**1. Introduction**

Health care systems all over the world have been facing major and unprecedented challenges since the outbreak of Coronavirus Disease 2019 (COVID-19). Extensive restrictions and nation-wide lockdowns were implemented to contain the spread of the novel coronavirus SARS-CoV-2. Its special features contributed to its fast and widespread transmission, including (1) being highly contagious, (2) the possible transmission from asymptomatic individuals and (3) causing mild symptoms in most of the infected patients [1,2]. Some countries were unexpectedly overwhelmed by a considerable increase in patients admitted to hospitals in need of intensive care [3]. Meanwhile, a worldwide shortage of personal protective equipment (PPE) in conjunction with limited bed capacities at intensive care units (ICU) resulted in suspension of elective surgeries. PPE and ICU beds were urgently needed as scarce medical resources for the managemen<sup>t</sup> of COVID-19 cases and for the protection of the medical staff [4,5]. Another reason for postponing elective surgeries was the fear that patients admitted to hospital for elective surgery would become vectors for the transmission of a nosocomial infection with SARS-CoV-2 [3,4].

The outbreak of the pandemic also resulted in restrictions and cancellations in terms of kidney transplantation (KT) [6–9]. In Italy, a notable decrease in solid organ transplantation and procurement has already been observed in the first four weeks of the pandemic [10]. Currently, decisions on prioritizing certain procedures—including KT—are based on expert opinions rather than on evidence, contributing to different spread-dependent restrictions between regions [7]. In addition, it is unclear which immunosuppressive induction regimen can be administered safely. Especially, the administration of thymoglobulins causing long-lasting lymphopenia has been discussed critically, as a low lymphocyte count has been negatively associated with the disease severity of SARS-CoV-2 infection [1,11,12]. Even planned immunosuppression in living donation has been questioned [1]. The American Society of Transplantation and the European Association of Urology currently recommend to defer non-urgen<sup>t</sup> KTs with living donors, but to perform urgen<sup>t</sup> KTs—depending on the local situation [13,14]. However, the main aim should be rationing scarce medical resources, especially PPE, ventilators and ICU beds, while providing the best possible medical care to our patients [4].

The costs and benefits of a kidney transplantation during a pandemic should be counterbalanced [2]. We know that KT is the best treatment option for patients suffering from end-stage kidney disease (ESKD), with an improved survival rate and quality of life [15]. On the other hand, we lack information about the risk for admission to ICU after KT. In the context of scarce ICU resources, knowing about risk factors for ICU admission is crucial. Especially, older patients with comorbidities could have a higher risk for admission to ICU. The Eurotransplant Senior Program (ESP) is a special kidney transplant program which was initiated in 1999 to reduce waiting times by allocating kidneys from deceased donors aged ≥65 years to old recipients aged ≥65 years. Before that date, only 3% of patients aged 65 years or older actually received a KT offer within the Eurotransplant region, because younger patients with more favorable outcomes were prioritized [16]. In ESP, organ allocation is not based on immunological compatibility, but on local, regional or national allocation and AB0-compatibility, in order to reduce cold ischemia time (CIT). For this reason, risk assessment scores such as the Kidney Donor Risk Index (KDRI) are not integrated into the standard allocation protocols [17]. Double kidney allocation is not allowed at the beginning of the allocation procedure. Within the regular Eurotransplant Kidney Allocation System (ETKAS), kidneys can be allocated for donation after brain death (DCB) and, if allowed by national law, donation after cardiocirculatory death (DCD). Within the first 10 years, ESP has significantly increased the number of old kidney recipients. Local allocation resulted in shorter CITs and lower delayed graft function (DGF) rates compared to old kidney recipients in the regular Eurotransplant Kidney Allocation System (ETKAS) [18,19].

We lately had to decide whether or not to accept an allocated kidney from a 66 year old donor with a negative SARS-CoV-2 test result, allocated within ESP. The recipient was a 70 year old male with a solitary kidney who had an underlying hypertensive nephropathy. He had been on dialysis for 36 months and additionally suffered from coronary artery disease (CAD). This was the first organ offer within the ESP program at our department since the beginning of the SARS-CoV-2 pandemic. To provide valid information and thereby help decision-making in times of SARS-CoV-2, we conducted

the first risk assessment for post-operative ICU stay among patients in the ESP so far. Additionally, the impact of an ICU admission on further outcome was assessed in this bi-center study.

#### **2. Materials and Methods**

In total, 105 KTs in the ESP performed at two tertiary referral centers were retrospectively analyzed. From 2010 to 2020, 40 (38.1%) and 65 (61.9%) kidneys were locally allocated to two transplant centers. In accordance with local law, all donors were brain-dead. No double kidney transplantations were included. All KTs were conducted in an open fashion by experienced transplant surgeons. After KT, the patients were admitted to an intermediate care unit by default. Only in the case of severe complications which could not be treated in an intermediate care unit, patients were admitted to the ICU. All kidney recipients received basiliximab as an induction treatment in combination with tacrolimus, mycophenolate mofetil and (methyl)prednisolone as the standard immunosuppressive regimen in both transplant centers.

This entire analysis was conducted in adherence with the correct scientific research work terms of the Charité Medical University of Berlin and Saarland University. Patients provided written informed consent and patient data was fully anonymized.

#### *2.1. Data Collection and Outcome Measures*

For the recipient characteristics, age, gender, BMI (kg/m2) and relevant health-conditions (arterial hypertension, CAD, diabetes mellitus, history of smoking) were obtained. The underlying cause for ESKD, duration and type of dialysis, and number of prior kidney transplantations characterized recipient's nephrological history. For the graft characteristics, donor age, number of HLA-mismatches and cold ischemia time (CIT) were obtained. Regarding KT, operating time, warm ischemia time (WIT) and intraoperative complications served as surgical outcomes. Admission to ICU, length of ICU stay, complications based on Clavien Dindo within 30 days after surgery (major complications defined as <sup>≥</sup>grade 3a) and length of hospital stay characterized the recipient's postoperative course. The graft function was assessed by DGF rates, defined as the need for dialysis within 7 days after transplantation, and serum creatinine during follow-up. Over 10 years, graft and patient survival were compared.

As the primary outcome, risk factors for ICU admission after KT in ESP were identified. Therefore, patients with ICU admission were compared with patients without an ICU stay. To assess the influence of recipient and donor age on ICU admission, age-dependent comparisons were conducted, considering very old donors ≥75 years (very old-for-old vs. old-for-old) and very old recipients ≥70 years (old-for-very old vs. old-for-old). A multivariate binary logistic regression analysis identified significant risk predictors for ICU stay, which were used to create a risk model.

As the secondary outcome, the impact of ICU admission on further outcome was assessed. For this objective, survival and regression analyses identifying factors impacting graft and overall survival were calculated. Graft survival was always censored for death with functioning graft (DWFG).

#### *2.2. Statistical Analysis*

Categorical variables were reported as frequencies and proportions, and continuous data as the median and range. Fisher's exact test and Mann-Whitney U test were conducted to compare between the groups. Kaplan Meier analyses compared graft and patient survival between groups by log-rank test. For binary logistic and cox regression analyses, covariates were included in multivariate regression analysis only if the respective effect was significant in the univariate analysis. For multivariate regression analyses, forward Wald selection was applied. The best cut-off for predicted probability of ICU stay in the multivariate risk model was estimated via ROC-analysis and Youden index. Statistical analyses were performed by SPSS version 25 with Fix pack 2 installed (IBM, Armonk, NY, USA). All tests were two-sided, and *p*-values < 0.05 were considered significant.
