Pre-operative Risk Assessment of Surgical Site Infection After Cardiac Surgery

NCT ID: NCT04762446

Last Updated: 2024-04-10

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

6379 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-07-15

Study Completion Date

2023-11-30

Brief Summary

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Surgical site infections (SSI) are serious complications accounting for 20% of all the healthcare-associated infections and are considered the second most frequent type of hospital-acquired infection in Europe and the United States. SSI after cardiac surgery is associated with delays to patient's discharge, readmissions and re-operations; and can result in increased hospital costs for staffing, diagnostics and treatment.

Risk assessment has been identified as potentially useful intervention in SSI prevention and in identifying at risk populations who may benefit from specific interventions to reduce this possible complication of cardiac surgery. However, there is currently a lack of evidence as to which risk tools are the most valid and reliable to be used in clinical practice. The investigators developed and locally validated the Barts Heart Centre Surgical Infection Risk (B-SIR) tool to include patients with various types of cardiac surgeries and found that the B-SIR tool is a better tool in predicting SSI risk compared with the existing cardiac risk tools in the study population.

However, various literatures recognised that the predictive performance of a risk model tends to vary across settings, populations and periods. Hence, the investigators aim to do a multi-centre validation of the newly developed B-SIR tool and apply all the other tools (Australian Cardiac Risk Index and Brompton and Harefield Infection Score) to identify what tool performs best that can potentially be use for the UK population. Further, the outcome of the study will be beneficial to future cardiac surgery patients to assess their risk of developing SSI and help identify those patients who may benefit from specific interventions. Existing patients' data, which will be anonymised, from the participating cardiac centres will be utilised to analyse and compare the performance of each risk tools.

Detailed Description

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Surgical site infections (SSI) are serious complications accounting for 20% of all the healthcare-associated infections and are considered the second most frequent type of hospital-acquired infection in Europe and the United States. The incidence of SSI in England at 30-days is 8.6% for coronary artery bypass graft (CABG) and 2.2% for non-CABG operations. SSI after cardiac surgery is associated with delays to patient's discharge, readmissions and re-operations; and can result in increased hospital costs for staffing, diagnostics and treatment.

Risk assessment has been identified as potentially useful intervention in SSI prevention and in identifying at risk populations who may benefit from targeted interventions to reduce this possible complication of cardiac surgery. However, there is currently a lack of evidence as to which risk tools are the most valid and reliable to be used in clinical practice. The investigators developed and locally validated the Barts Heart Centre Surgical Infection Risk (B-SIR) tool to include patients with various types of cardiac surgeries and found that the B-SIR tool has a greater predictive power of SSI risk compared with the existing cardiac risk tools in the study population.

However, various literatures recognised that the predictive performance of a risk model tends to vary across settings, populations and periods. Verification of the robustness and generalisability of a developed model is highly recommended in one or more external validation studies. Hence, the investigators aim to do a multi-centre validation of the newly developed B-SIR tool and apply all the other tools (Australian Cardiac Risk Index and Brompton and Harefield Infection Score) to identify what tool performs best that can potentially be use for the UK population.

This study is a secondary data analysis that will utilise prospectively collected data that were locally collected in 6 UK cardiac centres for the National Institute for Cardiovascular Outcome Research (NICOR) and Public Health of England (PHE) Surgical Site Infection Surveillance. Data on various patients' risk factors will be collected and analysed to compare the ability of each risk assessment tool in predicting SSI after cardiac surgery. The outcome of this study will be beneficial to future cardiac surgery patients to assess their risk of developing SSI and help identify those patients who may benefit from targeted interventions.

Conditions

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Surgical Site Infection Risk Assessment Cardiac Surgery

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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SSI group

Participants who developed surgical site infection (SSI) based on the definition of Centre for Disease Control and Prevention.

No interventions assigned to this group

Non-SSI group

Participants who did not develop SSI.

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

1. \>/= 18 years old at the time of surgery; and
2. had a primary surgery (CABG, valve surgery or both) in the UK cardiac centres.

Exclusion Criteria

1. patients undergoing grown-up congenital heart disease related surgery;
2. patients with concurrent aortovascular surgery;
3. patients who had ventricular-assist device (VAD), haemolung, impellar and/or extracorporeal membrane oxygenator (ECMO) before and/or after cardiac surgery;
4. patients who had an open-chest immediately after surgery.
Minimum Eligible Age

18 Years

Maximum Eligible Age

120 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Liverpool Heart and Chest Hospital NHS Foundation Trust

OTHER

Sponsor Role collaborator

University Hospitals, Leicester

OTHER

Sponsor Role collaborator

Oxford University Hospitals NHS Trust

OTHER

Sponsor Role collaborator

South Tees Hospitals NHS Foundation Trust

OTHER

Sponsor Role collaborator

Cardiff and Vale University Health Board

OTHER_GOV

Sponsor Role collaborator

Belfast Health and Social Care Trust

OTHER

Sponsor Role collaborator

Barts & The London NHS Trust

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Liverpool Heart and Chest Hospital

Liverpool, , United Kingdom

Site Status

James Cook University Hospital

Middlesbrough, , United Kingdom

Site Status

Oxford University Hospital

Oxford, , United Kingdom

Site Status

Countries

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United Kingdom

References

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Lamagni T CK, Wloch C, Harrington P. The epidemiology of cardiac surgical site infection in Englad, 2018/19. 30th European Congress of Clinical Microbiology and Infectious Diseases. 2020; Paris, France: Clin Microbiol Infect 2020.

Reference Type BACKGROUND

Magboo R, Drey N, Cooper J, Byers H, Shipolini A, Sanders J. Predicting cardiac surgical site infection: development and validation of the Barts Surgical Infection Risk tool. J Clin Epidemiol. 2020 Dec;128:57-65. doi: 10.1016/j.jclinepi.2020.08.015. Epub 2020 Aug 25.

Reference Type BACKGROUND
PMID: 32853763 (View on PubMed)

Debray TP, Vergouwe Y, Koffijberg H, Nieboer D, Steyerberg EW, Moons KG. A new framework to enhance the interpretation of external validation studies of clinical prediction models. J Clin Epidemiol. 2015 Mar;68(3):279-89. doi: 10.1016/j.jclinepi.2014.06.018. Epub 2014 Aug 30.

Reference Type BACKGROUND
PMID: 25179855 (View on PubMed)

Pennells L, Kaptoge S, White IR, Thompson SG, Wood AM; Emerging Risk Factors Collaboration. Assessing risk prediction models using individual participant data from multiple studies. Am J Epidemiol. 2014 Mar 1;179(5):621-32. doi: 10.1093/aje/kwt298. Epub 2013 Dec 22.

Reference Type BACKGROUND
PMID: 24366051 (View on PubMed)

Royston P, Parmar MK, Sylvester R. Construction and validation of a prognostic model across several studies, with an application in superficial bladder cancer. Stat Med. 2004 Mar 30;23(6):907-26. doi: 10.1002/sim.1691.

Reference Type BACKGROUND
PMID: 15027080 (View on PubMed)

Steyerberg EW, Moons KG, van der Windt DA, Hayden JA, Perel P, Schroter S, Riley RD, Hemingway H, Altman DG; PROGRESS Group. Prognosis Research Strategy (PROGRESS) 3: prognostic model research. PLoS Med. 2013;10(2):e1001381. doi: 10.1371/journal.pmed.1001381. Epub 2013 Feb 5.

Reference Type BACKGROUND
PMID: 23393430 (View on PubMed)

Vergouwe Y, Moons KG, Steyerberg EW. External validity of risk models: Use of benchmark values to disentangle a case-mix effect from incorrect coefficients. Am J Epidemiol. 2010 Oct 15;172(8):971-80. doi: 10.1093/aje/kwq223. Epub 2010 Aug 31.

Reference Type BACKGROUND
PMID: 20807737 (View on PubMed)

Bleeker SE, Moll HA, Steyerberg EW, Donders AR, Derksen-Lubsen G, Grobbee DE, Moons KG. External validation is necessary in prediction research: a clinical example. J Clin Epidemiol. 2003 Sep;56(9):826-32. doi: 10.1016/s0895-4356(03)00207-5.

Reference Type BACKGROUND
PMID: 14505766 (View on PubMed)

Related Links

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Other Identifiers

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294270

Identifier Type: -

Identifier Source: org_study_id

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