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Karunathilake RP, Kumara RA, Karunathilaka A, Wazil AWM, Nanayakkara N, Bandara CK, Abeysekera RA, Noordeen F, Gawarammana IB, Ratnatunga CN. 18-month longitudinal SARS COV-2 neutralizing antibody dynamics in haemodialysis patients receiving heterologous 3-dose vaccination (AZD-1222- AZD-1222- BNT162b2) in a lower middle income setting. BMC Nephrol 2024; 25:176. [PMID: 38778281 PMCID: PMC11112903 DOI: 10.1186/s12882-024-03599-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 05/03/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Patients with chronic kidney disease on haemodialysis (HD) were given priority COVID-19 vaccination due to increased disease risk. The immune response to COVID-19 vaccination in patients on HD was diminished compared to healthy individuals in 2-dose studies. This study aimed to evaluate seroconversion rate, neutralizing antibody (nAB) levels and longitudinal antibody dynamics to 3-dose heterologous vaccination against COVID-19 in a cohort of HD patients compared to healthy controls and assess patient factors associated with antibody levels. METHODS This study was a case-control longitudinal evaluation of nAB dynamics in 74 HD patients compared to 37 healthy controls in a low/middle income setting. Corresponding samples were obtained from the two cohorts at time-points (TP) 1-1-month post 2nd dose of AZD1222 vaccine, TP2- 4 months post 2nd dose, TP4- 2 weeks post 3rd dose with BNT162b2 vaccine, TP5-5 months post 3rd dose and TP6-12 months post 3rd dose. Additional data is available at TP0- pre 2nd dose and TP3- 6 months post 2nd dose in HC and HD cohorts respectively. Anti-SARS-CoV-2 nAB were detected using Genscript cPassTM pseudoviral neutralization kit. Demographic and clinical details were obtained using an interviewer administered questionnaire. RESULTS Cohorts were gender matched while mean age of the HD cohort was 54.1yrs (vs HCs mean age, 42.6yrs, p < 0.05). Percentage seroconverted and mean/median antibody level (MAB) in the HD cohort vs HCs at each sampling point were, TP1-83.7% vs 100% (p < 0.05), MAB-450 IU/ml vs 1940 IU/ml (p < 0.0001); TP2-71.4% vs 100%, (p < 0.001), MAB- 235 IU/ml vs 453 IU/ml, (p < 0.05); TP4-95.2% vs 100% (p > 0.05), MAB-1029 IU/ml vs 1538 IU/ml (p < 0.0001); TP5-100% vs 100%, MAB-1542 IU/ml vs 1741IU/ml (p > 0.05); TP6-100% vs 100%, MAB-1961 IU/ml vs 2911 IU/ml (p > 0.05). At TP2, patients aged < 60 years (p < 0.001) were associated with maintaining seropositivity compared to patients > 60 years. CONCLUSION Two dose vaccination of haemodialysis patients provided poor nAB levels which improved markedly following 3rd dose vaccination, the effect of which was long- lasting with high nAB levels in both patients and controls detectable at 1 year follow-up.
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Affiliation(s)
| | - Roshan Athula Kumara
- Department of Microbiology, Faculty of Medicine, University of Peradeniya, Peradeniya, 20400, Sri Lanka
| | - Amali Karunathilaka
- Department of Microbiology, Faculty of Medicine, University of Peradeniya, Peradeniya, 20400, Sri Lanka
| | | | | | | | - Rajitha Asanga Abeysekera
- Department of Medicine, Faculty of Medicine, University of Peradeniya, Peradeniya, 20400, Sri Lanka
- Center for Education, Research and Training in Kidney Disease (CERTKiD), University of Peradeniya, Peradeniya, 20400, Sri Lanka
| | - Faseeha Noordeen
- Department of Microbiology, Faculty of Medicine, University of Peradeniya, Peradeniya, 20400, Sri Lanka
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Hirai K, Shimotashiro M, Okumura T, Ookawara S, Morishita Y. Anti-SARS-CoV-2 spike antibody response to the third dose of BNT162b2 mRNA COVID-19 vaccine and associated factors in Japanese hemodialysis patients. Kidney Res Clin Pract 2024; 43:326-336. [PMID: 38389151 PMCID: PMC11181050 DOI: 10.23876/j.krcp.23.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 09/02/2023] [Accepted: 09/19/2023] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND We assessed the anti-SARS-CoV-2 spike antibody response to the third dose of BNT162b2 mRNA COVID-19 vaccine in Japanese hemodialysis patients and determined factors associated with the anti-SARS-CoV-2 spike antibody titer after the third dose of COVID-19 vaccine. METHODS Overall, 64 patients were enrolled in this single-center, prospective, longitudinal study. Anti-SARS-CoV-2 spike antibody titers were compared between hemodialysis patients and 18 healthcare workers. Multiple linear regression analysis was used to identify factors associated with the anti-SARS-CoV-2 spike antibody titer after the third vaccination. RESULTS There was no significant difference in anti-SARS-CoV-2 spike antibody titer 4 weeks after the third vaccination between hemodialysis patients and healthcare workers (18,500 [interquartile range, 11,000-34,500] vs. 11,500 [interquartile range, 7,918- 19,500], all values in AU/mL; p = 0.17). Uric acid (standard coefficient [β] = -0.203, p = 0.02), transferrin saturation (β = -0.269, p = 0.003), and log-anti-SARS-CoV-2 spike antibody titer 1 week before the third vaccination (β = 0.440, p < 0.001) correlated with the log-anti-SARS-CoV-2 spike antibody titer 4 weeks after the third vaccination. In contrast, only the log-anti-SARS-CoV-2 spike antibody titer 1 week before the third vaccination (β = 0.410, p < 0.001) correlated with the log- anti-SARS-CoV-2 spike antibody titer 12 weeks after the third vaccination. CONCLUSION The anti-SARS-CoV-2 spike antibody titer after the third dose of COVID-19 vaccine was comparable between hemodialysis patients and healthcare workers. Uric acid concentration, transferrin saturation, and anti-SARS-CoV-2 spike antibody titer before the third dose were associated with the anti-SARS-CoV-2 spike antibody titer after the third dose in Japanese hemodialysis patients.
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Affiliation(s)
- Keiji Hirai
- Division of Nephrology, First Department of Integrated Medicine, Saitama Medical Center, Jichi Medical University, Saitama, Japan
| | | | | | - Susumu Ookawara
- Division of Nephrology, First Department of Integrated Medicine, Saitama Medical Center, Jichi Medical University, Saitama, Japan
| | - Yoshiyuki Morishita
- Division of Nephrology, First Department of Integrated Medicine, Saitama Medical Center, Jichi Medical University, Saitama, Japan
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Goggins E, Sharma B, Ma JZ, Gautam J, Bowman B. Humoral immunity trends in a hemodialysis cohort following SARS-CoV-2 mRNA booster: A cohort study. Health Sci Rep 2024; 7:e1858. [PMID: 38357484 PMCID: PMC10864730 DOI: 10.1002/hsr2.1858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 10/24/2023] [Accepted: 01/22/2024] [Indexed: 02/16/2024] Open
Abstract
Background and Aims Patients with end stage kidney disease on hemodialysis are vulnerable to SARS-CoV-2 infection. Current guidelines recommend boosters of SARS-CoV-2 mRNA-based vaccines. The long-term humoral response of hemodialysis patients infected with SARS-CoV-2 after receiving a booster of SARS-CoV-2 mRNA-based vaccines has been incompletely characterized. Here, we determined the long-term humoral response of hemodialysis patients to two and three doses of the Pfizer BioNTech (BNT162b2) mRNA SARS-CoV-2 vaccine and investigated the effect of postbooster SARS-CoV-2 infection on antibody levels over time. Methods Samples were collected on a monthly basis and tested for anti-SARS-CoV-2 antibodies against anti-spike S1 domain. Thirty-five hemodialysis patients were enrolled in the original study and 27 of these received a booster. Patients were followed up to 6 months after the first two doses and an additional 7 months after the third BNT162b2 dose. Results are presented as the internationally harmonized binding antibody units (BAU/mL). Results Antibody level significantly increased from prebooster to 2 weeks postbooster, with a median [25th, 75th percentile] rise from 52.72 [28.55, 184.7] to 6216 [3806, 11,730] BAU/mL in the total population. Of patients with a negative or borderline detectable antibody level 6 months after vaccination who received a third dose, 89% developed positive antibody levels 2 weeks postbooster. Postbooster antibody levels declined an average rate of 29% per month in infection-naïve patients. Antibody levels spiked in patients infected with SARS-CoV-2 after receiving a booster but declined rapidly. No patients infected postbooster required hospitalization. Conclusions A third dose of BNT162b2 restores antibody levels to high levels in dialysis patients but levels decline over time. A third dose did not necessarily prevent infection, but no patients suffered severe infection or required hospitalization. SARS-CoV-2 recovered patients appear to have a blunted rise in antibody levels after a third dose. Although patients infected with SARS-CoV-2 postbooster had an immediate spike in antibody levels, these declined over time.
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Affiliation(s)
- Eibhlin Goggins
- Division of NephrologyUniversity of Virginia School of MedicineCharlottesvilleVirginiaUSA
| | - Binu Sharma
- Division of NephrologyUniversity of Virginia School of MedicineCharlottesvilleVirginiaUSA
| | - Jennie Z. Ma
- Division of NephrologyUniversity of Virginia School of MedicineCharlottesvilleVirginiaUSA
- Public Health SciencesUniversity of Virginia School of MedicineCharlottesvilleVirginiaUSA
| | - Jitendra Gautam
- Division of NephrologyUniversity of Virginia School of MedicineCharlottesvilleVirginiaUSA
| | - Brendan Bowman
- Division of NephrologyUniversity of Virginia School of MedicineCharlottesvilleVirginiaUSA
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Rouphael N, Bausch-Jurken M. COVID-19 Vaccination Among Patients Receiving Maintenance Renal Replacement Therapy: Immune Response, Real-World Effectiveness, and Implications for the Future. J Infect Dis 2023; 228:S46-S54. [PMID: 37539761 PMCID: PMC10401621 DOI: 10.1093/infdis/jiad162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/05/2023] Open
Abstract
Chronic kidney disease affects more than 800 million people worldwide and often progresses to end-stage renal disease, which requires maintenance dialysis. Patients receiving dialysis are at higher risk for severe respiratory infections, including SARS-CoV-2 (the causative agent of COVID-19). In addition, many patients who receive dialysis also receive immunosuppressive treatments for conditions such as systemic vasculitis, systemic lupus erythematosus, or malignancies. Many studies have shown that while mRNA COVID-19 vaccines induce some level of immune response in patients receiving dialysis, the magnitude of response is often lower than that of healthy individuals, and responses rapidly wane. Importantly, the risk of COVID-19-related hospitalization and mortality for patients receiving dialysis is 4- to 8-fold higher compared with the general population. In this article, we summarize recent immunogenicity and real-world outcomes of COVID-19 mRNA vaccination among patients receiving dialysis, with a focus on the 3-dose extended primary series and additional (fourth) doses.
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Affiliation(s)
- Nadine Rouphael
- Correspondence: Nadine Rouphael, MD, Division of Infectious Diseases, Emory University School of Medicine, 2015 Uppergate Dr, Atlanta, GA 30307, USA (); Mary Bausch-Jurken, PhD, Moderna, Inc., 200 Technology Square, Cambridge, MA 02139, USA ()
| | - Mary Bausch-Jurken
- Correspondence: Nadine Rouphael, MD, Division of Infectious Diseases, Emory University School of Medicine, 2015 Uppergate Dr, Atlanta, GA 30307, USA (); Mary Bausch-Jurken, PhD, Moderna, Inc., 200 Technology Square, Cambridge, MA 02139, USA ()
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Ciabattini A, Pastore G, Lucchesi S, Montesi G, Costagli S, Polvere J, Fiorino F, Pettini E, Lippi A, Ancillotti L, Tumbarello M, Fabbiani M, Montagnani F, Medaglini D. Trajectory of Spike-Specific B Cells Elicited by Two Doses of BNT162b2 mRNA Vaccine. Cells 2023; 12:1706. [PMID: 37443740 PMCID: PMC10340653 DOI: 10.3390/cells12131706] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 06/14/2023] [Accepted: 06/21/2023] [Indexed: 07/15/2023] Open
Abstract
The mRNA vaccines for SARS-CoV-2 have demonstrated efficacy and immunogenicity in the real-world setting. However, most of the research on vaccine immunogenicity has been centered on characterizing the antibody response, with limited exploration into the persistence of spike-specific memory B cells. Here we monitored the durability of the memory B cell response up to 9 months post-vaccination, and characterized the trajectory of spike-specific B cell phenotypes in healthy individuals who received two doses of the BNT162b2 vaccine. To profile the spike-specific B cell response, we applied the tSNE and Cytotree automated approaches. Spike-specific IgA+ and IgG+ plasmablasts and IgA+ activated cells were observed 7 days after the second dose and disappeared 3 months later, while subsets of spike-specific IgG+ resting memory B cells became predominant 9 months after vaccination, and they were capable of differentiating into spike-specific IgG secreting cells when restimulated in vitro. Other subsets of spike-specific B cells, such as IgM+ or unswitched IgM+IgD+ or IgG+ double negative/atypical cells, were also elicited by the BNT162b2 vaccine and persisted up to month 9. The analysis of circulating spike-specific IgG, IgA, and IgM was in line with the plasmablasts observed. The longitudinal analysis of the antigen-specific B cell response elicited by mRNA-based vaccines provides valuable insights into our understanding of the immunogenicity of this novel vaccine platform destined for future widespread use, and it can help in guiding future decisions and vaccination schedules.
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Affiliation(s)
- Annalisa Ciabattini
- Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (G.P.); (S.L.); (G.M.); (S.C.); (J.P.); (F.F.); (E.P.); (D.M.)
| | - Gabiria Pastore
- Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (G.P.); (S.L.); (G.M.); (S.C.); (J.P.); (F.F.); (E.P.); (D.M.)
| | - Simone Lucchesi
- Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (G.P.); (S.L.); (G.M.); (S.C.); (J.P.); (F.F.); (E.P.); (D.M.)
| | - Giorgio Montesi
- Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (G.P.); (S.L.); (G.M.); (S.C.); (J.P.); (F.F.); (E.P.); (D.M.)
| | - Simone Costagli
- Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (G.P.); (S.L.); (G.M.); (S.C.); (J.P.); (F.F.); (E.P.); (D.M.)
| | - Jacopo Polvere
- Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (G.P.); (S.L.); (G.M.); (S.C.); (J.P.); (F.F.); (E.P.); (D.M.)
| | - Fabio Fiorino
- Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (G.P.); (S.L.); (G.M.); (S.C.); (J.P.); (F.F.); (E.P.); (D.M.)
- Department of Medicine and Surgery, LUM University “Giuseppe Degennaro”, 70010 Casamassima, Italy
| | - Elena Pettini
- Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (G.P.); (S.L.); (G.M.); (S.C.); (J.P.); (F.F.); (E.P.); (D.M.)
| | - Arianna Lippi
- Infectious and Tropical Diseases Unit, Department of Medical Sciences, University Hospital of Siena, 53100 Siena, Italy; (A.L.); (L.A.); (M.T.); (M.F.); (F.M.)
- Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy
| | - Leonardo Ancillotti
- Infectious and Tropical Diseases Unit, Department of Medical Sciences, University Hospital of Siena, 53100 Siena, Italy; (A.L.); (L.A.); (M.T.); (M.F.); (F.M.)
- Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy
| | - Mario Tumbarello
- Infectious and Tropical Diseases Unit, Department of Medical Sciences, University Hospital of Siena, 53100 Siena, Italy; (A.L.); (L.A.); (M.T.); (M.F.); (F.M.)
- Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy
| | - Massimiliano Fabbiani
- Infectious and Tropical Diseases Unit, Department of Medical Sciences, University Hospital of Siena, 53100 Siena, Italy; (A.L.); (L.A.); (M.T.); (M.F.); (F.M.)
| | - Francesca Montagnani
- Infectious and Tropical Diseases Unit, Department of Medical Sciences, University Hospital of Siena, 53100 Siena, Italy; (A.L.); (L.A.); (M.T.); (M.F.); (F.M.)
- Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy
| | - Donata Medaglini
- Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (G.P.); (S.L.); (G.M.); (S.C.); (J.P.); (F.F.); (E.P.); (D.M.)
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Duan J, Li H, Ma X, Zhang H, Lasky R, Monaghan CK, Chaudhuri S, Usvyat L, Gu M, Guo W, Kotanko P, Wang Y. Predicting SARS-CoV-2 infection among hemodialysis patients using multimodal data. FRONTIERS IN NEPHROLOGY 2023; 3:1179342. [PMID: 37675373 PMCID: PMC10479652 DOI: 10.3389/fneph.2023.1179342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 04/28/2023] [Indexed: 09/08/2023]
Abstract
Background The coronavirus disease 2019 (COVID-19) pandemic has created more devastation among dialysis patients than among the general population. Patient-level prediction models for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are crucial for the early identification of patients to prevent and mitigate outbreaks within dialysis clinics. As the COVID-19 pandemic evolves, it is unclear whether or not previously built prediction models are still sufficiently effective. Methods We developed a machine learning (XGBoost) model to predict during the incubation period a SARS-CoV-2 infection that is subsequently diagnosed after 3 or more days. We used data from multiple sources, including demographic, clinical, treatment, laboratory, and vaccination information from a national network of hemodialysis clinics, socioeconomic information from the Census Bureau, and county-level COVID-19 infection and mortality information from state and local health agencies. We created prediction models and evaluated their performances on a rolling basis to investigate the evolution of prediction power and risk factors. Result From April 2020 to August 2020, our machine learning model achieved an area under the receiver operating characteristic curve (AUROC) of 0.75, an improvement of over 0.07 from a previously developed machine learning model published by Kidney360 in 2021. As the pandemic evolved, the prediction performance deteriorated and fluctuated more, with the lowest AUROC of 0.6 in December 2021 and January 2022. Over the whole study period, that is, from April 2020 to February 2022, fixing the false-positive rate at 20%, our model was able to detect 40% of the positive patients. We found that features derived from local infection information reported by the Centers for Disease Control and Prevention (CDC) were the most important predictors, and vaccination status was a useful predictor as well. Whether or not a patient lives in a nursing home was an effective predictor before vaccination, but became less predictive after vaccination. Conclusion As found in our study, the dynamics of the prediction model are frequently changing as the pandemic evolves. County-level infection information and vaccination information are crucial for the success of early COVID-19 prediction models. Our results show that the proposed model can effectively identify SARS-CoV-2 infections during the incubation period. Prospective studies are warranted to explore the application of such prediction models in daily clinical practice.
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Affiliation(s)
- Juntao Duan
- Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, United States
| | - Hanmo Li
- Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, United States
| | - Xiaoran Ma
- Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, United States
| | - Hanjie Zhang
- Renal Research Institute, New York NY, United States
| | - Rachel Lasky
- Fresenius Medical Care, Global Medical Office, Waltham, MA, United States
| | | | - Sheetal Chaudhuri
- Fresenius Medical Care, Global Medical Office, Waltham, MA, United States
- Division of Nephrology, Maastricht University Medical Center, Maastricht, Netherlands
| | - Len A. Usvyat
- Fresenius Medical Care, Global Medical Office, Waltham, MA, United States
| | - Mengyang Gu
- Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, United States
| | - Wensheng Guo
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia PA, United States
| | - Peter Kotanko
- Renal Research Institute, New York NY, United States
- Icahn School of Medicine at Mount Sinai, New York NY, United States
| | - Yuedong Wang
- Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, United States
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Notarte KI, Catahay JA, Peligro PJ, Velasco JV, Ver AT, Guerrero JJ, Liu J, Lippi G, Benoit SW, Henry BM, Fernández-de-Las-Peñas C. Humoral Response in Hemodialysis Patients Post-SARS-CoV-2 mRNA Vaccination: A Systematic Review of Literature. Vaccines (Basel) 2023; 11:vaccines11040724. [PMID: 37112636 PMCID: PMC10142871 DOI: 10.3390/vaccines11040724] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/20/2023] [Accepted: 03/22/2023] [Indexed: 04/29/2023] Open
Abstract
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has infected over 600 million individuals and caused nearly 7 million deaths worldwide (10 January 2023). Patients with renal disease undergoing hemodialysis are among those most adversely affected, with an increased predisposition to SARS-CoV-2 infection and death. This systematic review aimed to pool evidence assessing the humoral response of hemodialysis patients (HDP) post-mRNA SARS-CoV-2 vaccination. A systematic search of the literature was performed through MEDLINE, CINAHL, PubMed, EMBASE, and Web of Science databases, as well as medRxiv and bioRxiv preprint servers up to 10 January 2023. Cohort and case-control studies were included if they reported an immune response in one group of patients undergoing hemodialysis who received mRNA SARS-CoV-2 vaccination compared with another group of patients receiving the same vaccine but not on hemodialysis. The methodological quality was assessed using the Newcastle-Ottawa Scale. Meta-analysis was not deemed appropriate due to the high heterogeneity between studies. From the 120 studies identified, nine (n = 1969 participants) met the inclusion criteria. Most studies (n = 8/9, 88%) were of high or medium methodological quality (≥6/9 stars). The results revealed that HDP developed lower antibody levels across all timepoints post-vaccination when compared with controls. Patients with chronic kidney disease elicited the highest antibody immune response, followed by HDP and, lastly, kidney transplant recipients. Overall, post-vaccination antibody titers were comparatively lower than in the healthy population. Current results imply that robust vaccination strategies are needed to address waning immune responses in vulnerable populations.
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Affiliation(s)
- Kin Israel Notarte
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Jesus Alfonso Catahay
- Department of Medicine, Saint Peter's University Hospital, New Brunswick, NJ 08901, USA
| | | | | | - Abbygail Therese Ver
- Faculty of Medicine and Surgery, University of Santo Tomas, Manila 1008, Philippines
| | - Jonathan Jaime Guerrero
- Learning Unit IV, College of Medicine, University of the Philippines Manila, Manila 1001, Philippines
| | - Jin Liu
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Giuseppe Lippi
- Section of Clinical Biochemistry, University of Verona, 37129 Verona, Italy
| | - Stefanie W Benoit
- Clinical Laboratory, Division of Nephrology and Hypertension, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45103, USA
| | - Brandon Michael Henry
- Clinical Laboratory, Division of Nephrology and Hypertension, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - César Fernández-de-Las-Peñas
- Department of Physical Therapy, Occupational Therapy, Physical Medicine and Rehabilitation, Universidad Rey Juan Carlos, 28922 Madrid, Spain
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Real-World Effectiveness of SARS-CoV-2 Vaccine Booster in Hemodialysis Patients with COVID-19 Receiving Molnupiravir. Viruses 2023; 15:v15020543. [PMID: 36851757 PMCID: PMC9967999 DOI: 10.3390/v15020543] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/13/2023] [Accepted: 02/14/2023] [Indexed: 02/18/2023] Open
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine booster is one of the most essential strategies against coronavirus disease 2019 (COVID-19) in the era of emerging variants. However, the effectiveness of SARS-CoV-2 vaccine boosters has not much been investigated in hemodialysis (HD) patients receiving oral antiviral agents. In this retrospective study involving 258 HD patients with COVID-19 receiving molnupiravir, we stratified the study cohort according to vaccination status and compared the baseline characteristics and risks of 30-day composite events (COVID-19-related acute care visits, hospitalization, or mortality) among groups. Our analysis demonstrated that the SARS-CoV-2 vaccine boosters markedly decreased the risk of composite events in HD patients (hazard ratio (95% confidence interval), 0.163 (0.063-0.423) for three vs. ≤ two doses of vaccination, p < 0.001; 0.309 (0.115-0.830) for four vs. ≤ two doses of vaccination, p = 0.020). The benefits of vaccine boosters were similar between patients receiving mRNA-based and protein-based boosters and between those with post-booster intervals of ≤ 120 and > 120 days. In conclusion, for HD patients with initially mild or asymptomatic COVID-19 receiving molnupiravir, the benefits of SARS-CoV-2 vaccine boosters are prominent, irrespective of booster vaccine types.
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