Key Learning Points

1. 1. Precise estimates of post-operative mortality and morbidity are difficult to obtain and both are recognised to vary greatly, depending on a patient’s pre-operative functional status, the type and urgency of surgery and whether or not post-operative complications occur.

2. 2. Risk scores apply a weighting to each factor, usually representing a component value for the score, with the resultant score corresponding with predicted risk.

3. 3. Prognostic indicators may include population-based risk scores, individualised risk prediction models, objective functional capacity assessment and biomarkers.

4. 4. Model discrimination describes how well a model discriminates between high- and low-risk patients, and is measured using a receiver operator characteristic curve (ROC) to calculate the area under the curve (AUC).

5. 5. Technically, risk assessment tools are only valid for the specific patient population for whom the tool has been developed and on whom it has been tested.