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Your search keyword '"Motley, Kandice L"' showing total 3 results
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3 results on '"Motley, Kandice L"'

1. Early GFAP and UCH-L1 point-of-care biomarker measurements for the prediction of traumatic brain injury and progression in patients with polytrauma and hemorrhagic shock

Author

Sperry, Jason L., primary, Luther, James F., additional, Okonkwo, David O., additional, Vincent, Laura E., additional, Agarwal, Vikas, additional, Cotton, Bryan A., additional, Cannon, Jeremy W., additional, Schreiber, Martin A., additional, Moore, Ernest E., additional, Namias, Nicholas, additional, Minei, Joseph P., additional, Urbanek, Kelly L., additional, Yazer, Mark H., additional, Puccio, Ava M., additional, Fox, Erin E., additional, Brown, Joshua B., additional, Neal, Matthew D., additional, Guyette, Frank X., additional, Wisniewski, Stephen R., additional, _, _, additional, Early-Young, Barbara J., additional, Buck, Meghan L., additional, Adams, Peter W., additional, Molinaro, Rachel L., additional, Merti, Alexandra, additional, Harner, Ashely M., additional, Gimbel, Elizabeth A., additional, Owens, Logan, additional, Hayes, Hannah, additional, Jackson, Alan, additional, Silfies, Laurie, additional, Over, Lisa, additional, Knopf, Steve, additional, Macey-Kalcevic, Melody, additional, Pattison, Angela, additional, Buhay, Megan E., additional, Higginbottom, Brianna J., additional, Marcin, Marissa L., additional, Battistella, Cara, additional, Bai, Yu, additional, Motley, Kandice L., additional, Wang, Yao-Wei, additional, Herrick, Victoria, additional, Woodruff, Garrett, additional, Pa, Veda, additional, Hobbs, Rhonda, additional, Podbielski, Jeanette, additional, Vincent, Laura, additional, Allen, Christy, additional, Alexander, Subin, additional, Hamilton, Natolie, additional, Lopez, Symantha, additional, Gonzalez, Selina Hernandez, additional, Rashall, Jason, additional, Seymour, James, additional, Zarate, Nicole, additional, Zone, Alea, additional, Joergensen, Sarah, additional, Forsythe, Liam, additional, Zaitseva, Daria, additional, Callahan, Paul, additional, Khan, Komal, additional, Doran, Olivia, additional, Gamblin, Sarah, additional, Fisher, Lydia, additional, Schmulevich, Daniela, additional, Balian, Steve, additional, Diamond, Carrie, additional, Kolansky, Jonathan, additional, Torrente, Dena, additional, Van Walchren, Sean, additional, Lape, Diane, additional, Sauaia, Angela, additional, Haukoos, Jason, additional, Ammons, Lee Anne, additional, Chandler, James, additional, Fitzpatrick, Marcela, additional, Vittatoe, Emmalee, additional, Brant, Nick, additional, Kennedy, Stephanie, additional, Swope, Megan, additional, Manning, Ronald, additional, Fonnegra, Cristina Botero, additional, Brito, Sebastian, additional, Calderon, Vivian, additional, Chammas, Majid, additional, Dure, Anthony, additional, Ferreira, Chelsea, additional, Ferreira, Allison, additional, Guerra, Richard, additional, Guzman, Ivonne, additional, Jolly, Aaliyah, additional, Ramdev, Rajan, additional, Reddy, Shreedhar, additional, and Nassaj, Nadia, additional

Published
2024
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2. Opioid Risk Tool, in-hospital opioid exposure, and opioid demand predict pain outcomes following traumatic injury.

Author

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, and Suchting, Robert

Subjects
WOUNDS & injuries, PAIN measurement, RISK assessment, MEDICAL prescriptions, RESEARCH funding, PREDICTION models, HOSPITAL care, DESCRIPTIVE statistics, OPIOID analgesics, PAIN, PAIN management, DRUGS
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. [ABSTRACT FROM AUTHOR]

Published
2024
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