Risk stratification of renal transplant recipients using routine parameters: Implication of learning from SARS-CoV-2 into transplant follow-up program

Abstract

BACKGROUND Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is a global pandemic that is associated with a high risk of morbidity and mortality among recipients of solid organ transplantation. In the course of acute SARS-CoV-2 infection, various laboratory markers have been identified as predictors for high risk of mortality. AIM To risk stratify renal transplant recipients (RTxR) using general demographic parameters, comorbidities and routine laboratory markers for the severity of the disease and its outcomes. We believe that learning about these routinely monitored parameters can help us plan better strategies for the RTxR follow-up program. METHODS This present study includes RTxR who acquired SARS-CoV-2 infection from March 2020 to February 2021. We recorded the basic demographics, comorbidities and routine laboratory markers. We investigated the impact of SARS-CoV-2 infection on RTxRs and risk-stratified the progression of disease severity and outcomes in terms of recovery or mortality. RESULTS From 505 RTxRs in our renal transplant follow-up program, 29 (7.75%) RTxRs had PCR-positive SARS-CoV-2 infection. We recorded 8 deaths from SARS-CoV-2 infection giving an overall mortality rate of 1.6% but a significant 27.6% mortality in SARS-CoV-2 positive recipients. Age more than 68 years, non-Caucasian ethnicity and male gender were associated with a significant drop in survival probability; P ≤ 0.001. < 0.001 and < 0.0001 respectively. 87.5% of the deceased were diabetic; P ≤ 0.0.0001. Estimated glomerular filtration rate of less than 26 mL/min/1.73 m2, serum albumin less than 20 g/L, Hemoglobin less than 9.6 g/L and serum calcium less than 1.70 mmol/L were all associated with significantly increased risk of mortality; P = 0.0128, < 0.001, < 0.0001 and 0.0061 respectively. CONCLUSION This study has identified some routinely used modifiable parameters in predicting a higher risk of mortality and morbidity. This knowledge can be used in RTxR follow-up programs by addressing these parameters early to help reduce the morbidity and mortality in RTxRs.