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; Burns, John; Buvanendran, Asokumar; Caffo, Brian; D Calhoun, Vince; Clauw, Daniel; Chang, Andrew; S Coffey, Christopher; L Dailey, Dana; Ecklund, Dixie; Fiehn, Oliver; M Fisch, Kathleen; A Frey Law, Laura; E Harris, Richard; E Harte, Steven; D Howard, Timothy; Jacobs, Joshua; M Jacobs, Jon; Jepsen, Kristen; Johnston, Nicolas; D Langefeld, Carl; C Laurent, Louise; Lenzi, Rebecca; A Lindquist, Martin; Lokshin, Anna; Kahn, Ari; J McCarthy, Robert; Olivier, Michael; Porter, Linda; Qian, Wei-Jun; A Sankar, Cheryse; Satterlee, John; C Swensen, Adam; G T Vance, Carol; Waljee, Jennifer; D Wandner, Laura; A Williams, David; L Wixson, Richard; Joe Zhou, Xiaohong; Consortium, A2CPS

doi:10.1097/j.pain.0000000000002938

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

Shared by NobleBlocks on Sep 1, 2023 • 12:00 AM UTC

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...

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