https://orcid.org/0000-0001-5712-4272
Figures
Abstract
To investigate the association between biochemical and blood parameters collected before the pandemic in a large cohort of Italian blood donors with the risk of infection and severe disease. We also focused on the differences between the pre- and post-Omicron spread in Italy (i.e., pre- and post-January 01, 2022) on the observed associations. We conducted an observational cohort study on 13750 blood donors was conducted using data archived up to 5 years before the pandemic. A t-test or chi-squared test was used to compare differences between groups. Hazard ratios with 95% confidence intervals for SARS-CoV-2 infection and severe disease were estimated using Cox proportional hazards models. Subgroup analyses stratified by sex, age and epidemic phase of first infection (pre- and post-Omicron spread) were examined. We confirmed a protective effect of groups B and O, while groups A and AB had a higher likelihood of infection and severe disease. However, these associations were only significant in the pre-Omicron period. We found an opposite behavior after Omicron spread, with the O phenotype having a higher probability of infection. When stratified by variant, A antigen appeared to protect against Omicron infection, whereas it was associated with an increased risk of infection by earlier variants. We were able to stratify for the SARS CoV-2 dominant variant, which revealed a causal association between blood group and probability of infection, as evidenced by the strong effect modification observed between the pre- and post-Omicron spread. The mechanism by which group A acts on the probability of infection should consider this strong effect modification.
Citation: Marraccini C, Merolle L, Schiroli D, Razzoli A, Gavioli G, Iotti B, et al. (2023) A cohort study on the biochemical and haematological parameters of Italian blood donors as possible risk factors of COVID-19 infection and severe disease in the pre- and post-Omicron period. PLoS ONE 18(11): e0294272. https://doi.org/10.1371/journal.pone.0294272
Editor: Vittorio Sambri, University of Bologna / Romagna Local Health Authority, ITALY
Received: July 17, 2023; Accepted: October 27, 2023; Published: November 21, 2023
Copyright: © 2023 Marraccini et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The minimal data set used to prepare the figures of the paper is available in aggregate form in the Supplementary Information. According to Italian law, anonymized raw data cannot be made publicly available if there is potential for the re-identification of individuals (https://www.garanteprivacy.it). Furthermore, property of the data remains of the blood donor who gave consent to use them for the objective of the study. Thus, raw data cannot be shared publicly. However, the data underlying this study are available on request to researchers who meet the criteria for access to confidential data (even if anonymous data are provided, they should be published in aggregated form) and for studies with objectives consistent with those of the original one. In order to get data, approval must be obtained from the Area Vasta Emilia Nord (AVEN) Ethics Committee, who would check the consistency of the objective and planned analyses and would then authorize us to provide aggregated or anonymized data. Data access requests should be addressed to the Ethics Committee at CEReggioemilia@ausl.re.it, as well as to the Principal Investigator Dr. Chiara Marraccini (chiara.marraccini@ausl.re.it), who are the data guardians.
Funding: This study was partially supported by the Centro Regionale Sangue Emilia Romagna and by Italian Ministry of Health – Ricerca Corrente Annual Program 2024. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Since the COVID-19 pandemic outbreak in early 2020, many studies have attempted to correlate the risk of developing severe symptoms with a heterogeneous range of parameters. Age, pre-existing conditions, red blood cells (RBC), and platelet count (PLT) have been immediately proposed as factors significantly influencing COVID-19 severity [1]. Unexpectedly, other less evident features have emerged as possible prognostic factors: among these, ABO blood group has been associated with both the risk of infection and disease severity [2, 3], while the RBCs distribution width (RDW) has been strongly correlated with disease severity and mortality [3, 4].
Although essential for assessing potential transmission in new areas and preventing viral spread [5], identifying factors that determine the risk of SARS-CoV-2 infection is more complicated than identifying prognostic factors. The reason lies mainly in the lack of a large representative sample of the general population for which we have accessible clinical data in the period immediately preceding (1–2 years) SARS-CoV-2 spread. Hospital-based clinical databases can be used to construct retrospective cohort studies, but they generally refer to individuals suffering from various diseases that are not representative of the general population. In this sense, the UK Biobank (https://www.ukbiobank.ac.uk) [6], which collects the baseline and clinical records of biological and medical data from half a million people aged 40–69 recruited between 2006 and 2010, is a unique and valuable source of information and has been extensively used to screen for possible markers of COVID-19 severity and risk of infection [7]. Albeit important, the UK Biobank is limited to middle-aged and elderly individuals and mainly refers to values collected at the baseline (e.g., more than ten years ago).
An alternative source of information may be the blood donor registries being developed worldwide by local Transfusion Medicine Units. Despite the arrival of the pandemic deeply impacted donor recruitment routine activity [8], blood donor registries have been immediately exploited to identify possible correlations of the ABO blood group with COVID-19 severity and risk of infection [9–11]. Despite the mechanisms underlying the relationship between ABO blood group and susceptibility to infection are not fully understood, there is accumulating evidence that blood group A individuals are at higher risk of infection than non-A individuals, whereas O group individuals are least susceptible to infection [9]. However, the level of evidence is low, and these observations need further validation [9, 12]. Few studies have attempted to correlate Rh [10] and other antigens [11] with COVID-19 progression and severity. Other parameters routinely collected from blood donors (such as blood count, haemoglobin, cholesterol metabolism, iron metabolism, creatinine, aminotransferases, glycaemia and body mass index) have been poorly studied as well.
We aimed to investigate the association between biochemical and blood parameters collected before the pandemic in a large cohort of blood donors with the risk of infection and severe disease. We also focused on the differences between the pre- and post-Omicron period on the observed associations.
Materials and methods
Study population and study setting
This is a retrospective cohort study on blood donors of the Reggio Emilia province, in Northern Italy. Reggio Emilia has 531,751 inhabitants and there are six hospitals. By February 28, 2022 there were 121,154 ascertained cases of COVID-19 (22.5% of the total Reggio Emilia population) and a 60% three-doses vaccination coverage [13].
Six donor centres are located within the hospitals, and 21 collection points are run by the local voluntary association. Reggio Emilia accounts for over 14500 periodic blood donors, which must satisfy specific requirements: age between 18 and 65 years; weight ≥ 50 kg; systolic blood pressure ≤ 180 mmHg; diastolic blood pressure ≤ 100 mmHg; regular cardiac pulses (between 50 and 100 beats/min); Hb ≥ 13.5 g/dl for men and ≥ 12.5 g/dl for women [14]. Periodic donors were defined as those that donated at least once every two years in the five years pre-pandemic considered, and perform at least once a year: blood pressure, glycaemia, creatinine, alanine-amino-transferase (ALT), total cholesterol, HDL, LDL, triglycerides, total proteins and ferritin; and at each donation: complete blood count, HbsAg, Anti-HCV antibodies, HIV test, Anti-Treponema Palladium antibodies, HCV, HBV and HIV NAT, ABO, Rh and Kell antigens. Weight, height and body mass index (BMI) are also collected periodically. ABO, Rh and Kell are re-assessed at every donation, while complete phenotype characterisation (which includes Duffy, Kidd, MNS and Cw antigens) is performed only on O-group donors at their first donation. According to our Transfusion Medicine Unit protocols, blood grouping was performed on fully automated immunohematology system Galileo Neo (Immucor Inc., Norcross, GA, USA) using commercially available antisera’s (Immucor Inc., Norcross, GA, USA). Phenotyping was based on Capture technology (solid phase adherence).
Only periodic donors already active before the pandemic and their blood test data performed between February 1, 2015 and January 31, 2020, were included in the study.
In this study, the pre-Omicron period corresponds to the timeframe between February 20, 2020 and December 20, 2021, when the Emilia-Romagna region faced three main COVID-19 waves, driven by the SARS-CoV-2 wild-type, the Alpha (Pango lineage designation B.1.1.7), and Delta (Pango lineage designation B.1.617.2) variant [12]; the Omicron period corresponds to the timeframe between from January 01, 2022 and February 28, 2022, represented by the fourth wave driven by the Omicron BA.1 variant [12].
Data source
Data concerning the Transfusion Medicine Unit procedures and blood tests, performed on periodic donors, were collected from the internal database (Eliot, Engineering Ingegneria Informatica S.p.A., Italy), which is the central donor registry to which every blood centre of the Reggio Emilia province collects the information concerning donors and donations. The database was accessed on 14 July 2022. Date of symptom onset, diagnosis, hospitalization, and death were retrieved from the COVID-19 Surveillance Registry, implemented in each Local Health Authority. Data from the COVID-19 Surveillance Registry were accessed on 25 July 2022 and linked with the blood test data. Only the PI and co-PI accessed the databases, and all data on recruited donors were anonymised before the analysis. Outcomes of interest were: being tested for SARS-CoV-2 (at least one RT-PCR or antigen test performed), resulting positive for SARS-CoV-2 (at least one test resulted positive), and severe disease (SARS-CoV-2 infection followed by COVID-19 leading to hospitalization within 28 days from diagnosis or death within 90 days). The study follow-up started from February 20, 2020, and ended on February 28, 2022.
Statistical analyses
Continuous variables are reported as mean and standard deviation (SD) and categorical variables as proportions. With regard to the variables collected several times for the same donor during the 5 years preceding the pandemic, the mean value was taken into account. The inter-group differences were compared by using a t-test or chi-square test. Cox proportional hazard models were used to estimate hazard ratios (HR) with 95% confidence intervals (95% CI) for SARS-CoV-2 infection and for severe disease. For continuous variables, the HRs are computed for an increase from 25 to 75 centile of the exposure variable. For variables showing association, we also explored some subgroup analysis stratifying by sex, age (<50 and > = 50), and epidemic phase of first infection (pre-Omicron period, i.e., from February 20, 2020 to December 20, 2021 and Omicron period, i.e. from January 01, 2022 to February 28, 2022). Given the descriptive nature and hypothesis generation scope of the study, we did not fix a significance threshold. Confidence intervals should be interpreted as a description of the precision of the estimate, as well as p-values should be considered as continuous variables, not as formal statistical tests. Models were adjusted for age, sex, and vaccination history. STATA v. 16.0 was used for all analyses.
Ethics approval
The Ethics Committee of the Area Vasta Emilia Nord approved the study on 8 September 2021 (no. 2021/0111394). The Ethics Committee exempted the investigators from the obligation to collect written informed consent from all donors, the consent was asked only to those who attended a blood donation during the recruitment period (from 2 May 2022 to 1 June 2022). All donors in the province of Reggio Emilia were also informed of the study with a personal e-mail and SMS, through the usual communication channels used to advise donors by the local AVIS association personnel, and the opportunity to opt-off was offered simply by answering with an SMS or e-mail. The data from donors who chose not to participate either by refusing to sign the consent or by requesting an opt-off were not used.
Results
Starting from the 14,445 donors attending Reggio Emilia donor centres (and after the exclusion of non-periodic donors), 13750 participants were included in the study (Table 1). Of these, 9528 were males and 4222 were females. By February 28, 2022 (which corresponds to the end of the post-Omicron period considered in this study), 864 donors were still unvaccinated (6.3% of the total), while 9591 (69.7%) had already received three doses. A total number of 7976 donors (58%) were tested for SARS-CoV-2 infection and positivity was registered for 3690 donors (26.8%): of these, 73 (0.5%) experienced the severe disease, which led to hospitalisation and/or death. Infections were equally distributed between pre- and post-Omicron spread (1189 vs. 1169, S2 Table), while all the severe diseases occurred in the pre-Omicron period.
SARS-CoV-2 risk of infection
In the overall donor population, vaccination was associated to a lower probability of infection at increasing doses, with an almost null risk of severe disease at three doses (Fig 1 and S1 Table).
The protection of vaccines against the risk of infection decreased after Omicron diffusion (Fig 2 and S2 Table), for which on average the same protection was reached with at least one more dose than before. The protection against the risk of infection given by the vaccination was more evident in donors above the age of 50 (S4 Table).
High RDW was found to be weakly associated with decreased risk of infection (HR = 0.96, 95% CI 0.92 to 0.99, Fig 1 and S1 Table). This association appears to be mainly determined by the over-50 donor population (HR = 0.93, 95% CI 0.87 to 0.99, S4 Table).
The increase in the total amount of white blood cells (WBCs) was weakly associated with the risk of infection (HR = 0.95, 95% CI 0.89 to 1.01, Fig 1 and S1 Table); nevertheless, the difference was compatible with chance. The association was stronger in donors over 50 years of age (HR = 0.88, 95% CI 0.81 to 0.95, S4 Table). Among the leucocyte subpopulations monocytes, high levels of eosinophils and basophils were inversely associated with infection with the pre-Omicron period (HR = 0.94 for monocytes, HR = 0.95 for eosinophils and basophils, Fig 2 and S2 Table), while after Omicron spread only the association is only with neutrophils subpopulation (HR = 0.95, 95% CI 0.90 to 1.01, Fig 2 and S2 Table). It is worth noting that all these associations are compatible with chance.
Among blood parameters, high creatinine was associated with an increased risk of infection overall (HR = 1.06, 95% CI 1.00 to 1.12), in males (S3 Table), and over the age of 50 (S4 Table), whereas, again, we observed no major differences when looking at the Omicron variant (Fig 2). Conversely, high HDL cholesterol was associated with a lower risk of SARS-Cov-2 infection (HR = 0.92, 95% CI 0.88 to 0.97, S1 Table and Fig 1).
The ABO blood group was not associated with SARS-CoV-2 positivity in the whole study period (Fig 3). The association with infection emerged after stratifying by period: in the pre-Omicron period, the A and AB groups were associated with an increased risk of infection, while post-Omicron spread the O group showed increased risk compared to B, AB, and mostly A. Among the Rh antigens, the ccDEE was associated with higher incidence (HR 1.34, 95% CI 1.04 to 1.72). Among the genes, Ss heterozygotes showed a lower probability of infection.
Risk of COVID-19 severe disease
The severe disease mainly occurred in older donors (mean age 54.6±7.5 vs 44.1±13.0 in the whole donor population), on average 8.7 kg heavier (86.2±13.5 vs 77.5±14.0 kg) and with slightly higher blood pressure (both systolic and diastolic, Table 1). The Cox model adjusted for sex, age, and vaccination history (Fig 1 and S1 Table) confirmed an independent association with COVID-19 severity only for age, weight (HR 1.08 per year increase, 95%CI 1.06–1.11; and 1.04 per kg increase, 95%CI 1.02–1.05), and vaccination.
High RBCs (Table 1) were associated with the risk of severe disease but the estimate was extremely imprecise (HR = 1.35, 95% CI 0.93 to 1.95, Fig 1). Other red blood cell indexes showed weak and inconsistent associations with severe disease, all compatible with random fluctuations. Mean platelet volume (MPV) was found to behave in the opposite way (Table 1), being its increase associated with higher risk (HR = 1.19, 95% CI 1.01 to 1.41, Fig 1 and S1 Table).
Donors that experienced severe disease also showed higher total cholesterol (209.6±33.4 vs 195.7±34.5 mg/dL, Table 1) and triglycerides (115.3±54.9 vs 95.2±59.9 mg/dL, Table 1), whereas HDL was slightly lower (53.8±13.2 vs 57.7±13.4 mg/dL, Table 1). According to the Cox regression model, however, the association with creatinine became extremely imprecise (HR = 2.90, 95% CI 0.48 to 17.41), while the role of total cholesterol and HDL were confirmed.
When considering the totality of recruited subjects, the ABO blood group results are associated with COVID-19 severity (p-value = 0.051), with a higher occurrence of group A among the hospitalized donors. The risk of developing severe disease was significantly higher for donors bearing the A antigen (HR = 2.03 for group A; HR = 1.92 for group AB), compared to those that express only the B antigen or to those with the ABO blood type O (Fig 3 and S1 Table).
Regarding the blood subgroups, estimates are too imprecise to give any suggestion about associations. For many subgroups, zero events were observed. Only for Jka-b+ phenotype an increase in the occurrence of severe disease, based on only 12 cases, was observed but the estimate is very imprecise (HR = 2.12, 95% CI 0.95 to 4.72). Since no hospitalization or death occurred in the recruited population during the Omicron period, it was not possible to conduct stratified analyses on the risk of severe disease.
Discussion
We examined the association between the demographic and biochemical blood parameters, collected from a cohort of donors up to 5 years before the pandemic, with the probability of testing positive for SARS-CoV-2 and of being hospitalized for COVID-19. Although quite representative of the general population, blood donors have often been shown to deviate from the distribution of the general population due to their healthier condition [15, 16]. This aspect is a major strength of our cohort, as it allowed us to minimize the effect of comorbidities and population heterogeneity.
During the study period, more than half of the cohort was tested and 26% tested positive for SARS-CoV-2 at least once, a rate closely resembling the general population of similar age (24%) [12]. We observed small differences in testing propensity, suggesting that the probability of receiving a COVID-19 diagnosis in our cohort is similar to that of the general population. Infections were evenly distributed between pre- and post-Omicron spread. This was expected because, although the two time periods considered are significantly different (22 months for the pre-Omicron vs. 2 months for the post-Omicron period), the number of infections recorded in the province of Reggio Emilia during the fourth pandemic wave (corresponding to the spread of Omicron BA.1) was the same as, if not greater than, the sum of infections recorded in the previous 3 waves (determined by the spread of the wild-type, Alpha and Delta variants) [13]. In terms of severe disease, we observed only 73 hospitalizations and 1 death, only three hospitalizations occurred in the Omicron period.
We observed a weak protective effect of high RDW and WBCs against infection in the pre-Omicron period. The effect of blood group changed between pre- and post-Omicron diffusion: group A donors had a higher risk of infection in the pre-Omicron period, but a lower risk in the Omicron period. Other parameters showed weak and highly uncertain associations or no association.
To our knowledge, this is the first time that an inverse association between RDW and risk of infection, independently of virus variant, has been observed. Since RDW values are strictly related to erythropoiesis efficiency and can be enhanced by physical exercise or anaemic conditions [17], thus we cannot exclude that the observed association might be confounded by different social behaviours that change the probability of being exposed to the virus.
We observed a weak but consistent inverse association between WBC count and the probability of infection. It is important to note that the association cannot be due to pathologically low levels, as WBCs must be within the normal range to be eligible for donation. All WBC subpopulations go in the same direction, even if the observed differences in probability of infection are very small and each of them compatible with a random fluctuation; nevertheless, the whole pattern suggests that it is difficult to identify only one sub-group to explain the association with WBCs. High eosinophils, found in the airways of asthmatic patients, have already been suggested to play a protective role against SARS-CoV-2 infection and COVID-19 severity [18], possibly by counteracting the exacerbated inflammatory response typical of the severe COVID-19 phenotype [19]. Intriguingly, after the diffusion of the Omicron variant, the association with WBC subpopulations is lost, except for neutrophils. This could be due to the different Omicron biology and interaction with the host immune system and respiratory tract [20].
As expected, vaccination was protective against both infection and severe disease. We could not test for a difference before and after the spread of the Omicron variant because no hospitalizations or deaths occurred after 20 December 2021, when most of the cohort had already been vaccinated. Nevertheless, our results confirm the differences in protection against infection observed between the pre- and post-Omicron [21]. We observed higher vaccination protection in older people. This may be because older people (>50) were vaccinated earlier, during the peak of the Alpha variant that reached Italy in spring 2021, while younger people (<50) were vaccinated between summer and autumn, when the peak decreased, and the herd immunity increased. In addition, a larger proportion of the <50 years old were vaccinated during the Omicron period.
With the exception of vaccination, we observed only a weak association with the probability of infection. HDL and systolic pressure were inversely associated, while weight, triglycerides, ferritin, and creatinine high levels were associated positively associated. Subgroup analyses suggest that creatinine is associated only in older males. The estimates are rather precise and we can exclude large effects that were not observed by chance. Consistent with our study, serum creatinine was previously found to be associated with disease severity [22].
Body weight, low HDL cholesterol, and group A, were associated with a higher risk of severe disease. The risk of severe disease was also observed to be directly associated with triglycerides (HR = 1.11, 95% CI 1.00 to 1.24, S1 Table) and inversely associated with HDL cholesterol (HR = 0.61, 95% CI 0.42 to 0.88, S1 Table), as expected in a healthy population cohort.
We confirmed a protective effect of groups B and O [9, 23], while groups A and AB have a higher probability of infection and severe disease only in the pre-Omicron period. Surprisingly, we observed an opposite behaviour of blood groups after Omicron spread, with the O phenotype having a higher probability of infection than A. Since early works on SARS-CoV-2, the ABO group has been extensively investigated for its possible role in COVID-19 susceptibility [24]. Although the majority of studies have demonstrated a protective effect of blood group O compared with non-O on both the risk of infection and disease severity, the results have often been conflicting. These controversial observations may be partly explained by the variable distribution of the ABO phenotypes across geographical areas, human populations [25], and, finally, in light of our results, the dominant viral variants in the study period.
ABO antigens are highly abundant not only on the surface of RBCs but also on the epithelial cells in contact with the external environment [26]. Some authors suggested that A antigens expressed on the viral envelope could be recognized by anti-A antibodies in non-A individuals (and particularly in O phenotype individuals, who have the highest anti-A antibody titre) [27, 28]. Others found a similarity between the glycan structures on the SARS-CoV-2 S protein and the domains recognized by anti-A antibodies and hypothesized that the reduced viral infection may be the result of the antibody-mediated blockade of the interaction between the virus and the angiotensin-converting enzyme 2 (ACE2) receptor, thus preventing entry into the lung epithelium [22, 29]. The spread of the Omicron variant has been favoured by a more efficient transmission capacity compared to the Delta variant [22]. The structural differences between the two variants, together with an altered entry mechanism [19], account for immune and antibody escape and may also explain the different associations of this infection with blood groups.
Similarly, we observed a slight difference in the probability of infection for the ccDEE Rh specific antigen phenotype, even if the p-value reached the 5% threshold usually considered to be statistically significant, we cannot exclude that this was due to chance, given the large number of comparisons made and the fact that this association had previously been excluded in a similar cohort [11]. When examining the MNS blood group, we also observed an association for the S antigen (GYPB gene), for which we observed a borderline statistically significant protective effect of the Ss phenotype compared to both SS and ss, we did not find any other study confirming our observation [11].
The risk of hospitalization observed in this donor cohort (0.5%) is much lower than that observed in the general population of the province of Reggio Emilia during the study period (1.8%) [12]. The low hospitalization rate makes the study underpowered to observe even large differences between groups, and we cannot perform a stratified analysis for the Omicron period, because we have almost no hospitalizations after the decline of the Delta variant.
Our results confirm previous literature observations on women (who have a lower risk of developing severe disease than men) and age, which is the strongest determinant with an 8% increase in the probability of infection per year increase. We also confirmed the association with body weight and total cholesterol, as well as the protective effect of HDL.
While a high post-infection RDW is known to be an independent predictor of worse outcomes in patients with respiratory tract infections and has also been associated with adverse COVID-19 progression [30], our data suggest that RDW values observed prior to disease onset are not associated with a higher risk of severe disease. Therefore, RDW can be considered as a possible prognostic biomarker once the disease symptoms have occurred, but this parameter is not a risk factor.
We also observed an association of the Jka-b+ phenotype with COVID-19 severity. Kidd variants implication in pathogens response has been previously modeled [31], while jka and jkb alleles have been identified as risk and protective, respectively, in bladder cancer [32]. Nevertheless, anti-Jkb antibodies only occur after an alloimmunization, an event that is very rare in a healthy donor population. Furthermore, we do not see any excess risk in Jka+b+ phenotype. Therefore, association cannot be due to a protective effect of anti-Jkb antibodies and chance is a plausible explanation.
Conclusion
In our study of a blood donor cohort, we had the opportunity to stratify for the SARS-CoV-2 dominant variant, which brought to light a novelty regarding the possible impact of blood type on viral infection. We showed a weak association between the blood group and the probability of infection, which is likely to be causal, both because our results are consistent with previous findings [9] and because we observed a strong effect modification between the pre- and post-Omicron spread. The mechanism by which group A affects the probability of infection should now be considered in light of this strong effect modification.
Supporting information
S1 Table. Cox proportional regression analysis adjusted by age, sex, and vaccination status, according to donor features, blood parameters, and blood group.
https://doi.org/10.1371/journal.pone.0294272.s001
(DOCX)
S2 Table. Cox proportional regression analysis adjusted by sex, age, and vaccination status in donors tested positive for SARS-CoV-2 before and after December 20, 2021 (pre- and post-Omicron diffusion, respectively).
https://doi.org/10.1371/journal.pone.0294272.s002
(DOCX)
S3 Table. Cox proportional regression analysis adjusted by age, sex, and vaccination status in male and female donors.
https://doi.org/10.1371/journal.pone.0294272.s003
(DOCX)
S4 Table. Cox proportional regression analysis adjusted by age, sex, and vaccination status in donors under (<50) and over (> = 50) the age of 50.
https://doi.org/10.1371/journal.pone.0294272.s004
(DOCX)
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