A Comprehensive Way to Access Hospital Death Prediction Model for Acute Mesenteric Ischemia: A Combination of Traditional Statistics and Machine Learning

References

• Clair DG, Beach JM. Mesenteric ischemia. New Engl J Med. 2016;374(10):959–968. doi:10.1056/NEJMra1503884
   PubMed Web of Science ®Google Scholar
• Menke J. Diagnostic accuracy of multidetector CT in acute mesenteric ischemia: systematic review and meta-analysis. Radiology. 2010;256(1):93–101. doi:10.1148/radiol.10091938
   PubMed Web of Science ®Google Scholar
• Duran M, Pohl E, Grabitz K, Schelzig H, Sagban TA, Simon F. The importance of open emergency surgery in the treatment of acute mesenteric ischemia. WJES. 2015;10:45. doi:10.1186/s13017-015-0041-6
   PubMed Web of Science ®Google Scholar
• Wu W, Liu J, Zhou Z. Preoperative risk factors for short-term postoperative mortality of acute mesenteric ischemia after laparotomy: a systematic review and meta-analysis. Emerg Med Int. 2020;2020:1382475. doi:10.1155/2020/1382475
   PubMed Web of Science ®Google Scholar
• Huang HH, Chang YC, Yen DH, et al. Clinical factors and outcomes in patients with acute mesenteric ischemia in the emergency department. J Chinese Med Assoc. 2005;68(7):299–306. doi:10.1016/S1726-4901(09)70165-0
   PubMedGoogle Scholar
• Acosta-Merida MA, Marchena-Gomez J, Hemmersbach-Miller M, Roque-Castellano C, Hernandez-Romero JM. Identification of risk factors for perioperative mortality in acute mesenteric ischemia. World J Surg. 2006;30(8):1579–1585. doi:10.1007/s00268-005-0560-5
   PubMed Web of Science ®Google Scholar
• Wu W, Yang L, Zhou Z. Clinical features and factors affecting postoperative mortality for obstructive acute mesenteric ischemia in China: a hospital-based survey. Vasc Health Risk Manag. 2020;16:479–487. doi:10.2147/VHRM.S261167
   PubMed Web of Science ®Google Scholar
• Corcos O, Castier Y, Sibert A, et al. Effects of a multimodal management strategy for acute mesenteric ischemia on survival and intestinal failure. Clin Gastroenterol Hepatol. 2013;11(2):158–165. e152. doi:10.1016/j.cgh.2012.10.027
   PubMed Web of Science ®Google Scholar
• Yang S, Fan X, Ding W, et al. Multidisciplinary stepwise management strategy for acute superior mesenteric venous thrombosis: an intestinal stroke center experience. Thromb Res. 2015;135(1):36–45. doi:10.1016/j.thromres.2014.10.018
   PubMed Web of Science ®Google Scholar
• Iasonos A, Schrag D, Raj GV, Panageas KS. How to build and interpret a nomogram for cancer prognosis. J clin oncol. 2008;26(8):1364–1370. doi:10.1200/JCO.2007.12.9791
   PubMed Web of Science ®Google Scholar
• Alpaydin E. Introduction to Machine Learning. MIT press; 2020.
   Google Scholar
• Vieira SM, Mendonça LF, Farinha GJ, Sousa JM. Modified binary PSO for feature selection using SVM applied to mortality prediction of septic patients. Appl Soft Comput. 2013;13(8):3494–3504. doi:10.1016/j.asoc.2013.03.021
   Web of Science ®Google Scholar
• Shen Y, Wu C, Liu C, Wu Y, Xiong N. Oriented feature selection SVM applied to cancer prediction in precision medicine. IEEE Access. 2018;6:48510–48521. doi:10.1109/ACCESS.2018.2868098
   Web of Science ®Google Scholar
• Johnson AE, Pollard TJ, Shen L, et al. MIMIC-III, a freely accessible critical care database. Scientific Data. 2016;3:160035. doi:10.1038/sdata.2016.35
   PubMed Web of Science ®Google Scholar
• Moons KG, Altman DG, Reitsma JB, et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W1–W73. doi:10.7326/M14-0698
   PubMed Web of Science ®Google Scholar
• Harrell FE. Regression modeling strategies. BIOS. 2017;330:2018.
   Google Scholar
• Tibshirani R. Regression shrinkage and selection via the lasso. J Royal Stat Soc Series B. 1996;58(1):267–288.
   Google Scholar
• Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw. 2010;33(1):1. doi:10.18637/jss.v033.i01
   PubMed Web of Science ®Google Scholar
• Kursa MB, Rudnicki WR. Feature selection with the Boruta package. J Stat Softw. 2010;36(11):1–13. doi:10.18637/jss.v036.i11
   Web of Science ®Google Scholar
• Hastie T, Tibshirani R, Friedman J. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer Science & Business Media; 2009.
   Google Scholar
• Karatzoglou A, Smola A, Hornik K, Zeileis A. kernlab-an S4 package for kernel methods in R. J Stat Softw. 2004;11(9):1–20. doi:10.18637/jss.v011.i09
   Google Scholar
• Chen T, He T, Benesty M, Khotilovich V, Tang Y. Xgboost: extreme gradient boosting. R package version 04-2. 2015;1–4.
   Google Scholar
• Huang G-B, Zhu Q-Y, Siew C-K. Extreme learning machine: theory and applications. Neurocomputing. 2006;70(1–3):489–501. doi:10.1016/j.neucom.2005.12.126
   Web of Science ®Google Scholar
• Mouselimis L, Gosso A. elmNNRcpp: the extreme learning machine Algorithm, R Package Version 1.0. 1.
   Google Scholar
• Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decision Making. 2006;26(6):565–574. doi:10.1177/0272989X06295361
   PubMed Web of Science ®Google Scholar
• Akyildiz HY, Sozuer E, Uzer H, Baykan M, Oz B. The length of necrosis and renal insufficiency predict the outcome of acute mesenteric ischemia. Asian J Surg. 2015;38(1):28–32. doi:10.1016/j.asjsur.2014.06.001
   PubMed Web of Science ®Google Scholar
• Edwards MS, Cherr GS, Craven TE, et al. Acute occlusive mesenteric ischemia: surgical management and outcomes. Ann Vasc Surg. 2003;17(1):72–79. doi:10.1007/s10016-001-0329-8
   PubMed Web of Science ®Google Scholar
• Nuzzo A, Maggiori L, Ronot M, et al. Predictive factors of intestinal necrosis in acute mesenteric ischemia: prospective study from an intestinal stroke center. Am J Gastroenterol. 2017;112(4):597–605. doi:10.1038/ajg.2017.38
   PubMed Web of Science ®Google Scholar
• Jandial A, Kumar S, Bhalla A, Sharma N, Varma N, Varma S. Elevated red cell distribution width as a prognostic marker in severe sepsis: a prospective observational study. Indian J Critical Care Med. 2017;21(9):552. doi:10.4103/ijccm.IJCCM_208_17
   PubMed Web of Science ®Google Scholar
• Rajkomar A, Dean J, Kohane I. Machine learning in medicine. New Engl J Med. 2019;380(14):1347–1358. doi:10.1056/NEJMra1814259
   PubMed Web of Science ®Google Scholar
• Elstein AS. Heuristics and biases: selected errors in clinical reasoning. Acad Med. 1999;74:791–794. doi:10.1097/00001888-199907000-00012
   PubMed Web of Science ®Google Scholar