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SN Comprehensive Clinical Medicine

, Volume 1, Issue 11, pp 882–890 | Cite as

Fibromyalgia and Myositis Linked to Higher Burden and Disability in Patients with Migraine

  • Urvish K. PatelEmail author
  • Preeti Malik
  • Richa Sheth
  • Princy Malhi
  • Amita Kapoor
  • Bakhtiar M. Rasul
  • Saleha Saiyed
  • Tapan Kavi
  • Ashish Kapoor
Medicine
  • 193 Downloads
Part of the following topical collections:
  1. Topical Collection on Medicine

Abstract

The increase in migraine frequency—with shift towards chronicity—promotes an enhancement of the central hypersensitivity which has been linked with fibromyalgia and myositis (FM). Migraine patients with FM have been known to have higher burden of headaches across studies, but this is the first population-based study to evaluate disability and morbidity in migraine patients with concurrent FM. We performed a retrospective cross-sectional analysis of migraine hospitalizations using the nationwide database to determine cost, hospital stay, disability, and discharge disposition. This analysis was performed in migraine patients with and without FM using ICD-9-CM codes. We performed weighted analyses using chi-square and t test. Among year 2014 hospitalizations, we identified FM patients and regression analysis was performed to evaluate whether migraine or other headache disorders were predictors of FM hospitalization. Between years 2003 and 2014, of the total 446,446 migraine hospitalizations, 22,735(5.09%) patients had concurrent FM. Migraine patients with FM had higher prevalence of loss of function (8.4% vs. 6.5%, p<0.0001) and transfer to rehabilitation facilities (5.5% vs. 4.5%, p<0.0001) compared to those without FM. Migraine patients with FM also had higher hospitalization stay and cost. Through regression analysis, we found that migraine (aOR, 3.03; p<0.0001), cluster headache (aOR, 1.71; p=0.0124), and tension headache (aOR, 1.87; p<0.0001) were highly associated with FM hospitalization. FM was associated with significant increase in disability, morbidity, hospitalization stay, and cost in patients admitted with migraine. On the basis of this study finding, it would be reasonable to screen migraine patients with depression, anxiety, or other psychiatric disorders for symptoms of FM to mitigate the burden.

Keywords

Migraine Fibromyalgia Myositis Disability Cluster headache Tension headache Nationwide inpatient sample 

Introduction

Migraines are a type of headache disorder, affecting 14% of the population, associated with debilitating pain, recurrent episodes, nausea, and sensitivity to light and sound [1]. FM is chronic musculoskeletal disorders characterized by widespread pain, tenderness, and fatigue, as well as cognitive dysfunction. The reported prevalence of fibromyalgia is 2.0 to 5.7% [1]. While the cause of FM remains unknown, it is hypothesized that central sensitization causes the persistence of musculoskeletal pain. Central sensitization involves a noxious stimulus that leads to permanent damage to nociceptive pathways [2]. Pain persistence in migraine may be due to central sensitization, indicating a possible cause of comorbidity between fibromyalgia and migraine [2]. In a study by Centonze et al., it is suggested that fibromyalgia and episodic migraine may be a continuum of the same disease [3]. FM has been shown to be associated with more severe headaches and poorer quality of life in migraine patients [4, 5, 6]. In this retrospective cross-sectional study, we hypothesized that concurrent FM among migraineurs is associated with higher disability and morbidity.

Primary objective of this study was to investigate if FM predicts disability and morbidity in the subset of large inpatient sample with 446,446 migraine hospitalizations. Secondary objective was to study whether migraine or other headache disorders predict FM hospitalizations.

Methods

Data was obtained from the Agency for Healthcare Research and Quality’s Healthcare Cost and Utilization Project (HCUP) NIS files between January 2003 and December 2014. The NIS is the largest publicly available all-payer inpatient care database in the USA and contains discharge-level data provided by states that participate in the HCUP (including a total of 46 in 2011). This administrative dataset contains data on approximately 8 million hospitalizations in 1000 hospitals that were chosen to approximate a 20% stratified sample of all US community hospitals, representing more than 95% of the national population. Criteria used for stratified sampling of hospitals into the NIS include hospital ownership, patient volume, teaching status, urban or rural location, and geographic region. Discharge weights are provided for each patient discharge record, which allow extrapolation to obtain national estimates. Each hospitalization is treated as an individual entry in the database and is coded with one principal diagnosis, up to 24 secondary diagnoses, and 15 procedural diagnoses associated with that stay. Detailed information on NIS is available at http://www.hcup-us.ahrq.gov/db/nation/nis/nisdde.jsp

Study Population

We used the 9th revision of the International Classification of Diseases, clinical modification code (ICD-9-CM) to identify adult patients admitted to hospital with a primary diagnosis of migraine (ICD-9-CM code 346). Similarly, patients with fibromyalgia and myositis were identified as secondary diagnosis associated with migraine using ICD-9-CM code 729.1. Age <18 years and admissions with missing data for age, gender, and race were excluded. The sample size was based on the available data. We used ICD-9-CM codes to identify patients with Cluster Headache 339.0 and Tension Type Headache 339.1 or 307.81.

Patient and Hospital Characteristics

Patient characteristics of interest were age, gender, race, insurance status, and concomitant diagnoses as defined above. Race was defined by white (referent), African American, Hispanic, Asian or Pacific Islander, and Native American. Insurance status was defined by Medicare (referent), Medicaid, Private Insurance, and Other/Self-pay/No charge. We defined the severity of comorbid conditions using Deyo’s modification of the Charlson’s Comorbidity Index (Supplementary Table 1). Facilities were considered to be teaching hospitals if they have an American Medical Association-approved residency program, are a member of the Council of Teaching Hospitals, or have a full-time equivalent interns and residents to patient’s ratio of ≥0.25. HCUP NIS contains data on total charges for each hospital in the databases, which represents the amount that hospitals billed for services.

Outcomes

We tried to find out disability, morbidity, length of stay (LoS), and cost of hospitalization associated with FM among migraine hospitalizations (years 2003–2014). The comparison of disability/loss of function was investigated by All Patient Refined Diagnosis Related Groups (APR-DRGs) severity between patients with FM and patients without FM. APR-DRGs were assigned using software developed by 3M Health Information Systems, where score 1 indicates minor loss of function, 2 moderate, 3 major, and 4 extreme loss of function. Morbidity was defined as length of stay ≥7 days (≥95 percentile or +1.5 SD) and discharge other than home (short-term hospital, skilled nursing facility, intermediate care facility).

Our secondary outcome of interest was to evaluate whether headache disorders worsen FM which leads to FM-related hospitalization among January 2014–December 2014 US hospitalizations. The reason to choose only year 2014 data for secondary outcome was the large number of US hospitalizations (more than 20 million) each year to evaluate patients with and without FM and headache disorders.

Statistical Analysis

All statistical analyses were performed using the weighted survey methods in SAS (version 9.4). Weighted values of patient-level observations were generated to produce a nationally representative estimate of the entire US population of hospitalized patients. A p value of <0.05 was considered significant. Univariate analysis of differences between categorical variables was tested using the chi-square test and analysis of differences between continuous variables (length of stay and cost of hospitalization) was tested using paired Student’s t test. Mixed-effects survey logistic regression models with weighted analysis were used for the categorical dependent variables, including migraine and outcomes of interest, in order to estimate odds ratio (OR) and 95% confidence interval for the association between headache disorders (migraine, cluster headache, tension headache) and migraine in year 2014 cohort.

We included demographics (age, gender, race), patient-level hospitalization variables (admission day, primary payer, admission type, Median Household Income Category), hospital-level variables (hospital region, teaching versus non-teaching hospital, hospital bed size), comorbidities like hypertension, diabetes mellitus, hypercholesterolemia, obesity, smoking status, drug abuse, alcohol abuse, depression, generalized anxiety disorders, other psychiatric disorders, and Charlson’s Comorbidity Index (CCI).

For each model, C-index (a measure of goodness of fit for binary outcomes in a logistic regression model) was calculated. All statistical tests used were two-sided, and p<0.05 was deemed statistically significant. No statistical power calculation was conducted prior to the study.

Results

Disease Hospitalizations

We found a total of 596,231 hospitalizations (446,446: weighted-after removing missing data for age, gender and ethnicity) due to migraine from year 2003 to 2014 after excluding patients with age <18 years and admissions with missing data for age, gender, and ethnicity (Fig. 1). Out of 446,446 migraine hospitalizations, 22,735 (5.09%) had FM and 423,711 (94.91%) had no FM.
Fig. 1

Flowchart detailing cohort selection and analysis modeling

Prevalence Trends

We analyzed trends of FM in migraine hospitalizations. As shown in Fig. 2, trends of FM were increasing from 2003 to 2014. (FM, 3.02% in 2003 to 6.91% in 2014; P-Trend<0.0001).
Fig. 2

Yearly prevalence of fibromyalgia and myositis among migraine patients

Demographics, Patient and Hospital Characteristics, and Comorbidities

FM was more in common in 35–65 years of age group. Migraine hospitalizations with FM were more likely to be in female (96.27% vs. 79.68%, p<0.0001), white (82.02% vs. 73.23%, p< 0.0001), had private insurance (49.47% vs. 54.76%, p<0.0001), and elective admissions (12.45% vs. 9.71%, p<0.0001) than those with absent FM. Comorbidities like depression, generalized anxiety disorder, other psychiatric disorders and neurological disorders, arthritis, diabetes, hypertension, obesity, drug abuse, and current or past tobacco consumption were higher among FM patients than those without FM. Overall, hospitalizations with FM also have a high percentage of CCI (Deyo’s Charlson’s Comorbidity) Index (Table 1).
Table 1

Characteristics of fibromyalgia and myositis (FM) patients in migraine hospitalizations

 

FM

Non-FM

Total

p value

Migraine weighted (%)

22,735 (5.09)

423,711 (94.91)

446,446 (100)

<0.0001

Demographics of patients

  Age group (years)

 

<0.0001

    18–34

3654 (16.07)

113,726 (26.84)

117,379 (26.29)

 

    35–49

10,379 (45.65)

173,678 (40.99)

184,057 (41.23)

 

    50–64

7365 (32.4)

100,318 (23.68)

107,683 (24.12)

 

    65–79

1229 (5.41)

28,787 (6.79)

30,016 (6.72)

 

   ≥80

108 (0.47)

7202 (1.70)

7310 (1.64)

 

  Gender (%)

 

<0.0001

    Male

849 (3.73)

86,095 (20.32)

86,943 (19.47)

 

    Female

21,886 (96.27)

337,612 (79.68)

359,497 (80.53)

 

  Race (%)

 

<0.0001

    White

18,235 (82.02)

301,256 (73.23)

319,491 (73.69)

 

    African American

2290 (10.30)

60,837 (14.79)

63,127 (14.56)

 

    Hispanic

1461 (6.57)

42,271 (10.28)

43,732 (10.09)

 

    Asian or Pacific Islander

101 (0.45)

4848 (1.48)

4949 (1.14)

 

    Native American

145 (0.65)

2145 (0.52)

2290 (0.53)

 

Characteristics of patients

  Median household income category for patient’s zip code (%)

 

<0.0001

    0–25th percentile

5368 (24.08)

107,876 (26.05)

113,244 (25.95)

 

    26–50th percentile

6161 (27.63)

102,939 (24.86)

109,100 (25)

 

    51–75th percentile

5887 (26.4)

105,658 (25.51)

111,545 (25.56)

 

    76–100th percentile

4880 (21.89)

97,630 (23.58)

102,510 (23.49)

 

  Primary payer (%)

 

<0.0001

    Medicare

6318 (27.83)

74,074 (17.51)

80,392 (18.04)

 

    Medicaid

3310 (14.58)

63,888 (15.1)

67,198 (15.08)

 

    Private insurance

11,229 (49.47)

231,675 (54.76)

242,904 (54.49)

 

    Other/self-pay/no charge

1843 (8.12)

53,399 (12.62)

55,242 (12.39)

 

  Admission type (%)

 

<0.0001

    Non-elective

19,833 (87.55)

381,596 (90.29)

401,429 (90.15)

 

    Elective

2820 (12.45)

41,041 (9.71)

43,861 (9.85)

 

  Admission day (%)

 

0.2202

    Weekday

18,115 (79.68)

336,177 (79.34)

354,291 (79.36)

 

    Weekend

4620 (20.32)

87,534 (20.66)

92,154 (20.64)

 

Characteristics of hospitals

  Bed size of hospital (%)*

 

<0.0001

    Small

2855 (12.65)

46,919 (11.13)

49,775 (11.2)

 

    Medium

5739 (25.43)

103,335 (24.51)

109,073 (24.55)

 

    Large

13,971 (61.91)

271,425 (64.37)

285,397 (64.24)

 

  Hospital location and teaching status (%)

 

0.0001

    Rural

2086 (9.24)

37,213 (8.82)

39,299 (8.85)

 

    Urban non-teaching

9577 (42.44)

174,699 (41.43)

184,275 (41.48)

 

    Urban teaching

10,903 (48.32)

209,768 (49.75)

220,670 (49.67)

 

  Hospital region (%)

 

<0.0001

    Northeast

3874 (17.04)

96,850 (22.86)

100,724 (22.56)

 

    Midwest

5747 (25.28)

79,810 (18.84)

85,557 (19.16)

 

    South

9423 (41.45)

184,610 (43.57)

194,032 (43.46)

 

    West

3691 (16.23)

62,442 (14.74)

66,132 (14.81)

 

Comorbidities of patients (%)

  Arthritis

3085 (13.64)

12,422 (2.95)

15,507 (3.5)

<0.0001

  Depression

7960 (35.19)

81,744 (19.42)

89,704 (20.23)

<0.0001

  Generalized anxiety disorder

380 (1.67)

3393 (0.80)

3773 (0.85)

<0.0001

  Psychiatric disorder

3290 (14.54)

30,019 (7.13)

33,309 (7.51)

<0.0001

  Other neurological disorder

≤10 (0.04)

143 (0.03)

153 (0.03)

0.4746

  Diabetes

3192 (14.04)

54,125 (12.77)

57,317 (12.84)

<0.0001

  Hypertension

8758 (38.52)

153,821 (36.30)

162,579 (36.42)

<0.0001

  Obesity

3424 (15.06)

45,480 (10.73)

48,904 (10.95)

<0.0001

  Hypercholesterolemia

1127 (4.95)

21,236 (5.01)

22,363 (5.01)

0.6997

  Drug abuse

1408 (6.19)

17,240 (4.07)

18,648 (4.18)

<0.0001

  Alcohol abuse

136 (0.6)

5520 (1.3)

5656 (1.27)

<0.0001

  Current or past smoker

4972 (21.87)

86,819 (20.49)

91,791 (20.56)

<0.0001

  Acquired immunodeficiency syndrome (AIDS)

49 (0.21)

1703 (0.4)

1752 (0.39)

<0.0001

  Deyo’s Charlson’s Comorbidity Index (CCI)

 

<0.0001

    0

12,517 (55.06)

280,395 (66.18)

292,912 (65.61)

 

    1

6630 (29.16)

92,655 (21.87)

99,285 (22.24)

 

    2

2252 (9.9)

31,895 (7.53)

34,147 (7.65)

 

    3

852 (3.75)

10,536 (2.49)

11,387 (2.55)

 

    4

301 (1.32)

3611 (0.85)

3912 (0.88)

 

   ≥5

183 (0.81)

4619 (1.09)

4801 (1.08)

 

Percentage in brackets are column % indicates direct comparison between FM vs. non-FM among migraineurs

*Bed size of hospital indicates number of hospital beds which varies depending on hospital location (rural/urban), teaching status (teaching/non-teaching) and region (northeast/midwest/southern/western)

The Outcomes

Table 2 has mentioned outcomes of FM among migraine hospitalizations. Outcomes were disability/loss of function, morbidity (length of stay ≥7 days [≥ 95 percentile] and discharge other than home), discharge disposition (home vs. non-home [short-term hospital, skilled nursing/intermediate care facility, home health care]), cost of hospitalization, and length of stay.
Table 2

Univariate analysis of outcomes fibromyalgia and myositis (FM) among migraine hospitalizations

 

FM

Non-FM

Total

p value

APR-DRG severity or disability/loss of function (%)

   

<0.0001

  Minor loss of function

9133 (40.38)

210,664 (50.07)

219,797 (49.58)

 

  Moderate loss of function

1591 (51.25)

182,861 (43.46)

194,452 (43.86)

 

  Major loss of function

1810 (8)

26,257 (6.24)

28,067 (6.33)

 

  Severe loss of function

84 (0.37)

958 (0.23)

1042 (0.23)

 

  Total major/severe loss of function (%)

1894 (8.37)

27,215 (6.47)

29,109 (6.56)

 

Morbidity* (%)

222 (0.97)

2199 (0.52)

2420 (0.54)

<0.0001

Discharge disposition (%)

   

<0.0001

  Routine/home

21,216 (94.5)

399,178 (95.54)

420,395 (95.49)

 

  Transfer to short-term hospital

109 (0.48)

2255 (0.54)

2364 (0.54)

 

  Transfer to SNF/ICF/another type of facility

305 (1.36)

5805 (1.39)

6110 (1.39)

 

  Home health care

821 (3.66)

10,573 (2.53)

11,393 (2.59)

 

  Total discharge other than home (%)

1235 (5.50)

18,633 (4.46)

19,868 (4.52)

 

Length of stay ± SE (days)

3.4±0.043

2.8±0.008

 

<0.0001

Cost of hospitalization ± SE ($)

20,174±273.2

18,092±55.9

 

<0.0001

Percentage in brackets are column % indicates direct comparison between FM vs. non-FM among migraineurs

APR-DRG All Patients Refined Diagnosis-Related Groups, SNF skilled nursing facility, ICF intermediate care facility, SE standard error

*Morbidity: length of stay ≥7 days (≥95 percentile or +1.5 SD) and discharge other than home

The prevalence of moderate, major, and severe disability was higher among FM patients. An overall prevalence of major/severe loss of function was 8.37% in FM compared to patients without FM (6.47%) among migraineurs (p<0.0001). The morbidity was higher in FM patients (0.97% vs 0.52%, p<0.0001) than patients without FM. A total of 94.5% of FM patients had been discharged to home compared to 95.54% of patients with no FM (p<0.0001). Overall, patients with FM had higher prevalence of discharge other than home discharges (short-term hospital, skilled nursing/intermediate care facility, home health care) compared to those with no FM (5.50% vs. 4.46%, p<0.0001). Mean length of stay (3.4 days vs. 2.79 days, p<0.001) and total cost of hospitalization ($20,174 vs. $18,092, p<0.001) were higher in FM patients (Table 2).

Regression Model Derivation

Among year 2014 of total 28,212,820 hospitalizations, we had considered 26,614,100 patients after excluding age <18 years and admissions with missing data for age, gender, and race. Out of which 411,835 (1.55%) patients had FM. Among this population, we looked for concurrent headache disorders and other comorbidities which could predict the FM hospitalizations.

In the multivariate regression analysis, after adjusting for basic demographic with patient and hospital-level variables, comorbidities, concurrent conditions, and CCI, patients with migraine (adjusted OR, 3.03; 95% CI, 2.95–3.12; p<0.0001), cluster headache (adjusted OR, 1.71; 95% CI, 1.12–2.59; p=0.0124), and tension headache (adjusted OR, 1.87; 95% CI, 1.21–2.89; p<0.0001) were at higher risk of having hospitalizations due to FM than non-headache disorders (Table 3).
Table 3

Multivariate logistic regression analysis to predict the fibromyalgia and myositis hospitalization due to headache disorders

 

Odds ratio (OR)

Confidence interval (CI)

p value

 

LL

UL

 

No-Headache

Reference

 Migraine

3.03

2.95

3.12

<0.0001

 Cluster headache

1.71

1.12

2.59

0.0124

 Tension headache

1.87

1.21

2.89

0.0048

Age (every 10 years)

0.99

0.99

0.99

<0.0001

Gender

 Female

Reference

 Male

0.21

0.20

0.21

<0.0001

Race

 White

Reference

 African American

0.58

0.57

0.60

<0.0001

 Hispanic

0.63

0.61

0.64

<0.0001

 Asian or Pacific Islander

0.33

0.30

0.36

<0.0001

 Native American

0.81

0.74

0.89

<0.0001

Median household income category for patient’s zip code

 0–25th percentile

Reference

 26-50th percentile

1.01

0.99

1.03

0.4473

 51–75th percentile

0.96

0.94

0.98

<0.0001

 76–100th percentile

0.88

0.86

0.90

<0.0001

Primary payer

 Medicare

Reference

 Medicaid

0.69

0.68

0.71

<0.0001

 Private insurance

0.83

0.81

0.85

<0.0001

 Other/self-pay/no charge

0.74

0.71

0.76

<0.0001

Admission type

 Non-elective

Reference

  Elective

0.92

0.91

0.94

<0.0001

Admission day

 Weekday

Reference

 Weekend

0.94

0.93

0.96

<0.0001

Bed size of hospital

 Small

Reference

  Medium

0.97

0.95

0.99

0.0035

 Large

0.97

0.95

0.99

0.0007

Hospital location and teaching status

 Rural

Reference

 Urban non-teaching

1.06

1.03

1.09

<0.0001

 Urban teaching

1.07

1.04

1.10

<0.0001

Hospital region

 Northeast

Reference

 Midwest

1.32

1.29

1.35

<0.0001

 South

1.21

1.18

1.23

<0.0001

 West

1.28

1.25

1.32

<0.0001

Comorbidities of patients

 Arthritis

4.72

4.61

4.82

<0.0001

 Depression

2.31

2.28

2.35

<0.0001

 Generalized anxiety disorder

1.54

1.46

1.63

<0.0001

 Other psychiatric disorder

1.65

1.60

1.69

<0.0001

 Other neurological disorder

1.31

1.28

1.34

<0.0001

 Diabetes

1.15

1.12

1.17

<0.0001

 Hypertension

1.23

1.20

1.25

<0.0001

 Obesity

1.54

1.52

1.57

<0.0001

 Hypercholesterolemia

1.12

1.08

1.15

<0.0001

 Drug abuse

1.67

1.62

1.72

<0.0001

 Alcohol abuse

0.74

0.71

0.77

<0.0001

 Current or past smoker

1.30

1.27

1.32

<0.0001

 Acquired immunodeficiency syndrome (AIDS)

1.41

1.20

1.65

<0.0001

Deyo’s Charlson’s Comorbidity Index (CCI)

 1

Reference

 0

1.24

1.21

1.27

<0.0001

 2

1.11

1.08

1.15

<0.0001

 3

1.00

0.96

1.03

0.8641

 4

0.86

0.82

0.90

<0.0001

 ≥5

0.74

0.71

0.78

<0.0001

Area under the ROC curve/c-index

0.799

The model is adjusted for basic demographic with patient-level variables, comorbidities, CCI, concurrent conditions, and hospital-level variables such as hospital region, teaching status, and bed size

UL upper limit, LL lower limit

Table 3 also lists multivariate analysis of other predictors of FM. Comorbidities like arthritis (adjusted OR, 4.72; 95% CI, 4.61–4.82; p<0.0001), depression (adjusted OR, 2.31; 95% CI, 2.38–2.35; p<0.0001), generalized anxiety disorder (adjusted OR, 1.54; 95% CI, 1.46–1.63; p<0.0001), other psychiatric disorders (adjusted OR, 1.65; 95% CI, 1.60–1.69; p<0.0001), and other neurologic disorders (adjusted OR, 1.31; 95% CI, 1.28–1.34; p<0.0001) were significant predictors of FM hospitalizations.

Concurrent conditions like drug abuse/dependence (adjusted OR, 1.67; 95% CI, 1.62–1.72; p<0.0001), obesity (adjusted OR, 1.54; 95% CI, 1.52–1.57; p<0.0001), hypercholesterolemia (adjusted OR, 1.12; 95% CI, 1.08–1.15; p<0.0001), acquired immunodeficiency syndrome (adjusted OR, 1.41; 95% CI, 1.20–1.65; p<0.0001), current or past smoker (adjusted OR, 1.30; 95% CI, 1.27–1.32; p<0.0001), diabetes (adjusted OR, 1.15; 95% CI, 1.12–1.17; p<0.0001), and hypertension (adjusted OR, 1.23; 95% CI, 1.20–1.25; p<0.0001) were also significantly associated with FM-related hospitalization.

Accuracy of the Model

c-statistic was 0.799 which is used to validate the accuracy of the regressions. Adjusted model has c-index >0.7, which indicates a good model.

Discussion

The major finding from our study is high prevalence of FM in patients with migraine hospitalizations. Despite of different origin of pain, both FM and migraine are comorbidities due to central sensitization phenomenon [7]. Response to somatic hyperalgesia was enhanced by concurrent fibromyalgia and migraine than one condition alone. Higher migraine frequency and/or chronicity provokes hyperalgesia and fibromyalgia pain, which is reversed by effective migraine prophylaxis according to Giamberardino et al. [8]. Several studies have reported high prevalence of fibromyalgia in migraineurs [9, 10, 11, 12, 13]. A retrospective cohort study, fibromyalgia in migraine, by Whealy et al., found that patients with comorbid FM and migraine reported higher average headache intensity and severity than their age and sex-matched controls, who had migraine alone [4]. This reflects the findings of other studies, that in patients with FM, headaches are more likely to be rated as incapacitating, as compared to patients without FM [5]. While the Marcus et al. study found that there is not a significant difference in pain and cognitive distress between FM patients with migraine and FM patients without migraine, 76% of the FM patients seeking treatment suffered from chronic headache, indicating that headaches should be screened for in FM patients [14].

FM is associated with low quality of life in patients with migraine [9, 10]. A study by Beyazal et al. found that in migraine patients, FM comorbidity showed a significant impact on the patients’ quality of life. Those with FM had more frequent migraines, significantly higher mean widespread pain scores, and lower quality of life scores [6]. Our study corroborates previous findings by showing high prevalence of major/severe loss of function in migraine patient with FM as compared to those without FM (p<0.0001). We also found that migraineurs with FM had higher rates of discharge dispositions other than home, higher length of stay, and higher cost of hospitalizations than migraineurs without FM.

Similar to previous studies we also found a significantly higher prevalence of migraine and FM in females as compared to males [12, 15, 16]. Total 96.27% patients were females for migraine with FM and 79.68% were females for migraine without FM. In 2006, Aloisi et al. reported the different expression of pain between sexes is due to interaction between sex hormones, brain functions, and processing of pain [17]. We found increased prevalence of depression, generalized anxiety disorder, and other psychiatric disorders in migraine patient compared to those without FM similar to prior studies [9, 10, 12, 13]. Decreased pain habituation is common in migraine and FM and may lead to central sensitization and myofascial pain persistence in the presence of other favorable situations, such as depression, sleep disturbances, and anxiety [13]. Mongini et al. [18] have reported that the presence of anxiety alone or combined with depression significantly increase the level of muscle tenderness in the head and more in the neck might facilitate into chronic headache forms such as migraine. Similarly, anxiety may also increase FM and diffuse myofascial pain comorbidity in headache patients who present with increased pericranial muscle tenderness. Whealy et al. concluded that concurrent migraine and fibromyalgia patients have severe depressive symptoms, higher headache intensity, and severe headache-related disability; thus, migraineur should be evaluated for fibromyalgia especially with depressive symptoms, high headache intensity, or high headache-related disability [4]. According to Costantini et al., visceral pain due to comorbid irritable bowel syndrome, primary dysmenorrhea, endometriosis, and colon diverticulosis triggers fibromyalgia pain and hyperalgesia in female patients probably due to enhancing the level of central sensitization which decreases significantly after treatment. In such patients, an assessment and treatment of visceral pain comorbidities should be a part of management strategy [19].

Screening for FM in patients with migraine hospitalizations may be helpful in identifying this under-recognized comorbidity. Treatment of FM with cognitive behavioral therapy, exercise, and drug therapy may help improve outcomes in migraine patients as well because of high impact of FM on disability and quality of life in these patients. On basis of central sensitization phenomenon, Yilmaz et al. had evaluated the efficacy of greater occipital nerve blockage in patients with concurrent migraine and fibromyalgia and found it reduces pain severity, headache frequency, duration, and increases quality of life [20].

A major strength of the study was that findings were nationally representative for the USA. NIS data is a largest inpatient database, and our study has good statistical power. APR-DRG coding system used in this study to assess the severity of illness is external validated. It is a reliable method with accurate and consistent results and is widely used by hospitals, consumers, payers, and regulators [21, 22]. However, there are limitations to the study. Since this is an inpatient population-based study, there might be underreporting of concurrent prevalence as all migraine and FM patients are not hospitalized and managed as outpatients. ICD-9-CM code recognizes fibromyalgia and myositis as a combined code so burden of individual diseases cannot be established. Data from clinical registries are obtained retrospectively by chart abstractions based on the discharge diagnosis codes, billing codes, etc. and hence susceptible to coding errors. In such cross-sectional study, it is difficult to identify temporal relationship between FM and headache disorder.

Conclusion

The conclusion derived from the study data is the understanding of the significant association of FM with migraine and other headache disorders and its role in increasing burden of disability, morbidity, LOS, and cost of hospitalization among migraineurs. The evaluation of FM comorbidity in different types of chronic headache subtype patients may increase the knowledge about chronicization mechanism and central sensitization phenomenon. Our findings suggest the importance of screening for FM in migraine and other headache disorders due to significant impact of FM on quality of life. This will also help in creating the optimal individual treatment plan. On the basis of this study finding, it would also be reasonable to screen migraine patient with depression, anxiety, or other psychiatric disorders for symptoms of FM.

Notes

Authors’ Contributions

U.P. and P.M. conceive of the idea and performed biostatistics and analysis. R.S. and P.M. wrote the manuscript with support from A.K., B.R., and S.S. who contributed to the literature review, tables, figure, and citation. A.K. and T.K. supervised the project.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that there is no conflict of interest.

Informed Consent

The data has been taken from Nationwide Inpatient Sample, which is a deidentified database from “Health Care Utilization Project (HCUP)” sponsored by the Agency for Healthcare Research and Quality, so informed consent or IRB approval was not needed for the study. The relevant ethical oversight and HCUP Data Use Agreement (HCUP-4Q28K90CU) were obtained for the study.

Supplementary material

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References

  1. 1.
    Wolfe F, Ross K, Anderson J, Russell IJ, Hebert L. The prevalence and characteristics of fibromyalgia in the general population. Arthritis Rheum. 1995;38(1):19–28.CrossRefGoogle Scholar
  2. 2.
    de Tommaso M. Prevalence, clinical features and potential therapies for fibromyalgia in primary headaches. Expert Rev Neurother. 2012;12(3):287–95; quiz 296.  https://doi.org/10.1586/ern.11.190.CrossRefPubMedGoogle Scholar
  3. 3.
    Centonze V, Bassi A, Cassiano MA, Munno I, Dalfino L, Causarano V. Migraine, daily chronic headache and fibromyalgia in the same patient: an evolutive "continuum" of non organic chronic pain? About 100 clinical cases. Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology. 2004;25(Suppl 3):S291–2.  https://doi.org/10.1007/s10072-004-0314-4.CrossRefGoogle Scholar
  4. 4.
    Whealy M, Nanda S, Vincent A, Mandrekar J, Cutrer FM. Fibromyalgia in migraine: a retrospective cohort study. J Headache Pain. 2018;19(1):61.  https://doi.org/10.1186/s10194-018-0892-9.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Peres MF, Young WB, Kaup AO, Zukerman E, Silberstein SD. Fibromyalgia is common in patients with transformed migraine. Neurology. 2001;57(7):1326–8.  https://doi.org/10.1212/wnl.57.7.1326.CrossRefPubMedGoogle Scholar
  6. 6.
    Beyazal MS, Tufekci A, Kirbas S, Topaloglu MS. The impact of fibromyalgia on disability, anxiety, depression, sleep disturbance, and quality of life in patients with migraine. Noro Psikiyatri Arsivi. 2018;55(2):140–5.  https://doi.org/10.5152/npa.2016.12691.CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Fitzcharles MA, Yunus MB. The clinical concept of fibromyalgia as a changing paradigm in the past 20 years. Pain Res Treat. 2012;2012:184835–8.  https://doi.org/10.1155/2012/184835.CrossRefPubMedGoogle Scholar
  8. 8.
    Giamberardino MA, Affaitati G, Martelletti P, Tana C, Negro A, Lapenna D, et al. Impact of migraine on fibromyalgia symptoms. J Headache Pain. 2015;17:28.  https://doi.org/10.1186/s10194-016-0619-8.CrossRefPubMedGoogle Scholar
  9. 9.
    Ifergane G, Buskila D, Simiseshvely N, Zeev K, Cohen H. Prevalence of fibromyalgia syndrome in migraine patients. Cephalalgia : an international journal of headache. 2006;26(4):451–6.  https://doi.org/10.1111/j.1468-2982.2005.01060.x.CrossRefGoogle Scholar
  10. 10.
    Kucuksen S, Genc E, Yilmaz H, Salli A, Gezer IA, Karahan AY, et al. The prevalence of fibromyalgia and its relation with headache characteristics in episodic migraine. Clin Rheumatol. 2013;32(7):983–90.  https://doi.org/10.1007/s10067-013-2218-2.CrossRefPubMedGoogle Scholar
  11. 11.
    Marcus DA, Bhowmick A. Fibromyalgia comorbidity in a community sample of adults with migraine. Clin Rheumatol. 2013;32(10):1553–6.  https://doi.org/10.1007/s10067-013-2310-7.CrossRefPubMedGoogle Scholar
  12. 12.
    de Tommaso M, Sardaro M, Serpino C, Costantini F, Vecchio E, Prudenzano MP, et al. Fibromyalgia comorbidity in primary headaches. Cephalalgia : an international journal of headache. 2009;29(4):453–64.  https://doi.org/10.1111/j.1468-2982.2008.01754.x.CrossRefGoogle Scholar
  13. 13.
    de Tommaso M, Federici A, Serpino C, Vecchio E, Franco G, Sardaro M, et al. Clinical features of headache patients with fibromyalgia comorbidity. J Headache Pain. 2011;12(6):629–38.  https://doi.org/10.1007/s10194-011-0377-6.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Marcus DA, Bernstein C, Rudy TE. Fibromyalgia and headache: an epidemiological study supporting migraine as part of the fibromyalgia syndrome. Clin Rheumatol. 2005;24(6):595–601.  https://doi.org/10.1007/s10067-005-1121-x.CrossRefPubMedGoogle Scholar
  15. 15.
    Wolfe F. Fibromyalgia: the clinical syndrome. Rheum Dis Clin N Am. 1989;15(1):1–18.Google Scholar
  16. 16.
    MacGregor EA. Oestrogen and attacks of migraine with and without aura. Lancet Neurol. 2004;3(6):354–61.  https://doi.org/10.1016/s1474-4422(04)00768-9.CrossRefPubMedGoogle Scholar
  17. 17.
    Aloisi AM, Bonifazi M. Sex hormones, central nervous system and pain. Horm Behav. 2006;50(1):1–7.  https://doi.org/10.1016/j.yhbeh.2005.12.002.CrossRefPubMedGoogle Scholar
  18. 18.
    Mongini F, Deregibus A, Rota E. Psychiatric disorders and muscle tenderness in episodic and chronic migraine. Expert Rev Neurother. 2005;5(5):635–42.  https://doi.org/10.1586/14737175.5.5.635.CrossRefPubMedGoogle Scholar
  19. 19.
    Costantini R, Affaitati G, Wesselmann U, Czakanski P, Giamberardino MA. Visceral pain as a triggering factor for fibromyalgia symptoms in comorbid patients. Pain. 2017;158(10):1925–37.  https://doi.org/10.1097/j.pain.0000000000000992.CrossRefPubMedGoogle Scholar
  20. 20.
    Yilmaz V, Aras B, Erturk FA, Cakci FA, Umay E. Migraine in patients with fibromyalgia and outcomes of greater occipital nerve blockage. Clin Neurol Neurosurg. 2019;181:54–7.  https://doi.org/10.1016/j.clineuro.2019.04.004.CrossRefPubMedGoogle Scholar
  21. 21.
    McCormick PJ, Lin HM, Deiner SG, Levin MA. Validation of the all patient refined diagnosis related group (APR-DRG) risk of mortality and severity of illness modifiers as a measure of perioperative risk. J Med Syst. 2018;42(5):81.  https://doi.org/10.1007/s10916-018-0936-3.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Baram D, Daroowalla F, Garcia R, Zhang G, Chen JJ, Healy E, et al. Use of the all patient refined-diagnosis related group (APR-DRG) risk of mortality score as a severity adjustor in the medical ICU. Clin Med Circ Respirat Pulm Med. 2008;2:19–25.PubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Neurology & Public HealthIcahn School of Medicine at Mount SinaiNew YorkUSA
  2. 2.Department of Public HealthIcahn School of Medicine at Mount SinaiNew YorkUSA
  3. 3.Department of Internal MedicineAlbert Einstein College of MedicineNew YorkUSA
  4. 4.Department of Internal Medicine, CarePoint HealthBayonne Medical CenterBayonneUSA
  5. 5.Department of NeurologyCooper Medical School of Rowan UniversityCamdenUSA
  6. 6.Department of Neurology, Jersey City Medical Center-RWJ Barnabas Health & BayonneMedical Center-CarePoint HealthBayonneUSA

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