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Buta E, Heapy AA, Goulet JL. Longitudinal trajectories of pain intensity in veterans with low back pain. [Abstract]. The journal of pain : official journal of the American Pain Society. 2017 Apr 1; 18(4):S66.
Although there is high heterogeneity in the long-term course of pain, subjects with low back pain (LBP) could potentially be grouped in several distinct pain trajectory classes. We used electronic medical record data from the Veterans Health Administration (VHA) on veterans with an initial diagnosis of LBP in 2010 to investigate pain patterns over 24 months after diagnosis. Pain was collected during VHA clinical encounters using a 0 to 10 scale (0 = no pain, 10 = worst pain). We analyzed 500203 maximum monthly pain scores on 79865 veterans who had pain recorded in at least two months after diagnosis. Mean (SD) age of the sample was 52 (17), 8% were female, 73% white, and the median (IQR) first-month pain was 5 (0-7). Group-based trajectory modeling (SAS proc traj) was used to identify pain trajectory classes and assign subjects to their most likely class. A multinomial logit model assessed sociodemographic/clinical predictors of class membership. Three classes emerged: a "Consistently High Pain" class (28% of the sample consisting of subjects with average pain over time around 6); a "Consistently Mild Pain" class (44% of the sample: average pain starting at 4 and then steadying around 3); and a "No Pain" class (28% of the sample: average pain starts at 2 and then drops to nearly 0). Significant predictors of being in the two painful classes vs. "No Pain" class (all p < 0.001) included: baseline depressive disorder (adjusted odds-ratio (AOR) = 2.18 for "High Pain" vs. "No Pain"; AOR = 1.40 for "Mild Pain" vs. "No Pain"), PTSD (AOR = 1.50;1.22), an opioid prescription (AOR = 3.59;1.89), comorbid musculoskeletal disorders (AOR = 1.43;1.29) and being Black (vs. White) (AOR = 1.53;1.08). Women had lower odds than men of belonging to "High Pain" vs. "No Pain" (AOR = 0.75, p < 0.001). Identifying pain trajectory groups and their predictors may help with developing more targeted interventions, especially for patients in the High Pain group.