Proposal of a Multivariable Prediction Model for Graded Morbidity after Liver Resection for Colorectal Metastases.

BACKGROUND: Prognostic models to predict individual early postoperative morbidity after liver resection for colorectal liver metastases (CLM) are not available but could enable optimized preoperative patient selection and postoperative surveillance for patients at greater risk of complications. The aim of this study was to establish a prognostic model for the prediction of morbidity after liver resection graded according to Dindo. METHODS: N = 679 cases of primary liver resection for CLM were retrospectively analyzed using univariable and multivariable ordinal regression analyses. Receiver operating characteristics curve (ROC) analysis was utilised to assess the sensitivity and specificity of predictions and their potential usefulness as prognostic models. Internal validation of the score was performed using data derived from 129 patients. RESULTS: The final multivariable regression model revealed lower preoperative levels, a greater number of units of intraoperatively transfused packed red blood cells (pRBCs), longer duration of surgery, and larger metastases to independently influence postoperatively graded morbidity. ROC curve analysis demonstrated that the multivariable regression model is able to predict each individual grade of postoperative morbidity with high sensitivity and specificity. The areas under the receiver operating curves (AUROC) for all of these predictions of individual grades of morbidity were > 0.700, indicating potential usefulness as a predictive model. Moreover, a consistent concordance in Grades I, II, IV, and V according to the classification proposed by Dindo et al. was observed in the internal validation. CONCLUSION: This study proposes a prognostic model for the prediction of each grade of postoperative morbidity after liver resection for CLM with high sensitivity and specificity using pre- and intraoperatively available variables.

Identifying an optimal seeding protocol and endothelial cell substrate for biohybrid lung development.

Several key prerequisites need to be fulfilled for the development of a biohybrid lung, which can offer an actual alternative to lung transplantation. A major aspect is an optimized haemocompatibility of the device's artificial surfaces via endothelial cell seeding. In this study, four different types of polymeric gas exchange hollow fibre membranes (HFMs) were analysed utilizing four different seeding protocols in order to identify the ideal combination for sufficient long-term endothelialization. Human cord blood-derived endothelial cells (HCBECs) were used for the endothelialization of polypropylene HFMs with two different pore sizes and poly-4-methyl-1-pentene HFMs, both with and without heparin/albumin coating. The qualitative and quantitative impact of four different rotational seeding protocols regarding long-term HFM endothelialization and the impact of inflammatory stimulation on the seeded HCBECs were examined by fluorescence microscopy, cell counting, and analysis of relative expression levels of activation, shear stress, and thrombogenic state markers. Optimized endothelial cell seeding and long-term cultivation were only achieved using heparin/albumin-coated poly-4-methyl-1-pentene HFMs, applying 24 hr of rotational speed at 1 rpm followed by 120 hr of static culture. Neither cell-to-HFM contact nor the rotational cultivation procedure showed an impact on the physiological anti-thrombogenic and anti-inflammatory HCBEC activation status. Additionally, the cells maintained their physiological responsiveness towards inflammatory stimulation. Rotational seeding strategies and a seamless heparin/albumin coating of the HFMs are crucial requirements for a sufficient and long-lasting endothelialization and thus a key element in the future development and in vivo application of the biohybrid lung.