14 research outputs found
Development of a target product profile for a point-of-care cardiometabolic device
INTRODUCTION: Multi-parameter diagnostic devices can simplify cardiometabolic disease diagnosis. However, existing devices may not be suitable for use in low-resource settings, where the burden of non-communicable diseases is high. Here we describe the development of a target product profile (TPP) for a point-of-care multi-parameter device for detection of biomarkers for cardiovascular disease and metabolic disorders, including diabetes, in primary care settings in low- and middle-income countries (LMICs). METHODS: A draft TPP developed by an expert group was reviewed through an online survey and semi-structured expert interviews to identify device characteristics requiring refinement. The draft TPP included 41 characteristics with minimal and optimal requirements; characteristics with an agreement level for either requirement of ≤ 85% in either the survey or among interviewees were further discussed by the expert group and amended as appropriate. RESULTS: Twenty people responded to the online survey and 18 experts participated in the interviews. Twenty-two characteristics had an agreement level of ≤ 85% in either the online survey or interviews. The final TPP defines the device as intended to be used for basic diagnosis and management of cardiometabolic disorders (lipids, glucose, HbA1c, and creatinine) as minimal requirement, and offering an expanded test menu for wider cardiometabolic disease management as optimal requirement. To be suitable, the device should be intended for level 1 healthcare settings or lower, used by minimally trained healthcare workers and allow testing using self-contained cartridges or strips without the need for additional reagents. Throughput should be one sample at a time in a single or multi-analyte cartridge, or optimally enable testing of several samples and analytes in parallel with random access. CONCLUSION: This TPP will inform developers of cardiometabolic multi-parameter devices for LMIC settings, and will support decision makers in the evaluation of existing and future devices
Validation of Two Rapid Diagnostic Tests for Visceral Leishmaniasis in Kenya
BACKGROUND: Visceral leishmaniasis (VL) is a systemic parasitic disease that is fatal unless treated. In Kenya, national VL guidelines rely on microscopic examination of spleen aspirate to confirm diagnosis. As this procedure is invasive, it cannot be safely implemented in peripheral health structures, where non-invasive, accurate, easy to use diagnostic tests are needed. METHODOLOGY: We evaluated the sensitivity, specificity and predictive values of two rapid diagnostic tests (RDT), DiaMed IT LEISH and Signal-KA, among consecutive patients with clinical suspicion of VL in two treatment centres located in Baringo and North Pokot District, Rift Valley province, Kenya. Microscopic examination of spleen aspirate was the reference diagnostic standard. Patients were prospectively recruited between May 2010 and July 2011. PRINCIPAL FINDINGS: Of 251 eligible patients, 219 patients were analyzed, including 131 VL and 88 non-VL patients. The median age of VL patients was 16 years with predominance of males (66%). None of the tested VL patients were co-infected with HIV. Sensitivity and specificity of the DiaMed IT LEISH were 89.3% (95%CI: 82.7-94%) and 89.8% (95%CI: 81.5-95.2%), respectively. The Signal KA showed trends towards lower sensitivity (77.1%; 95%CI: 68.9-84%) and higher specificity (95.5%; 95%CI: 88.7-98.7%). Combining the tests did not improve the overall diagnostic performance, as all patients with a positive Signal KA were also positive with the DiaMed IT LEISH. CONCLUSION/SIGNIFICANCE: The DiaMed IT LEISH can be used to diagnose VL in Kenyan peripheral health facilities where microscopic examination of spleen aspirate or sophisticated serological techniques are not feasible. There is a crucial need for an improved RDT for VL diagnosis in East Africa
Field suitability and diagnostic accuracy of the Biocentric® open real-time PCR platform for plasma-based HIV viral load quantification in Swaziland
Abstract Background Viral load (VL) testing is being scaled up in resource-limited settings. However, not all commercially available VL testing methods have been evaluated under field conditions. This study is one of a few to evaluate the Biocentric platform for VL quantification in routine practice in Sub-Saharan Africa. Methods Venous blood specimens were obtained from patients eligible for VL testing at two health facilities in Swaziland from October 2016 to March 2017. Samples were centrifuged at two laboratories (LAB-1, LAB-2) to obtain paired plasma specimens for VL quantification with the national reference method and on the Biocentric platform. Agreement (correlation, Bland–Altman) and accuracy (sensitivity, specificity) indicators were calculated at the VL thresholds of 416 (2.62 log10) and 1000 (3.0 log10) copies/mL. Leftover samples from patients with discordant VL results were re-quantified and accuracy indicators recalculated. Logistic regression was used to compare laboratory performance. Results A total of 364 paired plasma samples (LAB-1: n = 198; LAB-2: n = 166) were successfully tested using both methods. The correlation was high (R = 0.82, p < 0.01), and the Bland–Altman analysis showed a minimal mean difference (− 0.03 log10 copies/mL; 95% CI: -1.15 to 1.08). At the clinical threshold level of 3.0 log10 copies/mL, the sensitivity was 88.6% (95% CI: 78.7 to 94.9) and the specificity was 98.3% (95% CI: 96.1 to 99.4). Sensitivity was higher in LAB-1 (100%; 95% CI: 71.5 to 100) than in LAB-2 (86.4%; 95% CI: 75.0 to 94.0). Most upward (n = 8, 2.2%) and downward (n = 11, 3.0%) misclassifications occurred at the 2.62 log threshold, with LAB-2 having a 16 (95% CI: 2.26 to 113.27; p = 0.006) times higher odds of downward misclassification. After retesting of discordant leftover samples (n = 17), overall sensitivity increased to 93.5% (95% CI: 85.5 to 97.9) and 97.1% (95% CI: 90.1 to 99.7) at the 2.62 and 3.0 thresholds, and specificity increased to 98.6% (95% CI: 96.5 to 99.6) and 99.0% (95% CI: 97.0 to 99.8) respectively. Conclusions The test characteristics of the Biocentric platform were overall comparable to the national reference method for VL quantification. One laboratory tended to misclassify VL results downwards, likely owing to unmet training needs and lack of previous hands-on practice
Predicting, Diagnosing, and Treating Acute and Early HIV Infection in a Public Sector Facility in Eswatini
Background: The lack of acute and early HIV infection (AEHI) diagnosis and care contributes to high HIV incidence in resource-limited settings. We aimed to assess the yield of AEHI, predict and diagnose AEHI, and describe AEHI care outcomes in a public sector setting in Eswatini.
Setting: This study was conducted in Nhlangano outpatient department from March 2019 to March 2020.
Methods: Adults at risk of AEHI underwent diagnostic testing for AEHI with the quantitative Xpert HIV-1 viral load (VL) assay. AEHI was defined as the detection of HIV-1 VL on Xpert and either an HIV-seronegative or HIV-serodiscordant third-generation antibody-based rapid diagnostic test (RDT) result. First, the cross-sectional analysis obtained the yield of AEHI and established a predictor risk score for the prediction of AEHI using Lasso logistic regression. Second, diagnostic accuracy statistics described the ability of the fourth-generation antibody/p24 antigen-based Alere HIV-Combo RDT to diagnose AEHI (vs Xpert VL testing). Third, we described acute HIV infection care outcomes of AEHI-positive patients using survival analysis.
Results: Of 795 HIV-seronegative/HIV-serodiscordant outpatients recruited, 30 (3.8%, 95% confidence interval: 2.6% to 5.3%) had AEHI. The predictor risk score contained several factors (HIV-serodiscordant RDT, women, feeling at risk of HIV, swollen glands, and fatigue) and had sensitivity and specificity of 83.3% and 65.8%, respectively, to predict AEHI. The HIV-Combo RDT had sensitivity and specificity of 86.2% and 99.9%, respectively, to diagnose AEHI. Of 30 AEHI-positive patients, the 1-month cumulative treatment initiation was 74% (95% confidence interval: 57% to 88%), and the 3-month viral suppression (<1000 copies/mL) was 87% (67% to 98%).
Conclusion: AEHI diagnosis and care seem possible in resource-limited settings.</p
Sensitivity, specificity, negative and positive predictive values of the DiaMed IT-LEISH and the Signal KA for VL diagnosis in Kacheliba and Kimalel, Rift Valley province, Kenya.
<p>Abbreviations: PPV = positive predictive value, NPV = negative predictive value, CI = Confidence Interval.</p
Comparison of demographic and laboratory characteristics between VL and non-VL patients in Kacheliba and Kimalel, Rift Valley province, Kenya.
<p>IQR = inter-quartile range.</p>*<p>p-value from t-test or Kruskal-Wallis test for continuous variables and Chi-square or Fisher Exact test for categorical variables.</p>**<p>measured between tip of spleen and left costal margin (at anterior axillary line level).</p
High Prevalence of Multidrug-Resistant Tuberculosis, Swaziland, 2009–2010
One third of previously treated patients had MDR TB