Dataset Information

The use of venous Doppler to predict adverse kidney events in a general ICU cohort.

ABSTRACT: BACKGROUND:Changes in Doppler flow patterns of hepatic veins (HV), portal vein (PV) and intra-renal veins (RV) reflect right atrial pressure and venous congestion; the feasibility of obtaining these assessments and the clinical relevance of the findings is unknown in a general ICU population. This study compares the morphology of HV, PV and RV waveform abnormalities in prediction of major adverse kidney events at 30 days (MAKE30) in critically ill patients. STUDY DESIGN AND METHODS:We conducted a prospective observational study enrolling adult patients within 24 h of admission to the ICU. Patients underwent an ultrasound evaluation of the HV, PV and RV. We compared the rate of MAKE-30 events in patients with and without venous flow abnormalities in the hepatic, portal and intra-renal veins. The HV was considered abnormal if S to D wave reversal was present. The PV was considered abnormal if the portal pulsatility index (PPI) was greater than 30%. We also examined PPI as a continuous variable to assess whether small changes in portal vein flow was a clinically important marker of venous congestion. RESULTS:From January 2019 to June 2019, we enrolled 114 patients. HV abnormalities demonstrate an odds ratio of 4.0 (95% CI 1.4-11.2). PV as a dichotomous outcome is associated with an increased odds ratio of MAKE-30 but fails to reach statistical significance (OR 2.3 95% CI 0.87-5.96), but when examined as a continuous variable it demonstrates an odds ratio of 1.03 (95% CI 1.00-1.06). RV Doppler flow abnormalities are not associated with an increase in the rate of MAKE-30 INTERPRETATION: Obtaining hepatic, portal and renal venous Doppler assessments in critically ill ICU patients are feasible. Abnormalities in hepatic and portal venous Doppler are associated with an increase in MAKE-30. Further research is needed to determine if venous Doppler assessments can be useful measures in assessing right-sided venous congestion in critically ill patients.

SUBMITTER: Spiegel R

PROVIDER: S-EPMC7574322 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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The use of venous Doppler to predict adverse kidney events in a general ICU cohort.

Spiegel Rory R Teeter William W Sullivan Scott S Tupchong Keegan K Mohammed Nabeel N Sutherland Mark M Leibner Evan E Rola Philippe P Galvagno Samuel M SM Murthi Sarah B SB

Critical care (London, England) 20201019 1

<h4>Background</h4>Changes in Doppler flow patterns of hepatic veins (HV), portal vein (PV) and intra-renal veins (RV) reflect right atrial pressure and venous congestion; the feasibility of obtaining these assessments and the clinical relevance of the findings is unknown in a general ICU population. This study compares the morphology of HV, PV and RV waveform abnormalities in prediction of major adverse kidney events at 30 days (MAKE30) in critically ill patients.<h4>Study design and methods</h ...[more]

PMID: 33076961

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Project description:BackgroundEmergency general surgery (EGS) is associated with increased mortality, with kidney failure a contributing risk, but comparative outcomes between patients with kidney failure and the general population are lacking.MethodsIn this retrospective population-cohort study, data were analysed for all EGS procedures performed in England between 1 April 2004 and 31 March 2019. EGS was defined as partial colectomy, small bowel resection, cholecystectomy, appendicectomy, lysis of peritoneal adhesions, surgery for peptic ulcer, or laparotomy. The main outcome measure was major adverse cardiovascular events (MACEs) and all-cause mortality after surgery.ResultsFrom 691 064 procedures, 0.16 per cent (n = 1097) and 0.23 per cent (n = 1567) were performed on kidney transplant and dialysis recipients respectively. Laparotomy was the most frequent EGS procedure for kidney transplant (46 per cent of procedures, n = 507) and dialysis (45 per cent of procedures, n = 704) recipients, with the highest 30-day and 1-year mortality. In logistic regression analysis, both kidney failure cohorts had higher risk for experiencing MACEs in the postoperative interval after emergency laparotomy; within 3 months (dialysis; OR 2.44 (95 per cent c.i. 2.08 to 2.87), P < 0.001 and transplant; OR 2.05 (95 per cent c.i. 1.57 to 2.68), P < 0.001) and within 1 year (dialysis; OR 2.39 (95 per cent c.i. 2.06 to 2.77), P < 0.001 and transplant; OR 2.21 (95 per cent c.i. 1.76 to 2.77), P < 0.001); however, in a propensity-score-matched cohort, increased risk for MACEs was observed among dialysis patients after emergency laparotomy (HR 2.10 (95 per cent c.i. 1.82 to 2.43), P < 0.001) but not kidney transplant recipients (HR 1.17 (95 per cent c.i. 0.97 to 1.41), P = 0.096).ConclusionMortality after emergency surgery is higher for patients with kidney failure and dialysis is worse than kidney transplantation, with cardiovascular deaths more common than the general population.

Project description:BACKGROUND:More than 20% of patients admitted to the intensive care unit (ICU) develop an adverse event (AE). No previous study has leveraged patients' data to extract the temporal features using their structural temporal patterns, that is, trends. OBJECTIVE:This study aimed to improve AE prediction methods by using structural temporal pattern detection that captures global and local temporal trends and to demonstrate these improvements in the detection of acute kidney injury (AKI). METHODS:Using the Medical Information Mart for Intensive Care dataset, containing 22,542 patients, we extracted both global and local trends using structural pattern detection methods to predict AKI (ie, binary prediction). Classifiers were built on 17 input features consisting of vital signs and laboratory test results using state-of-the-art models; the optimal classifier was selected for comparisons with previous approaches. The classifier with structural pattern detection features was compared with two baseline classifiers that used different temporal feature extraction approaches commonly used in the literature: (1) symbolic temporal pattern detection, which is the most common approach for multivariate time series classification; and (2) the last recorded value before the prediction point, which is the most common approach to extract temporal data in the AKI prediction literature. Moreover, we assessed the individual contribution of global and local trends. Classifier performance was measured in terms of accuracy (primary outcome), area under the curve, and F-measure. For all experiments, we employed 20-fold cross-validation. RESULTS:Random forest was the best classifier using structural temporal pattern detection. The accuracy of the classifier with local and global trend features was significantly higher than that while using symbolic temporal pattern detection and the last recorded value (81.3% vs 70.6% vs 58.1%; P<.001). Excluding local or global features reduced the accuracy to 74.4% or 78.1%, respectively (P<.001). CONCLUSIONS:Classifiers using features obtained from structural temporal pattern detection significantly improved the prediction of AKI onset in ICU patients over two baselines based on common previous approaches. The proposed method is a generalizable approach to predict AEs in critical care that may be used to help clinicians intervene in a timely manner to prevent or mitigate AEs.

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.

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The use of venous Doppler to predict adverse kidney events in a general ICU cohort.

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The use of venous Doppler to predict adverse kidney events in a general ICU cohort.

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