| Literature DB >> 18834523 |
Tarekegn A Abeku1, Mojca Kristan, Caroline Jones, James Beard, Dirk H Mueller, Michael Okia, Beth Rapuoda, Brian Greenwood, Jonathan Cox.
Abstract
BACKGROUND: The accuracy of malaria diagnosis has received renewed interest in recent years due to changes in treatment policies in favour of relatively high-cost artemisinin-based combination therapies. The use of rapid diagnostic tests (RDTs) based on histidine-rich protein 2 (HRP2) synthesized by Plasmodium falciparum has been widely advocated to save costs and to minimize inappropriate treatment of non-malarial febrile illnesses. HRP2-based RDTs are highly sensitive and stable; however, their specificity is a cause for concern, particularly in areas of intense malaria transmission due to persistence of HRP2 antigens from previous infections.Entities:
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Year: 2008 PMID: 18834523 PMCID: PMC2571107 DOI: 10.1186/1475-2875-7-202
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Altitude, annual climate, malaria incidence rates (estimated from the number of RDT-positive cases who were residents of the locality where each health centre is located and using the population of the locality as denominator) and RDT positivity rates at the four sentinel sites in Uganda and Kenya*.
| Site | Altitude | Average temperature | Average annual rainfall | Malaria incidence rates | Overall RDT positivity rate |
| Bufundi, Uganda | 2291 | 16.1 | 884 | 15.6 | 5.8 |
| Kilibwoni, Kenya | 2065 | 17.0 | 1,424 | 43.2 | 7.9 |
| Sengera, Kenya | 1816 | 18.9 | 1,709 | 3.4 | 42.2 |
| Kebisoni, Uganda | 1670 | 20.1 | 1,007 | 359.8 | 52.3 |
*Patients who had a travel history in the two weeks before the tests were done were excluded from the data presented in the table.
Figure 1RDT positivity rates at four sentinel sites in Uganda and Kenya, October 2002 – September 2006, by gender and age group (key: dark and grey bars represent males and females, respectively).
Figure 2Longitudinal variations in number tested (grey bars), RDT positive cases (solid line) and the corresponding RDT positivity rates (dashed line) at four sites in Kenya and Uganda between November 2002 and August 2006. Patients with a travel history in the previous two weeks before presentation were excluded. All patients clinically diagnosed as malaria cases were subsequently tested with RDTs, except in Kilibwoni between January 2003 and February 2004 when approximately 50% were tested.
Figure 3Sensitivity, specificity, PPV and NPV of RDTs compared to microscopy in Kebisoni (mesoendemic area) and Kilibwoni (hypoendemic area). Error bars indicate 95% confidence intervals.
Figure 4Sensitivity and specificity of RDTs as a function of the true parasite rate (as determined by microscopy) at Kebisoni, Rukungiri District, Uganda, by (a) month and (b) age groups (error bars indicate 95% confidence intervals).
Figure 5Differences in parasite densities between false negative and true positive RDT results compared to microscopy at Kebisoni, Uganda.
Outputs of the best-fitting logistic regression model for factors associated with the probability of obtaining true negative HRP2-based RDT test results at Kebisoni, Uganda.
| Factors | Odds ratio | Standard error | |
| Area (Kebisoni relative to baseline = Kilibwoni) | 0.002 | 0.002 | < 0.0001 |
| Age (years) | 1.017 | 0.005 | 0.002 |
| Presence of fever at the time of presentation (relative to baseline = absence of fever at the time of presentation) | 0.275 | 0.073 | < 0.0001 |
| January (relative to baseline = December)* | 1.173 | 0.367 | 0.609 |
| February (relative to baseline = December)* | 1.414 | 0.458 | 0.285 |
| March (relative to baseline = December)* | 2.623 | 1.026 | 0.014 |
Previous intake of antimalarials, a clinic visit in the previous two weeks, travel outside the district in the previous two weeks and sex were not significantly associated with the dependent variable.
* Significance of the combined effect of months: Chi-squared at 3 degrees of freedom = 8.57, p = 0.0356.