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

Autor:	A. R. De Gaudio, Silvia Falsini, Gianluca Villa, Cosimo Chelazzi, I. Vignale, Luca Boni
Rok vydání:	2015
Předmět:	medicine.medical_specialty Receiver operating characteristic business.industry Area under the curve General Medicine Anesthesiology and Pain Medicine Cutoff Medicine Derivation Radiology Risk factor Post operative Risk assessment Prospective cohort study business
Zdroj:	Acta Anaesthesiologica Scandinavica. 59:609-618
ISSN:	0001-5172
DOI:	10.1111/aas.12488
Popis:	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 Anesthesiological and Surgical Postoperative Risk Assessment (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 Clavien-Dindo 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.
Databáze:	OpenAIRE
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