Dataset Information

Peripheral Edema, Central Venous Pressure, and Risk of AKI in Critical Illness.

ABSTRACT: Although venous congestion has been linked to renal dysfunction in heart failure, its significance in a broader context has not been investigated.Using an inception cohort of 12,778 critically ill adult patients admitted to an urban tertiary medical center between 2001 and 2008, we examined whether the presence of peripheral edema on admission physical examination was associated with an increased risk of AKI within the first 7 days of critical illness. In addition, in those with admission central venous pressure (CVP) measurements, we examined the association of CVPs with subsequent AKI. AKI was defined using the Kidney Disease Improving Global Outcomes criteria.Of the 18% (n=2338) of patients with peripheral edema on admission, 27% (n=631) developed AKI, compared with 16% (n=1713) of those without peripheral edema. In a model that included adjustment for comorbidities, severity of illness, and the presence of pulmonary edema, peripheral edema was associated with a 30% higher risk of AKI (95% confidence interval [95% CI], 1.15 to 1.46; P<0.001), whereas pulmonary edema was not significantly related to risk. Peripheral edema was also associated with a 13% higher adjusted risk of a higher AKI stage (95% CI, 1.07 to 1.20; P<0.001). Furthermore, levels of trace, 1+, 2+, and 3+ edema were associated with 34% (95% CI, 1.10 to 1.65), 17% (95% CI, 0.96 to 1.14), 47% (95% CI, 1.18 to 1.83), and 57% (95% CI, 1.07 to 2.31) higher adjusted risk of AKI, respectively, compared with edema-free patients. In the 4761 patients with admission CVP measurements, each 1 cm H2O higher CVP was associated with a 2% higher adjusted risk of AKI (95% CI, 1.00 to 1.03; P=0.02).Venous congestion, as manifested as either peripheral edema or increased CVP, is directly associated with AKI in critically ill patients. Whether treatment of venous congestion with diuretics can modify this risk will require further study.

SUBMITTER: Chen KP

PROVIDER: S-EPMC4822669 | biostudies-other | 2016 Apr

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Peripheral Edema, Central Venous Pressure, and Risk of AKI in Critical Illness.

Chen Kenneth P KP Cavender Susan S Lee Joon J Feng Mengling M Mark Roger G RG Celi Leo Anthony LA Mukamal Kenneth J KJ Danziger John J

Clinical journal of the American Society of Nephrology : CJASN 20160119 4

<h4>Background and objectives</h4>Although venous congestion has been linked to renal dysfunction in heart failure, its significance in a broader context has not been investigated.<h4>Design, setting, participants, & measurements</h4>Using an inception cohort of 12,778 critically ill adult patients admitted to an urban tertiary medical center between 2001 and 2008, we examined whether the presence of peripheral edema on admission physical examination was associated with an increased risk of AKI ...[more]

PMID: 26787777

Similar Datasets

Project description:The cardiorenal syndrome generally focuses on left ventricular function, and the importance of the right ventricle as a determinant of renal function is described less frequently. In a cohort of critically ill patients with echocardiographic measurements obtained within 24 hours of admission to the intensive care unit, we examined the association of right ventricular function with acute kidney injury (AKI) and AKI-associated mortality. We also examined whether clinical measurement of volume overload modified the association between ventricular function and AKI in a subpopulation with documented admission physical examinations.Among 1879 critically ill patients with echocardiographic ventricular measurements, 43% (n = 807) had ventricular dysfunction-21% (n = 388), 9% (n = 167), and 13% (n = 252) with isolated left ventricular dysfunction, isolated right ventricular dysfunction, and biventricular dysfunction, respectively. Overall, ventricular dysfunction was associated with a 43% higher adjusted risk of AKI (95% confidence interval [CI] 1.14-1.80; P = 0.002) compared with those with normal biventricular function, whereas isolated left ventricular dysfunction, isolated right ventricular dysfunction, and biventricular dysfunction were associated with a 1.34 (95% CI 1.00-1.77, P = 0.05), 1.35 (95% CI 0.90-2.10, P = 0.14) and 1.67 (95% CI 1.23-2.31, P = 0.002) higher adjusted risk. Although an episode of AKI was associated with an approximately 2-fold greater risk of hospital mortality in those with isolated left ventricular dysfunction and biventricular dysfunction, in those with isolated right ventricular dysfunction, AKI was associated with a 7.85-fold greater risk of death (95% CI 2.89-21.3, P < 0.001). Independent of ventricular function, peripheral edema was an important determinant of AKI.Like left ventricular function, right ventricular function is an important determinant of AKI and AKI-associated mortality. Volume overload, independently of ventricular function, is a risk factor for AKI. Whether establishment of euvolemia might mitigate AKI risk will require further study.

Project description:Background and objectivesAKI is a risk factor for development or worsening of CKD. However, diagnosis of renal dysfunction by serum creatinine could be confounded by loss of muscle mass and creatinine generation after critical illness.Design, setting, participants, & measurementsA retrospective, single center analysis of serum in patients surviving to hospital discharge with an intensive care unit admission of 5 or more days between 2009 and 2011 was performed.ResultsIn total, 700 cases were identified, with a 66% incidence of AKI. In 241 patients without AKI, creatinine was significantly lower (P<0.001) at hospital discharge than admission (median, 0.61 versus 0.88 mg/dl; median decrease, 33%). In 160 patients with known baseline, discharge creatinine was significantly lower than baseline in all patients except those patients with severe AKI (Kidney Disease Improving Global Outcomes category 3), who had no significant difference. In a multivariable regression model, median duration of hospitalization was associated with a predicted 30% decrease (95% confidence interval, 8% to 45%) in creatinine from baseline in the absence of AKI; after allowing for this effect, AKI was associated with a 29% (95% confidence interval, 10% to 51%) increase in predicted hospital discharge creatinine. Using a similar model to exclude the confounding effect of prolonged major illness on creatinine, 148 of 700 patients (95% confidence interval, 143 to 161) would have eGFR<60 ml/min per 1.73 m(2) at hospital discharge compared with only 63 of 700 patients using eGFR based on unadjusted hospital creatinine (a 135% increase in potential CKD diagnoses; P<0.001).ConclusionCritical illness is associated with significant falls in serum creatinine that persist to hospital discharge, potentially causing inaccurate assessment of renal function at discharge, particularly in survivors of AKI. Prospective measurements of GFR and creatinine generation are required to confirm the significance of these findings.

Project description:BackgroundAn increase in the incidence of central venous catheter (CVC)-associated deep venous thrombosis (CADVT) has been reported in pediatric patients over the past decade. At the same time, current screening guidelines for venous thromboembolism risk have low sensitivity for CADVT in hospitalized children. This study utilized a multimodal deep learning model to predict CADVT before it occurs.MethodsChildren who were admitted to intensive care units (ICUs) between December 2015 and December 2018 and with CVC placement at least 3 days were included. The variables analyzed included demographic characteristics, clinical conditions, laboratory test results, vital signs and medications. A multimodal deep learning (MMDL) model that can handle temporal data using long short-term memory (LSTM) and gated recurrent units (GRUs) was proposed for this prediction task. Four benchmark machine learning models, logistic regression (LR), random forest (RF), gradient boosting decision tree (GBDT) and a published cutting edge MMDL, were used to compare and evaluate the models with a fivefold cross-validation approach. Accuracy, recall, area under the ROC curve (AUC), and average precision (AP) were used to evaluate the discrimination of each model at three time points (24 h, 48 h and 72 h) before CADVT occurred. Brier score and Spiegelhalter's z test were used measure the calibration of these prediction models.ResultsA total of 1830 patients were included in this study, and approximately 15% developed CADVT. In the CADVT prediction task, the model proposed in this paper significantly outperforms both traditional machine learning models and existing multimodal deep learning models at all 3 time points. It achieved 77% accuracy and 90% recall at 24 h before CADVT was discovered. It can be used to accurately predict the occurrence of CADVT 72 h in advance with an accuracy of greater than 75%, a recall of more than 87%, and an AUC value of 0.82.ConclusionIn this study, a machine learning method was successfully established to predict CADVT in advance. These findings demonstrate that artificial intelligence (AI) could provide measures for thromboprophylaxis in a pediatric intensive care setting.

Dataset Information

Peripheral Edema, Central Venous Pressure, and Risk of AKI in Critical Illness.

Publications

Peripheral Edema, Central Venous Pressure, and Risk of AKI in Critical Illness.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets