single-center Experience from Haryana, North India. Indian J Crit Care Med 2022;26(3):276–281.

The Performance of Equations That Estimate Glomerular Filtration Rate against Measured Urinary Creatinine Clearance in Critically Ill Patients

The performance of glomerular filtration rate- (GFR-) estimating equations was studied against creatinine clearance measured by 24-hour urine collection (CrCl_24h-urine) in critically ill patients. Methods. In this substudy of the PermiT trial (https://clinicaltrials.gov/ct2/show/ISRCTN68144998), patients from King Abdulaziz Medical City-Riyadh who had CrCl_24h-urine were included. We estimated GFR using Cockroft–Gault (CG), modification of diet in renal disease study (MDRD), chronic kidney disease epidemiology collaboration (CKD-EPI), and Jelliffe equations. For the CG equation, we entered the actual weight in one calculation (CG_actual-wt), and if BMI ≥30 kg/m², we entered the ideal body weight (CG_ideal-wt) and the adjusted body weight (CG_adjusted-wt) in two calculations. We calculated the MDRD equation based on 4 (MDRD-4) and 6 variables (MDRD-6). The performance of these equations was assessed by different ways including Spearman correlation, bias (difference between estimated GFR and CrCl_24h-urine), precision (standard deviation of bias), and Bland–Altman plot analysis. Results. The cohort consisted of 237 patients (age 45 ± 20 years, males 75%, mechanically ventilated 99% with serum creatinine 101 ± 94 µmol/L and CrCl_24h-urine 108 ± 69 ml/min/1.73 m²). The correlations between the different equations and CrCl_24h-urine were modest (r: 0.62 to 0.79; p < 0.0001). Bias was statistically significant for CG_actual-wt (21 ml/min), CG_adjusted-wt (12 ml/min), and MDRD-6 (-10 ml/min) equations. Precision ranged from 46 to 54 ml/min. The sensitivity of equations to correctly classify CrCl_24h-urine 30–59.9 ml/min/1.73 m² was 17.2% for CG_actual-wt, 30.0% for CG_ideal-wt, 31.0% for CG_adjusted-wt, 31.0% for MDRD-4, 39.1% for MDRD-6, 13.8% for CKD-EPI, and 34.5% for Jelliffe equation. Conclusions. Commonly used GFR-estimating equations had limited ability to properly estimate CrCl_24h-urine and to correctly classify GFR into clinically relevant ranges that usually determine dosing of medications.

A Nomogram to Predict the 28-day Mortality of Critically Ill Patients With Acute Kidney Injury and Treated With Continuous Renal Replacement Therapy

BACKGROUND

Acute kidney injury (AKI) is a severe and common complication in critically ill patients and is associated with increased morbidity and mortality. At present, there is not a tool to predict the prognosis of critically ill patients with AKI and treated with continuous renal replacement therapy (CRRT).

METHODS

A retrospective cohort study was to construct a prediction model for the 28-day mortality of patients with AKI and treated with CRRT. From January 2009 to September 2016, A total of 846 cases were included in our study.

RESULTS

A total of five variables selected by multi-factor Cox regression analysis were used to constructed three predictive models and adopted bootstrapping for internal validation. Finally, we get five sets of models (three sets of construction models and two sets of internal verification models) with similar predictive value. The stepwise model, which including four variables (CCI score, Alb, Phosphate (24h) and SOFA score), was the simplest model, so we chose it as our final predictive model and constructed a nomogram based on it. The area under the ROC curve (AUC) of the stepwise model and the stepwise bootstrap model (BS stepwise) were respectively 0.78(0.75,0.82) and 0.78 (0.75,0.82). The AUC of the stepwise model and the BS stepwise in patients with sepsis were 0.77 (0.73,0.81) and 0.77 (0.73,0.81). The AUC of the stepwise model and the BS stepwise in patients without sepsis were 0.83 (0.78,0.89) and 0.83 (0.78,0.89).

CONCLUSIONS

We developed a four-marker-based prognostic tool that could effectively predict each individual's 28-day mortality for patients with AKI and treated with CRRT.

Incidence of acute kidney injury and use of renal replacement therapy in intensive care unit patients in Indonesia

BACKGROUND

Currently, there is limited epidemiology data on acute kidney injury (AKI) in Indonesia. Therefore, we assessed the incidence of AKI and the utilization of renal replacement therapy (RRT) in Indonesia.

METHODS

Demographic and clinical data were collected from 952 ICU participants. The participants were categorized into AKI and non-AKI groups. The participants were further classified according to the 3 different stages of AKI as per the Kidney Disease Improving Global Outcome (KDIGO) criteria.

RESULTS

Overall incidence of AKI was 43%. The participants were divided into three groups based on the AKI stages: 18.5% had stage 1, 33% had stage 2, and 48.5% had stage 3. Primary diagnosis of renal disease and high APACHE II score were the risk factors associated with AKI (OR = 4.53, 95% CI: 1.67-12.33, p = 0.003 and OR = 1.14 per 1 unit increase, 95% CI: 1.09-1.20, p < 0.001, respectively). Chronic kidney disease was the risk factor for severe AKI. Sepsis was the leading cause of AKI. Among the AKI participants, 24.6% required RRT. The most common RRT modalities were intermittent hemodialysis (71.7%), followed by slow low-efficiency dialysis (22.8%), continuous renal replacement therapy (4.3%), and peritoneal dialysis (1.1%).

CONCLUSIONS

This study showed that AKI was a common problem in the Indonesian ICU. We strongly believe that identification of the risk factors associated with AKI will help us develop a predictive score for AKI so we can prevent and improve AKI outcome in the future.

Predictors of Acute Kidney Injury and Mortality in Intensive Care Unit at a Teaching Tertiary Hospital_ID

BACKGROUND AND AIMS

Despite the increased rates of acute kidney injury (AKI) in intensive care units (ICU) and associated mortality, information on the epidemiology of AKI is sparse in sub-Saharan Africa (SSA). We investigated the rates and predictors of AKI and associated mortality in a tertiary ICU.

MATERIALS AND METHODS

This retrospective study analyzed 280 hospital records of patients admitted to the ICU at a tertiary teaching hospital who were aged ≥15 years from January 2017 to May 31, 2018. The outcome parameters of the study were rates of AKI in the ICU, associated risk factors, and mortalities. Acute kidney injury and ICU mortality were established by the multivariate logistic analysis.

RESULTS

The median age was 36 years (IQR 28, 52). The rate of AKI was 52.9%, and the presence of human immunodeficiency virus (HIV) and oliguria was 2.3-fold (0.004) and 4-fold (0.016) positive predictors of ICU-AKI, respectively. Male gender (0.003), diabetes mellitus (DM) (0.010), respiratory disease (0.001), inotropes (0.004), and ventilator support (0.017) were predictors for ICU mortality after controlling for confounders.

CONCLUSION

The rate of AKI is significantly higher in a referral tertiary hospital in Zambia compared to developed countries and the presence of HIV and noncommunicable diseases such as DM impacts severely on outcomes.

HOW TO CITE THIS ARTICLE

Banda J, Chenga N, Nambaya S, Bulaya T, Siziya S. Predictors of Acute Kidney Injury and Mortality in Intensive Care Unit at a Teaching Tertiary Hospital_ID. Indian J Crit Care Med 2020;24(2):116-121.

Epidemiological Characteristics of Postoperative Sepsis

Background

Postoperative sepsis is a major type of sepsis. Sociodemographic characteristics, incidence trends, surgical procedures, comorbidities, and organ system dysfunctions related to the disease burden of postoperative sepsis episodes are unclear.

Methods

We analyzed epidemiological characteristics of postoperative sepsis based on the ICD-9-CM codes for the years 2002 to 2013 using the Longitudinal Health Insurance Databases of Taiwan’s National Health Insurance Research Database.

Results

We identified 5,221 patients with postoperative sepsis and 338,279 patients without postoperative sepsis. The incidence of postoperative sepsis increased annually with a crude mean of 0.06% for patients aged 45–64 and 0.34% over 65 years. Patients with postoperative sepsis indicated a high risk associated with the characteristics, male sex (OR:1.375), aged 45–64 or ≥ 65 years (OR:2.639 and 5.862), low income (OR:1.390), aged township (OR:1.269), agricultural town (OR:1.266), and remote township (OR:1.205). Splenic surgery (OR:7.723), Chronic renal disease (OR:1.733), cardiovascular dysfunction (OR:2.441), and organ system dysfunctions had the highest risk of postoperative sepsis.

Conclusion

Risk of postoperative sepsis was highest among men, older, and low income. Patients with splenic surgery, chronic renal comorbidity, and cardiovascular system dysfunction exhibited the highest risk for postoperative sepsis. The evaluation of high-risk factors assists in reducing the disease burden.

A prospective study of acute kidney injury in the intensive care unit: development and validation of a risk prediction model

BACKGROUND

Acute kidney injury (AKI) has high morbidity and mortality in intensive care units (ICU). It can also lead to chronic kidney disease (CKD), more costs and longer hospital stay. Early identification of AKI is important.

METHODS

We conducted this monocenter prospective observational study at West China Hospital, Sichuan University, China. We recorded information of each patient in the ICU within 24 h after admission and updated every two days. Patients who reached the primary outcome were accepted into the AKI group. Of all patients, we randomly drew 70% as the development cohort and the remaining 30% as the validation cohort. Using binary logistic regression we got a risk prediction model of the development cohort. In the validation cohort, we validated its discrimination by the area under the receiver operator curve (AUROC) and calibration by a calibration curve.

RESULTS

There were 656 patients in the development cohorts and 280 in the validation cohort. Independent predictors of AKI in the risk prediction model including hypertension, chronic kidney disease, acute pancreatitis, cardiac failure, shock, pH ≤ 7.30, CK > 1000 U/L, hypoproteinemia, nephrotoxin exposure, and male. In the validation cohort, the AUROC is 0.783 (95% CI 0.730-0.836) and the calibration curve shows good calibration of this prediction model. The optimal cut-off value to distinguish high-risk and low-risk patients is 4.5 points (sensitivity is 78.4%, specificity is 73.2% and Youden's index is 0.516).

CONCLUSIONS

This risk prediction model can help to identify high-risk patients of AKI in ICU to prevent the development of AKI and treat it at the early stages. Trial registration TCTR, TCTR20170531001. Registered 30 May 2017, http://www.clinicaltrials.in.th/index.php?tp=regtrials&menu=trialsearch&smenu=fulltext&task=search&task2=view1&id=2573.

Prospective longitudinal observational study of the macro and micro haemodynamic responses to septic shock in the renal and systemic circulations: a protocol for the MICROSHOCK - RENAL study

INTRODUCTION

Septic acute kidney injury (AKI) is the most common complication of septic shock and increases mortality. A large body of experimental data suggests alterations in renal perfusion occur, but this is yet to be fully assessed in humans. The aim of the current study is to observe the macro and microcirculations in both the systemic and renal circulations in a cohort of patients with early septic shock.

METHODS AND ANALYSIS

Single-centre, prospective, longitudinal, observational study of 50 patients with septic shock. Renal microcirculatory assessment will be performed with contrast-enhanced ultrasound, the sublingual microcirculation assessed with incident dark field microscopy and transthoracic echocardiography used to assess global flow. Patients will be enrolled as soon as possible after admission to the intensive care unit and then at +24,+48 and +96 hours. Blood samples of circulatory and renal biomarkers will be collected. Sample groups will be defined by the presence or absence of AKI and then subclassified by the severity (Kidney Disease Improving Global Outcomes (KDIGO) criteria), variables will be compared within and between groups over time.

ETHICS AND DISSEMINATION

Research Ethics Committee (REC) approval has been granted for this study by Yorkshire and the Humber, Leeds West Research Ethics Committee (18/YH/0371) and due to the nature of the patients enrolled with septic shock, capacity for informed consent is likely to be lacking. Therefore, a personal consultee (friend or relative) will be consulted or a nominated consultee (clinician) in their absence. After capacity is regained, consent will then be sought from the patient in accordance with the Mental Capacity Act, UK (2005). This consent process has been approved following REC review. Results will be published in a relevant peer-reviewed journal and presented at academic meetings.