Psychiatric Comorbidities in Women Veterans with Epilepsy

Abstract

Background:

Women Veterans with epilepsy (WVE) may have unique psychiatric comorbidities that affect presentation, treatment, and outcomes. This large, nationally representative study of Veterans Health Administration (VHA) patients explores sex differences in psychiatric diagnoses and treatment to better characterize WVE.

Methods:

This study included a retrospective cohort design utilizing VHA Corporate Data Warehouse administrative data. Data from 58,525 Veterans with epilepsy (8.5% women) were obtained. Psychiatric diagnoses and treatment were analyzed, with comparisons between men with epilepsy and WVE. Secondary analyses included further exploration of select gynecological conditions.

Results:

WVE had higher psychiatric burden than men, as evidenced by higher rates of nearly all psychiatric diagnoses, including depression (59.1% vs. 38.9%; χ ² = 771.6), posttraumatic stress disorder (42.0% vs. 26.5%; χ ² = 549.1), and anxiety disorder (44.9% vs. 24.5%; χ ² = 977.7), as well as higher use of psychotropic medication prescriptions (2.3 vs. 1.4 average number of psychotropics prescribed). Furthermore, higher percentages of women versus men utilized the emergency room for psychiatric purposes (11.7% vs. 6.9%; χ ² = 153.06) and were hospitalized with psychiatric diagnoses (9.8% vs. 6.1%; χ ² = 100.95).

Discussion:

Veterans with epilepsy represent a unique group with high rates of psychiatric comorbidity. These results suggest that among Veterans, men and women with epilepsy have differing psychiatric comorbidities, leading to disparate health care needs. Based on this study's findings, WVE may require a different approach to care with an increased focus on specialized psychiatric treatment for WVE.

Introduction

Women with epilepsy represent a unique group warranting special consideration. Compared to men, women with epilepsy are at risk for multiple psychiatric comorbidities,^1,2 specific medical conditions (e.g., migraine),³ catamenial exacerbation,⁴ interactions between contraception and antiseizure medication (ASM),⁵ pregnancy complications,⁶ gynecological and hormonal factors, and teratogenic risk of ASM exposure.⁷

Given these considerations, literature has begun to explore the nosology and presentation of women with epilepsy to better inform identification and treatment practices. While current studies provide a basis for understanding this clinical population, much of the existing literature is limited in scope and falls short of capturing the full clinical picture of epilepsy in women across multiple psychiatric variables. For example, while a few prospective studies have focused on psychiatric comorbidity, results are based on small sample sizes and highlight limited domains of psychiatric functioning, most notably depression and anxiety.^1,8,9

Within the larger population of women with epilepsy, women Veterans represent a distinct cohort with higher incidence and unique types of psychological trauma.¹⁰ In addition, given that seizures are an exclusionary diagnosis for entering the military, acquired epilepsy (e.g., subsequent to neurological conditions such as traumatic brain injury) is overrepresented in Veterans.¹¹ These complexities associated with epilepsy in women Veterans emphasize a critical need for research identifying key factors related to disease burden, treatment, and prevention strategies to ensure optimal quality of life within this population. In previous work, our research group examined utilization of epilepsy services in women Veterans with epilepsy (WVE) within the Veterans Health Administration (VHA).¹² While that study provided evidence for higher epilepsy care utilization in WVE compared to men, it did not more broadly explore psychiatric characteristics of WVE, which could influence care delivery and ultimately improve quality of life outcomes.

The purpose of the present investigation was to provide a comprehensive characterization of the psychiatric profile of WVE using a VHA-wide sample to better guide identification and treatment. As the nation's largest integrated health care system, VHA population-wide data allowed us to examine a broad range of demographic and clinical variables from a large sample of women Veterans being treated for epilepsy across the United States. We identified variables related to (1) demographics, (2) psychiatric comorbidities, and (3) hospitalizations. We then compared women and men cohorts to describe sex differences across these variables. In secondary analyses, we also explored gynecological variables, given the importance of such factors in this sample, a gap in the literature regarding gynecological presentation of WVE, and the close relationship between certain gynecological conditions and psychiatric functioning.¹³

Methods

Standard protocol approvals, registrations, and patient consents

This VHA population-wide study was approved as a Quality Improvement project by the VHA Epilepsy Centers of Excellence National Program Office, deemed as nonresearch activity not requiring research approval or consent, following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

Study background and data sources

We used VHA Corporate Data Warehouse (CDW) administrative data, including outpatient encounters, inpatient encounters, and prescription drugs. Demographic variables were extracted from Health Eligibility Center and CDW patient demographic files. The primary study period was fiscal year 2019 (FY19; October 1, 2018 to September 30, 2019). The year 2019 was chosen to eliminate confounding effects of the COVID-19 pandemic in 2020 on the data collected. For certain variables, the preceding 5-year (FY15 to FY19) “lookback” periods were examined to provide more comprehensive results (Fig. 1). Specifically, use of a lookback period was helpful in providing a longitudinal view of certain variables that may be missed if a shorter (e.g., 1 year) period was examined, such as diagnostic, hospitalization, and prescribing trends.

FIG. 1.

Study period. *FY(xx) = Fiscal Year(year).

Definition of epilepsy

Identification of epilepsy followed previously established guidelines.¹⁴ “Epilepsy” was defined as meeting all of the following three criteria: (1) ≥1 documented seizure-related diagnosis (i.e., International Classification of Diseases, Tenth Edition, Clinical Modification [ICD-10-CM] codes G40*, R40.4, R56.1, and R56.9) in the past 3 years (i.e., index year and previous 2 years) excluding encounters from electroencephalogram (EEG) and long-term EEG monitoring; (2) ≥1 ASM prescription for at least 30 days during the index year (FY19), with gabapentin considered an ASM only when accompanied by ≥1 encounter containing an epilepsy-related diagnosis (i.e., ICD-10-CM codes G40*, R56.1 or R56.9) given its widespread use for neuropathic pain within the VHA; and (3) a seizure diagnosis (i.e., International Classification of Diseases, Ninth Edition, Clinical Modification [ICD-09-CM] codes 780.39, 345.xx; ICD-10CM codes G40*, R56.1, and R56.9) was listed on the Problem List (i.e., list of a Veteran's active diseases and conditions in the electronic medical record).

ASM prescriptions for the study population during FY15-FY19 are included in Supplementary Table S1.

Variables of interest

Demographic information

Demographic variables included age, sex, ethnicity, race, and rurality. Sex was identified using VHA demographic data; information regarding gender identity was not available. Variables for ethnicity and race are listed separately in the VHA and thus extracted as unique variables from CDW data.

Psychiatric conditions

Comorbid psychiatric conditions were evaluated based on diagnoses received during FY15–FY19 (the lookback period). The following psychiatric conditions were assessed: depressive disorder, anxiety disorder, posttraumatic stress disorder (PTSD), bipolar disorder, unspecified mood disorder, and schizophrenia. Two gynecological variables, polycystic ovarian syndrome (PCOS), and hysterectomy were also explored. ICD Codes used to identify each of these conditions are listed in Supplementary Table S2. To be included, each psychiatric diagnosis was required to have been present in at least two outpatient encounters or one inpatient encounter during the study period; for gynecological conditions, assessment was based on ≥1 encounter. Accuracy and reliability of VA diagnostic codes have been demonstrated in prior work.^15

–18

Psychiatric treatment

Psychiatric treatments examined included number and type of psychotropic medications prescribed during the study period, frequency of psychiatric hospitalizations (i.e., frequency of hospital admissions related to psychiatric conditions identified by the principal diagnosis defined as major cause of stay), and duration of psychiatric hospitalizations (i.e., number of days admitted to the hospital based on documented admission and discharge dates, when available). Psychotropic medications and frequency of psychiatric hospitalizations were examined and calculated for the full study cohort, not just those with psychiatric diagnoses. Number of emergency room (ER) visits due to psychiatric conditions were also evaluated. For this variable, patients were divided into categories based on psychiatric diagnoses and then count of ER psychiatric visits was calculated. As such, results for a specific condition (e.g., depression) represent the number of patients with a diagnosis of depression who had a psychiatrically related ER visit (for any psychiatric reason).

Statistical analyses

SAS software version 9.4 (SAS Institute, Cary, NC) was used to examine statistically significant differences in demographics, psychiatric comorbidities, and medical comorbidities between men and WVE. Chi-square analyses were conducted for categorical variables, with confidence intervals (CIs) for differences in proportions estimated using a z-distribution. For continuous variables, Student's t-tests for unequal variances were performed. All analyses were performed at an error rate of alpha = 0.05. No adjustment was applied to correct for type I error due to multiple comparisons as p values were <0.0001 for all outcomes except schizophrenia. Adjustment to reduce error rate would only affect the significance of schizophrenia; however, the effect size (percentage difference of 0.6% described below in results) was minimal.

Data availability

Anonymized data not published within this article will be made available by request from any qualified investigator. As per VA policy, analytic datasets used for this study are not permitted to leave the VA firewall without a Data Use Agreement.

Results

Demographic characteristics

The study cohort consisted of 58,525 Veterans with epilepsy. Demographic characteristics are summarized in Table 1. The majority of the sample (91.5%; n = 53,542) were men, while 8.5% were women (n = 4,983). Notably, these percentages are similar to the VHA patient population as a whole (93.3% men, 6.7% women).¹⁹ Compared to men, WVE were younger and more racially diverse, especially in terms of percentage of African American/Black participants (27.0% of women were African American/Black vs. 19.7% of men). WVE were also more likely to live in urban locations than men (69.1% of women in urban locations vs. 63.8% of men).

Table 1.

Demographic Characteristics of Women Versus Men Veterans with Epilepsy

Characteristic	All cohort (n = 58,525)	Women (n = 4,983)	Men (n = 53,542)	Test statistic, degrees of freedom	Difference (95% CI)
Age^a
Mean, SD (years)	63.0 (14.9)	52.6 (13.7)	64.0 (14.7)	−55.86 (6107.5)^b	−11.37 (−11.77 to −10.97)
Ethnicity^c
Non-Hispanic/Latino	53,309 (91.1)	4,546 (91.2)	48,763 (91.1)	0.02 (1)^d	0.05% (0.0 to 0.7)
Hispanic/Latino	3,247 (5.6)	279 (5.6)	2,968 (5.5)
Unknown/declined to answer	1,969 (3.3)	158 (3.2)	1,811 (3.4)
Race^c
White	41,706 (71.3)	3,178 (63.8)	38,528 (72.0)	160.46 (1)^b	8.18% (6.80 to 9.56)
Black/African American	11,909 (20.4)	1,343 (27.0)	10,566 (19.7)
Other^e	4,910 (8.3)	462 (9.2)	4448 (8.3)
Rurality^c
Urban	37,598 (64.3)	3,444 (69.1)	34,154 (63.8)	48.7 (1)^b	4.94% (3.60 to 6.29)
Rural/highly rural	20,283 (34.7)	1,513 (30.4)	18,770 (35.0)
Other^f	644 (11.0)	26 (0.5)	618 (1.2)

Reported as M (SD); women versus men comparisons performed using Student's t-test.

p < 0.001,

Reported as n (%); women versus men comparisons performed using chi-square tests and reported as chi-square score.

p = 0.9.

Other includes American Indian/Alaskan Native, Native Hawaiian/Pacific Islander, Asian, Multiple races, declined to answer, and unknown.

Other includes Insular Islands and unknown.

CI, Confidence Interval; SD, standard deviation.

Psychiatric conditions

Prevalence rates for psychiatric comorbidities and women versus men comparisons are presented in Table 2. High rates of psychiatric conditions were found among WVE, including depression (59.1%), PTSD (42.0%) and anxiety (44.9%). Compared to men, WVE demonstrated higher prevalence of nearly all psychiatric disorders, including depression, PTSD, anxiety, bipolar disorder, other mood disorders, and suicidality (p < 0.001). Schizophrenia was the only diagnosis found to be higher in men (p = 0.03), with this disorder affecting a small percentage of the overall sample (3.2%) and a minimal difference between groups (0.6%). The two gynecological variables examined, PCOS and hysterectomy, presented in 1.70% and 7.43% of WVE, respectively.

Table 2.

Prevalence of Psychiatric Comorbidities Among Women Versus Men Veterans with Epilepsy

Psychiatric diagnosis	All cohort ^a (n = 58,525)	Women ^a (n = 4,983)	Men ^a (n = 53,542)	χ²	p	Percentage difference (95% CI)
Depression	23,749 (40.6)	2,943 (59.1)	20,806 (38.9)	771.6	<0.001	20.2 (18.8 to 21.6)
PTSD	16,259 (27.8)	2,093 (42.0)	14,166 (26.5)	549.1	<0.001	15.5 (14.1 to 17.0)
Anxiety disorder	15,354 (26.2)	2,236 (44.9)	13,118 (24.5)	977.7	<0.001	20.4 (19.0 to 21.8)
Bipolar disorder	4,494 (7.7)	779 (15.6)	3,715 (6.9)	486.0	<0.001	8.7 (7.7 to 9.7)
Suicidality	3,654 (6.2)	429 (8.6)	3,225 (6.0)	52.1	<0.001	2.6 (1.8 to 3.4)
Other mood disorder	2,896 (5.0)	306 (6.1)	2,590 (4.8)	16.5	<0.001	1.3 (0.6 to 2.0)
Schizophrenia	1,874 (3.2)	133 (2.7)	1,741 (3.3)	5.0	0.026	−0.6 (−1.0 to −0.1)

Percentages may total >100% given that patients may present with multiple conditions.

Percentages reported as n (%); women versus men comparisons performed using chi-square tests and reported as χ ².

score with degrees of freedom = 1.

PTSD, posttraumatic stress disorder.

Psychiatric treatment

Overall, women were prescribed a higher number of psychiatric medications than men (average 2.3 vs. 1.4; difference = 0.85; 95% CI = 0.78–0.91). Comparisons of classes of psychiatric medication prescribed to men and WVE are presented in Table 3. Percentages of specific psychiatric medications prescribed are presented in Supplementary Table S3. Sex comparisons for psychiatric treatment, including emergency care and hospitalization, are summarized in Table 4. A higher percentage of women versus men utilized the ER for psychiatric purposes (11.7% vs. 6.9%; percentage difference = 4.77; 95% CI = 3.85–5.69; χ ² = 153.06).

Table 3.

Classes of Psychiatric Drugs Prescribed Among Women Versus Men Veterans with Epilepsy

Psychiatric drug	All cohort	Women	Men	χ²	p	Percentage difference (95% CI)
Any psychiatric medication	34,669 (59.24)	3,770 (75.66)	30,899 (57.71)	608.1	<0.001	17.95 (16.68–19.21)
SSRI	22,467 (38.39)	2,560 (51.37)	19,907 (37.18)	388.35	<0.001	14.19 (12.75–15.64)
SNRI	10,387 (17.75)	1,583 (31.77)	8,804 (16.44)	733.40	<0.001	15.32 (13.99–16.66)
TCA	8,961 (15.31)	1,329 (26.67)	7,632 (14.25)	542.00	<0.001	12.42 (11.15–13.68)
Atypical antipsychotic	11,010 (18.81)	1,324 (26.57)	9,686 (18.09)	214.63	<0.001	8.48 (7.21–9.75)
Mood stabilizer	962 (1.64)	176 (3.53)	786 (1.47)	120.12	<0.001	2.06 (1.54–2.59)
Other^a	17,308 (29.57)	1,909 (38.31)	19,907 (37.18)	199.61	<0.001	9.55 (8.15–10.95)

Other = bupropion, mirtazapine, nefazodone, trazodone, vilazodone, vortioxetine.

SNRI, serotonin and norepinephrine reuptake inhibitor; SSRI, selective serotonin reuptake inhibitor; TCA, tricyclic antidepressant.

Table 4.

Comparison of Psychiatric Treatment Between Women and Men Veterans with Epilepsy

Type of treatment	All cohort ^a (n = 58,525)	Women ^a (n = 4,983)	Men ^a (n = 53,542)	t-Score (degrees of freedom)	p	Percentage difference (95% CI) ^b
ER visits^c	0.15 (0.88)	0.21 (0.84)	0.15 (0.88)	4.97 (6052.1)	<0.001	0.06 (0.04 to 0.09)
Suicidality	1.76 (2.82)	1.53 (2.11)	1.79 (2.90)
Schizophrenia	1.04 (2.45)	1.20 (2.33)	1.03 (2.46)
Bipolar disorder	0.90 (2.32)	0.66 (1.56)	0.95 (2.45)
Anxiety	0.43 (1.50)	0.38 (1.13)	0.44 (1.55)
Depression	0.34 (1.31)	0.32 (1.03)	0.35 (0.34)
PTSD	0.40 (1.43)	0.39 (1.15)	0.40 (1.43)
Unspecified mood	0.61 (1.97)	0.59 (1.65)	0.61 (2.01)
Hospitalizations^d	0.13 (0.74)	0.18 (0.77)	0.13 (0.74)	4.61 (5861.9)	<0.001	0.05 (0.03 to 0.07)
Suicidality	1.23 (0.58)	1.19 (0.40)	1.23 (0.60)
Schizophrenia	2.37 (2.54)	1.83. (1.58)	2.43 (2.62)
Bipolar disorder	2.03(2.24)	1.86 (1.84)	2.07 (2.32)
Anxiety	1.12 (0.40)	1.25 (0.68)	1.10 (0.34)
Depression	1.67 (1.51)	1.44 (0.96)	1.71 (1.56)
PTSD	1.57 (1.10)	1.41 (0.97)	1.60 (1.12)
Unspecified mood	1.20 (0.53)	1.50 (0.71)	1.18 (0.53)
Hospitalization Duration^e	32.54 (55.08)	30.49 (55.25)	32.84 (55.06)	−0.86 (620)	0.3888	−2.34 (−7.68 to 2.99)
Suicidality	8.02 (14.46)	4.13 (2.33)	8.37 (15.04)
Schizophrenia	46.87 (78.86)	49.69 (83.39)	46.56 (77.80)
Bipolar disorder	29.05 (53.68)	29.68 (62.90)	28.91 (51.62)
Anxiety	11.69 (26.71)	9.77 (14.51)	11.97 (28.04)
Depression	19.26 (35.53)	13.68 (22.38)	19.98 (36.83)
PTSD	39.36 (52.51)	37.48 (52.40)	39.69 (52.56)
Unspecified mood	8.46 (8.89)	5.50 (3.54)	8.64 (9.11)

Reported as M (SD); women versus men comparisons performed using Student's t-tests and reported as t-score (df).

The difference in 95% CIs are reported for means.

Total number of ER visits for any psychiatric condition for FY15-FY19 stratified by psychiatric diagnosis.

Total number of psychiatric hospitalizations for any condition for FY15-FY19 identified by the principal diagnosis.

Average number of days of psychiatric hospitalization for any condition for FY15-FY19.

ER, emergency room.

Similarly, a higher proportion of women versus men were hospitalized with psychiatric diagnoses during the study period (9.8% vs. 6.1%; % difference = 3.65; 95% CI = 2.80–4.50; χ ² = 100.95). As is demonstrated in Table 4, not only were women more likely to have ER visits and psychiatric hospitalizations but were also found to have greater numbers of psychiatric ER visits (difference = 0.06; 95% CI = 0.04–0.09) and hospitalizations compared to men over the study period (difference = 0.05; 95% CI = 0.03–0.07).

Discussion

Women with epilepsy have unique psychiatric presentations that are crucial to investigate to guide identification and intervention efforts. Using a large, VHA-wide sample, we characterized WVE across several psychiatric variables and compared them to a cohort of men to explore unique aspects of their presentations. Findings suggest that WVE have high psychiatric burdens, with greater rates of all psychiatric conditions compared to men. Exploration of gynecological conditions provided estimated rates of PCOS and hysterectomy in this population, which have been suggested to be elevated in women with epilepsy,²⁰ but have not been previously quantified in WVE.

Sex differences in psychiatric presentations and treatment

In our sample, WVE demonstrated high rates of psychiatric conditions, most notably depression, anxiety, and PTSD. All psychiatric conditions examined were more prevalent in women than men, aside from schizophrenia, although it notably was present in small percentages across sexes. Furthermore, WVE were prescribed higher rates of psychotropic medications and had more hospital encounters due to psychiatric conditions, both when considering emergency care and inpatient hospitalization.

It has long been acknowledged that women have higher psychiatric burdens than men, with rates of depression,²¹ anxiety,²² and PTSD²³ all outpacing men in the general population. Similar trends are also present in the Veteran literature, with women Veterans representing an especially vulnerable group.^10,24 Furthermore, there is an established relationship between epilepsy and psychiatric conditions, with prevalent depression and anxiety in this population.^25
–27 Thus, while it logically follows that WVE would be prone to mental health conditions, only a few studies have begun to examine this trend.²⁸ Thus, the current findings highlight an important area of consideration for the treatment of these patients. Given previous findings describing the downstream effects of psychiatric conditions on hospital needs and care utilization,¹² this study suggests that interventions targeting depression and anxiety may reduce the need for emergency or inpatient hospitalization care, each of which can burden the health care system.

Gynecological conditions in WVE

Exploration of gynecological conditions provided estimated rates of PCOS (1.7%) and hysterectomy (7.4%) in WVE. The relationship between epilepsy and sex hormones is one of the more extensively explored areas in women's epilepsy research, with evidence for hormonal dysregulation from seizure activity as well as from ASM treatment.²⁹ In a similar realm, teratogenic effects of ASM have also drawn increased focus in recent years, including by our research team. In a recent investigation of this sample focusing on utilization of epilepsy care, we described problematic patterns of ASM prescription as it relates to teratogenic effects, highlighting rates of valproate (17.6%) and topiramate (33.1%) in WVE.¹² In the current study, we examined gynecological conditions more broadly, seeking to provide an important informational data source related to WVE.

Epilepsy is a risk factor for PCOS given the influence of both seizures and ASM on women's reproductive hormones.^30,31 Yet, the rate of PCOS observed in our sample (1.7%) is far lower than literature-based estimates, which range from 10% to 26% in women with epilepsy.³² While it is unclear why prevalence of PCOS in our study is notably less than established estimates, this finding does raise concern for screening and documentation of PCOS in a WVE sample. As such, measures to identify and treat PCOS represent a future direction of clinical work and research within this population.

Similarly, prevalence of hysterectomy in our study (7.4%) was considerably lower than that found in a previous investigation of women Veterans treated at a single epilepsy monitoring unit, where individual chart review yielded a hysterectomy rate of 17.9% in WVE.³³ However, hysterectomy prevalence rates in the current study were greater than estimates from the women Veteran population as a whole (∼2.6 per 1000).³⁴ While literature examining hysterectomy in WVE is scarce, emerging data suggest that factors associated with both hysterectomy and epilepsy in Veterans (e.g., sexual trauma, high-impact physical activity, physical trauma, and psychiatric conditions) render WVE especially vulnerable to requiring this procedure.³⁴

Study limitations

The present study is the largest known investigation into WVE and, as such, provides crucial prevalence data and sex difference information to inform identification and treatment of WVE. Nonetheless, study limitations are present which may be best addressed in future studies. Primary limitations include those inherent to population-based studies,²⁸ such as the inability to distinguish epilepsy from other seizure conditions, including psychogenic nonepileptic seizures (PNES). Smaller studies that accommodate individual chart review can thus supplement the current findings, as they are better able to distinguish epilepsy from PNES when identifying their sample.

Furthermore, the current study was population-based and we were not able to determine the indication of various medications, including ASM and psychotropic medication. It is certainly the case that some ASM and psychotropic medications can be prescribed for other conditions; for example, gabapentin may be prescribed for seizure control or neuropathic pain. As such, while rates of medication provide a generally accurate overview of prescribing practices in the population, there is inherent variability in conclusions that can be drawn based on this data.

Finally, key variables of interest can be expanded in future investigations. In this study, we focused on women broadly to provide an initial characterization of this group; however, we did delve into additional intersectional variables that potentially influence their comorbidities, including aspects of identity such as race, ethnicity, socioeconomic status, and living location/rurality. In addition, certain gynecological conditions were identified as key variables of interest in this study based on elevated prevalence rates in the existing epilepsy literature and relationship to psychiatric functioning. However, these conditions do not represent the full scope of relevant medical conditions that can comorbidly occur in WVE. As such, future studies should explore additional intersectional traits and comorbid medical and gynecological conditions to provide a broader picture of WVE's health needs.

Conclusions

This VHA population-wide study represents the largest known investigation into the psychiatric complexities of WVE. Women are a rapidly expanding group within the military and Veteran populations, and thus this research pursuit is timely in its characterization of an understudied but increasingly large cohort. Findings emphasize the psychiatric burden present in WVE, in terms of psychiatric conditions, psychotropic medications, and psychiatrically related hospital encounters. PCOS warrants greater identification and documentation in WVE given the likely underestimated rates in the current study, and elevated rates of hysterectomy provide a future direction for research and care.

Footnotes

Acknowledgments

We acknowledge the following program analysts from the VHA Support Service Center (VSSC) for help with data abstraction: Monica J. Kluger, Joseph Fortner, Jo Owens, and Cheryl Strickland.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

Supplementary Material

Supplementary Table S1

Supplementary Table S2

Supplementary Table S3

References

Chan

, Chen

, Makhija

, et al. Gender differences in the incidence of psychiatric co-morbidity in patients with epilepsy (P3.196). Neurology, 2015;84(14 Supplement).

Reiter

, Veiby

, Daltveit

A-K

, et al. Psychiatric comorbidity and social aspects in pregnant women with epilepsy—The Norwegian Mother and Child Cohort Study. Epilepsy Behav, 2013; 29(2):379–385; doi: 10.1016/j.yebeh.2013.08.016

Wilner

, Sharma

, Soucy

, et al. Common comorbidities in women and men with epilepsy and the relationship between number of comorbidities and health plan paid costs in 2010. Epilepsy Behav, 2014; 32:15–20; doi: 10.1016/j.yebeh.2013.12.032

Frank

, Tyson

. A clinical approach to catamenial epilepsy: A review. Perm J, 2020; 24:19.145; doi: 10.7812/TPP/19.145

Stephen

, Harden

, Tomson

, et al. Management of epilepsy in women. Lancet Neurol, 2019; 18(5):481–491; doi: 10.1016/S1474-4422(18)30495-2

Viale

, Allotey

, Cheong-See

, et al. Epilepsy in pregnancy and reproductive outcomes: A systematic review and meta-analysis. Lancet, 2015; 386(10006):1845–1852; doi: 10.1016/S0140-6736(15)00045-8

Spiegel

, Merius

. Principles of epilepsy management for women in their reproductive years. Front Neurol, 2020; 11; doi: 10.3389/fneur.2020.00322

Sundar

, Honrao

, Shah

. Psychiatric co-morbidities in women with epilepsy. J Assoc Physicians India, 2017; 65(12):30–32; PMID: 29327519

Zhong

, Chen

, Li

, et al. Sex differences in anxiety in patients with epilepsy: Status and risk factors analysis. Epilepsy Behav, 2021; 116:107801; doi: 10.1016/j.yebeh.2021.107801

10.

Maguen

, Cohen

, Ren

, et al. Gender differences in military sexual trauma and mental health diagnoses among Iraq and Afghanistan Veterans with posttraumatic stress disorder. Women's Health Issues, 2012; 22(1):e61–e66; doi: 10.1016/j.whi.2011.07.010

11.

Pugh

MJV

, Orman

, Jaramillo

, et al. The prevalence of epilepsy and association with traumatic brain injury in Veterans of the Afghanistan and Iraq wars. J Head Trauma Rehabil, 2015; 30(1):29–37; doi: 10.1097/HTR.0000000000000045

12.

Sullivan-Baca

, Lorkiewicz

, Rehman

, et al. Utilization of Epilepsy Care among Women Veterans: A population-based study. Epilepsy Res, 2023; 107130; doi: 10.1016/j.eplepsyres.2023.107130

13.

Rodriguez-Paris

, Remlinger-Molenda

, Kurzawa

, et al. Psychiatric disorders in women with polycystic ovary syndrome. Psychiatr Pol, 2019; 53(4):955–966; doi: 10.12740/PP/OnlineFirst/93105

14.

Rehman

, Everhart

, Frontera

, et al. Implementation of an established algorithm and modifications for the identification of epilepsy patients in the veterans health administration. Epilepsy Res, 2016; 127:284–290; doi: 10.1016/j.eplepsyres.2016.09.012

15.

Szeto

, Coleman

, Gholami

, et al. Accuracy of computerized outpatient diagnoses in a Veterans Affairs general medicine clinic. Am J Manag Care, 2002; 8(1):37–43.

16.

Kashner

. Agreement between administrative files and written medical records: A case of the Department of Veterans Affairs. Med Care, 1998; 36(9):1324–1336; PMID: 11814171

17.

Zeber

, Copeland

, Amuan

, et al. The role of comorbid psychiatric conditions in health status in epilepsy. Epilepsy Behav, 2007; 10(4):539–546; doi: 10.1016/j.yebeh.2007.02.008

18.

Pugh

MJV

, Zeber

, Copeland

, et al. Psychiatric disease burden profiles among veterans with epilepsy: The association with health services utilization. Psychiatr Serv, 2008; 59(8):4.

19.

Anonymous. Overview of VHA patient, veteran, and non-veteran populations and characteristics. In: National Healthcare Quality and Disparities Report: Chartbook on Healthcare for Veterans [Internet]. Agency for Healthcare Research and Quality (US): Rockville, MD, USA; 2020.

20.

Verrotti

, D'Egidio

, Coppola

, et al. Epilepsy, sex hormones and antiepileptic drugs in female patients. Expert Rev Neurother, 2009; 9:1803–1814; doi: 10.1586/ern.09.112

21.

Nolen-Hoeksema

. Gender differences in depression. Curr Dir Psychol Sci, 2001; 10(5):173–176; doi: 10.1111/1467-8721.00142

22.

McLean

, Asnaani

, Litz

, et al. Gender differences in anxiety disorders: Prevalence, course of illness, comorbidity and burden of illness. J Psychiatr Res, 2011; 45(8):1027–1035; doi: 10.1016/j.jpsychires.2011.03.006

23.

Olff

, Langeland

, Draijer

, et al. Gender differences in posttraumatic stress disorder. Psychol Bull, 2007; 133(2):183–204; doi: 10.1037/0033-2909.133.2.183

24.

Ziobrowski

, Sartor

, Tsai

, et al. Gender differences in mental and physical health conditions in U.S. veterans: Results from the National Health and Resilience in Veterans Study. J Psychosom Res, 2017; 101:110–113; doi: 10.1016/j.jpsychores.2017.08.011

25.

Tellez-Zenteno

, Patten

, Jetté

, et al. Psychiatric comorbidity in epilepsy: A population-based analysis. Epilepsia, 2007; 48(12):2336–2344; doi: 10.1111/j.1528-1167.2007.01222.x

26.

Jackson

. Depression and anxiety in epilepsy. J Neurol Neurosurg Psychiatry, 2005; 76(suppl_1):i45–i47; doi: 10.1136/jnnp.2004.060467

27.

Kwon

O-Y

, Park

S-P

. Depression and anxiety in people with epilepsy. J Clin Neurol, 2014; 10(3):175–188; doi: 10.3988/jcn.2014.10.3.175

28.

Sullivan-Baca

, Rehman

, Towne

, et al. Psychiatric co-morbidity of drug-resistant epilepsy in Veterans. Epilepsy Behav, 2023; 139; doi: 10.1016/j.yebeh.2022.109059

29.

Bui

. Women's issues in epilepsy. Continuum, 2022; 28(2):399; doi: 10.1212/CON.0000000000001126

30.

, Wang

, Dong

, et al. A meta-analysis of polycystic ovary syndrome in women taking valproate for epilepsy. Epilepsy Res, 2011; 97(1):73–82; doi: 10.1016/j.eplepsyres.2011.07.006

31.

Rashad

, Ashour

WMR

, Allam

, et al. Oxidative stress and risk of polycystic ovarian syndrome in women with epilepsy: Implications of malondialdehyde and superoxide dismutase serum levels on female fertility. Egypt J Intern Med, 2019; 31:609–619; doi: 10.4103/ejim.ejim_3_19

32.

Ortiz Salas

, Rodríguez

, Florez

SJB

, et al. Polycystic ovary syndrome and the new antiepileptic drugs: A systematic review. Epilepsy Res, 2022; 185:106968; doi: 10.1016/j.eplepsyres.2022.106968

33.

Sullivan-Baca

, Modiano

, Miller

, et al. Characterizing women veterans receiving seizure care in the veterans affairs healthcare system. Epilepsy Res, 2022; 180:106849; doi: 10.1016/j.eplepsyres.2021.106849

34.

Katon

, Gray

, Callegari

, et al. Trends in hysterectomy rates among women veterans in the US Department of Veterans Affairs. Am J Obstet Gynecol, 2017; 217(4):428.e1–e428.e11; doi: 10.1016/j.ajog.2017.05.057

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