METHODS: A total of 760 voluntary donors who attended the Blood Bank, Penang Hospital or offsite blood donation campaigns from April to May 2014 were recruited. The ABO and RhD blood groups were determined by the conventional tile method and the solid phase method, in which the tube method was used as the gold standard.

RESULTS: For ABO blood grouping, the tile method has shown 100% concordance results with the gold standard tube method, whereas the solid-phase method only showed concordance result for 754/760 samples (99.2%). Therefore, for ABO grouping, tile method has 100% sensitivity and specificity while the solid phase method has slightly lower sensitivity of 97.7% but both with good specificity of 100%. For RhD grouping, both the tile and solid phase methods have grouped one RhD positive specimen as negative each, thus giving the sensitivity and specificity of 99.9% and 100% for both methods respectively.

METHODS: The study was divided into two phases: (I) Marker discovery by miRNA microarray using paired cancer tissues (n = 30) and blood samples (CRC, n = 42; control, n = 18). (II) Marker validation by stem-loop reverse transcription real time PCR using an independent set of paired cancer tissues (n = 30) and blood samples (CRC, n = 70; control, n = 32). Correlation analysis was determined by Pearson's test. Logistic regression and receiver operating characteristics curve analyses were applied to obtain diagnostic utility of the miRNAs.

RESULTS: Seven miRNAs (miR-150, miR-193a-3p, miR-23a, miR-23b, miR-338-5p, miR-342-3p and miR-483-3p) have been found to be differentially expressed in both tissue and blood samples. Significant positive correlations were observed in the tissue and blood levels of miR-193a-3p, miR-23a and miR-338-5p. Moreover, increased expressions of these miRNAs were detected in the more advanced stages. MiR-193a-3p, miR-23a and miR-338-5p were demonstrated as a classifier for CRC detection, yielding a receiver operating characteristic curve area of 0.887 (80.0% sensitivity, 84.4% specificity and 83.3% accuracy).

METHODS: This was a meta-analysis of diagnostic accuracy. Relevant studies that assessed the diagnostic performance of LAMP for the detection of malaria in pregnancy were searched in health-related electronic databases including PubMed, Ovid, and Google Scholar. The methodological quality of the studies included was evaluated using the QUADAS-2 tool.

RESULTS: Of the 372 studies identified, eight studies involving 2999 pregnant women in five endemic countries that assessed the accuracy of LAMP were identified. With three types of PCR as reference tests, the pooled sensitivity of LAMP was 91% (95%CI 67-98%) and pooled specificity was 99% (95%CI 83-100%, 4 studies), and the negative likelihood ratio was 9% (2-40%). Caution is needed in the interpretation as there was substantial between-study heterogeneity (I2: 80%), and a low probability that a person without infection is tested negative. With microscopy as a reference, the pooled sensitivity of LAMP was 95% (95%CI 26-100%) and pooled specificity was 100% (95%CI 94-100%, 4 studies). There was a wide range of sensitivity and substantial between-study heterogeneity (I2: 83.5-98.4%). To investigate the source of heterogeneity, a meta-regression analysis was performed with covariates. Of these potential confounding factors, reference test (p: 0.03) and study design (p:0.03) had affected the diagnostic accuracy of LAMP in malaria in pregnancy. Overall, there was a low certainty of the evidence in accuracy estimates.