Comparison of different risk stratification systems for prediction of acute pancreatitis severity in patients referred to the emergency department of a tertiary care hospital


BARDAKÇI O., AKDUR G., DAŞ M., SIDDIKOĞLU D., AKDUR O., BEYAZIT Y.

ULUSAL TRAVMA VE ACIL CERRAHI DERGISI-TURKISH JOURNAL OF TRAUMA & EMERGENCY SURGERY, cilt.28, sa.7, ss.967-973, 2022 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 28 Sayı: 7
  • Basım Tarihi: 2022
  • Doi Numarası: 10.14744/tjtes.2021.51892
  • Dergi Adı: ULUSAL TRAVMA VE ACIL CERRAHI DERGISI-TURKISH JOURNAL OF TRAUMA & EMERGENCY SURGERY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CINAHL, EMBASE, MEDLINE
  • Sayfa Sayıları: ss.967-973
  • Anahtar Kelimeler: Acute pancreatitis, acute physiology and chronic health evaluation II, bedside index for severity acute pancreatitis, Modified Glasgow prognostic score, Ranson, SCORING SYSTEMS, BISAP SCORE
  • Çanakkale Onsekiz Mart Üniversitesi Adresli: Evet

Özet

BACKGROUND: Prognostic prediction and estimation of severity at early stages of acute pancreatitis (AP) are crucial to reduce the complication rates and mortality. The objective of the present study is to evaluate the predicting ability of different clinical and radiological scores in AP. METHODS: We retrospectively collected demographic and clinical data from 159 patients diagnosed with AP admitted to Canakkale Onsekiz Mart University Hospital between January 2017 and December 2019. Bedside index for severity AP (BISAP), and acute phys-iology and chronic health evaluation II (APACHE II) score at admission, Ranson and modified Glasgow Prognostic Score (mGPS) score at 48 h after admission were calculated. Modified computed tomography severity index (CTSI) was also calculated for each patient. Area under the curve (AUC) was calculated for each scoring system for predicting severe AP, pancreatic necrosis, length of hospital stay, and mortality by determining optimal cutoff points from the (ROC) curves. RESULTS: mGPS and APACHE II had the highest AUC (0.929 and 0.823, respectively) to predict severe AP on admission with the best specificity and sensitivity. In predicting mortality BISAP (with a sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) of 75.0%, 70.9%, 98.2%, and 12.0%, respectively, [AUC: 0.793]) and APACHE II (with a sensitivity, specificity, NPV and PPV of 87.5%, 86.1%, 99.2%, and 25.0%, respectively, [AUC: 0.840]). CONCLUSION: mGPS can be a valuable tool in predicting the patients more likely to develop severe AP and maybe somewhat better than BISAP score, APACHE II Ranson score, and mCTSI.