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. 2023 Feb 20;2023(1):6.
doi: 10.5339/qmj.2023.6. eCollection 2023.

Time-Series Forecasting of Hemodialysis Population in the State of Qatar by 2030

Abdullah Hamad  1 , Anas Mefleh Al Halabi  2 , Hafedh Ghazouani  2 , Elmukhtar M Habas  2 , Abdelsalam Mohamed Borham  2 , Sahar Mohamed Ismail  1 , Hassan Ali Al-Malki  1 , Mohamad M Alkadi  1
Affiliations

Time-Series Forecasting of Hemodialysis Population in the State of Qatar by 2030

Abdullah Hamad et al. Qatar Med J. .

Abstract

Background: There are few statistics on dialysis-dependent individuals with end-stage kidney disease (ESKD) in Qatar. Having access to this information can aid in better understanding the dialysis development model, aiding higher-level services in future planning. In order to give data for creating preventive efforts, we thus propose a time-series with a definitive endogenous model to predict ESKD patients requiring dialysis.

Methods: In this study, we used four mathematical equations linear, exponential, logarithmic decimal, and polynomial regression, to make predictions using historical data from 2012 to 2021. These equations were evaluated based on time-series analysis, and their prediction performance was assessed using the mean absolute percentage error (MAPE), coefficient of determination (R2), and mean absolute deviation (MAD). Because it remained largely steady for the population at risk of ESKD in this investigation, we did not consider the population growth factor to be changeable. (FIFA World Cup 2022 preparation workforce associated growth was in healthy and young workers that did not influence ESKD prevalence).

Result: The polynomial has a high R2 of 0.99 and is consequently the best match for the prevalence dialysis data, according to numerical findings. Thus, the MAPE is 2.28, and the MAD is 9.87%, revealing a small prediction error with good accuracy and variability. The polynomial algorithm is the simplest and best-calculated projection model, according to these results. The number of dialysis patients in Qatar is anticipated to increase to 1037 (95% CI, 974-1126) in 2022, 1245 (95% CI, 911-1518) in 2025, and 1611 (95% CI, 1378-1954) in 2030, with a 5.67% average yearly percentage change between 2022 and 2030.

Conclusion: Our research offers straightforward and precise mathematical models for predicting the number of patients in Qatar who will require dialysis in the future. We discovered that the polynomial technique outperformed other methods. Future planning for the need for dialysis services can benefit from this forecasting.

Keywords: Chronic Kidney Disease; Dialysis; Forecasting; Hemodialysis; Prediction; Prevalence. Model. Trends; Qatar; Times series.

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Figures

Figure 1.
Figure 1.
Schematic diagram of forecasting using a trend-based process time-series model. NOTE: Time-series analysis is a statistical method that examines trend data and time-series data.
Figure 2.
Figure 2.
Shows the idea of change in such patients requiring dialysis over time. NOTE: • The time-series plot for the number of frequent dialysis patients during the study period is represented by the blue line • The red line indicates a simple annual percent change curve with distinct periods
Figure 3.
Figure 3.
Different statistical models fitting. NOTE: P-value has been determined using the Chi-square test, and it was significant at p < 0.05 level.
Figure 4.
Figure 4.
Forecasting and fitting polynomials to predict the number of dialysis patients in Qatar between 2022 and 2030.
See this image and copyright information in PMC

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References

    1. Thurlow JS, Joshi M, Yan G, Norris KC, Agodoa, LY, Yuan, CM et al. Global epidemiology of end-stage kidney disease and disparities in kidney replacement therapy. Am J Nephrol. 2021;52((2):):98-107. doi: 10.1159/000514550. PMID: 33752206; PMCID: PMC8057343. - PMC - PubMed
    1. Shigidi MM, Ramachandiran G, Rashed AH, Fituri OM. Demographic data and hemodialysis population dynamics in Qatar: A five year survey. Saudi J Kidney Dis Transpl. 2009;20((3):):493-500. PMID: 19414963. - PubMed
    1. Vachharajani T, Jasuja S, AlSahow A, Alghamdi SMG, Al-Aradi AH, Al Salmi, I, et al. Current status and future of end-stage kidney disease in gulf cooperation council countries: Challenges and opportunities. Saudi J Kidney Dis Transpl. 2021;32((4):):1073-10881. - PubMed
    1. AlSahow A, AlRukhaimi M, Al Wakeel J, Al-Ghamdi SM, AlGhareeb S, AlAli F et al. Demographics and key clinical characteristics of hemodialysis patients from the gulf cooperation council countries enrolled in the dialysis outcomes and practice patterns study phase 5 (2012-2015) Saudi J Kidney Dis Transpl. 2016;;27((6) (Suppl. 1):):S12-S23. - PubMed
    1. Data Commons: Place Explorer, country of Qatar. (Data from datacatalog.worldbank.org): Available online: https://datacommons.org/place/country/QAT?utm_medium=explore&mprop=count.... Available online: https://datacommons.org. (accessed in July 2022)

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