Background Some authors have proposed different predictive factors of severe acute cholecystitis, but generally, the results of risk analyses are expressed as odds ratios, which makes it difficult to apply in the clinical practice of the acute care surgeon. The severe form of acute cholecystitis should include both gangrenous and phlegmonous cholecystitis, due to their severe clinical course, and cholecystectomy should not be delayed. The aim of this study was to create a nomogram to obtain a graphical tool to compute the probability of having a severe acute cholecystitis. Methods This is a retrospective study on 393 patients who underwent emergency cholecystectomy between January 2010 and December 2015 at the Acute Care Surgery Service of the S. Anna University Hospital of Ferrara, Italy. Patients were classified as having a non-severe acute cholecystitis or a severe acute cholecystitis (i.e., gangrenous and phlegmonous) based on the final pathology report. The baseline characteristics, pre-operative signs, and abdominal ultrasound (US) findings were assessed with a stepwise multivariate logistic regression analysis to predict the risk of severe acute cholecystitis, and a nomogram was created. Results Age as a continuous variable, WBC count ≥ 12.4 × 103/μl, CRP ≥9.9 mg/dl, and presence of US thickening of the gallbladder wall were significantly associated with severe acute cholecystitis at final pathology report. A significant interaction between the effect of age and CRP was found. Four risk classes were identified based on the nomogram total points. Conclusions Patients with a nomogram total point ≥ 74 should be considered at high risk of severe acute cholecystitis (at 74 total point, sensitivity = 78.5%; specificity = 78.2%; accuracy = 78.3%) and this finding could be useful for surgical planning once confirmed in a prospective study comparing the risk score stratification and clinical outcomes.
Do I Need to Operate on That in the Middle of the Night? Development of a Nomogram for the Diagnosis of Severe Acute Cholecystitis
Valpiani, Giorgia;Andreotti, Dario;Stano, Rocco;Carcoforo, PaoloPenultimo
;Occhionorelli, SavinoUltimo
2018
Abstract
Background Some authors have proposed different predictive factors of severe acute cholecystitis, but generally, the results of risk analyses are expressed as odds ratios, which makes it difficult to apply in the clinical practice of the acute care surgeon. The severe form of acute cholecystitis should include both gangrenous and phlegmonous cholecystitis, due to their severe clinical course, and cholecystectomy should not be delayed. The aim of this study was to create a nomogram to obtain a graphical tool to compute the probability of having a severe acute cholecystitis. Methods This is a retrospective study on 393 patients who underwent emergency cholecystectomy between January 2010 and December 2015 at the Acute Care Surgery Service of the S. Anna University Hospital of Ferrara, Italy. Patients were classified as having a non-severe acute cholecystitis or a severe acute cholecystitis (i.e., gangrenous and phlegmonous) based on the final pathology report. The baseline characteristics, pre-operative signs, and abdominal ultrasound (US) findings were assessed with a stepwise multivariate logistic regression analysis to predict the risk of severe acute cholecystitis, and a nomogram was created. Results Age as a continuous variable, WBC count ≥ 12.4 × 103/μl, CRP ≥9.9 mg/dl, and presence of US thickening of the gallbladder wall were significantly associated with severe acute cholecystitis at final pathology report. A significant interaction between the effect of age and CRP was found. Four risk classes were identified based on the nomogram total points. Conclusions Patients with a nomogram total point ≥ 74 should be considered at high risk of severe acute cholecystitis (at 74 total point, sensitivity = 78.5%; specificity = 78.2%; accuracy = 78.3%) and this finding could be useful for surgical planning once confirmed in a prospective study comparing the risk score stratification and clinical outcomes.File | Dimensione | Formato | |
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