Intra-Abdominal Hypertension and Compartment Syndrome after Pediatric Liver Transplantation: Incidence, Risk Factors and Outcome.
Norman JungeAnnika ArtmannNicolas RichterFlorian W R VondranDietmar BöthigMichael SasseHarald KöditzUlrich BaumannPhilipp BeerbaumTorsten KaussenPublished in: Children (Basel, Switzerland) (2022)
In pediatric liver transplantation (pLT), the risk for the manifestation and relevance of intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS) is high. This observational study aimed to evaluate the incidence, relevance and risk factors for IAH and ACS by monitoring the intra-abdominal pressure (IAP), macro- and microcirculation (near-infrared spectroscopy (NIRS)), clinical and laboratory status and outcomes of 27 patients (16 female) after pLT (median age at pLT 35 months). Of the patients, 85% developed an elevated IAP, most of them mild. However, 17% achieved IAH° 3, 13% achieved IAH° 4 and 63% developed ACS. A multiple linear regression analysis identified aortal hepatic artery anastomosis and cold ischemia time (CIT) as risk factors for increased IAP and longer CIT and staged abdominal wall closure for ACS. ACS patients had significantly longer mechanical ventilation ( p = 0.004) and LOS-PICU ( p = 0.003). No significant correlation between NIRS or biliary complications and IAH or ACS could be shown. IAH and ACS after pLT were frequent. NIRS or grade of IAH alone should not be used for monitoring. A longer CIT is an important risk factor for higher IAP and ACS. Therefore, approaches such as the ex vivo machine perfusion of donor organs, reducing CIT effects on them, have great potential. Our study provides important basics for studying such approaches.
Keyphrases
- acute coronary syndrome
- end stage renal disease
- risk factors
- ejection fraction
- newly diagnosed
- chronic kidney disease
- mechanical ventilation
- prognostic factors
- intensive care unit
- type diabetes
- magnetic resonance
- computed tomography
- metabolic syndrome
- machine learning
- skeletal muscle
- adipose tissue
- risk assessment
- deep learning
- climate change
- contrast enhanced