Serum Creatinine Criteria Research Articles

Development of a Prediction Score for In-Hospital Mortality in COVID-19 Patients with Acute Kidney Injury: A Machine Learning Approach

Introduction: Acute kidney injury (AKI) is frequently associated to COVID-19, adding severity and increasing mortality risk.Objective: The aim of the study was to develop and validate a prognostic score at hospital admission for predicting in-hospital mortality in COVID-19 patients with AKI (AKI-COV score).Design: Cross-sectional multicenter prospective cohort study.Setting: The Latin America AKI COVID-19 Registry has been conducted in 57 cities in 12 countries from Latin America. Model training was performed on a cohort of patients admitted from May 1 to December 31, 2020. Participants: Eight hundred and seventy COVID-19 patients with AKI defined according KDIGO serum creatinine criteria were included between 01 March to 31 December 2020.Material and Methods: We evaluated four categories of predictor variables available at the time of AKI diagnosis: (1) demographic data; (2) comorbidities and condition at admission; (3) laboratory exams at admission; (4) characteristics and causes of AKI. We used a machine learning approach to fit models in the training set using 10-fold-cross validation. Predictors with more than 30% missing were removed. We select the best model and confirm the accuracy in a validation cohort using the area under the receiver operating characteristic curve (AUC-ROC).Main Outcome Measured: In-hospital mortality.Results: There were 544 (62.5%) in-hospital deaths. Increasing age, mechanical ventilation, use of vasopressors, leukocytosis, hypertension, severe condition at admission, AKI ethiology, and need kidney replacement therapies (KRT) were associated with increased risk of death. Longer time from symptoms to hospitalization or to AKI diagnosis, and higher urine output were associated with reduced risk of death. The coefficients of the best model (Elastic Net) were used to build the predictive ImAgeS score. The final model has an AUC-ROC of 0.823 [95% CI 0.761 – 0.885] in the validation cohort.Conclusion: We developed a predictive model using only demographic data, comorbidities, hospital admission condition, laboratory variables and causes of AKI that shows good accuracy and is easily applicable. The use of AKI-COV score may assist health-care workers in identifying hospitalized COVID-19 patients with AKI that may require more intensive monitoring and can be used for resource allocation.Funding Statement: This study was partially funded by Latin American Society of Nephrology and Hypertension (SLANH).Declaration of Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.Ethics Approval Statement: The Institutional Review Board of the Clínica Los Olivos, Cochabamba, Bolivia approved the study.

P0145 / #1860: RISK FACTORS AND OUTCOMES OF ACUTE KIDNEY INJURY IN CHILDREN WITH DIABETIC KETOACIDOSIS IN PEDIATRIC INTENSIVE CARE UNIT AT A TERTIARY CARE CENTER

Aims & Objectives: To identify the risk factors and outcomes of Acute Kidney Injury (AKI) in children with Diabetic Ketoacidosis (DKA) admitted in PICU of a tertiary care hospital. Methods: We did a chart review of children aged 1 month to 17 years, admitted with a diagnosis of DKA in PICU between January, 2018- October, 2019. Data collection included demographic, clinical, laboratory and outcome related variables. AKI was defined as using Kidney Disease Improving Global Outcomes serum creatinine criteria. Data were analysed using Stata 11 software. Results: Out of 22 children admitted with DKA in PICU, 7 (31.8%) children developed AKI during the hospital stay. Among them, 6 (85.7%) had AKI at admission while one (14.3%) had AKI at 72 hours. 4 (57.1%) had AKI Stage 1, 2 (28.6%) had AKI Stage 2 and 1 (14.3%) had AKI stage 3. All 7 children with AKI recovered with hydration alone with median duration of recovery of 48 hrs (IQR-12, 192 hrs) without need of renal replacement therapy. Serum sodium at admission, pH and bicarbonate at 24 hours and presence of shock at admission were associated with AKI (p value<0.05 for all). Children with AKI had prolonged acidosis, increased need for mechanical ventilation, cerebral edema and longer PICU stay. However, AKI was not associated with increased mortality in our study. Conclusions: All children with AKI and DKA recovered with hydration alone. Serum sodium at admission, pH and bicarbonate at 24 hours and presence of shock at admission predicted AKI in children with DKA.

Urinary Cyclophilin A as Marker of Tubular Cell Death and Kidney Injury.

Background: Despite the term acute kidney injury (AKI), clinical biomarkers for AKI reflect function rather than injury and independent markers of injury are needed. Tubular cell death, including necroptotic cell death, is a key feature of AKI. Cyclophilin A (CypA) is an intracellular protein that has been reported to be released during necroptosis. We have now explored CypA as a potential marker for kidney injury in cultured tubular cells and in clinical settings of ischemia-reperfusion injury (IRI), characterized by limitations of current diagnostic criteria for AKI. Methods: CypA was analyzed in cultured human and murine proximal tubular epithelial cells exposed to chemical hypoxia, hypoxia/reoxygenation (H/R) or other cell death (apoptosis, necroptosis, ferroptosis) inducers. Urinary levels of CypA (uCypA) were analyzed in patients after nephron sparing surgery (NSS) in which the contralateral kidney is not disturbed and kidney grafts with initial function. Results: Intracellular CypA remained unchanged while supernatant CypA increased in parallel to cell death induction. uCypA levels were higher in NSS patients with renal artery clamping (that is, with NSS-IRI) than in no clamping (NSS-no IRI), and in kidney transplantation (KT) recipients (KT-IRI) even in the presence of preserved or improving kidney function, while this was not the case for urinary Neutrophil gelatinase-associated lipocalin (NGAL). Furthermore, higher uCypA levels in NSS patients were associated with longer surgery duration and the incidence of AKI increased from 10% when using serum creatinine (sCr) or urinary output criteria to 36% when using high uCypA levels in NNS clamping patients. Conclusions: CypA is released by kidney tubular cells during different forms of cell death, and uCypA increased during IRI-induced clinical kidney injury independently from kidney function parameters. Thus, uCypA is a potential biomarker of kidney injury, which is independent from decreased kidney function.

Non-invasive continuous renal tissue oxygenation monitoring to identify preterm neonates at risk for acute kidney injury.

Near-infrared spectroscopy (NIRS) is an emerging tool to identify signs of inadequate tissue oxygenation in preterm neonates with acute kidney injury (AKI). Previous studies have shown a correlation between low renal tissue oxygenation (RrSO2) in the first 24hours of age and the later development of AKI. In this prospective clinical trial, NIRS monitoring was used to identify changes in RrSO2 in comparison to traditional AKI markers, serum creatinine (SCr), and urine output (UOP). We enrolled 35 preterm neonates born less than 32weeks' gestation and applied neonatal NIRS sensors at less than 48hours of age. Neonates underwent 7days of continuous monitoring. Renal and demographic information were collected for the first 7days of age. AKI was determined by the modified neonatal Kidney Disease: Improving Global Outcomes (KDIGO) definition including UOP. Three patients experienced AKI, all based on both SCr and UOP criteria. Each neonate with AKI had decreases in RrSO2 over 48hours prior to changes in SCr and UOP. Patients with AKI had lower median RrSO2 values compared to patients without AKI over the first week of age, (32.4% vs. 60%, p < 0.001). RrSO2 monitoring identified preterm neonates at risk for AKI. NIRS detected a decline in RrSO2 prior to changes in SCr and UOP and was significantly lower in patients with AKI compared to those without AKI. Further studies are needed to evaluate the ability of RrSO2 monitoring to detect signs of kidney stress prior to the diagnosis of AKI. Graphical abstract.

Acute kidney injury in children hospitalized with a relapse of nephrotic syndrome: A short-term outcome study.

Children with nephrotic syndrome (NS) have a number of potential risk factors for the development of acute kidney injury (AKI) including intravascular volume depletion, infection, exposure to nephrotoxic medication, and renal interstitial edema. This study was aimed to determine the incidence of AKI in children hospitalized with a relapse of NS and its short-term outcome. This prospective observational study was conducted from February 2017 to January 2018 at a tertiary care teaching hospital. A total of 54 children and adolescents (1-18 years) hospitalized with a diagnosis of NS and relapse with/or without other complications were enrolled. Clinical data and examination were recorded. AKI was defined using the Kidney Disease Improving Global Outcomes (KDIGO) serum creatinine criteria and Pediatric Risk, Injury, Failure, Loss, End-Stage Renal Disease (p-RIFLE) classification. Children who developed AKI during the first two weeks of hospitalization were followed up till recovery or six weeks whichever was earlier to determine the outcome and factors predisposing to AKI. The mean age of the study population was 59.5 months and 35 (64.8%) patients were male. Of the 54 patients hospitalized, 42 (77.8%) were admitted with infection-associated relapses while 22.2% of children had relapse alone. Diarrhea and spontaneous bacterial peritonitis were the most common infections (26.1% each) followed by urinary tract infections in 19% and pneumonia in 14.3%. Twenty-three (42.6%) children developed AKI according to the KDIGO definition and 27 (50%) using the pRIFLE classification. Fourteen (60.9%) had stage 2 AKI while 21.7% had stage 3 AKI. Infections [odds ratio (OR) 1.24] and use of angiotensin-converting enzyme inhibitors (ACEI) (OR 2.3) were the most common predisposing factors for AKI. The mean recovery time for AKI was 7.34 days. Development of AKI was associated with prolonged hospital stay (12.57 vs.8.55 days P <0.01) and delayed recovery. At the end of follow-up all children recovered from AKI. The incidence of AKI in children hospitalized with complications of NS is high. While the occurrence of these AKI episodes may appear transient, a recurrence of such episodes may be detrimental to the long-term outcome of children with NS. Infections and the use of ACEI during relapses are risk factor for the occurrence of AKI.

Biomarker-Guided Risk Assessment for Acute Kidney Injury: Time for Clinical Implementation?

Acute kidney injury (AKI) is a common and serious complication in hospitalized patients, which continues to pose a clinical challenge for treating physicians. The most recent Kidney Disease Improving Global Outcomes practice guidelines for AKI have restated the importance of earliest possible detection of AKI and adjusting treatment accordingly. Since the emergence of initial studies examining the use of neutrophil gelatinase-associated lipocalin (NGAL) and cycle arrest biomarkers, tissue inhibitor metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein (IGFBP7), for early diagnosis of AKI, a vast number of studies have investigated the accuracy and additional clinical benefits of these biomarkers. As proposed by the Acute Dialysis Quality Initiative, new AKI diagnostic criteria should equally utilize glomerular function and tubular injury markers for AKI diagnosis. In addition to refining our capabilities in kidney risk prediction with kidney injury biomarkers, structural disorder phenotypes referred to as “preclinical-” and “subclinical AKI” have been described and are increasingly recognized. Additionally, positive biomarker test findings were found to provide prognostic information regardless of an acute decline in renal function (positive serum creatinine criteria). We summarize and discuss the recent findings focusing on two of the most promising and clinically available kidney injury biomarkers, NGAL and cell cycle arrest markers, in the context of AKI phenotypes. Finally, we draw conclusions regarding the clinical implications for kidney risk prediction.

Intraoperative oliguria does not predict postoperative acute kidney injury in major abdominal surgery: a cohort analysis.

Background:Acute kidney injury (AKI) is a common complication in patients undergoing major abdominal surgery and is associated with considerable morbidity and mortality. Several studies investigating the association between intraoperative urine output and postoperative AKI have shown conflicting results. Here, we investigated the association of intraoperative oliguria with postoperative AKI in a cohort of patients submitted to elective major abdominal surgery.Methods:This was a single-center retrospective analysis of adult patients who underwent elective major abdominal surgery from January 2016 to December 2018. AKI was defined according to the serum creatinine criteria of the KDIGO classification. Intraoperative oliguria was defined as urine output of less than 0.5 mL/kg/h. Risk factors were evaluated using multivariate logistic regression analysis.Results:A total of 165 patients were analyzed. In the first 48 h after surgery the incidence of AKI was 19.4%. Postoperative AKI was associated with hospital mortality (p=0.011). Twenty percent of patients developed intraoperative oliguria. There was no association between preexisting comorbidities and development of intraoperative oliguria. There was no correlation between the type of anesthesia used and occurrence of intraoperative oliguria, but longer anesthesia time was associated with intraoperative oliguria (p=0.007). Higher baseline SCr (p=0.001), need of vasoactive drugs (p=0.007), and NSAIDs use (p=0.022) were associated with development of intraoperative oliguria. Intraoperative oliguria was not associated with development of postoperative AKI (p=0.772), prolonged hospital stays (p=0.176) or in-hospital mortality (p=0.820).Conclusion:In this cohort of patients we demonstrated that intraoperative oliguria does not predict postoperative AKI in major abdominal surgery.

795. Impact of Revised Infectious Diseases Society of America and Society for Healthcare Epidemiology of America Guideline on the Classification of Clostridioides difficile Infection Severity

BackgroundThe Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA) revised their Clostridioides difficile infection (CDI) severity classification criteria in 2017 to include a serum creatinine (SCr) value above a threshold (≥ 1.5 mg/dL) rather than a relative increase from baseline (≥ 1.5 times the premorbid level). To date, these criteria have not been validated and may overestimate the number of severe CDI cases in patients with underlying renal insufficiency.MethodsThis multicenter, retrospective cohort study included all patients ≥ 18 years of age with CDI diagnosed in two large health systems in the Houston, Texas area between 2016 and 2018. Patients were assessed for presence of acute kidney injury (AKI) and chronic kidney disease (CKD), defined per the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines, and IDSA/SHEA CDI severity classification criteria per the 2010 and 2017 CDI guidelines. The primary outcome was all-cause inpatient mortality.ResultsThe study cohort consisted of 770 CDI episodes from 12 hospitals. A large proportion of episodes occurred in patients with preexisting CKD (36.5%) and concomitant AKI (29.6%). Eighty-two episodes (10.6%) showed discordant results when applying the 2017 revised severity classification criteria due to the identification of patients with preexisting CKD. However, the 2017 severity classification criteria were better correlated with all-cause mortality (OR, 5.40; 95% CI, 1.84-15.86; P = 0.002) than were the 2010 severity classification criteria (OR, 3.12; 95% CI, 1.35-7.19; P = 0.008) as the 2017 SCr criterion was an independent predictor of mortality (OR, 3.66; 95% CI, 1.66-8.05; P = 0.001) while the 2010 SCr criterion was not (OR, 1.47; 95% CI, 0.71-3.08; P = 0.30).ConclusionOur findings support the inclusion of the 2017 IDSA/SHEA CDI severity classification criteria in future CDI guideline updates.Disclosures Kevin W. Garey, PharmD, MS, FASHP, Merck & Co. (Grant/Research Support, Scientific Research Study Investigator)

Severe acute kidney injury in COVID-19 patients is associated with in-hospital mortality

Although the lungs are major targets for COVID-19 invasion, other organs—such as the kidneys—are also affected. However, the renal complications of COVID-19 are not yet well explored. This study aimed to identify the incidence of acute kidney injury (AKI) in patients with COVID-19 and to evaluate its impact on patient outcomes. This retrospective study included 704 patients with COVID-19 who were hospitalized at two hospitals in Daegu, Korea from February 19 to March 31, 2020. AKI was defined according to the serum creatinine criteria in the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. The final date of follow-up was May 1, 2020. Of the 704 patients, 28 (4.0%) developed AKI. Of the 28 patients with AKI, 15 (53.6%) were found to have AKI stage 1, 3 (10.7%) had AKI stage 2, and 10 (35.7%) had AKI stage 3. Among these patients, 12 (42.9%) recovered from AKI. In the patients with AKI, the rates of admission to intensive care unit (ICU), administration of mechanical ventilator (MV), and in-hospital mortality were significantly higher than in patients without AKI. Multivariable analysis revealed that old age (Hazard ratio [HR] = 4.668, 95% confidence interval [CI] = 1.250–17.430, p = 0.022), high neutrophil-to-lymphocyte ratio (HR = 1.167, 95% CI = 1.078–1.264, p < 0.001), elevated creatinine kinase (HR = 1.002, 95% CI = 1.001–1.004, p = 0.007), and severe AKI (HR = 12.199, 95% CI = 4.235–35.141, p < 0.001) were independent risk factors for in-hospital mortality. The Kaplan-Meier curves showed that the cumulative survival rate was lowest in the AKI stage 3 group (p < 0.001). In conclusion, the incidence of AKI in patients with COVID-19 was 4.0%. Severe AKI was associated with in-hospital death.

Monitoring peripheral perfusion in sepsis associated acute kidney injury: Analysis of mortality.

Microcirculatory disorders have been consistently linked to the pathophysiology of sepsis. One of the major organs affected is the kidneys, resulting in sepsis-associated acute kidney injury (SA-AKI) that correlates considerably with mortality. However, the potential role of clinical assessment of peripheral perfusion as a possible tool for SA-AKI management has not been established. To address this gap, the purpose of this study was to investigate the prevalence of peripheral hypoperfusion in SA-AKI, its association with mortality, and fluid balance. This observational cohort study enrolled consecutive septic patients in the Intensive Care Unit. After fluid resuscitation, peripheral perfusion was evaluated using the capillary filling time (CRT) and peripheral perfusion index (PI) techniques. The AKI was defined based on both serum creatinine and urine output criteria. One hundred and forty-one patients were included, 28 (19%) in the non-SA-AKI group, and 113 (81%) in the SA-AKI group. The study revealed higher peripheral hypoperfusion rates in the SA-AKI group using the CRT (OR 3.6; 95% CI 1.35-9.55; p < 0.05). However, this result lost significance after multivariate adjustment. Perfusion abnormalities in the SA-AKI group diagnosed by both CRT (RR 1.96; 95% CI 1.25-3.08) and PI (RR 1.98; 95% CI 1.37-2.86) methods were associated to higher rates of 28-day mortality (p < 0.01). The PI's temporal analysis showed a high predictive value for death over the first 72 h (p < 0.01). A weak correlation between PI values and the fluid balance was found over the first 24 h (r = - 0.20; p < 0.05). In conclusion, peripheral perfusion was not different intrinsically between patients with or without SA-AKI. The presence of peripheral hypoperfusion in the SA-AKI group has appeared to be a prognostic marker for mortality. This evaluation maintained its predictive value over the first 72 hours. The fluid balance possibly negatively influences peripheral perfusion in the SA-AKI.

Assessment of Kidney Injury as a Severity Criteria for Clostridioides Difficile Infection.

BackgroundThe Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA) revised their Clostridioides difficile infection (CDI) severity classification criteria in 2017 to include an absolute serum creatinine (SCr) value above a threshold (≥1.5 mg/dL) rather than a relative increase from baseline (≥1.5 times the premorbid level). To date, how to best define kidney injury as a CDI disease severity marker has not been validated to assess severe outcomes associated with CDI.MethodsThis multicenter cohort study included adult hospitalized patients with CDI. Patients were assessed for the presence of acute kidney injury (AKI), chronic kidney disease (CKD), and CDI severity using the 2010 and 2017 IDSA/SHEA CDI guidelines. Primary outcome was all-cause inpatient mortality.ResultsThe final study cohort consisted of 770 CDI episodes from 705 unique patients aged 65 ± 17 years (female, 54%; CKD, 36.5%; AKI, 29.6%). Eighty-two episodes (10.6%) showed discordant severity classification results due to the inclusion of more patients with preexisting CKD in the severe disease category using an absolute SCr threshold criterion. The absolute SCr criterion better correlated with all-cause mortality (odds ratio [OR], 4.04; 95% confidence interval [CI], 1.76–9.28; P = .001) than the relative increase in SCr (OR, 1.34; 95% CI, 0.62–2.89; P = .46). This corresponded to an increased likelihood of the 2017 CDI severity classification criteria to predict mortality (OR, 5.33; 95% CI, 1.81–15.72; P = .002) compared with the 2010 criteria (OR, 2.71; 95% CI, 1.16–6.32; P = .02).ConclusionsOur findings support the 2017 IDSA/SHEA CDI severity classification criteria of a single pretreatment SCr in future CDI guideline updates.

Under-Recognition of Neonatal Acute Kidney Injury and Lack of Follow-Up.

Acute kidney injury (AKI) incidence is 30% in neonatal intensive care units (NICU). AKI is associated with increased mortality and risk of chronic kidney disease (CKD) in children. To assess follow-up and early CKD, we retrospectively reviewed outcomes of Cincinnati Children's Hospital Medical Center (CCHMC) cohort of neonates from the AWAKEN trial (2014). Data from 81 CCHMC patients were extracted from the AWAKEN dataset. KDIGO (Kidney Disease: Improving Global Outcomes) criteria for serum creatinine (SCr) and urine output (UOP) <1 mL/kg/h, reported per 24 hours on postnatal days 2 to 7, were used to define AKI. Charts were reviewed until May 2019 for death, nephrology consult, AKI diagnosis on discharge summary, follow-up, and early CKD at >6 months of age (defined as: estimated glomerular filtration rate < 90 mL/min/1.73 m2, hyperfiltration, proteinuria, hypertension, or abnormal ultrasound). Patients were considered to have renal follow-up if they had ≥1 follow-up visit containing: SCr, urinalysis, or blood pressure measurement. Seventy-seven patients had sufficient data to ascertain AKI diagnosis. In total 47 of 77 (61%) were AKI+ by SCr or UOP criteria (20 stage 1, 14 stage 2, 13 stage 3). Four died during their admission and five were removed from CKD analyses due to urologic anomalies. AKI-UOP alone outnumbered AKI-SCr (45 AKI+ vs 5 AKI+ for all stages). 33% of patients had <2 SCr measured while inpatient. Only 3 of 47 AKI+ patients had a nephrology consult (all stage 3 by SCr) and 2 of 47 had AKI included in discharge summary. 67% of AKI+ patients had follow-up. In total 10 of 43 (23%) AKI+ versus 12 of 25 (48%) AKI- patients had ≥1 marker of early CKD assessed after 6 months. Based on SCr, 3 of 7 (43%) AKI+ had hyperfiltration versus 0 of 7 (0%) AKI- (p = 0.19). AKI is vastly under-recognized in the NICU, especially if based on SCr alone. This leads to insufficient follow-up to ascertain renal sequelae in this high-risk population. · AKI is under-recognized in high-risk neonates.. · There is a lack of adequate follow-up.. · Identification of AKI by SCr alone is insufficient..

Dividing Stage 1 Acute Kidney Injury After Cardiac or Thoracic Aortic Surgery

Although the Kidney Disease: Improving Global Outcomes (KDIGO) criteria are used to define acute kidney injury, the criteria have limitations for including 2 different serum creatinine criteria in stage 1. We hypothesized that there would be differences in clinical outcomes between the 2 subgroups of stage 1 acute kidney injury in patients undergoing cardiac or thoracic aortic surgery. We reviewed 2510 cases. Patients with KDIGO stage 1 were divided into 2 subgroups (stage 1a: 0.3 mg/dL or greater of absolute increase in serum creatinine, n= 376; and stage 1b: 50% or greater relative increase, n= 365). Propensity score analysis was performed between stage 1a and 1b groups, yielding 240 pairs. We compared the length of hospital stay, the incidence of cardiovascular complications, 5-year all-cause mortality between these subgroups. Overall survival was compared between the subgroups after propensity score matching. We performed sensitivity analysis for Acute Kidney Injury Network (AKIN) criteria. Length of hospital stay and 5-year all-cause mortality were worse in patients with KDIGO stage 1b compared with stage 1a. Five-year patient survival was significantly worse in patients with stage 1b compared with stage 1a after matching (log rank test, P= .002). We found similar results regarding AKIN criteria. Subgroup analysis showed that the significant difference in survival existed only when baseline serum creatinine was 0.8 mg/dL or greater. The KDIGO or AKIN criteria for stage 1 acute kidney injury could be further divided into 2 substages with different severity of clinical outcomes. These modified criteria could give additional prognostic information in patients undergoing cardiac or thoracic aortic surgery.

Rule Out Acute Kidney Injury in the Emergency Department With a Urinary Dipstick

IntroductionThe identification of acute injury of the kidney relies on serum creatinine (SCr), a functional marker with poor temporal resolution as well as limited sensitivity and specificity for cellular injury. In contrast, urinary biomarkers of kidney injury have the potential to detect cellular stress and damage in real time.MethodsTo detect the response of the kidney to injury, we have tested a lateral flow dipstick that measures a urinary protein called neutrophil gelatinase-associated lipocalin (NGAL). Analysis of urine was performed in a prospective cohort of 479 patients (final cohort N = 426) entering an emergency department in New York City and subsequently admitted for inpatient care.ResultsColorimetric development had high interrater reliability (88% concordance rate) and correlated with traditional enzyme-linked immunosorbent assay (ELISA) measurements (ρ = 0.732, P < .0001). Of the 14% of the cohort who met Acute Kidney Injury Network (AKIN) SCr criteria for acute kidney injury (AKI), 67% demonstrated transient (<2 days) and 33% demonstrated sustained (>2 days) elevation of SCr. Comparing the outcomes of patients with sustained versus transient or undetectable changes in SCr revealed that the urinary NGAL (uNGAL) dipstick had high specificity and negative predictive value (NPV) (high- vs. low-intermediate readings, sensitivity = 0.55, specificity = 0.91, positive predictive value = 0.24, NPV = 0.97, χ2 = 20.39, P < 0.001).ConclusionWe show that the introduction of a bedside uNGAL dipstick permits accurate triage by identifying individuals who do not have tubular injury. In an era of shortening length of stay and rapid decisions based on isolated SCr measurements, real-time exclusion of kidney injury by a dipstick will be particularly useful to overcome the retrospective, insensitive, and nonspecific attributes of SCr.

Renin-angiotensin-aldosterone system inhibition decreased contrast-associated acute kidney injury in chronic kidney disease patients

Chronic kidney disease (CKD) is a risk factor for contrast associated acute kidney injury (CA-AKI). The risk of renin-angiotensin-aldosterone system inhibitor (RASi) use in patients with CKD before the administration of contrast is not clear. In this nested case-control study, 8668 patients received contrast computed tomography (CT) from 2013 to 2018 during index administration in a multicenter hospital cohort. The identification of AKI is based on the Kidney Disease: Improving Global Outcomes (KDIGO) serum creatinine criteria within 48h after contrast medium used. Finally, 986 patients (age, 63.36±12.22; men, 72.92%) with CKD (estimated glomerular filtration rate (eGFR)=35.0±19.8mL/min/1.73m2) were eligible for analysis. After the index date, RASi users (n=315) were less likely to develop CA-AKI (13.65% vs 30.4%, p<0.001), and had a lower hospital mortality (8.25% vs 19.23%, p<0.001) compared with non-users. The pre-contrast use of RASi decrease the risk of AKI (OR, 0.342, p<0.001) and hospital mortality (OR, 0.602, p=0.045). Even a few defined daily doses (DDDs) of RASi treatment, more than 0.02 prior to contrast CT could attenuate CA-AKI. The hospital mortality was higher in RASi non-users if their eGFR value was more than 17.9mL/min/1.73m2. RASi use in patients with CKD prior to contrast CT has the potential to mitigate the incidence of AKI and hospital mortality. Even a low dose of RASi will noticeably decrease the risk of AKI and will not increase the risk of hyperkalemia.

Changing relative risk of clinical factors for hospital-acquired acute kidney injury across age groups: a retrospective cohort study

BackgroundLikelihood of developing acute kidney injury (AKI) increases with age. We aimed to explore whether the predictability of AKI varies between age groups and assess the volatility of risk factors using electronic medical records (EMR).MethodsWe constructed a retrospective cohort of adult patients from all inpatient units of a tertiary care academic hospital and stratified it into four age groups: 18–35, 36–55, 56–65, and > 65. Potential risk factors collected from EMR for the study cohort included demographics, vital signs, medications, laboratory values, past medical diagnoses, and admission diagnoses. AKI was defined based on the Kidney Disease Improving Global Outcomes (KDIGO) serum creatinine criteria. We analyzed relative importance of the risk factors in predicting AKI using Gradient Boosting Machine algorithm and explored the predictability of AKI across age groups using multiple machine learning models.ResultsIn our cohort, older patients showed a significantly higher incidence of AKI than younger adults: 18–35 (7.29%), 36–55 (8.82%), 56–65 (10.53%), and > 65 (10.55%) (p < 0.001). However, the predictability of AKI decreased with age, where the best cross-validated area under the receiver operating characteristic curve (AUROC) achieved for age groups 18–35, 36–55, 56–65, and > 65 were 0.784 (95% CI, 0.769–0.800), 0.766 (95% CI, 0.754–0.777), 0.754 (95% CI, 0.741–0.768), and 0.725 (95% CI, 0.709–0.737), respectively. We also observed that the relative risk of AKI predictors fluctuated between age groups.ConclusionsAs complexity of the cases increases with age, it is more difficult to quantify AKI risk for older adults in inpatient population.

Impact of admission serum ionized calcium levels on risk of acute kidney injury in hospitalized patients

This study aimed to investigate the risk of acute kidney injury (AKI) in hospitalized patients based on admission serum ionized calcium levels. This is a cohort study of all hospitalized adult patients, from January 2009 to December 2013 at a tertiary referral hospital, who had available serum ionized calcium at the time of admission. We excluded patients who had end-stage kidney disease or AKI at admission. We stratified admission serum ionized calcium into 6 groups; ≤ 4.39, 4.40–4.59, 4.60–4.79, 4.80–4.99, 5.00–5.19, and ≥ 5.20 mg/dL. We used serum creatinine criterion of KDIGO definition for diagnosis of AKI. We performed logistic regression analysis to assess the risk of in-hospital AKI occurrence based on admission serum ionized calcium, using serum ionized calcium of 5.00–5.19 mg/dL as the reference group. We studied a total of 25,844 hospitalized patients. Of these, 3,294 (12.7%) developed AKI in hospital, and 622 (2.4%) had AKI stage 2 or 3. We observed a U-shaped association between admission serum ionized calcium and in-hospital AKI, with nadir in-hospital AKI was in serum ionized calcium of 5.00–5.19 mg/dL. After adjustment for confounders, low serum ionized calcium of 4.40–4.59, ≤ 4.39 mg/dL and elevated serum ionized calcium ≥ 5.20 mg/dL were associated with increased risk of AKI with odds ratio of 1.33 (95% CI 1.14–1.56), 1.45 (95% CI 1.21–1.74), and 1.26 (95% CI 1.04–1.54), respectively. Both hypocalcemia, and hypercalcemia at the time of admission were associated with an increased risk of hospital-acquired AKI.

RIFLE serum creatinine and urine output criteria combined is superior to RIFLE serum creatinine criterion alone in predicting Acute Kidney Injury (AKI) in critically ill patients: A prospective observational study

Background: Approximately 7% of all hospitalized patients and 20% of acutely ill patients develop signs of AKI. AKI incidence is very high worldwide among intensive care unit patients. Previously long known term, acute renal failure (ARF) is largely replaced by acute kidney injury (AKI), reflecting the recognition that smaller decrements in kidney function that do not result in overt organ failure are of substantial clinical relevance and are associated with increased morbidity and mortality.&#x0D; Objectives: We designed this study to diagnose even mild renal dysfunction earlier than usual time frame with the combined effect of both serum creatinine and urine output criteria, when compared with serum creatinine criterion alone. To establish this objective we used RIFLE serum creatinine and urine output (UO) criteria combined (Scr+UO) and compared with RIFLE serum creatinine (Scr) alone to diagnose AKI early (in days).&#x0D; Design: Prospective observational cohort study. Duration of the study was one year (01 year), from January 2014 to December 2014&#x0D; Method: All adult patients admitted into department of critical care medicine, BIRDEM General Hospital, DHAKA who received treatment for 48 hours and fulfilled the inclusion and exclusion criteria was included in the study. Representative serum creatinine value was obtained either from the day of admission in hospital, day of admission into or transfer to ICU or any document within last six months. The lesser of pre-ICU admission serum creatinine (SCr) and ICU admission SCr would serve as baseline renal function. Weight in kilogram, representative serum urea/BUN, co-morbidities and reason for ICU admission were incorporated in it. Patient’s daily data entry of renal replacement therapy, daily creatinine value, urinary output over 6 hours, 12 hours, and 24 hours, episode of anuria over 12 hours, if present were documented. Data collected on renal replacement therapy at the time of discharge, if any and outcome in terms of loss and ESRD status were collected. APACHE II data and SAPS II data were calculated and analyzed.&#x0D; Result: Total 236 adult patients were enrolled in the study to assess their renal function status using RIFLE (Risk, Injury, Failure, Loss, End Stage Renal Disease). Serum creatinine was estimated daily for seven days. Those patients who fulfilled the creatinine criteria for RIFLE were categorized into RIFLE serum creatinine (Scr) group. Those patients who met both the criteria for urine output and serum creatinine according to RIFLE was designated as RIFLE serum creatinine and urine output criteria Combined (Scr+ UO) group. In our study, mean of number of days needed for diagnosis of AKI using RIFLE creatinine (Scr) was 3.25 (±1.24) and using RIFLE combined (Scr+uo) criteria was 2.84(±1.03).&#x0D; Conclusion: The present study concludes that RIFLE serum creatinine criterion (Scr) alone delays the diagnosis of AKI in comparison to RIFLE serum creatinine and urine output criteria combined (Scr+UO). AKI should be graded using both the criteria of RIFLE serum creatinine and urine output criteria combined (Scr+UO). Urine output should not be underestimated in AKI diagnosis in ICU patients.&#x0D; Bangladesh Crit Care J March 2020; 8(1): 17-23

Acute kidney injury risk prediction score for critically-ill surgical patients

BackgroundThere has been a global increase in the incidence of acute kidney injury (AKI), including among critically-ill surgical patients. AKI prediction score provides an opportunity for early detection of patients who are at risk of AKI; however, most of the AKI prediction scores were derived from cardiothoracic surgery. Therefore, we aimed to develop an AKI prediction score for major non-cardiothoracic surgery patients who were admitted to the intensive care unit (ICU).MethodsThe data of critically-ill patients from non-cardiothoracic operations in the Thai Surgical Intensive Care Unit (THAI-SICU) study were used to develop an AKI prediction score. Independent prognostic factors from regression analysis were included as predictors in the model. The outcome of interest was AKI within 7 days after the ICU admission. The AKI diagnosis was made according to the Kidney Disease Improving Global Outcomes (KDIGO)-2012 serum creatinine criteria. Diagnostic function of the model was determined by area under the Receiver Operating Curve (AuROC). Risk scores were categorized into four risk probability levels: low (0–2.5), moderate (3.0–8.5), high (9.0–11.5), and very high (12.0–16.5) risk. Risk of AKI was presented as likelihood ratios of positive (LH+).ResultsA total of 3474 critically-ill surgical patients were included in the model; 333 (9.6%) developed AKI. Using multivariable logistic regression analysis, older age, high Sequential Organ Failure Assessment (SOFA) non-renal score, emergency surgery, large volume of perioperative blood loss, less urine output, and sepsis were identified as independent predictors for AKI. Then AKI prediction score was created from these predictors. The summation of the score was 16.5 and had a discriminative ability for predicting AKI at AuROC = 0.839 (95% CI 0.825–0.852). LH+ for AKI were: low risk = 0.117 (0.063–0.200); moderate risk = 0.927 (0.745–1.148); high risk = 5.190 (3.881–6.910); and very high risk = 9.892 (6.230–15.695), respectively.ConclusionsThe function of AKI prediction score to predict AKI among critically ill patients who underwent non-cardiothoracic surgery was good. It can aid in early recognition of critically-ill surgical patients who are at risk from ICU admission. The scores could guide decision making for aggressive strategies to prevent AKI during the perioperative period or at ICU admission.Trial registrationTCTR20190408004, registered on April 4, 2019.

TO020POTENTIAL INTERPRETATIONS OF CRITERIA FOR AKI BY AUTOMATED DECISION SUPPORT ALGORITHMS: IMPACT ON AKI INCIDENCE

Abstract Background and Aims The reported incidence of Acute Kidney Injury (AKI) at the intensive care unit (ICU) is variable. Although the Kidney Disease Improving Global Outcome (K-DIGO) improved harmonisation of this definition, there is remaining variability in the actual implementation of this AKI definition, with variable interpretation of the urinary output (UO) criterion, and of the baseline serum creatinine (Screa) criterion. This hampers progress of our understanding of the clinical concept AKI and leads to confusion and unclarity when interpreting models to predict AKI or associated outcomes. With the advent of big data and artificial intelligence based decision algorithms, this problem will only become more of interest, as the user will not know what exactly the construct AKI in the application used means and represents. Therefore, we intended to explore the impact of different interpretations of the Screa and the UO criterium as presented in the K-DIGO definition on the incidence of AKI stage 2. Method We included all patients of an electronic health data system applied in a tertiary ICU between 2013 and 2017. Sequential Organ Failure Assessment (SOFA) score was calculated, and gender, age, weight and mortality at ICU and in hospital were extracted. All serum creatinine (sCrea) values during ICU stay and hospitalisation were extracted, as were UO data, with their time stamps. In addition, all available Screa data up to 1 year before ICU admission were retrieved from a dataset external to the ICU. AKI was defined according to KDIGO stage 2, using different possible interpretations of the Screa and/or the UO criterion. For the evolution of Screa as compared to a baseline value, we sued either a value directly available to ICU staff (def 1), a presumed eGFR of 75ml/min (def 2), the first available value after admission to ICU (def 3), the lowest value during the current hospitalisation before ICU admission (def 4), the lowest value before the hospitalisation episode as found in an external dataset (def 5). For the UO criterion, we also applied two criteria in line with K-DIGO stage 2: a UO below 6ml/kg during a 12 hour block (def 6) or a UO below 0.5ml/kg/hour during each of 12 consecutive one hour intervals (def 7). Def 8 identified patients who did not comply with any of the definitions (1-7), so who had no AKI according to any definition. Definition 9 and 10 identified patients who complied with at least one out of the Screa criteria 1-5 (def 9) or out of the UO criteria (def 10). Definition 11 identified patients who complied both with at least one Screa and one UO criterium. Results Our dataset included 16433 ICU admissions (34.7% female, age 60.7±16.4 years). Overall, 8.1% of patients died at ICU, and another 5.2% during their hospitalisation. The SOFA score at admission was 6.9±4.1. The incidence of AKI according to the stage 2 definition of K-DIGO varied according to the interpretation of the diagnostic criteria from 4.3% when baseline creatinine was defined as the first ICU value, to 35.3% when the UO criterium was interpreted as a UO below 6ml/kg over a 12 hour block (fig). Only half of patients (53.7%) did not comply with any of the definitions (def 8), 10.9% and 19.7% complied with one of the Screa (def 9) OR one of the UO criteria (def 10) respectively, and 15.7% complied with both (def 11). There was substantial reclassification across the different definitions. Conclusion Unclarity on the actual interpretation of the Screa and UO criteria used in the K-DIGO definition of AKI leads to substantial differences in incidence of AKI, and also with substantial reclassification according to different definitions. This is especially concerning in an era of big data and automated decision support, as clinicians might not know which construct of AKI is actually being represented.