What are the predictors of disability in pancreatitis patients?

Several factors characterize and even predict disability in patients with chronic pancreatitis (CP), suggests a study. These predictors can be targeted to reduce disease burden and healthcare expenditure.

A total of 404 patients with CP were assessed, of whom 18 percent had a disability. Those with disability were younger (53.8 vs 58.8; p=0.001), had alcoholic CP (54.1 percent vs 30 percent; p<0.001), more recurrent pancreatitis (83.6 percent vs 61.1 percent; p=0.001), chronic abdominal pain (96.7 percent vs 78.2 percent; p=0.001), and exocrine pancreatic insufficiency (83.6 percent vs 55.5 percent; p<0.001).

This population was also more likely to have concurrent alcohol (39.3 percent vs 23.3 percent; p=0.001) and tobacco abuse (42.6 percent vs 26 percent; p=0.02), anxiety (23 percent vs 18.2 percent; p<0.001), and depression (57.5 percent vs 28.5 percent; p<0.001).

Additionally, a greater number of CP patients with disability were on opiates (68.9 percent vs 43.6 percent; p<0.001), neuromodulators (73.3 percent vs 44 percent; p<0.001), and recreational drugs (27.9 percent vs 15.8 percent; p=0.036).

Disability significantly correlated with the following: chronic pain (odds ratio [OR], 8.71, 95 percent confidence interval [CI], 2.61‒12.9; p<0.001), coeliac block (OR, 4.66, 95 percent CI, 2.49‒8.41; p<0.001), neuromodulator use (OR, 3.78, 95 percent CI, 2.09‒6.66; p<0.001), opioid use (OR, 3.57, 95 percent CI, 2.06‒6.31; p<0.001), and exocrine pancreatic insufficiency (OR, 3.56, 95 percent CI, 1.89‒6.82; p<0.001).

Other predictors of disability included nonopioid controlled medications (OR, 3.45, 95 percent CI, 2.01‒5.99; p<0.001), history of recurrent acute pancreatitis (OR, 2.49, 95 percent CI, 1.25‒4.77; p<0.001), depression (OR, 2.26, 95 percent CI, 1.79‒3.01; p<0.001), and active smoking (OR, 1.8, 95 percent CI, 1.25‒2.29; p<0.001).

A team of investigators reviewed CP patients in a Pancreas Center between 1 January 2016 and 30 April 2021 and divided participants into two groups based on disability. They then performed univariate analysis to identify differences in demographics, risk factors, comorbidities, complications, controlled medications, and resource utilization, as well as multivariate analysis to identify predictors of disability.