Retrospective Analysis of Sarcopenia in Older Patients Undergoing Laparotomy

NCT ID: NCT04493710

Last Updated: 2020-10-08

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 200 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2015-01-01
• Study Completion Date: 2022-12-01

Brief Summary

Assess the influence of sarcopenia on outcomes of emergency laparotomy in the over 65 age group

Detailed Description

Emergency laparotomy is associated with substantial morbidity and mortality. These risks are increased in the elderly population with a third of over-80s dying within thirty days of surgery, rising to 50% at 1-year post emergency laparotomy. Many patients are frail and have multiple co-morbidities, often with coexistent malnutrition and so present a significant challenge in the emergency surgery setting. The National Emergency Laparotomy Audit has reported that greater than half of patients undergoing emergency laparotomy in the UK are over-65 years of age and are the highest risk patients with the highest mortality. This group, therefore, is one in which accurate prognostication is desirable to allow optimal treatment decisions, provision of critical care treatment, and resource allocation.

A number of multivariate risk prediction models exist including POSSUM, P-POSSUM and APACHE-II with on-going modification of P-POSSUM as part of the National Emergency Laparotomy Audit(NELA). Whilst such models are commonly used, evidence suggests that they may be less accurate in elderly patients, a group which offer difficult decision-making problems to the surgeon

. Frailty is the lack of physiological functional reserve and is commonplace in elderly patients. It has profound effects on the ability to withstand and recover from emergency surgery. Despite this, frailty does not form part of the commonly used multivariate risk prediction models.

Sarcopenia is the progressive and global loss of skeletal muscle mass as well as reduction in strength and is closely linked to frailty. Multiple methods of quantifying skeletal muscle mass and therefore sarcopenia have been defined, but calculation of psoas major cross-sectional area on pre-operative CT imaging may be the most pragmatic in the emergency setting due to routine use of pre-operative CT imaging prior to emergency laparotomy. Measurement of the psoas major as a marker of sarcopenia has been shown to predict outcomes in a wide range of surgical specialties. However, there is no consensus as to how this marker of sarcopenia should be used in surgical practice.

Proposal- To assess the utility of psoas major measurement to predict outcomes following emergency laparotomy in older patients and whether it could enhance the accuracy of mortality prediction when combined with P-POSSUM model variables.

Methods An analysis of data collected as part of the National Emergency Laparotomy Audit was conducted. Data were collected from patients over the age of 65 who underwent emergency laparotomy in Merseyside, United Kingdom between 2014 and 2018. Patients who underwent pre-operative cross-sectional imaging with abdominal CT pre-operatively were included in the analysis.

Demographic, histological, clinical, biochemical and operative data were collected and analysed by accessing patient clinical notes and electronic records.

Outcome measures included inpatient mortality, 30-day mortality and 90-day mortality.

Radiological Analysis Pre-operative CT imaging of the abdomen were accessed and analysed. Cross-sectional images at the level of the L3 inferior end plate were analysed. Cross-sectional area of the psoas major and L3 vertebral body (mm2) were calculated and a ratio of psoas major to L3 cross-sectional area calculated (PML3) . Higher PML3 values indicate higher levels of skeletal muscle mass. Cross-sectional area calculation was conducted using the area of interest tool.

Statistical Analysis Statistical analysis for continuous variables was conducted using Mann-Whitney U test and Chi-squared test for categorical variables. Receiver operating characteristics curves were used for analysis of association of PML3 with mortality.

Multivariate analysis was conducted using binary logistic regression analysis. Logistic regression models were produced including P-POSSUM variables with and without the inclusion of PML3. Receiver operating characteristic analysis of the respective logistic regression models were conducted to assess whether the addition of PML3 enhanced mortality prediction.

Conditions

Frailty; Surgery; Emergencies

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: CROSS_SECTIONAL

Interventions

Sarcopenia estimation

Analysis of pre-existing CT imaging

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

• Patient aged 65 or over having emergency laparotomy

Exclusion Criteria

• None

• Minimum Eligible Age: 65 Years
• Maximum Eligible Age: 110 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Wirral University Teaching Hospital NHS Trust

OTHER

Sponsor Role: lead

Responsible Party

Conor Magee

Consultant Surgeon

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Conor Magee, MD

Role: PRINCIPAL_INVESTIGATOR

Wirral University Teaching Hospitals

Locations

WUTH

Upton, Wirral, United Kingdom

Site Status: RECRUITING

Countries

United Kingdom

Central Contacts

Conor Magee, MD

Role: CONTACT

conormagee@nhs.net

+441516785111

Greg Simpson, FRCS

Role: CONTACT

gregorysimpson@doctors.org.uk

+441516785111

Facility Contacts

Conor Magee, MD

Role: primary

01516785111

Other Identifiers

Sarco1

Identifier Type: -

Identifier Source: org_study_id