A new approach to classify risk in dengue infection using bioelectrical impedance analysis
The study on risk classification was conducted on 183 hospitalized dengue patients (4 DF, 179 DHF). The severity of the risk criteria was determined based on three blood investigations, namely, platelet (PLT) count (less than or equal to 30 000 cells per mm 3), haematocrit (HCT) (increase by more th...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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2007
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| Online Access: | http://eprints.um.edu.my/9316/1/A_new_approach_to_classify_risk_in_dengue_infection.pdf |
| _version_ | 1825719686449332224 |
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| author | Ibrahim, F. Wan Abas, W.A.B. Taib, M.N. Guan, C.C. Sulaiman, S. |
| author_facet | Ibrahim, F. Wan Abas, W.A.B. Taib, M.N. Guan, C.C. Sulaiman, S. |
| author_sort | Ibrahim, F. |
| collection | UM |
| description | The study on risk classification was conducted on 183 hospitalized dengue patients (4 DF, 179 DHF). The severity of the risk criteria was determined based on three blood investigations, namely, platelet (PLT) count (less than or equal to 30 000 cells per mm 3), haematocrit (HCT) (increase by more than or equal to 20), and either aspartate aminotransferase (AST) level (raised by 5-fold the normal upper limit) or alanine aminotransferase (ALT) level (raised by 5-fold the normal upper limit). The patients were divided into three groups based on their risk factors and the corresponding bioelectrical impedance analysis (BIA) (i.e. bioelectrical tissue conductivity (BETC) parameters), namely, resistance (R), phase angle (α), body capacitance (BC) and capacitive reactance (X c) were obtained and quantified. Using logistic regression analysis, X c was found to be the best predictor in predicting the risk and severity in dengue patients. Subsequent two-way analysis of variance (ANOVA) found that there was a statistically significant relationship between the group categories and the change in X c. Hence, it was shown that BIA, as reflected by the X c value, can effectively segregate between the lower-risk (female mean X c = 60.70Ω, range 58.09Ω-63.43Ω; male mean X c = 62.17Ω, range 59.92Ω-64.46Ω) and the higher-risk dengue patients (female mean X c = 43.99Ω, range 42.05Ω-45.97Ω; male mean X c = 50.65Ω range 49.25Ω-52.09Ω, with the control data ((female mean X c =69.41Ω, range 67.09Ω-71.74Ω, and (male mean X c =64.19Ω, range 61.37Ω-67.15Ω. |
| first_indexed | 2024-03-06T05:23:32Z |
| format | Article |
| id | um.eprints-9316 |
| institution | Universiti Malaya |
| language | English |
| last_indexed | 2024-03-06T05:23:32Z |
| publishDate | 2007 |
| record_format | dspace |
| spelling | um.eprints-93162018-08-09T09:05:32Z http://eprints.um.edu.my/9316/ A new approach to classify risk in dengue infection using bioelectrical impedance analysis Ibrahim, F. Wan Abas, W.A.B. Taib, M.N. Guan, C.C. Sulaiman, S. T Technology (General) TA Engineering (General). Civil engineering (General) The study on risk classification was conducted on 183 hospitalized dengue patients (4 DF, 179 DHF). The severity of the risk criteria was determined based on three blood investigations, namely, platelet (PLT) count (less than or equal to 30 000 cells per mm 3), haematocrit (HCT) (increase by more than or equal to 20), and either aspartate aminotransferase (AST) level (raised by 5-fold the normal upper limit) or alanine aminotransferase (ALT) level (raised by 5-fold the normal upper limit). The patients were divided into three groups based on their risk factors and the corresponding bioelectrical impedance analysis (BIA) (i.e. bioelectrical tissue conductivity (BETC) parameters), namely, resistance (R), phase angle (α), body capacitance (BC) and capacitive reactance (X c) were obtained and quantified. Using logistic regression analysis, X c was found to be the best predictor in predicting the risk and severity in dengue patients. Subsequent two-way analysis of variance (ANOVA) found that there was a statistically significant relationship between the group categories and the change in X c. Hence, it was shown that BIA, as reflected by the X c value, can effectively segregate between the lower-risk (female mean X c = 60.70Ω, range 58.09Ω-63.43Ω; male mean X c = 62.17Ω, range 59.92Ω-64.46Ω) and the higher-risk dengue patients (female mean X c = 43.99Ω, range 42.05Ω-45.97Ω; male mean X c = 50.65Ω range 49.25Ω-52.09Ω, with the control data ((female mean X c =69.41Ω, range 67.09Ω-71.74Ω, and (male mean X c =64.19Ω, range 61.37Ω-67.15Ω. 2007 Article PeerReviewed application/pdf en http://eprints.um.edu.my/9316/1/A_new_approach_to_classify_risk_in_dengue_infection.pdf Ibrahim, F. and Wan Abas, W.A.B. and Taib, M.N. and Guan, C.C. and Sulaiman, S. (2007) A new approach to classify risk in dengue infection using bioelectrical impedance analysis. Dengue Bulletin, 31. pp. 58-74. ISSN 1020895X, http://www.scopus.com/inward/record.url?eid=2-s2.0-56249101356&partnerID=40&md5=d8f68d7d7ad558201bf706bc772a8104 209.61.208.233/LinkFiles/DengueBulletinsc7vol31.pdf http://repository.searo.who.int/handle/123456789/16073 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) Ibrahim, F. Wan Abas, W.A.B. Taib, M.N. Guan, C.C. Sulaiman, S. A new approach to classify risk in dengue infection using bioelectrical impedance analysis |
| title | A new approach to classify risk in dengue infection using bioelectrical impedance analysis |
| title_full | A new approach to classify risk in dengue infection using bioelectrical impedance analysis |
| title_fullStr | A new approach to classify risk in dengue infection using bioelectrical impedance analysis |
| title_full_unstemmed | A new approach to classify risk in dengue infection using bioelectrical impedance analysis |
| title_short | A new approach to classify risk in dengue infection using bioelectrical impedance analysis |
| title_sort | new approach to classify risk in dengue infection using bioelectrical impedance analysis |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) |
| url | http://eprints.um.edu.my/9316/1/A_new_approach_to_classify_risk_in_dengue_infection.pdf |
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