Non-communicable disease (NCD) prevalence rates are on a constant rise in populations from low- and middle-income countries (LMICs) and the rate of premature death due to NCDs is significantly higher than in high-income settings. In addition to exposure to cardiovascular risk factors due to westernisation of lifestyle, urbanisation, and ageing of the population, low awareness, shortcomings in diagnostic approaches, lack of accurate epidemiological data, prevention programs and trained health care workers are adding substantially to the NCD epidemic in LMIC settings.~Some of the most important NCDs and cardiovascular risk factors (cvRF) in the general population are obesity, arterial hypertension (AHT), as well as type two diabetes mellitus (T2DM), all of them associated with chronic kidney disease (CKD), yet another important NCD. The interaction of CKD with socioeconomic factors, lifestyle habits, as well as still highly prevalent endemic infectious diseases in a population from SSA is under-researched and demands prospective longitudinal investigations. In clinical practice and in public health planing CKD itself is often under-acknowledged although already early stages pose an increased risk for cardiovascular morbidity and mortality - long before the kidney fails.~Therefore, public health authorities and global policy maker have requested accurate CKD prevalence data also from the sub-Sharan African (SSA) region, to inform and support healthcare planning and further understand dynamics that drive CKD in populations living in SSA. To date, mainly cross-sectional data are available, but for a correct diagnosis of CKD repeated measurements within a longitudinal setting is required. Further, the interplay of classical cardiovascular and specific region-dependent factors for the development of CKD needs to be better understood in order to develop adapted strategies for better prevention, diagnosis, and therapies.~The RenalTWO study will help to close this knowledge gap by recruiting approximately 1200 adults looking for primary care health services in the Bagamoyo district hospital catchment area in semi-rural Tanzania, East Africa. All enrolled patients will be prospectively and longitudinally studied and undergo a wide spectrum of clinical and biomedical tests as well as questionnaire based in-depth medical histories, socioeconomic backgrounds, and lifestyle habits for the evaluation of the risk signature for CKD. Based on this data set predictive models can be developed. Based on an optimal validated model, a prognosis score is calculated and illustrated as nomograms.~Further the RenalTWO study provides the opportunity to examine the use of state-of-the-art diagnostic tests in a population with economic limitations and specific health problems, such as a high prevalence of anaemia and infectious diseases. The collected data will allow to report for the first time the urgently needed longitudinally assessed CKD prevalence rate staged and classified according to Kidney Disease: Improving Global Outcomes (KDIGO) guidelines and give an in-depth insight into the risk signature of CKD in a primary care population from semirural SSA. The RenaTWO dataset, will also provide evidence on the validity of cross-sectional data, which are faster, cheaper and easier to collect, but might have sever limitation in the context of chronic diseases. Further the ReanlTWO project can provide insights into the onset of CKD and the incidence and progression of its cvRF as well as define risk signatures in this particular setting. Predictive models will be built and internally validated 100 times, using 10-fold cross validation the models will be developed with either standard logistic regression or with penalised regression using methods such as: LASSO, ridge or sparse principal component analysis (PCA) regression, based on the 10-fold cross-validation. Additionally a random forest model is also validated and compared. Based on the best validation of these models a risk score will be calculated and graphically presented as a nomogram if feasible.To predict the longitudinal course of disease, state transition models such as Markov can be applied and prognosis score data can then be used to develop, and independently test, interactive digital applications to estimate population and personalised risk signatures and trajectories. Finally, the RenalTWO project will build sustainable capacity in primary care and help to improve diagnostic approaches to cvRF and NCD that are still neglected in SSA.
The RenalTWO study is a longitudinal investigation of chronic kidney disease (CKD) prevalence rates and its risk signature in a primary care walk-in population from semirural sub-Saharan Africa. The study is prospectively assessing CKD epidemiology according to current international guidelines, which includes an initial screening and a subsequent confirmation of kidney function and a quantitative proteinuria assessment after a minimum gap time of 90 days. The dataset will help to better understand the pattern and early onset of CKD in a society that is thought to undergo a rapid transition of lifestyle with constantly increasing life expectancy over the past decades and westernisation of lifestyle. In all 1200 patients recruited, a thorough medical check-up is carried out for cardiovascular risk factors associate with CKD as well as in-depth questionnaires of medical histories, socioeconomic backgrounds and lifestyle.