Senapati Debadutta, Debata Prasanna Kumar, Jenasamant Saumya Sekhar, Nayak Anil Kumar, Gowda S Manoj, Swain Narendra Nath
Department of General Surgery, SCB Medical College, Cuttack, Odisha, 753007, India.
Department of General Surgery, SCB Medical College, Cuttack, Odisha, 753007, India.
Pancreatology. 2014 Sep-Oct;14(5):335-9. doi: 10.1016/j.pan.2014.07.007. Epub 2014 Jul 22.
A simple and easily applicable system for stratifying patients with acute pancreatitis is lacking. The aim of our study was to evaluate the ability of BISAP score to predict mortality in acute pancreatitis patients from our institution and to predict which patients are at risk for development of organ failure, persistent organ failure and pancreatic necrosis.
All patients with acute pancreatitis were included in the study. BISAP score was calculated within 24 h of admission. A Contrast CT was used to differentiate interstitial from necrotizing pancreatitis within seven days of hospitalization whereas Marshall Scoring System was used to characterize organ failure.
Among 246 patients M:F = 153:93, most common aetiology among men was alcoholism and among women was gallstone disease. 207 patients had no organ failure and remaining 39 developed organ failure. 17 patients had persistent organ failure, 16 of those with BISAP score ≥3. 13 patients in our study died, out of which 12 patients had BISAP score ≥3. We also found that a BISAP score of ≥3 had a sensitivity of 92%, specificity of 76%, a positive predictive value of 17%, and a negative predictive value of 99% for mortality.
The BISAP score is a simple and accurate method for the early identification of patients at increased risk for in hospital mortality and morbidity.
目前缺乏一种简单且易于应用的急性胰腺炎患者分层系统。我们研究的目的是评估BISAP评分预测我院急性胰腺炎患者死亡率的能力，以及预测哪些患者有发生器官衰竭、持续性器官衰竭和胰腺坏死的风险。
所有急性胰腺炎患者均纳入本研究。入院24小时内计算BISAP评分。住院7天内使用对比增强CT区分间质性胰腺炎和坏死性胰腺炎，而使用马歇尔评分系统对器官衰竭进行评估。
246例患者中，男:女 = 153:93，男性最常见的病因是酗酒，女性是胆结石疾病。207例患者无器官衰竭，其余39例发生器官衰竭。17例患者出现持续性器官衰竭，其中16例BISAP评分≥3。本研究中有13例患者死亡，其中12例BISAP评分≥3。我们还发现，BISAP评分≥3对死亡率的敏感性为92%，特异性为76%，阳性预测值为17%，阴性预测值为99%。
BISAP评分是一种简单而准确的方法，可早期识别住院死亡率和发病率风险增加的患者。
