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Opioid Risk Tool, in-hospital opioid exposure, and opioid demand predict pain outcomes following traumatic injury.
Kessler, Danielle A; Webber, Heather E; de Dios, Constanza; Yoon, Jin H; Schmitz, Joy M; Lane, Scott D; Harvin, John A; Heads, Angela M; Green, Charles E; Kapoor, Shweta; Stotts, Angela L; Motley, Kandice L; Suchting, Robert.
Afiliação
  • Kessler DA; Drexel University College of Medicine at Tower Health, USA.
  • Webber HE; University of Texas Health Science Center at Houston, USA.
  • de Dios C; University of Texas Health Science Center at Houston, USA.
  • Yoon JH; University of Texas Health Science Center at Houston, USA.
  • Schmitz JM; University of Texas Health Science Center at Houston, USA.
  • Lane SD; University of Texas Health Science Center at Houston, USA.
  • Harvin JA; University of Texas Health Science Center at Houston, USA.
  • Heads AM; University of Texas Health Science Center at Houston, USA.
  • Green CE; University of Texas Health Science Center at Houston, USA.
  • Kapoor S; Mayo Clinic Alix School of Medicine, Mayo Clinic, USA.
  • Stotts AL; University of Texas Health Science Center at Houston, USA.
  • Motley KL; University of Texas Health Science Center at Houston, USA.
  • Suchting R; University of Texas Health Science Center at Houston, USA.
J Health Psychol ; 29(7): 680-689, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38641873
ABSTRACT
Prescribed opioids are a mainstay pain treatment after traumatic injury, but a subgroup of patients may be at risk for continued opioid use. We evaluated the predictive utility of a traditional screening tool, the Opioid Risk Tool (ORT), and two other

measures:

average in-hospital milligram morphine equivalents (MME) per day and an assessment of opioid demand in predicting pain outcomes. Assessments of pain-related outcomes (pain intensity, interference, injury-related stress, and need for additional pain treatment) were administered at 2 weeks and 12 months post-discharge in a sample of 34 patients hospitalized for traumatic injury. Bayesian linear models were used to evaluate changes in responses over time as a function of predictors. High-risk ORT, higher MME per day, and greater opioid demand predicted less change in outcomes over time. This report provides first evidence that malleable factors of opioid and opioid demand have utility in predicting pain outcomes following traumatic injury.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Dor / Ferimentos e Lesões / Analgésicos Opioides Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: J Health Psychol Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Dor / Ferimentos e Lesões / Analgésicos Opioides Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: J Health Psychol Ano de publicação: 2024 Tipo de documento: Article