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Nephrology

The burden of end-stage renal disease in Khartoum, Sudan: cost of illness study

Hiba Ali Hajomera Community Medicine Department, National University, Khartoum, Sudan

Osama Ahmed Elkhidira Community Medicine Department, National University, Khartoum, Sudan

Shaima Omer Elawadb Faculty of Medicine, University of Khartoum, Khartoum, SudanCorrespondence[email protected]

https://orcid.org/0000-0001-6157-3820

Ola Hatim Elniemab Faculty of Medicine, University of Khartoum, Khartoum, Sudan

https://orcid.org/0000-0002-3469-1386

Mustafa Khalid Khalidb Faculty of Medicine, University of Khartoum, Khartoum, Sudan

https://orcid.org/0000-0001-6102-352X

Lina S. Altayibb Faculty of Medicine, University of Khartoum, Khartoum, Sudan

https://orcid.org/0000-0002-6175-0695

Ibrahim Ahmed Abdallab Faculty of Medicine, University of Khartoum, Khartoum, Sudan

https://orcid.org/0000-0002-6542-7780

Tahani Amin Mahmoudc National University, Khartoum, Sudan

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Figures & data

Table 1. Number of end-stage renal disease patients in the 13 dialysis centres in Khartoum state and the size of the sample chosen from each centre.

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Figure 1. Average income sources in USD among households of families of end stage renal disease patients in Khartoum, Sudan 2019 (n = 150).

Table 2. Socio-demographic characteristics, insurance status and employment analysis and their association with total ESRD cost rank using analysis of Man Whitney test^a, Kruskal-Wallis test^b, and spearman correlation^c test in Khartoum, Sudan 2019 (n = 150).

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Table 3. Renal failure duration, comorbidities and dialysis information and their association with total ESRD cost rank using analysis of Man Whitney test^a, Kruskal-Wallis test^b, and spearman correlation^c test in Khartoum, Sudan 2019 (n = 150).

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Table 4. Hospitalization information among ESRD patients and their association with total ESRD cost rank using analysis of man whitney test^a, and spearman correlation^c test in Khartoum, Sudan 2019 (n = 150).

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Table 5. Annual average total and categories of direct cost, indirect cost (loss of productivity), working days loss and annual total cost categories in SDGs ($PPP), among patients and caregivers of end-stage renal disease in Khartoum, Sudan 2019 (n = 150).

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Table 6. Multivariate linear regression model for potentially significant predictors (P-value <0.2) associated with the total ESRD cost among patients of end-stage renal disease in Khartoum, Sudan 2019 (n = 150).

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Data availability statement

The data that support the findings of this study are available from the corresponding author (SOE) upon reasonable request.

The burden of end-stage renal disease in Khartoum, Sudan: cost of illness study

Table 1. Number of end-stage renal disease patients in the 13 dialysis centres in Khartoum state and the size of the sample chosen from each centre.

Table 2. Socio-demographic characteristics, insurance status and employment analysis and their association with total ESRD cost rank using analysis of Man Whitney test^a, Kruskal-Wallis test^b, and spearman correlation^c test in Khartoum, Sudan 2019 (n = 150).

Table 3. Renal failure duration, comorbidities and dialysis information and their association with total ESRD cost rank using analysis of Man Whitney test^a, Kruskal-Wallis test^b, and spearman correlation^c test in Khartoum, Sudan 2019 (n = 150).

Table 4. Hospitalization information among ESRD patients and their association with total ESRD cost rank using analysis of man whitney test^a, and spearman correlation^c test in Khartoum, Sudan 2019 (n = 150).

Table 5. Annual average total and categories of direct cost, indirect cost (loss of productivity), working days loss and annual total cost categories in SDGs ($PPP), among patients and caregivers of end-stage renal disease in Khartoum, Sudan 2019 (n = 150).

Table 6. Multivariate linear regression model for potentially significant predictors (P-value <0.2) associated with the total ESRD cost among patients of end-stage renal disease in Khartoum, Sudan 2019 (n = 150).

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The burden of end-stage renal disease in Khartoum, Sudan: cost of illness study

Figures & data

Table 1. Number of end-stage renal disease patients in the 13 dialysis centres in Khartoum state and the size of the sample chosen from each centre.

Table 2. Socio-demographic characteristics, insurance status and employment analysis and their association with total ESRD cost rank using analysis of Man Whitney testa, Kruskal-Wallis testb, and spearman correlationc test in Khartoum, Sudan 2019 (n = 150).

Table 3. Renal failure duration, comorbidities and dialysis information and their association with total ESRD cost rank using analysis of Man Whitney testa, Kruskal-Wallis testb, and spearman correlationc test in Khartoum, Sudan 2019 (n = 150).

Table 4. Hospitalization information among ESRD patients and their association with total ESRD cost rank using analysis of man whitney testa, and spearman correlationc test in Khartoum, Sudan 2019 (n = 150).

Table 5. Annual average total and categories of direct cost, indirect cost (loss of productivity), working days loss and annual total cost categories in SDGs ($PPP), among patients and caregivers of end-stage renal disease in Khartoum, Sudan 2019 (n = 150).

Table 6. Multivariate linear regression model for potentially significant predictors (P-value <0.2) associated with the total ESRD cost among patients of end-stage renal disease in Khartoum, Sudan 2019 (n = 150).

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Table 2. Socio-demographic characteristics, insurance status and employment analysis and their association with total ESRD cost rank using analysis of Man Whitney test^a, Kruskal-Wallis test^b, and spearman correlation^c test in Khartoum, Sudan 2019 (n = 150).

Table 3. Renal failure duration, comorbidities and dialysis information and their association with total ESRD cost rank using analysis of Man Whitney test^a, Kruskal-Wallis test^b, and spearman correlation^c test in Khartoum, Sudan 2019 (n = 150).

Table 4. Hospitalization information among ESRD patients and their association with total ESRD cost rank using analysis of man whitney test^a, and spearman correlation^c test in Khartoum, Sudan 2019 (n = 150).