Skip to main content

Advertisement

Table 2 Impact of propensity score matching for prospective cohort

From: The feasibility of matching on a propensity score for acupuncture in a prospective cohort study of patients with chronic pain

  Referred for Acupuncture
(n = 173)
Not Referred for Acupuncture
(n = 350)
Standardized differencea
Propensity score characteristicsb
 Opioid therapy plan 20.2% 30.6% −0.239
 Physical therapy past 30 days 1.2% 3.1% −0.141
 Physical therapy past 31–180 days 11.6% 8.6% 0.010
 Physical therapy past 181–365 days 16.2% 8.3% 0.244
 Nonspecific chronic pain 30.1% 30.0% 0.013
 Substance abuse 5.2% 3.7% 0.072
 Sleep problem 26.0% 20.0% 0.143
 History of tobacco use 24.9% 27.1% −0.052
 Anxiety 21.7% 18.5% −0.080
 Pain treatment procedure 18.5% 22.0% −0.087
 Pain diagnosis procedure 46.2% 51.4% −0.104
 Pain medication 57.8% 56.0% 0.036
 Age (years) 49.6 (11.8) 52.8 (11.5) −0.283
 Number of outpatient visits 10.3 (8.0) 10.8 (8.2) −0.062
 Months since cohort entry 42.4 (27.7) 45.5 (26.9) −0.114
 Ambulatory Charlson score 1.1 (1.4) 1.5 (2.0) −0.264
Characteristics that did not contribute to the propensity score
Demographic Characteristics
 Female 71.1% 73.7% −0.059
 White 88.5% 93.5% −0.176
 Hispanic 3.8% 4.1% −0.016
Medical and Psychiatric Comorbidities
 Depression 12.7% 16.6% −0.109
Types of Nonmalignant Chronic Pain (NCP)
 Back and/or neck pain 71.1% 60.6% 0.223
 Joint pain (including osteoarthritis) 66.5% 70.9% −0.095
 Fibromyalgia/other myofascial pain 30.6% 16.9% 0.327
 Headaches 20.2% 11.1% 0.252
 Neuropathy 3.5% 9.1% −0.240
 Temporomandibular disorders 2.9% 2.6% 0.020
 Carpal tunnel syndrome 2.9% 5.1% −0.116
 Abdominal pain 11.0% 9.4% 0.051
 Other NCP 5.2% 5.1% 0.003
 Two of above NCP types 74.0% 68.0% 0.132
Pharmacotherapy
 Any use of an opioid 20.2% 21.7% −0.036
 Opioid morphine equivalent dose (MED) 0.3 (1.1) 0.3 (1.1) −0.026
  ≥ 120 MED 7.5% 8.6% −0.039
Mental health related
 Any antidepressant use 54.9% 49.4% 0.110
 Any anxiolytic use 28.3% 28.3% 0.001
 Any benzodiazepine use 28.9% 27.1% 0.039
  1. aStandardized difference expressed as (difference in means)/(pooled standard deviation) for continuous measures and as 2*(arcsin(√P1)-arcsin(√P2)) for binary data. For propensity score decile adjusted data, standardized differences calculated using same standard deviation as for unadjusted data in order to make comparison of standardized differences with and without adjustment more meaningful
  2. bContinuous data expressed as mean (standard deviation)