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Predicting persistent organ failure on admission in patients with acute pancreatitis: development and validation of a mobile nomogram

  • Author Footnotes
    ∗ These authors contributed equally to this work.
    Na Shi
    Footnotes
    ∗ These authors contributed equally to this work.
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Author Footnotes
    ∗ These authors contributed equally to this work.
    Xiaoxin Zhang
    Footnotes
    ∗ These authors contributed equally to this work.
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Yin Zhu
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Lihui Deng
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Lan Li
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Ping Zhu
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Liang Xia
    Affiliations
    Department of Gastroenterology, First Affiliated Hospital of Nanchang University, Nanchang, China
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  • Tao Jin
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Thomas Ward
    Affiliations
    Liverpool Pancreatitis Research Group, Liverpool University Hospitals NHS Foundation Trust and Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
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  • Peter Sztamary
    Affiliations
    Liverpool Pancreatitis Research Group, Liverpool University Hospitals NHS Foundation Trust and Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
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  • Wenhao Cai
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China

    Liverpool Pancreatitis Research Group, Liverpool University Hospitals NHS Foundation Trust and Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
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  • Linbo Yao
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Xinmin Yang
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Ziqi Lin
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Kun Jiang
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Jia Guo
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Xiaonan Yang
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Vikesh K. Singh
    Affiliations
    Pancreatitis Center, Division of Gastroenterology, Johns Hopkins Medical Institutions, Baltimore, USA
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  • Robert Sutton
    Affiliations
    Liverpool Pancreatitis Research Group, Liverpool University Hospitals NHS Foundation Trust and Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
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  • Nonghua Lu
    Affiliations
    Department of Gastroenterology, First Affiliated Hospital of Nanchang University, Nanchang, China
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  • John A. Windsor
    Affiliations
    Surgical and Translational Research Centre, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
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  • Wenhua He
    Correspondence
    Correspondence: Wenhua He, Pancreatic Disease Centre, Department of Gastroenterology, First Affiliated Hospital of Nanchang University, 17 Yong wai zheng Street, Nanchang, Jiangxi Province, 330006, China.
    Affiliations
    Department of Gastroenterology, First Affiliated Hospital of Nanchang University, Nanchang, China
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  • Wei Huang
    Correspondence
    Correspondence: Wei Huang, Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Centre, West China Hospital, Sichuan University, No. 37 Wannan Guoxue Alley, Chengdu 610041, Sichuan Province 610041, China.
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Qing Xia
    Correspondence
    Correspondence: Qing Xia, Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Centre, West China Hospital, Sichuan University, No. 37 Wannan Guoxue Alley, Chengdu 610041, Sichuan Province 610041, China.
    Affiliations
    Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China
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  • Author Footnotes
    ∗ These authors contributed equally to this work.
Open AccessPublished:June 05, 2022DOI:https://doi.org/10.1016/j.hpb.2022.05.1347

      Abstract

      Background

      Early prediction of persistent organ failure (POF) is important for triage and timely treatment of patients with acute pancreatitis (AP).

      Methods

      All AP patients were consecutively admitted within 48 h of symptom onset. A nomogram was developed to predict POF on admission using data from a retrospective training cohort, validated by two prospective cohorts. The clinical utility of the nomogram was defined by concordance index (C-index), decision curve analysis (DCA), and clinical impact curve (CIC), while the performance by post-test probability.

      Results

      There were 816, 398, and 880 patients in the training, internal and external validation cohorts, respectively. Six independent predictors determined by logistic regression analysis were age, respiratory rate, albumin, lactate dehydrogenase, oxygen support, and pleural effusion and were included in the nomogram (web-based calculator: https://shina.shinyapps.io/DynNomapp/). This nomogram had reasonable predictive ability (C-indexes 0.88/0.91/0.81 for each cohort) and promising clinical utility (DCA and CIC). The nomogram had a positive likelihood ratio and post-test probability of developing POF in the training, internal and external validation cohorts of 4.26/31.7%, 7.89/39.1%, and 2.75/41%, respectively, superior or equal to other prognostic scores.

      Conclusions

      This nomogram can predict POF of AP patients and should be considered for clinical practice and trial allocation.

      Introduction

      Acute pancreatitis (AP) has a spectrum of severity ranging from mild to critical.
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      The early prediction of the severity of AP informs clinical decisions about triage, transfer, and intervention.
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      Early prediction is also important in the research setting, where the accurate allocation of patients into trial arms based on predicted severity is important for testing treatments for AP. The key determinants of AP severity are organ failure and infected pancreatic necrosis.
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      Organ failure and infection of pancreatic necrosis as determinants of mortality in patients with acute pancreatitis.
      Persistent organ failure (POF) is the most important determinant for mortality,
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      Duration of organ failure impacts mortality in acute pancreatitis.
      the leading cause of death from AP
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      and is the basis for the severe grade of AP in the revised Atlanta classification (RAC)
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      Classification of acute pancreatitis--2012: revision of the Atlanta classification and definitions by international consensus.
      ).
      Given the importance of predicting severity and since Ranson defined his score in 1974,
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      Prognostic signs and the role of operative management in acute pancreatitis.
      there have been more than 20 prognostic scores have been studied for AP severity prediction.
      • Di M.Y.
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      • Tang J.L.
      • Lau J.
      Prediction models of mortality in acute pancreatitis in adults: a systematic review.
      However, their clinical utility is limited by an accuracy of predicting POF of around 75% and many are cumbersome to use.
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      Comparison of existing clinical scoring systems to predict persistent organ failure in patients with acute pancreatitis.
      Recent systematic reviews and meta-analyses conclude that current early predictors of POF,
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      • Petrov M.S.
      Predictors of severe and critical acute pancreatitis: a systematic review.
      infected pancreatic necrosis,
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      • Chen J.
      • Phillips A.R.
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      Predictors of severe and critical acute pancreatitis: a systematic review.
      and mortality
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      • Tang J.L.
      • Lau J.
      Prediction models of mortality in acute pancreatitis in adults: a systematic review.
      are not sufficiently accurate for decision making in individual patients. The ideal predictor of POF would be applied on patient admission and within 24 h of the onset of symptoms. It would be cost-effective, easy to use and have an accuracy between 95 and 100%. Considerable progress has been made in identifying serum biomarkers to stratify early risk and severity in patients with AP.
      • van den Berg F.F.
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      Early laboratory biomarkers for severity in acute pancreatitis; A systematic review and meta-analysis.
      However, due to their rapid time-course changes in serum concentration, non-specificity, cost, complexity, and suboptimal accuracy, none of these biochemical biomarkers have been adopted into routine clinical practice. In recent years, different nomograms have been applied for predicting severity and mortality,
      • Jiang X.
      • Su Z.
      • Wang Y.
      • Deng Y.
      • Zhao W.
      • Jiang K.
      • et al.
      Prognostic nomogram for acute pancreatitis patients: an analysis of publicly electronic healthcare records in intensive care unit.
      • Li C.
      • Ren Q.
      • Wang Z.
      • Wang G.
      Early prediction of in-hospital mortality in acute pancreatitis: a retrospective observational cohort study based on a large multicentre critical care database.
      • Xu X.
      • Ai F.
      • Huang M.
      Deceased serum bilirubin and albumin levels in the assessment of severity and mortality in patients with acute pancreatitis.
      • Cao X.
      • Wang H.M.
      • Lu R.
      • Zhang X.H.
      • Qu Y.L.
      • Wang L.
      • et al.
      Establishment and verification of a nomogram for predicting severe acute pancreatitis.
      splanchnic vein thrombosis,
      • Zhou J.
      • Ke L.
      • Yang D.
      • Chen Y.
      • Li G.
      • Tong Z.
      • et al.
      Predicting the clinical manifestations in necrotizing acute pancreatitis patients with splanchnic vein thrombosis.
      abdominal infection,
      • Zhu C.
      • Zhang S.
      • Zhong H.
      • Gu Z.
      • Kang Y.
      • Pan C.
      • et al.
      Intra-abdominal infection in acute pancreatitis in eastern China: microbiological features and a prediction model.
      oral refeeding intolerance,
      • Bevan M.G.
      • Asrani V.M.
      • Pendharkar S.A.
      • Goodger R.L.
      • Windsor J.A.
      • Petrov M.S.
      Nomogram for predicting oral feeding intolerance in patients with acute pancreatitis.
      success of catheter drainage in necrotizing AP,
      • Hollemans R.A.
      • Bollen T.L.
      • van Brunschot S.
      • Bakker O.J.
      • Ahmed Ali U.
      • van Goor H.
      • et al.
      Predicting success of catheter drainage in infected necrotizing pancreatitis.
      ,
      • Bellam B.L.
      • Samanta J.
      • Gupta P.
      • Kumar M.P.
      • Sharma V.
      • Dhaka N.
      • et al.
      Predictors of outcome of percutaneous catheter drainage in patients with acute pancreatitis having acute fluid collection and development of a predictive model.
      and risk of new-onset diabetes after AP,
      • Ma J.H.
      • Yuan Y.J.
      • Lin S.H.
      • Pan J.Y.
      Nomogram for predicting diabetes mellitus after the first attack of acute pancreatitis.
      as well as computed tomography index for assessing AP outcomes
      • Gupta P.
      • Kumar M.P.
      • Verma M.
      • Sharma V.
      • Samanta J.
      • Mandavdhare H.
      • et al.
      Development and validation of a computed tomography index for assessing outcomes in patients with acute pancreatitis: "SMART-CT" index.
      (Table 1). Of 4 studies
      • Jiang X.
      • Su Z.
      • Wang Y.
      • Deng Y.
      • Zhao W.
      • Jiang K.
      • et al.
      Prognostic nomogram for acute pancreatitis patients: an analysis of publicly electronic healthcare records in intensive care unit.
      • Li C.
      • Ren Q.
      • Wang Z.
      • Wang G.
      Early prediction of in-hospital mortality in acute pancreatitis: a retrospective observational cohort study based on a large multicentre critical care database.
      • Xu X.
      • Ai F.
      • Huang M.
      Deceased serum bilirubin and albumin levels in the assessment of severity and mortality in patients with acute pancreatitis.
      • Cao X.
      • Wang H.M.
      • Lu R.
      • Zhang X.H.
      • Qu Y.L.
      • Wang L.
      • et al.
      Establishment and verification of a nomogram for predicting severe acute pancreatitis.
      that used a nomogram to predict severity and mortality, 3 studies used online Critical Care Database (Medical Information Mart for Intensive Care III database [MIMIC-III],
      • Jiang X.
      • Su Z.
      • Wang Y.
      • Deng Y.
      • Zhao W.
      • Jiang K.
      • et al.
      Prognostic nomogram for acute pancreatitis patients: an analysis of publicly electronic healthcare records in intensive care unit.
      ,
      • Xu X.
      • Ai F.
      • Huang M.
      Deceased serum bilirubin and albumin levels in the assessment of severity and mortality in patients with acute pancreatitis.
      eICU Collaborative Research Database [eICU-CRD]
      • Li C.
      • Ren Q.
      • Wang Z.
      • Wang G.
      Early prediction of in-hospital mortality in acute pancreatitis: a retrospective observational cohort study based on a large multicentre critical care database.
      ) and the fourth used retrospective data.
      • Cao X.
      • Wang H.M.
      • Lu R.
      • Zhang X.H.
      • Qu Y.L.
      • Wang L.
      • et al.
      Establishment and verification of a nomogram for predicting severe acute pancreatitis.
      None of the 4 studies reported the duration of symptoms prior to hospital admission. No study to date has used training and validation cohorts to develop a nomogram to predict POF in AP patients.
      Table 1Summarize of the present developed nomograms in AP
      Nomograms for predicting SAP or mortality
      Predicted outcomeStudy designSymptom onset timeData collection timeIndicators of the NomogramTraining cohortValidation cohortMain findings
      NC-indexNC-index
      Jiang et al. 2019 [
      • Jiang X.
      • Su Z.
      • Wang Y.
      • Deng Y.
      • Zhao W.
      • Jiang K.
      • et al.
      Prognostic nomogram for acute pancreatitis patients: an analysis of publicly electronic healthcare records in intensive care unit.
      ]
      Mortality30-dayMIMIC-IIINAWithin 24 hWithin 24 hage, ALT, RDW, BUN2280.7511140.875Nomogram > BISAP > SOFA > SIRS for long-term mortality both in cohorts.
      180-day/ 1-yearage, WBC, RDW, SCR0.7580.856
      Li et al. 2020 [
      • Li C.
      • Ren Q.
      • Wang Z.
      • Wang G.
      Early prediction of in-hospital mortality in acute pancreatitis: a retrospective observational cohort study based on a large multicentre critical care database.
      ]
      In-hospital mortalityeICU-CRDNAWithin 24 hage, BUN and lactate3780.8961230.892The nomogram and APACHE IV demonstrated comparable power in predicting in-hospital mortality.
      Xu et al. 2020 [
      • Xu X.
      • Ai F.
      • Huang M.
      Deceased serum bilirubin and albumin levels in the assessment of severity and mortality in patients with acute pancreatitis.
      ]
      SAPMIMIC-IIINAOn admissionOn admissionSOFA, hemoglobin, albumin, TBIL, BUN7080.8554770.879Nomogram > SOFA / OASIS for SAP and mortality in both cohorts.
      In-hospital mortalityAge, SOFA, WBC, TBIL, albumin0.8210.822
      Cao et al. 2021 [
      • Cao X.
      • Wang H.M.
      • Lu R.
      • Zhang X.H.
      • Qu Y.L.
      • Wang L.
      • et al.
      Establishment and verification of a nomogram for predicting severe acute pancreatitis.
      ]
      SAPRetrospectiveNAWithin 24 hSex, Ca2+, SCR, NE%, LYMPH%, EO%5710.691500.71No comparison with others.
      Other nomograms in AP
      Predicted outcomeStatistical methodsIndicators of the NomogramTraining cohortValidation cohort
      NC-indexNC-index
      Hollemans et al. 2016 [
      • Hollemans R.A.
      • Bollen T.L.
      • van Brunschot S.
      • Bakker O.J.
      • Ahmed Ali U.
      • van Goor H.
      • et al.
      Predicting success of catheter drainage in infected necrotizing pancreatitis.
      ]
      Success of catheter drainage in infected necrotizing pancreatitisUnivariate and multivariate logistic regressionSex, percentage of pancreatic necrosis, density collection, multiple organ failure1300.76NANA
      Zhou et al. 2016 [
      • Zhou J.
      • Ke L.
      • Yang D.
      • Chen Y.
      • Li G.
      • Tong Z.
      • et al.
      Predicting the clinical manifestations in necrotizing acute pancreatitis patients with splanchnic vein thrombosis.
      ]
      Symptomatic splanchnic vein thrombosis in necrotizing acute pancreatitisUnivariate and multivariate logistic regressionBalthazar's CT score, intra-abdominal pressure and superior mesenteric vein thrombosis1040.842NANA
      Bevan et al. 2017 [
      • Bevan M.G.
      • Asrani V.M.
      • Pendharkar S.A.
      • Goodger R.L.
      • Windsor J.A.
      • Petrov M.S.
      Nomogram for predicting oral feeding intolerance in patients with acute pancreatitis.
      ]
      Oral feeding intoleranceUnivariate and multivariate logistic regressionDay 2 GCSI nausea/vomiting subs-core, etiology217NANANA
      Ma et al. 2019 [
      • Ma J.H.
      • Yuan Y.J.
      • Lin S.H.
      • Pan J.Y.
      Nomogram for predicting diabetes mellitus after the first attack of acute pancreatitis.
      ]
      New-onset diabetes mellitus after the first attack of acute pancreatitisUnivariate and multivariate logistic regressionAge, BMI, glucose, triglyceride, and LDL-C6160.686NANA
      Bellam et al. 2019 [
      • Bellam B.L.
      • Samanta J.
      • Gupta P.
      • Kumar M.P.
      • Sharma V.
      • Dhaka N.
      • et al.
      Predictors of outcome of percutaneous catheter drainage in patients with acute pancreatitis having acute fluid collection and development of a predictive model.
      ]
      Success of percutaneous catheter drainage in patients with acute pancreatitis having acute fluid collectionUnivariate and multivariate logistic regressionvolume of collection after PCD and organ failure resolution after PCD510.915NANA
      Gupta et al. 2021 [
      • Gupta P.
      • Kumar M.P.
      • Verma M.
      • Sharma V.
      • Samanta J.
      • Mandavdhare H.
      • et al.
      Development and validation of a computed tomography index for assessing outcomes in patients with acute pancreatitis: "SMART-CT" index.
      ]
      MortalityBinomial logistic regressionPancreatic necrosis, ascites, pleural effusion1030.79200.74
      ICU stayNumber of collection, pleural effusion0.660.70
      hospital stay≥4 weeksPancreatic necrosis, number of collection, amount PE0.750.77
      ReadmissionNumber of collection, coeliac artery0.700.52
      ICU stay≥2 weeksPancreatic necrosis, largest dimension of collection, pleural effusion0.830.45
      SAPNumber of collection, liver steatosis0.640.69
      Zhu et al. 2021 [
      • Zhu C.
      • Zhang S.
      • Zhong H.
      • Gu Z.
      • Kang Y.
      • Pan C.
      • et al.
      Intra-abdominal infection in acute pancreatitis in eastern China: microbiological features and a prediction model.
      ]
      Intra-abdominal infectionLASSO regressionIntra-abdominal pressure, APACHE II score, CTSI, ICU admission, and severity grade4170.992940.98
      SAP, severe acute pancreatitis; MIMIC-III, Medical Information Mart for Intensive Care III; NA, not available; ALT, alanine aminotransferase; RDW, red cell distribution width; BUN, blood urea nitrogen; WBC, white blood cell count; SCR, serum creatinine; BISAP, Bedside Index of Severity in Acute Pancreatitis; SOFA, Sequential Organ Failure Assessment; SIRS, Systemic Inflammatory Response Syndrome; ICU, intensive care unit; eICU-CRD, eICU Collaborative Research Database; APACHE, Acute Physiology, Age, and Chronic Health Evaluation; TBIL, total bilirubin; OASIS, Outcome and Assessment Information Set; NE%, neutrophil ratio; LYMPH%, lymphocyte Ratio; eosinophil ratio, EO%; GCSI, Gastroparesis Cardinal Symptom Index; LDL-C, low density lipoprotein-cholesterol; PCD, percutaneous catheter drainage; CTSI, computed tomography severity index.
      The aim of this study was (1) to develop and validate a nomogram for predicting POF on admission in patients with AP, and (2) to compare the performance of the nomogram with conventional prognostic scores for predicting POF.

      Methods

      Study design and ethics

      This study followed the STROBE guidelines
      • von Elm E.
      • Altman D.G.
      • Egger M.
      • Pocock S.J.
      • Gotzsche P.C.
      • Vandenbroucke J.P.
      • et al.
      Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.
      for observational studies. The study protocol was approved by respective Institutional Review Board in two tertiary hospitals. Data were obtained from two AP cohorts in West China Hospital of Sichuan University (WCH/SCU; Chengdu). The training cohort was from a retrospective dataset from 1st July 2009 to 30th June 2013.
      • Shi N.
      • Liu T.
      • de la Iglesia-Garcia D.
      • Deng L.
      • Jin T.
      • Lan L.
      • et al.
      Duration of organ failure impacts mortality in acute pancreatitis.
      The internal validation cohort was from a prospective dataset from 1st January 2016 and 31st August 2017.
      • Li L.
      • Jin T.
      • Wen S.
      • Shi N.
      • Zhang R.
      • Zhu P.
      • et al.
      Early rapid fluid therapy is associated with increased rate of noninvasive positive-pressure ventilation in hemoconcentrated patients with severe acute pancreatitis.
      The external validation cohort was from a prospective dataset from The First Affiliated Hospital of Nanchang University (Nanchang) from 1st January 2005 to 31st December 2012.
      • Zhu Y.
      • Pan X.
      • Zeng H.
      • He W.
      • Xia L.
      • Liu P.
      • et al.
      A study on the etiology, severity, and mortality of 3260 patients with acute pancreatitis according to the revised Atlanta classification in jiangxi, China over an 8-year period.

      Inclusion and exclusion criteria

      The inclusion criteria were (1) diagnosis of AP diagnosed by the RAC criteria,
      • Banks P.A.
      • Bollen T.L.
      • Dervenis C.
      • Gooszen H.G.
      • Johnson C.D.
      • Sarr M.G.
      • et al.
      Classification of acute pancreatitis--2012: revision of the Atlanta classification and definitions by international consensus.
      (2) age >18 and ≤80 years old, and (3) duration of abdominal pain from onset to admission ≤48 h, (4) data to calculate conventional prognostic scores within 6 h of admission.
      The exclusion criteria were (1) patients admitted to another hospital first and then transferred, (2) patients re-admitted during the same episode of AP, (3) patients with an etiology related to chronic pancreatitis, pancreatic neoplasia, pancreatic trauma, or pregnancy, (4) advanced pulmonary, cardiac, renal diseases (chronic kidney disease stage 4–5), liver cirrhosis (modified Child–Pugh grade 2–3) or malignancy, and (5) if the nomogram could not be completed because of missing data.

      Definitions, variables, and outcome measures

      Data collection: Experienced doctoral students and resident doctors specializing in management of AP were stringently trained for data collection according to pre-defined proforma and standard operating procedures in both centers. Each proforma was checked and signed off by attending or more senior doctors. The data collected on admission included age, gender, data for Charlson co-morbidity index, and duration of abdominal pain prior to admission. Vital signs, laboratory parameters (indices of routine blood, liver and renal function, myocardial enzymes, blood lipids and glucose, electrolyte levels and etc.), details of treatment (especially use of oxygen support, vasopressors, dialysis, antibiotic, and steroids), surgical interventions, and clinical outcomes were also recorded.
      Presence of pleural effusion that were mostly obtained from nonenhanced computed tomography scan on admission. Patients without overt symptoms of pleural effusion (dyspnea, cough, and occasionally sharp, non-radiating, pleuritic chest pain) were not referred to having X-ray or CT scan in up to 10% of overall patients and these patients were considered as pleural effusion free.

      Etiology

      Hypertriglyceridemia as the etiology was defined as admission serum triglyceride (TG) level >11.3 mmol/l (1000 mg/dl) or TG > 5.65 mmol/l (500 mg/dl) with lipemic serum when other causes have been ruled out.
      • Nawaz H.
      • Koutroumpakis E.
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      • et al.
      Elevated serum triglycerides are independently associated with persistent organ failure in acute pancreatitis.
      • Carr R.A.
      • Rejowski B.J.
      • Cote G.A.
      • Pitt H.A.
      • Zyromski N.J.
      Systematic review of hypertriglyceridemia-induced acute pancreatitis: a more virulent etiology?.
      • Vipperla K.
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      • Koutroumpakis E.
      • Saul M.
      • Chennat J.
      • et al.
      Clinical profile and natural course in a large cohort of patients with hypertriglyceridemia and pancreatitis.
      Biliary etiology was considered if gallstones or biliary sludge was present on radiological imaging or had an admission alanine aminotransferase level of over three times the upper limit of normal.
      • van Geenen E.J.
      • van der Peet D.L.
      • Bhagirath P.
      • Mulder C.J.
      • Bruno M.J.
      Etiology and diagnosis of acute biliary pancreatitis.
      Alcohol excess was diagnosed if with drinking history >35 standard drinks per week for >5 years
      • Easler J.J.
      • de-Madaria E.
      • Nawaz H.
      • Moya-Hoyo N.
      • Koutroumpakis E.
      • Rey-Riveiro M.
      • et al.
      Patients with sentinel acute pancreatitis of alcoholic etiology are at risk for organ failure and pancreatic necrosis: a dual-center experience.
      or was deduced according to our center's own practice according to the drinking history after ruling out other etiologies.
      • Shi N.
      • Liu T.
      • de la Iglesia-Garcia D.
      • Deng L.
      • Jin T.
      • Lan L.
      • et al.
      Duration of organ failure impacts mortality in acute pancreatitis.

      Organ failure, complications, and mortality

      POF was defined as at least one organ systems (respiratory, circulatory, and renal) with a SOFA score of ≥2 and lasting ≥48 h.
      • Dellinger E.P.
      • Forsmark C.E.
      • Layer P.
      • Lévy P.
      • Maraví-Poma E.
      • Petrov M.S.
      • et al.
      Determinant-based classification of acute pancreatitis severity: an international multidisciplinary consultation.
      Acute necrotic collection and acute peripancreatic fluid collection were defined as per RAC criteria.
      • Banks P.A.
      • Bollen T.L.
      • Dervenis C.
      • Gooszen H.G.
      • Johnson C.D.
      • Sarr M.G.
      • et al.
      Classification of acute pancreatitis--2012: revision of the Atlanta classification and definitions by international consensus.
      Major infection included infected pancreatic necrosis, bacteremia, or pneumonia alone or in combination.
      • Bakker O.J.
      • van Brunschot S.
      • van Santvoort H.C.
      • Besselink M.G.
      • Bollen T.L.
      • Boermeester M.A.
      • et al.
      Early versus on-demand nasoenteric tube feeding in acute pancreatitis.
      Mortality was recorded during the index admission or at 3 months of follow up for those who were automatically discharged with persistent multiple organ failure and had high possibility of death. Length of hospital stay were recorded for the index hospitalization.

      Prognostic scores

      The prognostic scores that were compared with the nomogram in this study were National Early Warning Score (NEWS),
      National Early Warning Score(NEWS)
      Standardising the assessment of acute- illness severity in the NHS. Report of a working party.
      Systemic Inflammatory Response Syndrome (SIRS),
      • Mounzer R.
      • Langmead C.J.
      • Wu B.U.
      • Evans A.C.
      • Bishehsari F.
      • Muddana V.
      • et al.
      Comparison of existing clinical scoring systems to predict persistent organ failure in patients with acute pancreatitis.
      Bedside Index for Severity in Acute Pancreatitis (BISAP),
      • Mounzer R.
      • Langmead C.J.
      • Wu B.U.
      • Evans A.C.
      • Bishehsari F.
      • Muddana V.
      • et al.
      Comparison of existing clinical scoring systems to predict persistent organ failure in patients with acute pancreatitis.
      modified Glasgow criteria,
      • Mounzer R.
      • Langmead C.J.
      • Wu B.U.
      • Evans A.C.
      • Bishehsari F.
      • Muddana V.
      • et al.
      Comparison of existing clinical scoring systems to predict persistent organ failure in patients with acute pancreatitis.
      Acute Physiology and Chronic Health Examination (APACHE) II,
      • Mounzer R.
      • Langmead C.J.
      • Wu B.U.
      • Evans A.C.
      • Bishehsari F.
      • Muddana V.
      • et al.
      Comparison of existing clinical scoring systems to predict persistent organ failure in patients with acute pancreatitis.
      and Sequential Organ Failure Assessment (SOFA).
      • Mounzer R.
      • Langmead C.J.
      • Wu B.U.
      • Evans A.C.
      • Bishehsari F.
      • Muddana V.
      • et al.
      Comparison of existing clinical scoring systems to predict persistent organ failure in patients with acute pancreatitis.
      These were all calculated on admission (or within 6 h of admission in rare cases).

      Statistical analysis

      Continuous variables were expressed as median with 25th-75th percentile and were compared by Mann–Whitney U test (2 groups) or Kruskal–Wallis H test (3 groups). Categorical data were reported as number with percentage and were compared by means of χ2 or Fisher's exact test.
      Independent risk factors for POF were identified and assessed significance of each by univariate logistic regression analysis in the training cohort. All variables significantly associated with POF were candidates for stepwise multivariate analysis, the results of which were used to formulate a nomogram. The predictive performance of the nomogram was measured by concordance index (C-index) and calibration with 1000 bootstrap samples to decrease the overfit bias.
      • Steyerberg E.W.
      • Vergouwe Y.
      Towards better clinical prediction models: seven steps for development and an ABCD for validation.
      The clinical utility of the nomogram was assessed by decision curve analysis (DCA) and clinical impact curve (CIC).
      • Kerr K.F.
      • Brown M.D.
      • Zhu K.
      • Janes H.
      Assessing the clinical impact of risk prediction models with decision curves: guidance for correct interpretation and appropriate use.
      DCA is a simple, novel method of evaluating predictive models with decision analyses of diagnostic and prognostic tests by using a risk-benefit ratio.
      • Vickers A.J.
      • Elkin E.B.
      Decision curve analysis: a novel method for evaluating prediction models.
      CIC shows the estimated number considered at high risk for each risk threshold and depicts the proportion of those that are true positives.
      • Kerr K.F.
      • Brown M.D.
      • Zhu K.
      • Janes H.
      Assessing the clinical impact of risk prediction models with decision curves: guidance for correct interpretation and appropriate use.
      The area under curve (AUC) of the receiver operating characteristic (ROC) curves with 95% confidence intervals (CI) was calculated for potential predictors. An AUC of 0.5–0.7 was taken to represent no significant discrimination, 0.7 to 0.8 acceptable, 0.8 to 0.9 excellent, and >0.9 outstanding.
      • Mandrekar J.N.
      Receiver operating characteristic curve in diagnostic test assessment.
      The AUC of two predictors were compared by method of DeLong.
      • DeLong E.R.
      • DeLong D.M.
      • Clarke-Pearson D.L.
      Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.
      The optimum cut-off for each predictor was determined by the ROC curve. The sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated by clinical decision analysis. A positive likelihood ratio is the probability that a positive test would be expected in a patient divided by the probability that a positive test would be expected in a patient without the endpoint of interest (e.g. POF). A negative likelihood ratio is the converse and if < 0.1 effectively rules out the endpoint. The post-test probabilities for each predictor were derived from the PLR (and NLR), using the pre-test probability of the particular endpoint from the relevant cohort and the standard likelihood ratio nomogram.
      • Grimes D.A.
      • Schulz K.F.
      Refining clinical diagnosis with likelihood ratios.
      The analyses were performed using IBM SPSS Statistics V26.0 software (SPSS, IBM Corp; Armonk, New York, USA) and R software version 4.0.4 (http://www.Rproject.org). Two-tailed P value with statistical significance set at < 0.05 was used for all tests.

      Results

      Patient characteristics

      There were 816, 398, and 880 eligible patients in the training, internal validation and external validation cohorts, respectively. The demographic and clinical outcome profiles are outlined in Table 2 and Online Supplementary Tables S1a–c. These results are similar to previous published studies.
      • Shi N.
      • Liu T.
      • de la Iglesia-Garcia D.
      • Deng L.
      • Jin T.
      • Lan L.
      • et al.
      Duration of organ failure impacts mortality in acute pancreatitis.
      ,
      • Li L.
      • Jin T.
      • Wen S.
      • Shi N.
      • Zhang R.
      • Zhu P.
      • et al.
      Early rapid fluid therapy is associated with increased rate of noninvasive positive-pressure ventilation in hemoconcentrated patients with severe acute pancreatitis.
      ,
      • Zhu Y.
      • Pan X.
      • Zeng H.
      • He W.
      • Xia L.
      • Liu P.
      • et al.
      A study on the etiology, severity, and mortality of 3260 patients with acute pancreatitis according to the revised Atlanta classification in jiangxi, China over an 8-year period.
      The median age was 45 years old and about 70% patients were male in both training and internal validation cohorts, while median age was 50 years old and 61% patients were male in the external validation cohorts. Hypertriglyceridemia (32.7% and 42%) was the most common etiology in the training and internal validation cohorts. Biliary (57.5%) was the most common etiology in the external validation cohort.
      Table 2Baseline characteristics and clinical outcomes in training and validation cohorts
      VariablesTraining cohortValidation cohorts
      n = 816(Internal) n = 398(External) n = 880
      Demographics
       Age, years∗45 (37–55)45 (38–51)50 (41–62)
       Male568 (69.6)273 (68.6)533 (60.6)
       Charlson comorbidity index∗1 (0–1)1 (0–2)0 (0–0)
       Etiology
      Biliary230 (28.2)78 (19.6)506 (57.5)
      Hypertriglyceridemia267 (32.7)167 (42.0)184 (20.9)
      Alcohol30 (3.7)31 (7.8)61 (6.9)
      Unknown or others289 (35.4)122 (30.7)129 (14.7)
       Time to admission, hours∗12 (7–24)15 (9–24)NA
      Clinical outcomes
       Persistent organ failure80 (9.8)30 (7.5)178 (20.2)
      Respiratory77 (9.4)30 (7.5)169 (19.2)
      Circulatory14 (1.7)2 (0.5)12 (1.4)
      Renal10 (1.2)3 (0.8)28 (3.2)
       Need for HDU/ICU59 (7.2)29 (7.3)168 (19.1)
       Local complication
       Acute peripancreatic fluid collection163 (20.0)119 (29.9)332 (37.7)
       Acute necrotic collection59 (7.2)55 (13.8)204 (23.2)
      Major infection45 (5.5)20 (5.0)53 (6.0)
       Infected pancreatic necrosis12 (1.5)9 (2.3)36 (4.1)
       Bacteremia15 (1.8)6 (1.5)13 (1.5)
       Lung35 (4.3)9 (2.3)18 (2.0)
      Necrosectomy14 (1.7)13 (3.3)17 (1.9)
      Mortality10 (1.2)4 (1.0)20 (2.3)
      RAC
       Mild508 (62.3)190 (47.7)328 (37.3)
       Moderately severe228 (27.9)178 (44.7)374 (42.5)
       Severe80 (9.8)30 (7.5)178 (20.2)
      Length of hospital stay (days)∗9 (6–13)8 (6–11)8 (6–13)
      NA, not available; HDU, high dependency unit; ICU, intensive care unit; RAC, revised Atlanta classification.
      Values in parentheses are percentages unless indicated otherwise ∗values are median with 25th-75th percentile.

      Developing the prediction nomogram

      Candidate variables for the nomogram were drawn from demographic, vital signs, blood and biochemical tests, on admission. The independent prognostic factors for POF after univariate and multivariate logistic regression analysis were age (OR 1.03 [95% CI 1.01–0.05]; P = 0.01), respiratory rate (1.25 [1.10–1.42]; P = 0.001), albumin (0.92 [0.87–0.98]; P = 0.013), lactate dehydrogenase (LDH; 1.002 [1.000–1.003]; P = 0.036), oxygen support (5.17 [2.91–9.20]; P < 0.001), and pleural effusion (3.61 [1.97–6.61]; P < 0.001) (Table 3). These variables were then used to construct the predictive nomogram (Fig. 1a). The total score was calculated as: ([age × 0·3224] – 4.8358]) + ([respiratory rate × 2.5] – 25]) + (43.518 – [0·7912 × albumin]) + (LDH × 0.0196) + 15.521 (if oxygen support) + 12.551 (if exist of pleural effusion). To facilitate the clinical application of our findings, we developed a mobile terminal-based calculator (https://shina.shinyapps.io/DynNomapp/) of the predictive nomogram (Fig. 1b and c).
      Table 3Univariate and multivariate logistic regression analysis with stepwise variable selection
      VariablesUnivariate analysisMultivariate analysis
      OR (95% CI)P valueOR (95% CI)P value
      Demographics
       Age, years1.036 (1.019–1.053)<0.0011.030 (1.007–1.053)0.01
       Gender1.263 (0.777–2.053)0.346
       Charlson comorbidity index0.96 (0.684–1.346)0.811
       Etiology0.861 (0.711–1.043)0.127
       Time to admission, hours1.005 (0.984–1.026)0.658
      Admission vital signs
       Body temperature1.377 (0.902–2.102)0.138
       Respiratory rate1.352 (1.207–1.514)<0.0011.249 (1.099–1.420)0.001
       Heart rate1.029 (1.016–1.042)<0.0011.006 (0.989–1.023)0.499
      Admission laboratory parameters
       Amylase, IU/l1.000 (1.000–1.001)0.0011.000 (1.000–1.000)0.448
       Lipase, IU/l1.000 (1.000–1.000)0.096
       White blood cell, 109/l1.112 (1.062–1.165)<0.0011.085 (0.854–1.379)0.505
       Neutrophils, 109/l1.115 (1.063–1.169)<0.0010.974 (0.755–1.257)0.839
       Lymphocytes, 109/l0.958 (0.709–1.293)0.777
       NLR1.007 (0.996–1.018)0.186
       Platelet, 109/l1.000 (0.997–1.003)0.868
       Hematocrits, I/l2.973 (0.023–377.4)0.659
       Hemoglobin, g/l1.011 (1.000–1.022)0.057
       ALT, IU/l1.001 (0.999–1.002)0.247
       AST, IU/l1.001 (1.000–1.002)0.125
       Albumin, g/l0.884 (0.844–0.925)<0.0010.924 (0.868–0.984)0.013
       Glucose, mmol/l1.063 (1.021–1.106)0.0031.003 (0.945–1.066)0.915
       Urea, mmol/l1.219 (1.124–1.321)<0.0011.105 (0.973–1.256)0.123
       Creatinine, μmol/l1.012 (1.005–1.018)<0.0011.001 (0.992–1.009)0.904
       Triglycerides, mmol/l1.017 (0.993–1.041)0.162
       Cholesterol, mmol/l1.041 (0.977–1.109)0.211
       Lactate dehydrogenase, IU/l1.003 (1.002–1.004)<0.0011.002 (1.000–1.003)0.036
       Calcium, mmol/l0.093 (0.033–0.263)<0.0010.719 (0.174–2.970)0.648
      Oxygen supporting5.722 (3.486–9.393)<0.0015.170 (2.905–9.202)<0.001
      Pleural effusion3.802 (2.318–6.237)<0.0013.611 (1.973–6.610)<0.001
      NLR, neutrophil to lymphocyte ratio; LDH, lactate dehydrogenase; ALT, alanine aminotransferase; AST, aspartate aminotransferase.
      Figure 1
      Figure 1Nomogram for predicting POF in patients with AP and dynamic web-based calculator. Patient prognostic values are located on the axis of each variable; a line is then drawn upwards at a 90° angle to determine the number of points for that particular variable. The sum of these numbers is located on the total points axis, and a line is drawn at a 90° angle downward to the “Predicted SAP” axis to determine the likelihood of POF (a). Alternatively, POF rate can be ascertained from the online calculator with 95% CI in both graphical (b) and numerical (c) summary

      Concordance and clinical utility of the nomogram

      In the training cohort there was good concordance (C-index) between predicted POF and actual POF at 0.88 (Fig. 2a) and shown by the calibration curve (Fig. 2b). The C-index was 0.91 for the internal validation cohort (Figure 2c and d) and 0.81 for the external validation cohort (Figure 2e and f) compared with the training cohort.
      Figure 2
      Figure 2Assessment of the nomogram in all three cohorts. The accuracy of the model was determined using AUC analysis and the distribution of the predicted probabilities presented by calibration curve for cohorts of the training (a, b), internal validation (c, d), and external validation (e, f)
      The nomogram of training cohort (Fig. 3a and b), internal validation cohort (Fig. 3c and d), and external validation cohort (Fig. 3e and f) exhibited better or equal clinical utility (DCA) with the other prognostic scores and had good clinical net benefits (CIC) for the identification of SAP patients. Of particular note, the nomogram outperformed all other indices in the internal validation cohort suggesting that it could help clinicians to obtain maximum benefit when making clinical decisions as it showed more benefit than the extreme situation of diagnosing POF in all patients or none.
      Figure 3
      Figure 3Clinical utility of the nomogram. The DCA and CIC of the nomogram for predicting POF in cohorts of training (a, b), internal validation (c, d), and external validation (e, f)

      Prediction of POF, major infection, and mortality by nomogram

      Prediction of POF

      The pre-test probability of POF in the training, internal validation and external validation cohorts was 9.8% (80/816), 7.5% (30/398) and 20.2% (178/880) patients, respectively (Table 2).
      The nomogram had a positive likelihood ratio and post-test probability of developing POF in the training, internal validation and external validation cohorts of 4.26 and 31.7% (259/816), PLR 7.89 and 39.1% (156/398) and PLR 2.75 and 41% (361/880) patients, respectively (Table 4).
      Table 4Predictive value of the nomogram and clinical prognostic scores for persistent organ failure
      AUCP valueCut-offSensitivity (%)Specificity (%)PLRNLRPost_Prob_Pos (%)Post_Prob_Neg (%)
      Training cohort (9.8% pre-test probability)
      Nomogram0.88 (0.86–0.91)<0.00191.278.881.54.260.2631.72.8
      NEWS0.85 (0.82–0.87)<0.001466.3885.540.3837.64
      BISAP0.89 (0.87–0.91)<0.001278.889.17.240.2444.02.5
      APACHE II0.79 (0.76–0.82)<0.001661.3833.610.4728.24.9
      SIRS0.84 (0.81–0.86)<0.001291.374.63.590.1228.11.3
      Glasgow0.75 (0.72–0.78)<0.001261.378.82.890.4923.95.1
      SOFA0.87 (0.84–0.89)<0.00118581.24.530.1833.01.9
      Validation cohort
      Internal validation (7.5% pre-test probability)
      Nomogram0.91 (0.88–0.94)<0.00179.29088.67.890.1139.10.9
      NEWS0.79 (0.75–0.83)<0.001470.075.02.800.4018.53.1
      BISAP0.75 (0.71–0.79)<0.001246.791.95.720.5831.74.5
      APACHE II0.66 (0.61–0.71)0.005636.789.43.460.7121.95.4
      SIRS0.68 (0.63–0.72)<0.001270.061.41.810.4912.83.8
      Glasgow0.69 (0.64–0.73)<0.001346.780.72.420.6616.45.1
      SOFA0.73 (0.68–0.77)<0.001263.375.82.620.4817.53.7
      External validation (20.2% pre-test probability)
      Nomogram0.81 (0.79–0.84)<0.00169.479.870.92.750.29416.7
      NEWS0.76 (0.73–0.79)<0.001562.478.62.920.4842.510.8
      BISAP0.75 (0.72–0.78)<0.001253.484.33.410.5546.312.3
      APACHE II0.75 (0.72–0.78)<0.001956.280.82.920.5442.612.1
      SIRS0.73 (0.70–0.76)<0.001268.069.22.210.4635.910.5
      Glasgow0.78 (0.75–0.81)<0.001359.682.53.40.4946.311.1
      SOFA0.80 (0.77–0.83)<0.001263.585.04.240.4351.89.8
      AUC, area under curve; PLR, positive likelihood ratio; NLR, negative likelihood ratio; Post_Prob_Pos, post-test probability of a positive test; Post_Prob_Neg, post-test probability of a negative test; NEWS, National Early Warning Score; BISAP, Bedside Index for Severity in Acute Pancreatitis; APACHE II, Acute Physiology and Chronic Health Examination II; SIRS, Systemic Inflammatory Response Syndrome; SOFA, Sequential Organ Failure Assessment.
      The nomogram had a negative likelihood ratio and post-test probability of not developing POF in the training, internal validation and external validation cohorts of 0.26 and 2.8% (23/816), PLR 0.11 and 0.9% (4/398) and PLR 0.29 and 6.7% (59/880) patients, respectively (Table 4).

      Comparison with other prognostic systems for POF

      Training Cohort: Comparing with the other prognostic scores, the nomogram had the second highest AUC (AUC 0.88 [0.86–0.91]; the AUC for BISAP was 0.89 [0.87–0.91]. BISAP had the highest predictive value (AUC 0.89 [0.87–0.91], PLR 7.24) for POF compared with the other indices (Table 4; upper panel) and followed by the nomogram (AUC 0.88 [0.86–0.91], PLR 4.26), both higher than APACHE II (0.79 [0.76–0.82], PLR 3.61) and Glasgow (0.75 [0.72–0.78], PLR 2.89) (P < 0.05, Online Supplementary Table S2) in training cohort.
      Internal validation cohort: The nomogram showed the best predictive value (AUC 0.91 [0.88–0.94], PLR 7.89, Table 4; middle panel) in internal validation cohort and higher than all other clinical scoring systems (P < 0.05; Online Supplementary Table S2), followed by NEWS (0.79 [0.75–0.83], PLR 2.80) and BISAP (0.75 [0.71–0.79], PLR 5.72). In addition, the NLR (0.11) of the nomogram ranked the best among all the comparative indices, with the lowest post-test probability of not being POF (0.9%) indicating a high negative prediction value.
      External validation cohort: The nomogram also ranked the top AUC (0.81 [0.79–0.84]), lowest NLR (0.29) and post-test probability of not being POF (6.7%) among all the indices in the external validation cohort (Table 4; lower panel), with the AUC higher than NEWS, BISAP, APACHE II and SIRS (P < 0.05; Online Supplementary Table S2).
      Subgroup analyses compared predictive value of the nomogram on POF between different causes of AP patients. The nomogram showed no significant difference in predictive values for predicting POF in both hypertriglyceridemia and non-hypertriglyceridemia (biliary, alcohol and others) patients in all three cohorts (Table 5).
      Table 5Accuracy of nomogram in predicting POF between hypertriglyceridemia and non-hypertriglyceridemia associated-acute pancreatitis patients
      EtiologyPre-test probabilityAUCP valueCut-offSensitivity (%)Specificity (%)PLRNLRPost_Prob_Pos (%)Post_Prob_Neg (%)P value
      Training cohort
      HTG12.4%0.89 (0.84–0.92)<0.00171.710062.02.630.027.00.00.998
      Non-HTG8.56%0.89 (0.86–0.91)<0.00191.283.078.73.890.2226.72.0
      Validation cohort
      Internal validation cohort
      HTG8.98%0.91 (0.86–0.95)<0.00182.593.390.810.130.0750.00.70.970
      Non-HTG6.49%0.92 (0.87–0.95)<0.00179.286.790.38.910.1538.21.0
      External validation cohort
      HTG25%0.86 (0.80–0.91)<0.00176.376.182.64.370.2959.38.80.115
      Non-HTG19%0.80 (0.77–0.83)<0.00169.677.370.92.660.3238.37.0
      POF, persistent organ failure; AUC, area under curve; PLR, positive likelihood ratio; NLR, negative likelihood ratio; Post_Prob_Pos, post-test probability of a positive test; Post_Prob_Neg, post-test probability of a negative test; HTG, hypertriglyceridemia.

      Prediction of major infection

      There was 5.5% (45/816), 5.0% (20/398) and 6.0% (53/880) had infection in the training, internal and external validation cohorts, respectively. In the training cohort, the accuracy of these predictors was generally low with BISAP (0.75 [0.72–0.78], PLR 4.29) having the highest predictive value compared with the other indices in training cohort (Online Supplementary Table S3; upper panel), but there was no statistical difference between any of them (Online Supplementary Table S2). In both the internal and external validation cohorts, the nomogram showed the best predictive value (highest AUC 0.78 [0.73–0.82]/0.80 [0.77–0.83]; lowest NLR 0.47/0.22; lowest post-test probability of not being major infection 2.4%/1.4%; Online Supplementary Table S3; middle and lower panels).

      Prediction of mortality

      There was 1.2% (10/816), 1.0% (4/398) and 2.3% (20/880) mortality in the training, internal validation and external validation cohorts, respectively. All the deaths were from patients with POF in the three cohorts (12.5%, 13.3% and 11.2%; Online Supplementary Tables S1a–c). In both the training and external cohorts, the nomogram (AUC 0.88 [0.85–0.90], 0.89 [0.87-0.91]) showed the equivalent predictive values for mortality with most of the clinical scoring systems (Online Supplementary Table S4). In the internal validation cohort, the nomogram had the highest predictive values (0.99 [0.98–1.00], PLR 32.8, NLR 0.26) for mortality, followed by BISAP (0.95 [0.92–0.97], PLR 9.85), and NEWS (0.90 [0.86–0.93], PLR 29.6, NLR 0.26), all higher than the remaining clinical scores (Online Supplementary Table S4).

      Data integrity

      Since there was substantial amount of missing data, we assessed whether the patients included in all cohorts were different from those who were excluded due to missing data. There were no significant differences in age, hypertriglycedemic etiology, persistent organ failure, major infection, and mortality (Online Supplementary Table S5).

      Discussion

      In this study, we developed and validated a mobile terminal-based nomogram for predicting POF, major infection, and mortality using six independent prognostic factors (age, respiratory rate, albumin, LDH, oxygenation, and pleural effusion) that readily available on admission. This nomogram was found to be superior with the both internal and external validation cohort compared with other prognostic scores recommended for clinical use for predicting POF and major infection. Subgroup analysis comparing hypertriglyceridemia and non-hypertriglyceridemia etiology did not significantly change the predictive values of the nomogram for predicting POF, indicating its suitability for heterogenous etiologies. As POF is the diagnostic criteria for SAP, this nomogram is recommended for routine clinical use to predict SAP on admission or to rule it out (validation NLR 0.11/0.29). Therefore, these findings encourage the use of the simple-to-use web-based nomogram before new markers are developed and introduced in our settings. The consecutive nature of patient recruitment and short time from onset of pain to admission, stringently applied in two large different Chinese centers, adds strength to these conclusions.
      Age is recognized as an individual risk factor for increased severity of AP and has been used by several prognostic scores
      • Di M.Y.
      • Liu H.
      • Yang Z.Y.
      • Bonis P.A.
      • Tang J.L.
      • Lau J.
      Prediction models of mortality in acute pancreatitis in adults: a systematic review.
      ,
      • Mounzer R.
      • Langmead C.J.
      • Wu B.U.
      • Evans A.C.
      • Bishehsari F.
      • Muddana V.
      • et al.
      Comparison of existing clinical scoring systems to predict persistent organ failure in patients with acute pancreatitis.
      and practice guidelines.
      • Leppaniemi A.
      • Tolonen M.
      • Tarasconi A.
      • Segovia-Lohse H.
      • Gamberini E.
      • Kirkpatrick A.W.
      • et al.
      WSES guidelines for the management of severe acute pancreatitis.
      To investigate the role of age and comorbidity in the severity of AP, Frey et al.
      • Frey C.
      • Zhou H.
      • Harvey D.
      • White R.H.
      Co-morbidity is a strong predictor of early death and multi-organ system failure among patients with acute pancreatitis.
      carried out a retrospective study in 84,713 patients with a first-attack AP. They found that the 65 to 75 age group, and age >75 are strong predictors of early death with an odds ratio (OR) of 2.6 and 5.2, respectively. Similar findings also applied to patients with two chronic comorbidities (OR: 3.5) or ≥ 3 comorbidities (OR: 7.4). Moreover, the mortality rate was only 0.1% (14/14,280) for younger patients (age <55) without chronic comorbidities compared to 5.9% (701/24,852) for elderly patients (age >64) with ≥3 comorbidities in the first 14 days. In addition, they showed that recent cancer, heart failure, and renal and liver diseases are strongly correlated with outcomes. Further, in acute interstitial AP, which is known to have low mortality, the Charlson comorbidity index was strongly associated with adverse clinical outcomes.
      • Singh V.K.
      • Bollen T.L.
      • Wu B.U.
      • Repas K.
      • Maurer R.
      • Yu S.
      • et al.
      An assessment of the severity of interstitial pancreatitis.
      A recent review has concluded that age is associated with frequent cases of severe AP, leading to increased multiorgan failure and high mortality.
      • Baeza-Zapata A.A.
      • Garcia-Compean D.
      • Jaquez-Quintana J.O.
      • Collaborators
      Acute pancreatitis in elderly patients.
      Because of the significant impact of the degree and number of comorbidities on clinical outcomes, we therefore excluded patients with advanced (end-stage) comorbidities with an emphasizing on assessing the intrinsic prognostic factors for AP severity.
      Hypoalbuminemia occur in critically ill patients due to several factors including dilution from resuscitation, increased interstitial loss, altered liver function, and catabolic nutritional state.
      • Vincent J.L.
      • Russell J.A.
      • Jacob M.
      • Martin G.
      • Guidet B.
      • Wernerman J.
      • et al.
      Albumin administration in the acutely ill: what is new and where next?.
      It is strongly associated with poor clinical outcomes in acutely ill patients and it has also been shown to independently associated with POF and mortality in AP patients.
      • Hong W.
      • Lin S.
      • Zippi M.
      • Geng W.
      • Stock S.
      • Basharat Z.
      • et al.
      Serum albumin is independently associated with persistent organ failure in acute pancreatitis.
      Whitcomb et al.
      • Komara N.L.
      • Paragomi P.
      • Greer P.J.
      • Wilson A.S.
      • Breze C.
      • Papachristou G.I.
      • et al.
      Severe acute pancreatitis: capillary permeability model linking systemic inflammation to multiorgan failure.
      has recently found that albumin dropped rapidly in AP patients with multiple organ failure resulting in unregulated capillary leak with continued loss of larger plasma proteins. In contrast, the plasma albumin levels only dropped slightly in patients without multiple organ failure who tended to recover quickly unless they develop complications (infected pancreatic necrosis or sepsis). The therapeutic effect of albumin in inflammatory states is not only by affecting plasma volume dilation, but also by regulating inflammation and oxidative stress.
      • Bernardi M.
      • Angeli P.
      • Claria J.
      • Moreau R.
      • Gines P.
      • Jalan R.
      • et al.
      Albumin in decompensated cirrhosis: new concepts and perspectives.
      Hypalbuminemia has recently been shown to be associated with severe AP and increased mortality in a cohort of 1149 patients.
      • Ocskay K.
      • Vinko Z.
      • Nemeth D.
      • Szabo L.
      • Bajor J.
      • Godi S.
      • et al.
      Hypoalbuminemia affects one third of acute pancreatitis patients and is independently associated with severity and mortality.
      This is consistent with the inclusion of serum albumin level in a number of prognostic indices, including the Glasgow criteria.
      • Xu X.
      • Ai F.
      • Huang M.
      Deceased serum bilirubin and albumin levels in the assessment of severity and mortality in patients with acute pancreatitis.
      Raised lactate levels has been observed in many critical acute illness situations including sepsis
      • Singer M.
      • Deutschman C.S.
      • Seymour C.W.
      • Shankar-Hari M.
      • Annane D.
      • Bauer M.
      • et al.
      The third international consensus definitions for sepsis and septic shock (Sepsis-3).
      and AP.
      • Shu W.
      • Wan J.
      • Chen J.
      • He W.
      • Zhu Y.
      • Lu N.
      • et al.
      Elevated arterial lactate level as an independent risk factor for pancreatic infection in moderately severe acute pancreatitis.
      Elevated lactate may serve as a protective mechanism and has been shown to reduce Toll-like receptor and inflammasome-mediated pancreatic and liver injury via its receptor GPR81. LDH can reversibly catalyze the oxidation of lactate to pyruvate and has been employed by Ranson, Glasgow, Japanese Severity Score,
      • Mounzer R.
      • Langmead C.J.
      • Wu B.U.
      • Evans A.C.
      • Bishehsari F.
      • Muddana V.
      • et al.
      Comparison of existing clinical scoring systems to predict persistent organ failure in patients with acute pancreatitis.
      and a nomogram
      • Li C.
      • Ren Q.
      • Wang Z.
      • Wang G.
      Early prediction of in-hospital mortality in acute pancreatitis: a retrospective observational cohort study based on a large multicentre critical care database.
      for early AP severity prediction and reported as a simple and useful parameter for predicting POF
      • Xiao W.
      • Liu W.
      • Yin L.
      • Li Y.
      • Lu G.
      • Liu X.
      • et al.
      Serum hydroxybutyrate dehydrogenase as an early predictive marker of the severity of acute pancreatitis: a retrospective study.
      and pancreatic necrosis.
      • Komolafe O.
      • Pereira S.P.
      • Davidson B.R.
      • Gurusamy K.S.
      Serum C-reactive protein, procalcitonin, and lactate dehydrogenase for the diagnosis of pancreatic necrosis.
      Respiratory rate and oxygen support reflect respiratory status and with respiratory failure as one most common organ dysfunction in AP,
      • Shi N.
      • Liu T.
      • de la Iglesia-Garcia D.
      • Deng L.
      • Jin T.
      • Lan L.
      • et al.
      Duration of organ failure impacts mortality in acute pancreatitis.
      the early recognition of respiratory dysfunction is considered important. Our results showed a positive association between the development of POF and an increased respiratory rate or requirement for oxygen support on admission. Therefore, both respiratory rate and oxygen support have been adopted in NEWS
      National Early Warning Score(NEWS)
      Standardising the assessment of acute- illness severity in the NHS. Report of a working party.
      for their convenience and prognostic value. The significance of pleural effusion in AP patients has been long reported, and is part of BISAP.
      • Wu B.U.
      • Johannes R.S.
      • Sun X.
      • Tabak Y.
      • Conwell D.L.
      • Banks P.A.
      The early prediction of mortality in acute pancreatitis: a large population-based study.
      Our results showed that pleural effusion (odds ratio: 3.61 95%CI 1.97–6.6, P < 0.001) was an independent predictor for SAP, consistent with a previous study.
      • He F.
      • Zhu H.M.
      • Li B.Y.
      • Li X.C.
      • Yang S.
      • Wang Z.
      • et al.
      Factors predicting the severity of acute pancreatitis in elderly patients.
      In our univariate analysis before establishing the predictive nomogram, we also found white blood cell count, glucose, urea (or blood urea nitrogen), creatinine, and ionized calcium were independent individual prognostic factors for POF, consistent with previously published literature.
      • Mounzer R.
      • Langmead C.J.
      • Wu B.U.
      • Evans A.C.
      • Bishehsari F.
      • Muddana V.
      • et al.
      Comparison of existing clinical scoring systems to predict persistent organ failure in patients with acute pancreatitis.
      However, when these parameters were fitted into our multiple logistic regression model, they only had negligible impact on the final nomogram. Unlike most previously published studies included high proportion of SAP patients, we used a training consecutive cohort constituted only up to 10% of SAP patients which may partially explain different weights of individual prognostic factors in varied epidemiology situations. For example, three of the four existing predictive nomograms for AP severity were conducted in the ICU settings which cannot be generalizable for emergence departments or general wards where patients are primarily admitted.
      Some of the six independent prognostic factors of our nomogram are included as part of NEWS (respiratory rate and oxygen support) and BISAP (age, respiratory rate, and pleural effusion), the two that we found had justifiable good predictive values for POF in both our training and internal validation cohorts. However, the nomogram was simpler than BISAP and more AP-specific than NEWS to quantitatively predict clinical outcomes in a personalized way. In addition, we validated the nomogram in another Chinese tertiary hospital with the etiological composition different from ours. The results showed that the nomogram with stable clinical applicability in both AP cohorts with hypertriglyceridemia (internal validation) or biliary (external validation) as the main etiology, adding strength to its applicability.
      Our study also has some limitations. Firstly, excluding missing data may contribute to varied accuracy of the nomogram. However, we found majority of the key parameters of baseline and outcomes, albeit not all (i.e. gender and length of hospital stay), were similar between those included and those with missing data in all cohorts. Secondly, the nomogram model was developed mainly based on the variables that were easy to get in our retrospective sets, but did not include other factors that may influence the precision of the model. For example, the oxygenation index was not included in our analysis because only paucity data were available. In a most recent study,
      • Liu Y.
      • Liu J.
      • Huang L.
      A simple-to-use web-based calculator for survival prediction in acute respiratory distress syndrome.
      the authors found that oxygenation index had low prognostic power (AUC 55.3%) for acute respiratory distress syndrome. Thirdly, the nomogram did not have specific markers for circulatory and renal failure. The reasons for this may be attributed to low incidence of circulatory and renal failure of the study population and at the early disease stage respiratory failure commonly precedes other organ failures.
      • Guo Q.
      • Li A.
      • Xia Q.
      • Liu X.
      • Tian B.
      • Mai G.
      • et al.
      The role of organ failure and infection in necrotizing pancreatitis: a prospective study.
      ,
      • Schepers N.J.
      • Bakker O.J.
      • Besselink M.G.
      • Ahmed Ali U.
      • Bollen T.L.
      • Gooszen H.G.
      • et al.
      Impact of characteristics of organ failure and infected necrosis on mortality in necrotising pancreatitis.
      In the last, the lack of international validation may limit the extrapolation and generalizability of the nomogram.

      Conclusions

      Our nomogram based on six readily available factors accurately predicted POF on admission in patients with AP. This nomogram can be routinely used for early AP severity prediction in our clinical practice if further validated in multiple center studies.

      Authors’ contributions

      QX, WH, and WHe obtained funding, and concepted, designed and supervised the study. NS collected, analyzed all retrospective and prospective data of Chengdu center, and drafted the manuscript. XZ collected and analyzed all retrospective data. WHe, LX, YZ, and NL provided and analyzed external validation datasets. LL, WC, LY, XY (Xinmin Yang) and RZ supported collecting data. PZ assisted data analysis. LD, TJ, ZL and KJ audited data quality. GJ and XY (XiaonanYang) supervised the patients’ treatment. WH and QX designed, TW and PS assisted, RS reviewed the proforma and e-database. VKS, RS, and JAW had important intelligence input. WH and JAW critically revised the manuscript. All authors read and approved the final manuscript.

      Ethics approval and consent to participate

      This study was approved by the Institutional Review Board of West China Hospital of Sichuan University and The First Affiliated Hospital of Nanchang University.

      Consent for publication

      All authors have provided consent for publication of the manuscript.

      Availability of data and materials

      The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

      Acknowledgements

      The authors thank all the participants and attending physicians for their contributions. This study was supported by NZ-China Strategic Research Alliance 2016 Award (China: 2016YFE0101800, QX, TJ, WH and LD; New Zealand: JAW); Key Research and Development Program of Science and Technology Department of Sichuan Province (2020YFS0235, NS; 2019YFS0259, XZ); National Natural Science Foundation of China (81973632, WH; 81774120, QX; 81860122, WHe); and National Institute for Health Research ( NIHR ) Senior Investigator Award (RS).

      Conflicts of interest

      None to declare.

      Appendix A. Supplementary data

      The following are the Supplementary data to this article:

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