Prevalence of Stroke in Individuals with Sickle Cell Disease Pre- and during Hydroxyurea Uses: A Descriptive Cross-Sectional Study in Tanzania.

Sickle cell disease (SCD) is an inherited blood disorder that leads to a variety of complications, including stroke. The use of hydroxyurea (HU) is reported to lessen the frequency and burden of stroke in SCD patients. However, less is known about the prevalence of stroke in SCD patients pre- and during the use of HU in sub-Saharan African (SSA) countries. Therefore, the study assessed stroke prevalence before and during uses of hydroxyurea among SCD patients in Tanzania. A hospital-based descriptive cross-sectional study was conducted at the sickle cell clinics in Dar es Salaam, Tanzania, from April 2023 to May 2023. A total of 228 participants were recruited, and data on demographic and clinical characteristics, HU use, and history of stroke were collected using a checklist from the respective patients' medical records and verbal communication with the patients or caregivers. Data analysis was done using SPSS software version 25, and findings are summarized using frequency and percentages. Out of 228 enrolled SCD patients, 124 (54.4%) were females, 109 (47.8%) were aged between 6 and 12 years, 226 (99.1%) were not married, 181 (79.4%) had primary education, and 209 (95%) were unemployed. The prevalence of stroke pre-HU use was 28 (12.3%) and 6 (2.6%) after starting using HU. Out of 6 with stroke after starting using HU, 3 (50%) had a history of stroke pre-HU uses. The study showed that the prevalence of stroke among SCD patients is significantly reduced after HU use. The findings suggest the need for stakeholders to implement measures to ensure eligible SCD patients are kept on HU.

Improved Biorepository to Support Sickle Cell Disease Genomics and Clinical Research: A Practical Approach to Link Patient Data and Biospecimens from Muhimbili Sickle Cell Program, Tanzania.

In Africa, sickle cell disease phenotypes' genetic contributors remain understudied due to the dearth of databases that pair biospecimens with demographic and clinical details. The absence of biorepositories in these settings can exacerbate this issue. This article documents the physical verification process of biospecimens in the biorepository, connecting them to patient clinical and demographic data and aiding in the planning of future genomic and clinical research studies' experience from the Muhimbili Sickle Cell Program in Dar es Salaam, Tanzania. The biospecimen database was updated with the current biospecimen position following the physical verification and then mapping this information to its demographic and clinical data using demographic identifiers. The biorepository stored 74,079 biospecimens in three -80°C freezers, including 63,345 from 5159 patients enrolled in the cohort between 2004 and 2016. Patients were identified by a control (first visit), entry (when confirmed sickle cell homozygous), admission (when hospitalized), and follow-up numbers (subsequent visits). Of 63,345 biospecimens, follow-ups were 46,915 (74.06%), control 8067 (12.74%), admission 5517 (8.71%), and entry 2846 (4.49%). Of these registered patients, females were 2521 (48.87%) and males were 2638 (51.13%). The age distribution was 1-59 years, with those older than 18 years being 577 (11.18%) and children 4582 (88.82%) of registered patients. The notable findings during the process include a lack of automated biospecimen checks, laboratory information management system, and tubes with volume calibration; this caused the verification process to be tedious and manual. Biospecimens not linked to clinical and demographic data, date format inconsistencies, and lack of regular updating of a database on exhausted biospecimens and updates when biospecimens are moved between positions within freezers were other findings that were found. A well-organized biorepository plays a crucial role in answering future research questions. Enforcing standard operating procedures and quality control will ensure that laboratory users adhere to the best biospecimen management procedures.

Infrastructure for bioinformatics applications in Tanzania: Lessons from the Sickle Cell Programme.

Sickle cell disease (SCD) is a common genetic disorder in Africa. Some ongoing work in SCD research includes the analysis and comparisons of variation in phenotypic presentations and disease outcomes with the genotypic signatures. This has contributed to the observed growth of molecular and genetic data in SCD. However, while the "omics" data continues to pile, the capacity to interpret and turn the genetic findings into clinical practice is still underdeveloped, especially in the developing region. Building bioinformatics infrastructure and capacity in the region is key to bridging the gap. This paper seeks to illustrate how the Sickle Cell Programme (SCP) at the Muhimbili University of Health and Allied Sciences (MUHAS) in Tanzania, modeled the integration of infrastructure for bioinformatics and clinical research while running day-to-day clinical care for SCD in Tanzania.

Patterns and patient factors associated with loss to follow-up in the Muhimbili sickle cell cohort, Tanzania.

BACKGROUND: Monitoring patient's clinical attendance is a crucial means of improving retention in care and treatment programmes. Sickle cell patients' outcomes are improved by participation in comprehensive care programmes, but these benefits cannot be achieved when patients are lost from clinical care. In this study, patients are defined as loss to follow-up when they did not attend clinic for more than 9 months. Precise information on the retention rate and characteristics of those who are not following their clinic appointments is needed to enable the implementation of interventions that will be effective in increasing the retention to care. METHOD: This was a retrospective study involving sickle cell patients registered in the Muhimbili Sickle Cohort in Tanzania. Descriptive and survival analysis techniques both non-parametric methods (Kaplan-Meier estimator and Log-rank test) and semi-parametric method (Cox's proportional hazard model), were used. A p-value of 0.05 was considered significant to make an inference from the analysis. RESULTS: A total of 5476 patients were registered in the cohort from 2004 to 2016. Of these, 3350 (58.13%) were actively participating in clinics, while 2126 (41.87%) were inactive, of which 1927 (35.19%) were loss to follow-up. We used data from 2004 to 2014 because between 2015 and 2016, patients were referred to other government hospitals. From the survival analysis results, pediatric (HR: 14.29,95% CI: 11.0071-18.5768, p <  0.001) and children between 5 and 17 years [HR:2.61,95% CI:2.2324-3.0705, p <  0.001] patients were more likely to be loss to follow-up than the adult (18 and above years) patients. It was found that patients with above averages for hematocrit (HR: 2.38, 95% CI: 1.0076-1.0404, p = 0.0039) or mean cell volume (HR: 4.28, (95% CI: 1.0260-1.0598, p < 0.001) were more likely to be loss to follow-up than their counterparts. CONCLUSION: Loss to follow-up is evident in the cohort of patients in long term comprehensive care. It is, therefore, necessary to design interventions that improve patients' retention. Suggested solutions include refresher training for health care workers and those responsible for patient follow-up on techniques for retaining patients and comprehensive transition programs to prepare patients who are moving from pediatric to adult clinics.