Skip to main content

Advertisement

SpringerLink
Log in

A Simple Risk Score to Predict Clavien-Dindo Grade IV and V Complications After Non-elective Cholecystectomy

  • Original Article
  • Published:
Journal of Gastrointestinal Surgery Aims and scope

Abstract

Background

Non-elective cholecystectomies can lead to severe postoperative complications and mortality. Existing risk prediction tools do not meet the need to reliably predict these complications.

Methods

Using the 2011–2016 American College of Surgeons National Surgical Quality Improvement Program datasets, we identified patients undergoing non-elective cholecystectomy with primary ICD 9/10 codes indicating the following diagnoses: symptomatic cholelithiasis, acute cholecystitis, choledocholithiasis, gallstone pancreatitis, and cholangitis. We randomly allocated patients to derivation and validation cohorts (80/20 split). Severe complications (Clavien-Dindo grades IV and V) included unplanned intubation, prolonged mechanical ventilation, pulmonary embolism, acute renal failure requiring dialysis, stroke, myocardial infarction, cardiac arrest, septic shock, and mortality. Logistic regression using backward selection identified predictors of severe complications and a risk score was generated based on this model.

Results

Of 68,953 patients in the derivation cohort, 1.7% (N = 1157) suffered severe complications. The final multivariable risk score model included the following predictors: age (0–12 points), preoperative sepsis (5 points), planned open procedure (5 points), estimated glomerular filtration rate (0–13 points), and preoperative albumin level (0–8 points). The associated risk-score model yielded scores from 0 to 43 with 0.1–59.4% predicted probability of severe complications and had a C-statistic of 0.845 (95% CI 0.834, 0.857) in the derivation cohort and 0.870 (95% CI 0.851, 0.889) in the validation cohort.

Conclusion

A simple risk-score model predicts severe complications in patients undergoing unplanned cholecystectomy for common indications encountered in an acute care surgery service and identifies high-risk patients.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. The American College of Surgeons Quality Improvement Program and its participating hospitals are the source of the data for this study. They have not verified nor are they responsible for the statistical validity of the data analysis or for the author’s conclusions.

  2. https://www.facs.org/~/media/files/quality%20programs/nsqip/pt_nsqip_puf_userguide_2016.ashx; Accessed September 28, 2018.

  3. https://www.tripod-statement.org/Portals/0/Tripod%20Checklist%20Prediction%20Model%20Development%20and%20Validation%20PDF.pdf; Accessed January 23, 2019.

References

  1. Cullen KA, Hall MJ, Golosinskiy A. Ambulatory surgery in the United States, 2006. Natl Health Stat Report 2009; 1–25.

    Google Scholar 

  2. DeFrances CJ, Lucas CA, Buie VC, Golosinskiy A. 2006 National Hospital Discharge Survey. Natl Health Stat Report 2008; 1–20.

    Google Scholar 

  3. Giger UF, Michel JM, Opitz I et al. Risk factors for perioperative complications in patients undergoing laparoscopic cholecystectomy: analysis of 22,953 consecutive cases from the Swiss Association of Laparoscopic and Thoracoscopic Surgery database. J Am Coll Surg 2006; 203: 723–728.

    PubMed  Google Scholar 

  4. Wolf AS, Nijsse BA, Sokal SM et al. Surgical outcomes of open cholecystectomy in the laparoscopic era. Am J Surg 2009; 197: 781–784.

    PubMed  Google Scholar 

  5. Barrett M, Asbun HJ, Chien HL et al. Bile duct injury and morbidity following cholecystectomy: a need for improvement. Surg Endosc 2018; 32: 1683–1688.

    PubMed  Google Scholar 

  6. Donkervoort SC, Kortram K, Dijksman LM et al. Anticipation of complications after laparoscopic cholecystectomy: prediction of individual outcome. Surg Endosc 2016; 30: 5388–5394.

    CAS  PubMed  Google Scholar 

  7. Kanakala V, Borowski DW, Pellen MG et al. Risk factors in laparoscopic cholecystectomy: a multivariate analysis. Int J Surg 2011; 9: 318–323.

    PubMed  Google Scholar 

  8. Philip Rothman J, Burcharth J, Pommergaard HC et al. Preoperative Risk Factors for Conversion of Laparoscopic Cholecystectomy to Open Surgery—A Systematic Review and Meta-Analysis of Observational Studies. Dig Surg 2016; 33: 414–423.

    PubMed  Google Scholar 

  9. Rosero EB, Joshi GP. Hospital readmission after ambulatory laparoscopic cholecystectomy: incidence and predictors. J Surg Res 2017; 219: 108–115.

    PubMed  Google Scholar 

  10. Kaafarani HM, Smith TS, Neumayer L et al. Trends, outcomes, and predictors of open and conversion to open cholecystectomy in Veterans Health Administration hospitals. Am J Surg 2010; 200: 32–40.

    PubMed  Google Scholar 

  11. Bilimoria KY, Liu Y, Paruch JL et al. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons. J Am Coll Surg 2013; 217: 833–842 e831–833.

    PubMed  PubMed Central  Google Scholar 

  12. Massoumi RL, Trevino CM, Webb TP. Postoperative Complications of Laparoscopic Cholecystectomy for Acute Cholecystitis: A Comparison to the ACS-NSQIP Risk Calculator and the Tokyo Guidelines. World J Surg 2017; 41: 935–939.

    PubMed  Google Scholar 

  13. To KB, Cherry-Bukowiec JR, Englesbe MJ et al. Emergent versus elective cholecystectomy: conversion rates and outcomes. Surg Infect (Larchmt) 2013; 14: 512–519.

    Google Scholar 

  14. Fink AS, Campbell DA, Jr., Mentzer RM, Jr. et al. The National Surgical Quality Improvement Program in non-veterans administration hospitals: initial demonstration of feasibility. Ann Surg 2002; 236: 344–353; discussion 353-344.

    PubMed  PubMed Central  Google Scholar 

  15. Shiloach M, Frencher SK, Jr., Steeger JE et al. Toward robust information: data quality and inter-rater reliability in the American College of Surgeons National Surgical Quality Improvement Program. J Am Coll Surg 2010; 210: 6–16.

    PubMed  Google Scholar 

  16. Alli VV, Yang J, Xu J et al. Nineteen-year trends in incidence and indications for laparoscopic cholecystectomy: the NY State experience. Surg Endosc 2017; 31: 1651–1658.

    PubMed  Google Scholar 

  17. Warren DK, Nickel KB, Wallace AE et al. Risk Factors for Surgical Site Infection After Cholecystectomy. Open Forum Infect Dis 2017; 4: ofx036.

    PubMed  PubMed Central  Google Scholar 

  18. Stevens PE, Levin A, Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline Development Work Group M. Evaluation and management of chronic kidney disease: synopsis of the kidney disease: improving global outcomes 2012 clinical practice guideline. Ann Intern Med 2013; 158: 825–830.

    PubMed  Google Scholar 

  19. Renquist K. Obesity classification. Obes Surg 1998; 8: 480.

    CAS  PubMed  Google Scholar 

  20. Dindo D, Demartines N, Clavien PA. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg 2004; 240: 205–213.

    PubMed  PubMed Central  Google Scholar 

  21. Clavien PA, Barkun J, de Oliveira ML et al. The Clavien-Dindo classification of surgical complications: five-year experience. Ann Surg 2009; 250: 187–196.

    Article  PubMed  Google Scholar 

  22. Katayama H, Kurokawa Y, Nakamura K et al. Extended Clavien-Dindo classification of surgical complications: Japan Clinical Oncology Group postoperative complications criteria. Surg Today 2016; 46: 668–685.

    PubMed  Google Scholar 

  23. Webb S, Rubinfeld I, Velanovich V et al. Using National Surgical Quality Improvement Program (NSQIP) data for risk adjustment to compare Clavien 4 and 5 complications in open and laparoscopic colectomy. Surg Endosc 2012; 26: 732–737.

    PubMed  Google Scholar 

  24. Brahmbhatt R, Gander J, Duwayri Y et al. Improved trends in patient survival and decreased major complications after emergency ruptured abdominal aortic aneurysm repair. J Vasc Surg 2016; 63: 39–47.

    PubMed  Google Scholar 

  25. Sullivan LM, Massaro JM, D’Agostino RB, Sr. Presentation of multivariate data for clinical use: The Framingham Study risk score functions. Stat Med 2004; 23: 1631–1660.

    PubMed  Google Scholar 

  26. Glance LG, Lustik SJ, Hannan EL et al. The Surgical Mortality Probability Model: derivation and validation of a simple risk prediction rule for noncardiac surgery. Ann Surg 2012; 255: 696–702.

    PubMed  Google Scholar 

  27. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988; 44: 837–845.

    CAS  PubMed  Google Scholar 

  28. van Heesewijk AE, Lammerts RGM, Haveman JW et al. Outcome after cholecystectomy in the elderly. Am J Surg 2019; 218: 368–373.

    PubMed  Google Scholar 

  29. Carbonell AM, Lincourt AE, Kercher KW et al. Do patient or hospital demographics predict cholecystectomy outcomes? A nationwide study of 93,578 patients. Surg Endosc 2005; 19: 767–773.

    CAS  PubMed  Google Scholar 

  30. Chung PJ, Smith MC, Roudnitsky V et al. A Calculated Risk: Performing Laparoscopic Cholecystectomy for Acute Cholecystitis on Patients with End Stage Renal Disease. Am Surg 2018; 84: 963–970.

    PubMed  Google Scholar 

  31. Terho PM, Leppaniemi AK, Mentula PJ. Laparoscopic cholecystectomy for acute calculous cholecystitis: a retrospective study assessing risk factors for conversion and complications. World J Emerg Surg 2016; 11: 54.

    PubMed  PubMed Central  Google Scholar 

  32. Lee TH, Marcantonio ER, Mangione CM et al. Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation 1999; 100: 1043–1049.

    CAS  PubMed  Google Scholar 

  33. Kamath PS, Wiesner RH, Malinchoc M et al. A model to predict survival in patients with end-stage liver disease. Hepatology 2001; 33: 464–470.

    CAS  PubMed  Google Scholar 

  34. Levitt DG, Levitt MD. Human serum albumin homeostasis: a new look at the roles of synthesis, catabolism, renal and gastrointestinal excretion, and the clinical value of serum albumin measurements. Int J Gen Med 2016; 9: 229–255.

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Meyer CP, Rios-Diaz AJ, Dalela D et al. The association of hypoalbuminemia with early perioperative outcomes—A comprehensive assessment across 16 major procedures. Am J Surg 2017; 214: 871–883.

    PubMed  Google Scholar 

  36. Cloyd JM, Ma Y, Morton JM et al. Does chronic kidney disease affect outcomes after major abdominal surgery? Results from the National Surgical Quality Improvement Program. J Gastrointest Surg 2014; 18: 605–612.

    PubMed  Google Scholar 

  37. Roberts I, Blackhall K, Alderson P et al. Human albumin solution for resuscitation and volume expansion in critically ill patients. Cochrane Database Syst Rev 2011; CD001208.

  38. Committee on S, Practice P, Apfelbaum JL et al. Practice advisory for preanesthesia evaluation: an updated report by the American Society of Anesthesiologists Task Force on Preanesthesia Evaluation. Anesthesiology 2012; 116: 522–538.

    Google Scholar 

  39. In Health, United States, 2009: With Special Feature on Medical Technology. Hyattsville (MD): 2010.

  40. Augustin T, Moslim MA, Brethauer S et al. Obesity and its implications for morbidity and mortality after cholecystectomy: A matched NSQIP analysis. Am J Surg 2017; 213: 539–543.

    PubMed  Google Scholar 

  41. Kiriyama S, Kozaka K, Takada T et al. Tokyo Guidelines 2018: diagnostic criteria and severity grading of acute cholangitis (with videos). J Hepatobiliary Pancreat Sci 2018; 25: 17–30.

    PubMed  Google Scholar 

  42. Wu BU, Johannes RS, Sun X et al. The early prediction of mortality in acute pancreatitis: a large population-based study. Gut 2008; 57: 1698–1703.

    CAS  PubMed  Google Scholar 

  43. Karvellas CJ, Abraldes JG, Zepeda-Gomez S et al. The impact of delayed biliary decompression and anti-microbial therapy in 260 patients with cholangitis-associated septic shock. Aliment Pharmacol Ther 2016; 44: 755–766.

    CAS  PubMed  Google Scholar 

  44. Azuhata T, Kinoshita K, Kawano D et al. Time from admission to initiation of surgery for source control is a critical determinant of survival in patients with gastrointestinal perforation with associated septic shock. Crit Care 2014; 18: R87.

    PubMed  PubMed Central  Google Scholar 

  45. Su CH, P’Eng F K, Lui WY. Factors affecting morbidity and mortality in biliary tract surgery. World J Surg 1992; 16: 536–540.

    CAS  PubMed  Google Scholar 

  46. Loozen CS, van Santvoort HC, van Duijvendijk P et al. Laparoscopic cholecystectomy versus percutaneous catheter drainage for acute cholecystitis in high risk patients (CHOCOLATE): multicentre randomised clinical trial. BMJ 2018; 363: k3965.

    PubMed  PubMed Central  Google Scholar 

  47. Okamoto K, Suzuki K, Takada T et al. Tokyo Guidelines 2018: flowchart for the management of acute cholecystitis. J Hepatobiliary Pancreat Sci 2018; 25: 55–72.

    PubMed  Google Scholar 

  48. Amirthalingam V, Low JK, Woon W, Shelat V. Tokyo Guidelines 2013 may be too restrictive and patients with moderate and severe acute cholecystitis can be managed by early cholecystectomy too. Surg Endosc 2017; 31: 2892–2900.

    PubMed  Google Scholar 

  49. Endo I, Takada T, Hwang TL et al. Optimal treatment strategy for acute cholecystitis based on predictive factors: Japan-Taiwan multicenter cohort study. J Hepatobiliary Pancreat Sci 2017; 24: 346–361.

    PubMed  Google Scholar 

  50. van Santvoort HC, Besselink MG, de Vries AC et al. Early endoscopic retrograde cholangiopancreatography in predicted severe acute biliary pancreatitis: a prospective multicenter study. Ann Surg 2009; 250: 68–75.

    PubMed  Google Scholar 

Download references

Funding

This publication was supported by the National Center for Advancing Translational Sciences, National Institutes of Health through grant number KL2TR001874 (MK). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Author information

Authors and Affiliations

  1. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA

    Jonathan Burke & Minjae Kim

  2. University of Miami Miller School of Medicine, Miami, FL, USA

    Jonathan Burke & Shaina Sedighim

  3. DeWitt Daughtry Family Department of Surgery, Division of Trauma and Surgical Critical Care, University of Miami Miller School of Medicine, Miami, FL, USA

    Rishi Rattan

  4. Department of Anesthesiology, Columbia University Medical Center, New York, NY, USA

    Minjae Kim

Authors
  1. Jonathan Burke
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rishi Rattan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shaina Sedighim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Minjae Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Minjae Kim.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic Supplementary Material

ESM 1

(DOCX 15 kb)

ESM 2

(DOCX 14 kb)

ESM 3

(PDF 140 kb)

ESM 4

(DOCX 16 kb)

ESM 5

(DOCX 13 kb)

ESM 6

(DOCX 19 kb)

ESM 7

(PDF 15 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Burke, J., Rattan, R., Sedighim, S. et al. A Simple Risk Score to Predict Clavien-Dindo Grade IV and V Complications After Non-elective Cholecystectomy. J Gastrointest Surg 25, 201–210 (2021). https://doi.org/10.1007/s11605-020-04514-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11605-020-04514-9

Keywords

Search

Navigation