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Sickle cell anemia (SCA) is caused by a single point variation in the β-globin gene (HBB): c.20A> T (p.Glu7Val), in homozygous state. SCA is characterized by sickling of red blood cells in small blood vessels which leads to a range of multiorgan complications, including kidney dysfunction. This case-control study aims at identifying sickle cell nephropathy biomarkers in a group of patients living with SCA from Senegal. A total of 163 patients living with SCA and 177 ethnic matched controls were investigated. Biological phenotyping included evaluation of glycemia, glucosuria, albuminuria, proteinuria, tubular proteinuria, serum creatinine, urine creatinine, urine specific gravity and glomerular filtration rate. Descriptive statistics of biomarkers were performed using the χ2 -test, with the significance level set at p

Background: HIV infection is a concern in the army troupes because of the risk behaviour of the military population. In order to allow regular access to CD4+ T cell enumeration of military personnel as well as their dependents and civilians living with HIV, the Senegalese Army AIDS program is implementing PIMATM Alere technology in urban and semi-urban military medical centres. Validation such device is therefore required prior their wide implementation. The purpose of this study was to compare CD4+ T cell count measurements between the PIMATM Alere to the BD FACSCountTM. Methodology: We selected a total of 200 subjects including 50 patients with CD4+ T-cells below 200/mm3, 50 between 200 and 350/mm3, 50 between 351 and 500/mm3, and 50 above 500/mm3. CD4+ T-cell count was performed on venous blood using the BD FASCountTM as reference method and the PIMATM Point of Care technology. The mean biases and limits of agreement between the PIMATM Alere and BD FACSCountTM were assessed with the Bland-Altman analysis, the linear regression performed using the Passing-Bablok regression analysis, and the percent similarity calculated using the Scott method. Results: Our data have shown a mean difference of 22.3 cells/mm3 [95%CI:9.1–35.5] between the BD FACSCountTM and PIMATM Alere CD4 measurements. However, the mean differences of the two methods was not significantly different to zero when CD4+ T-cell count was below 350/mm3 (P = 0.76). The Passing-Bablok regression in categorized CD4 counts has also showed concordance correlation coefficient of 0.89 for CD4+ T cell counts below 350/mm3 whilst it was 0.5 when CD4 was above 350/mm3. Conclusion: Overall, our data have shown that for low CD4 counts, the results from the PIMATM Alere provided accurate CD4+ T cell counts with a good agreement compared to the FACSCountTM. [ABSTRACT FROM AUTHOR]

ObjectiveThe aim of this study is to find the most suitable heat wave definition among 15 different ones and to evaluate its impact on total, age-, and gender-specific mortality for Bandafassi, Senegal.MethodsDaily weather station data were obtained from Kedougou situated at 17 km from Bandafassi from 1973 to 2012. Poisson generalized additive model (GAM) and distributed lag non-linear model (DLNM) are used to investigate the effect of heat wave on mortality and to evaluate the nonlinear association of heat wave definitions at different lag days, respectively.ResultsHeat wave definitions, based on three or more consecutive days with both daily minimum and maximum temperatures greater than the 90th percentile, provided the best model fit. A statistically significant increase in the relative risk (RRs 1.4 (95% Confidence Interval (CI): 1.2-1.6), 1.7 (95% CI: 1.5-1.9), 1.21 (95% CI: 1.08-1.3), 1.2 (95% CI: 1.04-1.5), 1.5 (95% CI: 1.3-1.8), 1.4 (95% CI: 1.2-1.5), 1.5 (95% CI: 1.07-1.6), and 1.5 (95% CI: 1.3-1.8)) of total mortality was observed for eight definitions. By using the definition based on the 90th percentile of minimum and maximum temperature with a 3-day duration, we also found that females and people aged ≥ 55 years old were at higher risks than males and other different age groups to heat wave related mortality.ConclusionThe impact of heat waves was associated with total-, age-, gender-mortality. These results are expected to be useful for decision makers who conceive of public health policies in Senegal and elsewhere. Climate parameters, including temperatures and humidity, could be used to forecast heat wave risks as an early warning system in the area where we conduct this research. More broadly, our findings should be highly beneficial to climate services, researchers, clinicians, end-users and decision-makers.

BACKGROUND:HIV infection is a concern in the army troupes because of the risk behaviour of the military population. In order to allow regular access to CD4+ T cell enumeration of military personnel as well as their dependents and civilians living with HIV, the Senegalese Army AIDS program is implementing PIMATM Alere technology in urban and semi-urban military medical centres. Validation such device is therefore required prior their wide implementation. The purpose of this study was to compare CD4+ T cell count measurements between the PIMATM Alere to the BD FACSCountTM. METHODOLOGY:We selected a total of 200 subjects including 50 patients with CD4+ T-cells below 200/mm3, 50 between 200 and 350/mm3, 50 between 351 and 500/mm3, and 50 above 500/mm3. CD4+ T-cell count was performed on venous blood using the BD FASCountTM as reference method and the PIMATM Point of Care technology. The mean biases and limits of agreement between the PIMATM Alere and BD FACSCountTM were assessed with the Bland-Altman analysis, the linear regression performed using the Passing-Bablok regression analysis, and the percent similarity calculated using the Scott method. RESULTS:Our data have shown a mean difference of 22.3 cells/mm3 [95%CI:9.1-35.5] between the BD FACSCountTM and PIMATM Alere CD4 measurements. However, the mean differences of the two methods was not significantly different to zero when CD4+ T-cell count was below 350/mm3 (P = 0.76). The Passing-Bablok regression in categorized CD4 counts has also showed concordance correlation coefficient of 0.89 for CD4+ T cell counts below 350/mm3 whilst it was 0.5 when CD4 was above 350/mm3. CONCLUSION:Overall, our data have shown that for low CD4 counts, the results from the PIMATM Alere provided accurate CD4+ T cell counts with a good agreement compared to the FACSCountTM.