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Implementation and preliminary validation of a new score that predicts post‐operative complications
Author(s) -
CHELAZZI C.,
VILLA G.,
VIGNALE I.,
FALSINI S.,
BONI L.,
DE GAUDIO A. R.
Publication year - 2015
Publication title -
acta anaesthesiologica scandinavica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.738
H-Index - 107
eISSN - 1399-6576
pISSN - 0001-5172
DOI - 10.1111/aas.12488
Subject(s) - medicine , receiver operating characteristic , cutoff , predictive value , predictive value of tests , derivation , framingham risk score , risk assessment , correlation , surgery , physics , computer security , disease , artery , quantum mechanics , computer science , geometry , mathematics
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.