Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures

A. Sluka, Kathleen; D. Wager, Tor; P. Sutherland, Stephani; A. Labosky, Patricia; Balach, Tessa; O. Bayman, Emine; Berardi, Giovanni; M. Brummett, Chad; W. Burns, John; Buvanendran, Asokumar; Caffo, Brian; D. Calhoun, Vince; J. Clauw, Daniel; C. Chang, Andrew; S. Coffey, Christopher; L. Dailey, Dana; Ecklund, Dixie; Fiehn, Oliver; M. Fisch, Kathleen; Frey‐Law, Laura; E. Harris, Richard; E. Harte, Steven; D. Howard, Timothy; Jacobs, Joshua; Jacobs, Jon; Jepsen, Kristen; Johnston, Nicolas; D. Langefeld, Carl; C. Laurent, Louise; N. Lenzi, Rebecca; A. Lindquist, Martin; Lokshin, Anna; E. Kahn, Ari; J. McCarthy, Robert; Olivier, Michael; Porter, Linda; Qian, Weijun; A. Sankar, Cheryse; S. Satterlee, John; Swensen, Adam; Vance, Carol; F. Waljee, Jennifer; D. Wandner, Laura; A. Williams, David; L. Wixson, Richard; Joe Zhou, Xiaohong

doi:10.1097/j.pain.0000000000002938

Public

Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures

Published in Pain • Jun 15, 2023

Authors:

Kathleen A. Sluka

Tor D. Wager

Stephani P. Sutherland

Abstract

ABSTRACT: Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and ph...

Subject

Chronic pain

Biomarker

Medicine

Research Assistant

AI chat, annotations, notes & similar papers

Finding related papers...

Discussions

(0)

No comments yet

Be the first to share your thoughts!