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Predicting Major Adverse Kidney Events among Critically Ill Adults Using the Electronic Health Record.

ABSTRACT: Prediction of major adverse kidney events in critically ill patients may help target therapy, allow risk adjustment, and facilitate the conduct of clinical trials. In a cohort comprised of all critically ill adults admitted to five intensive care units at a single tertiary care center over one year, we developed a logistic regression model for the outcome of Major Adverse Kidney Events within 30 days (MAKE30), the composite of persistent renal dysfunction, new renal replacement therapy (RRT), and in-hospital mortality. Proposed risk factors for the MAKE30 outcome were selected a priori and included age, race, gender, University Health System Consortium (UHC) expected mortality, baseline creatinine, volume of isotonic crystalloid fluid received in the prior 24 h, admission service, intensive care unit (ICU), source of admission, mechanical ventilation or receipt of vasopressors within 24 h of ICU admission, renal replacement therapy prior to ICU admission, acute kidney injury, chronic kidney disease as defined by baseline creatinine value, and renal failure as defined by the Elixhauser index. Among 10,983 patients in the study population, 1489 patients (13.6%) met the MAKE30 endpoint. The strongest independent predictors of MAKE30 were UHC expected mortality (OR 2.32 [95%CI 2.06-2.61]) and presence of acute kidney injury at ICU admission (OR 4.98 [95%CI 4.12-6.03]). The model had strong predictive properties including excellent discrimination with a bootstrap-corrected area-under-the-curve (AUC) of 0.903, and high precision of calibration with a mean absolute error prediction of 1.7%. The MAKE30 composite outcome can be reliably predicted from factors present within 24 h of ICU admission using data derived from the electronic health record.

SUBMITTER: McKown AC

PROVIDER: S-EPMC5821255 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Predicting Major Adverse Kidney Events among Critically Ill Adults Using the Electronic Health Record.

McKown Andrew C AC Wang Li L Wanderer Jonathan P JP Ehrenfeld Jesse J Rice Todd W TW Bernard Gordon R GR Semler Matthew W MW

Journal of medical systems 20170831 10

Prediction of major adverse kidney events in critically ill patients may help target therapy, allow risk adjustment, and facilitate the conduct of clinical trials. In a cohort comprised of all critically ill adults admitted to five intensive care units at a single tertiary care center over one year, we developed a logistic regression model for the outcome of Major Adverse Kidney Events within 30 days (MAKE30), the composite of persistent renal dysfunction, new renal replacement therapy (RRT), an ...[more]

PMID: 28861688

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Project description:BACKGROUND:Acute kidney injury (AKI) is a common problem in critically ill patients and associated with high rates of morbidity and mortality. Recently, Major Adverse Kidney Events (MAKE) were introduced as important kidney endpoints. If these endpoints can be predicted, then it may help the physicians to identify high-risk patients and provide the opportunity to have targeted preventive therapy. The objective of this study was to create a simplified scoring system to predict MAKE within 28 days among AKI patients in ICU. METHODS:This is a prospective web-based multicenter cohort study that was conducted in adults who were admitted to the ICU in 17 centers across Thailand from 2013 to 2015. A predicting score was derived from the regression equation with Receiver Operating Characteristic (ROC) analysis to evaluate the diagnostic test and produce predictive models. Internal validation was obtained using the bootstrapping method. RESULTS:From 5071 cases, 2856 (56%) had AKI. Among those with AKI, 1749 (61%) had MAKE. Among those that have MAKE, there were 1175 (41.4%) deaths, 414 (14.4%) were on dialysis and 1154 (40.7%) had non-recovery renal function. The simplified score points of low Glasgow coma scale was 3, tachypnea was 1, vasopressor use was 1, on mechanical ventilation was 2, oliguria was 2, serum creatinine rising ≥ 3 times was 5, high blood urea nitrogen was 3, low hematocrit was 2, and thrombocytopenia was 1. The area under ROC curve for optimism corrected performance was 0.80 (0.78, 0.81). When the cut-off value was 7, the sensitivity, specificity, positive likelihood ratio, and positive predictive values were 0.75, 0.76, 3.10, and 0.84, respectively. When the scoring system was calibrated, the α intercept and β slope were 1.001 and 0, respectively. CONCLUSIONS:SEA-MAKE scoring system is a new simplified clinical tool that can be used to predict major adverse kidney events in AKI patients. The simplicity of the scoring system is highly likely to be used in resource-limited settings. However, external validation is necessary before widespread use.

Project description:Klotho and Fibroblast Growth Factor (FGF)-23 were recently postulated as candidate biomarkers and/or therapeutic targets in acute kidney injury (AKI). We examined whether urine Klotho and serum intact FGF23 levels were differentially and independently associated with major adverse kidney events (MAKE) in critically ill patients with and without AKI. Single-center, prospective, case-control study. ICU in a tertiary medical center. 54 AKI patients and 52 controls without AKI admitted to the ICU. None. AKI was defined by KDIGO criteria and included only AKI stage ≥2. Controls were matched by age, gender, and baseline eGFR. Paired serum and urine samples were obtained 24-48h after AKI diagnosis (cases) or ICU admission (controls). The primary outcome was 90-day MAKE, which was the composite of all-cause death, dependence on renal replacement therapy or a 50% or higher decrease in eGFR from baseline. Forty-four (41.5%) patients developed MAKE-90. Patients who developed MAKE-90 had more comorbidity, higher acuity of illness scores and more prevalent AKI. Levels of urine Klotho adjusted by creatinine (Cr) were lower and serum intact FGF23 levels were higher in AKI patients vs. ICU controls. In adjusted models, the highest vs. lowest tertile of urine Klotho/Cr was independently associated with an overall 95% lower risk of MAKE-90 (81% lower risk in patients with AKI). The highest vs. lowest tertile of serum intact FGF23 was associated with >300% higher risk of MAKE-90. Urine Klotho/Cr levels were significantly lower and serum intact FGF23 levels significantly higher in critically ill patients with AKI vs. matched-controls without AKI. When measured in the first 48h of ICU admission or AKI diagnosis, urine Klotho/Cr independently associated with major adverse kidney events, particularly in patients with AKI. These results show promise for testing these biomarkers -individually or in combination- as part of novel risk-prediction models of renal outcomes in the ICU.

Project description:OBJECTIVE:Guidelines recommend that encephalopathic critically ill children undergo continuous electroencephalographic (CEEG) monitoring for electrographic seizure (ES) identification and management. However, limited data exist on antiseizure medication (ASM) safety for ES treatment in critically ill children. METHODS:We performed a single-center prospective observational study of encephalopathic critically ill children undergoing CEEG. Clinical and EEG features and ASM utilization patterns were evaluated. We determined the incidence, types, and risk factors for adverse events associated with ASM administration. RESULTS:A total of 472 consecutive critically ill children undergoing CEEG were enrolled. ES occurred in 131 children (28%). Clinicians administered ASM to 108 children with ES (82%). ES terminated after the initial ASM in 38% of patients who received one ASM, after the second ASM in 35% of patients who received two ASMs, after the third ASM in 50% of patients who received three ASMs, and after the fourth ASM in 53% of patients who received four ASMs. Thirty patients (28%) received anesthetic infusions for ES management. Adverse events occurred in 18 patients (17%). Adverse effects were expected and resolved in all patients, and they were generally serious (in 15 patients) and definitely related (in 12 patients). Adverse events were rare in patients with acute symptomatic seizures requiring only one to two ASMs for treatment, but were more common in children with epilepsy, ictal-interictal continuum EEG patterns, or patients requiring more extensive ASM management. SIGNIFICANCE:ES ceased after one ASM in only 38% of critically ill children but ceased after two ASMs in 73% of critically ill children. Thus, ES management was often accomplished with readily available medications, but optimization of multistep ES management strategies might be beneficial. Adverse events were rare and manageable in children with acute symptomatic seizures requiring only one to two ASMs for treatment. Future studies are needed to determine whether management of acute symptomatic ES improves neurobehavioral outcomes.

Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyteÂ® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyteÂ® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyteÂ® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyteÂ® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyteÂ® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyteÂ® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples Retrospective, mutli-site sutdy using retrospective physician adjudication as a comparator

Project description:Background and objectivesMajor adverse kidney events, a composite of death, new kidney replacement therapy, or persistent kidney dysfunction, is a potential patient-centered outcome for clinical trials in sepsis-associated kidney injury. We sought to determine the incidence of major adverse kidney events within 30 days and validate this end point in pediatric sepsis.Design, setting, participants, & measurementsWe conducted a retrospective observational study using the Pediatric Health Information Systems Plus database of patients >6 months to <18 years old with a diagnosis of severe sepsis/septic shock; orders for bacterial blood culture, antibiotics, and at least one fluid bolus on hospital day 0/1; and known hospital disposition between January 2007 and December 2011. The primary outcome was incidence of major adverse kidney events within 30 days. Major adverse kidney events within 30 days were validated against all-cause mortality at hospital discharge, hospital length of stay, total hospital costs, hospital readmission within 30 days and 1 year, and lowest eGFR between 3 months and 1 year after discharge. We reported incidence of major adverse kidney events within 30 days with 95% confidence intervals using robust SEM and used multivariable logistic regression to test the association of major adverse kidney events within 30 days with hospital costs and mortality.ResultsOf 1685 admissions, incidence of major adverse kidney events within 30 days was 9.6% (95% confidence interval, 8.1% to 11.0%), including 4.5% (95% confidence interval, 3.5% to 5.4%) death, 1.7% (95% confidence interval, 1.1% to 2.3%) kidney replacement therapy, and 5.8% (95% confidence interval, 4.7% to 6.9%) persistent kidney dysfunction. Patients with versus without major adverse kidney events within 30 days had higher all-cause mortality at hospital discharge (28% versus 1%; P<0.001), higher total hospital costs ($61,188; interquartile range, $21,272-140,356 versus $28,107; interquartile range, $13,056-72,697; P<0.001), and higher proportion with eGFR<60 ml/min per 1.73 m2 between 3 months and 1 year after discharge (19% versus 4%; P=0.001). Major adverse kidney events within 30 days was not associated with length of stay or readmissions.ConclusionsIn children with sepsis, major adverse kidney events within 30 days are common, feasible to measure, and a promising end point for future clinical trials.

Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples

Dataset Information

Predicting Major Adverse Kidney Events among Critically Ill Adults Using the Electronic Health Record.

Publications

Predicting Major Adverse Kidney Events among Critically Ill Adults Using the Electronic Health Record.

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