Material and Methods

Study design

We performed a cross-sectional study to recruit renal transplant recipients who were under regular follow-up in two university hospital’s transplantation centers (CMF and KMF) and had RT-PCR confirmed COVID-19. We also recruited consecutive renal transplant recipients who did not have a history of COVID-19 and were attending transplantation outpatient clinics in those institutions. We constructed two additional control groups from a previously screened cohort of health care workers [10]. None of the included patients were vaccinated for COVID-19 prior to antibody measurement.
We used descriptive comparative design to assess the outcomes. The study protocol was approved by the local medical ethics committee (approval no: 2021-2921) and the Ministry of Health’s Scientific Committee (approval no: 2020-11-30T14_57_30). The study was conducted in accordance with the 1975 Declaration of Helsinki, as revised in 2013.

Sampling

The study was conducted between December 7, 2020, and February 12, 2021. The date of blood specimen collection for antibody measurement was accepted as the enrollment date to the study. The date of RT-PCR testing was accepted as the first day of infection.

Transplant recipients

Based on previous studies we predicted seropositivity following COVID-19 as 60% for transplant recipients [9,11] and 90% for subjects from the general population [12-14]. We performed a power analysis, and we planned to recruit 42 participants to each group.
A total of 623 patients were attending outpatient transplantation clinics during the year 2020. Target population was patients who had COVID-19 following April, 2020. We did not formally screen all patients under follow-up; however, all of our transplant patients who had an RT-PCR confirmed COVID-19 history were eligible for the study. We located 57 patients who had COVID-19, one of them died before the start of the study, 46 of them accepted to participate in the study.
We recruited transplant patients who gave informed consent to the COVID-19 negative group if they declared that they did not have a diagnosis of COVID-19 as of the recruitment day. We also checked if they had any RT-PCR test due to mandatory screening (before hospitalization due to any cause, having a household member with COVID-19) and confirmed that the RT-PCR test was negative.

Controls

We recruited control subjects from a cohort of health care workers that we examined previously [10]. Details of recruitment and data collection for those participants were previously described in detail [10].
In that cohort, 116 subjects were RT-PCR positive. We excluded any subjects with malignancy or using immunosuppressive drugs. We transformed the duration between RT-PCR and antibody testing to binomial data based on eight weeks’ cut-off value. RT-PCR positive control group is formed by recruiting subjects using propensity score matching based on age, sex, and transformed antibody testing duration data with a 1:1 ratio.
Among healthcare workers who do not have COVID-19 history, we selected subjects designated as ”no risk” (health care workers who were not attending the hospital because of administrative changes related to pandemic) regarding COVID-19. We excluded any subjects with malignancy or using immunosuppressive drugs; 106 subjects were eligible for selection. We used age and sex-based propensity score matching to select subjects from this cohort with a ratio of 1:1.
We used the same laboratory procedures to measure antibody levels in those subjects and transplant recipients.

Data Collection

We filled a standard form for every patient, and we used patient interviews, medical records of the patients, the hospital’s electronic database, and the national public health data management system to collect data. Our form consisted of the following parts; demographics, clinical data including transplantation history, drug use, laboratory parameters, history, and clinical data related to COVID-19, and computed tomography (CT) findings. We also used the COVID-19 severity index to classify the patients into five mutually exclusive categories; asymptomatic or presymptomatic, mild, moderate, severe, critical illness [15].

PCR testing and Assessment of Antibodies

We used the same methods for RT-PCR testing and SARS-CoV-2- antibody measurement as described in detail previously [10,16]. For detection of COVID-19 RNA, a commercial RT-PCR kit (Bio-Speedy COVID-19 RT-qPCR kit; Bioeksen R & D Technologies Ltd., Istanbul, Turkey) was used. For detection of SARS-CoV-2 IgG (anti-nucleocapsid protein antibodies), chemiluminescent microparticle immunoassay (Abbott Laboratories, Cat no: 6R86, Lot no: 16253FN00) was carried out according to the manufacturer’s instructions, and samples were run on the related instrument (ARCHITECT, Abbott Laboratories, Abbott Park, IL, USA). Qualitative results were reported by the instrument with the cut-off value of 1.40 S/C as recommended.

Statistical Analysis

Descriptive data were presented as mean and ± standard deviation (SD) and median and interquartile range (IQR) for the continuous variables and frequency and percentages (%) for the categorical variables. Continuous variables were evaluated for normality distribution using Shapiro-Wilk test. Kidney transplant recipients and control groups were compared with an independent sample t test for normally distributed variables and Mann-Whitney U test for non-normally distributed variables. Categorical variables were compared by using Chi Square or Fisher’s Exact test for proportion. Multivariate analysis was applied to determine association between antibody level, group and post-infection duration. All significance tests were 2-tailed, and values of p <0.05 were considered statistically significant. All statistical analyzes were performed by SPSS software version 21 (Chicago, IL).
We employed propensity score matching to balance in observed baseline covariates and reduce the bias of treatment effect between kidney transplant recipients and control groups. We assumed at ratio of 1:1 on age and sex with nearest neighbor matching method. The propensity score matching was performed using the RStudio (version 4.0.2 software).
According to previous studies, we accepted a seropositivity rate following COVID-19 as 60% for transplant patients and 90% for the general population. Therefore, considering the percentage of previous studies, we performed power analysis (Gpower software, version 3.1, Kiel, Germany) with 90% power and an error of 0.05 to determine the minimum sample size for RT-PCR positive kidney transplant recipients and control groups. A minimum sample size of 42 was estimated in each group.