METHODOLOGY/PRINCIPAL FINDINGS: Photos of urine samples were taken in a customized photo booth, then processed using Adobe Photoshop to index urine colour into the red, green, and blue (RGB) colour space and assigned a unique RGB value. The RGB values were then correlated with patients' clinical and laboratory hydration indices using Pearson's correlation and multiple linear regression. There were strong correlations between urine osmolality and the RGB of urine colour, with r = -0.701 (red), r = -0.741 (green), and r = -0.761 (blue) (all p-value <0.05). There were strong correlations between urine specific gravity and the RGB of urine colour, with r = -0.759 (red), r = -0.785 (green), and r = -0.820 (blue) (all p-value <0.05). The blue component had the highest correlations with urine specific gravity and urine osmolality. There were moderate correlations between RGB components and serum urea, at r = -0.338 (red), -0.329 (green), -0.360 (blue). In terms of urine biochemical parameters linked to dehydration, multiple linear regression studies showed that the green colourimetry code was predictive of urine osmolality (β coefficient -0.082, p-value <0.001) while the blue colourimetry code was predictive of urine specific gravity (β coefficient -2,946.255, p-value 0.007).
CONCLUSIONS/SIGNIFICANCE: Urine colourimetry using mobile phones was highly correlated with the hydration status of dengue patients, making it a potentially useful hydration status tool.
METHODS: The mid-stream urine was collected from 96 patients diagnosed with dengue fever at Penang General Hospital (PGH) and 50 healthy volunteers. Urine samples were analyzed with proton nuclear magnetic resonance (1H NMR) spectroscopy, followed by chemometric multivariate analysis. NMR signals highlighted in the orthogonal partial least square-discriminant analysis (OPLS-DA) S-plots were selected and identified using Human Metabolome Database (HMDB) and Chenomx Profiler. A highly predictive model was constructed from urine profile of dengue infected patients versus healthy individuals with the total R2Y (cum) value 0.935, and the total Q2Y (cum) value 0.832.
RESULTS: Data showed that dengue infection is related to amino acid metabolism, tricarboxylic acid intermediates cycle and β-oxidation of fatty acids. Distinct variations in certain metabolites were recorded in infected patients including amino acids, various organic acids, betaine, valerylglycine, myo-inositol and glycine.
CONCLUSION: Metabolomics approach provides essential insight into host metabolic disturbances following dengue infection.
CASE PRESENTATION: A 59-year old man staying near the Belum-Temengor rainforest at the Malaysia-Thailand border was admitted with fever for 6 days, with respiratory distress. His non-structural protein 1 antigen and Anti-DENV Immunoglobulin M tests were positive. He was treated for severe dengue with compensated shock. Treating the dengue had so distracted the clinicians that a blood film for the malaria parasite was not done. Despite aggressive supportive treatment in the intensive care unit (ICU), the patient had unresolved acidosis as well as multi-organ failure involving respiratory, renal, liver, and haematological systems. It was due to the presentation of shivering in the ICU, that a blood film was done on the second day that revealed the presence of P. knowlesi with a parasite count of 520,000/μL. The patient was subsequently treated with artesunate-doxycycline and made a good recovery after nine days in ICU.
CONCLUSIONS: This case contributes to the body of literature on co-infection between DENV and P. knowlesi and highlights the clinical consequences, which can be severe. Awareness should be raised among health-care workers on the possibility of dengue-malaria co-infection in this region. Further research is required to determine the real incidence and risk of co-infection in order to improve the management of acute febrile illness.