| Literature DB >> 33393172 |
Tommaso M Manzia1, Roberta Angelico1, Luca Toti1, Gennaro Pisani1, Giuseppe Vita1, Francesca Romano1, Brunella M Pirozzi1, Danilo Vinci1, Roberto Cacciola1, Giuseppe Iaria1, Giuseppe Tisone1.
Abstract
The outbreak of COVID-19 led to a reduction in the number of organ transplant interventions in most Countries. In April 2020, at the Tor Vergata University in Rome, Italy, two patients on the waiting list for kidney transplantation (KT) declined a deceased donor's kidney offer. Therefore, between April 20 and 25, 2020, we conducted a telephone survey among our 247 KT waitlist patients. Our aim was to explore: (a) the COVID-19 diffusion among them and (b) their current willingness to be transplanted in case of a kidney offer from a deceased donor. Two hundred and forty-three patients participated in a phone interview. One patient had died from COVID-19. Eighty-five (35%) KT candidates would decline any kidney offer, in most cases until the end of the COVID-19 pandemic. Upon a multivariate analysis, female gender (OR = 2.25, 95% CI = 1.26-4.03, P = .006), high cardiovascular risk (OR = 2.33, 95% CI = 1.06-5.08, P = .034), a waiting list time <3 years (OR = 0.375, 95% CI = 0.15-0.95, P = .04), and the need to be transferred to another hospital for HD (OR = 2.56, 95% CI = 1.10-5.9, P = .03) were associated with such refusal. The COVID-19 pandemic led to a fear of transplantation in a third of the KT candidates. Proactive educational webinars could be a useful tool to remove, or at least lessen, any doubts on the part of KT candidates and to avoid losing the opportunity to quit dialysis.Entities:
Keywords: COVID-19; SARS-CoV-2; deceased donor; kidney transplantation
Mesh:
Year: 2021 PMID: 33393172 PMCID: PMC7883127 DOI: 10.1111/tid.13560
Source DB: PubMed Journal: Transpl Infect Dis ISSN: 1398-2273
Demographic and characteristics of patients on the waiting list for kidney transplantation who would accept or decline transplantation during the COVID‐19 pandemic (n = 243)
| Variables | Would accept the KT (n = 158, 65%) | Would decline the KT (n = 85, 35%) | ∆* |
|
|---|---|---|---|---|
| Age median years (IQR) | 56 (47.7‐62) | 58 (51‐65) | — | .113 |
| Median time on waiting list (IQR) | 33 (15.6‐57.3) | 24 (10‐41.5) | — |
|
| Gender | ||||
| Male (n = 157) | 110 (70.1%) | 47 (29.9%) | Female (+14.3%) | .033 |
| Female (n = 86) | 48 (55.8%) | 38 (44.2%) | ||
| PRA (median and IQR) | ||||
| Class I | 0 (0‐88.25) | 0 (0‐32) | — | .321 |
| Class II | 0 (0‐64.5) | 0 (0‐25) | — | .267 |
| Primary kidney disease | ||||
| Autoimmune/GN (n = 110) | 77 (70%) | 33 (30%) | Other (+9.1%) | .176 |
| Other (n = 133) | 81 (60.9%) | 52 (39.1%) | ||
| Diuresis | ||||
| Yes (n = 65) | 39 (60%) | 26 (40%) | Diuresis yes (+6.9%) | .363 |
| No (n = 178) | 119 (66.9%) | 59 (33.1%) | ||
| Previous KT | ||||
| Yes (n = 65) | 49 (75.4%) | 16 (24.6%) | No previous KT (+14.2%) |
|
| No (n = 178) | 109 (61.2%) | 69 (38.8%) | ||
| Previous calling for KT | ||||
| Yes (n = 109) | 72 (66.1%) | 37 (33.9%) | — | .788 |
| No (n = 134) | 86 (64.2%) | 48 (35.8%) | ||
| Pre‐emptive KT | ||||
| Yes (n = 5) | 3 (60%) | 2 (40%) | Pre‐emptive Y (+5.1%) | 1.000 |
| No (n = 238) | 155 (65.1%) | 83 (34.9%) | ||
| Dialysis type | ||||
| HD (n = 211) | 136 (64.5%) | 75 (35.5%) | HD (+7.5%) | .513 |
| Peritoneal (n = 25) | 18 (72%) | 7 (28%) | ||
| Dialysis | ||||
| ≤5 y (n = 122) | 74 (60.7%) | 48 (39.3%) | Years ≤ 5 (+8.5%) | .180 |
| >5 y (n = 120) | 83 (69.2%) | 37 (30.8%) | ||
| Cardiovascular risk | ||||
| Yes (n = 193) | 119 (62%) | 74 (38%) | Cardiovascular risk (+18%) |
|
| No (n = 50) | 40 (80%) | 10 (20%) | ||
| History of chronic pulmonary obstructive disease | ||||
| No (n = 230) | 151 (65.7%) | 79 (34.3%) | COPD (+15.7%) | .353 |
| Yes (n = 12) | 6 (50%) | 6 (50%) | ||
| Waiting list time | ||||
| ≤3 y (n = 208) | 130 (62.5%) | 78 (37.5%) | ≤3 y (+17.5%) |
|
| >3 y (n = 35) | 28 (80%) | 7 (20%) | ||
| Covid‐19 in hemodialysis unit | ||||
| No (n = 218) | 143 (65.6%) | 75 (34.4%) | Covid‐19 in HD Unit (+4.7%) | .651 |
| Yes (n = 23) | 14 (60.9%) | 9 (39.1%) | ||
| Vascular access problems | ||||
| Yes (n = 48) | 29 (60.4%) | 19 (39.6%) | Vascular access problems (+5.2%) | .665 |
| No (n = 189) | 124 (65.6%) | 65 (34.4%) | ||
| Italian hyperimmune program 3.0 | ||||
| Yes (n = 19) | 14 (73.7%) | 5 (26.3%) | Not hyperimmune (+11.7%) | .139 |
| No (n = 224) | 139 (62.0%) | 85 (38.0%) | ||
| Region | ||||
| Lazio area (n = 209) | 136 (65.1%) | 73 (34.9%) | — | .96 |
| Outside (n = 34) | 22 (64.7%) | 12 (35.3%) | ||
| Transferred to another hospitals for HD | ||||
| Yes (n = 27) | 13 (48.1%) | 14 (51.9%) | Transferred to another hospital for HD (+19.5%) |
|
| No (n = 213) | 144 (67.6%) | 69 (32.4%) | ||
∆: Difference in percentage for each variable in patients who would decline the offer for Kidney Transplantation.
Bold italic values refers to significant P values (P < .05).
The type of dialysis for two patients was not available.
In one patient the time since the start of dialysis was not available.
Two patients did not answer.
No data available for six patients.
Three patients did not answer.
Multivariable logistic model for decision making (decline the kidney offer) in the cohort of waitlisted Kidney Transplantation patients who participated to the phone survey questionnaire (n = 243)
| Variables | Beta | OR | 95% CI |
|
|---|---|---|---|---|
| Gender (female) | 0.081 | 2.25 | 1.26‐4.03 |
|
| High cardiovascular risk (yes) | 0.845 | 2.33 | 1.06‐5.08 | . |
| Transferred to another hospital for HD (yes) | 0.939 | 2.56 | 1.10‐5.92 |
|
| Waiting list time (>3 y) | −0.981 | 0.37 | 0.15‐0.95 |
|
| Constant | 0.024 | .967 |
The multivariate logistic model was built on the backward conditional method; variables fit in the model were those who showed a P < .05 at univariate analysis (gender, previous kidney transplantation, cardiovascular risk, transfer to another hospital for dialysis, waiting list time). The table shows the results of the last step of the backward conditional model (step 2). Bold italic values refers to significant P values (P < .05).