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Saudi Journal of Kidney Diseases and Transplantation
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Table of Contents   
Year : 2020  |  Volume : 31  |  Issue : 3  |  Page : 699-700
Risk-prediction model for COVID-19 infection in dialysis patients

1 Private Academic Practice, Bangkok, Thailand
2 Department of Community Medicine, Dr. D. Y. Patil University, Pune, Maharashtra, India; Department of Tropical Medicine, Hainan Medical University, Haikou, China

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Date of Submission19-Feb-2020
Date of Acceptance23-Feb-2020
Date of Web Publication10-Jul-2020

How to cite this article:
Yasri S, Wiwanitkit V. Risk-prediction model for COVID-19 infection in dialysis patients. Saudi J Kidney Dis Transpl 2020;31:699-700

How to cite this URL:
Yasri S, Wiwanitkit V. Risk-prediction model for COVID-19 infection in dialysis patients. Saudi J Kidney Dis Transpl [serial online] 2020 [cited 2022 Dec 2];31:699-700. Available from: https://www.sjkdt.org/text.asp?2020/31/3/699/289460

To the Editor,

Patient undergone renal dialysis is usually prone to infection. Several new infections become the big threaten to dialysis patient. The emerging coronavirus infection is the new infection that becomes an important consideration in nephrology. The new disease is named COVID-19. This infection first occurred in China[1] and then spread to Thailand and many countries.[2] The disease is still a present disease to be managed. In early 2020, the WHO mentioned for the need for global collaboration to fight this new disease.

In this report, the authors focus interest on risk prediction for COVID-19 infection in dialysis patients. In fact, there is a previous study to create the risk-prediction model for Middle East Respiratory Syndrome (MERS) infection in dialysis patients. According to that study, Ahmed et al.[3] reported this following model, “The predicted probability of MERS = [1+exp (2.362 – 3.186 × Chest pain – 1.805 × leukopenia – 2.414 × elevated AST)]-1.” Here, the authors use the previous model in MERS as primary template for clinical modeling development. The data of clinical spectrum in MERS and COVID-19 in referencing publiccations are used as variable parameters for adjustment of the model. Briefly, in MERS[4] versus COVID-19,[5] the rates of chest pain, leukopenia, and elevated AST are, 15% versus 2%, 14% versus 9% and 11% versus 28%, respectively.

Based on the mentioned data, modeling adjustment is done and the final derived model for predicting COVID-19 infection in dialysis patients is “The predicted probability of MERS = [1 + exp (2.362 – 23.895 × Chest pain – 2.808 × leukopenia – 0.948 × elevated AST)]-1”. This model is useful for monitoring of risk for the new disease among the dialysis patients.

Conflict of interest: None declared.

   References Top

Hsia W. Emerging new coronavirus infection in Wuhan, China: Situation in early 2020. Case Study Case Rep 2020;10:8-9.  Back to cited text no. 1
Yasri S, Wiwanitkit V. Editorial: Wuhan coronavirus outbreak and imported case. Adv Trop Med Pub Health Int 2020;10:1 -2.  Back to cited text no. 2
Ahmed AE, Alshukairi AN, Al-Jahdali H, et al. Development of a risk-prediction model for Middle East respiratory syndrome coronavirus infection in dialysis patients. Hemodial Int 2018;22:474-9.  Back to cited text no. 3
Assiri A, Al-Tawfiq JA, Al-Rabeeah AA, et al. Epidemiological, demographic, and clinical characteristics of 47 cases of Middle East respiratory syndrome coronavirus disease from Saudi Arabia: A descriptive study. Lancet Infect Dis 2013;13:752-61.  Back to cited text no. 4
Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet 2020;395:507-13.  Back to cited text no. 5

Correspondence Address:
Sora Yasri
Private Academic Practice, Bangkok
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/1319-2442.289460

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