Development of clinical decision rules to predict recurrent shock in dengue

Critical Care

Volumn 17, Issue 6, 2013, Pages

  Huy, Nguyen T ^a   Thao, Nguyen Thanh H ^b   Ha, Tran Thi N ^c   Lan, Nguyen Thi P ^c   Nga, Phan Thi T ^d   Thuy, Tran T ^b   Tuan, Ha M ^b   Nga, Cao Thi P ^e   Van Tuong, Vo ^e   Van Dat, Tran ^e   Huong, Vu Thi Q ^c   Karbwang, Juntra ^a   Hirayama, Kenji ^a  

^a NAGASAKI UNIVERSITY   (Japan)

^b Children's Hospital   (Viet Nam)

^c PASTEUR INSTITUTE   (Viet Nam)

^d UNIVERSITY OF MEDICINE AND PHARMACY AT HO CHI MINH CITY   (Viet Nam)

^e Center for Preventive Medicine   (Viet Nam)

Author keywords

[No Author keywords available]

Indexed keywords

ASCITES; COMPLICATION; DECISION SUPPORT SYSTEM; DENGUE; ECCHYMOSIS; HOSPITALIZATION; HUMAN; PLEURAL EFFUSION; PULSE RATE; PURPURA; RECURRENT DISEASE; SHOCK; STATISTICAL MODEL; THROMBOCYTE COUNT; TIME;

ASCITES; DECISION SUPPORT TECHNIQUES; DENGUE; ECCHYMOSIS; HOSPITALIZATION; HUMANS; LOGISTIC MODELS; PLATELET COUNT; PLEURAL EFFUSION; PULSE; PURPURA; RECURRENCE; SHOCK; TIME FACTORS;

EID: 84888613099     PISSN: 13648535     EISSN: 1466609X     Source Type: Journal    
DOI: 10.1186/cc13135     Document Type: Article

References (51)

1. Guzman MG, Halstead SB, Artsob H, Buchy P, Farrar J, Gubler DJ, Hunsperger E, Kroeger A, Margolis HS, Martínez E, Nathan MB, Pelegrino JL, Simmons C, Yoksan S, Peeling RW. Dengue: a continuing global threat. Nat Rev Microbiol 2010, 8(12 Suppl):S7-S16.
2. World Health Organization (WHO) Epidemiology, burden of disease and transmission. Dengue: Guidelines for Diagnosis, Treatment, Prevention and Control 2009, 3-21. Geneva: WHO, World Health Organization (WHO).
3. Kurane I. Dengue hemorrhagic fever with special emphasis on immunopathogenesis. Comp Immunol Microbiol Infect Dis 2007, 30:329-340.
4. White NJ. Variation in virulence of dengue virus. Lancet 1999, 354:1401-1402.
5. Halstead SB. Dengue. Lancet 2007, 370:1644-1652.
6. Lan NT, Hirayama K. Host genetic susceptibility to severe dengue infection. Trop Med Health 2011, 39(4 Suppl):73-81.
7. Lan NTP, Kikuchi M, Huong VTQ, Ha DQ, Thuy TT, Tham VD, Tuan HM, Tuong VV, Nga CTP, Dat TV, Oyama T, Morita K, Yasunami M, Hirayama K. Protective and enhancing HLA alleles, HLA-DRB1*0901 and HLA-A*24, for severe forms of dengue virus infection, dengue hemorrhagic fever and dengue shock syndrome. PLoS Negl Trop Dis 2008, 2:e304.
8. Mongkolsapaya J, Duangchinda T, Dejnirattisai W, Vasanawathana S, Avirutnan P, Jairungsri A, Khemnu N, Tangthawornchaikul N, Chotiyarnwong P, Sae-Jang K, Koch M, Jones Y, McMichael A, Xu X, Malasit P, Screaton G. T cell responses in dengue hemorrhagic fever: Are cross-reactive T cells suboptimal?. J Immunol 2006, 176:3821-3829.
9. Chaturvedi UC, Nagar R, Shrivastava R. Macrophage and dengue virus: friend or foe?. Indian J Med Res 2006, 124:23-40.
10. Chaturvedi UC, Agarwal R, Elbishbishi EA, Mustafa AS. Cytokine cascade in dengue hemorrhagic fever: implications for pathogenesis. FEMS Immunol Med Microbiol 2000, 28:183-188.
11. Lin CF, Chiu SC, Hsiao YL, Wan SW, Lei HY, Shiau AL, Liu HS, Yeh TM, Chen SH, Liu CC, Lin YS. Expression of cytokine, chemokine, and adhesion molecules during endothelial cell activation induced by antibodies against dengue virus nonstructural protein 1. J Immunol 2005, 174:395-403.
12. Whitehorn J, Simmons CP. The pathogenesis of dengue. Vaccine 2011, 29:7221-7228.
13. World Health Organization (WHO) Dengue Haemorrhagic Fever: Diagnosis, Treatment, Prevention and Control 1997, Geneva: WHO, 2, World Health Organization (WHO).
14. World Health Organization (WHO) Dengue: Guidelines for Diagnosis, Treatment, Prevention and Control 2009, Geneva: WHO, World Health Organization (WHO).
15. Wilder-Smith A, Ooi EE, Vasudevan SG, Gubler DJ. Update on dengue: epidemiology, virus evolution, antiviral drugs, and vaccine development. Curr Infect Dis Rep 2010, 12:157-164.
16. Kalayanarooj S. Clinical manifestations and management of dengue/DHF/DSS. Trop Med Health 2011, 39(4 Suppl):83-87.
17. Al-Muhandis N, Hunter PR. The value of educational messages embedded in a community-based approach to combat dengue fever: a systematic review and meta regression analysis. PLoS Negl Trop Dis 2011, 5:e1278.
18. Gibbons RV, Vaughn DW. Dengue: an escalating problem. BMJ 2002, 324:1563-1566.
19. Anders KL, Nguyet NM, Chau NV, Hung NT, Thuy TT, Lien LB, Farrar J, Wills B, Hien TT, Simmons CP. Epidemiological factors associated with dengue shock syndrome and mortality in hospitalized dengue patients in Ho Chi Minh City, Vietnam. Am J Trop Med Hyg 2011, 84:127-134.
20. Ngo NT, Cao XT, Kneen R, Wills B, Nguyen VM, Nguyen TQ, Chu VT, Nguyen TT, Simpson JA, Solomon T, White NJ, Farrar J. Acute management of dengue shock syndrome: a randomized double-blind comparison of 4 intravenous fluid regimens in the first hour. Clin Infect Dis 2001, 32:204-213.
21. Ha TT, Huy NT, Murao LA, Lan NT, Thuy TT, Tuan HM, Nga CT, Tuong VV, Dat TV, Kikuchi M, Yasunami M, Morita K, Huong VT, Hirayama K. Elevated levels of cell-free circulating DNA in patients with acute dengue virus infection. PLoS One 2011, 6:e25969.
22. Furuta T, Murao LA, Lan NT, Huy NT, Huong VT, Thuy TT, Tham VD, Nga CT, Ha TT, Ohmoto Y, Kikuchi M, Morita K, Yasunami M, Hirayama K, Watanabe N. Association of mast cell-derived VEGF and proteases in dengue shock syndrome. PLoS Negl Trop Dis 2012, 6:e1505.
23. Wills BA, Oragui EE, Stephens AC, Daramola OA, Dung NM, Loan HT, Chau NV, Chambers M, Stepniewska K, Farrar JJ, Levin M. Coagulation abnormalities in dengue hemorrhagic fever: serial investigations in 167 Vietnamese children with dengue shock syndrome. Clin Infect Dis 2002, 35:277-285.
24. Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 1996, 49:1373-1379.
25. Harrell FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996, 15:361-387.
26. Little RJA. A test of missing completely at random for multivariate data with missing values. J Am Stat Assoc 1988, 83:1198-1202.
27. Schafer JL. Multiple imputation: a primer. Stat Methods Med Res 1999, 8:3-15.
28. Kumar CA, Srinivas S. Mining associations in health care data using formal concept analysis and singular value decomposition. J Biol Syst 2010, 18:787-807.
29. Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH. The WEKA data mining software: an update. SIGKDD Explor 2009, 11:10-18.
30. Kohavi R, John GH. Wrappers for feature subset selection. Artif Intell 1997, 97:273-324.
31. Pearl J. Heuristics: Intelligent Search Strategies for Computer Problem Solving 1984, Boston: Addison-Wesley Longman.
32. Stiell IG, Wells GA. Methodologic standards for the development of clinical decision rules in emergency medicine. Ann Emerg Med 1999, 33:437-447.
33. Huang J, Ling CX. Using AUC and accuracy in evaluating learning algorithms. IEEE Trans Knowl Data Eng 2005, 17:299-310.
34. Kohavi R. A study of cross-validation and bootstrap for accuracy estimation and model selection. Proceedings of the 14th International Joint Conference on Artificial Intelligence, Volume 2 1995, 1137-1143. San Francisco: Morgan Kaufmann; IJCAI (U S).
35. Witten IH, Frank E. Data Mining: Practical Machine Learning Tools and Techniques 2005, San Francisco: Morgan Kaufmann, 2.
36. Nadeau C, Bengio Y. Inference for the generalization error. Mach Learn 2003, 52:239-281.
37. Kerr WT, Lau EP, Owens GE, Trefler A. The future of medical diagnostics: large digitized databases. Yale J Biol Med 2012, 85:363-377.
38. Li L, Tang H, Wu Z, Gong J, Gruidl M, Zou J, Tockman M, Clark RA. Data mining techniques for cancer detection using serum proteomic profiling. Artif Intell Med 2004, 32:71-83.
39. Denekamp Y. Clinical decision support systems for addressing information needs of physicians. Isr Med Assoc J 2007, 9:771-776.
40. Kong L, Milbrandt EB, Weissfeld LA. Advances in statistical methodology and their application in critical care. Curr Opin Crit Care 2004, 10:391-394.
41. Moser SA, Jones WT, Brossette SE. Application of data mining to intensive care unit microbiologic data. Emerg Infect Dis 1999, 5:454-457.
42. Potts JA, Gibbons RV, Rothman AL, Srikiatkhachorn A, Thomas SJ, Supradish PO, Lemon SC, Libraty DH, Green S, Kalayanarooj S. Prediction of dengue disease severity among pediatric Thai patients using early clinical laboratory indicators. PLoS Negl Trop Dis 2010, 4:e769.
43. Dal Moro F, Abate A, Lanckriet GR, Arandjelovic G, Gasparella P, Bassi P, Mancini M, Pagano F. A novel approach for accurate prediction of spontaneous passage of ureteral stones: support vector machines. Kidney Int 2006, 69:157-160.
44. Anderson B, Hardin JM, Alexander DD, Grizzle WE, Meleth S, Manne U. Comparison of the predictive qualities of three prognostic models of colorectal cancer. Front Biosci (Elite Ed) 2010, 2:849-856.
45. Wang CJ, Li YQ, Wang L, Li LL, Guo YR, Zhang LY, Zhang MX, Bie RH. Development and evaluation of a simple and effective prediction approach for identifying those at high risk of dyslipidemia in rural adult residents. PLoS One 2012, 7:e43834.
46. Takayama T, Ebinuma H, Tada S, Yamagishi Y, Wakabayashi K, Ojiro K, Kanai T, Saito H, Hibi T, Keio Association for the Study of Liver Diseases Prediction of effect of pegylated interferon α-2b plus ribavirin combination therapy in patients with chronic hepatitis C infection. PLoS One 2011, 6:e27223. Keio Association for the Study of Liver Diseases.
47. Eller-Vainicher C, Chiodini I, Santi I, Massarotti M, Pietrogrande L, Cairoli E, Beck-Peccoz P, Longhi M, Galmarini V, Gandolini G, Bevilacqua M, Grossi E. Recognition of morphometric vertebral fractures by artificial neural networks: analysis from GISMO Lombardia Database. PLoS One 2011, 6:e27277.
48. Austin PC. A comparison of regression trees, logistic regression, generalized additive models, and multivariate adaptive regression splines for predicting AMI mortality. Stat Med 2007, 26:2937-2957.
49. Jonsdottir T, Hvannberg ET, Sigurdsson H, Sigurdsson S. The feasibility of constructing a Predictive Outcome Model for breast cancer using the tools of data mining. Expert Syst Appl 2008, 34:108-118.
50. Buri L, Hassan C, Bersani G, Anti M, Bianco MA, Cipolletta L, Di Giulio E, Di Matteo G, Familiari L, Ficano L, Loriga P, Morini S, Pietropaolo V, Zambelli A, Grossi E, Intraligi M, Buscema M, SIED Appropriateness Working Group Appropriateness guidelines and predictive rules to select patients for upper endoscopy: a nationwide multicenter study. Am J Gastroenterol 2010, 105:1327-1337. SIED Appropriateness Working Group.
51. Hosmer DW, Lemeshow S. Assessing the fit of the model. Applied Logistic Regression 2000, 143-202. New York: John Wiley & Sons, 2.