MATERIAL AND METHODS: A total of 300 elderly Malay participants (age ≥ 65 years) with CKD, attending the Hospital University Sains Malaysia were included in the study. Demographic data and history were also recorded. Serum creatinine was assayed by Chemistry Analyzer Model Architect-C8000 (Jaffe method). While serum cystatin C was examined by Human cystatin C ELISA kit (Sigma-Aldrich) using Thermo Scientific Varioskan Flash ELISA reader.
RESULTS: Out of 300 study participants, 169 (56.3%) were females. Mean age of patients was 67.6 ± 6.7 years. 64 male (64.6%) and 35 female (35.4%) patients were between 70 and 79 years. When estimated by MDRD equation, the prevalence of CKD stage 3 (defined as eGFR = 30 - 59 mL/min/1.73m2) was 27.7%, while based on CKD-EPIcr, CKD-EPIcys, and CKD-EPIcr-cys equations, it was 28%, 36.3%, and 36.3%, respectively. The prevalence of CKD stage 4 (defined as eGFR = 15 - 29 mL/min/1.73m2) when estimated by MDRD was 37.6%, whereas based on CKD-EPIcr, CKD-EPIcys, and CKD-EPIcr-cys equations, it was 36.3%, 46.4%, and 46.4%, respectively. CKD stage 5 (defined as eGFR < 15 mL/min/1.73m2) when estimated by the MDRD equation was 34.7%. While based on CKD-EPIcr, CKD-EPIcys, and CKD-EPIcr-cys equations, the prevalence of CKD stage 5 was 35.7%, 17.3%, and 17.3%, respectively.
CONCLUSION: The staging of CKD is different between the creatinine- and cystatin C-based equations. Creatinine-based equations classify patients as having CKD stage 5 twice as often as cystatin C-based equations.
METHODS: This retrospective study involved consecutive hospitalized patients with non-structural protein 1 (NS1) antigen positivity during an outbreak (Jan to April 2014). Multiplex RT-PCR was performed directly on NS1 positive serum samples to detect and determine the DENV serotypes. All PCR-positive serum samples were inoculated onto C6/36 cells. Multiplex PCR was repeated on the supernatant of the first blind passage of the serum-infected cells. Random samples of supernatant from the first passage of C6/36 infected cells were subjected to whole genome sequencing. Clinical and laboratory variables were compared between patients with and without DENV co-infections.
RESULTS: Of the 290 NS1 positive serum samples, 280 were PCR positive for DENV. Medical notes of 262 patients were available for analysis. All 4 DENV serotypes were identified. Of the 262 patients, forty patients (15.3 %) had DENV co-infections: DENV-1/DENV-2(85 %), DENV-1/DENV-3 (12.5 %) and DENV-2/DENV-3 (2.5 %). Another 222 patients (84.7 %) were infected with single DENV serotype (mono-infection), with DENV- 1 (76.6 %) and DENV- 2 (19.8 %) predominating. Secondary dengue infections occurred in 31.3 % patients. Whole genome sequences of random samples representing DENV-1 and DENV-2 showed heterogeneity amongst the DENVs. Multivariate analysis revealed that pleural effusion and the presence of warning signs were significantly higher in the co-infected group, both in the overall and subgroup analysis. Diarrhoea was negatively associated with co-infection. Additionally, DENV-2 co-infected patients had higher frequency of patients with severe thrombocytopenia (platelet count < 50,000/mm(3)), whereas DENV-2 mono-infections presented more commonly with myalgia. Elevated creatinine levels were more frequent amongst the co-infected patients in univariate analysis. Haemoconcentration and haemorrhagic manifestations were not higher amongst the co-infected patients. Serotypes associated with severe dengue were: DENV-1 (n = 9), DENV-2 (n = 1), DENV-3 (n = 1) in mono-infected patients and DENV-1/DENV-2 (n = 5) and DENV-1/DENV-3 (n = 1) amongst the co-infected patients.
CONCLUSION: DENV co-infections are not uncommon in a hyperendemic region and co-infected patients are skewed towards more severe clinical manifestations compared to mono-infected patients.