First dose ChAdOx1 and BNT162b2 COVID-19 vaccinations and cerebral venous sinus thrombosis: A pooled self-controlled case series study of 11.6 million individuals in England, Scotland, and Wales.

BACKGROUND: Several countries restricted the administration of ChAdOx1 to older age groups in 2021 over safety concerns following case reports and observed versus expected analyses suggesting a possible association with cerebral venous sinus thrombosis (CVST). Large datasets are required to precisely estimate the association between Coronavirus Disease 2019 (COVID-19) vaccination and CVST due to the extreme rarity of this event. We aimed to accomplish this by combining national data from England, Scotland, and Wales. METHODS AND
FINDINGS: We created data platforms consisting of linked primary care, secondary care, mortality, and virological testing data in each of England, Scotland, and Wales, with a combined cohort of 11,637,157 people and 6,808,293 person years of follow-up. The cohort start date was December 8, 2020, and the end date was June 30, 2021. The outcome measure we examined was incident CVST events recorded in either primary or secondary care records. We carried out a self-controlled case series (SCCS) analysis of this outcome following first dose vaccination with ChAdOx1 and BNT162b2. The observation period consisted of an initial 90-day reference period, followed by a 2-week prerisk period directly prior to vaccination, and a 4-week risk period following vaccination. Counts of CVST cases from each country were tallied, then expanded into a full dataset with 1 row for each individual and observation time period. There was a combined total of 201 incident CVST events in the cohorts (29.5 per million person years). There were 81 CVST events in the observation period among those who a received first dose of ChAdOx1 (approximately 16.34 per million doses) and 40 for those who received a first dose of BNT162b2 (approximately 12.60 per million doses). We fitted conditional Poisson models to estimate incidence rate ratios (IRRs). Vaccination with ChAdOx1 was associated with an elevated risk of incident CVST events in the 28 days following vaccination, IRR = 1.93 (95% confidence interval (CI) 1.20 to 3.11). We did not find an association between BNT162b2 and CVST in the 28 days following vaccination, IRR = 0.78 (95% CI 0.34 to 1.77). Our study had some limitations. The SCCS study design implicitly controls for variables that are constant over the observation period, but also assumes that outcome events are independent of exposure. This assumption may not be satisfied in the case of CVST, firstly because it is a serious adverse event, and secondly because the vaccination programme in the United Kingdom prioritised the clinically extremely vulnerable and those with underlying health conditions, which may have caused a selection effect for individuals more prone to CVST. Although we pooled data from several large datasets, there was still a low number of events, which may have caused imprecision in our estimates.
CONCLUSIONS: In this study, we observed a small elevated risk of CVST events following vaccination with ChAdOx1, but not BNT162b2. Our analysis pooled information from large datasets from England, Scotland, and Wales. This evidence may be useful in risk-benefit analyses of vaccine policies and in providing quantification of risks associated with vaccination to the general public.

Introduction

There have been concerns over possible associations between some Coronavirus Disease 2019 (COVID-19) vaccines and hematological and vascular adverse events, including, in particular, cerebral venous sinus thrombosis (CVST) following ChAdOx1 nCoV-19 (Oxford/AstraZeneca; henceforth ChAdOx1). A number of case reports and case series of CVST following adenovirus vector COVID-19 vaccination have been published [1-5]. A potential link between ChAdOx1 was initially noted by the European Medicines Agency (EMA) in a safety update on March 29, 2021 [6]. On April 8, 2021, the EMA issued an analysis of pharmacovigilance data covering the European Economic Area that found a safety signal for CVST following ChAdOx1 vaccination, risk ratio = 7.73 (95% confidence interval (CI) 5.35 to 10.80) [7]. An observed versus expected analysis using data from the Mayo Clinic Health System in the United States found a relative risk of 1.50 (95% CI 0.28 to 7.10) of CVST in a combined analysis of COVID-19 vaccines [8]. An observed versus expected analysis in Denmark and Norway found a standardised morbidity ratio of 20.25 (95% CI 8.14 to 41.73) for cerebral venous thrombosis following ChAdOx1 vaccination [9]. A self-controlled case series (SCCS) using the QResearch database in England found incidence rate ratio (IRR) in the 8 to 28 days following vaccination of 2.37 (95% CI 1.34 to 4.21) for ChAdOx1 and 1.93 (95% CI 0.87 to 4.28) for BNT162b2 [10]. Several countries suspended ChAdOx1 or restricted its use to older age groups due to these and other safety concerns [11]. The Joint Committee on Vaccination and Immunisation (JCVI), an independent UK-wide body that advises the government on vaccine approval, has recommended that adults under the age of 40 should be offered an alternative to the ChAdOx1 vaccine, if available [12,13].

At the time of writing, 3 vaccines are being administered in the UK: ChAdOx1, BNT162b2 (Pfizer-BioNTech), and mRNA-1273 (Moderna). They have all shown high levels of efficacy in Phase II and III clinical trials [14-16]. ChAdOx1 and BNT162b2 have also shown high levels of “real-world effectiveness” against COVID-19 hospitalisation and death [17,18]. Vaccine rollout in the UK started with BNT162b2 on December 8, 2020, followed by ChAdOx1 on January 4, 2021 and mRNA-1273 on April 7, 2021. Guidance from the JCVI included a list of priority groups with the elderly, frontline social and health care workers, and the clinically extremely vulnerable at the highest levels of priority (S2 File). Relatively few people in our cohort were vaccinated with mRNA-1273, so this study focused on BNT162b2 and ChAdOx1 only.

The aim of this study was to investigate possible associations between COVID-19 vaccines and CVST. We carried out a SCCS study of CVST events following first dose vaccination with ChAdOx1 and BNT162b2. The data platform used in this study consisted of linked primary care, secondary care, mortality and virological testing data stored in secure trusted research environments (TREs) in each of England, Scotland, and Wales. CVST is an extremely rare event, with an estimated incidence of 3 to 4 per million person years in adults [19]. In our previous analysis exploring COVID-19 vaccine associations with thrombocytopenic, thromboembolic, and hemorrhagic events using Scottish national data, there were insufficient CVST events to undertake a statistical analysis [20]. We were not able to reliably estimate the association between COVID-19 vaccines and CVST with any individual country-specific dataset due to the low number of events. In order to address this, we pooled incident CVST cases from each of the datasets and carried out a SCCS analysis to estimate IRRs for CVST in those who received a first dose of ChAdOx1 or BNT162b2 vaccines.

Methods

Study design and population

We followed a prespecified statistical analysis plan (S3 File). The datasets consisted of linked primary care, secondary care, mortality, and virological testing data stored in secure TREs in each of England, Scotland, and Wales (Fig 1). These data were deterministically linked using unique patient identifiers—NHS number in England and Community Health Index (CHI) number in Scotland. In Wales, a combination of deterministic linkage based on NHS number and probabilistic linkage based personal identifiers was used. Anyone under the age of 16 at the date of event was excluded. A case was defined as anyone in our cohorts with a CVST event following the start of the COVID-19 vaccination programme in the UK. An incident case was defined as the first such event in the cohort time period. The cohort start date was December 8, 2020, and the end date was June 30, 2021.

Fig 1

Data linkage diagram.

ADDD, Annual District Death Daily; ADDE, Annual District Death Extract; CCDS, Critical Care Dataset; CDDS, Consolidated Death Data Source; ConCov, Controlling COVID-19 through enhanced population surveilance and intervention; CVVD, COVID-19 Vaccine Data; EAVE, Early Assessment of Vaccine and antiviral Effectiveness; ECOSS, Electronic Communication of Surveillance in Scotland; EDDS, Emergency Department Dataset; GP, general practices; HES, Hospital Episode Statistics; ICCD, ICNARC – Intensive Care National Audit & Research Centre (COVID only admissions); ICNC, Intensive Care National Audit & Research Centre; NHS, National Health Service; NIMS, National Immunisation Management System; NRS, National Records of Scotland; ONS, Office for National Statistics; PATD, Pathology data COVID-19 Daily; PEDW, Patient Episode Database for Wales; PHS, Publish Health Scotland; RCGP RSC, Oxford-Royal College of General Practitioners Research and Surveillance Centre; SICSAG, Scottish Intensive Care Society Audit Group; SMR01, Scottish Morbidity Records 01; SUS, Secondary Users Service; TVMT, Turas Vaccine Management Tool; WDSD, Welsh Demographic Service Dataset; WLGP, Welsh Longitudinal General Practice Dataset.

In accordance with our statistical analysis plan, we initially sought to carry out a meta-analysis of estimates from each country. However, there were too few events in each country for this to be feasible. As a result, we undertook a pooled analyses of aggregate count data from each country. We sought to carry out both a SCCS study and a case–control study using pooled data. However, the case–control study would have required sharing of individual-level information, which was not permitted under the data governance rules implemented by each country’s TREs. Therefore, we focused on the pooled SCCS study.

The observation period for the SCCS started 104 days before first dose vaccination and ended 28 days after first dose vaccination (Fig 2). The reference period was defined as the first 90 days of the observation period. The prerisk period was defined as the 14-day period prior to first dose vaccination. The risk period was defined as 0 to 28 days post–first dose vaccination. No individual was censored because we examined incident cases only. We pooled data across the 3 nations on incident cases during the observation period around first dose vaccination with ChAdOx1 or BNT162b2 (Fig 3). Each stratum consisted of an incident case during the reference, prerisk, and risk periods.

Fig 2

SCCS study design.

SCCS, self-controlled case series.

Fig 3

Selection procedure.

CVST, cerebral venous sinus thrombosis.

Exposure

We defined an individual as exposed from the day they were administered their first dose of either the BNT162b2 or ChAdOx1 vaccines.

Outcomes

The outcome of interest was incident CVST cases in the observation period. SNOMED codes were used to identify CVST events recorded in primary care electronic health records in England, and Read Codes (Version 2) were used in Scotland and Wales (S4 File). International Classification of Diseases-10th Revision (ICD-10) codes were used to identify CVST events in hospital admission records (S4 File). SNOMED and Read Codes have hierarchies that enable thromboembolic events to be grouped by their location. These enable recording of the diagnosis of an event of interest—for example, a thromboembolic event could be recorded as intracranial, with further subdivisions into CVST, intracranial thrombophlebitis, and thrombosis of cerebral veins, within the SNOMED hierarchy. The code lists used in this study were drawn up by the Early Assessment of Vaccine and antiviral Effectiveness (EAVE) II clinical team and validated by experts in neurology and hematology.

Statistical analysis

The data governance procedure of the TREs in each country did not allow for individual level data to be shared. However, we obtained permissions to confidentially share counts of individuals stratified by categories, on the understanding that these would be combined in a pooled count. For a SCCS study of the rate ratios (RRs) of incident events in the observation time periods that does not include any covariates, the only information that is required to estimate the conditional Poisson model is event counts in the reference, prerisk, and risk periods. Analysts in each country had full access to their country’s data. Counts of incident cases in the reference, prerisk, and risk periods stratified by vaccine type received were collated in each nation. These were then gathered in the Scottish TRE and expanded into a full dataset with 1 row per individual and observation time period. Synthetic IDs were generated in order to distinguish distinct incident cases in the count data from each other and to label the strata in the model. The process of pooling the data is explained in more detail in the Supporting information (S5 File). IRRs and their 95% CIs were estimated using a conditional Poisson model, with cases during the reference, prerisk, and risk periods as the strata and an offset for the length of each time period. The reference period was taken as the baseline period for calculating IRRs. Conditional Poisson models have a likelihood function that is identical to the corresponding conditional logistic model [21]. Furthermore, incident events can occur at most once. Thus, we used the clogit function for conditional logistic regression from the survival package in R to fit the model. Following a suggestion from one of the reviewers, we undertook 2 post hoc sensitivity analyses: The first excluded any cases who died within 90 days of their event in order to explore the SCCS assumption of event-dependent exposure, and the second focused only on CVST cases identified in secondary care records.

Ethics and permission

In England, approvals were obtained from the Health Research Authority, London Central (reference number 21/HRA/2786). In Scotland, data approvals were obtained from the National Research Ethics Service Committee, Southeast Scotland 02 (reference number: 12/SS/0201), and Public Benefit and Privacy Panel for Health and Social Care (reference number: 1920–0279). In Wales, approval was provided by SAIL independent Information Governance Review Panel (IGRP) (Project 0911).

Reporting

This study is reported in accordance with the REporting of studies Conducted using Observational Routinely-collected Data (RECORD) guidelines (S1 File) [22,23].

Results

The cohorts started on December 8, 2020 and ended on June 30, 2021. Tables 1–3 show the marginal distributions of a number of characteristics in each country’s cohort. Clinical risk groups in these tables were derived from the QCovid algorithm [24]. Among the approximately 4.95 million people vaccinated with ChAdOx1, there were 45 incident cases of CVST during the 90-day reference period and 27 incident cases of CVST during the 28-day postvaccine risk period. We found an IRR of 1.93 (95% CI 1.20 to 3.11) in the risk period following first dose vaccination with ChAdOx1 and an IRR of 0.78 (95% CI 0.34 to 1.77) in the risk period following first dose vaccination with BNT162b2 (Table 4). Assuming a baseline incidence of 3 to 4 cases of CVST per million people per year outside of the risk period, our estimates imply an absolute risk of 0.44 to 0.59 incident CVST cases per million people in the 4-week risk period following vaccination with ChAdOx1.

Table 1

Cohort summary statistics, England.

Characteristic	Level	Unvaccinated	One-dose ChAdOx1	One-dose BNT162b2
Total		1,322,305	2,247,155	1,629,360
Person years of follow-up		745,303	1,269,229	927,224
Incident CVST cases		27	49	30
Deaths		16,369 (1.2%)	11,327 (0.5%)	8,066 (0.5%)
Sex	Female	649,546 (49.1%)	1,176,988 (52.4%)	924,283 (56.7%)
	Male	672,759 (50.9%)	1,070,167 (47.6%)	705,077 (43.3%)
Age (years)	Mean (SD)	38.58 (15.54)	56.49 (14.77)	52.56 (21.67)
Age group (years)	18 to 64	1,222,023 (92.4%)	1,576,834 (70.2%)	1,067,807 (65.5%)
	65 to 79	69,637 (5.3%)	558,596 (24.9%)	318,241 (19.5%)
	80+	30,645 (2.3%)	111,725 (5.0%)	243,312 (14.9%)
Deprivation status†	1 (high)	303,447 (22.9%)	323,925 (14.4%)	232,356 (14.3%)
	2	295,143 (22.3%)	381,384 (17.0%)	290,696 (17.8%)
	3	253,275 (19.2%)	451,355 (20.1%)	333,697 (20.5%)
	4	239,858 (18.1%)	512,133 (22.8%)	368,663 (22.6%)
	5 (low)	229,464 (17.4%)	576,815 (25.7%)	402,905 (24.7%)
	Unknown	1,118 (0.1%)	1,543 (0.1%)	1,043 (0.1%)
Urban/rural index	Rural town and fringe	324,138 (14.4%)	221,355 (13.6%)	106,384 (8.0%)
	Rural town and fringe in a sparse setting	32,629 (1.5%)	21,147 (1.3%)	8,133 (0.6%)
	Rural village and dispersed	51,315 (2.3%)	34,761 (2.1%)	19,813 (1.5%)
	Rural village and dispersed in a sparse setting	8,122 (0.4%)	5,633 (0.3%)	4,225 (0.3%)
	Urban city and town	1,116,335 (49.7%)	783,133 (48.1%)	591,421 (44.7%)
	Urban city and town in a sparse setting	10,593 (0.5%)	6,858 (0.4%)	3,384 (0.3%)
	Urban major conurbation	614,524 (27.3%)	494,346 (30.3%)	549,592 (41.6%)
	Urban minor conurbation	81,632 (3.6%)	56,723 (3.5%)	35,933 (2.7%)
	Unknown	7,867 (0.4%)	5,404 (0.3%)	3,420 (0.3%)
Number of risk groups‡	0	908,219 (68.7%)	1,165,109 (51.8%)	807,851 (49.6%)
	1	304,222 (23.0%)	661,515 (29.4%)	475,206 (29.2%)
	2	76,147 (5.8%)	255,007 (11.3%)	199,650 (12.3%)
	3	19,985 (1.5%)	96,980 (4.3%)	83,191 (5.1%)
	4	7,719 (0.6%)	40,388 (1.8%)	36,949 (2.3%)
	5+	6,013 (0.5%)	28,156 (1.3%)	26,513 (1.6%)
Number of previous tests§	0	1,147,503 (86.8%)	1,889,412 (84.1%)	1,350,615 (82.9%)
	1	119,612 (9.0%)	235.388 (10.5%)	183.933 (11.3%)
	2	34,089 (2.6%)	66,502 (3.0%)	53,012 (3.3%)
	3	10,610 (0.8%)	23,322 (1.0%)	17,770 (1.1%)
	4 to 9	10,442 (0.8%)	32,427 (1.4%)	23,953 (1.5%)
	10+	49 (0.0%)	104 (0.0%)	77 (0.0%)
Average household age	Mean (SD)	32.6 (17.5)	47.07 (21.61)	45.91 (24.88)
Number of people in household	1	338,168 (25.6%)	556,975 (24.8%)	429,940 (26.4%)
	2	261,989 (19.8%)	698,293 (31.1%)	499,565 (30.7%)
	3 to 5	551,966 (41.7%)	859,932 (38.3%)	602,873 (37.0%)
	6 to 10	129,832 (9.8%)	100,041 (4.5%)	75,591 (4.6%)
	11 to 30	18,660 (1.4%)	17,587 (0.8%)	9,650 (0.6%)
	31 to 100	6,485 (0.5%)	12,837 (0.6%)	6,950 (0.4%)
	101+	15,205 (1.1%)	1,490 (0.1%)	4,791 (0.3%)
BMI	Underweight	115,851 (8.8%)	46,480 (2.1%)	75,842 (4.7%)
	Normal weight	626,235 (47.4%)	757,023 (33.7%)	636,389 (39.1%)
	Overweight	359,299 (27.2%)	809,120 (36.0%)	527,780 (32.4%)
	Obese	220,920 (16.7%)	634,532 (28.2%)	389,349 (23.9%)
Smoking status	Ex-smoker	308,038 (23.3%)	657,234 (29.2%)	438,683 (26.9%)
	Nonsmoker	241,142 (18.2%)	1,241,281 (55.2%)	952,839 (58.5%)
	Smoker	714,755 (54.1%)	338,007 (15.0%)	209,358 (12.8%)
	Unknown	58,370 (4.4%)	10,633 (0.5%)	28,480 (1.7%)
Atrial fibrillation		11,713 (0.9%)	68,860 (3.1%)	74,990 (4.6%)
Asthma		180,744 (13.7%)	342,874 (15.3%)	264,060 (16.2%)
Blood cancer		4,066 (0.3%)	20,228 (0.9%)	18,117 (1.1%)
Heart failure		8,217 (0.6%)	40,231 (1.8%)	39,508 (2.4%)
Cerebral palsy		724 (0.1%)	3,326 (0.1%)	1,442 (0.1%)
Coronary heart disease		17,102 (1.3%)	100,989 (4.5%)	99,116 (6.1%)
Cirrhosis		1,678 (0.1%)	6,829 (0.3%)	4,598 (0.3%)
Congenital heart disease		4,399 (0.3%)	15,787 (0.7%)	10,637 (0.7%)
COPD		12,266 (0.9%)	69,891 (3.1%)	57,883 (3.6%)
Dementia		7,468 (0.6%)	29,271 (1.3%)	23,567 (1.4%)
Diabetes type 1		16,158 (0.7%)	16,158 (0.7%)	11,773 (0.7%)
Diabetes type 2		34,079 (2.6%)	185,353 (8.2%)	153,568 (9.4%)
Epilepsy		22,824 (1.7%)	52,820 (2.4%)	33,655 (2.1%)
Fracture		35,154 (2.7%)	89,439 (4.0%)	73,717 (4.5%)
Neurological disorder		1,964 (0.1%)	9,885 (0.4%)	6,276 (0.4%)
Parkinson disease		1,483 (0.1%)	8,338 (0.4%)	6,571 (0.4%)
Pulmonary hypertension		1,751 (0.1%)	8,106 (0.4%)	8,079 (0.5%)
Pulmonary rare		2,635 (0.2%)	16,128 (0.7%)	14,666 (0.9%)
Peripheral vascular disease		3,856 (0.3%)	20,518 (0.9%)	18,554 (1.1%)
Rheumatoid arthritis or SLE		7,909 (0.6%)	39,102 (1.7%)	27,449 (1.7%)
Respiratory cancer		1,891 (0.1%)	7,224 (0.3%)	5,814 (0.4%)
Severe mental illness		157,557 (11.9%)	387,974 (17.3%)	236,108 (14.5%)
Sickle cell disease		794 (0.1%)	1,731 (0.1%)	1,236 (0.1%)
Stroke/TIA		12,140 (0.9%)	64,068 (2.9%)	60,588 (3.7%)
Thrombosis or pulmonary embolus		5,219 (0.4%)	23,610 (1.1%)	18,864 (1.2%)
Care housing category	Care home	5,168 (0.4%)	21,534 (1.0%)	10,419 (0.6%)
	Homeless	5,026 (0.4%)	3,585 (0.2%)	1,563 (0.1%)
Learning disability or Down syndrome	Learning disability	15,620 (1.2%)	39,679 (1.8%)	23,426 (1.4%)
	Down syndrome	271 (0.0%)	1,857 (0.1%)	714 (0.0%)
Kidney disease	CKD5 without dialysis or transplant	18,609 (1.4%)	105,376 (4.7%)	121,038 (7.4%)
	CKD5 with dialysis	238 (0.0%)	928 (0.0%)	812 (0.0%)
	CKD5 with transplant	225 (0.0%)	1,530 (0.1%)	1,132 (0.1%)

†Deprivation status: quintiles of UK IMD (2000).

‡Number of risk groups: count of QCovid risk groups.

§Number of previous tests: proxy for working in a high-risk occupation (e.g., healthcare worker).

BMI, body mass index; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; CVST, cerebral venous sinus thrombosis; IMD, index of multiple deprivation; SD, standard deviation; SLE, systemic lupus erythematosus; TIA, transient ischemic attack.

Table 3

Cohort summary statistics, Wales.

Characteristic	Levels	Unvaccinated	One-dose ChAdOx1	One-dose BNT162b2
Total		346,683	964,494	717,224
Person years of follow-up		205,886	541,057	402,723
Incident CVST cases		6	24	9
Deaths		7,741 (2.2%)	6,876 (0.7%)	1,388 (0.2%)
Sex	Male	197,387 (56.9%)	476,300 (49.4%)	329,736 (46.0%)
	Female	149,296 (43.1%)	488,194 (50.6%)	387,488 (54.0%)
Age (years)	Mean (SD)	36.27 (17.10)	58.49 (15.94)	44.82 (19.60)
Age group (years)	18 to 64	274,386 (91.3%)	636,502 (66.0%)	538,559 (75.9%)
	65 to 79	17,389 (5.8%)	209,653 (21.7%)	158,915 (22.4%)
	80+	8,739 (2.9%)	117,968 (12.2%)	12,278 (1.7%)
Deprivation status†	1 (most deprived)	94,765 (27.3%)	183,424 (19.0%)	143,271 (20.0%)
	2	74,747 (21.6%)	195,260 (20.2%)	146,938 (20.5%)
	3	69,401 (20.0%)	190,358 (19.7%)	131,847 (18.4%)
	4	53,523 (15.4%)	191,504 (19.9%)	131,130 (18.3%)
	5 (least deprived)	54,247 (15.6%)	203,948 (21.1%)	164,038 (22.9%)
Number of risk groups‡	1	129,012 (37.2%)	181,916 (18.9%)	211,942 (29.6%)
	2	122,262 (35.3%)	305,529 (31.7%)	256,138 (35.7%)
	3	60,691 (17.5%)	239,308 (24.8%)	150,040 (20.9%)
	4	22,745 (6.6%)	129,906 (13.5%)	61,613 (8.6%)
	5+	11,973 (3.5%)	107,835 (11.2%)	37,491 (5.2%)
Number of previous tests§	0	289,816 (83.6%)	787,529 (81.7%)	525,062 (73.2%)
	1	39,404 (11.4%)	122,007 (12.6%)	123,853 (17.3%)
	2	9,074 (2.6%)	28,177 (2.9%)	32,648 (4.6%)
	3	2,676 (0.8%)	9,090 (0.9%)	9,544 (1.3%)
	4 to 9	3,371 (1.0%)	11,425 (1.2%)	10,037 (1.4%)
Average household age	Mean (SD)	36.12 (15.09)	52.28 (18.83)	42.83 (18.64)
Number of people in household	1	35,087 (10.1%)	164,573 (17.1%)	77,093 (10.8%)
	2	59,280 (17.1%)	322,717 (33.5%)	190,182 (26.5%)
	3 to 5	191,646 (55.4%)	413,605 (42.9%)	389,868 (54.4%)
	6 to 10	52,028 (15.0%)	47,698 (4.9%)	53,992 (7.5%)
	11 to 30	5,817 (1.7%)	10,467 (1.1%)	4,431 (0.6%)
	31 to 100	1,164 (0.3%)	4,356 (0.5%)	882 (0.1%)
	101+	830 (0.2%)	183 (0.0%)	408 (0.1%)
BMI	Normal weight	137,044 (39.8%)	238,075 (24.7%)	214,268 (29.9%)
	Obese	75,615 (21.9%)	374,711 (38.9%)	237,832 (33.2%)
	Overweight	103,442 (30.0%)	325,633 (33.8%)	237,648 (33.2%)
	Underweight	28,634 (8.3%)	25,261 (2.6%)	26,418 (3.7%)
Smoking status	Ex-smoker	37,314 (10.8%)	231,039 (24.0%)	127,107 (17.7%)
	Nonsmoker	140,892 (40.6%)	512,280 (53.1%)	402,210 (56.1%)
	Smoker	98,437 (28.4%)	201,499 (20.9%)	136,068 (19.0%)
	Unknown	70,040 (20.2%)	19,676 (2.0%)	51,839 (7.2%)
Atrial fibrillation		3,005 (0.9%)	43,976 (4.6%)	15,274 (2.1%)
Asthma		45,591 (13.2%)	147,572 (15.3%)	110,270 (15.4%)
Blood cancer		699 (0.2%)	7,116 (0.7%)	2,886 (0.4%)
Heart failure		1,816 (0.5%)	22,248 (2.3%)	6,879 (1.0%)
Cirrhosis		586 (0.2%)	4,903 (0.5%)	1,889 (0.3%)
Congestive heart disease		4,482 (1.3%)	61,338 (6.4%)	22,283 (3.1%)
COPD		3,794 (1.1%)	44,984 (4.7%)	16,158 (2.3%)
Dementia		1,438 (0.4%)	13,155 (1.4%)	2,540 (0.4%)
Diabetes type I		714 (0.2%)	6,034 (0.6%)	1,628 (0.2%)
Diabetes type II		8,081 (2.3%)	108,610 (11.3%)	36,764 (5.1%)
Epilepsy		3,295 (1.0%)	18,776 (1.9%)	5,136 (0.7%)
Fracture		11,205 (3.2%)	40,808 (4.2%)	26,066 (3.6%)
Neurological disorder		439 (0.1%)	4,260 (0.4%)	1,154 (0.2%)
Parkinson disease		313 (0.1%)	3,845 (0.4%)	1,312 (0.2%)
Pulmonary hypertension		254 (0.1%)	2,550 (0.3%)	904 (0.1%)
Pulmonary rare		528 (0.2%)	6,287 (0.7%)	2,755 (0.4%)
Peripheral vascular disease		1,107 (0.3%)	12,368 (1.3%)	4,547 (0.6%)
Rheumatoid arthritis		1,376 (0.4%)	14,754 (1.5%)	6,454 (0.9%)
Respiratory cancer		495 (0.1%)	3,620 (0.4%)	1,621 (0.2%)
Severe mental illness		42,890 (12.4%)	153,083 (15.9%)	87,343 (12.2%)
Stroke		3,175 (0.9%)	39,032 (4.0%)	12,706 (1.8%)
Thrombosis or pulmonary embolus		3,468 (1.0%)	30,726 (3.2%)	10,296 (1.4%)
Care housing category	Care home	1,150 (0.3%)	7,729 (0.8%)	1,375 (0.2%)
	Homeless	2,308 (0.7%)	2,431 (0.3%)	1,230 (0.2%)
Learning disability or Down syndrome	Learning disability	7,232 (2.1%)	16,250 (1.7%)	9,397 (1.3%)
	Down syndrome	25 (0.0%)	195 (0.0%)	74 (0.0%)
Kidney disease	CKD5 without dialysis or transplant	277 (0.1%)	2,711 (0.3%)	802 (0.1%)
	CKD5 with transplant	69 (0.0%)	921 (0.1%)	364 (0.1%)
	CKD5 with dialysis	47 (0.0%)	304 (0.0%)	61 (0.0%)

†Deprivation status: WIMD 2020.

‡Number of risk groups: Individual QCovid.

§Number of previous tests: Proxy for working in a high-risk occupation (e.g., healthcare worker).

BMI, body mass index; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; CVST, cerebral venous sinus thrombosis; SD, standard deviation; SLE, systemic lupus erythematosus; TIA, transient ischemic attack; WIMD, Welsh index of multiple deprivation.

Table 4

Number of events and IRRs for CVST following first dose vaccination with ChAdOx1 and BNT162b2.

Time period	Number of events	IRR (95% CI)
ChAdOx1
Reference	45	1
Prerisk	9	1.29 (0.63 to 2.63)
Risk	27	1.93 (1.20 to 3.11)
BNT162b2
Reference	29	1
Prerisk	<5	0.89 (0.31 to 2.52)
Risk	7	0.78 (0.34 to 1.77)

Event counts of <5 have been suppressed in accordance with disclosure control principles implemented by the data controllers. With the day of vaccination as day 0, the reference period was day −104 to day −14. The prerisk period was day −14 to day 0. The risk period was day 0 to day 28.

CI, confidence interval; CVST, cerebral venous sinus thrombosis; IRR, incidence rate ratio.

We sought to carry out a post hoc sensitivity analysis focusing on CVST events identified in secondary care records only; however, there were too few events to permit useful estimation of IRRs. We carried out a post hoc sensitivity analysis excluding anyone who died within 90 days of their CVST event. The only estimate that changed from our main analysis was that for the risk period following vaccination with ChAdOx1, the IRR was 1.79 (95% CI 1.10 to 2.91) (S6 File).

Within each nation, we plotted histograms of event counts in the observation period in order to explore the suitability of the prerisk period to account for event-dependent exposure to vaccination. There appeared to be a reduction in events in the 2-week prerisk period, but no obvious reduction outside of that time period. We are unable to share these histograms due to the statistical disclosure principles enacted by the TREs that hosted this analysis.

Discussion

Our pooled SCCS analysis of national datasets from England, Scotland, and Wales found an elevated risk of CVST in the 4-week period following vaccination with ChAdOx1. We did not find an association between BNT162b2 and CVST.

There have hitherto been few population-based studies estimating the association between COVID-19 vaccines and CVST. Such analyses are made challenging by the extreme rarity of CVST. Our study corroborates previous observed–expected analyses from the EMA [7], the Mayo Clinic Health System [8], a population-based study in Denmark and Norway [9], and a SCCS using the QResearch database in England [10]. Our results are broadly consistent with the latter study [10], as would be expected due to the similar study design and population. Our estimated RRs are, however, notably smaller than risk ratios reported in [7-9]. This is likely due to the fact that we conducted a SCCS that implicitly controls for variables that are constant over the observation period, as opposed to an observed–expected analysis.

A limitation in the SCCS analysis is the assumption that occurrence of an event does not affect subsequent exposure [25]. CVST is a serious adverse event that can be life threatening. Therefore, the assumption of event-independent exposure may not have been satisfied. This could have caused a selection effect where individuals who were more likely to have a CVST event were less likely to be vaccinated and thus less likely to be included in our analysis. A large multinational study of prognosis for CVST found a death rate of 4.3% and a death or dependency rate of 18.9% at hospital discharge, where dependency was defined as a score of >2 on the modified Rankin scale [26]. On the other hand, among the JCVI priority groups for vaccination are “clinically extremely vulnerable individuals” (group 4), and “all individuals aged 16 to 64 years with underlying health conditions which put them at higher risk of serious disease and mortality” (group 6) (S2 File). It is possible that the vaccination programme created a selection effect for vaccination of people more prone to CVST events.

In order to explore the validity of the assumption of event-independent exposure, we carried out a sensitivity analysis excluding those who died within 90 days of their event. This had a small effect on the IRR for the risk period following vaccination with ChAdOx1, with all other estimates unchanged. We also included a prerisk period in the SCCS study design to account for the possibility that occurrence of a CVST event affected subsequent vaccination and plotted histograms of event counts over time in order to assess its suitability. Our statistical analysis plan included a case–control analysis, which may have been useful to further explore this assumption. However, this would have required sharing more detailed data between TREs, which was not possible under the permissions in place.

We estimated IRRs as opposed to RRs. Estimating RRs with pooled data across the 3 nations could be achieved if we were able to share individual-level data. However, this was not permitted under the statistical disclosure rules implemented by the data controllers. We do not believe that the estimates for RRs and IRRs would be significantly different because of the rarity of CVST events.

We plan to extend our analysis to mRNA-1273 and to second and booster dose vaccinations. To date, there have been very few studies that have estimated the association between COVID-19 vaccine and CVST events using large-scale nationally representative datasets [7-9]. Although we had access to a large, combined cohort, there were still relatively few events. Further evidence corroborating our results is required.

In conclusion, we found an increased risk of CVST following first dose vaccination with ChAdOx1. We did not find an increased risk following first dose vaccination with BNT162b2. This evidence may be useful in risk–benefit evaluations for vaccine-related policies and in providing quantification of risks associated with vaccination to the general public.

STROBE and RECORD checklists.

RECORD, REporting of studies Conducted using Observational Routinely-collected Data; STROBE, STrengthening the Reporting of OBservational studies in Epidemiology.

(DOCX)

Click here for additional data file.

Vaccine priority groups.

Context of vaccine roll-out in the UK: JCVI COVID-19 vaccination priority group list. COVID-19, Coronavirus Disease 2019; JCVI, Joint Committee on Vaccination and Immunisation.

(DOCX)

Click here for additional data file.

Statistical analysis plan.

(DOCX)

Click here for additional data file.

Code lists.

Read Codes and SNOMED CT codes for CVST. CVST, cerebral venous sinus thrombosis.

(DOCX)

Click here for additional data file.

Data pooling procedure.

(DOCX)

Click here for additional data file.

Sensitivity analysis.

(DOCX)

Click here for additional data file.

23 Aug 2021

Dear Dr Kerr,

Thank you for submitting your manuscript entitled "First dose ChAdOx1 and BNT162b2 COVID-19 vaccinations and cerebral venous sinus thrombosis: pooled self-controlled case series of UK datasets" for consideration by PLOS Medicine.

Your manuscript has now been evaluated by the PLOS Medicine editorial staff and I am writing to let you know that we would like to send your submission out for external peer review.

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Louise Gaynor-Brook, MBBS PhD

Senior Editor

PLOS Medicine

22 Sep 2021

Dear Dr. Kerr,

Thank you very much for submitting your manuscript "First dose ChAdOx1 and BNT162b2 COVID-19 vaccinations and cerebral venous sinus thrombosis: pooled self-controlled case series of UK datasets" (PMEDICINE-D-21-03598R1) for consideration at PLOS Medicine.

Your paper was evaluated by three independent reviewers, including a statistical reviewer, and was discussed among all the editors here and with an academic editor with relevant expertise. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

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Associate Editor

PLOS Medicine

plosmedicine.org

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

Requests from the editors:

General comments:

Throughout the paper, please adapt reference call-outs to the following style: "... ChAdOx1 vaccine, if available [11,12]." (noting the absence of spaces within the square brackets).

Title: Please revise your title according to PLOS Medicine's style. We suggest “First dose ChAdOx1 and BNT162b2 COVID-19 vaccinations and cerebral venous sinus thrombosis: A pooled self-controlled case series study of 12 million individuals in England, Scotland and Wales” or similar

Abstract:

Abstract Background: Please specify which COVID-19 vaccines were restricted. “England, Scotland and Wales” would be preferable to “Great Britain”

Abstract Methods and Findings:

Please provide brief demographic details of the study population (e.g. sex, age, ethnicity, etc)

Please provide the exact number of participants, population, the dates between which the study took place, length of follow up, and main outcome measures.

If possible, please provide the actual incidence of CVST in the study population in addition to IRRs

Line 62 - Please revise to “Vaccination with ChAdOx1 was associated with an elevated risk…”

In the last sentence of the Abstract Methods and Findings section, please describe 2-3 of the main limitations of the study's methodology.

Abstract Conclusions:

Please begin your Abstract Conclusions with "In this study, we observed ..." or similar, to summarize the main findings from your study, without overstating your conclusions. Please emphasize what is new and address the specific implications of your study, being careful to avoid assertions of primacy and general statements such as "these results have implications for policy".

Author Summary:

At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

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Please add the following statement, or similar, to the Methods: "This study is reported as per the REporting of studies Conducted using Observational Routinely-collected Data (RECORD) guideline (S1 Checklist)."

Line 153 - sentence appears incomplete

Results:

Please provide a table showing the baseline characteristics of the study population as Table 1.

Please replace ~ with approximately

Line 184 - please revise to ‘incident cases of CVST’

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Please present and organize the Discussion as follows: a short, clear summary of the article's findings; what the study adds to existing research and where and why the results may differ from previous research; strengths and limitations of the study; implications and next steps for research, clinical practice, and/or public policy; one-paragraph conclusion.

Line 202 - please temper assertions of primacy by adding ‘to the best of our knowledge’ or similar. “England, Scotland and Wales” would be preferable to “Great Britain”

Tables:

Please define all abbreviations used in the table legend of each table.

References:

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Comments from the reviewers:

Reviewer #1: "First dose ChAdOx1 and BNT162b2 COVID-19 vaccinations and cerebral venous sinus thrombosis: pooled self-controlled case series of UK datasets" is a concise self-controlled case series (SCCS) analysis on incident cerebral venous sinus thrombosis (CVST) events, on over 12 million individuals from England, Scotland and Wales. The extremely low incidences for CVST (<50 for 4.33 million ChAdOx1 doses, <15 for 2.32 million BNT162b2 doses) has made any conclusive determination of increased risk challenging. With the SCCS design that implicitly controls for time-invariant variables (by effectively comparing every individual against himself before [including a clearance period] and after dosing), a 2.66 (1.48-4.79) incidence rate ratio (IRR) was found for ChAdOx1, against 1.07 (0.22-5.31) for BNT162b2 (Table 2).

While the study framework appears to allow for the analysis of other potential side effects in addition to CVST, this submission remains a timely addition to the literature, with further work on mRNA-1273 and further doses already proposed (Line 236). Still, a few issues might be considered:

1. While the description of the data compilation is relatively comprehensive (Figure 1), the detailed selection of the cohort might stand to be defined in greater detail. For example, the starting point (all individual given at least one dose of either the ChAdOx1 or BNT162b2 vaccine?) and any exclusions (e.g. missing data) might be presented in a flowchart.

2. While simple cohort demographics are provided in Table 1, it appears relevant to also present other demographic variables (e.g. age, gender, ethnicity, etc.) stratified by vaccine received, which would moreover help to give an idea of whether the demographics for each vaccine are comparable (all the more as their administration appears non-random from S1 Table).

Moreover, it appears possible that the underlying demographics may remain important in the analysis of IRR (related to the selection bias raised in Line 218), despite the SCCS study design. For example, assume that a rare disease has effectively zero incidence below a certain age (e.g. 50 years). Then, if Treatment A were provided mostly to those below that age, and Treatment B mostly to those above that age, then the potential for incidence would appear biased towards Treatment B (before considerations on whether increased disease incidence due to vaccine dosing is itself affected by age and other variables). Notably, from Table 2, given the 25 pre-risk events for ChAdOx1 (4.33 million doses), about 13 pre-risk events would be expected for BNT162b2 (2.32 million doses). However, only 6 pre-risk events were observed for BNT162b2 in reality. A fuller evaluation of the demographics for each vaccine group might therefore be warranted.

3. Data coverage would seem to remain somewhat of a concern, especially for the English data (~10% GP coverage, from Figure 1). In particular, the validity of SCCS would seem to assume individuals remaining "in system" throughout, i.e. if CVST were to occur for an individual, this CVST incidence would be expected to be recorded whether in the pre-risk, clearance or risk period. Would this be a reasonable expectation, or is it possible that CVST be treated at a venue that is not included in the databases used (e.g. the ~90% of GP practices not covered, for England)?

Reviewer #2: Thank you for the opportunity to review this manuscript on a matter of importance to public health.

Major comments:

1. 34 authors? Please elaborate.

2. Overall, the manuscript appears rushed and needs more attention. See e.g. line 153?

3. I do not understand the statistical approach. It is unclear what aggregation in each country and then expansion with so-called synthetic ID's is. If this means that you have first aggregated the true events and then tried to reconstruct synthetic events I am concerned. Please provide more detail and references that this is a valid approach. Alternatively, please estimate the association in each country and combine the three using e.g. inverse variance weighting.

4. Please provide sensitivity analyses supporting that the assumptions of the SCCS analysis is not violated.

5. Please provide a figure with two panels: each panel showing a histogram of the timing of event compared to date of vaccination with the two vaccines.

6. You need to convince the reader that the many SNOMED and READ codes you have included accurately reflect CVST. Have these been validated?

7. Are you including GP information? Can you please provide a sensitivity analysis of only cases identified in a hospital setting.

8. What are you using laboratory data for?

9. You need to discuss your results in more detail in comparison to other studies. You report a <1 CVST case per 1 mil vaccinated. This is much less than what others have reported.

10. You conclude "Public health officials should take account of this evidence in designing policies on vaccination." What do you mean? Elaborate please?

Minor comments:

11. incidence rate ratio instead of incident rate ratio

12. I am confused by the Sup table 1 mentioning Scotland only?

13. In SCCS terminology, a pre-risk period is your clearance period and the reference period is your pre-risk period.

Reviewer #3: This is a straightforward analysis and methodological sound. However, I fail to see the novelty of the data as the association between CVT and vaccination has already been reported. Nonetheless, the study provides estimates for the British population.

Some important data is missing and could add relevant information. Please provide data on mortality, demographic differences, or association with coagulation disorders.

You might consider presenting you findings as a brief report or as a letter.

The figure legends are somewhat misplaced in the text.

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

[LINK]

12 Nov 2021

Submitted filename: Response letter.docx

Click here for additional data file.

1 Dec 2021

Dear Dr. Kerr,

Thank you very much for submitting your manuscript "First dose ChAdOx1 and BNT162b2 COVID-19 vaccinations and cerebral venous sinus thrombosis: A pooled self-controlled case series study of 11.6 million individuals in England, Scotland and Wales" (PMEDICINE-D-21-03598R2) for consideration at PLOS Medicine.

Your paper was re-reviewed by three reviewers and discussed among all the editors here. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of the statistical re-review, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We expect to receive your revised manuscript by Dec 22 2021 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***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.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript.

Sincerely,

Louise Gaynor-Brook, MBBS PhD

Associate Editor, PLOS Medicine

plosmedicine.org

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

Requests from the editors:

It is of concern that the results of your analysis appear to have changed substantially during your revision (Table 4) - in particular, the differences in numbers of events. Please provide clarification as to how the revised results were generated, including changes in the data used and methodology. This may be subject to statistical re-review.

Comments from the reviewers:

Reviewer #1: Figure 2 defining the pre-risk, clearance and risk periods appears unchanged from the previous revision (R1). However Table 4 for reference/pre-risk/risk events/incidence rate ratios appears wholly different from Table 2 from the previous revision (R1). This might be clarified, since it appears the core of the analysis.

Reviewer #2: The authors have satisfactorily addressed my comments. Thank you.

Reviewer #3: all well addressed

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

[LINK]

6 Dec 2021

Submitted filename: Response letter 2.docx

Click here for additional data file.

14 Jan 2022

Dear Dr. Kerr,

Thank you very much for re-submitting your manuscript "First dose ChAdOx1 and BNT162b2 COVID-19 vaccinations and cerebral venous sinus thrombosis: A pooled self-controlled case series study of 11.6 million individuals in England, Scotland and Wales" (PMEDICINE-D-21-03598R3) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor. 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.

The remaining issues that need to be addressed are listed at the end of this email. 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.***

In revising the manuscript for further consideration here, please ensure you address the specific points made by the editors. In your rebuttal letter you should indicate your response to the editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper.

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

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Requests from Editors:

Abstract Methods and Findings:

Please revise to “6,808,293 person years of follow-up”

If possible, please provide a brief demographic summary of the study population(s) (e.g. % female, mean age (SD), etc)

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Please revise to “following first dose vaccination with either ChAdOx1 or Pfizer BioNTech (BNT162b2)”, or similar

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Please add a final bullet point to ‘What Do These Findings Mean?’ to describe the main limitations of the study in non-technical language.

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Please revise to “...United States found a relative risk of 1.50 (95% CI 0.28-7.10) of CVST …”

Methods

Please provide your STROBE/RECORD checklist as (S1 Checklist)

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Please revise “4.95 million people total vaccinated”

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[LINK]

17 Jan 2022

Submitted filename: Response letter 3.docx

Click here for additional data file.

21 Jan 2022

Dear Dr Kerr,

On behalf of my colleagues and the Academic Editor, Prof. Suzanne Cannegieter, I am pleased to inform you that we have agreed to publish your manuscript "First dose ChAdOx1 and BNT162b2 COVID-19 vaccinations and cerebral venous sinus thrombosis: A pooled self-controlled case series study of 11.6 million individuals in England, Scotland and Wales" (PMEDICINE-D-21-03598R4) in PLOS Medicine.

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

Sincerely,

Louise Gaynor-Brook, MBBS PhD

Associate Editor

PLOS Medicine

Table 2

Cohort summary statistics, Scotland.

Characteristic	Levels	Unvaccinated	One-dose ChAdOx1	One-dose BNT162b2
Total		1,837,555	1,743,343	829,038
Person years of follow-up		627,935	1,136,652	952,284
Incident CVST cases		9	34	13
Deaths		14,792 (0.80%)	12,485 (0.72%)	6,554 (0.79%)
Sex	Female	847,192 (46.1%)	900,591 (51.7%)	519,423 (62.7%)
	Male	990,363 (53.9%)	842,752 (48.3%)	309,615 (37.3%)
Age (years)	Mean (SD)	35.8 (13.6)	59 (15.3)	57.4 (16.6)
Age group (years)	18 to 64	1,756,236 (95.6%)	1,178,096 (67.6%)	462,906 (55.8%)
	65 to 79	47,113 (2.6%)	380,175 (21.8%)	329,739 (39.8%)
	80+	34,206 (1.9%)	185,072 (10.6%)	36,393 (4.4%)
Deprivation status†	1 (high)	393,735 (21.4%)	315,337 (18.1%)	152,365 (18.4%)
	2	363,509 (19.8%)	340,417 (19.5%)	164,078 (19.8%)
	3	345,606 (18.8%)	361,645 (20.7%)	166,194 (20.0%)
	4	345,959 (18.8%)	362,057 (20.8%)	176,278 (21.3%)
	5 (low)	364,644 (19.8%)	355,356 (20.4%)	165,303 (19.9%)
	Unknown	24,101 (1.3%)	8,531 (0.5%)	4,820 (0.6%)
Urban/rural index	1—large urban areas	779,728 (42.4%)	527,068 (30.2%)	246,393 (29.7%)
	2—other urban areas	592,533 (32.2%)	652,571 (37.4%)	334,968 (40.4%)
	3—accessible small towns	148,961 (8.1%)	178,437 (10.2%)	80,831 (9.7%)
	4—remote small towns	72,218 (3.9%)	98,686 (5.7%)	42,336 (5.1%)
	5—accessible rural	147,110 (8.0%)	179,672 (10.3%)	71,206 (8.6%)
	6—remote rural	72,905 (4.0%)	98,378 (5.6%)	48,484 (5.8%)
	Unknown	24,101 (1.3%)	8,531 (0.5%)	4,820 (0.6%)
Number of risk group‡	0	1,380,273 (75.1%)	812,869 (46.6%)	411,082 (49.6%)
	1	370,157 (20.1%)	519,923 (29.8%)	241,381 (29.1%)
	2	65,651 (3.6%)	238,303 (13.7%)	103,522 (12.5%)
	3	13,232 (0.7%)	100,913 (5.8%)	42,747 (5.2%)
	4	4,740 (0.3%)	43,232 (2.5%)	18,217 (2.2%)
	5+	3,502 (0.2%)	28,103 (1.6%)	12,089 (1.5%)
Number of previous tests§	0	1,521,965 (82.8%)	1,450,847 (83.2%)	599,480 (72.3%)
	1	237,779 (12.9%)	204,180 (11.7%)	114,003 (13.8%)
	2	46,071 (2.5%)	46,784 (2.7%)	33,299 (4.0%)
	3	11,350 (0.6%)	15,396 (0.9%)	14,173 (1.7%)
	4 to 9	11,842 (0.6%)	18,816 (1.1%)	27,847 (3.4%)
	10+	8,548 (0.5%)	7,320 (0.4%)	40,236 (4.9%)
Average household age	Mean (SD)	34.4 (13.8)	54.8 (17.8)	53.7 (18.5)
Number of people in household¶	1	545,823 (29.7%)	613,519 (35.2%)	259,370 (31.3%)
	2	404,714 (22.0%)	603,417 (34.6%)	298,158 (36.0%)
	3 to 5	784,498 (42.7%)	493,935 (28.3%)	236,711 (28.6%)
	6 to 10	82,513 (4.5%)	30,138 (1.7%)	15,493 (1.9%)
	11 to 30	8,569 (0.5%)	1,532 (0.1%)	6,669 (0.8%)
	31 to 100	6,255 (0.3%)	600 (0.0%)	10,967 (1.3%)
	101+	5,182 (0.3%)	202 (0.0%)	1,670 (0.2%)
BMI	Underweight	23,875 (1.3%)	17,726 (1.0%)	7,908 (1.0%)
	Normal weight	234,944 (12.8%)	214,888 (12.3%)	108,885 (13.1%)
	Overweight	1,422,006 (77.4%)	1,108,478 (63.6%)	519,249 (62.6%)
	Obese	156,730 (8.5%)	402,251 (23.1%)	192,996 (23.3%)
Smoking status	Ex-smoker	143,236 (7.8%)	297,503 (17.1%)	138,702 (16.7%)
	Nonsmoker	700,880 (38.1%)	669,699 (38.4%)	328,683 (39.6%)
	Smoker	299,528 (16.3%)	430,035 (24.7%)	192,753 (23.3%)
	Unknown	693,910 (37.8%)	346,106 (19.9%)	168,900 (20.4%)
Atrial fibrillation		6,353 (0.3%)	73,050 (4.2%)	29,466 (3.6%)
Asthma		224,636 (12.2%)	243,888 (14.0%)	109,010 (13.1%)
Blood cancer		1,772 (0.1%)	14,751 (0.8%)	5,541 (0.7%)
Heart failure		3,448 (0.2%)	33,261 (1.9%)	12,293 (1.5%)
Cerebral palsy		664 (0.0%)	4,334 (0.2%)	1,072 (0.1%)
Coronary heart disease		11,859 (0.6%)	133,205 (7.6%)	60,514 (7.3%)
Cirrhosis		3,483 (0.2%)	14,263 (0.8%)	6,204 (0.7%)
Congenital heart disease		3,586 (0.2%)	24,379 (1.4%)	10,277 (1.2%)
COPD		9,670 (0.5%)	90,514 (5.2%)	35,037 (4.2%)
Dementia		3,276 (0.2%)	17,779 (1.0%)	17,286 (2.1%)
Diabetes type 1		2,005 (0.1%)	14,889 (0.9%)	5,589 (0.7%)
Diabetes type 2		16,641 (0.9%)	167,766 (9.6%)	79,735 (9.6%)
Epilepsy		9,160 (0.5%)	43,185 (2.5%)	12,989 (1.6%)
Fracture		55,777 (3.0%)	97,098 (5.6%)	43,284 (5.2%)
Neurological disorder		1,433 (0.1%)	12,562 (0.7%)	4,561 (0.6%)
Parkinson disease		626 (0.0%)	6,061 (0.3%)	3,093 (0.4%)
Pulmonary hypertension		709 (0.0%)	6,523 (0.4%)	1,722 (0.2%)
Pulmonary rare		1,399 (0.1%)	16,060 (0.9%)	5,849 (0.7%)
Peripheral vascular disease		3,441 (0.2%)	28,820 (1.7%)	12,450 (1.5%)
Rheumatoid arthritis or SLE		3,414 (0.2%)	31,267 (1.8%)	12,947 (1.6%)
Respiratory cancer		1,218 (0.1%)	7,243 (0.4%)	2,552 (0.3%)
Severe mental illness		161,104 (8.8%)	263,637 (15.1%)	119,114 (14.4%)
Sickle cell disease		388 (0.0%)	1,905 (0.1%)	762 (0.1%)
Stroke/TIA		7,931 (0.4%)	80,030 (4.6%)	35,481 (4.3%)
Thrombosis or pulmonary embolus		8,086 (0.4%)	50,760 (2.9%)	18,625 (2.2%)
Care housing category	Care home	2,277 (0.1%)	2,806 (0.2%)	16,583 (2.0%)
	Homeless	2,271 (0.1%)	1,360 (0.1%)	342 (0.0%)
Learning disability or Down syndrome	Learning disability	24,695 (1.3%)	34,031 (2.0%)	9,551 (1.2%)
	Down syndrome	116 (0.0%)	1,193 (0.1%)	391 (0.0%)
Kidney disease	CKD5 without dialysis or transplant	7,558 (0.4%)	103,725 (5.9%)	41,568 (5.0%)
	CKD5 with dialysis	546 (0.0%)	4,335 (0.2%)	1,394 (0.2%)
	CKD5 with transplant	370 (0.0%)	3,107 (0.2%)	1,279 (0.2%)

†Deprivation status: quintiles of SIMD 2020.

‡Number of risk groups: count of QCovid risk groups.

§Number of previous tests: proxy for working in a high-risk occupation (e.g., healthcare worker).

¶Household information taken from September 2020.

BMI, body mass index; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; CVST, cerebral venous sinus thrombosis; SD, standard deviation; SIMD, Scottish Index of Multiple Deprivation; SLE, systemic lupus erythematosus; TIA, transient ischemic attack.