The prognostic evaluation of acute pancreatitis

Early identification of severity is one of the most important problems in acute pancreatitis, both for decision-making and classification. Predictive criteria show a wide range of accuracy: clinical examination (on admission: 76-85%); single laboratory data (PCR: 68-98%, C3-C4: 63-72%); multifactorial scoring systems (Ranson: 65-82%, Imrie: 78-95%); diagnostic peritoneal lavage (72-90%); CT features (52-81%). In 1982 we started a prospective evaluation of the prognostic performances of a bayesian statistical model for the prediction of severe vs mild pancreatis and death vs survival, which uses the outcome-related patterns of several variables, assuming their independence, analysed on a data of 44 patients. The performances have been calculated prospectively by comparing the expected vs actual results on 88 further patients (accuracy, sensitivity and specificity, respectively, in the prediction of severe pancreatitis: 92%, 92%, 93%; in the prediction of death: 95%, 97%, 87%). Moreover, the model can represent classes of risk by combining prediction of death + severe pancreatitis (DSP), survival + severe pancreatitis (SSP) and survival + mild pancreatitis (SMP) (accuracy, sensitivity and specificity, respectively, in the prediction of DSP: 97%, 83%, 100%; in the prediction of SSP: 95%, 87%, 97%; in the prediction of SMP: 95%, 97%, 90%). Our model enables clinicians dealing with other population to re-determine different variables or integrate them with new information, whenever available. It seems to be transferable and adaptable, even with a probable further increase of the performances, without compromising the objectivity of the predictive judgement and the homogeneity of the classes of risk