When clinical and laboratory parameters are included, a model predicting intraoperative MT in patients undergoing liver transplantation is sufficiently accurate that its predictions could guide the blood order schedule for individual patients based on institutional data, thereby reducing the impact on blood bank resources. Ongoing evaluation of model accuracy and transfusion practices is required to ensure continuing performance of the predictive model.

Background Clinical monitoring of cerebral blood flow (CBF) autoregulation in patients undergoing liver transplantation may provide a means for optimizing blood pressure to reduce the risk of brain injury. The purpose of this pilot project is to test the feasibility of autoregulation monitoring with transcranial Doppler (TCD) and near infrared spectroscopy (NIRS) in patients undergoing liver transplantation and to assess changes that may occur perioperatively. Methods We performed a prospective observational study in 9 consecutive patients undergoing orthotopic liver transplantation. Patients were monitored with TCD and NIRS. A continuous Pearson’s correlation coefficient was calculated between mean arterial pressure (MAP) and CBF velocity and between MAP and NIRS data, rendering the variables mean velocity index (Mx) and cerebral oximetry index (COx), respectively. Both Mx and COx were averaged and compared during the dissection phase, anhepatic phase, first 30 mins of reperfusion, and remaining reperfusion phase. Impaired autoregulation was defined as Mx ≥ 0.4. Results Autoregulation was impaired in one patient during all phases of surgery, in two patients during the anhepatic phase, and in one patient during reperfusion. Impaired autoregulation was associated with a MELD score > 15 (p=0.015) and postoperative seizures or stroke (p<0.0001). Analysis of Mx categorized in 5-mmHg bins revealed that MAP at the lower limit of autoregulation (MAP when Mx increased to ≥ 0.4) ranged between 40 and 85 mmHg. Average Mx and average COx were significantly correlated (p=0.0029). The relationship between COx and Mx remained when only patients with bilirubin > 1.2 mg/dL were evaluated (p=0.0419). There was no correlation between COx and baseline bilirubin (p=0.2562) but MELD score and COx were correlated (p=0.0458). Average COx was higher for patients with a MELD score > 15 (p=0.073) and for patients with a neurologic complication than for patients without neurologic complications (p=0.0245). Conclusions These results suggest that autoregulation is impaired in patients undergoing liver transplantation, even in the absence of acute, fulminant liver failure. Identification of patients at risk for neurologic complications after surgery may allow for prompt neuroprotective interventions, including directed pressure management.

Background: Intraoperative massive transfusion (MT) is common during liver transplantation (LT). A predictive model of MT has the potential to improve use of blood bank resources. Study Design and Methods: Development and validation cohorts were identified among deceased-donor LT recipients from 2010 to 2016. A multivariable model of MT generated from the development cohort was validated with the validation cohort and refined using both cohorts. The combined cohort also validated the previously reported McCluskey risk index (McRI). A simple modified risk index (ModRI) was then created from the combined cohort. Finally, a method to translate model predictions to a population-specific blood allocation strategy was described and demonstrated for the study population. Results: Of the 403 patients, 60 (29.6%) in the development and 51 (25.5%) in the validation cohort met the definition for MT. The ModRI, derived from variables incorporated into multivariable model, ranged from 0 to 5, where 1 point each was assigned for hemoglobin level of less than 10 g/dL, platelet count of less than 100 × 10 9 /dL, thromboelastography R interval of more than 6 minutes, simultaneous liver and kidney transplant and retransplantation, and a ModRI of more than 2 defined recipients at risk for MT. The multivariable model, McRI, and ModRI demonstrated good discrimination (c statistic