ABSTRACT
Background: Patients on hemodialysis are at high-risk for complications derived from coronavirus disease 2019 (COVID-19). The present analysis evaluated the impact of a booster vaccine dose and breakthrough severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections on humoral immunity 3 months after the booster dose. Methods: This is a multicentric and prospective study assessing immunoglobulin G anti-Spike antibodies 6 and 9 months after initial SARS-CoV-2 vaccination in patients on hemodialysis that had also received a booster dose before the 6-month assessment (early booster) or between the 6- and 9-month assessments (late booster). The impact of breakthrough infections, type of vaccine, time from the booster and clinical variables were assessed. Results: A total of 711 patients [67% male, median age (range) 67 (20-89) years] were included. Of these, 545 (77%) received an early booster and the rest a late booster. At 6 months, 64 (9%) patients had negative anti-Spike antibody titers (3% of early booster and 29% of late booster patients, P = .001). At 9 months, 91% of patients with 6-month negative response had seroconverted and there were no differences in residual prevalence of negative humoral response between early and late booster patients (0.9% vs 0.6%, P = .693). During follow-up, 35 patients (5%) developed breakthrough SARS-CoV-2 infection. Antibody titers at 9 months were independently associated with mRNA-1273 booster (P = .001), lower time from booster (P = .043) and past breakthrough SARS-CoV-2 infection (P < .001). Conclusions: In hemodialysis patients, higher titers of anti-Spike antibodies at 9 months were associated with mRNA-1273 booster, lower time from booster and past breakthrough SARS-CoV-2 infection.
ABSTRACT
BACKGROUND AND AIMS Patients with ESRD present high symptom burden and impaired health-related quality of life (HRQoL). While the maintenance of medical Key Performance Indicators (KPIs) within defined ranges has been traditionally the focus for dialysis patients' healthcare, there is now increasing evidence of how self-reported HRQoL data could also significantly impact their outcomes. The inclusion of these data, using Patient-Reported Outcomes Measurements (PROM), to the routine medical practice works in favor of providing personalized treatments and detecting new outcomes' predictive factors. In the present study, we aimed to evaluate possible correlations between demographic and clinical variables as well as the COVID-19 incidence rate with HRQoL scores in a haemodialysis patients' cohort. METHOD This is a retrospective, observational analysis performed in a total of 47 clinics from Fresenius Medical Care (FMC) Spain in the last quarter of 2021. Patients' demographic and clinical variables were obtained from EuCliD® (European Clinical database). As part of our Healthcare Quality Improvement Program, HRQoL measurements were assessed using the KDQOL™-36 questionnaire by an electronic device (ePROM). This questionnaire was developed specifically for patients affected by kidney disease and combines a generic assessment, which evaluates Physical and Mental Composite Scores (PCS and MCS, respectively) and three disease-specific scales where Effects, Burden and Symptoms dimensions are scored (EKD, BKD and SKD) [1]. For all clinics, we also collect data regarding their Spanish region, the presence or not of multidisciplinary teams in their staff and their number of active issues. This last parameter, part of FMC Balanced Scorecard, is calculated according to the number of KPIs below range, where a higher score indicates a higher number of active issues. Finally, the COVID-19 incidence rate adjusted per region was obtained from the Spanish Ministry of Health register. The mean (±SD) for quantitative variables and frequencies (%) for those categorical were calculated. We explored possible correlations between the HRQoL average scores and the different variables included in the study. All tests were performed using IBM® SPSS®Statistics V19 software and a P-value < 0.05 was considered statistically significant. RESULTS A total of 3480 ePROM were completed (patients' response rate = 82.4%, Figure 1). Descriptive parameters for demographic and clinical variables are shown in Table 1. The different KDQOL™-36 average scores were the following: PCS: 39.3 ± 2.3; MCS: 47 ± 3; EKD: 70 ± 7.4; BKD: 48.1 ± 8.9 and SKD: 81.2 ± 4.3. We found positive correlations between the presence of nutritionist staff with MCS and the quality of dialysis treatment (measured by OCM Kt/V) and the frequency of AVF as vascular access with EKD score. Unexpectedly, the Charlson Comorbidity Index (CCI) showed positively correlation with PCS. Regarding negative correlations, variables as the Spanish region, the proportion of women in the clinics, body composition parameters (ATM and FTM) and serum P concentration were all associated with PCS. We also observed that EKD scores could be affected in those clinics with a higher number of active issues. Moreover, high levels of CRP or Vitamin D may lead to worsening symptoms. Interestingly, we finally observed how a higher incidence rate of COVID-19 in the region could influence the BDK score in patients receiving haemodialysis treatment.FIGURE 1: Study flowchart. CONCLUSION Although further analyses are needed, our study showed the correlation of HRQoL scores obtained by ePROM with factors of great impact in patients' outcomes. According to provide a higher healthcare quality and personalized treatments for ESRD patients, an integral approach considering their HRQoL data should be essential. Editable version available.