| Literature DB >> 32866433 |
Gwilym J Webb1, Thomas Marjot2, Jonathan A Cook3, Costica Aloman4, Matthew J Armstrong5, Erica J Brenner6, Maria-Andreea Catana7, Tamsin Cargill2, Renumathy Dhanasekaran8, Ignacio García-Juárez9, Hannes Hagström10, James M Kennedy2, Aileen Marshall11, Steven Masson12, Carolyn J Mercer2, Ponni V Perumalswami13, Isaac Ruiz14, Sarang Thaker15, Nneka N Ufere16, Eleanor Barnes2, Alfred S Barritt17, Andrew M Moon17.
Abstract
BACKGROUND: Despite concerns that patients with liver transplants might be at increased risk of adverse outcomes from COVID-19 because of coexisting comorbidities and use of immunosuppressants, the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on this patient group remains unclear. We aimed to assess the clinical outcomes in these patients.Entities:
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Year: 2020 PMID: 32866433 PMCID: PMC7455160 DOI: 10.1016/S2468-1253(20)30271-5
Source DB: PubMed Journal: Lancet Gastroenterol Hepatol
Figure 1Cohort selection
(A) Liver transplant cohort. (B) Comparison cohort. SARS-CoV-2= severe acute respiratory syndrome coronavirus 2.
Characteristics of the liver transplant and non-transplant comparison cohorts
| Age, years | 60 (47–66) | 73 (55–84) | <0·0001 | ||
| Sex | .. | .. | 0·0010 | ||
| Male | 102 (68%) | 329 (52%) | .. | ||
| Female | 49 (32%) | 298 (48%) | .. | ||
| Smoker | 3 (2%) | 7 (1%) | 0·418 | ||
| Ethnicity | |||||
| White | 111 (74%) | 434 (69%) | 0·324 | ||
| Other ethnicities | 40 (26%) | 193 (31%) | .. | ||
| African American | 16 (11%) | NA | .. | ||
| Southeast Asian | 11 (7%) | NA | .. | ||
| Hispanic | 6 (4%) | NA | .. | ||
| East Asian | 2 (1%) | NA | .. | ||
| Arab | 2 (1%) | NA | .. | ||
| Unknown | 4 (3%) | NA | .. | ||
| Obesity | 44 (29%) | 158 (25%) | 0·352 | ||
| Cardiovascular disease | 22 (15%) | 202 (32%) | <0·0001 | ||
| Diabetes | 65 (43%) | 144 (23%) | <0·0001 | ||
| Asthma | 0 | 69 (11%) | <0·0001 | ||
| Chronic obstructive pulmonary disease | 4 (3%) | 59 (9%) | 0·0043 | ||
| Other chronic lung disease | 4 (3%) | 32 (5%) | 0·279 | ||
| Hypertension | 63 (42%) | 241 (38%) | 0·459 | ||
| Non-liver cancer | 8 (5%) | 92 (15%) | 0·0011 | ||
| Stroke or transient ischaemic attack | 3 (2%) | 73 (12%) | <0·0001 | ||
| Serum creatinine concentration, mg/dL | 1·2 (0·9–1·5) | 0·9 (0·7–1·1) | <0·0001 | ||
| Immunosuppressant use | 150 (99%) | 19 (3%) | .. | ||
| Prednisolone or prednisone | 67 (44%) | 17 (3%) | <0·0001 | ||
| Calcineurin inhibitor | 135 (89%) | 6 (1%) | <0·0001 | ||
| Tacrolimus | 127 (84%) | 4 (1%) | <0·0001 | ||
| Ciclosporin | 8 (5%) | 2 (<1%) | <0·0001 | ||
| Antimetabolite | 90 (60%) | 7 (1%) | <0·0001 | ||
| Mycophenolate mofetil | 77 (51%) | 6 (1%) | <0·0001 | ||
| Azathioprine | 13 (9%) | 1 (<1%) | <0·0001 | ||
| Sirolimus | 7 (5%) | 0 | <0·0001 | ||
| SARS-CoV-2-targeted therapy | 49 (32%) | 17 (3%) | <0·0001 | ||
| Chloroquine or hydroxychloroquine | 38 (25%) | 5 (1%) | <0·0001 | ||
| Lopinavir or ritonavir | 9 (6%) | 5 (1%) | 0·0003 | ||
| Remdesivir | 6 (4%) | 2 (<1%) | 0·0010 | ||
| Oseltamivir | 3 (2%) | 0 | 0·0072 | ||
| Anakinra | 2 (1%) | 0 | 0·037 | ||
| Convalescent plasma | 2 (1%) | 0 | 0·037 | ||
| Tocilizumab | 2 (1%) | 0 | 0·037 | ||
| Azithromycin | 1 (1%) | 0 | 0·194 | ||
| Heparin | 1 (1%) | 0 | 0·194 | ||
| Sofosbuvir | 1 (1%) | 0 | 0·194 | ||
| Dexamethasone | 0 | 1 (<1%) | 1·000 | ||
| Interferon alfa | 0 | 3 (<1%) | 1·000 | ||
| Interferon beta | 0 | 1 (<1%) | 1·000 | ||
| Intravenous immunoglobulin | 0 | 1 (<1%) | 1·000 | ||
Data are median (IQR) or n (%). Comparisons with Mann-Whitney U tests or Fisher's exact test as appropriate. NA=not available. SARS-CoV-2= severe acute respiratory syndrome coronavirus 2.
For white ethnicity versus other ethnicities grouped.
One patient had two recorded ethnicities.
Body-mass index >30 kg/m2.
Data were missing for 7 patients in the transplant group and 81 in the non-transplant group.
Explicit use of heparin as therapy for SARS-CoV-2 infection.
Figure 2Major outcomes from severe acute respiratory syndrome coronavirus 2 infection in patients who have (n=151) and have not (n=627) undergone liver transplantation
Risk differences between groups are presented with 95% CIs and were calculated with Newcombe's method 10. ICU=intensive care unit.
Figure 3Propensity score-matched models for the association between liver transplantation and death in patients with severe acute respiratory syndrome coronavirus 2 infection
The plot shows four separate propensity-score matched models with liver transplantation as the treatment variable and death as the outcome variable. Risk difference (95% CI) is presented for each model. For model 1, variables included in the calculation of propensity score were age, sex, obesity, white ethnicity, hypertension, diabetes, and serum creatinine. Subsequent models also included interactions with age (model 2), interactions with serum creatinine and age (model 3), and interactions with age but with serum creatinine concentration omitted (model 4). Seven (5%) of 151 transplant patients lacked baseline data for serum creatinine and were not included in models including serum creatinine. Further details are provided in the appendix (pp 9, 11).
Associations between patient characteristics and death in the liver transplant cohort
| OR (95% CI) | p value | OR (95% CI) | p value | ||||
|---|---|---|---|---|---|---|---|
| Age (per 1-year increase) | 57 (47–65) | 66 (61–68) | 1·07 (1·03–1·12) | <0·0001 | 1·06 (1·01–1·11) | 0·031 | |
| Years from liver transplant (per 1 year increase) | 4 (2–11) | 9 (5–14) | 1·05 (0·99–1·10) | 0·086 | 1·04 (0·96–1·12) | 0·393 | |
| Male sex ( | 83 (67%) | 19 (68%) | 1·02 (0·42–2·45) | 0·969 | 0·79 (0·24–2·62) | 0·702 | |
| Smoker ( | 2 (2%) | 1 (4%) | 2·24 (0·20–25·62) | 0·516 | 0·95 (0·03–29·82) | 0·978 | |
| White ethnicity ( | 91 (74%) | 20 (71%) | 0·88 (0·35–2·19) | 0·782 | 1·56 (0·45–5·42) | 0·485 | |
| Obesity | 34 (28%) | 10 (36%) | 1·45 (0·61–3·46) | 0·398 | 1·10 (0·37–3·31) | 0·864 | |
| Cardiovascular disease (yes | 17 (14%) | 5 (18%) | 1·36 (0·45–4·05) | 0·586 | 0·65 (0·15–2·71) | 0·550 | |
| Diabetes (yes | 51 (41%) | 14 (50%) | 1·41 (0·62–3·22) | 0·412 | 1·83 (0·57–5·87) | 0·310 | |
| Asthma (yes | 0 (0%) | 0 (0%) | .. | .. | .. | .. | |
| Chronic obstructive pulmonary disease (yes | 4 (3%) | 0 (0%) | .. | .. | .. | .. | |
| Other chronic lung disease (yes | 1 (1%) | 3 (11%) | 1·36 (0·45–4·05) | 0·586 | 13·04 (0·60–281·45) | 0·101 | |
| Hypertension (yes | 50 (41%) | 13 (46%) | 1·27 (0·55–2·89) | 0·576 | 1·03 (0·34–3·09) | 0·961 | |
| Non-liver cancer (yes | 2 (2%) | 6 (21%) | 16·50 (3·13–87·09) | <0·0001 | 18·30 (1·96–170·75) | 0·011 | |
| Stroke or transient ischaemic attack (yes | 3 (2%) | 0 (0%) | .. | .. | .. | .. | |
| Serum creatinine concentration (per 1 mg/dL increase) | 1·2 (0·9–1·4) | 1·5 (1·1–2·0) | 1·46 (1·07–1·97) | 0·016 | 1·57 (1·05–2·36) | 0·028 | |
| Prednisolone use (yes | 56 (46%) | 11 (39%) | 0·77 (0·34–1·79) | 0·549 | 1·74 (0·55–5·50) | 0·345 | |
| Calcineurin inhibitor use (yes | 109 (89%) | 26 (93%) | 1·67 (0·36–7·81) | 0·515 | 3·73 (0·26–52·41) | 0·329 | |
| Tacrolimus use | 105 (85%) | 22 (79%) | .. | .. | .. | .. | |
| Ciclosporin use | 4 (3%) | 4 (14%) | .. | .. | .. | .. | |
| Antimetabolite use (yes | 75 (61%) | 15 (54%) | 0·74 (0·32–1·69) | 0·472 | 0·68 (0·23–2·01) | 0·484 | |
| Mycophenolate mofetil use | 64 (52%) | 13 (46%) | .. | .. | .. | .. | |
| Azathioprine use | 11 (9%) | 2 (7%) | .. | .. | .. | .. | |
| Sirolimus use (yes | 7 (6%) | 0 (0%) | .. | .. | .. | .. | |
| Hydroxychloroquine treatment (yes | 31 (25%) | 7 (25%) | 0·99 (0·38–2·55) | 0·982 | 1·22 (0·34–4·36) | 0·760 | |
Associations between patient characteristics and death were assessed by univariable and multivariable logistic regression analyses. Multivariable analysis included all the variables for which results are presented in the table; other variables were excluded because of collinearity or absence of patients with the given characteristic in one group. Data were available (after assumptions detailed in the methods) for all patients in all categories, with the exception of missing baseline serum creatinine values in seven patients (excluded from multivariable analysis). The Hosmer-Lemeshow goodness-of-fit statistic was 0·684. OR=odds ratio.
Data are median (IQR) or n (%).
Body-mass index >30 kg/m2.
Figure 4Case fatality rate of severe acute respiratory syndrome coronavirus 2 infection according to age group and liver transplantation status
n denotes the total number of patients in each age group for each cohort.