Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO)
University of Nottingham · Academic
Expired The latest version ended on 1 October 2024. The September 2026 register still lists the agreement, but its term has passed.
- Reference
- DARS-NIC-237669-T9W5N
- Latest version
- v2.4
- Term of latest version
- 25 July 2022 to 1 October 2024
- Start date
- 15 June 2019
- Data controller
- Sole Data Controller
- Commercial purposes
- No
- Sublicensing
- No
- Files released to date
- 69
Why the data was released
Objective for processing
The Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO) is a database linkage study sponsored by the University of Nottingham.
The study aims to assess:
1. What is the impact of clinically recognised pre-operative strokes and heart attacks (myocardial infarction) on perioperative outcome?
2. Do the characteristics and management of strokes and heart attacks modify perioperative outcome?
3. How are the effects of strokes and heart attacks modified by surgical procedure?
Previous strokes and heart attacks (that take place prior to being operated on) are recognised risk factors for an adverse outcome following surgery. It is not clear how long this risk exists and whether it is modified by characteristics of the stroke or heart attack (treatment, pathophysiological effect) or by the type of surgery. Previous work by this group and others using HES (Hospital Episode Statistics) data has demonstrated an association between both strokes and heart attacks, and adverse perioperative outcomes following major orthopaedic surgery; the effects were less evident for patients undergoing major vascular surgery.
The CAPO study proposes to build on this previous work by studying data from a larger cohort of patients from the HES database and linking this HES patient data to patient data from the Myocardial Ischaemia National Audit Project (MINAP), the Sentinel Stroke National Audit Project (SSNAP) and the Office for National Statistics (ONS). Through this data linkage process this study will achieve better capture of patients who have had a stroke or heart attack prior to surgery, as well as additional information about the characteristics and treatment of these events.
The University of Nottingham propose to use pseudonymised patient level HES data to identify a cohort of patients who underwent surgery between 2007 and 2017. The HES data will be linked to data from the MINAP and SSNAP registries to gain information regarding the occurrence of pre-operative strokes or ACS in these patients. This linked data and mortality data will also be used to look at post-operative outcomes in these patients: mortality, postoperative ACS, prolonged length of stay and emergency readmission rates.
The University of Nottingham will be the sole data controller who process data for the pseudonymised dataset produced following the data linkage. While non-Nottingham University employees (University of Wisconsin School of Medicine, University College London, Health Services Research Centre) were involved in the initial development of the study (study idea) and will be involved in the distribution of the published results of the study they will not be involved in decisions as to how the study dataset is processed and will not access the study dataset.
Non special category data will be processed on the basis of being a task performed in the public interest (Article 6(1)(e)): the results of this study will help the planning of surgery for patients who have previously had a heart attack or stroke hopefully improving outcomes. Special category data will be processed on the basis of being necessary for reason of public health (Article 9(2)(i)). The use of identifiable information for data linkage has section 251 approval (19/CAG/0013).
There are approximately 4.4 million intermediate surgeries (surgeries routinely undertaken in an operating theatre and/or under general anaesthetic) in England each year (Abbott et al. analysis of HES data, British Journal of Anaesthesia 2017). It is therefore estimated that the 10 year study-cohort will contain 44 million intermediate surgical episodes. It is estimated that at least 400,000 of these episodes will represent patients who have had a previous heart attack or stroke. This is based on a conservative estimate of the proportion of the UK population who have had a previous heart attack or stroke as 1% (British Heart Foundation Heart & Circulatory Disease Statistics). 400,000 of the total episodes are estimated to result in patient death within 30 days. This is based on an average 30 day mortality of slightly above 1% of those who undergo intermediate surgery (Abbott et al. analysis of HES data, British Journal of Anaesthesia 2017).
This size dataset is required to adequately power the study. Much of the value of the study in terms of informing clinical decision making will result from the analysis of individual surgical subgroups. For total hip and knee arthroplasty where annual numbers are around 100,000 and mortality is 0.2% at thirty days, 2,000 deaths would be observed in the 10-year study dataset. Using a requirement of ten events per predictor to adequately power the regression analysis this would allow the analysis of over 100 predictors. Many of the other surgical subgroups will be much smaller (e.g. abdominal aortic aneurysm repair) or have much lower mortality rates (elective ophthalmological surgery). Hence it is essential to have this large dataset to allow analysis of these subgroups; the analysis of which underpins the ability of the study to produce clinically relevant findings.
The use of a 10-year cohort will also allow assessment of how the relationship between exposures and outcomes changes during the 10-year period. This may reflect temporal changes in the management of heart attacks and strokes or changes in perioperative practice.
Episodes containing surgical events not required in the analysis (obstetric surgery and surgeries likely related to the occurrence of a vascular event) will not be requested.
Selecting a smaller dataset through random sampling of patient episodes would greatly limit the study. Reducing the dataset size would reduce the power of the analysis and the ability to analyse smaller surgical subgroups and subgroups with lower mortality rates. The other limitation with randomly selecting a proportion of the cohort is that if it was done before the data linkage to the other registries this will lose many of the MINAP/SSNAP linked patients and hence compromise the granularity of the analysis. If the patients were selected after linkage and stratified to include all linked patients this would potentially bias the study (it may be that the patients with more severe heart attacks or strokes are more likely to appear in MINAP/SSNAP).
While the primary regression analysis will include only the earliest surgical episode for each patient within the dataset, minimising the dataset by selecting only the earliest patient episodes would not be feasible. University of Nottingham intend to perform analyses of multiple surgical sub-categories. While a patient may have multiple surgical episodes in the full dataset these are unlikely to all be in the same surgical category. Hence if only the earliest surgical episode for each patient is included in the dataset this would lose episodes that would have been used in surgical subgroup analysis.
University of Nottingham also require multiple surgical episodes for each patient to perform a sensitivity analysis. They intend to repeat the analysis using the final surgical episode within each surgical subgroup as the index surgery in patients who had multiple surgeries between 2007 and 2017. Patients without multiple surgeries will be excluded from this analysis. This sensitivity analysis will allow assessment of the appropriateness of using the first surgical event in the primary analysis and may highlight any potential effect on outcome of multiple surgeries post a vascular event.
Expected outcomes are robust estimates of time-dependent risks associated with stroke and ACS, stratified by surgical type and characteristics of stroke and heart attack.
Processing activities
There was a flow of data out of NHS digital in the form of the HES APC linked to mortality datasets under the previous version of this agreement. This extension application is to hold and process the data disseminated under the previous version of this agreement, DARS-NIC-237669-T9W5N-v1.3.
NHS Digital will identify a cohort of patients who have an episode in the HES-APC (Hospital Episode Statistics - Admitted Patient Care) database with a surgical procedure between 2007 and 2017 at the time of which they were 18 years or older.
NHS Digital will receive identifiable patient level data from the Healthcare Quality Improvement Partnership (HQIP) - MINAP and SSNAP data controller. The identifiers will be NHS number, date of birth, sex, and post-code. NHS Digital will link this data to the HES-APC data from 1997 to 2018 for the patients in the cohort. NHS Digital will also link this data to mortality data (date of death).
The linked dataset created by NHS digital will be pseudonymised (identifiers removed/encrypted HES ID created for each patient in dataset).
The linkage of identifiable data by NHS digital to form the pseudonymised dataset has been approved by the Confidential Advisory Group under Section 251 of the NHS Act 2006 (CAG ref: 19/CAG/0013).
The pseudonymised dataset will be transferred to the University of Nottingham where it will be analysed by the study group. Logistical regression analysis will be performed on the data to generate estimates of time-dependent risks associated with strokes and heart attacks, stratified by surgical type and characteristics of stroke and heart attacks. Any results distributed from the analysis will be at an anonymous and aggregated level with small numbers suppressed in line with the HES Analysis Guide.
Access to the information will be limited to the study staff and investigators. Computer held data including the study database will be held securely and password protected. All data will be stored on a University of Nottingham secure dedicated web server and only accessed on University of Nottingham computers. Access will be restricted by user identifiers and passwords (encrypted using a one way encryption method).
The University of Nottingham will be the sole data controller for the pseudonymised dataset transferred from NHS Digital. Only University of Nottingham employees will access the dataset or make decisions about how it is processed. While non-Nottingham University employees (University of Wisconsin School of Medicine and University College London) were involved in the initial development of the study (study idea) and will be involved in the distribution of the published results of the study they will not be involved in decisions as to how the study dataset is processed and will not access the study dataset. Therefore although the study protocol names two non-Nottingham University employees as co-investigators, they do not have a data controller or data processor role in relation to the data shared under this agreement. Nottingham University Hospitals NHS Trust will play no role in the study. All University of Nottingham employees accessing the data will be trained in data protection and confidentiality.
At the end of the data retention period, the University of Nottingham will destroy the data or an extension of the agreement will be applied for.
Expected output
All study outputs will only contain anonymous aggregate level data. Small numbers would be suppressed as per the HES analysis guide. University of Nottingham plan to distribute findings from the study in the following ways:
-Peer-reviewed publications in high impact journals (surgical, anaesthetic, and perioperative medicine journals).
- Direct link of study team (Health Services Research Centre) to Royal College of Anaesthetists and hence Lay Committee and Patient Information Group, allowing timely dissemination of information. The Patient information Group is a sub-committee at the Royal College of Anaesthetists that is responsible for developing and keeping patient information up-to-date. They develop information in varied formats to try and best inform patients about various aspects of anaesthetic/perioperative care.
-Influencing the national (NHS) agenda through existing links of the study team with National Clinical Directors.
-Wide dissemination of findings by the study team
- National and regional presentations
- Social media
- Dissemination of findings through Health Services Research Centre
- Presentations
- Social media
- Published reports
While many direct outputs from the study will not be aimed specifically at patients/general public it is hoped that the findings, communicated as above, will be used by medical professionals to inform their discussion with patients regarding perioperative risk and joint surgical decision making. Also, as mentioned the direct link of the study group to the Royal College of Anaesthetists Patient Information Group will hopefully allow the finding of the study to influence perioperative patient information.
University of Nottingham would hope to begin publishing the results of the study within 2 years of the start of the data analysis.
Therefore, the team expect to publish the full study results in October 2023.
The preliminary findings of the study were presented at Anaesthesia UK 2022. The 1st draft of the manuscript has been written and is being reviewed by the authors. The team would hope to submit for publication within the next few months.
Expected measurable benefits
Cardiovascular events (heart attacks or strokes) that have occurred prior to surgery are risk factors for adverse outcomes following surgery. In recent years treatment of heart attacks has improved significantly and more patients are surviving and presenting for surgery following stroke. In addition, surgery is being offered to patients with co-morbidities previously felt to preclude it. The increased risk of surgery associated with cardiovascular events may be due to increased risk associated with the event itself (which might be expected to reduce with time) or increased risk due to the underlying cause of the cardiovascular event (e.g. arterial disease, smoking, diabetes) which may not change with time.
It is increasingly recognised that it is important for medical professionals and patients to work as a team to make the most appropriate decisions about a patient’s care. In this context the joint decision-making process requires knowledge of the optimal timing of surgery following a cardiovascular event. Delaying surgery unnecessarily, at best causes patient distress, and at worst may result in worse outcome. Conversely, proceeding to surgery too soon may expose patients to unnecessary risks. Furthermore, the risks may be specific to the type of operation a patient is having.
It is therefore important to have accurate information about the risks of specific operations in patients who have had previous vascular events. It is important to know how this risk changes with time and if it is affected by the type and severity of the cardiovascular event or the treatment the patient received for it.
Existing studies have provided some insight, but the impact on perioperative outcomes of the interval between stroke or heart attack and surgery still remains unclear. The modifying effects of disease severity, underlying cause and treatment have not been fully investigated. Through combining information from a number of registries collected over a large time period this study will analyse data from a much larger group of patients than previous studies. Unlike previous studies, the dataset analysed in this study will contain detailed data on the type of stroke or heart attack patients may have had previously and information on how they were treated. The study should provide a better understanding of how a heart attack or stroke influences the risk of having a subsequent operation and how this risk changes with time after the heart attack or stroke. University of Nottingham hope to be able to provide accurate information that is specific to different types of surgery. This information should inform the shared decision-making process when planning patient care.
It is estimated that at least 1% of the population of England have had a previous heart attack or stroke (British Heart Foundation Heart & Circulatory Disease Statistics). There are approximately 4.4 million intermediate surgeries (surgeries routinely undertaken in an operating theatre and/or under general anaesthetic) in England each year (Abbott et al. analysis of HES data, British Journal of Anaesthesia 2017). Therefore a conservative estimate of 40,000 patients undergo intermediate surgery in England each year having had a previous heart attack or stroke. The results of this study will provide accurate time-dependent data about the risks associated with these surgeries. This information will inform the shared decision-making process improving assessment of the appropriateness and optimal timing of a surgical intervention. This may potentially lead to improved outcomes for these patients.
University of Nottingham anticipate the study results will be used as a basis for planning randomised controlled trials of potential cardioprotective therapy during the perioperative period. They will also use these data to construct perioperative risk models for NHS patients.
University of Nottingham aim to begin publishing the results of the study within 2 years of the start of the data analysis. This information could then be used to estimate patient risk and guide surgical decision-making. As described it is hoped this will be beneficial to patient care.
This study is in support of postgraduate research.
Benefits reported so far
Data was received in October 2021 and analysis is still in progress. There are therefore no yielded benefits to date.
Datasets on the latest version
Legal basis for provision: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'
| Dataset | Type of data | Sensitivity | Frequency | Confidential data |
|---|---|---|---|---|
| Civil Registrations of Death - Secondary Care Cut | Anonymised - ICO Code Compliant | Sensitive | One-Off | Section 251 NHS Act 2006 |
| HES-ID to MPS-ID HES Admitted Patient Care | Anonymised - ICO Code Compliant | Non-Sensitive | One-Off | Section 251 NHS Act 2006 |
| HES:Civil Registration (Deaths) bridge | Anonymised - ICO Code Compliant | Non-Sensitive | One-Off | Section 251 NHS Act 2006 |
| Hospital Episode Statistics Admitted Patient Care (HES APC) | Anonymised - ICO Code Compliant | Non-Sensitive | One-Off | Section 251 NHS Act 2006 |
Files released
Files released counts only files released externally by DARS. Access granted in NHS England's own systems, such as its Secure Data Environment, is not included.
Patient opt-outs were applied to 46 of the 69 files released under this agreement, across every version. About opt-outs
No files recorded as released under the latest version. 69 were released under earlier versions, shown in the version history.
Version history
The register lists each renewal of this agreement as a separate row. This site has 3 versions.
DARS-NIC-237669-T9W5N-v2.4 25 July 2022 to 1 October 2024
- Title
- Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO)
- Commercial
- No
- Sublicensing
- No
- Datasets
- 4
- Files released
- 0
Datasets: Civil Registrations of Death - Secondary Care Cut; HES-ID to MPS-ID HES Admitted Patient Care; HES:Civil Registration (Deaths) bridge; Hospital Episode Statistics Admitted Patient Care (HES APC)
What changed from DARS-NIC-237669-T9W5N-v1.3
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2022-07-25 | |
| End date | 2024-10-01 | |
| Civil Registrations of Death - Secondary Care Cut: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| HES-ID to MPS-ID HES Admitted Patient Care: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| HES:Civil Registration (Deaths) bridge: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Hospital Episode Statistics Admitted Patient Care (HES APC): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' |
Objective for processing
The Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO) is a database linkage study sponsored by the University of Nottingham.
The study aims to assess:
The study aims to assess:
[6 paragraphs unchanged]
The University of Nottingham will be the sole data controller
and processor
who process data
for the
pseudoanonymised
pseudonymised
dataset produced following the data linkage. While non-Nottingham University employees (University of
[46 words unchanged]
the study dataset is processed and will not access the study dataset.
[9 paragraphs unchanged]
Processing activities
There was a flow of data out of NHS digital in the form of the HES APC linked to mortality datasets under the previous version of this agreement. This extension application is to hold and process the data disseminated under the previous version of this agreement, DARS-NIC-237669-T9W5N-v1.3.
[6 paragraphs unchanged]
The University of Nottingham will be the sole data controller for the
[104 words unchanged]
data processor role in relation to the data shared under this agreement.
While some study team members are substantive employees of the Nottingham University Hospitals NHS Trust they will be seconded to the University of Nottingham (forming an employee-employer relationship) for the purpose of this study;
Nottingham University Hospitals NHS Trust will play no role in the study. All University of Nottingham employees accessing the data will be trained in data protection and confidentiality.
At the end of the data retention
period
period,
the University of Nottingham will destroy the
data.
data or an extension of the agreement will be applied for.
All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).
Expected output
[13 paragraphs unchanged] Therefore, the team expect to publish the full study results in October 2023. The preliminary findings of the study were presented at Anaesthesia UK 2022. The 1st draft of the manuscript has been written and is being reviewed by the authors. The team would hope to submit for publication within the next few months.
Benefits reported
Not stated in the previous version; added here.
Data was received in October 2021 and analysis is still in progress. There are therefore no yielded benefits to date.
Unchanged: Expected measurable benefits.
DARS-NIC-237669-T9W5N-v1.3 6 July 2020 to 14 June 2022
- Title
- Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO)
- Commercial
- No
- Sublicensing
- No
- Datasets
- 4
- Files released
- 47
Datasets: Civil Registrations of Death - Secondary Care Cut; HES-ID to MPS-ID HES Admitted Patient Care; HES:Civil Registration (Deaths) bridge; Hospital Episode Statistics Admitted Patient Care (HES APC)
What changed from DARS-NIC-237669-T9W5N-v0.7
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-07-06 |
Datasets: + HES-ID to MPS-ID HES Admitted Patient Care
Objective for processing
[7 paragraphs unchanged]
Non special category data will be processed on the basis of being a task performed in the public interest (Article 6(1)(e)). Special category data will be processed on the basis of being necessary for reason of public health (Article 9(2)(i)). The use of identifiable information for data linkage has section 251 approval (19/CAG/0013).
The University of Nottingham will be the sole data controller and processor for the pseudoanonymised dataset produced following the data linkage. While non-Nottingham University employees (University of Wisconsin School of Medicine, University College London, Health Services Research Centre) were involved in the initial development of the study (study idea) and will be involved in the distribution of the published results of the study they will not be involved in decisions as to how the study dataset is processed and will not access the study dataset.
Non special category data will be processed on the basis of being a task performed in the public interest (Article 6(1)(e)): the results of this study will help the planning of surgery for patients who have previously had a heart attack or stroke hopefully improving outcomes. Special category data will be processed on the basis of being necessary for reason of public health (Article 9(2)(i)). The use of identifiable information for data linkage has section 251 approval (19/CAG/0013).
[8 paragraphs unchanged]
Processing activities
[5 paragraphs unchanged]
The University of Nottingham will be the sole data controller for the pseudonymised dataset transferred from NHS digital. Only University of Nottingham employees will access the dataset or make decisions about how it is processed. While non-Nottingham University employees (University of Wisconsin School of Medicine and University College London) were involved in the initial development of the study (study idea) and will be involved in the distribution of the published results of the study they will not be involved in decisions as to how the study dataset is processed and will not access the study dataset. Therefore although the study protocol names two non-Nottingham University employees as co-investigators, they do not have a data controller or data processor role in relation to the data shared under this agreement. While some study team members are substantive employees of the Nottingham University Hospitals NHS Trust they will be seconded to the University of Nottingham (forming an employee-employer relationship) for the purpose of this study; Nottingham University Hospitals NHS Trust will play no role in the study.
Access to the information will be limited to the study staff and investigators. Computer held data including the study database will be held securely and password protected. All data will be stored on a University of Nottingham secure dedicated web server and only accessed on University of Nottingham computers. Access will be restricted by user identifiers and passwords (encrypted using a one way encryption method).
The University of Nottingham will be the sole data controller for the pseudonymised dataset transferred from NHS Digital. Only University of Nottingham employees will access the dataset or make decisions about how it is processed. While non-Nottingham University employees (University of Wisconsin School of Medicine and University College London) were involved in the initial development of the study (study idea) and will be involved in the distribution of the published results of the study they will not be involved in decisions as to how the study dataset is processed and will not access the study dataset. Therefore although the study protocol names two non-Nottingham University employees as co-investigators, they do not have a data controller or data processor role in relation to the data shared under this agreement. While some study team members are substantive employees of the Nottingham University Hospitals NHS Trust they will be seconded to the University of Nottingham (forming an employee-employer relationship) for the purpose of this study; Nottingham University Hospitals NHS Trust will play no role in the study. All University of Nottingham employees accessing the data will be trained in data protection and confidentiality.
[2 paragraphs unchanged]
Expected output
[1 paragraph unchanged]
-Peer-reviewed publications in high impact journals
(surgical, anaesthetic, and perioperative medicine journals).
[9 paragraphs unchanged]
-Linkage of findings with data collection and analysis of surgical and perioperative medicine Getting It Right First Time (GIRFT) project leads.
[2 paragraphs unchanged]
Expected measurable benefits
[7 paragraphs unchanged] This study is in support of postgraduate research.
Benefits reported
Stated in the previous version and removed here.
Yielded Benefits is not a requirement for new applications.
Objective for processing
The Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO) is a database linkage study sponsored by the University of Nottingham. The study aims to assess:
1. What is the impact of clinically recognised pre-operative strokes and heart attacks (myocardial infarction) on perioperative outcome?
2. Do the characteristics and management of strokes and heart attacks modify perioperative outcome?
3. How are the effects of strokes and heart attacks modified by surgical procedure?
Previous strokes and heart attacks (that take place prior to being operated on) are recognised risk factors for an adverse outcome following surgery. It is not clear how long this risk exists and whether it is modified by characteristics of the stroke or heart attack (treatment, pathophysiological effect) or by the type of surgery. Previous work by this group and others using HES (Hospital Episode Statistics) data has demonstrated an association between both strokes and heart attacks, and adverse perioperative outcomes following major orthopaedic surgery; the effects were less evident for patients undergoing major vascular surgery.
The CAPO study proposes to build on this previous work by studying data from a larger cohort of patients from the HES database and linking this HES patient data to patient data from the Myocardial Ischaemia National Audit Project (MINAP), the Sentinel Stroke National Audit Project (SSNAP) and the Office for National Statistics (ONS). Through this data linkage process this study will achieve better capture of patients who have had a stroke or heart attack prior to surgery, as well as additional information about the characteristics and treatment of these events.
The University of Nottingham propose to use pseudonymised patient level HES data to identify a cohort of patients who underwent surgery between 2007 and 2017. The HES data will be linked to data from the MINAP and SSNAP registries to gain information regarding the occurrence of pre-operative strokes or ACS in these patients. This linked data and mortality data will also be used to look at post-operative outcomes in these patients: mortality, postoperative ACS, prolonged length of stay and emergency readmission rates.
The University of Nottingham will be the sole data controller and processor for the pseudoanonymised dataset produced following the data linkage. While non-Nottingham University employees (University of Wisconsin School of Medicine, University College London, Health Services Research Centre) were involved in the initial development of the study (study idea) and will be involved in the distribution of the published results of the study they will not be involved in decisions as to how the study dataset is processed and will not access the study dataset.
Non special category data will be processed on the basis of being a task performed in the public interest (Article 6(1)(e)): the results of this study will help the planning of surgery for patients who have previously had a heart attack or stroke hopefully improving outcomes. Special category data will be processed on the basis of being necessary for reason of public health (Article 9(2)(i)). The use of identifiable information for data linkage has section 251 approval (19/CAG/0013).
There are approximately 4.4 million intermediate surgeries (surgeries routinely undertaken in an operating theatre and/or under general anaesthetic) in England each year (Abbott et al. analysis of HES data, British Journal of Anaesthesia 2017). It is therefore estimated that the 10 year study-cohort will contain 44 million intermediate surgical episodes. It is estimated that at least 400,000 of these episodes will represent patients who have had a previous heart attack or stroke. This is based on a conservative estimate of the proportion of the UK population who have had a previous heart attack or stroke as 1% (British Heart Foundation Heart & Circulatory Disease Statistics). 400,000 of the total episodes are estimated to result in patient death within 30 days. This is based on an average 30 day mortality of slightly above 1% of those who undergo intermediate surgery (Abbott et al. analysis of HES data, British Journal of Anaesthesia 2017).
This size dataset is required to adequately power the study. Much of the value of the study in terms of informing clinical decision making will result from the analysis of individual surgical subgroups. For total hip and knee arthroplasty where annual numbers are around 100,000 and mortality is 0.2% at thirty days, 2,000 deaths would be observed in the 10-year study dataset. Using a requirement of ten events per predictor to adequately power the regression analysis this would allow the analysis of over 100 predictors. Many of the other surgical subgroups will be much smaller (e.g. abdominal aortic aneurysm repair) or have much lower mortality rates (elective ophthalmological surgery). Hence it is essential to have this large dataset to allow analysis of these subgroups; the analysis of which underpins the ability of the study to produce clinically relevant findings.
The use of a 10-year cohort will also allow assessment of how the relationship between exposures and outcomes changes during the 10-year period. This may reflect temporal changes in the management of heart attacks and strokes or changes in perioperative practice.
Episodes containing surgical events not required in the analysis (obstetric surgery and surgeries likely related to the occurrence of a vascular event) will not be requested.
Selecting a smaller dataset through random sampling of patient episodes would greatly limit the study. Reducing the dataset size would reduce the power of the analysis and the ability to analyse smaller surgical subgroups and subgroups with lower mortality rates. The other limitation with randomly selecting a proportion of the cohort is that if it was done before the data linkage to the other registries this will lose many of the MINAP/SSNAP linked patients and hence compromise the granularity of the analysis. If the patients were selected after linkage and stratified to include all linked patients this would potentially bias the study (it may be that the patients with more severe heart attacks or strokes are more likely to appear in MINAP/SSNAP).
While the primary regression analysis will include only the earliest surgical episode for each patient within the dataset, minimising the dataset by selecting only the earliest patient episodes would not be feasible. University of Nottingham intend to perform analyses of multiple surgical sub-categories. While a patient may have multiple surgical episodes in the full dataset these are unlikely to all be in the same surgical category. Hence if only the earliest surgical episode for each patient is included in the dataset this would lose episodes that would have been used in surgical subgroup analysis.
University of Nottingham also require multiple surgical episodes for each patient to perform a sensitivity analysis. They intend to repeat the analysis using the final surgical episode within each surgical subgroup as the index surgery in patients who had multiple surgeries between 2007 and 2017. Patients without multiple surgeries will be excluded from this analysis. This sensitivity analysis will allow assessment of the appropriateness of using the first surgical event in the primary analysis and may highlight any potential effect on outcome of multiple surgeries post a vascular event.
Expected outcomes are robust estimates of time-dependent risks associated with stroke and ACS, stratified by surgical type and characteristics of stroke and heart attack.
Expected output
All study outputs will only contain anonymous aggregate level data. Small numbers would be suppressed as per the HES analysis guide. University of Nottingham plan to distribute findings from the study in the following ways:
-Peer-reviewed publications in high impact journals (surgical, anaesthetic, and perioperative medicine journals).
- Direct link of study team (Health Services Research Centre) to Royal College of Anaesthetists and hence Lay Committee and Patient Information Group, allowing timely dissemination of information. The Patient information Group is a sub-committee at the Royal College of Anaesthetists that is responsible for developing and keeping patient information up-to-date. They develop information in varied formats to try and best inform patients about various aspects of anaesthetic/perioperative care.
-Influencing the national (NHS) agenda through existing links of the study team with National Clinical Directors.
-Wide dissemination of findings by the study team
- National and regional presentations
- Social media
- Dissemination of findings through Health Services Research Centre
- Presentations
- Social media
- Published reports
While many direct outputs from the study will not be aimed specifically at patients/general public it is hoped that the findings, communicated as above, will be used by medical professionals to inform their discussion with patients regarding perioperative risk and joint surgical decision making. Also, as mentioned the direct link of the study group to the Royal College of Anaesthetists Patient Information Group will hopefully allow the finding of the study to influence perioperative patient information.
University of Nottingham would hope to begin publishing the results of the study within 2 years of the start of the data analysis.
DARS-NIC-237669-T9W5N-v0.7 15 June 2019 to 14 June 2022
- Title
- Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO)
- Commercial
- No
- Sublicensing
- No
- Datasets
- 3
- Files released
- 22
Datasets: Civil Registrations of Death - Secondary Care Cut; HES:Civil Registration (Deaths) bridge; Hospital Episode Statistics Admitted Patient Care (HES APC)
Objective for processing
The Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO) is a database linkage study sponsored by the University of Nottingham. The study aims to assess:
1. What is the impact of clinically recognised pre-operative strokes and heart attacks (myocardial infarction) on perioperative outcome?
2. Do the characteristics and management of strokes and heart attacks modify perioperative outcome?
3. How are the effects of strokes and heart attacks modified by surgical procedure?
Previous strokes and heart attacks (that take place prior to being operated on) are recognised risk factors for an adverse outcome following surgery. It is not clear how long this risk exists and whether it is modified by characteristics of the stroke or heart attack (treatment, pathophysiological effect) or by the type of surgery. Previous work by this group and others using HES (Hospital Episode Statistics) data has demonstrated an association between both strokes and heart attacks, and adverse perioperative outcomes following major orthopaedic surgery; the effects were less evident for patients undergoing major vascular surgery.
The CAPO study proposes to build on this previous work by studying data from a larger cohort of patients from the HES database and linking this HES patient data to patient data from the Myocardial Ischaemia National Audit Project (MINAP), the Sentinel Stroke National Audit Project (SSNAP) and the Office for National Statistics (ONS). Through this data linkage process this study will achieve better capture of patients who have had a stroke or heart attack prior to surgery, as well as additional information about the characteristics and treatment of these events.
The University of Nottingham propose to use pseudonymised patient level HES data to identify a cohort of patients who underwent surgery between 2007 and 2017. The HES data will be linked to data from the MINAP and SSNAP registries to gain information regarding the occurrence of pre-operative strokes or ACS in these patients. This linked data and mortality data will also be used to look at post-operative outcomes in these patients: mortality, postoperative ACS, prolonged length of stay and emergency readmission rates.
Non special category data will be processed on the basis of being a task performed in the public interest (Article 6(1)(e)). Special category data will be processed on the basis of being necessary for reason of public health (Article 9(2)(i)). The use of identifiable information for data linkage has section 251 approval (19/CAG/0013).
There are approximately 4.4 million intermediate surgeries (surgeries routinely undertaken in an operating theatre and/or under general anaesthetic) in England each year (Abbott et al. analysis of HES data, British Journal of Anaesthesia 2017). It is therefore estimated that the 10 year study-cohort will contain 44 million intermediate surgical episodes. It is estimated that at least 400,000 of these episodes will represent patients who have had a previous heart attack or stroke. This is based on a conservative estimate of the proportion of the UK population who have had a previous heart attack or stroke as 1% (British Heart Foundation Heart & Circulatory Disease Statistics). 400,000 of the total episodes are estimated to result in patient death within 30 days. This is based on an average 30 day mortality of slightly above 1% of those who undergo intermediate surgery (Abbott et al. analysis of HES data, British Journal of Anaesthesia 2017).
This size dataset is required to adequately power the study. Much of the value of the study in terms of informing clinical decision making will result from the analysis of individual surgical subgroups. For total hip and knee arthroplasty where annual numbers are around 100,000 and mortality is 0.2% at thirty days, 2,000 deaths would be observed in the 10-year study dataset. Using a requirement of ten events per predictor to adequately power the regression analysis this would allow the analysis of over 100 predictors. Many of the other surgical subgroups will be much smaller (e.g. abdominal aortic aneurysm repair) or have much lower mortality rates (elective ophthalmological surgery). Hence it is essential to have this large dataset to allow analysis of these subgroups; the analysis of which underpins the ability of the study to produce clinically relevant findings.
The use of a 10-year cohort will also allow assessment of how the relationship between exposures and outcomes changes during the 10-year period. This may reflect temporal changes in the management of heart attacks and strokes or changes in perioperative practice.
Episodes containing surgical events not required in the analysis (obstetric surgery and surgeries likely related to the occurrence of a vascular event) will not be requested.
Selecting a smaller dataset through random sampling of patient episodes would greatly limit the study. Reducing the dataset size would reduce the power of the analysis and the ability to analyse smaller surgical subgroups and subgroups with lower mortality rates. The other limitation with randomly selecting a proportion of the cohort is that if it was done before the data linkage to the other registries this will lose many of the MINAP/SSNAP linked patients and hence compromise the granularity of the analysis. If the patients were selected after linkage and stratified to include all linked patients this would potentially bias the study (it may be that the patients with more severe heart attacks or strokes are more likely to appear in MINAP/SSNAP).
While the primary regression analysis will include only the earliest surgical episode for each patient within the dataset, minimising the dataset by selecting only the earliest patient episodes would not be feasible. University of Nottingham intend to perform analyses of multiple surgical sub-categories. While a patient may have multiple surgical episodes in the full dataset these are unlikely to all be in the same surgical category. Hence if only the earliest surgical episode for each patient is included in the dataset this would lose episodes that would have been used in surgical subgroup analysis.
University of Nottingham also require multiple surgical episodes for each patient to perform a sensitivity analysis. They intend to repeat the analysis using the final surgical episode within each surgical subgroup as the index surgery in patients who had multiple surgeries between 2007 and 2017. Patients without multiple surgeries will be excluded from this analysis. This sensitivity analysis will allow assessment of the appropriateness of using the first surgical event in the primary analysis and may highlight any potential effect on outcome of multiple surgeries post a vascular event.
Expected outcomes are robust estimates of time-dependent risks associated with stroke and ACS, stratified by surgical type and characteristics of stroke and heart attack.
Expected output
All study outputs will only contain anonymous aggregate level data. Small numbers would be suppressed as per the HES analysis guide. University of Nottingham plan to distribute findings from the study in the following ways:
-Peer-reviewed publications in high impact journals
- Direct link of study team (Health Services Research Centre) to Royal College of Anaesthetists and hence Lay Committee and Patient Information Group, allowing timely dissemination of information. The Patient information Group is a sub-committee at the Royal College of Anaesthetists that is responsible for developing and keeping patient information up-to-date. They develop information in varied formats to try and best inform patients about various aspects of anaesthetic/perioperative care.
-Influencing the national (NHS) agenda through existing links of the study team with National Clinical Directors.
-Wide dissemination of findings by the study team
- National and regional presentations
- Social media
- Dissemination of findings through Health Services Research Centre
- Presentations
- Social media
- Published reports
-Linkage of findings with data collection and analysis of surgical and perioperative medicine Getting It Right First Time (GIRFT) project leads.
While many direct outputs from the study will not be aimed specifically at patients/general public it is hoped that the findings, communicated as above, will be used by medical professionals to inform their discussion with patients regarding perioperative risk and joint surgical decision making. Also, as mentioned the direct link of the study group to the Royal College of Anaesthetists Patient Information Group will hopefully allow the finding of the study to influence perioperative patient information.
University of Nottingham would hope to begin publishing the results of the study within 2 years of the start of the data analysis.
Benefits reported
Yielded Benefits is not a requirement for new applications.
Register history
When this agreement appeared in, or was edited in, each monthly edition of the register. Built by comparing every edition this site holds, the earliest of which is July 2021.
-
July 2021 —
already listed in the earliest edition this site holds, so it may be older. 2 versions: DARS-NIC-237669-T9W5N-v0.7, DARS-NIC-237669-T9W5N-v1.3
-
October 2021
Amended DARS-NIC-237669-T9W5N-v1.3
- Datasets: + HES-ID to MPS-ID HES Admitted Patient Care
-
November 2022
1 version added: DARS-NIC-237669-T9W5N-v2.4
-
December 2022
Register-wide edit DARS-NIC-237669-T9W5N-v0.7, DARS-NIC-237669-T9W5N-v1.3 — Datasets: legal basis: “
s261(1) and” taken out. Made to 639 agreements in this edition, so it is reported once, on the changes page, and not counted as an amendment of this agreement.
"Amended in place" means NHS England changed the record without issuing a new version number. The register publishes no changelog for those edits; this site infers them by comparing editions. An edit is attributed to the edition it first appears in, not to the date it was made.
Cite this page
NHS England (2026) Data Uses Register, September 2026 edition, agreement DARS-NIC-237669-T9W5N, “Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO)”. Read via NHS Data Access Explorer (unofficial), https://healthdatauses.uk/agreements/dars-nic-237669-t9w5n/ (accessed [date]).
This address stays the same, but the page is rebuilt with each monthly edition, so the citation names the edition it shows. Every edition's data is kept in the facts store.
Source: datausesregister_september2026.xlsx, September 2026 edition of the NHS England Data Uses Register. Search that workbook for DARS-NIC-237669-T9W5N to see the original rows.