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.
CONCLUSION: The findings suggest that LAMP is more sensitive than traditional tests used at facilities, but the utility of detecting and treating these low-density infections is not well understood. Due to the limited number of studies with bias in their methodological quality, variation in the study design, and different types of reference tests further research is likely to change the estimate. Well-conceived large prospective studies with blinding of the index test results are recommenced.
METHODS: Diabetes data were derived from the Malaysian National Health and Morbidity Surveys conducted in 2006, 2011 and 2015. The air pollution data (NOx, NO2, SO2, O3 and PM10) were obtained from the Department of Environment Malaysia. Using multiple logistic and linear regression models, the association between long-term exposure to these pollutants and prevalence of diabetes among Malaysian adults was evaluated.
RESULTS: The PM10 concentration decreased from 2006 to 2014, followed by an increase in 2015. Levels of NOx decreased while O3 increased annually. The air pollutant levels based on individual modelled air pollution exposure as measured by the nearest monitoring station were higher than the annual averages of the five pollutants present in the ambient air. The prevalence of overall diabetes increased from 11.4% in 2006 to 21.2% in 2015. The prevalence of known diabetes, underdiagnosed diabetes, overweight and obesity also increased over these years. There were significant positive effect estimates of known diabetes at 1.125 (95% CI, 1.042, 1.213) for PM10, 1.553 (95% CI, 1.328, 1.816) for O3, 1.271 (95% CI, 1.088, 1.486) for SO2, 1.124 (95% CI, 1.048, 1.207) for NO2, and 1.087 (95% CI, 1.024, 1.153) for NOx for NHMS 2006. The adjusted annual average levels of PM10 [1.187 (95% CI, 1.088, 1.294)], O3 [1.701 (95% CI, 1.387, 2.086)], NO2 [1.120 (95% CI, 1.026, 1.222)] and NOx [1.110 (95% CI, 1.028, 1.199)] increased significantly from NHMS 2006 to NHMS 2011 for overall diabetes. This was followed by a significant decreasing trend from NHMS 2011 to 2015 [0.911 for NO2, and 0.910 for NOx].
CONCLUSION: The findings of this study suggest that long-term exposure to O3 is an important associated factor of underdiagnosed DM risk in Malaysia. PM10, NO2 and NOx may have mixed effect estimates towards the risk of DM, and their roles should be further investigated with other interaction models. Policy and intervention measures should be taken to reduce air pollution in Malaysia.