การวิเคราะห์อภิมานความถูกต้องของการวินิจฉัยการติดเชื้อไวรัสเด็งกี่โดยใช้คะแนนความเสี่ยงของการติดเชื้อไวรัสเด็งกี่
Article Sidebar
Main Article Content
Abstract
Abstract
Dengue virus infection it is a global health problem. It is also a major public health issue in Southeast Asia, including Thailand. Untreated patients with severe infection may cause death. The application of dengue scoring to predict or diagnose dengue infection severity based on patient characteristics and routine clinical profiles and laboratory medical examination. Current application of scoring to predict or diagnose severe dengue infection is use of clinical signs and laboratory results. To make it easier to distinguish dengue infections, this study sought systematic review and systematic review of the efficacy of scoring systems in predicting or diagnosing dengue infection. Published articles were searched from accessible database such as Pub med, Embase and Science Direct. The studies published in January, 2007 to present, written in English or Thai. The results of the research were consistent with the 5 selected criteria when the quality of the research was high. The QUADAS-2 tool has a minimum sample size of 84. Most studies were conducted in Asian countries. Pooled relative risk (RR) value for predicting or diagnosing dengue infection using dengue score was 0.910 (95 % CI: 0.678 to 1.221, p = 0.528). Dengue score was more effective for predicting the severity of the dengue than WHO guideline (p < 0.001) (Pooled OR; Random 0.843; 95 % CI: 0.285 to 0.497 times). This meta-analysis revealed that dengue risk score is more effective in distinguishing severity of dengue infection than the WHO guideline.
Keywords: dengue score; meta-analysis; systematic review
Article Details
References
[2] Bhatt, S., Gething, P.W., Brady, O.J., Messina, J.P., Farlow, A.W., Moyes, C.L., Drake, J.M., Brownstein, J.S., Hoen, A.G., Sankoh, O., Myers, M.F., George, D.B., Jaenisch, T., Wint, G.R., Simmons, C.P., Scott, T.W., Farrar, J.J. and Hay, S.I., 2013, The global distribution and burden of dengue, Nature 496: 504-507.
[3] ชิษณุ พันธุ์เจริญ, 2546, โรคไขเลือดออก, น. 215-238, ใน พรรณพิศ สุวรรณกูล, ธีระพงษ์ ตัณฑวิเชียร, ศศิธร ลิขิตนุกูล (บรรณาธิการ), Current Practice in Common Infectious Diseases, สวิชาญการพิมพ์, กรุงเทพฯ.
[4] Guzman, M.G. and Kouri, G., 2004, Dengue diagnosis, advances and challenges, J. Infect. Dis. 8: 69-80.
[5] Neeraja, M., Lakshmi, V., Teja, V.D., Umabala, P. and Subbalakshmi, M.V., 2006, Serodiagnosis of dengue virus infection in patients presenting to a tertiary care hospital, Ind. J. Med. Microbiol. 24: 280-282.
[6] Dewi, L.P. and Nurfitri, E., 2012, Pediatric logistic organ dysfunction score as a predictive tool of dengue shock syndrome outcomes, Paediatr. Indones. 52: 72-77.
[7] Carlos, C.C, Oishi, K., Cinco, M.T., Mapua, C.A., Inoue, S., Cruz, D.J., Pancho, M.A., Tanig, C.Z., Matias, R.R., Morita, K., Natividad, F.F., Igarashi, A. and Nagatake, T., 2005, Comparison of clinical features and hematologic abnormalities between dengue fever and dengue hemorrhagic fever among children in the Philippines, Am. J. Trop. Med. Hyg. 73: 435-440.
[8] Chambers, T.J., Hahn, C.S., Galler, R. and Rice, C.M., 1990, Flavivirus genome organization, expression, and replication, Ann. Rev. Microbiol. 10: 649-688.
[9] Phillips, M.L., 2008, Dengue reborn: Widespread resurgence of a resilient vector, Environ. Health Perspect. 116: 382-388.
[10] Martina, B.E., Koraka, P. and Osterhaus, A.D., 2009, Dengue virus pathogenesis: An integrated view, Clin. Microbiol. 22: 564-568.
[11] Cook, K.R., Murphy, T.D., Nguyen, T.C. and Karpen, G.H., 1997, Identification of trans-acting genes necessary for centromere function in Drosophila melanogaster using centromere-defective minichromosomes, J. Genet. 145: 737-747.
[12] Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G. and The PRISMA Group, 2009, Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement, PLoS. Med. 6: e1000097.
[13] Higgins, J.P.T. and Green, S., 2011, Cochrane Handbook for Systematic Reviews of Interventions, Version 5.1.0:6.4.1, The Cochrane Collaboration, Available Source: http://www.cochrane-handbook.org, October 10, 2017.
[14] The Cochrane Collaboration, 2014, Review Manager (RevMan) [Computer program] version 5.3. Copenhagen: The Nordic Cochrane Centre.
[15] Higgins, J.P.T, Thomson, S.G., Deeks, J.J. and Altman, D.G., 2003, Measuring inconsistency in meta-analyses, BMJ 327: 557-560.
[16] Cucunawangsih, Beti, E.D., Veli S., Nata, P., Hardjo, L., Bambang, S., Herdiman, T.P., Agus, S., Djoko, W., Sudarto, R., Modastri, K.S., Cicilia W. and Mirawati, S., 2015, Scoring model to predict dengue infection in the early phase of illness in primary health care centre, Arch. Clin. Microb. 6: 1-8.
[17] Chang, K., Lu, P. Chien, K.W., Tsai, J.J., Tsai, K.H., Chen, C.D., Chen, Y.H., Chen, T.C., Chen, H., Pan, C.Y. and Harn, M.R., 2009, Dengue fever scoring system: New strategy for the early detection of acute dengue virus infection in Taiwan, J. Formos. Med. Assoc. 108: 879-885.
[18] Lee, L.K., Liu, J.W., Chen, Y.H., Chen, Y.C, Tsai, C.Y, Huang SY, Lin, C.Y. and Huang, C.H., 2016, Development of a simple clinical risk score for early prediction of severe dengue in adult patients, PLoS ONE 11: e0154772.
[19] Pongpan, S., Wisitwong, A., Tawichasri, C. and Patumanond, J., 2013, Prognostic indicators for dengue infection severity, Int. J. Clin. Pediatr. 2: 12-18.
[20] Suhendro, S., Leonard, N., Robert, S., Bonita, E., Eppy, I., Maulana, S. and Tedjo, S., 2016, Dengue score: A proposed diagnostic predictor for pleural effusion and/or ascites in adults with dengue infection, BMC Infect. Dis. 16: 322.
[21] Higgins, J., Altman, D. and Sterne, J., 2009, Assessing risk of bias in included studies, In Higgins, J. and Green, S. (Eds.), Cochrane Handbook for Systematic Reviews of Interventions: The Cochrane Collaboration.
[22] Ioannidis, J.P.A. and Trikalinos, T.A., 2007, The appropriateness of asymmetry tests for publication bias in meta-analyses: A large survey, CMA. J. 176: 1091-1096.
[23] Whiting, P., Rutjes, A.W.S., Reitsma, J.B., Bossuyt, P.M.M. and Kleijnen, J., 2003, The development of QUADAS: A tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews, BMC Med. Res. Methodol. 3: 25.
[24] Horstick, O. and Ranzinger, S., 2015, Progress on the use of the WHO 2009 dengue case classification: a review, South East Asian J. Trop. Med. Public. Heal. 46: 49-54.
[25] Epelboin, L., Boulle, C., Ouar-Epelboin, S., Hanf, M., Dussart, P., Djossou, F., Nacher, M. and Carme, B., 2013, Discriminating malaria from dengue fever in endemic areas: Clinical and biological criteria, prognostic score and utility of the C-reactive protein: A retrospective matched-pair study in French Guiana, PLoS Negl. Trop. Dis. 7: 1-9.