Abdominal Compartment Syndrome and Acute Kidney Injury Due to Excessive Auto–Positive End-Expiratory Pressure

Matthew, Dwight; Oxman, David; Djekidel, Karim; Ahmed, Ziauddin; Sherman, Michael S.

doi:10.1053/j.ajkd.2012.06.030

Cited by 8 publications

(5 citation statements)

References 12 publications

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“…The median APACHE II score of patients in the AKI group is much higher than that in the non-AKI group (18.28 vs. 9.87, p < 0.005). IAP is the most important feature in the XGBoost model, and previous studies showed that IAP is the independent risk factor for AKI [ 31 – 34 ]. Locally in the abdomen, intra-abdominal hypertension compresses and compromises blood flow in the renal parenchyma, vena cava, and renal vein.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Models of Acute Kidney Injury Prediction in Acute Pancreatitis Patients

Cheng

Mei

et al. 2020

Gastroenterology Research and Practice

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Background. Acute kidney injury (AKI) has long been recognized as a common and important complication of acute pancreatitis (AP). In the study, machine learning (ML) techniques were used to establish predictive models for AKI in AP patients during hospitalization. This is a retrospective review of prospectively collected data of AP patients admitted within one week after the onset of abdominal pain to our department from January 2014 to January 2019. Eighty patients developed AKI after admission (AKI group) and 254 patients did not (non-AKI group) in the hospital. With the provision of additional information such as demographic characteristics or laboratory data, support vector machine (SVM), random forest (RF), classification and regression tree (CART), and extreme gradient boosting (XGBoost) were used to build models of AKI prediction and compared to the predictive performance of the classic model using logistic regression (LR). XGBoost performed best in predicting AKI with an AUC of 91.93% among the machine learning models. The AUC of logistic regression analysis was 87.28%. Present findings suggest that compared to the classical logistic regression model, machine learning models using features that can be easily obtained at admission had a better performance in predicting AKI in the AP patients.

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Section: Discussionmentioning

confidence: 99%

Machine Learning Models of Acute Kidney Injury Prediction in Acute Pancreatitis Patients

Cheng

Mei

et al. 2020

Gastroenterology Research and Practice

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“…Matthew et al. reported a patient with ACS presented with AKI caused by air‐trapping and excessive auto‐positive end‐expiratory pressure during intubation and recovered after extubation. After abdominal surgeries IAH is not rare and measurement of IAP is thought to be a predictor of AKI development for patients followed in intensive care units .…”

Section: Discussionmentioning

confidence: 99%

Acute kidney injury due to abdominal compartment syndrome caused by duodenal metastases of prostate cancer

Gürel

2015

Clinical Case Reports

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“…The pathophysiology of ACS is intricate and complex. Abdominal disease is the most common etiology of ACS, such as abdominal surgery, abdominal trauma, and ileus [ 26 ]. Therefore, abdominal viscera are the most commonly affected organs.…”

Section: Discussionmentioning

confidence: 99%

Controlled peritoneal drainage improves survival in children with abdominal compartment syndrome

et al. 2015

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BackgroundChildren with massive ascites can develop abdominal compartment syndrome (ACS), which has been identified as an independent risk factor for mortality.ObjectivesThe objective of this study was to assess the effectiveness of volume-controlled percutaneous catheter drainage (PCD) for treating children with massive ascites and ACS.MethodsA retrospective descriptive study was conducted; Comprising 12patients with ACS with massive ascites treated with volume-controlled PCD in a pediatric intensive care unitof a university hospital in southern China from April 2011 to June 2013.ResultsThe etiology of ascites in these children included abdominal tumor (8/12), capillary leak after liver or kidney transplantation (2/12) and urine leakage (2/12). Intra-abdominal hypertension was closely associated with multiple organ dysfunction and high mortality. Digestive and pulmonary functions were the most frequently affected by ACS, while the cerebrum was the least involved. Treatment with ultrasound-guided PCD significantly decreased intra-abdominal pressure, abdominal circumference, and indices of organ dysfunction. PCD treatment also significantly improved glomerular filtration rate and PaO2/FiO2. Complications of PCD included abdominal infection (1/12) and electrolyte imbalance (4/12). The mortality rate of patients treated with PCD was 25%, which was lower than previous reports.ConclusionsControlled peritoneal drainage is a minimally invasive and safe decompression method that is effective in patients with ACS, and should be considered in children with massive ascites.

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Abdominal Compartment Syndrome and Acute Kidney Injury Due to Excessive Auto–Positive End-Expiratory Pressure

Cited by 8 publications

References 12 publications

Machine Learning Models of Acute Kidney Injury Prediction in Acute Pancreatitis Patients

Machine Learning Models of Acute Kidney Injury Prediction in Acute Pancreatitis Patients

Acute kidney injury due to abdominal compartment syndrome caused by duodenal metastases of prostate cancer

Controlled peritoneal drainage improves survival in children with abdominal compartment syndrome

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