Abstract
Background
Patients with end-stage kidney disease who are undergoing dialysis have reduced immune responses to COVID-19 vaccination. Frailty is extremely common among dialysis patients and may contribute to the impaired immunogenicity. This study aimed to determine the association between frailty and humoral immune responses following COVID-19 vaccination in hemodialysis patients.
Design, Setting, Participants
Adult hemodialysis patients without prior SARS-CoV-2 infection who received a priming dose of ChAdOx1 nCoV-19, an adenovirus-vectored vaccine, were assessed for eligibility. Participants were categorized as robust, pre-frail, or frail using the Fried frailty criteria. Humoral responses were assessed 28 days after vaccination by measuring titers of anti-spike IgG antibodies. The primary outcome was anti-spike antibody seroconversion, defined as antibody levels ≥50 AU/mL. Multivariable-adjusted logistic regression models were used to assess the association between frailty status and the primary outcome.
Results
A total of 206 participants (mean age 67 ± 13 years, 50% women) were included in the study, of whom 50 (24%) were characterized as frail, 86 (42%) were characterized as pre-frail, and 70 (34%) were characterized as robust. Anti-spike antibody levels were progressively lower with more advanced stages of frailty (P <0.001). Compared with robust patients, a significantly smaller proportion of pre-frail and frail patients developed anti-spike antibody seroconversion (87%, 66%, and 40%, respectively; P <0.001). Frailty was associated with the absence of humoral responses after adjustment for age, sex, body mass index, diabetes, coronary artery disease, serum albumin, and lymphocyte count (OR=0.25; 95% CI, 0.08–0.80).
Conclusions
Frailty is independently associated with impaired humoral responses following COVID-19 vaccination among hemodialysis patients. Strategies aimed at preventing or attenuating frailty in the dialysis population are warranted.
Key words: COVID-19, frailty, hemodialysis, immunogenicity, vaccine
Introduction
Patients with end-stage kidney disease (ESKD) are highly susceptible to infection and adverse outcomes from coronavirus disease 2019 (COVID-19), especially those with older age or additional comorbidities. Data from France, England, Belgium, Italy, and the United States showed that compared with the general population, patients receiving hemodialysis were 5 to 20 times more likely to be infected with COVID-19 (1). Moreover, once infected, patients on hemodialysis are at least 30% to 130% more likely to die than hospitalized patients with COVID-19 but no underlying chronic kidney disease. Vaccination is seen as the most effective strategy against COVID-19 (2). Despite the high availability and coverage of COVID-19 vaccines, however, accumulating data have revealed blunted and delayed immune responses among dialysis patients compared with those among healthy adults (3).
Frailty, defined as an accumulation of health and functional problems, is characterized by individuals' vulnerability to various stressors resulting from multisystemic dysfunction (4). Although considered to be a geriatric syndrome, frailty is common in patients with ESKD treated with hemodialysis. Using the Fried frailty criteria, the prevalence of frailty and pre-frailty was 43.3% and 35.3%, respectively, in a cohort of 503 maintenance hemodialysis patients (5). In addition to oxidative stress, mitochondrial dysfunction, and cellular senescence, altered immune system has been proposed an underlying mechanism of frailty syndrome (6). Thus, frailty may also contribute to the impaired immunogenicity to vaccination. Indeed, it has been shown that frailty was associated with an impaired immune response following influenza and pneumococcal vaccination among older populations (7). However, whether frailty is associated with a blunted immune response to COVID-19 vaccination in dialysis patients is unclear. Therefore, our objective in this study was to assess the association of frailty with humoral responses following COVID-19 vaccination in patients with ESKD who are undergoing hemodialysis.
Methods
Study Design and Patients
This was a prospective cohort study conducted in the hemodialysis unit of Taipei Tzu Chi Hospital, Taiwan. A total of 242 prevalent hemodialysis patients over 20 years of age, with no history of laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or of COVID-19-like symptoms obtained from patient interviews and medical records, were eligible for enrollment. Twenty-one patients who had been vaccinated prior to the initiation of the study (n=9) or refused vaccination due to personal reasons (n=12) were excluded from the study. Overall, 221 hemodialysis patients received the first dose of the ChAdOxl nCoV-19 vaccine, an adenovirus-vectored vaccine, in June 2021. Of these, 3 patients with inadequate dialysis (defined as Kt/V urea < 1.2 or treatment time < 12 hour per week) and 12 patients who refused to participate were also excluded. All patients were dialyzed for 4 to 4.5 hours thrice weekly using a single-use dialyzer Polyflux H (Baxter, USA) with an effective surface area range from 1.4 to 2.1 m2, blood flow of 250 to 350 mL/min, and dialysate flow of 500 mL/min. This study complied with the Declaration of Helsinki and was approved by the institutional review board of Taipei Tzu Chi Hospital (10-XD-117). All participants provided written informed consent.
Data Collection and Measurements
A thorough medical history was taken at the time of study enrollment. Diabetes was defined as a self-reported history or the use of oral anti-diabetic agents or insulin. Hypertension was defined as blood pressure > 140/90 mm Hg or the use of antihypertensive medications. Coronary artery disease (CAD) was documented by coronary angiography or a history of myocardial infarction. Blood samples were taken at baseline and at 28 and 56 days after the first dose of vaccine. None of the patients received their second dose before day 56. Anthropometric measurements were performed 1 hour after the mid-week hemodialysis session. Body mass index (BMI) was calculated as dry weight in kilograms divided by the square of height in meters (kg/m2).
Frailty Assessments
Baseline frailty was estimated using the Fried frailty phenotype according to the following five criteria; each frailty criterion was recoded as a dichotomous score (8). A Taiwanese version of the protocol was applied (Supplemental Table 1) (9).
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1.
Weight loss was defined as unintentional weight loss of ≥ 3.0 kg or ≥ 5% of body mass in the last year.
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2.
Weakness was based on the measurement of hand grip strength by a handheld dynamometer (Jamar; Lafayette Instrument, Lafayette, IN) immediately before a dialysis session. Patients performed three tests of maximum grip strength with the dominant hand or with the nonfistula hand if implanted, and the mean of the strongest hand was used to determine frailty. The strength measurement was adjusted by sex and BMI.
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3.
Exhaustion was assessed by responses to questions about endurance and energy from the Center for Epidemiologic Studies depression scale (10).
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4.
Low physical activity was assessed by the short version of the Taiwan International Physical Activity Questionnaire, which asks about the frequency and duration of various activities over a 1-week time period.
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5.
Slow walking speed was scored based on the walking time over a distance of 5 meters. Patients were asked to walk 5 meters at their usual pace two times immediately before a dialysis session, and the faster of the two walking trials was recorded. The interpretation of the results was adjusted for sex and height.
Patients received a total of zero to five points according to the number of criteria that they met. Consistent with previous literature, a score of zero was considered robust, one to two as pre-frail, and three or more as frail (8).
Immunogenicity Assessments
At Days 28 and 56 after a priming dose of ChAdOx1 nCoV-19, IgG antibodies to the receptor binding domain of the S1 subunit of the spike protein (anti-S1-RBD IgG) of SARS-CoV-2 were assessed using the AdviseDx SARS-CoV-2 IgG II assay (Abbot Laboratories, Abbott Park, IL). The cutoff value for positivity is 50 arbitrary units per mL (AU/mL) based on manufacturer's recommendations (11). A SARS-CoV-2 IgG titer of 1050 AU/mL, 3550 AU/mL, and 4160 AU/mL corresponds to a 95% probability of being at or above a plaque reduction neutralization test with 50% inhibition of infection of cultured cells (PRNT50) dilution of 1:80, 1:160, and 1:250, respectively (12). Neutralizing antibodies were determined at Day 28 using the MeDiPro SARS-CoV-2 Antibody ELISA (Formosa Biomedical Technology, Taipei, Taiwan), with 50% neutralizing titers (NT50) > 2.56 being considered positive (13).
Safety Assessments
We monitored the solicited local (pain, redness, and swelling) and systemic reactions [fatigue, headache, muscle and joint pain, nausea or vomiting, abdominal pain, diarrhea, and fever (defined as body temperature ≥ 38 °C)] of the participants for 7 days after vaccination using a questionnaire established by the Taiwan Society of Nephrology. In addition, data on unsolicited adverse events and severe adverse events were collected for 28 days following vaccination.
Exposure and Outcomes
The main exposure was the frailty phenotype defined by the Fried criteria. Participants were categorized as robust, pre-frail, or frail according to their frailty scores. The primary endpoint was seroconversion, defined as anti-spike IgG levels ≥ 50 AU/mL, 28 days following the first dose of COVID-19 vaccine. The secondary endpoint was seroconversion determined by neutralizing antibodies titers (NT50 ≥ 2.56).
Statistical Analyses
Continuous data with or without a normal distribution are presented as the means ± standard deviations or medians (interquartile ranges [IQR]) and were compared by one-way ANOVA or the Kruskal-Wallis test as appropriate. Categorical data are presented as a number and percentage and were compared by using a chi-square test. Proportions of participants exceeding the different thresholds were compared using logistic regression models. To adjust for confounders, we sequentially added to multivariate models groups of covariates, which were identified by prior studies as significant predictors of vaccine response and included age, sex, BMI, diabetes, CAD, serum albumin, and lymphocyte count (3, 14, 15). Adjusted odds ratios (ORs) with associated 95% confidence intervals (CIs) were calculated for frail and pre-frail patients using robust patients as the reference. The trend test was performed by treating frailty status as a continuous variable to examine whether frailty status has an ordered relation with immune responses. Two-tailed P values < 0.05 were considered statistically significant. All statistical analyses were performed using the Statistical Package for the Social Sciences software, version 20.0 (SPSS Inc., Chicago, IL).
Results
Patient Characteristics
A total of 206 patients (104 men and 102 women; mean age 67 ± 13 years) who received on a dose of the ChAdOx1 nCoV-19 vaccine were included in the final analysis (Figure 1). Among them, the median dialysis vintage was 7.8 (3.3–12.5) years, 112 (54.4%) had diabetes, and 52 (25.2%) had CAD. The median number of frailty components based on the Fried criteria present at baseline was 1.0 (0.0–2.0). Overall, 50 patients (24.3%) were identified as frail, and 86 (41.7%) were identified as pre-frail. Baseline demographic and clinical characteristics by frailty phenotype are presented in Table 1. As expected, patients meeting more frailty criteria were older, more likely to have diabetes and CAD, and had a slightly higher Kt/V but had a lower serum albumin and lymphocyte count. Other characteristics that have been reported to be predictive of immunogenicity, such as dialysis vintage, BMI, and the use of immunosuppressants, did not differ among groups.
Figure 1.
Patient flow diagram
Table 1.
Baseline characteristics of hemodialysis patients according to frailty status
| Variables | Robust (n=70) | Pre-frail (n=86) | Frail (n=50) | P |
|---|---|---|---|---|
| Demographic data | ||||
| Age (yr) | 59 ± 11 | 68 ± 11 | 76 ± 12 | <0.001 |
| Male sex, n (%) | 41 (58.6%) | 44 (51.2%) | 19 (38.0%) | 0.084 |
| Smoking history, n (%) | 13 (18.6%) | 16 (18.6%) | 10 (20.0%) | 0.976 |
| Dialysis vintage (yr) | 6.9 (3.1–11.5) | 7.9 (3.4–13.3) | 8.2 (3.6–12.8) | 0.539 |
| Kt/V | 1.7 ± 0.2 | 1.7 ± 0.3 | 1.8 ± 0.2 | 0.017 |
| URR(%) | 74.9 ± 4.6 | 75.6 ± 6.3 | 77.8 ± 4.4 | 0.010 |
| nPCR (g/kg/day) | 1.09 (0.93–1.24) | 1.07 (0.94–1.21) | 1.03 (0.88–1.33) | 0.738 |
| Body mass index (kg/m2) | 23.8 ± 3.6 | 23.8 ± 3.9 | 22.3 ± 3.9 | 0.053 |
| Diabetes mellitus, n (%) | 28 (40.0%) | 49 (57.0%) | 35 (70.0%) | 0.004 |
| Hypertension, n (%) | 62 (88.6%) | 76 (88.4%) | 48 (96.0%) | 0.293 |
| CAD, n (%) | 8 (11.4%) | 26 (30.2%) | 18 (36.0%) | 0.004 |
| Cancer, n (%) | 9 (12.9%) | 9 (10.5%) | 6 (12.0%) | 0.895 |
| Use of IS, n (%) | 1 (1.4%) | 2 (2.3%) | 2 (4.0%) | 0.663 |
| Laboratory data | ||||
| Albumin (g/dL) | 4.0 (3.8–4.1) | 3.8 (3.7–4.0) | 3.6 (3.5–3.9) | <0.001 |
| Fasting glucose (mg/dL) | 133 (110–185) | 138 (114–171) | 175 (129–240) | 0.002 |
| Lymphocyte (x109/L) | 1.2 (1.0–1.6) | 1.1 (0.8–1.3) | 1.0 (0.8–1.5) | 0.005 |
| Hemoglobin (g/dL) | 10.5 (9.9–11.2) | 10.1 (9.2–10.9) | 10.5 (9.5–11.0) | 0.006 |
| Ferritin (ng/mL) | 413(158–610) | 526 (288–680) | 413 (262–605) | 0.389 |
| Calcium (mg/dL) | 9.3 (8.7–9.9) | 9.6 (9.0–10.1) | 9.4 (8.8–10.0) | 0.224 |
| Phosphate (mg/dL) | 4.5 (3.7–5.1) | 4.5 (3.7–5.3) | 4.0 (3.6–5.4) | 0.784 |
| iPTH (pg/mL) | 316 (133–567) | 321 (121–582) | 400(174–794) | 0.355 |
CAD = coronary arteiy disease; iPTH = intact parathyroid hormone; IS = immunosuppressant; nPCR = normalized protein catabolic rate; URR = urea reduction ratio.
Immune Responses
Anti-spike antibody levels were progressively lower with more advanced stages of frailty (Figure 2A). The geometric means of antibody levels for robust, pre-frail, and frail patients were 281.3 (95% CI 201.3–393.3) AU/mL, 206.1 (95% CI 134.8–315.3) AU/mL, and 69.3 (95% CI 34.5–139.1) AU/mL, respectively (P<0.001). Likewise, neutralizing antibody titers decreased incrementally with increasing frailty criteria (Figure 2B). The geometric means of NT50 values for robust, pre-frail, and frail patients were 2.28 (95% CI 1.83–2.84), 1.99 (95% CI 1.64–2.41), and 1.36 (95% CI 1.13–1.63), respectively (P=0.002).
Figure 2.
(A) SARS-CoV-2 anti-spike antibody concentrations, and (B) SARS-CoV-2 neutralizing antibody titers at 28 days following the first dose of the ChAdOxl nCoV-19 vaccine according to frailty status
Geometric mean titers and 95% confidence intervals are shown. AU, arbitrary unit; NT50, 50% neutralizing titer.
Primary Outcome
Overall, 138 patients (67.0%) developed antibodies against the SARS-CoV-2 spike protein (≥50 AU/mL) (Table 2). A higher proportion of seroconversion after vaccination was found in robust (87.1%) and pre-frail patients (66.3%) than in frail patients (40.0%) (P<0.001). We found that patients with more frail status were less likely to develop seroconversion in univariate (P for trend=0.001) and multivariate logistic regression analyses (P for trend=0.025) (Table 3). In univariate analysis, frail and pre-frail patients were associated with lower odds of seroconversion than robust patients (OR=0.10; 95% CI 0.04–0.24 for frail and OR=0.29; 95% CI 0.13–0.67 for pre-frail patients, respectively). However, only frailty remained associated with a lower chance of developing seroconversion in multivariate analysis (OR=0.25; 95% CI, 0.08–0.80).
Table 2.
Proportion of patients achieving positive immune responses according to frailty status
| Variables | Robust (n=70) | Pre-frail (n=86) | Frail (n=50) | P |
|---|---|---|---|---|
| Anti-spike antibody | ||||
| <50 AU/mL | 9 (12.9%) | 29 (33.7%) | 30 (60.0%) | <0.001 |
| 50–1050 AU/mL | 53 (75.7%) | 49 (57.0%) | 18 (36.0%) | |
| 1050–4160 AU/mL | 7 (10.0%) | 8 (9.3%) | 2 (4.0%) | |
| >4160 AU/mL | 1 (1.4%) | 0 (0.0%) | 0 (0.0%) | |
| Neutralizing antibody | ||||
| NT50 value <2.56 | 45 (64.3%) | 60 (69.8%) | 45 (90.0%) | 0.005 |
| NT50 value ≥2.56 | 25 (35.7%) | 26 (30.2%) | 5 (10.0%) | |
NT50 = 50% neutralizing titer.
Table 3.
Association of frailty phenotype with immune responses to COVID-19 vaccination
| Unadjusted OR (95% CI) | Model 1 OR (95% CI) | Model 2 OR (95% CI) | Model 3 OR (95% CI) | |
|---|---|---|---|---|
| Anti-spike antibody seroconversion (≥ 50 AU/mL) | ||||
| Robust | Reference | Reference | Reference | Reference |
| Pre-frail | 0.29 (0.13–0.67) | 0.35 (0.15–0.86) | 0.44 (0.18–1.09) | 0.61 (0.24–1.60) |
| Frail | 0.10 (0.04–0.24) | 0.15 (0.05–0.41) | 0.21 (0.07–0.62) | 0.25 (0.08–0.80) |
| P for trend | <0.001 | <0.001 | 0.005 | 0.025 |
| Neutralizing antibody production (NT50 value ≥ 2.56) | ||||
| Robust | Reference | Reference | Reference | Reference |
| Pre-frail | 0.78 (0.40–1.53) | 0.71 (0.34–1.48) | 0.67 (0.31–1.44) | 0.76 (0.34–1.69) |
| Frail | 0.20 (0.07–0.57) | 0.18 (0.06–0.58) | 0.16 (0.05–0.54) | 0.13 (0.03–0.48) |
| P for trend | 0.003 | 0.006 | 0.005 | 0.005 |
Model 1 is adjusted for age, sex, and body mass index. Model 2 is adjusted for Model 1 variables, diabetes, and coronary artery disease. Model 3 is adjusted for Model 2 variables, albumin, and lymphocyte count. CI = confidence interval; NT50 = 50% neutralizing titer; OR = odds ratio
With respect to individual components of frailty, all components of the Fried criteria showed a significant negative association with antibody development in univariate analysis (Supplemental Table 2). After accounting for age, sex, and BMI, weight loss, weakness, slow walking speed, and low physical activity remained independently associated with lower odds of seroconversion.
Secondary Outcome
The distribution of vaccine-induced neutralizing antibodies among the three frailty phenotypes followed a similar pattern as that seen in anti-spike antibody responses (Table 2). The overall neutralizing antibody was low, with only 10% frail patients showing positive immunogenicity. Multivariate analyses showed frailty to be associated with a lower chance of developing neutralizing antibodies (OR=0.13; 95% CI, 0.03–0.48; P for trend=0.005) (Table 3).
Safety Outcomes
Solicited local reactions were similar among the three frailty phenotypes (Table 4). Of note, the ChAdOx1 nCoV-19 vaccine was more tolerated among patients who were frail, with 54.3% robust, 68.6% pre-frail, and 44.0% frail patients reporting systemic reactions (P=0.015). No severe adverse events were observed during the 28-day observation period.
Table 4.
Reactogenicity to COVID-19 vaccination according to frailty phenotype
| Robust (n=70) | Pre-frail (n=86) | Frail (n=50) | P | |
|---|---|---|---|---|
| Local reaction, n (%) | 33 (47.1%) | 33 (38.4%) | 14 (28.0%) | 0.105 |
| Pain, n (%) | 32 (45.7%) | 31 (36.0%) | 14 (28.0%) | 0.134 |
| Redness, n (%) | 6 (8.6%) | 9 (10.5%) | 4 (8.0%) | 0.868 |
| Swelling, n (%) | 9 (12.9%) | 12 (14.0%) | 4 (8.0%) | 0.576 |
| Systemic reaction, n (%) | 38 (54.3%) | 59 (68.6%) | 22 (44.0%) | 0.015 |
| Fever, n (%) | 25 (35.7%) | 23 (26.7%) | 12 (24.0%) | 0.310 |
| Headache, n (%) | 13 (18.6%) | 17 (19.8%) | 4 (8.0%) | 0.173 |
| Muscle and joint pain, n (%) | 21 (30.0%) | 20 (23.3%) | 6 (12.0%) | 0.068 |
| Nausea or vomiting, n (%) | 0 (0.0%) | 2 (2.3%) | 2 (4.0%) | 0.277 |
| Abdominal pain, n (%) | 1 (1.4%) | 9 (10.5%) | 1 (2.0%) | 0.021 |
| Diarrhea, n (%) | 5 (7.1%) | 7 (8.1%) | 2 (4.0%) | 0.645 |
| Fatigue, n (%) | 20 (28.6%) | 29 (33.7%) | 13 (26.0%) | 0.603 |
| Rash, n (%) | 1 (1.4%) | 2 (2.3%) | 0 (0.0%) | 0.551 |
Sensitivity Analyses
To assess the reliability of our findings, two sensitivity analyses were conducted. Firstly, we repeated the primary analyses after excluding patients aged 50 or less to reduce heterogeneity of the study population. A total of 186 of subjects were included. The results were similar in the unadjusted and adjusted models. A higher burden of frailty was significantly associated with lower odds of seroconversion (Supplemental Table 3). Secondly, we examined frailty status and serological responses using anti-spike antibody seroconversion at Day 56 as the outcome measure. The results of the analyses were largely consistent with the main findings (Supplemental Table 4). More advanced frailty stages were associated with decreased odds of antibody positivity in univariate analysis (P for trend<0.001).
Discussion
In this prospective cohort of hemodialysis patients, we observed that a higher frailty burden was associated with a blunted humoral response following one dose of the ChAdOx1 nCoV-19 vaccine. These associations were not modified even after adjustment for known predictors of vaccine response. Our study findings have important clinical implications. This highlights the potential role of frailty assessment in identifying hemodialysis patients who are less likely to respond to COVID-19 vaccination.
Our observations are consistent with findings from previous studies showing an impaired immune response to influenza vaccination in frail older individuals. Yao et al. reported that frailty is associated with a reduced humoral response to influenza vaccination in a cohort of community-dwelling older adults (16). Similarly, Andrew et al. demonstrated the important contribution of frailty to the protection conferred by vaccines against influenza hospitalization in older adults (17). Conversely, several studies found no difference in serological responses to influenza vaccination across patients with different frailty levels (7). With respect to COVID-19 vaccination, very few studies have examined the impact of frailty on immunogenicity. In a retrospective study, Kolland et al. showed that peritoneal dialysis patients with frailty defined by the CFS exhibited a significantly worse serological response after receiving 2 doses of the mRNA-1273 vaccine (18). In addition, a weaker COVID-19 vaccine effectiveness among frail patients has been shown in two recent studies. Tang et al. found that mRNA vaccine effectiveness against symptomatic COVID-19 infection was lower in patients with frailty compared to the robust and pre-frail groups in a test-negative case control study using data derived from Veterans Affairs COVID-19 Shared Data Resource (19). They also demonstrated that frailty was associated with lower levels of vaccination protection against COVID-19-associated hospitalization and all-cause death compared with robustness and pre-frailty (20). However, Salmerön et al. observed that in a cohort of 134 nursing home residents, frailty assessed by the FRAIL instrument was not associated with humoral responses following the administration of 2 doses of the BNT162b2 vaccine (21). These contradictory results may be ascribed in part to the frailty assessment methods used among different studies and the heterogeneity of the study population in some cohorts.
One of the mechanisms underlying frailty and a blunted immune response may be related to immunosenescence. Immunosenescence is a process of aging-associated changes affecting both innate and adaptive immune systems. The immunological phenotype of aging includes a progressive reduction in the number of naïve T cells, an increase in the percentage of memory T cells, mostly CD8+, and a shift toward dysfunctional effector T cells, which are responsible for a less effective response to new antigens, as in the case of vaccines (22). Additionally, immunosenescence is accompanied by a state of chronic low-grade inflammation, known as inflammaging. Inflammaging, which manifests as increased serum levels of proinflammatory cytokines, promotes a shift toward the production of myeloid rather than lymphoid precursors in the bone marrow, resulting in defective adaptive immune responses. Previous studies have demonstrated that frail older individuals had higher levels of proinflammatory cytokines, including interleukin-6 and tumor necrosis factor-α, than non-frail individuals (23, 24). Patients with ESKD have a premature aging phenotype characterized by systemic inflammation, muscle wasting, accelerated atherosclerosis, vascular calcification, and frailty (25). Interestingly, serum albumin and the use of erythropoiesis-stimulating agents, which may reflect a state of proinflammation, have been shown to be associated with attenuated immune responses following COVID-19 vaccination in patients treated with dialysis (4, 18). Therefore, immunosenescence may hinder the impaired immune responses to vaccination in frail hemodialysis patients. Nevertheless, more studies are required to investigate this association.
Frailty is extremely common in the dialysis population. Based on the Fried criteria, frailty is present in approximately 35–48% of dialysis patients (26, 27). Importantly, frailty has been identified as a risk factor for poor outcomes following COVID-19 infection in this population in several studies. Hsu et al. reported that markers of frailty, including age, peripheral vascular disease, and decreased mobility, were associated with mortality among individuals with COVID-19 using data from 7948 US dialysis patients from Dialysis Clinic Inc (28). In addition, a recent study by Hendra et al. showed that a higher frailty score defined by the CFS was associated with a higher risk of the need for hospitalization and death due to COVID-19 based on 746 UK patients undergoing regular hemodialysis (29). The results of our study demonstrated that COVID-19 vaccines, although less effective, are safe and well tolerated in frail patients treated with hemodialysis. The extreme risk of severe SARS-CoV-2 infections but blunted immune responses to vaccination highlights the importance of optimizing the vaccination strategy for this population.
Our study has several strengths. We prospectively evaluated frailty using a validated and objective frailty instrument in a relatively homogenous population. In addition, comprehensive analyses of humoral responses were applied to assess immunogenicity following COVID-19 vaccination. However, several limitations should be acknowledged. First, the levels of anti-spike IgG antibody and neutralization titers do not necessarily equate to clinical outcomes. However, accumulating data have indicated a positive association between anti-spike IgG concentrations and vaccine efficacy (30). Second, we only evaluated anti-spike antibody responses at 28 and 56 days after the first dose of vaccination. Indeed, Danthu et al. demonstrated that compared with healthy individuals, hemodialysis patients had a similar pattern of immune response, but at a lower magnitude, with greater heterogeneity and a longer time to maximal response (31). Third, this study was unable to assess how frailty affects immune responses to COVID-19 vaccination in patients with ESKD undergoing hemodialysis and whether hemodialysis affects frailty-related vaccine responses. Finally, our study was limited by the absence of baseline anti-spike antibody titers. Although we recruited patients with no history of prior COVID-19 infection or of COVID-19-like symptoms, there may still be some possibility of asymptomatic COVID-19 infections in the study population. However, a combination of case-based (including contact tracing and quarantine) and population-based (including social distancing and facial masking with wide adherence) interventions has been extraordinarily successful in containing COVID-19 in Taiwan (32).
In conclusion, the prevalence of frailty was high among hemodialysis patients. Immune responses to COVID-19 vaccination are significantly impaired in frail patients treated with hemodialysis. Our findings highlight the importance of incorporating frailty assessment into routine dialysis care to identify patients at risk for suboptimal immune responses to COVID-19 vaccination. In addition, our results suggest that strategies aimed at preventing or attenuating frailty in hemodialysis patients are warranted. Earlier or additional booster vaccination may be particularly advantageous for this population. Future studies are urgently needed to develop optimal COVID-19 vaccination policies among frail hemodialysis patients.
Acknowledgments
The authors appreciate the assistance of the Biobank of Taipei Tzu Chi Hospital for the collection and processing of clinical specimens.
Funding Sources:
This work is supported by grants from Research Projects MOST 111231443-303-009, MOST 111-2314-B-303-032, MOST 112-2314-B-303-014, and MOST 112-2314-B-303-009-MY3 from the National Science and Technology Council, Taiwan and Research Projects TCRD-TPE-109-RT-2, TCRD-TPE-111-03, TCRD-TPE-111-05, and TCMF-CP 111-02 from Taipei Tzu Chi Hospital, Taiwan.
Ethical standards:
This study was approved by the Institutional Review Board of Taipei Tzu Chi Hospital (IRB 10-XD-117).
Conflict of interest:
There are no conflicts of interest.
Electronic Supplementary Material
Supplementary material is available in the online version of this article at https://doi.org/10.1007/s12603-023-1994-x.
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