Comparative Analysis of Kidney Transplant Recipients with Severe Acute Respiratory Syndrome Coronavirus 2 Compared with Nonkidney Transplant Recipients: A Largest Single-center Report from the Second Wave of Coronavirus Disease 2019 Pandemic in South East Asia

   Abstract 


Outcomes of severe acute respiratory syndrome coronavirus 2 in kidney transplant recipients (KTR) compared with matched cohort are certainly lacking for different pandemic waves and geographic regions. In this single-center retrospective study of coronavirus disease-2019 (COVID-19) cases admitted during March 26, 2021 to June 7, 2021, a propensity-matched analysis in a 1:1 ratio was performed to compare the clinical profile and outcomes between KTR and non-KTR. A Cox proportional hazard model from the whole study population to analyze risk factors for severe disease and mortality was calculated. We identified 1052 COVID-19 cases, of which 107 (10.1%) were KTR. In propensity-matched analysis, KTR had higher fever (81.6 % vs. 60%; P = 0.01), lymphopenia (30% vs. 11.7%; P = 0.02), higher neutrophil-to-lymphocyte ratio (43.3% vs. 25%; P = 0.05), and acute kidney injury (66.6% vs. 36.7%; P = 0.001). In Kaplan–Meier survival analysis, there was no difference in mortality or severity of COVID-19. In Cox hazard proportional analysis, the European cooperative oncology group (ECOG) score of 1 to 2 [Hazard ratio (HR) 95% lower confidence interval (CI), upper CI = 4.9 (1.8–13.5); P <0.01], ECOG of >2 [HR = 20 (7.5, 54.7); P <0.01] and waitlisted status [HR = 1.9 (1.1–3.3); P = 0.02] was associated with significant mortality. Kidney transplantation [HR = 0.8 (0.47–1.44); P = 0.5] was not associated with mortality in the analysis. In our report, kidney transplantation status had a different spectrum but was not found to be independently associated with COVID-19 severity or mortality.

How to cite this article:
Chauhan S, Meshram HS, Kute VB, Patel H, Deshmukh S, Desai S, Dave R, Banerjee S. Comparative Analysis of Kidney Transplant Recipients with Severe Acute Respiratory Syndrome Coronavirus 2 Compared with Nonkidney Transplant Recipients: A Largest Single-center Report from the Second Wave of Coronavirus Disease 2019 Pandemic in South East Asia. Saudi J Kidney Dis Transpl 2022;33:46-57
How to cite this URL:
Chauhan S, Meshram HS, Kute VB, Patel H, Deshmukh S, Desai S, Dave R, Banerjee S. Comparative Analysis of Kidney Transplant Recipients with Severe Acute Respiratory Syndrome Coronavirus 2 Compared with Nonkidney Transplant Recipients: A Largest Single-center Report from the Second Wave of Coronavirus Disease 2019 Pandemic in South East Asia. Saudi J Kidney Dis Transpl [serial online] 2022 [cited 2023 Jan 17];33:46-57. Available from: 
https://www.sjkdt.org/text.asp?2022/33/1/46/367825    Introduction Top

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had a devastating impact on health-care services across the globe. Previous reports of the impact of organ transplantation in the coronavirus disease 2019 (COVID-19) demonstrate the ongoing struggle.[1],[2],[3],[4] The mortality described in published literature among solid organ transplant (SOT) patients is diverse in different studies and settings. The United States Center for Disease control and prevention has declared organ transplant recipients as a risk factor for COVID-19-associated morbidity and mortality. Recently, a meta-analysis has shown SOT at increased risk for the adverse impact of COVID-19 in SOT compared to general patients.[5],[6],[7] However, the comparative studies between organ transplant recipients and general patients are somewhat inconclusive in the initial pandemic waves[8] and lacking for the subsequent waves. In addition, data from the developing world on this topic have never been reported. India is one of the worst affected nations in the second wave of the pandemic. As of May 2021, India reports a daily tally of 9009 cases, which is the highest in global rankings. We conducted this study with a rationale to assess the differences in the impact of COVID-19 on organ transplant recipients compared to the general population. Hereunder, we aimed to explore and compare the clinical characteristics, laboratory analysis, and outcome between kidney transplant recipients (KTR) versus non-KTR admitted with COVID-19 in the same settings amid the second wave of pandemic.

   Materials and Methods Top

Ethical committee

The study was approved by the institutional ethical board (ECR/143/Inst/GJ/2013/RR-19). We also abided by the norms and regulations of the Declaration of Helsinki, the declaration of Istanbul, THOTA and good clinical practice. Our study was in accordance with the STROBE checklist for reporting of observational studies. Informed consent from the participants for publication of the report was not taken as the data are retrospective and also anonymized.

Design, settings, study population

This was a retrospective cohort study of all patients admitted with a probable or confirmed SARS-CoV-2 at the COVID-19 center of the Institute of Kidney Diseases and Research Centre, Dr. H. L. Trivedi Institute of Transplantation Sciences, Ahmedabad, Gujarat, India. The patient identification period was limited from March 26, 2021, to June 7, 2021. The time period corresponds to the duration of the index and the last COVID-19 case during the conversion of our transplant center to a dedicated COVID-19 center amid the second wave of the pandemic. We have excluded posttransplant cases who were managed at home/teleconsultation (n = 47) or on an OPD basis (n = 29) and only posttransplant cases coming to the dedicated COVID-19 ward are included to eliminate the selection bias.

Definition

Probable and confirmed COVID-19 was defined as classified by the WHO[9]COVID-19 severity was defined as per the modified 7-point ordinal scale10 where 1 = not hospitalized without limitations of activities; 2 = not hospitalized with some limitations; 3 = hospitalized on room air; 4 = on low flow oxygen (flow <3 L/min); 5 = High flow oxygen or non-re-breather mask; 6 = noninvasive ventilation; 7 = mechanical ventilation; 8 = death. The definition of severe disease is the cases with an ordinal scale of 5. Critical COVID-19 is defined with an ordinal scale of 6 or 7European cooperative oncology group (ECOG) scoring at hospital admission was assessed as follows: 0 = fully active, able to carry on all pre-disease performance without restriction; 1 = Restricted in physically strenuous activity but ambulatory and able to carry out work of a light or sedentary nature, for example, light housework, office work; 2 = Ambulatory and capable of all self-care but unable to carry out any work activities; up and about more than 50% of waking hours; 3 = Capable of only limited self-care; confined to bed or chair more than 50% of waking hours; 4 = completely disabled; cannot carry on any self-care; totally confined to bed or chairAcute kidney injury (AKI) was defined as the rise of 0.3 mg/dL from the baseline or 1.5 times from the initial value in 48 h as per the Kidney Disease Improving Global OutcomesChronic graft dysfunction was defined in KTR as the serum creatinine value >1.5 mg/dL.

Institutional management protocol

The patients were managed as per the Indian government advisories for the management of COVID-19.[11] As no definitive therapy was available for COVID-19, all investigational therapies approved by the Indian government on availability in the center were used during the study period. Therapeutics used were systemic steroids, favipiravir, azithromycin, tocilizumab, remdesivir, tofacitinib, bevacizumab, itolizumab, inhaled budesonide, ivermectin, nitazoxanide, and convalescent plasma. The changes in the hospital policy and management protocol for the second pandemic wave are described in our previous report.[12]

Data collection

The data collection was ceased for analysis on June 2021. The demographic and outcome were collected from the electronic database (Medipro4) of the hospital for retrieval of laboratory parameters. The medical records, including comorbidities and clinical progress, were analyzed from the institutional electronic software and through case files. Data handling and organization were done by (VK and HSM) with the support of IT staff.

Outcomes

The primary outcome was the 28-day mortality differences between propensity-matched KTR and non-KTR. The secondary outcome was the difference in severe COVID-19 between the two groups. Clinical, laboratory, and outcome differences between KTR and non-KTR were also assessed. The risk factors for mortality in the study were also the other secondary outcome measured.

   Statistical Analysis Top

Data were expressed as numbers and percentages. Continuous data were expressed as mean ± standard deviation (SD) if normally distributed. Moreover, continuous data, if nonnormally distributed, are expressed as median and interquartile range (IQR). For comparison of KTR and non-KTR patients through a Chi-square was used if data were categorical. For variables with smaller sample size, Chi-square test with Yates’s correction or a Fisher’s test was used. The continuous variables were compared using Student’s t or Mann–Whitney U test as per appropriate. A Cox regression proportional hazard model was made for identifying the risk factors for mortality and development of severe COVID-19. All variables used in the Cox model were dichotomous. The covariates with a small number of events (death/severe disease) were excluded from the model. The variables used in the Cox analysis included age stratified as 18–30, 31–40, 41–50, 50–60, 60–70, 70–80, and >80 years; male sex, obesity (defined as body mass index <30 kg/m2); higher ECOG score of 1–2, and 3–4; diabetes, hypertension, cardiac disease, postrenal transplantation, heart disease, hemodialysis (HD) patients and the number of comorbidities. The variables with a small sample size were excluded for the stability of the model. In view of the differences in baseline characteristics of the two groups [Table 1], propensity matching was done to eliminate the Berkson’s bias.

Table 1: Baseline characteristics of the unmatched cohort along with propensity-matched cohort.

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All baseline characteristics in [Table 1] were included as covariates in the matching process. The individual predicted probability scores were calculated by logistic regression. The nearest neighbor algorithm was used with a caliper width of 0.2. The match was done in a ratio of 1:1, with the matching order as random and without replacement. The standardized difference for all the covariates was between -1 and +1 SD. The analysis is reported for both prior and after adjustment with propensity score. After matching KTR with matched cohort were compared for clinical features, peak laboratory values during stay and outcomes. The 28-day mortality was analyzed for propensity-matched KTR versus non-KTR with a Kaplan–Meier plot. A two-tailed P <0.05 was considered statistically significant for the purpose of our report. All analysis was performed through R version 3.03 and IBM SPSS Statistics 25.0 software (IBM Corp., Armonk, NY, USA).

   Results Top

During the study period, 107 (10.1%) of the 1052 total COVID-19 cases were KTR. Median (IQR) follow-up of KTR cases was 2 (2–3) months. The follow-up of non-KTR was censored at discharge from the hospital. All cases with discharge on request/leave against medical advice belonged to non-KTR. A total of 317 cases died during the study period, which corresponds to 30.1% mortality in all COVID-19 cases (Supplementary Figure 1). Twenty-one deaths (19.6%) were reported among the 107 admitted KTR in our dedicated ward during the study period.

Baseline characteristics

[Table 1] shows the baseline characteristics of the study for the whole cohort along with adjustment as the propensity-matched cohort. Sixty cases in each group were matched with no differences in the baseline variables. In unmatched analysis, KTR was younger [40 (10) vs. 53 (16); P <0.01]; male predominant (80.4% vs. 61.7%; P <0.01). Among the comorbid conditions, diabetes (22.4% vs. 5.8%; P <0.01), hypertension (63.6 % vs. 11.1%; P <0.01), and obesity (22.4% vs. 7.5%; P <0.01) were more common in KTR. The burden of comorbidities was significantly higher in KTR. There was no difference in the ECOG score on admission between the unmatched groups.

The baseline features of the matched KTR depicted median (IQR) time from transplantation to COVID-19 as four (1–7) years. All the matched KTR were on standard triple immunosuppression. Six (10%) of them presented within the 1st year of transplant and 83.3% were living kidney transplantation. Seven (11.7%) matched KTR had chronic graft dysfunction.

Comparison of KTR with matched non-KTR

[Table 2] shows the clinical profile, laboratory features, and outcomes of the KTR with matched cohort.

Table 2: Clinical features, laboratory profile, and outcomes between matched cohort and kidney transplant recipients.

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In the comparative analysis for clinical features, fever (81.6% vs. 60%; P = 0.01) was more common in KTR, while cough (61.7% vs. 30%; P = 0.01) was a predominant symptom was more common in the matched cohort. Radiological abnormalities (93.3% vs. 78.3%; P = 0.03) were present in a greater number of cases in the matched cohort compared to cohort. Among the laboratory profile, KTR had higher number of cases with raised neutrophil-to-lymphocyte ratio (43.3% vs. 25%; P= 0.05) and low ALC (30% vs. 11.7%; P = 0.02) compared to the matched cohort.

The oxygen modality in the study consisted of low-flow oxygen (13.3% vs. 11.7%; P = 1), high-flow oxygen (8.3% vs. 8.3%; P= 1), NRBM (5% vs. 8.3%; P = 0.7), NIV (11.7% vs. 10%; P = 1), and mechanical ventilation (18.4% vs. 25%; P = 0.5) in KTR compared to the matched cohort. As per the ordinal scale, there were no differences with significant statistical rigor. All the cases on mechanical ventilation died in both the matched cohort. [Figure 1]a and [Figure 1]b shows the Kaplan–Meier analysis for mortality and severe COVID-19 in KTR with matched cohort. Fifteen (25%) death in matched control compared to 11 deaths (18.3%) in KTR were observed. The median survival time was 11 and 17 days for KTR and non-KTR, respectively, with statistically insignificant P-value by all survival methods (Mantel-Cox = 0.3, Breslow = 0.12, and Tarone ware = 0.17). Sixteen (26.6%) severe cases in matched cohort compared to 15 (25%) to KTR. Moreover, the difference was not statistically significant in Kaplan–Meier analysis (Mantel-Cox = 0.66, Breslow = 0.45 and Tarone ware = 0.54). AKI was more frequent in KTR compared to matched cohort (66.6% vs. 36.7%; P = 0.001). HD requirement was present in three KTR cases compared to four in the matched cohort. There were two graft losses in the matched cohort.

Figure 1: Kaplan Meier plots for death and severe COVID-19 comparison between two groups.

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Predictors of mortality in the study

[Table 3] shows the Cox hazard proportional analysis for predicting independent risk factors for the association with mortality.

Admission ECOG score of 1 to 2 [Hazard ratio (HR) (95% lower confidence interval (CI), upper CI) = 4.9 (1.8–13.5); P <0.01], ECOG of >2 [HR = 20 (7.5, 54.7); P <0.01] and waitlisted status [HR = 1.9 (1.1–3.3); P = 0.02] was associated with significant mortality. Kidney transplantation [HR = 0.8 (0.47–1.44); P = 0.5] was not associated with mortality in the analysis. In the analysis, the mortality trend shifted toward older age, but the difference did not achieve a statistically significant value.

   Discussion Top

SARS-CoV-2 has impacted the transplant communities worldwide, and from the beginning of the pandemic, organ transplant recipients are considered at high risk for mortality with COVID-19. While there are a few studies demonstrating higher severity in SOT, there are also some studies reporting similar outcomes compared to normal patients. The current data are limited to the initial pandemic waves, and there is hardly any report from the pandemic wave of May–June 2021. This is imperative to analyze the outcomes of SOT in different waves and different regions of the world, as it is largely known that there are geographic variations among strains and variants. Overall, COVID-19-related mortality was lower in the Indian subcontinent compared to the western, mainly due to the higher burden of comorbidities and higher age in the western world.[13] The reports of mortality in the Indian subcontinent extend from 0.05% to as high as 16% in older groups.[14] Hereabout, we report an Indian experience of COVID-19 in a signal center that was converted to a dedicated COVID-19 unit during the March 2021 to June 2021 pandemic. The reported mortality of KTR for the second wave in our previously published report was 10% (10 of 102) which is lower than the current report of 20.5% (21 of 107). We analyzed only hospitalized cases (n = 107) in this report, and also the time period for the inclusion of cases spanned more. There have been previous such reports from other centers but the time period and settings were altogether different. Linares et al,[15] in a Spanish study, showed a similar outcome in SOT in a propensity-matched control of general patients. Sharma et al[16] in the US have shown similar COVID-19 severity in SOT compared to general patients. Rinaldi et al[17] reported no difference in survival between SOT and non-SOT in an Italian experience. Miarons et al[18] in Spain reported higher mortality compared to the general population.[18] Caillard et al[19] in the US reported increased mortality in SOT compared to non-SOT.[19] Craig-Schapiro[20] in the US reported higher hospitalization rates and mortality in waitlist compared to KTR. Webb et al[21] in the liver transplant registry also showed no difference in mortality.

There are other similar reports from different parts of the world.[22],[23],[24],[25] A large data were recently reported by Hadi et al[7] from the USA, in which no difference in mortality was found, along with increased chances of AKI in SOT. In the most recent data by Trapani et al[26] from Italy, the odds of mortality in SOT were found to be higher than non-SOT. In a nutshell, we report no difference in mortality or disease severity between KTR and non-KTR in our report. There were a fair number of cases who were transplanted a year ago, and the mortality in them was 10% as one case died of the 60-matched KTR. The mortality of waitlisted patients in our report in the Cox analysis was additionally higher. These observations point in favor of continuing transplantation. We have not been able to isolate the strains from our center, but the state and the city had 80%–90% of cases with the Delta variant, as per the unpublished reports.[27] The delta variant is considered to be more contagious and carries more risk of severe infection.[28] Overall, there were many breakthrough vaccination cases in the study, with the majority being partially vaccinated. Due to logistic issues, the vaccination data for general patients were not collected meticulously compared to waitlisted and kidney transplants. In the study period, a total of 9 and 10 breakthrough COVID-19 were reported after vaccination in KTR[29] and waitlisted patients,[30] respectively. The breakthrough COVID-19 cases is a serious concern, but a recent report by Aslam et al[31] has shown the real-world clinical effectiveness of vaccination in organ transplantation.

   Strength of the study Top

At the time of drafting the manuscript, this remains the largest study reporting comparison of KTR with general patients from a South East Asian region. To our knowledge, this is the only study comparing such outcomes during the pandemic wave of March to June 2021. The outcome is measured in the same settings, so the bias of different regimens and care is effectively eliminated. KTR with different spectrums of renal functions, transplant age, and severity are included, so the data can be generalized to all sub-groups of KTR. The admission status of the cohort was electronically recorded in all; hence the reliability and reproducibility of the data strengthen the study.

   Limitations Top

The alarmingly high mortality in the study is explained by referral bias for the large number of sicker patients being referred to our center and cannot be interpolated as the true incidence of mortality in the general population or KTR. The detailed analysis in the study, in the context of clinical progress was not possible owing to the retrospective design of the study. The data for breakthrough COVID-19 cases post-vaccination were incomplete for the general population; hence a comparison was not analyzed due to information bias. The true burden of comorbidities could be higher than reported as the data could be missing due to recall bias and information bias, which is expected in resource settings during the peak of the pandemic. The results cannot be generalized to other SOT patients, as the study included only KTR. There was no genetic sequencing available due to resource limitations, and hence the strain was not isolated.

   Conclusion Top

To summarize, our report highlights that organ transplantation status has a different profile of COVID-19 but, as such, may not be an independent risk factor for mortality or severe COVID-19. The association of high mortality in waitlisted patients in our report suggests continuing transplantation activities with available resources. Breakthrough COVID-19 cases is a matter of concern in waitlisted and transplant. Addition and revisions of the existing literature will be fruitful to further upgrade our knowledge and understanding of the impact and trend of COVID-19 in organ transplantation.

Conflict of interest: none declared.

 

   References Top
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Correspondence Address:
Hari Shankar Meshram
Department of Nephrology and Clinical Transplantation, Institute of Kidney Diseases and Research Centre, Dr. H. L. Trivedi Institute of Transplantation Sciences, Ahmedabad, Gujarat
India
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Source of Support: None, Conflict of Interest: None

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DOI: 10.4103/1319-2442.367825

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