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X Demographics
Mendeley readers
| Title |
Differentiating between dengue fever and malaria using hematological parameters in endemic areas of Thailand
|
|---|---|
| Published in |
Infectious Diseases of Poverty, March 2017
|
| DOI | 10.1186/s40249-017-0238-x |
| Pubmed ID | |
| Authors |
Manas Kotepui, Bhukdee PhunPhuech, Nuoil Phiwklam, Kwuntida Uthaisar |
| Abstract |
Dengue fever (DF) and malaria are the two major public health concerns in tropical countries such as Thailand. Early differentiation between dengue and malaria could help clinicians to identify patients who should be closely monitored for signs of dengue hemorrhagic fever or severe malaria. This study aims to build knowledge on diagnostic markers that are used to discriminate between the infections, which frequently occur in malaria-endemic areas, such as the ones in Thailand. A retrospective study was conducted in Phop Phra Hospital, a hospital located in the Thailand-Burma border area, a malaria-endemic area, between 2013 and 2015. In brief, data on 336 patients infected with malaria were compared to data on 347 patients infected with DF. White blood cells, neutrophil, monocyte, eosinophil, neutrophil-lymphocyte ratio, and monocyte-lymphocyte ratio were significantly lower in patients with DF compared to patients with malaria (P < 0.0001). In contrast, red blood cells, hemoglobin, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration were significantly higher in patients with DF as compared to patients with malaria (P < 0.0001). A decision tree model revealed that using neutrophils, lymphocyte, MCHC, and gender was guided to discriminate between dengue and malaria infection. This study concluded that several hematological parameters were different for diagnosing DF and malaria. A decision tree model revealed that using neutrophils, lymphocyte, MCHC, and gender was guided to discriminate patients with dengue and malaria infection. In addition, using these markers will thus lead to early detection, diagnosis, and prompt treatment of these tropical diseases. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
| Members of the public | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 123 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 21 | 17% |
| Student > Bachelor | 17 | 14% |
| Researcher | 16 | 13% |
| Student > Ph. D. Student | 7 | 6% |
| Student > Doctoral Student | 7 | 6% |
| Other | 21 | 17% |
| Unknown | 34 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 36 | 29% |
| Biochemistry, Genetics and Molecular Biology | 13 | 11% |
| Immunology and Microbiology | 9 | 7% |
| Nursing and Health Professions | 6 | 5% |
| Social Sciences | 5 | 4% |
| Other | 17 | 14% |
| Unknown | 37 | 30% |