Prevalence and Predictors of Opioid Prescription at Discharge after Necrotizing Soft Tissue Infections (NSTIs)

Author(s):
Manuel Castillo-Angeles ; Mehreen Kisat; Sean Hickey; Deepika Nehra; Stephanie Nitzschke; Adil Haider; Ali Salim; Reza Askari

Background:

The prevalence of moderate-to-severe pain after hospital discharge in patients with Necrotizing Soft Tissue Infections (NSTIs) is high, and opioids are a predominant analgesic agent used to treat pain in this population. Recent data has shown that the rates of opioid prescription after Emergency General Surgery (EGS) are approximately 13%. There is paucity of data about prescribing-patterns in the NSTI population. Our aim was to study the proportion and predictors of opioid prescription in patients with NSTI at discharge.

Hypothesis:

We hypothesize that the proportion of opioids prescribed to patients with NSTI will be higher than that reported for EGS patients.

Methods:

The 2007-2015 TRICARE insurance database was queried for opioid-naive patients 18-64 years, with a diagnosis of NSTI (identified through ICD-9 diagnosis codes). Prescription of opioid analgesics at discharge was the outcome of interest. Data collection included patient demographics and clinical characteristics. Logistic regression models were used to determine the predictors of opioid prescription at discharge.

Results:

1, 280 patients met our inclusion criteria where 327 (25.55%) received an opioid prescription at discharge. In unadjusted analysis, older patients, male gender, higher rank, being retired, and having a history of depression were less likely to be prescribed opioids at discharge. In multivariate analysis, pre-existing comorbidities (Charlson Comorbidity Index ≥ 1, OR: 2.63, CI: 1.53 – 4.53, p=<0.001) were associated with higher likelihood of opioid prescription. Older patients (>=35 years, OR: 0.47, CI: 0.26 – 0.86, p=0.014) were associated with decreased likelihood of opioid prescription. Race, gender, marital status, rank, beneficiary category, region, history of depression or anxiety and length of hospitalization (LOS) were not significant predictors of opioid prescription.

Conclusions:

The rate of opioid prescription in NSTI patients was almost twice the reported rate for EGS procedures. There was a higher opioid use at discharge in patients with comorbidities. Further studies are needed to understand and optimize pain management strategies for this group of high-risk patients.