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Predictors of opioid use for rib fractures in a regional Australian hospital. | LitMetric

Predictors of opioid use for rib fractures in a regional Australian hospital.

Injury

Albury-Wodonga Rural Clinical School, UNSW Medicine, 559 East Street, Albury, NSW, 2640, Australia; Department of Anaesthesia, Albury Wodonga Health, PO Box 326, Albury, NSW, 2640, Australia. Electronic address:

Published: September 2024

AI Article Synopsis

  • - Rib fractures are the most common serious injury in trauma patients in New South Wales, leading to severe pain and potential complications like pneumonia and respiratory failure, often managed with opioids despite their side effects.
  • - A study analyzed data from 624 patients with rib fractures, identifying factors such as the number of fractures, age, and previous opioid use as predictors for opioid consumption during hospitalization.
  • - Although the model effectively identifies predictors of opioid use similar to metropolitan trauma centers, its low predictive accuracy limits its use for individual patient management in this regional setting.

Article Abstract

Background: Rib fractures (RFs) are the leading type of single serious injury in New South Wales trauma patients. Uncontrolled pain drives the sequelae of atelectasis, pneumonia, respiratory failure, and death in severe cases. Opioids are the mainstay of management; however, they carry numerous adverse effects. Understanding patient or injury factors which predict opioid requirement is important to tailor management. Existing evidence is limited to metropolitan trauma centres (MTCs).

Methods: We conducted an observational, retrospective, single-centre cohort study of all admissions to Albury Wodonga Health diagnosed with one or more RFs and discharged between January 1st, 2017, and December 31st, 2022, inclusive. Data collected included demographics, injury characteristics, and management, including analgesia. LASSO regression was performed to determine predictors of average daily opioid use for the first five days of admission in oral morphine equivalents (mg). R and root mean square error (RMSE) were calculated to assess model performance.

Results: We included 624 patients. LASSO selected number of RFs, fracture displacement score, pulmonary contusion, new injury severity score, age, chest tube use, chronic pain history, opioid history and upper or middle lateral RF location categories as predictors. Sex, middle anterior, middle posterior, and lower RF location categories were excluded by LASSO. The out of sample R was 28.6 %. On the scale of log OME, the RMSE was 1.08.

Conclusion: The model is effective at identifying predictors of opioid use in this regional centre, which are similar to those described in evidence from MTCs. However, the low R with wide prediction intervals limits its utility on an individual level.

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Source
http://dx.doi.org/10.1016/j.injury.2024.111586DOI Listing

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