Surgery Clinical Trial
Official title:
Retrospective Analysis of Sarcopenia in Older Patients Undergoing Laparotomy-
Assess the influence of sarcopenia on outcomes of emergency laparotomy in the over 65 age group
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.
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