METHOD: This is a retrospective cohort study of confirmed severe dengue patients that were admitted in 2014 to Hospital Kuala Lumpur. Data on baseline characteristics, clinical parameters, and laboratory findings at diagnosis of severe dengue were collected. The outcome of interest is death among patients diagnosed with severe dengue.
RESULTS: There were 199 patients with severe dengue included in the study. Multivariate analysis found lethargy, OR 3.84 (95% CI 1.23-12.03); bleeding, OR 8.88 (95% CI 2.91-27.15); pulse rate, OR 1.04 (95% CI 1.01-1.07); serum bicarbonate, OR 0.79 (95% CI 0.70-0.89) and serum lactate OR 1.27 (95% CI 1.09-1.47), to be statistically significant predictors of death. The regression equation to our model with the highest AUROC, 83.5 (95% CI 72.4-94.6), is: Log odds of death amongst severe dengue cases = - 1.021 - 0.220(Serum bicarbonate) + 0.001(ALT) + 0.067(Age) - 0.190(Gender).
CONCLUSION: This study showed that a large proportion of severe dengue occurred early, whilst patients were still febrile. The best prediction model to predict death at recognition of severe dengue is a model that incorporates serum bicarbonate and ALT levels.
METHODS: Using Singapore Malaysia Hospital-Based Breast Cancer Registry, clinical information was retrieved from 7064 stage I to III breast cancer patients who were diagnosed between 1990 and 2011 and underwent surgery. Predicted and observed probabilities of positive nodes and survival were compared for each subgroup. Calibration was assessed by plotting observed value against predicted value for each decile of the predicted value. Discrimination was evaluated by area under a receiver operating characteristic curve (AUC) with 95 % confidence interval (CI).
RESULTS: The median predicted probability of positive lymph nodes is 40.6 % which was lower than the observed 43.6 % (95 % CI, 42.5 %-44.8 %). The calibration plot showed underestimation for most of the groups. The AUC was 0.71 (95 % CI, 0.70-0.72). Cancermath predicted and observed overall survival probabilities were 87.3 % vs 83.4 % at 5 years after diagnosis and 75.3 % vs 70.4 % at 10 years after diagnosis. The difference was smaller for patients from Singapore, patients diagnosed more recently and patients with favorable tumor characteristics. Calibration plot also illustrated overprediction of survival for patients with poor prognosis. The AUC for 5-year and 10-year overall survival was 0.77 (95 % CI: 0.75-0.79) and 0.74 (95 % CI: 0.71-0.76).
CONCLUSIONS: The discrimination and calibration of CancerMath were modest. The results suggest that clinical application of CancerMath should be limited to patients with better prognostic profile.
METHODS: Healthy participants consumed pure forms of a non-nutritive sweetener (NNS) mixed with water that were standardized to doses of 14% (0.425 g) of the acceptable daily intake (ADI) for aspartame and 20% (0.136 g) of the ADI for sucralose every day for two weeks. Blood samples were collected and analysed for glucose, insulin, active glucagon-like peptide-1 (GLP-1), and leptin.
RESULTS: Seventeen participants (10 females and 7 males; age 24 ± 6.8 years; BMI 22.9 ± 2.5 kg/m2) participated in the study. The total area under the curve (AUC) values of glucose, insulin, active GLP-1 and leptin were similar for the aspartame and sucralose treatment groups compared to the baseline values in healthy participants. There was no change in insulin sensitivity after NNS treatment compared to the baseline values.
CONCLUSIONS: These findings suggest that daily repeated consumption of pure sucralose or aspartame for 2 weeks had no effect on glucose metabolism among normoglycaemic adults. However, these results need to be tested in studies with longer durations. Novelty: • Daily consumption of pure aspartame or sucralose for 2 weeks had no effect on glucose metabolism. • Daily consumption of pure aspartame or sucralose for 2 weeks had no effect on insulin sensitivity among healthy adults.
DESIGN: Cross-sectional study.
SETTING: Probability proportionate to size was used to randomly select two schools in Selangor state, Malaysia.
PARTICIPANTS: A total of 513 adolescents (58.9% women and 41.1% men) aged 12-16 years were recruited.
PRIMARY AND SECONDARY OUTCOME MEASURES: Weight, height, WC and BP of the adolescents were measured. The predictive power of anthropometric indices was analysed by sex using the receiver operating characteristic curve.
RESULTS: BMI and WHtR were the indices with higher areas under the curve (AUCs), yet the optimal cut-offs to predict high BP using the 95th percentile were higher than the threshold for overweight/obesity. Most indices showed poor sensitivity under the suggested cut-offs. In contrast, the optimal BMI and WHtR cut-offs to predict high BP using the 90th percentile were lower (men: BMI-for-age=0.79, WHtR=0.46; women: BMI-for-age=0.92, WHtR=0.45). BMI showed the highest AUC in both sexes but had poor sensitivity among women. WHtR presented good sensitivity and specificity in both sexes.
CONCLUSIONS: These findings suggested that WHtR might be a useful indicator for screening high blood pressure risk in the routine primary-level health services for adolescents. Future studies are warranted to involve a larger sample size to confirm these findings.
METHODS: Drug formulations were administered to the experimental animals via oral, intravenous and intraperitoneal routes. Blood samples were collected at different pre-determined time intervals to determine the pharmacokinetic parameters. To understand the biodistribution profile of HCZ, tissue samples were isolated from different groups of Sprague-Dawley rats at different time points. The pharmacokinetic parameters of HZC were evaluated after administration through oral (100 mg/kg), intraperitoneal (100 mg/kg) and intravenous (10 mg/kg) routes.
RESULTS: Significantly (p
METHODS: Subjects were recruited among those responding to a social media announcement or patients attending the SEGi Oral Health Care Centre between May and December 2019, and among some staff at the centre. Five ml of unstimulated whole saliva was collected and salivary LDH enzyme activity levels were measured with a LDH colorimetric assay kit. Salivary LDH activity level was determined for each group and compared statistically.
RESULTS: Eighty-eight subjects were categorized into three groups (control n=30, smokers n=29, and vapers n=29). The mean ± standard deviation (SD) values for salivary LDH activity levels for vapers, smokers, and control groups were 35.15 ± 24.34 mU/ml, 30.82 ± 20.73 mU/ml, and 21.45 ± 15.30 mU/ml, respectively. The salivary LDH activity levels of smoker and vaper groups were significantly higher than in the control group (p = 0.031; 0.017). There was no significant difference of salivary LDH activity level in vapers when compared with smokers (p= 0.234).
CONCLUSION: Our findings showed higher LDH levels in the saliva of vapers when compared with controls, confirming cytotoxic and harmful effects of e-cigarettes on the oral mucosa.
Methods: This cross-sectional study, which was carried out at the Paediatric Intensive Care Unit of Hospital Universiti Sains Malaysia (HUSM) in Kelantan, Malaysia, had involved 60 neonates admitted for suspected sepsis. Sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV) and the area under receiver operating characteristics curve (AUC) for PCT were determined at initial presentation (0 h) as well as 12 h and 24 h after presentation in comparison to blood culture as the gold standard.
Results: The study consisted of 27 (45.0%) male and 33 (55.0%) female neonates with a mean (SD) age of 76.8 (48.25) h. At cut-off PCT value of > 2 ng/mL, the sensitivity, specificity, PPV and NPV were 66.7%, 66.7%, 33.3% and 88.9% at 0 h. The respective parameters were 83.3%. 56.3%, 32.3% and 93.1% at 12 h and 83.3%, 52.1%, 30.3% and 92.6% at 24 h. AUC was 71.6%, 76.6% and 71.7% at 0 h, 12 h and 24 h.
Conclusions: Diagnostic performance and discrimination values of PCT for diagnosis of neonatal sepsis varied with time of obtaining the blood samples. The PCT result at 12 h demonstrates the most optimal diagnostic performance and discrimination values.
Methods: One hundred and fifty hard-working agricultural farmers from high-prevalence area for CKDu (Madawachchiya) were screened three times for proteinuria; 66 proteinuric and 21 non-proteinuric were identified as the baseline classification. Selected individuals were analysed further for creatinine, protein and cystatin C in urine and creatinine, cystatin C in serum. Urine protein-to-creatinine ratio (UP/UC) was calculated.
Results: Based on creatinine and cystatin C cut-off levels in serum, individuals were classified as high or normal. Diagnosis of two functional markers (creatinine and cystatin C) were evaluated using receiver operating characteristic (ROC) curve and in terms of sensitivity and specificity using UP/UC as the baseline. Creatinine and cystatin C-based eGFR (estimated Glomerular filtration rate) levels were calculated, and Pearson's correlation coefficient was determined between different eGFR measurements using UP/UC. Mean (SD) UP/UC ratio, serum creatinine, and serum cystatin C levels of the proteinuric subjects were 129.0 (18.4) mg/mmol, 1.35 (0.39) mg/dL, 1.69 (0.58) mg/L. For non-proteniuric individuals, the results were found to be 14.4 (2.28), 1.22 (0.40) mg/dL, 0.82 (0.25) mg/L. The ROC analysis showed excellent accuracy in using cystatin C for identifying proteinuric patients than creatinine area under the curve (AUC): 0.9675, P < 0.001). Cut-off points were identified as 1.015 mg/dL for serum creatinine and 0.930mg/L for cystatin C. Furthermore, cystatin C based Hoek formula showed the better correlation (0.635, P < 0.001) with UP/UC compared with creatinine based modification of diet in renal disease (MDRD) formula.
Conclusion: The study showed elevated serum cystatin C in patients with persisting proteinuria compared with non-responding serum creatinine. Moreover, cystatin C-based eGFR equations were more accurate to determine the kidney function than serum creatinine in proteinuric patients who are vulnerable for CKDu in high-prevalence areas.