Implementation and preliminary validation of a new score that predicts post‐operative complications

Background An accurate pre‐operative risk assessment could reduce morbidity and mortality for high‐risk surgical patients. The aim of the study was to implement and preliminary validate a new score that could predict the occurrence of post‐operative complications ( PoCs ): the A nesthesiological and S urgical P ostoperative R isk A ssessment ( ASPRA ) score. Methods The ASPRA score was created through a literature's review; a score of 1–3 was given to each identified risk factor, according to its statistical correlation with PoC . ASPRA was retrospectively applied to a derivation set of 176 surgical patients. A receiver operating characteristic ( ROC ) analysis evaluated the discriminating ability of the score and cutoff value in predicting the occurrence of PoCs , according to the C lavien‐ D indo classification of surgical complications. The statistical validation of the score and related cutoff values was prospectively ran within a validation set of 1928 surgical patients. Results Through ROC analysis, an ASPRA score of 7 was chosen as the cutoff value in the derivation set. In the validation set, 65.3% of patients presented a PoC (Clavien ≥ 1). In this group, ROC analysis showed an area under the curve ( AUC ) of 0.72, and although potentially related to the high rate of complications a high positive predictive value of 87.0% has been observed. No significant differences were found in ROC‐AUC , sensitivity, specificity, or positive or negative predictive value between the derivation and validation sets ( P  > 0.05). Conclusion The new ASPRA score has a high positive predictive value to predict the occurrence of PoCs . Further prospective studies are required to confirm these results.