Estimating pre-operative mortality risk may inform clinical decision-making for peri-operative care. However, pre-operative mortality risk prediction models are rarely implemented in routine clinical practice. High predictive accuracy and clinical usability are essential for acceptance and clinical implementation. In this systematic review, we identified and appraised prediction models for 30-day postoperative mortality in noncardiac surgical cohorts. PubMed and Embase were searched up to December 2022 for studies investigating pre-operative prediction models for 30-day mortality. We assessed predictive performance in terms of discrimination and calibration. Risk of bias was evaluated using a tool to assess the risk of bias and applicability of prediction model studies. To further inform potential adoption, we also assessed clinical usability for selected models. In all, 15 studies evaluating 10 prediction models were included. Discrimination ranged from a cstatistic of 0.82 (MySurgeryRisk) to 0.96 (extreme gradient boosting machine learning model). Calibration was reported in only six studies. Model performance was highest for the surgical outcome risk tool (SORT) and its external validations. Clinical usability was highest for the surgical risk pre-operative assessment system. The SORT and risk quantification index also scored high on clinical usability. We found unclear or high risk of bias in the development of all models. The SORT showed the best combination of predictive performance and clinical usability and has been externally validated in several heterogeneous cohorts. To improve clinical uptake, full integration of reliable models with sufficient face validity within the electronic health record is imperative.

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Background Medical schools seek the best curricular designs for the transition to postgraduate education, such as the Dutch elective-based final, ‘transitional’ year. Most Dutch graduates work a mean of three years as a physician-not-in-training (PNIT) before entering residency training. To ease the transition to selected specialties and to decrease the duration of the PNIT period, UMC Utrecht introduced an optional, thematic variant of the usual transitional year, that enables the development of theme-specific competencies, in addition to physicians’ general competencies. Methods We introduced an optional transitional year for interested students around the theme of acute care, called the Acute Care Transitional Year (ACTY). This study aimed to evaluate the ACTY by judging whether graduates meet postgraduate acute care expectations, indicating enhanced learning and preparation for practice. In a comprehensive assessment of acute care knowledge, clinical reasoning, skills, and performance in simulations, we collected data from ACTY students, non-ACTY students interested in acute care, and PNITs with approximately six months of acute care experience. Results ACTY graduates outperformed non-ACTY graduates on skills and simulations, and had higher odds of coming up to the expectations faculty have of a PNIT, as determined by global ratings. PNITs did better on simulations than ACTY graduates. Discussion ACTY graduates show better resemblance to PNITs than non-ACTY graduates, suggesting better preparation for postgraduate acute care challenges. Conclusion Transitional years, offering multidisciplinary perspectives on a certain theme, can enhance learning and preparedness for entering residency.