Background

Correlation between antibody-mediated rejection (ABMR) and circulating HLA donor-specific antibodies (HLA-DSA) is strong but imperfect in kidney transplant (KT) recipients, raising the possibility of undetected HLA-DSA or non-HLA antibodies contributing to ABMR. Detailed evaluation of the degree of HLA matching together with the identification of non-HLA antibodies in KT may help to decipher the antibody involved.

Methods

We retrospectively assessed patients with transplant biopsies scored following Banff'15 classification. Pre- and post-transplant serum samples were checked for HLA and non-HLA antibodies [MICA-Ab, angiotensin-II type-1-receptor (AT₁R)-Ab, endothelin-1 type-A-receptor (ETAR)-Ab and crossmatches with primary aortic endothelial cells (EC-XM)]. We also analyzed HLA epitope mismatches (HLA-EM) between donors and recipients to explore their role in ABMR histology (ABMR_h) with and without HLA-DSA.

Results

One-hundred eighteen patients with normal histology (n = 19), ABMR_h (n = 52) or IFTA (n = 47) were studied. ABMR_h patients were HLA-DSA_pos (n = 38, 73%) or HLA-DSA_neg (n = 14, 27%). Pre-transplant HLA-DSA and AT₁R-Ab were more frequent in ABMR_h compared with IFTA and normal histology cases (p = 0.006 and 0.003), without differences in other non-HLA antibodies. Only three ABMR_hDSA_neg cases showed non-HLA antibodies. ABMR_hDSA_neg and ABMR_hDSA_pos cases showed similar biopsy changes and graft-survival. Both total class II and DRB1 HLA-EM were associated with ABMR_hDSA_pos but not with ABMR_hDSA_neg. Multivariate analysis showed that pre-transplant HLA-DSA (OR: 3.69 [1.31-10.37], p = 0.013) and AT₁R-Ab (OR: 5.47 [1.78-16.76], p = 0.003) were independent predictors of ABMR_hDSA_pos.

Conclusions

In conclusion, pre-transplant AT₁R-Ab is frequently found in ABMR_hDSA_pos patients. However, AT₁R-Ab, MICA-Ab, ETAR-Ab or EC-XM⁺ are rarely found among ABMR_hDSA_neg patients. Pre-transplant AT₁R-Ab may act synergistically with preformed or de novo HLA-DSA to produce ABMR_hDSA_pos but not ABMR_hDSA_neg. HLA epitope mismatch associates with ABMR_hDSA_pos compared with ABMR_hDSA_neg, suggesting factors other than HLA are responsible for the damage.

Background

Coronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis.

Methods

We analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression.

Results

In 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∼5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome.

Conclusions

Mortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis.

Background

Patients on kidney replacement therapy (KRT) are at very high risk of coronavirus disease 2019 (COVID-19). The triage pathway for KRT patients presenting to hospitals with varying severity of COVID-19 illness remains ill-defined. We studied the clinical characteristics of patients at initial and subsequent hospital presentations and the impact on patient outcomes.

Methods

The European Renal Association COVID-19 Database (ERACODA) was analysed for clinical and laboratory features of 1423 KRT patients with COVID-19 either hospitalized or non-hospitalized at initial triage and those re-presenting a second time. Predictors of outcomes (hospitalization, 28-day mortality) were then determined for all those not hospitalized at initial triage.

Results

Among 1423 KRT patients with COVID-19 [haemodialysis (HD), n = 1017; transplant, n = 406), 25% (n = 355) were not hospitalized at first presentation due to mild illness (30% HD, 13% transplant). Of the non-hospitalized patients, only 10% (n = 36) re-presented a second time, with a 5-day median interval between the two presentations (interquartile range 2-7 days). Patients who re-presented had worsening respiratory symptoms, a decrease in oxygen saturation (97% versus 90%) and an increase in C-reactive protein (26 versus 73 mg/L) and were older (72 vs 63 years) compared with those who did not return a second time. The 28-day mortality between early admission (at first presentation) and deferred admission (at second presentation) was not significantly different (29% versus 25%; P = 0.6). Older age, prior smoking history, higher clinical frailty score and self-reported shortness of breath at first presentation were identified as risk predictors of mortality when re-presenting after discharge at initial triage.

Conclusions

This study provides evidence that KRT patients with COVID-19 and mild illness can be managed effectively with supported outpatient care and with vigilance of respiratory symptoms, especially in those with risk factors for poor outcomes. Our findings support a risk-stratified clinical approach to admissions and discharges of KRT patients presenting with COVID-19 to aid clinical triage and optimize resource utilization during the ongoing pandemic.