Abstract
Objective
The purpose of this retrospective cohort study was to characterize the prevalence, incidence, associated conditions, and demographics of complex regional pain syndrome (CRPS) using a large, real-world dataset.
Methods
This retrospective cohort study analyzed data from the TriNetX Global Collaborative Network, including over 150 million patients across 18 countries, to identify CRPS prevalence, incidence, demographics, and comorbidities.
Results
A total of 99,878 patients with CRPS were identified over a 20-year period, based on ICD-10-coded electronic health record data. Overall prevalence was 62 per 100,000 individuals, and incidence was 13.5 per 100,000 person-years, with rates more than twice as high in females compared to males. Both measures peaked in individuals aged 40–44 years and were highest among Native Hawaiians/Pacific Islanders. Lower extremity involvement was 1.5 times more common than upper extremity involvement, and cumulative incidence was noticeably higher following fractures, particularly foot fractures (495 per 100,000). Rates of CRPS more than doubled from 2004–2008 to 2019–2023. Bidirectional associations were observed between CRPS and multiple conditions, including depression, anxiety, insomnia, and irritable bowel syndrome, with relative risks ranging from approximately 1.4-fold to 24-fold.
Discussion
Using one of the largest CRPS cohorts reported to date, this real-world analysis clarifies contemporary epidemiology and reveals bidirectional associations with psychological, inflammatory, and autoimmune conditions. The findings are consistent with a multifactorial clinical profile involving immune, neurologic, and psychosocial mechanisms, guiding future mechanistic and clinical research.
Keywords: complex regional pain syndrome, chronic pain, epidemiology, risk factors, comorbidities
Introduction
Complex Regional Pain Syndrome Type I (CRPS) is a chronic pain disorder that can result in substantial disability. There is no diagnostic test for CRPS; it is diagnosed clinically based on the presence of characteristic signs and symptoms, as outlined in the Budapest Criteria.1 CRPS is characterized by disproportionate pain, hyperalgesia, and allodynia, predominantly affecting the limbs and frequently following trauma or surgery.2 The underlying pathophysiology is multifactorial, involving both peripheral and central mechanisms, including neurogenic inflammation, central sensitization, and autonomic dysregulation.3
Although relatively uncommon, CRPS is clinically important due to its severity and functional impact. Reported estimates of CRPS occurrence differ depending on the metric used. Incidence reflects the rate of new cases over a defined period of time (typically expressed per 100,000 person-years), while prevalence reflects the proportion of a population with a condition (often expressed per 100,000 individuals). Pooled prevalence estimates are derived from systematic reviews and combine figures across multiple studies. The reported incidence and prevalence of CRPS vary across studies and regions. A population-based study in the Netherlands found an incidence of 26.2 per 100,000 person-years, with higher rates in females and individuals aged 61–70 years.4 Sandroni et al reported a lower incidence of 5.46 per 100,000 person-years, with a 4:1 female-to-male ratio and a median age of onset of 46 years.5 A study in Korea reported an incidence of 29.0 per 100,000 person-years, and an analysis of a large US inpatient database found a prevalence of 0.07%.6,7 A systematic review of 214 articles from 35 countries estimated a pooled 12-month prevalence of approximately 3%.8 These findings highlight the heterogeneity of CRPS epidemiological estimates, which may reflect differences in population characteristics, diagnostic practices, and study design.
Fractures are one of the most common injuries that lead to the development of CRPS. Distal radius fractures are particularly implicated, although reported incidence rates vary widely, ranging from 1% to 37%.5,8 Lower extremity fractures can also lead to CRPS. One study reported an incidence of 15.2% for ankle fractures and 2.9% for fractures of the fifth metatarsal.9
The mechanisms underlying the development of CRPS are not fully understood, but multiple contributing factors have been identified, including genetic, neurological, inflammatory, immune, psychological, and environmental influences.10 Evidence for a genetic component comes from higher incidence rates observed in women, individuals of Northern European descent, and family members of affected individuals.10 Inflammatory and immune processes appear to play a role as well. Studies have reported elevated levels of pro-inflammatory cytokines and the presence of autoantibodies in patients with CRPS.11 In addition, functional and structural alterations of the central nervous system are frequently observed in this population, suggesting that neural mechanisms contribute to symptom persistence.12–15 Psychological factors may further increase susceptibility. Adverse childhood experiences, post-traumatic stress disorder, and anxiety have all been identified as risk factors for developing CRPS.1,16 Environmental factors such as smoking have been shown to elevate the risk of chronic pain conditions more broadly and may contribute to CRPS onset or severity.17–19
Existing estimates of CRPS prevalence and incidence are largely derived from single-institution or single-country cohorts with limited sample sizes. This contributes to heterogeneity across studies and the limited characterization of demographic patterns. In addition, few studies have examined how CRPS rates have changed over time, and the bidirectional relationship between CRPS and psychological, autoimmune, and inflammatory conditions. To address these gaps, this investigation uses a large, multinational real-world dataset to characterize the prevalence, incidence, demographic distribution, temporal trends, and associated conditions of CRPS.
Materials and Methods
We conducted a retrospective cohort design using data from the TriNetX Global Collaborative Network. TriNetX is a federated electronic health record platform with aggregated patient information from 18 countries and over 144 healthcare organizations. The database includes basic demographics information, diagnostic codes, procedural codes, lab results, genetic information, and medication codes. At the time of the query (10/23/2024), the Global Collaborative Network included over 150 million patients. The TriNetX platform includes advanced query capabilities and built-in analysis tools. Access to the database is restricted to institutions with contractual agreements with TriNetX. Researchers at institutions within the TriNetX research network obtain access to data through institutional approval. All data accessed through TriNetX were de-identified in compliance with HIPAA Privacy Rules and applicable international data protection regulations. This study was approved by the SUNY Upstate Medical University Institutional Review Board (ID: 2199459–1).
Demographics, Prevalence, and Incidence
Patients with CRPS Type 1 were identified using the International Classification of Diseases 2010 (ICD-10) codes. The code G90.5 was used to identify individuals with CRPS, and the group was subdivided by upper extremity, lower extremity, and laterality. TriNetX uses an ICD-9-to-ICD-10 mapping algorithm to convert codes from ICD-9 to ICD-10. As a result, previously used ICD-9 codes for CRPS (337.20–337.22, 337.29) have been incorporated into the G90.5 codes used in TriNetX. Because cases were identified from ICD-10 codes, CRPS diagnosis is dependent on the accuracy of clinician diagnosis and coding, introducing the potential for misclassification. Upper extremity and lower extremity CRPS prevalence and incidence rates were generated using region-specific codes (G90.51, G90.52). CRPS cases not coded for upper or lower extremity were excluded from this analysis. The query was performed for a 20-year window (10/22/2004–10/23/2024) and in four 5-year increments (1/1/2004–12/31/2008, 1/1/2009–12/31/2013, 1/1/2014–12/31/2018, 1/1/2019–12/31/2023). Incidence and prevalence were calculated using the TriNetX platform’s built-in analysis tool. This tool applies its own cohort-generation criteria, which differ from those used by the Explore Cohort feature that was used to report the sample demographics. As a result, the cohort used for prevalence and incidence calculation (n=90,040) was a subset of the CRPS cohort reported in the demographics analysis (n=99,878). Prevalence was defined as the number of patients with CRPS (G90.5) during a specified period divided by the number of patients active in the network during that same period, expressed per 100,000 persons. The incidence rate was defined as the number of new CRPS cases during the period divided by the accumulated person-time risk, expressed per 100,000 person-years. Accumulated person-time risk is the number of patients multiplied by the days at risk. A patient’s days at risk start with the first patient record and end with the event of interest, patient’s death, or the last medical record. Fracture cohorts were identified using ICD-10 codes for upper and lower extremity. For each cohort, only patients whose CRPS diagnosis followed the index fracture were counted as cases, and the denominator comprised all patients with the corresponding fracture. Incidence of CRPS in patients with upper extremity fractures was calculated based on the risk of developing upper extremity or lower extremity CRPS in patients who sustained an upper or lower extremity fracture, respectively. For patients with upper extremity fractures, the development of CRPS was investigated by using the general code for CRPS (G90.5), the code for upper extremity CRPS (G90.51), and excluding individuals with lower extremity CRPS (G90.52). The same method was used for lower extremity fractures; however, lower extremity CRPS was included, and upper extremity CRPS was excluded.
Associated Conditions
Potential risk factors that may be associated with CRPS were investigated using TriNetX’s built-in Compare Cohort tool. Cohorts of patients with and without each target condition were generated, and the rate of subsequent CRPS was compared. The index date was the first documented diagnosis of the target condition, and for the comparison group, it was the first documented visit. Individuals were counted if they developed CRPS after a 1-month lag from the index event. Eight conditions (depression, anxiety, lupus erythematosus, rheumatoid arthritis, inflammatory bowel disease, irritable bowel syndrome, insomnia, and nicotine use) were selected a priori based on prior literature and clinical observation. Psychological and sleep conditions (depression, anxiety, and insomnia) were included because they have been associated with chronic pain and may share overlapping central mechanisms with central sensitization.10,20–22 Autoimmune and inflammatory conditions (rheumatoid arthritis, lupus erythematosus, and inflammatory bowel disease) were selected because CRPS involves inflammatory and autoimmune processes, raising the possibility of shared pathophysiology.11,23,24 Irritable bowel syndrome was included because it frequently co-occurs with other chronic pain disorders.25 Nicotine, a modifiable environmental factor, was also evaluated as it has been associated with the development of chronic pain.17,18 Individuals were counted as cases if they developed CRPS after the diagnosis of the target condition. Two analyses were performed: (1) cohorts balanced for age and sex only, and (2) a restricted analysis that also excluded individuals with any of the other seven target conditions. In the restricted analysis, patients with a prior diagnosis of 7 of the 8 selected conditions were excluded from both comparison cohorts before propensity score matching for age and sex. These exclusions were applied identically to both groups and were intended to reduce diagnostic overlap and shared-mechanism confounding among conditions that may co-occur. Additional exclusions beyond the selected conditions were not feasible because applying further restrictions reduced cohort sizes below the threshold at which TriNetX returns results. As a consequence, residual confounding conditions not included in the restricted analysis may impact the results. Cohorts were balanced for age and sex within the TriNetX Analytics platform using propensity score matching. Propensity scores were generated by logistic regression with age and sex as covariates, and patients were matched 1:1 using a greedy nearest-neighbor algorithm (caliper = 0.1 pooled SD). Balance was evaluated using standardized mean difference for age and percentage of cohort for sex, with a difference of <0.1 considered well balanced. The large size of the original cohorts limited balancing using propensity score matching to age and sex.
Conditions more likely to occur in individuals with CRPS were also examined using the Compare Cohort tool. For the analysis of conditions arising after CRPS, the same conditions were examined, excluding nicotine use, with the addition of malaise and fatigue, obesity, and osteoporosis. These factors were included because malaise and fatigue are often reported by patients with chronic pain conditions,26 and obesity and osteoporosis may occur due to lifestyle and neurophysiologic changes that occur in patients with chronic pain.9,27,28 Patients with and without CRPS were compared for subsequent development of these conditions. The index date was the first documented diagnosis of CRPS, and for the comparison group, it was the first documented visit. Individuals were counted if they developed the target condition at least 1 month after the index event. As above, analyses included age- and sex-balanced comparisons and a restricted analysis. In the restricted analysis, patients with any of the other nine selected conditions were excluded. To further reduce confounding, patients with chronic pain conditions, chronic neurologic conditions, major psychiatric disorders, and autoimmune or inflammatory conditions were also excluded (See Appendix Table 1). As above, patients with a controlled diagnosis were excluded from both cohorts before matching based on age and sex.
Data Analysis
Demographic characteristics were summarized using descriptive statistics. Prevalence was reported as the number of cases per 100,000 individuals, and incidence was expressed as new cases per 100,000 person-years. Prevalence and incidence rates were reported for a 20-year period, and in 5-year increments. For the fracture cohorts, cumulative incidence (per 100,000 patients) and incidence rate (new cases per 100,000 person-years) were reported. To assess whether the sex-based prevalence comparison was influenced by patients with unknown sex, a sensitivity analysis was performed by recalculating the 20-year sex-based analysis in a cohort excluding patients with unknown sex. For analyses examining the relationship between the selected conditions and CRPS, the number of individuals with and without each condition was reported. Risk differences and risk ratios with 95% confidence intervals were calculated, with statistical significance set at α = 0.05.
Results
Demographics
A total of 99,878 patients with CRPS were identified using the TriNetX Explore Cohort feature. Demographics are reported in Table 1. The upper extremity was involved in 29.0% of cases, the lower extremity in 43.8%, and 27.2% were not coded for body region. Among patients with upper extremity involvement, 28.6% had right-sided symptoms, 23.5% had left-sided symptoms, 10.5% had bilateral symptoms, and 37.4% were not coded for laterality. For lower extremity involvement, 28.7% had right-sided symptoms, 28.6% had left-sided symptoms, 13.8% had bilateral symptoms, and 28.9% were not coded for laterality.
Table 1.
Demographic Information for Patients with CRPS Type 1
| Patients (%) | Female | Male | Unknown | Mean Age (range) | Hispanic | Non-Hispanic | Unknown | White | Black | Asian | Hawaiian/Pacific Islander | Native American | Unknown | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| All Patients | 99,878 (100%) | 68.8% | 27.6% | 3.7% | 55(1–90) | 5.3% | 63.2% | 31.5% | 68.6% | 9.9% | 1.6% | 0.9% | 0.4% | 15.3% |
| UE | 28,918(29.0%) | 69.1% | 27.5% | 3.4% | 57(7–90) | 6.3% | 62.6% | 31.2% | 66.0% | 11.7% | 1.6% | 1.0% | 0.4% | 15.9% |
| UE R | 8,264(8.0%) | 69.7% | 25.5% | 4.9% | 55(7–90) | 6.7% | 65.6% | 27.7% | 65.8% | 13.0% | 1.5% | 1.2% | 1.2% | 13.9% |
| UE L | 6,798(7.0%) | 67.4% | 28.6% | 4.0% | 56(7–90) | 7.1% | 65.5% | 27.4% | 66.0% | 13.2% | 1.8% | 0.9% | 0.5% | 13.6% |
| UE Bil | 3,032(3.0%) | 71.2% | 24.6% | 4.2% | 55(9–90) | 6.1% | 68.3% | 25.6% | 72.6% | 9.3% | 2.2% | 0.6% | 0.6% | 10.5% |
| LE | 43,763(43.8%) | 68.0% | 27.4% | 4.6% | 54(4–90) | 5.0% | 64.1% | 30.9% | 70.1% | 9.8% | 1.1% | 1.1% | 0.4% | 14.8% |
| LE R | 12,548(12.6%) | 68.8% | 25.8% | 5.3% | 51(5–90) | 5.7% | 67.9% | 25.8% | 70.9% | 10.3% | 1.1% | 0.9% | 0.4% | 12.9% |
| LE L | 12,517(12.5%) | 67.5% | 26.7% | 5.8% | 51(4–90) | 5.3% | 65.9% | 28.8% | 70.2% | 10.8% | 1.2% | 1.0% | 0.4% | 13.5% |
| LE B | 6,019 (6.0%) | 67.9% | 26.9% | 5.2% | 54(1–90) | 5.4% | 70.8% | 23.8% | 73.9% | 7.8% | 1.3% | 1.1% | 0.5% | 11.0% |
Notes: 10/22/2004–10/23/2024 (20 Years), Total Patients in Global Network 154,294,240. Key: UE, Upper Extremity; R, Right; L, Left; LE, Lower Extremity; B, Bilateral.
The average age of patients with CRPS was 55 years (range = 1–90, SD = 18). Patients with upper extremity symptoms had the highest average age (57 years), while those with lower extremity symptoms had the lowest (54 years). The sample was primarily White (68.6%), non-Hispanic (63.2%), and female (68.8%).
Prevalence and Incidence
Prevalence and incidence rates per 100,000 individuals are reported in Table 2. Over the 20-year study period, the prevalence of CRPS was 62 per 100,000 individuals, and the incidence rate was 13.5 per 100,000 person-years. The prevalence of CRPS in females was more than double that in males. A sensitivity analysis excluding patients with unknown sex yielded a similar female-to-male prevalence ratio (2.18:1) compared to the primary analysis (2.19:1). The highest prevalence (125 per 100,000) and incidence (22.6 per 100,000 person-years) occurred in 40–44-year-olds, while the lowest rates were observed in those aged 85 years and older. Native Hawaiians or Pacific Islanders had the highest prevalence (174 per 100,000) and incidence rates (33.2 per 100,000 person-years) by race, nearly double that of White individuals.
Table 2.
Rates of CRPS Type 1
| 20 Years (10/2004–10/2024) | ||
|---|---|---|
| Prevalence | Incidence Rate (Person-Years) |
|
| CRPS All | 62 (90,040) | 13.5 |
| Sex | ||
| Female | 81 (61,646) | 16.8 |
| Male | 37 (24,711) | 8.8 |
| Unknown Gender | 130 (3683) | 30.7 |
| Age | ||
| 0–4 | 38 (5894) | 12.4 |
| 5–9 | 26 (4165) | 6.9 |
| 10–14 | 23 (3737) | 7.3 |
| 15–19 | 34 (4621) | 11.0 |
| 20–24 | 63 (5973) | 15.3 |
| 25–29 | 82 (6998) | 18.3 |
| 30–34 | 103 (8694) | 21.2 |
| 35–39 | 116 (10,042) | 21.9 |
| 40–44 | 125 (11,718) | 22.6 |
| 45–49 | 112 (10,201) | 19.7 |
| 50–54 | 91 (7437) | 15.7 |
| 55–59 | 72 (5032) | 12.1 |
| 60–64 | 52 (2767) | 8.8 |
| 65–69 | 37 (1454) | 6.2 |
| 70–74 | 27 (801) | 4.7 |
| 75–79 | 19 (321) | 3.3 |
| 80–84 | 13 (125) | 2.9 |
| 85 and older | 11 (60) | 2.9 |
| Race/Ethnicity | ||
| Native American | 100 (344) | 22.3 |
| Asian | 27 (1350) | 5.1 |
| Black or African American | 62 (9187) | 11.7 |
| Native Hawaiian or Pacific Islander | 174 (854) | 33.2 |
| Unknown Race/Ethnicity | 27 (13,137) | 7.5 |
| White | 93 (61,912) | 17.5 |
| Other Race/Ethnicity | 34 (3256) | 10.6 |
| Involved Body Region | ||
| CRPS UE | 10 (14,077) | 2.2 |
| UE Right | 6 (9095) | 1.5 |
| UE Left | 5 (7555) | 1.1 |
| UE Bilateral | 2 (3017) | 0.4 |
| CRPS LE | 15 (21,977) | 3.3 |
| LE Right | 9 (13,225) | 1.8 |
| LE Left | 9 (13,987) | 2.2 |
| LE Bilateral | 4 (6454) | 1.1 |
Notes: Numbers are per 100,000 patients. Values in () represent number of patients.
Abbreviations: UE, Upper Extremity; LE, Lower Extremity.
Lower extremity involvement was 1.5 times higher than upper extremity, with a prevalence of 15 per 100,000 and an incidence of 3.3 per 100,000 person-years. Bilateral presentations were rare, with an incidence rate of 1.1 per 100,000 person-years in the lower extremity and 0.4 in the upper extremity. Similar to the overall sample, the prevalence and incidence rates in the upper and lower extremities were greatest in females, Native Hawaiians or Pacific Islanders, and individuals aged 40–44 years. Rates of CRPS were similar for the right and left extremities.
Over a 20-year period, both prevalence and incidence increased. From 2004–2008, prevalence and incidence were 23 and 7.7 per 100,000, respectively, compared with 49 and 19.7 per 100,000, respectively, from 2019 to 2023 (Table 3).
Table 3.
Rates of CRPS Type 1 in 5-Year Increments
| Prevalence | Incidence Rate (Person-Years) |
|
|---|---|---|
| 2004–2008 | 23 (5759) | 7.7 |
| 2009–2013 | 34 (15,833) | 11.7 |
| 2014–2018 | 47 (36,409) | 17.2 |
| 2019–2023 | 49 (46,019) | 19.7 |
Notes: Numbers are per 100,000 patients. Values in () represent number of patients.
The cumulative incidence and incidence rates for CRPS among individuals with extremity fractures are presented in Table 4. The cumulative incidence of CRPS was nearly twice as high in patients with lower extremity fractures (354 per 100,000) compared with those with upper extremity fractures (189 per 100,000). The highest cumulative incidence and incidence rates were observed in patients with foot fractures (495 per 100,000 and 48.2 per 100,000 person-years, respectively). In contrast, the lowest rates were found in patients with humerus fractures (200 per 100,000 and 22.3 per 100,000 person-years).
Table 4.
Rates of CRPS Type 1 in Patients with a History of a Fracture
| 20 Years (10/2004–10/2024) | ||
|---|---|---|
| Cumulative Incidence | Incidence Rate (Person-Years) |
|
| UE Fracture | 189 {8140} | 21.5 |
| Wrist/Hand Fracture (S62) | 239 {4625} | 24.8 |
| Forearm Fracture (S52) | 254 {4269} | 28.5 |
| Humerus Fracture (S42) | 200 {3102} | 22.3 |
| LE Fracture | 354 {12,086} | 38.0 |
| Foot Fracture (S92) | 495 {6956} | 48.2 |
| Lower Leg Fracture (S82) | 433 {7058} | 46.4 |
| Femur Fracture (S72) | 259 {2459} | 29.2 |
Notes: Numbers are per 100,000 patients. Values in {} represent number of patients.
Abbreviations: UE, Upper Extremity; LE, Lower Extremity, ()-ICD-10 Code.
Associated Conditions
Association with CRPS
The association between the selected conditions and the development of CRPS is reported in Table 5. In the unrestricted cohorts, autoimmune conditions showed strong associations with CRPS. Compared with individuals without these conditions, those with rheumatoid arthritis, lupus erythematosus, or inflammatory bowel disease had substantially higher relative likelihoods of CRPS (RRs of 19, 11, and 14, respectively). Insomnia (RR=18, 95% CI, 16.7–20.4), depression (RR=20, 95% CI, 18.5–21.7), anxiety (RR=6, 95% CI, 5.6–6.8), and nicotine use (RR=13, 95% CI, 12.3–14.3) were also associated with greater likelihood of CRPS.
Table 5.
Potential Risk Factors for the Development of CRPS Type 1
| Condition | Without Condition* | With Condition# | Risk Difference (95% CI) | Risk Ratio |
|---|---|---|---|---|
| Depression | 8,177,794 | 8,171,014 | 0.175% (0.172, 0.178), p<0.001 | 20 (18.5, 21.7) |
| Code: F32, F33 | 750 (0.009%) | 15,017 (0.184%) | ||
| Depression (Restricted) | 603,060 | 603,060 | 0.011% (0.005, 0.016), p<0.001 | 1.7 (1.3, 2.2) |
| Code: F32, F33 | 92 (0.015%) | 156 (0.026%) | ||
| Anxiety | 4,528,285 | 4,519,130 | 0.054% (0.051, 0.056), p<0.001 | 6 (5.6, 6.8) |
| Code: F40-F48 | 468 (0.010%) | 2,899 (0.064%) | ||
| Anxiety (Restricted) | 1,227,223 | 1,228,289 | 0.006% (0.003, 0.010), p<0.001 | 1.4 (1.2, 1.6) |
| Code: F40-F48 | 204 (0.017%) | 283 (0.023%) | ||
| Lupus Erythematosus | 85,497 | 85,347 | 0.254% (0.217, 0.291), p<0.001 | 11 (7.2, 17.9) |
| Code: L93 | 21 (0.025%) | 238 (0.279%) | ||
| Lupus Erythematosus (Restricted) | 7,748 | 7,748 | - | - |
| Code: L93 | - | - | ||
| Rheumatoid Arthritis | 938,189 | 937,036 | 0.221% (0.211, 0.231), p<0.001 | 19 (15.9, 23.3) |
| Code: M05, M06 | 114 (0.012%) | 2,181 (0.233%) | ||
| Rheumatoid Arthritis (Restricted) | 120,900 | 121,020 | 0.005% (−0.007, 0.017), p=0.41 | 1.3 (0.73, 2.2) |
| Code: M05, M06 | 23 (0.019%) | 29 (0.024%) | ||
| Inflammatory Bowel Disease | 3,941,612 | 3,939,938 | 0.141% (0.137, 0.145), p<0.001 | 14 (12.7, 15.4) |
| Code: K50-K52 | 429 (0.011%) | 5,979 (0.152%) | ||
| Inflammatory Bowel Disease (Restricted) | 337,583 | 337,861 | 0.002% (−0.004, 0.008), p=0.55 | 1.1 (0.76, 1.7) |
| Code: K50-K52 | 46 (0.014%) | 52 (0.015%) | ||
| Irritable Bowel Syndrome | 1,327,500 | 1,325,246 | 0.221% (0.212, 0.229), p<0.001 | 18 (15.4, 20.8) |
| Code: K58 | 173 (0.013%) | 3,097 (0.234%) | ||
| Irritable Bowel Syndrome (Restricted) | 110,143 | 110,234 | 0.021% (0.008, 0.034), p=0.002 | 2.5 (1.4, 4.6) |
| Code: K58 | 15 (0.014%) | 38 (0.034%) | ||
| Insomnia | 2,937,108 | 2,931,758 | 0.214% (0.208, 0.220), p<0.001 | 18 (16.7, 20.4) |
| Code: G47 | 361 (0.012%) | 6,634 (0.226%) | ||
| Insomnia (Restricted) | 1,049,119 | 1,049,997 | 0.012% (0.008, 0.016), p<0.001 | 2.0 (1.6, 2.4) |
| Code: G47 | 131 (0.012%) | 256 (0.024%) | ||
| Nicotine Use | 8,348,923 | 8,347,200 | 0.116% (0.114, 0.119), p<0.001 | 13 (12.3, 14.3) |
| Code: Z87.891, F17.21 | 790 (0.009%) | 10,482 (0.126%) | ||
| Nicotine Use (Restricted) | 1,351,855 | 1,352,993 | 0.014% (0.011, 0.018), p<0.001 | 2.0 (1.7, 2.4) |
| Code: Z87.891, F17.21 | 190 (0.014%) | 382 (0.028%) |
Notes: Cohorts are matched based on age and sex. Conditions labeled “(Restricted)” removed individuals from the cohort who were diagnosed with any of the other conditions prior to the diagnosis of CRPS. * Total number of patients without the target condition and number of those patients with CRPS. # Total number of patients with the target condition and number of those patients with CRPS. “-” Patient count was too low for TriNetX to provide results.
In the restricted cohorts, these associations were attenuated. Rheumatoid arthritis, lupus erythematosus, and inflammatory bowel disease were no longer significantly associated with CRPS. The strongest remaining association was observed for irritable bowel syndrome (RR=2.5, 95% CI, 1.4–4.6), while anxiety demonstrated the smallest statistically significant association (RR=1.4, 95% CI 1.2–1.6). This contrast between unrestricted and restricted cohorts highlights the importance of accounting for potential confounding and diagnostic overlap.
CRPS as an Associated Condition
The association between CRPS and the subsequent development of selected conditions is reported in Table 6. In the unrestricted cohorts, individuals with CRPS were more likely to receive diagnoses of autoimmune disorders, including rheumatoid arthritis (RR=12, 95% CI, 10.1–13.7), lupus erythematosus (RR=24, 95% CI, 12.7–45.5), and inflammatory bowel disease (RR=10, 95% CI, 9.1–10.8). Individuals with CRPS were also associated with higher likelihood of insomnia (RR=15, 95% CI, 13.7–16.4), malaise and fatigue (RR=11, 95% CI, 10.4–11.8), depression (RR=13, 95% CI, 12.2–13.7), anxiety (RR=10, 95% CI, 9.8–10.9), irritable bowel syndrome (RR=13, 95% CI, 11.9–15.4), obesity (RR=6, 95% CI, 5.6–6.1), and osteoporosis (RR=8, 95% CI, 7.4–8.8).
Table 6.
CRPS Type 1 as a Potential Risk Factor
| Condition | Without CRPS* | With CRPS# | Risk Difference (95% CI) | Risk Ratio |
|---|---|---|---|---|
| Depression (F32, F33) | 75,804 | 66,447 | 17.980% (17.666, 18.293), p<0.0001 | 13 (12.2, 13.7) |
| 1,142 (1.50%) | 12,948 (19.5%) | |||
| Depression (Restricted) | 17,240 | 17,508 | 8.579% (8.146, 9.012), p<0.0001 | 24 (18.6, 30.4) |
| 65 (0.377%) | 1,568 (8.96%) | |||
| Anxiety (F40-F48) | 72,167 | 65,059 | 18.885% (18.556, 19.214), p<0.0001 | 10 (9.8, 10.9) |
| 1,457 (2.02%) | 13,600 (20.9%) | |||
| Anxiety (Restricted) | 17,196 | 17,704 | 12.635% (12.095, 13.176), p<0.0001 | 10 (8.9, 11.5) |
| 239 (1.39%) | 2,483 (14.0%) | |||
| Lupus Erythematosus (L93) | 87,097 | 86,954 | 0.262% (0.227, 0.298), p<0.0001 | 24 (12.7, 45.5) |
| <10 (0.011%) | 238 (0.274%) | |||
| Lupus Erythematosus (Restricted) | 17,399 | 17,399 | - | - |
| - | - | |||
| Rheumatoid Arthritis (M05, M06) | 85,895 | 84,537 | 2.161% (2.054, 2.267), p<0.0001 | 12 (10.1, 13.7) |
| 172 (0.200%) | 1,996 (2.36%) | |||
| Rheumatoid Arthritis (Restricted) | 16,686 | 16,650 | 1.249% (1.066, 1.433), p<0.0001 | 12 (7.5, 19.1) |
| 19 (0.114%) | 227 (1.36%) | |||
| Inflammatory Bowel Disease (K50-K52) |
82,554 | 79,976 | 6.228% (6.043, 6.413), p<0.0001 | 10 (9.1, 10.8) |
| 579 (0.701%) | 5,542 (6.93%) | |||
| Inflammatory Bowel Disease (Restricted) |
14,009 | 14,151 | 2.850% (2.533, 3.167), p<0.0001 | 7 (5.4, 8.9) |
| 67 (0.478%) | 471 (3.33%) | |||
| Irritable Bowel Syndrome (K58) |
82,032 | 79,936 | 3.668% (3.528, 3.808), p<0.0001 | 13 (11.9, 15.4) |
| 239 (0.291%) | 3,165 (3.96%) | |||
| Irritable Bowel Syndrome (Restricted) |
16,678 | 16,704 | 1.724% (1.513, 1.935), p<0.0001 | 15 (9.6, 23.3) |
| 21 (0.126%) | 309 (1.85%) | |||
| Malaise and Fatigue (R53.8) | 74,178 | 69,250 | 14.083% (13.801, 14.366), p<0.0001 | 11 (10.4, 11.8) |
| 1,034 (1.39%) | 10,718 (15.5%) | |||
| Malaise and Fatigue (Restricted) | 15,706 | 16,007 | 6.197% (5.783, 6.610), p<0.0001 | 10 (8.6, 12.8) |
| 110 (0.700%) | 1,104 (6.90%) | |||
| Insomnia (G47) | 79,954 | 76,072 | 9.045% (8.828, 9.263), p<0.0001 | 15 (13.7, 16.4) |
| 516 (0.645%) | 7,372 (9.69%) | |||
| Insomnia (Restricted) | 16,389 | 16,666 | 7.375% (6.942, 7.807), p<0.0001 | 12 (9.6, 14.0) |
| 114 (0.696%) | 1,345 (8.07%) | |||
| Obesity (E66) | 76,844 | 75,637 | 12.485% (12.206, 12.764), p<0.0001 | 6 (5.6, 6.1) |
| 1,991 (2.59%) | 11,403 (15.1%) | |||
| Obesity (Restricted) | 14,318 | 15,378 | 5.590% (5.135, 6.044), p<0.0001 | 4.6 (3.9, 5.3) |
| 222 (1.54%) | 1,098 (7.14%) | |||
| Osteoporosis (M81) | 82,643 | 81,732 | 4.690% (4.526, 4.854), p<0.0001 | 8 (7.4, 8.8) |
| 549 (0.664%) | 4,376 (5.35%) | |||
| Osteoporosis (Restricted) | 14,911 | 14,860 | 2.417% (2.147, 2.686), p<0.0001 | 11 (8.0, 15.9) |
| 35 (0.235%) | 394 (2.65%) |
Notes: Cohorts are matched based on age and sex. Conditions labeled “(Restricted)” removed individuals from the cohort who were diagnosed with any of the other conditions prior to the diagnosis of CRPS and patients with selected chronic pain, psychiatric, autoimmune, inflammatory, and neurologic conditions were excluded (see Appendix). * Total number of patients without CRPS and number of those patients who develop the target condition. # Total number of patients with CRPS and number of those patients who develop the target condition.
In the restricted cohorts, several associations increased in magnitude. The largest increase was for depression, rising from a relative risk of 13 to 24. No relative risk change was observed for anxiety or rheumatoid arthritis, while four conditions demonstrated reduced associations. Inflammatory bowel disease had the greatest proportional reduction, with relative risk decreasing from 10 to 7. In the restricted cohorts, the sample size for lupus erythematosus was too small to report.
Discussion
The purpose of this study was to describe the demographics, prevalence, and incidence of CRPS, as well as to examine its associations with other medical conditions. Although these areas have been investigated previously, results across studies have been mixed. The large sample size in the present study provides more robust estimates, helping to clarify existing research.
As seen in previous studies,5,29–34 we found an increased rate of CRPS in females (2.19:1), with a mean age slightly older than those reported by other authors.5 In contrast to prior work, which has often identified the upper extremities as the most commonly affected,4,35–37 our data showed that CRPS of the lower extremities was 1.5 times more common than in the upper extremities. A recent systematic review found an incidence rate of 0.19 to 13.6% after a radial fracture, with higher body mass index, female sex, and psychological factors identified as risk factors.38 The few studies that have investigated rates of CRPS after lower extremity fractures reported a number ranging from 2.9% for fifth metatarsal fractures to 30% after tibial fractures.39,40 Although these rates are higher than those observed in our study, the pattern of increased incidence following lower extremity fractures compared with upper extremity fractures is consistent with our findings.9
The TriNetX data used in this study showed an overall CRPS prevalence of 0.06%, which is consistent with some prior literature.7,37 In a population-based study from Minnesota, Sandroni et al reported a lower prevalence of 20.6 per 100,000, though their analysis was limited to 106,470 individuals and only 74 identified cases of CRPS.5 Our estimated 20-year incidence rate of 13.5 per 100,000 person-years falls within the range reported in several other studies (5.5–29.0 per 100,000 person-years).4–6 The highest prevalence and incidence rates in our cohort were observed among Hawaiians and Pacific Islanders, followed by Native Americans, who were 1.9 and 1.3 times more likely, respectively, to develop CRPS compared with White individuals. In 2007, de Mos et al found that individuals with Northern European ancestry were four times more likely to develop CRPS than people in the United States.4 However, their analysis compared rates from the Netherlands to a Minnesota-based study that reported lower CRPS rates than most other studies.4 Despite our inability to compare rates by geographical area, the elevated prevalence and incidence observed in Native Hawaiians/Pacific Islanders and Native Americans support prior evidence suggesting that genetic factors may contribute to CRPS susceptibility.10,41
The TriNetX data demonstrated that CRPS prevalence and incidence more than doubled from 2004–2008 to 2019–2023. Prior studies examining temporal trends have produced mixed results. In the United States, Murphy et al (2017) reported a similar rise in prevalence from 2000–2012 using retrospective analysis of the Truven MarketScan® Commercial and Medicare Supplemental database.42 In contrast, Bang et al (2020) observed a slight decline in prevalence between 2009–2013 using diagnostic codes from Korea’s National Health Insurance Service (NHIS).43 The cause of the increased rates of CRPS in our study is unclear. It is possible that population rates are rising, or the apparent increase may reflect evolving diagnostic criteria or a greater awareness among health-care providers.
Given the complex nature of CRPS, it is possible that the underlying mechanisms contributing to its development may overlap with those of other medical conditions. To explore these potential connections, we examined associations between CRPS and a set of selected conditions. We assessed whether these conditions were associated with the development of CRPS, and conversely, whether CRPS was associated with the development of these conditions. In the unrestricted cohorts, we found a strong association between the development of CRPS and autoimmune and inflammatory-related conditions such as rheumatoid arthritis, lupus erythematosus, and inflammatory bowel disease. When more controls were placed on the cohorts, these associations were no longer significant. In contrast, psychological factors (depression and anxiety), irritable bowel syndrome, insomnia, and nicotine use increased the risk of developing CRPS in both the unrestricted and restricted cohorts.
Individuals with CRPS were more likely to develop several other medical conditions. In the unrestricted cohorts, the highest relative likelihood was observed for developing lupus erythematosus (24-fold increase), while the lowest was for developing obesity (6-fold increase). When additional controls were applied to create more restricted cohorts, the magnitude of several associations changed: three increased, four decreased, two remained unchanged, and one condition could not be reported due to small sample size. Notably, the relative likelihood of depression, irritable bowel syndrome, and osteoporosis among individuals with CRPS increased from 13- to 24-fold, 13- to 15-fold, and 8- to 11-fold, respectively, in the restricted cohorts. These increases should be interpreted cautiously, as restriction-related selection effects, rather than reduced confounding, may partly account for the amplified estimates.
There is limited information in the literature describing associations between CRPS and other health conditions. However, several conditions have been consistently linked with chronic pain disorders. For example, numerous studies have demonstrated associations between chronic pain and psychological conditions such as stress, depression, and anxiety.44 In a systematic review, Aaron et al reported that approximately 40% of individuals with chronic pain experience anxiety and depression.20 Other research suggests that individuals with psychological conditions are more likely to develop chronic pain conditions.45,46 Similar to the TriNetX data, previous research has shown a bidirectional relationship between pain and psychological conditions in patients with CRPS.21,37 This association aligns with evidence suggesting that neurological mechanisms, such as central sensitization and altered pain processing, contribute to the development and the ongoing symptoms related to CRPS.
Consistent with the current findings, autoimmune and inflammatory conditions have also been found to be associated with chronic pain.23 Pardo et al identified rheumatoid arthritis and inflammatory bowel disease as risk factors for the development of fibromyalgia and chronic widespread pain.24 Likewise, Tang et al found that widespread pain was associated with an increased risk of rheumatoid arthritis and multiple sclerosis, although not with lupus erythematosus or inflammatory bowel disease.23 CRPS is thought to involve inflammatory and autoimmune mechanisms, which may help explain its association with other disorders that share similar underlying processes.
Interpretation of these findings should consider several limitations inherent to the study design and data source. The data were obtained from the TriNetX Global Collaborative Network and were based on International Classification of Diseases 2010 (ICD-10) codes. Reliance on diagnostic codes introduces the potential for misclassification, as coding accuracy depends on clinician documentation and correct code selection. Missing data within the network also limits interpretation of certain findings, as body region (upper or lower extremity) was not coded for 27.2% of cases, and laterality was missing for 37.4% of upper extremity cases and 28.9% of lower extremity cases. Variability in the diagnostic criteria of CRPS may also contribute to inaccuracies in the study. Although the Budapest Criteria are currently the most widely accepted, other criteria, such as the Harden and Bruehl criteria and the Veldman criteria, have also been used.47 Differences among these diagnostic standards may lead to heterogeneity in the populations identified as having CRPS. It is likely that a combination of these criteria informed the assignment of ICD-10 codes used within the TriNetX database, influencing our results.1,5,39 An additional limitation concerns the interpretation of temporal trends in CRPS prevalence and incidence. TriNetX is a continuously expanding federated network, having grown from 55 healthcare organizations across 7 countries in 2017 to 137 healthcare organizations across 17 countries by 2024.48 Because our 20-year study window spans a period of substantial network growth, the observed increase in prevalence and incidence from 2004 to 2023 may partly reflect this expansion, along with increased EHR adoption and evolving documentation practices, rather than a true rise in disease occurrence alone. While the use of large datasets helps to reduce type II errors, it raises the risk of detecting statistically significant associations that may not be meaningful. The retrospective nature of the database limits the ability to control for confounding variables. In this study, potential confounders were identified and controlled for based on prior literature and clinical experience; however, unmeasured or misidentified confounders may still have influenced the results. Additionally, detection bias may have influenced the reported associations because patients with CRPS typically require more frequent clinical contact, which increases the opportunity for incidental diagnosis of other conditions. The restricted analysis produced asymmetric shifts relative to the unrestricted cohorts: some associations were reduced, while others increased. The attenuated associations are consistent with reduced confounding; however, the increased associations may not be attributed to de-confounding. Excluding patients with a broad set of diagnoses may have introduced bias, leading to spurious increases in association. The restricted cohorts show that some associations persist independent of the excluded variables, but their strength may be inflated by the bias introduced by the controls. Future research using advanced analytic methods, such as machine learning, may help to more accurately identify and account for relevant confounding variables. Despite these limitations, the large sample size and use of matched control cohorts strengthen internal validity and suggest that the findings may be generalizable to comparable clinical populations.
In this large, retrospective cohort study using data from the TriNetX Global Collaborative Network, CRPS was found to affect approximately 0.06% of the population, with an incidence of 13.5 per 100,000 person-years. Consistent with prior research, CRPS occurred more frequently in females and peaked in midlife. Unlike many earlier studies, lower extremity involvement was more common than upper extremity involvement. Prevalence and incidence increased over the 20-year study period, which may reflect true population changes, heightened clinical recognition, or evolving diagnostic criteria. Our findings also highlight bidirectional associations between CRPS and several disorders, including psychological, inflammatory, and autoimmune conditions; however, the retrospective, observational design of this study precludes causal conclusions. These results suggest that clinicians may consider targeted screening for psychological, inflammatory, and autoimmune comorbidities in patients at higher likelihood of CRPS, and future research should evaluate whether multidisciplinary, early-intervention strategies can reduce symptom burden or improve long-term outcomes. The findings support a multifactorial conceptualization of CRPS that includes immune, neurologic, and psychosocial components, while underscoring the need for cautious interpretation of observational associations.
Acknowledgments
The authors would like to thank Karen Yang, SPT, for her valuable assistance with the pilot data for this study.
Funding Statement
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Institutional Review Board Approval
This study was approved by the SUNY Upstate Medical University Institutional Review Board.
Data
The data used in this study were obtained from the TriNetX Research Network, a third-party database containing de-identified patient information. All analysis was performed within the TriNetX platform, and these data cannot be shared publicly. Researchers may access similar data through TriNetX (https://trinetx.com) upon establishing a data use agreement with the provider.
Use of Artificial Intelligence
During the preparation of this work, the authors used OpenAI ChatGPT, GPT-4 to assist with grammar and wording of selected sections of this manuscript. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.
Disclosure
We affirm that we have no financial affiliation or involvement with any commercial organization that has a direct financial interest in any matter included in this manuscript.
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