Optimized vascular network by stereolithography for tissue engineered skin

This paper demonstrates the essential and efficient methods to design, and fabricate optimal vascular network for tissue engineering structures based on their physiological conditions. Comprehensive physiological requirements in both micro and macro scales were considered in developing the optimisation design for complex vascular vessels. The optimised design was then manufactured by stereolithography process using materials that are biocompatible, elastic and surface bio-coatable. The materials are self-developed photocurable resin consist of BPA-ethoxylated-diacrylate, lauryl acrylate and isobornylacrylate with Irgacure® 184, the photoinitiator. The optimised vascular vessel offers many advantages: 1) it provides the maximum nutrient supply; 2) it minimises the recirculation areas and 3) it allows the wall shear stress on the vessel in a healthy range. The stereolithography manufactured vascular vessels were then embedded in the hydrogel seeded with cells. The results of in vitro studies show that the optimised vascular network has the lowest cell death rate compared with a pure hydrogel scaffold and a hydrogel scaffold embedded within a single tube in day seven. Consequently, these design and manufacture routes were shown to be viable for exploring and developing a high range complex and specialised artificial vascular networks

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

Background Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. Methods We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). Findings In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683–0·717]). Interpretation In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. Funding British Journal of Surgery Society