Association between COVID-19 vaccination and sudden death in apparently healthy younger individuals: A population-based case-control study

Husam Abdel-Qadir; Hardil Anup Bhatt; Sarah Swayze; Michael Paterson; Dennis T Ko; David N Juurlink; Jeffrey C Kwong

doi:10.1371/journal.pmed.1004924

. 2026 Mar 19;23(3):e1004924. doi: 10.1371/journal.pmed.1004924

Association between COVID-19 vaccination and sudden death in apparently healthy younger individuals: A population-based case-control study

Husam Abdel-Qadir ^1,^2,^3,^*,^#, Hardil Anup Bhatt ^4,^5,^#, Sarah Swayze ³, Michael Paterson ^3,^6,⁷, Dennis T Ko ^3,^7,^8,⁹, David N Juurlink ^3,¹⁰, Jeffrey C Kwong ^3,^11,^12,^13,^14,¹⁵

Editor: Rebecca F Grais¹⁶

¹Women’s College Hospital, Toronto, Ontario, Canada

²Peter Munk Cardiac Centre, University Health Network, Toronto, Ontario, Canada

³ICES, Toronto, Ontario, Canada

⁴Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada

⁵Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada

⁶Department of Family Medicine, McMaster University, Hamilton, Ontario, Canada

⁷Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada

⁸Department of Medicine, University of Toronto, Toronto, Ontario, Canada

⁹Schulich Heart Centre, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada

¹⁰Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada

¹¹Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada

¹²Public Health Ontario, Toronto, Ontario, Canada

¹³University Health Network, Toronto, Ontario, Canada

¹⁴Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada

¹⁵Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, Ontario, Canada

¹⁶Pasteur Network, FRANCE

The authors have declared that no competing interests exist.

^✉

* E-mail: h.abdel.qadir@utoronto.ca

Contributed equally.

Roles

Husam Abdel-Qadir: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Visualization, Writing – original draft, Writing – review & editing

Hardil Anup Bhatt: Investigation, Visualization, Writing – original draft, Writing – review & editing

Sarah Swayze: Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing – review & editing

Michael Paterson: Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing – review & editing

Dennis T Ko: Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing – review & editing

David N Juurlink: Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing – review & editing

Jeffrey C Kwong: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Writing – review & editing

Rebecca F Grais: Academic Editor

PMCID: PMC13001984 PMID: 41855201

Abstract

Background

COVID-19 vaccines can cause rare but serious adverse events such as myocarditis and immune thrombotic thrombocytopenia. Despite a lack of strong evidence, concerns have been expressed that COVID-19 vaccination might lead to sudden death in younger healthy adults. We studied the association between COVID-19 vaccination and sudden death in apparently healthy people aged 12–50 years.

Methods and findings

We conducted a population-based case-control study using linked administrative datasets of residents of Ontario, Canada who were alive as of April 1, 2021. We excluded individuals aged >50 years and those with documented cardiovascular disease, mental illness, or diseases that predispose to adverse outcomes from COVID-19. We defined cases as those with out-of-hospital death, or death within 24 hours of presentation to hospital with a final diagnosis of cardiac arrest between April 1, 2021 and June 30, 2023. We matched each case with five controls on age, sex, region of residence, and neighborhood income quintile. We used conditional logistic regression to assess the association between sudden death and previous COVID-19 vaccination after adjusting for multiple potential confounders (positive severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] tests, number of SARS-CoV-2 polymerase chain reaction (PCR) tests, influenza vaccination, common comorbidities). Sensitivity analyses were conducted with different definitions of the exposure and subsets of cases (with their matched controls). Another sensitivity analysis utilized a modified self-controlled case series (SCCS) of vaccinated individuals meeting the case definition during the study period with up to three doses of any COVID-19 vaccine.

Of 6,365,451 eligible individuals, we identified 4,963 (0.08%) cases meeting our definition of sudden death (median age 36 years, 74.4% male). In the primary analysis, COVID-19 vaccination was associated with a lower risk of sudden death (adjusted odds ratio [aOR] = 0.57; 95% confidence interval (CI) [0.53,0.61]; p < 0.001). The findings were consistent for COVID-19 vaccination within six weeks before death (aOR = 0.63; 95%CI [0.55,0.72]; p < 0.001) and in sensitivity analyses limited to people aged <40 years (aOR = 0.53; 95%CI [0.48,0.58]; p < 0.001), those who died in hospital or in the emergency department (aOR = 0.71; 95%CI [0.55,0.91]; p = 0.006), and after exclusion of opioid-related deaths (aOR = 0.57; 95%CI [0.51,0.64]; p < 0.001). The SCCS sensitivity analysis showed no significant difference in the rate of sudden death in the 6 weeks following first (relative incidence (RI) 0.87; 95%CI [0.54,1.40]; p = 0.57), second (RI 0.94; 95%CI [0.57,1.57]; p = 0.82), or third (RI 0.87; 95%CI [0.37,2.05]; p = 0.10) dose of the COVID-19 vaccine. Study limitations include the inability to confirm the cause of out-of-hospital deaths and residual confounding due to differences in health-seeking behaviors for the case-control analysis.

Conclusions

These findings do not support the hypothesis that COVID-19 vaccines increase the risk of sudden cardiac death in young healthy adults.

Author summary

Why was this study done?

COVID-19 vaccines were received by a large segment of the population as part of the public health response to the pandemic
There are emerging concerns that COVID-19 vaccines are responsible for sudden death in younger healthy individuals despite a lack of evidence to support this claim

What did the researchers do and find?

A case-control study was conducted involving Ontario residents aged 12–50 years without documented comorbidities predisposing to premature death between April 1, 2021 and June 30, 2023 to examine the association between COVID-19 vaccination and sudden death
The primary outcome was sudden death; the exposure of interest was any COVID-19 vaccination
Among 6,365,451 eligible individuals, 4,806 cases who experienced sudden death were matched to 24,030 controls who were alive on the date of sudden death for each corresponding case
Receipt of COVID-19 vaccination was not associated with increased odds of sudden death

What do these findings mean?

These findings do not support the hypothesis that COVID-19 vaccines increase the risk of sudden cardiac death in younger healthy adults
A limitation of this study was the inability to confirm the cause of out-of-hospital deaths

In a case-control study, Husam Abdel-Qadir, Hardil Bhatt and colleagues investigate whether there is an association between COVID-19 vaccination and sudden death in apparently healthy younger individuals.

Introduction

Messenger ribonucleic acid (mRNA) vaccines were an essential element of the strategy for curtailing the COVID-19 pandemic [1,2]. Emergency approval of the vaccines was provided in an accelerated timeframe after large-scale clinical trials demonstrated robust efficacy and relatively benign adverse event profiles. With widespread use, however, it became clear that mRNA vaccines were associated with cases of myocarditis, most prominently in males aged <40 years [3]. The non-replicating viral vector vaccines were associated with vaccine-induced immune thrombotic thrombocytopenia (VITT), which led to rare cases of fatal thromboembolism [4]. Despite these concerns, the anticipated benefits of these vaccines were deemed to outweigh their risks at the time, and more than 75% of the adult population in high-income countries have been vaccinated [5].

Recently, concerns have been raised that healthy younger people were dying suddenly because of COVID-19 vaccination, however, this notion is not supported by any reliable scientific evidence [6–9]. Because most people living in the Western hemisphere have been vaccinated, most sudden deaths are expected to occur in previously vaccinated people. It is plausible that subclinical myocarditis after vaccination could predispose to arrhythmias if residual scar tissue served as an arrhythmogenic focus. In a prospective evaluation of 54 participants, we previously demonstrated that 1 in 8 people with confirmed acute symptomatic myocarditis had evidence of focal myocardial inflammation by fluorodeoxyglucose positron emission tomography/magnetic resonance imaging at two months follow-up [10]. A longer-term follow-up study in 13 patients with symptomatic myocarditis using cardiac MRI demonstrated that myocardial edema had resolved in all participants, although small areas of myocardial scar persisted in 2 (13%) patients [11].

There are limited data on the potential association of COVID-19 vaccination with sudden death in healthy people. Concerns about sudden death due to COVID-19 vaccination can deter future vaccination [12]. Accordingly, we conducted a population-based case-control study to explore the hypothesis that COVID-19 vaccination increases risk of sudden death in apparently healthy people aged 12–50 years.

Methods

Study design, setting, and population

We used a case-control design and linked databases in the Canadian province of Ontario, which provides universal health coverage to all residents through the Ontario Health Insurance Plan (OHIP). The datasets were linked using unique encoded identifiers and analyzed at ICES (previously known as the Institute for Clinical Evaluative Sciences [www.ices.on.ca]) [13,14]. ICES is an independent, non-profit research institute whose legal status under Ontario’s health information privacy law allows it to collect and analyze healthcare and demographic data, without consent, for health system evaluation and improvement.

We used Ontario’s Registered Persons Database to identify all residents who were alive on April 1, 2021. This date was chosen to allow for accrual during a period with fewer restrictions on vaccine access for healthier people. We excluded residents without OHIP eligibility on April 1, 2021, those with no recorded contact with the healthcare system in the prior 10 years (to decrease the potential for undocumented disease), those missing key data (date of birth, sex, postal code), and those younger than 12 years (given lower vaccine coverage and weaker vaccination mandates).

We then applied exclusion criteria to limit the study population to people who did not have diseases that would predispose them to sudden cardiovascular death or adverse outcomes from COVID-19, and those with documented mental illness (excluding mood/anxiety disorders) [15,16]. Exclusions included age 50 years or older, long-term care residence, schizophrenia [17], healthcare encounters for alcohol or illicit drug use in the 5 years preceding April 1, 2021 [18], cardiovascular disease (CVD; including coronary artery disease, heart failure, and atrial fibrillation) [19], diabetes [20], cancer [21], dementia [22], chronic obstructive pulmonary disease (COPD) [23], chronic liver or kidney disease [24,25], inflammatory bowel disease [26], autoimmune rheumatologic disease [27,28], human immunodeficiency virus (HIV) infection [29], frailty (as per the Johns Hopkins ACG System Version 10 frailty indicator) [30], other forms of immunocompromised status/autoimmune diseases [31], or receipt of chronic home care in the 5 years before April 1, 2021. We did not exclude people with hypertension, asthma, or mood/anxiety disorders given the high prevalence of these diagnoses in otherwise healthy people. Application of these exclusions left us with a study population aged 12–50 years without documented illnesses that are expected to be strongly associated with either the exposure (COVID-19 vaccination) or the outcome of interest (death).

Definition of cases and controls

Cases were required to fulfill one of three criteria between April 1, 2021 and June 30, 2023:

Death outside of hospital; OR
Death in an emergency department (ED), with a most responsible discharge diagnosis of cardiac arrest, sudden death, or significant ventricular arrhythmia, and where none of the other diagnostic codes indicated trauma, mental illness, or substance use (see S1 Table); OR
In-hospital death within 24 hours of admission, with a most responsible discharge diagnosis of cardiac arrest, sudden death, or ventricular arrhythmia, and where no other diagnostic code indicated trauma, mental illness, or substance use (see S1 Table)

We ascertained hospitalization status and discharge diagnoses from the Canadian Institute for Health Information (CIHI) Discharge Abstract Database (DAD), and ED records from the CIHI National Ambulatory Care Reporting System (NACRS).

We matched each case with up to 5 controls from the pool of eligible individuals who were alive on the index date, matching on age, sex, geographic area of residence (based upon the forward sortation area), and neighborhood income quintile. The index date for controls was the date of death of their matched case.

Definition of the exposure

The exposure of interest was receipt of any COVID-19 vaccination, which was ascertained from the COVaxON database, a centralized registry that identifies all COVID-19 vaccination events in Ontario [32].

Statistical analysis

The primary and secondary sensitivity case-control analyses were prospectively planned on January 5, 2023. The post-hoc analysis with modified self-controlled case series (SCCS) was performed after the peer-review process to address potential confounding associated with health-seeking behaviors of vaccine recipients.

Baseline characteristics of case and controls were summarized using medians (with 25th–75th percentiles) for continuous variables and counts with percentages for categorical variables. Given the large sample size, we used standardized differences rather than p-values to compare baseline differences between groups, with values greater than 0.1 indicating meaningful differences [33].

We used conditional logistic regression to determine the association between COVID-19 vaccination and the odds of being a case or a control while accounting for the matched nature of the sample. The model included terms for a positive SARS-CoV-2 test in the preceding 90 days (since SARS-CoV-2 infection can predispose to myocarditis [34]), a positive SARS-CoV-2 test >90 days prior, influenza vaccination in the preceding 365 days, and the number of SARS-CoV-2 PCR tests in the preceding year (to adjust for health-seeking behaviors), as well as a history of asthma, hypertension, and mood or anxiety disorders.

We conducted several sensitivity analyses to test the robustness of our conclusions. We first limited the exposure to mRNA vaccines, given their association with myocarditis, and then the AstraZeneca vaccine, given its association with thromboembolic events. We next examined COVID-19 vaccination in the six weeks preceding the index date (the period when myocarditis is most likely). We then limited cases to deaths in hospital or the ED where the cause of death was documented to be due to sudden cardiac death, with exclusion of diagnostic codes indicating trauma, mental illness, or substance use. Furthermore, we restricted the analysis to people aged 40 years or younger, a population with a lower likelihood of undiagnosed cardiac disease and a higher risk of vaccine-associated myocarditis. In addition, we repeated the analysis with a secondary case definition that excluded opioid-related deaths using the Drug and Drug/Alcohol Related Death (DDARD) database. This analysis was limited to deaths before June 30, 2022 due to data availability.

In an additional post-hoc sensitivity analysis, we utilized a modified SCCS method [35,36]. This was restricted to vaccinated residents meeting the case definition during the study period who had up to three doses of any COVID-19 vaccine. For this analysis, the observation period remained the same (April 1, 2021 to June 30, 2023). We used a 6-week risk interval beginning on the vaccination date (day 0) for each dose received, with person-time for each interval included in the model as an offset. The control period was the remainder of the observation period after exclusion of the 6-week risk intervals if applicable. Vaccine exposures were modeled as first dose, second dose, or third dose. Relative incidence (RI) was estimated using conditional Poisson regression with a pseudo-likelihood approach and sandwich variance estimators to calculate Wald confidence intervals. Models were adjusted for age as a time-varying covariate and for quarterly rate of sudden death among unvaccinated individuals derived from our case-control analysis.

All analyses were conducted using SAS Version 9.4 (SAS Institute). Statistical significance for comparisons of outcomes was defined as a two-tailed p-value <0.05. This study is reported as per the Reporting of Studies Conducted using Observational Routinely-Collected Data (RECORD) guideline (S1 Checklist).

Ethics approval

The use of most data in this project is authorized under section 45 of Ontario’s Personal Health Information Protection Act (PHIPA) and does not require review by a Research Ethics Board [37]. Ethics approval was required for the analyses excluding opioid-related deaths, which was part of our secondary case definition; this was obtained from the Women’s College Hospital Research Ethics Board (REB # 2024-0002-E).

Results

We identified 14,664,193 Ontario residents who were alive as of April 1st, 2021. After applying exclusion criteria (Fig 1), we were left with 6,365,451 eligible individuals. During the accrual period, 4,963 (0.08%) individuals died and met criteria to be cases. Of these, 4,448 (89.6%) died in the prehospital setting and 515 (10.4%) died within 24 hours of presenting to a hospital or ED with a discharge diagnosis of cardiac arrest. From this pool of 4,963 cases, 4,806 (96.8%) were included in the primary case-control analysis after each was matched to 5 controls (for a total of 24,030 controls).

Prior to matching, cases were older and were more likely to be male compared to controls. They were also more likely to reside in northern Ontario, and less likely to reside in Toronto or the neighboring regions of Peel and York (S2 Table). Cases were more likely to live in neighborhoods with lower income, fewer people per household, lower proportions of visible minorities, and higher proportions of people employed in sales, trades, manufacturing, or agriculture (industries more likely to stay open during pandemic-related lockdowns). There was a higher prevalence of hypertension and mood/anxiety disorders, but a lower prevalence of documented influenza vaccination among cases. There were no relevant differences in the percentage receiving COVID-19 vaccination. A total of 4,806 cases were matched with 5 controls on age, sex, and forward sortation area (Table 1). Most differences between cases and controls were nullified after matching, but there remained a higher prevalence of hypertension and mood/anxiety disorders and lower documented COVID-19 and influenza vaccinations among cases.

Table 1. Baseline characteristics of residents of Ontario, Canada who were included in the case-control analysis.

Variable	Cases	Controls	Std. Diff^*
	N = 4,806	N = 24,030
Age, mean ± SD, years	35.21 ± 10.40	35.21 ± 10.39	0
Age, median (IQR), years	36 (27-45)	36 (27-45)	0
Aged 12–18 years, n(%)	346 (7.2%)	1,730 (7.2%)	0
Aged 19–30 years, n(%)	1,309 (27.2%)	6,545 (27.2%)	0
Aged 31–40 years, n(%)	1,348 (28.0%)	6,740 (28.0%)	0
Aged 41–50 years, n(%)	1,803 (37.5%)	9,015 (37.5%)
Male sex, n(%)	3,564 (74.2%)	17,820 (74.2%)	0
Public health unit region
Central East, n(%)	384 (8.0%)	1,863 (7.8%)	0.01
Central West, n(%)	935 (19.5%)	4,672 (19.4%)	<0.01
Durham, n(%)	237 (4.9%)	1,176 (4.9%)	<0.01
Eastern, n(%)	340 (7.1%)	1,779 (7.4%)	0.01
Northern, n(%)	467 (9.7%)	2,334 (9.7%)	<0.01
Ottawa, n(%)	301 (6.3%)	1,477 (6.1%)	<0.01
Peel, n(%)	403 (8.4%)	2,015 (8.4%)	<0.01
Southwest, n(%)	666 (13.9%)	3,331 (13.9%)	<0.01
Toronto, n(%)	808 (16.8%)	4,040 (16.8%)	<0.01
York, n(%)	255 (5.3%)	1,293 (5.4%)	<0.01
Missing data, n(%)	10 (0.2%)	50 (0.2%)	<0.01
Neighborhood income quintile
1 (Lowest), n(%)	1,291 (26.9%)	6,455 (26.9%)	0
2, n(%)	991 (20.6%)	4,955 (20.6%)	0
3, n(%)	946 (19.7%)	4,730 (19.7%)	0
4, n(%)	837 (17.4%)	4,185 (17.4%)	0
5 (Highest), n(%)	727 (15.1%)	3,635 (15.1%)	0
Missing data, n(%)	14 (0.3%)	70 (0.3%)	0
Neighborhood average number of persons per dwelling quintile
1 (Lowest), n(%)	1,011 (21.0%)	4,801 (20.0%)	0.03
2, n(%)	968 (20.1%)	4,636 (19.3%)	0.02
3, n(%)	605 (12.6%)	3,213 (13.4%)	0.02
4, n(%)	1,018 (21.2%)	5,233 (21.8%)	0.01
5, n(%)	860 (17.9%)	4,384 (18.2%)	0.01
Missing, n(%)	344 (7.2%)	1,763 (7.3%)	0.01
Neighborhood quintile by proportion of people who self-identify as visible minority quintile
1 (Lowest), n(%)	941 (19.6%)	4,732 (19.7%)	<0.01
2, n(%)	908 (18.9%)	4,319 (18.0%)	0.02
3, n(%)	790 (16.4%)	4,014 (16.7%)	0.01
4, n(%)	916 (19.1%)	4,549 (18.9%)	<0.01
5 (Highest), n(%)	906 (18.9%)	4,653 (19.4%)	0.01
Missing, n(%)	345 (7.2%)	1,763 (7.3%)	0.01
Neighborhood quintile by proportion employed in sales/trades/manufacturing/agriculture
1 (Lowest), n(%)	652 (13.6%)	3,300 (13.7%)	0
2, n(%)	850 (17.7%)	4,449 (18.5%)	0.02
3, n(%)	907 (18.9%)	4,636 (19.3%)	0.01
4, n(%)	1,010 (21.0%)	4,854 (20.2%)	0.02
5 (Highest), n(%)	1,042 (21.7%)	5,028 (20.9%)	0.02
Missing, n(%)	345 (7.2%)	1,763 (7.3%)	0.01
Asthma, n(%)	972 (20.2%)	4,068 (16.9%)	0.08
Hypertension, n(%)	411 (8.6%)	1,335 (5.6%)	0.12
History of mood or anxiety disorder in the past 5 years, n(%)	266 (5.5%)	411 (1.7%)	0.21
Influenza vaccination in past year, n(%)	587 (12.2%)	4,024 (16.7%)	0.13
Number of COVID-19 vaccine doses received as of index date
0, n(%)	1,569 (32.6%)	5,510 (22.9%)	0.22
1, n(%)	325 (6.8%)	1,423 (5.9%)	0.03
≥2, n(%)	2,912 (60.6%)	17,097 (71.1%)	0.22
Received any COVID-19 vaccine before index date, n(%)	3,237 (67.4%)	18,520 (77.1%)	0.22
Received COVID-19 vaccine within 6 weeks before index date, n(%)	317 (6.6%)	2,246 (9.3%)	0.1
Received ≥1 dose of any mRNA vaccine, n(%)	3,212 (66.8%)	18,374 (76.5%)	0.21
Received ≥1 dose of Pfizer/BioNTech Comirnaty vaccine, n(%)	2,482 (51.6%)	14,801 (61.6%)	0.20
Received ≥1 dose of Moderna Spikevax vaccine, n(%)	1,458 (30.3%)	7,999 (33.3%)	0.06
Received ≥1 dose of AstraZeneca Vaxzevria vaccine, n(%)	154 (3.2%)	1,055 (4.4%)	0.06
Recent SARS-CoV-2 PCR test before case death date
Never tested positive before, n(%)	4,406 (91.7%)	22,119 (92.0%)	0.01
Remote prior positive test (>90 days), n(%)	293 (6.1%)	1,694 (7.0%)	0.04
Recent prior positive test (≤90 days), n(%)	107 (2.2%)	217 (0.9%)	0.11
Number of SARS-CoV-2 PCR tests prior to case death date
Mean ± SD	1.47 ± 3.61	1.18 ± 3.26	0.08
Median (IQR)	0 (0–2)	0 (0–1)	0.11

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Note: The data are presented after dividing the cohort into two groups: cases and matched controls.

*std, standardized difference, IQR, interquartile range.

A total of 3,237 (67.4%) of cases had prior COVID-19 vaccination, compared with 18,520 (77.1%) of controls. Two or more COVID-19 vaccines had been received before the index date in 2,912 (60.6%) cases and 17,097 (71.1%) controls. When limiting the exposure to mRNA vaccines, at least one dose was documented in 3,212 (66.8%) cases compared to 18,374 (76.5%) controls. These observations were mostly driven by the Pfizer/BioNTech Comirnaty vaccine, which was received by 2,482 (51.6%) cases and 14,801 (61.6%) controls. The standardized differences for all these comparisons were ≥0.1. For vaccines that were administered in lower numbers, such as Moderna’s Spikevax and AstraZeneca’s Vaxzevria vaccines, the prevalence of vaccination was low in both groups. There were fewer than 6 cases who died with prior exposure to Janssen’s Jcoyden vaccine and none with exposure to Novavax’s Nuvaxovid vaccine. When we specifically focused on COVID-19 vaccination in the preceding six weeks, vaccination was documented for 317 (6.6%) of cases compared with 2,246 (9.3%) of controls (standardized difference = 0.1).

In the primary analysis, COVID-19 vaccination was associated with lower odds of sudden death (adjusted odds ratio [aOR] = 0.57; 95%CI [0.53,0.61]]; p < 0.001; Fig 2). Documented influenza vaccination was also associated with lower odds of death (aOR = 0.72; 95%CI [0.66,0.80]; p < 0.001). A documented positive SARS-CoV-2 PCR test within 90 days of the index date was associated with higher odds of death (aOR = 2.36; 95%CI [1.84,3.02]; p < 0.001), while a positive SARS-CoV-2 PCR test greater than 90 days before the index date was associated with lower odds of death (aOR = 0.83; 95%CI [0.72,0.95]; p = 0.006). The odds of death were also increased by the presence of asthma (aOR = 1.26; 95%CI [1.16,1.36]; p < 0.001), hypertension (aOR = 1.70; 95%CI [1.50,1.92]; p < 0.001), and a mood or anxiety disorder (aOR = 3.46; 95%CI [2.94,4.07]; p < 0.001).

The inverse association of COVID-19 vaccination with death was consistent for most other definitions of vaccine exposure. Receipt of mRNA COVID-19 vaccination was associated with an aOR of 0.57 (95%CI [0.53,0.62]; p < 0.001) for death. Recent COVID-19 vaccination within six weeks prior to the index date was also associated with lower odds of death (aOR = 0.63; 95%CI [0.55,0.72]; p < 0.001). Individuals who received two doses of COVID-19 vaccination displayed a stronger negative association with death (aOR = 0.53; 95%CI [0.49,0.57]; p < 0.001), while receipt of only one dose was associated with lower risk of death that did not reach statistical significance (aOR = 0.88; 95%CI [0.76,1.01]; p = 0.071).

People aged <40 years

The baseline characteristics of matched cases and controls in the subgroup aged <40 years are described in S3 Table. They demonstrated similar patterns to the overall cohort, wherein COVID-19 vaccination was less prevalent among cases (1,832 [64.3%]) compared to controls (10,778 [75.7%]). After adjusting for differences between cases and controls, there was an inverse association between any COVID-19 vaccination and sudden death (aOR = 0.53; 95%CI [0.48,0.58]; p < 0.001). The aORs for other definitions of COVID-19 vaccination are summarized in S1 Fig.

Analyses excluding opioid-related deaths

The baseline characteristics of matched cases that excluded opioid-related deaths, along with matched controls, are described in S4 Table. Once again, COVID-19 vaccination was less prevalent among cases who died (1,232 [61.1%]) compared to living controls (7,159 [71.0%]). This pattern was observed in other definitions of the vaccination exposure, with standardized differences for all the comparisons being ≥0.1. After adjustment, we continued to observe an inverse association between any COVID-19 vaccination and sudden death (aOR = 0.57; 95%CI [0.51,0.64]; p < 0.001). The aORs for other definitions of COVID-19 vaccination are summarized in S2 Fig.

Deaths in hospital or an emergency department

S5 Table lists the baseline characteristics of people who died within 24 hours of presenting to hospital or ED with a discharge diagnosis indicating cardiac arrest, with comparison to their matched controls. We observed a lower prevalence of COVID-19 vaccination among cases (365 [73.6%]) compared to controls (1,952 [78.7%]). Cases had lower proportions of people vaccinated with mRNA vaccines than controls (73.2% versus 78.1%) and a lower proportion vaccinated within 6 weeks prior to the index date (8.3% versus 11.4%). The standardized differences for all the comparisons described were ≥0.1. After adjustment, there continued to be an inverse association between COVID-19 vaccination and sudden death (aOR = 0.71; 95%CI [0.55,0.91]; p = 0.006). The aORs for other definitions of COVID-19 vaccination are summarized in S3 Fig.

Modified SCCS analysis

The SCCS sensitivity analysis demonstrated that there was no significant difference in the rate of sudden death in the 6 weeks following first (RI 0.87; 95%CI [0.54,1.40]; p = 0.57), second (RI 0.94; 95%CI [0.57,1.57]; p = 0.82), or later doses (RI 0.87; 95%CI [0.37, 2.05]; p = 0.10) of a COVID-19 vaccine (S6 Table).

Discussion

In this population-based study, vaccination against COVID-19 was not associated with an increased risk of sudden death in people younger than 50 years who had no documented evidence of cardiovascular disease. This finding persisted through sensitivity analyses limited to people aged <40 years, those who died in-hospital with a diagnosis of sudden cardiac arrest within 24 hours of presentation, after exclusion of admissions associated with trauma, mental illness, and substance use, after exclusion of opioid-related deaths, and another sensitivity analysis utilizing a modified SCCS. While most Ontarians received the Pfizer/BioNTech mRNA vaccine, we did not observe a higher prevalence of exposure to any Health Canada-approved vaccine among people who died. Collectively, these observations refute the claim that COVID-19 vaccination increases the risk of sudden death.

Our data align with recent publications which report that COVID-19 vaccination is not associated with higher risk of sudden death. Previous studies from the United States and England utilized a modified SCCS design to demonstrate no significant increase in cardiac or all-cause mortality in the 4 weeks and 12 weeks after COVID-19 vaccination, respectively [38,39]. A case-control study from India suggested a decreased likelihood of sudden death in younger individuals who had received 2 or more doses of COVID-19 vaccines (odds ratio 0.58; 95%CI [0.37, 0.92]) compared to those who had received only 1 dose (odds ratio = 1.00; 95%CI [0.73,1.36]) [40]. Our primary case-control analyses similarly demonstrated a dose-dependent protective effect, while the SCCS sensitivity analysis showed no protective effect associated with any dose of COVID-19 vaccination. It is possible that the apparent protective effective of increasing doses of COVID-19 vaccination in the case-control analyses may reflect confounding due to greater health-seeking behaviors among vaccinated individuals.

While some studies have suggested dose-dependent safety concerns due to higher risks of myocarditis after the second dose [41,42], this does not align with our data and that from other large, epidemiologic analyses. Further supporting the absence of an increased risk of sudden death following COVID-19 vaccines, an analysis of mortality records of residents in Italy aged 1–40 years showed no increase in sudden cardiac death after the introduction of COVID-19 vaccines [43]. Indeed, rates of sudden death have decreased among athletes between the years 2002–2022, including the years when COVID-19 vaccines were introduced [44]. Furthermore, a study examining death certificates of younger individuals between the years 2021–2022 found no evidence directly attributing COVID-19 vaccination to cardiac death [45]. While mRNA vaccines have demonstrated an increased risk of myocarditis in younger men, mortality rates following the development of postvaccine myocarditis are lower than mortality rates following COVID-19-related myocarditis or conventional myocarditis [46]. Postmortem histopathologic analyses have raised potential causal relations between unexpected death and VITT following COVID-19 vaccination [47–49], but this may be less relevant for mRNA vaccines which comprise most COVID-19 vaccines in use today.

The strengths of our study include its large, population-based cohort of residents covered by a universal single-payer healthcare system. The combination of case-control and SCCS methods provides more confidence in our conclusions. A major limitation of this study is that we could not confirm the underlying cause of death out of hospital, so could not exclude deaths out of hospital that were due to motor vehicle collisions, violence, or suicides. However, we consistently found that COVID-19 vaccination was not associated with increased odds of deaths due to cardiac arrest diagnosed in hospital or the ED within 24 hours of presentation after exclusion of alternative causes of death. We could only utilize neighborhood-level data rather than individual data for income, proportion of visible minorities, and occupations. For SARS-CoV-2 testing, we accounted for PCR tests but could not capture results of rapid antigen tests. Moreover, the registries used to derive a cohort free of cardiac and other chronic diseases would not capture people with undiagnosed diseases. Lastly, differences in healthcare seeking behaviors may have led to residual confounding; this is expected to be less applicable for the SCCS analysis.

This population-based case-control study did not show a positive association between COVID-19 vaccination and death in apparently healthy individuals aged <50 years. We did not observe higher odds of death in people who received any of the Health Canada-approved COVID-19 vaccines. These data do not support the hypothesis that COVID-19 vaccines increase the risk of sudden cardiac death.

Supporting information

S1 Checklist. Reporting of Studies Conducted using Observational Routinely-Collected Data (RECORD) checklist.

(DOCX)

pmed.1004924.s001.docx^{(21.3KB, docx)}

S1 Table. ICD-10 diagnostic codes used for defining a case.

(DOCX)

pmed.1004924.s002.docx^{(13.3KB, docx)}

S2 Table. Baseline characteristics of the residents of Ontario, Canada who met criteria for inclusion in the study.

The data are presented after dividing the cohort into two groups—people who met the definition for being a case, and those who were eligible for being selected as controls. Please note that the cases are not matched to controls in this table.

(DOCX)

pmed.1004924.s003.docx^{(18.7KB, docx)}

S3 Table. Baseline characteristics of matched cases and controls aged <40 years.

(DOCX)

pmed.1004924.s004.docx^{(19.3KB, docx)}

S4 Table. Baseline characteristics of matched cases and controls excluding opioid-related deaths.

(S4_Table.DOCX)

pmed.1004924.s005.docx^{(20.2KB, docx)}

S5 Table. Baseline characteristics of matched cases and controls only including deaths within 24-hours of presenting to the hospital.

(DOCX)

pmed.1004924.s006.docx^{(20.2KB, docx)}

S6 Table. The relative incidence (with 95% confidence interval) of sudden death in vaccinated individuals within the post COVID-19 vaccination risk period (6-weeks after the vaccination date for each dose received) compared to the control period.

The analysis adjusted for age and quarterly rate of sudden death among unvaccinated individuals.

(DOCX)

pmed.1004924.s007.docx^{(15.4KB, docx)}

S1 Fig. The adjusted odds ratio (with 95% confidence interval) for death and COVID-19 vaccination in individuals younger than 40 years of age among the matched cohort (n = 17,094), assessed using conditional logistic regression modeling.

(TIFF)

pmed.1004924.s008.tiff^{(2.5MB, tiff)}

S2 Fig. The adjusted odds ratio (with 95% confidence interval) for death and COVID-19 vaccination excluding opioid-related deaths among the matched cohort (n = 12,096), assessed using conditional logistic regression modeling.

(TIFF)

pmed.1004924.s009.tiff^{(2.5MB, tiff)}

S3 Fig. The adjusted odds ratio (with 95% confidence interval) for death and COVID-19 vaccination only involving deaths within 24-hours of arriving to the hospital among the matched cohort (n = 2,976), assessed using conditional logistic regression modeling.

(TIFF)

pmed.1004924.s010.tiff^{(2.5MB, tiff)}

Acknowledgments

We would like to acknowledge Public Health Ontario for access to vaccination data from COVaxON. This document used data adapted from the Statistics Canada Postal Code Conversion File, which is based on data licensed from Canada Post Corporation, and/or data adapted from the Ontario Ministry of Health Postal Code Conversion File, which contains data copied under license from Canada Post Corporation and Statistics Canada. Parts of this material are based on data and/or information compiled and provided by: the Ontario Ministry of Health, Ontario Health (OH), and CIHI. The analyses, conclusions, opinions, and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources. We thank IQVIA Solutions Canada for use of their Drug Information File. Importantly, we thank the Ontario residents, without whom this research would be impossible.

Abbreviations

aOR: adjusted odds ratio
CI: confidence interval
CIHI: Canadian Institute for Health Information
COPD: chronic obstructive pulmonary disease
CVD: cardiovascular disease
DAD: Discharge Abstract Database
ED: emergency department
HIV: human immunodeficiency virus
mRNA: messenger ribonucleic acid
NACRS: National Ambulatory Care Reporting System
OHIP: Ontario Health Insurance Plan
PCR: polymerase chain reaction
PHIPA: Personal Health Information Protection Act
RECORD: Reporting of Studies Conducted using Observational Routinely-Collected Data
RI: relative incidence
SARS-CoV-2: severe acute respiratory syndrome coronavirus 2
SCCS: self-controlled case series
VITT: vaccine-induced immune thrombotic thrombocytopenia

Data Availability

The dataset from this study is held securely in coded form at ICES. While legal data sharing agreements between ICES and data providers (e.g., healthcare organizations and government) prohibit ICES from making the dataset publicly available, access may be granted to those who meet pre-specified criteria for confidential access, available at http://www.ices.on.ca/DAS (email: das@ices.on.ca). The full dataset creation plan and underlying analytic code are available from ICES upon request, understanding that the computer programs may rely upon coding templates or macros that are unique to ICES and are therefore either inaccessible or may require modification. To view details on the types of data and datasets available, please visit the ICES Data Dictionary (at https://datadictionary.ices.on.ca/Applications/DataDictionary/Default.aspx).

Funding Statement

This work was supported by funding from the Canadian Immunization Research Network (CIRN, [https://landing.cirnetwork.ca]) through a grant from the Public Health Agency of Canada and the Canadian Institutes of Health Research (CNF 151944), and funding from the Public Health Agency of Canada, through the Vaccine Surveillance Working Party and the COVID-19 Immunity Task Force (both grants to JCK). This study was supported by Public Health Ontario and by ICES, which is funded by an annual grant from the Ontario Ministry of Health (MOH) and Ministry of Long-Term Care (MLTC). This work was also supported by the Ontario Health Data Platform (OHDP), a Province of Ontario initiative to support Ontario’s ongoing response to COVID-19 and its related impacts. HA-Q is supported by a Tier 2 Canada Research Chair in Cardiovascular Disease Epidemiology and Outcomes (from the Government of Canada), a Hold’em for Life Professorship in Cancer Research (from the University of Toronto) and was previously supported by a Chair in Women’s Heart and Brain Health (from the Heart and Stroke Foundation of Canada). JCK is supported by a Clinician-Scientist Award from the University of Toronto Department of Family and Community Medicine. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS Med. doi: 10.1371/journal.pmed.1004924.r001

Decision Letter 0

Suzanne De Bruijn

19 Mar 2025

Dear Dr Abdel-Qadir,

Thank you for submitting your manuscript entitled "The association between COVID-19 vaccination and sudden death in apparently healthy younger individuals: a population-based case-control study" for consideration by PLOS Medicine.

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PLoS Med. doi: 10.1371/journal.pmed.1004924.r002

Decision Letter 1

Suzanne De Bruijn

28 May 2025

Dear Dr Abdel-Qadir,

Many thanks for submitting your manuscript "The association between COVID-19 vaccination and sudden death in apparently healthy younger individuals: a population-based case-control study" (PMEDICINE-D-25-01000R1) to PLOS Medicine. The paper has been reviewed by subject experts and a statistician; their comments are included below and can also be accessed here: [LINK]

As you will see, although the reviewers outline several concerns, they support a revision. We strongly recommend that you follow the suggestions of reviewer #2 and adjust the analyses accordingly. After discussing the paper with the editorial team and an academic editor with relevant expertise, I'm pleased to invite you to revise the paper in response to the reviewers' comments. We plan to send the revised paper to some or all of the original reviewers, and we cannot provide any guarantees at this stage regarding publication.

When you upload your revision, please include a point-by-point response that addresses all of the reviewer and editorial points, indicating the changes made in the manuscript and either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please also be sure to check the general editorial comments at the end of this letter and include these in your point-by-point response. When you resubmit your paper, please include a clean version of the paper as the main article file and a version with changes tracked as a marked-up manuscript. It may also be helpful to check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper.

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Alexandra Tosun, PhD

atosun@plos.org

[on behalf of]

Suzanne De Bruijn, PhD

Associate Editor

PLOS Medicine

sbruijn@plos.org

-----------------------------------------------------------

Comments from the academic editor:

The Academic Editor thinks that you could state more clearly what is novel about your study. They agree with the comments made by reviewers #2 and #3 regarding residual confounding and encourage you to follow reviewer #2's advice and adjust the analyses.

-----------------------------------------------------------

Comments from the reviewers:

Reviewer #1: This population-based case-control study has large sample size, reliable data source, the selection of cases is clear and well-explained, the statistical approach is straightforward, and the results are well organised, for example, it is nice to have Table 1 where the readers can have a clear understanding of the cases' demographic information as compared with the general population.

Minor comments:

This study has a large dataset to closely match the cases by age, sex and residence region. However, the matching by age is not clear. As by Line 134, "Controls were matched to their case according to date of birth, sex, and forward sortation area", controls should have the exact age as that of the cases. However, the variable age differs between case and control groups in the tables (Table 1, 2, S3 ). Please explain. If the matching is not limited to the exact date of birth, please clarify. If a case has more than 5 potential controls, what are the principles to select 5 from them? Are there cases with less than 5 matched controls?

Table 1 contains 4963 cases while Table 2 contains 4806 cases. Can the authors explain why over 150 cases were removed?

The COVID pandemic triggered many abnormalities in public health and medical settings. It would be interesting to see the longitudinal trend of the sudden death rate (same definition of cases in this study) before and during COVID, and for during COVID, before and after Vaccine initiation. Having those figures - without any statistical inference - would be the icing on the cake.

The term "undoubtedly" in line 303 is too strong.

Reviewer #2: This paper addresses an important safety concern expressed largely in social media and other non-scientific fora that COVID-19 vaccines can cause sudden death in previously healthy young people. The authors use a matched case control design to test the hypothesis of an increased risk of death after COOVID-19 vaccine and find no evidence in support of this. I have the following comments:

Line 187 says that prior to matching the cases were older and more likely to be male but doesn't say than whom. In table 1 the comparator column is called controls but they are just the non-cases in the eligible population. I think it is confusing to label them controls. Since this is by design a matched case control study I am unclear as to the relevance of the detail shown in Table 1. If the authors think table 1 is important to show, perhaps they can discuss its relevance otherwise it would seem more appropriate to show it in Supplementary appendix for background information.

The numbers of cases in Table 2 which is with matched controls has dropped to 4896 from 4936 in Table 2. The authors should account for this difference.

Despite restricting the population under study by a number of factors that would predispose towards sudden death and matching controls on date of birth, sex and first 3 digits of the postcode, a lower proportion of cases than controls had received influenza vaccination. This would suggest residual confounding in some health care seeking or other behaviour/risk factors which would not necessarily be fully adjusted for by including receipt of influenza vaccine in the regression model. The consistency of the findings of an apparent protective effect of vaccination, with a lower OR after two than one dose is consistent with there being an unmeasured confounding variable associated with health care seeking behaviour. Given this, it would have been informative to conduct an analysis using the self-controlled cases only method to see whether the apparent protective effect was still there with a method that automatically controls for time invariant individual level confounding variables. Did the authors consider this method which is now widely used for vaccine safety studies to deal with the problem of unmeasured confounding? In any event this issue should be discussed by the authors and while they authors are correct that their study did not provide evidence of an increased risk of sudden death a small elevated risk may have been masked by the confounding.

Line 273. The authors say that "Our data align with recent publications that also report no association of COVID-19 vaccination with sudden death". They cite one study from England that used the SCCS method (ref 37) but this study found no evidence of a protective effect either. Neither did a separate study in England (Stowe J et al. Risk of cardiac arrhythmia and cardiac arrest after primary and booster COVID-19 vaccination in England: A self-controlled case series analysis. Vaccine X. 2023 Dec 1;15:100418 - not referenced by the authors). In contrast a case control study from India (ref 39) did find an apparent protective effect of COVID-19 vaccination. It would have been valuable if the authors had considered potential reasons for the apparent protective effect in the two case-control studies and why this was not observed in the two self controlled cases only studies. At the end of the discussion (line 317) the authors do seem to acknowledge the potential for confounding by saying that unvaccinated individuals may be less likely to seek health care encounters and to be more likely to have undiagnosed health conditions but don't then discuss what impact they think this this might have on their study results.

Reviewer #3: The authors present a case control study of death and COVID-19 vaccination. The case-control study design is an appropriate choice. Potential confounders have been considered, and measured confounders have been accounted for by matching or adjustment. The paper is well written.

The protective effect of COVID-19 vaccination found could suggest that there remains unmeasured confounding, e.g. as a result of differential reporting of COVID-19 infection among cases and controls, but of course it is impossible to be certain. It is noted as a limitation in the discussion that rapid antigen tests could not be captured and so unmeasured infection could not be accounted for (this would be an issue for any study design).

I agree with the overall conclusion: There is no evidence from this study that COVID-19 vaccination is associated with an increased risk of cardiac death. Given the potential for unmeasured confounding, I think that the overall conclusions are fair and are not overstated.

Any attachments provided with reviews can be seen via the following link: [LINK]

--------------------------------------------------------- ---

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PLoS Med. 2026 Mar 19;23(3):e1004924. doi: 10.1371/journal.pmed.1004924.r003

Author response to Decision Letter 2

21 Nov 2025

Attachment

Submitted filename: Final Response letter - Nov 2.docx

pmed.1004924.s013.docx^{(43.6KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1004924.r004

Decision Letter 2

Suzanne De Bruijn

17 Dec 2025

Dear Dr. Abdel-Qadir,

Thank you very much for re-submitting your manuscript "The association between COVID-19 vaccination and sudden death in apparently healthy younger individuals: a population-based case-control study" (PMEDICINE-D-25-01000R2) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by 2 reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

Before we can accept your manuscript, we have several editorial requests we need you to address:

A) We would like you to address all remaining concerns from Reviewer 2, including modifying the abstract.

B) We would like you to reframe your narrative in the introduction, as well as in the rest of the manuscript, to not base your research on a social media narrative. We would suggest to just state that 'there is a fear that the vaccine leads to sudden death despite lack of evidence'. Please also remove the specific examples calling people out by name. Similarly, please rephrase the bullet point in the authors summary under 'what do these findings mean' to just state your conclusion, rather than that this 'refutes a narrative'.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

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If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Jan 07 2026 11:59PM.

Sincerely,

Suzanne De Bruijn, PhD

Associate Editor

PLOS Medicine

plosmedicine.org

------------------------------------------------------------

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* Did your study have a prospective protocol or analysis plan? Please state this (either way) early in the Methods section.

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Comments from Reviewers:

Reviewer #1: The authors have clearly addressed my previous questions; the manuscript is well-written, and I agree with the study methodology and their conclusions.

Reviewer #2: The revisions the authors have made are comprehensive and address all my comments. The addition of the SCCS analysis is particularly informative as unlike the matched case control study it shows no evidence of a protective effect of COVID-19 vaccination which is consistent with my concerns that the protective effect in the case control analysis reflected residual confounding. This point is acknowledged by the authors on lines 322-324 in the discussion. I am therefore surprised that the authors have modified the conclusion of their abstract which now states that "COVID-19 vaccination was consistently associated with a lower risk of sudden death". What is the justification for adding "consistently" when the SCCS did not show a protective effect especially as there are now grounds for concluding that the apparent protective effect from the case control study likely reflects residual confounding? A more balanced conclusion would be to omit this sentence and just say "These data do not support the hypothesis that COVID-19 vaccines increase the risk of sudden cardiac death" which was the final sentence in the authors' original abstract. This would also bring the conclusion in the abstract in line with the Author Summary (lines 77-81).

Additional comments:

I was unable to find mention of what the acronym ICES stands for in the paper. Three different organisations came up with this acronym in Canada in my wed search. There is a link to how to access ICES data in the data sharing section of the paper but it would be helpful if the name of ICES was given in full with a generic weblink to the main ICES website in the reference list for readers to understand exactly what this organisation is and how it works.

Line 336 - is there a verb missing here eg "found"

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. 2026 Mar 19;23(3):e1004924. doi: 10.1371/journal.pmed.1004924.r005

Author response to Decision Letter 3

9 Jan 2026

Attachment

Submitted filename: Response Letter - January, 2026.docx

pmed.1004924.s014.docx^{(19.2KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1004924.r006

Decision Letter 3

Suzanne De Bruijn

13 Jan 2026

Dear Dr. Abdel-Qadir,

We have a few remaining editorial requests:

1) Please confirm that your abstract complies with our requirements, including format (three sections: Background, Methods and Findings, and Conclusions) and providing all the information relevant to this study type https://journals.plos.org/plosmedicine/s/submission-guidelines#loc-abstract

2) Please ensure that all abbreviations are defined at first use throughout the text.

3) Please confirm that all numbers presented in the abstract are present and identical to numbers presented in the main manuscript text.

FUNDING STATEMENT

4) Please include initials of authors who received each award.

5) Please add URLs to the funders website, as well as grant numbers where possible.

ETHICS

6) Include IRB approval number

7) Was informed consent necessary, or was this waived? Please state so in the methods section. If it was necessary, please state whether informed consent was written or oral.

OTHER

8) Please mention the fact that differences in health care seeking behaviours may lead to residual confounding as an additional limitation in the abstract.

9) Line 104: include ‘previously’ to make clear these data are not presented in this manuscript.

10) Line 109: add a sentence stating the knowledge gap: e.g. ‘sudden death in apparently healthy people has not been studied yet’.

11) Line 328: remove ‘decisively’

12) We appreciate that you discuss the differences in covid vaccinations after matching in detail (line 250-256); however, please also mention the difference in covid vaccines in the sentence prior to this paragraph, to avoid any possible confusion. (line 242-244: “Most differences between cases and controls were nullified, but there remained a higher prevalence of hypertension and mood/anxiety disorders, and lower documented influenza vaccination, among cases.”)

We expect to receive your revised manuscript within 1 week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Jan 20 2026 11:59PM.

Sincerely,

Suzanne De Bruijn, PhD

Associate Editor

PLOS Medicine

plosmedicine.org

PLoS Med. 2026 Mar 19;23(3):e1004924. doi: 10.1371/journal.pmed.1004924.r007

Author response to Decision Letter 4

16 Jan 2026

Attachment

Submitted filename: Response to Editorial Requests - Jan 15.docx

pmed.1004924.s015.docx^{(18.7KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1004924.r008

Decision Letter 4

Suzanne De Bruijn

22 Jan 2026

Dear Dr Abdel-Qadir,

On behalf of my colleagues and the Academic Editor, Rebecca Grais, I am pleased to inform you that we have agreed to publish your manuscript "The association between COVID-19 vaccination and sudden death in apparently healthy younger individuals: a population-based case-control study" (PMEDICINE-D-25-01000R4) in PLOS Medicine.

Before your manuscript can formally we accepted, we have two remaining request:

1) Please remove 'speculated' from the sentence on line 112.

2) Please consider removing 'the' from your title.

Furthermore, before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. Once you have received these formatting requests, please note that your manuscript will not be scheduled for publication until you have made the required changes.

In the meantime, please log into Editorial Manager at http://www.editorialmanager.com/pmedicine/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process.

PRESS

We frequently collaborate with press offices. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximise its impact. If the press office is planning to promote your findings, we would be grateful if they could coordinate with medicinepress@plos.org. If you have not yet opted out of the early version process, we ask that you notify us immediately of any press plans so that we may do so on your behalf.

We also ask that you take this opportunity to read our Embargo Policy regarding the discussion, promotion and media coverage of work that is yet to be published by PLOS. As your manuscript is not yet published, it is bound by the conditions of our Embargo Policy. Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit http://www.plos.org/about/media-inquiries/embargo-policy/.

Thank you again for submitting to PLOS Medicine. We look forward to publishing your paper.

Sincerely,

Suzanne De Bruijn, PhD

Associate Editor

PLOS Medicine

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Checklist. Reporting of Studies Conducted using Observational Routinely-Collected Data (RECORD) checklist.

(DOCX)

pmed.1004924.s001.docx^{(21.3KB, docx)}

S1 Table. ICD-10 diagnostic codes used for defining a case.

(DOCX)

pmed.1004924.s002.docx^{(13.3KB, docx)}

S2 Table. Baseline characteristics of the residents of Ontario, Canada who met criteria for inclusion in the study.

(DOCX)

pmed.1004924.s003.docx^{(18.7KB, docx)}

S3 Table. Baseline characteristics of matched cases and controls aged <40 years.

(DOCX)

pmed.1004924.s004.docx^{(19.3KB, docx)}

S4 Table. Baseline characteristics of matched cases and controls excluding opioid-related deaths.

(S4_Table.DOCX)

pmed.1004924.s005.docx^{(20.2KB, docx)}

S5 Table. Baseline characteristics of matched cases and controls only including deaths within 24-hours of presenting to the hospital.

(DOCX)

pmed.1004924.s006.docx^{(20.2KB, docx)}

The analysis adjusted for age and quarterly rate of sudden death among unvaccinated individuals.

(DOCX)

pmed.1004924.s007.docx^{(15.4KB, docx)}

(TIFF)

pmed.1004924.s008.tiff^{(2.5MB, tiff)}

(TIFF)

pmed.1004924.s009.tiff^{(2.5MB, tiff)}

(TIFF)

pmed.1004924.s010.tiff^{(2.5MB, tiff)}

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Submitted filename: Final Response letter - Nov 2.docx

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Submitted filename: Response Letter - January, 2026.docx

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Submitted filename: Response to Editorial Requests - Jan 15.docx

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Data Availability Statement

[pmed.1004924.ref001] 1.Tuite AR, Ng V, Ximenes R, Diener A, Rafferty E, Ogden NH, et al. Quantifying the economic gains associated with COVID-19 vaccination in the Canadian population: a cost-benefit analysis. Can Commun Dis Rep. 2023;49(6):263–73. doi: 10.14745/ccdr.v49i06a03 [DOI] [PMC free article] [PubMed] [Google Scholar]

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[pmed.1004924.ref004] 4.Klok FA, Pai M, Huisman MV, Makris M. Vaccine-induced immune thrombotic thrombocytopenia. Lancet Haematol. 2022;9(1):e73–80. doi: 10.1016/S2352-3026(21)00306-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1004924.ref005] 5.WHO. WHO COVID-19 dashboard data [cited 2024 Jan 19]. COVID-19 vaccination data. Available from: https://data.who.int/dashboards/covid19/data?n=c

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PERMALINK

Association between COVID-19 vaccination and sudden death in apparently healthy younger individuals: A population-based case-control study

Husam Abdel-Qadir

Hardil Anup Bhatt

Sarah Swayze

Michael Paterson

Dennis T Ko

David N Juurlink

Jeffrey C Kwong

Roles

Abstract

Background

Methods and findings

Conclusions

Author summary

Why was this study done?

What did the researchers do and find?

What do these findings mean?

Introduction

Methods

Study design, setting, and population

Definition of cases and controls

Definition of the exposure

Statistical analysis

Ethics approval

Results

Table 1. Baseline characteristics of residents of Ontario, Canada who were included in the case-control analysis.

Fig 2. The adjusted odds ratio (with 95% confidence interval) for death and COVID-19 vaccination among the matched cohort (n = 28,836) assessed using conditional logistic regression modeling.

People aged <40 years

Analyses excluding opioid-related deaths

Deaths in hospital or an emergency department

Modified SCCS analysis

Discussion

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Suzanne De Bruijn

Roles

Decision Letter 1

Suzanne De Bruijn

Roles

Author response to Decision Letter 2

Decision Letter 2

Suzanne De Bruijn

Roles

Author response to Decision Letter 3

Decision Letter 3

Suzanne De Bruijn

Roles

Author response to Decision Letter 4

Decision Letter 4

Suzanne De Bruijn

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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