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Department of Clinical Biochemistry, Rigshospitalet Glostrup, Valdemar Hansens vej 1-23, 2600 Glostrup, DenmarkFaculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark
Department of Neurology, Rigshospitalet Glostrup, Valdemar Hansens vej 1-23, 2600 Glostrup, DenmarkDepartment of Clinical Biochemistry, Rigshospitalet Glostrup, Valdemar Hansens vej 1-23, 2600 Glostrup, Denmark
Patients with epilepsy who use EIAEDs have an increased risk of osteoporosis.
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The risk of osteoporosis increases with duration of epilepsy.
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Using more than one AED increases the risk of osteoporosis.
Abstract
Background
Osteoporosis is a bone disorder defined by a decrease in bone mineral density (BMD) which can lead to an increased risk of fractures. Patients with epilepsy are more prone to having fractures. When accounting for seizure-related fractures, the epilepsy patient population still suffers from an increased risk of fractures. This can be attributed to adverse effects of antiepileptic drugs (AEDs).
Aim
The aim of this study was to investigate the association between the use of AEDs and decreased BMD in a large unselected population of Danish patients with epilepsy.
Method
The study was a cross-sectional study based on data retrieved from 835 patients visiting an outpatient Epilepsy Clinic in Glostrup, Denmark, from January 1st 2006 - January 31st 2018. The data included results from DXA-scans and demographic information. Logistic regression models and other statistical analyses were performed.
Results
The results showed that the odds for having osteoporosis when taking EIAEDs were 2.2 (95 % CI: 1.2–3.8, P = 0.007) times higher than those taking NEIAEDs. Furthermore, the odds for having osteoporosis increased with duration of epilepsy (OR = 1.0, 95 % CI: 1.0 – 1.0, P = 0.001) and when the patients consume two AEDs compared to one AED (OR = 2.3, 95 % CI: 1.3–4.1, P < 0.001). Additionally, consuming three AEDs compared to one lead to a 2.3 times higher risk of having osteoporosis (95 % CI: 1.2–4.4, P = 0.01).
Conclusion
When accounted for many riskfactors, EIAEDs, polytherapy with AEDs and duration of epilepsy are correlated with osteoporosis. There is a need for using these known riskfactors as guidelines in indentifying patients at increased risk of developing osteoporosis.
]. Osteoporosis is a chronic multifactorial disease characterized by decreased bone mineral density (BMD) due to an imbalance in the bone remodeling process which leads to porous bones, impaired structural integrity, decreased strength, and an increased risk of fractures [
]. According to WHO, the definition of osteoporosis is a BMD ≤ -2.5 standard deviations (SD) below the average for a young healthy Caucasian woman also known as a T-score ≤ -2.5 SD [
]. Furthermore, osteoporosis leads to immobilization and a reduction of daily activities and has therefore been associated with lower health-related quality of life (HRQoL) [
]. Several risk factors have been linked to the development of osteoporosis such as increasing age, female sex, low body mass index (BMI), smoking, alcohol consumption, and use of certain medications such as glucocorticoids and antiepileptic drugs (AEDs) [
Previous studies have detected a higher prevalence of fractures in patients with epilepsy. The overall risk for fractures in patients with epilepsy is two- to six-fold increased compared to the general population [
]. This is due to various reasons including seizure-related fractures and an increased risk of falls both due to seizures but also caused by adverse-effects of AEDs such as impaired balance. Current literature suggests that seizure-related fractures in patients with epilepsy accounts for only 25–43 % of all fractures [
]. This indicates that other factors contribute to an increased fracture risk, including worse bone health in patients with epilepsy. An association between the consumption of AEDs and impaired bone quality, decreased BMD and the diagnosis of osteoporosis has been found [
]. These studies suggest that AEDs have a negative effect on bone health, and especially the type of AED that is Enzyme-inducing (EIAED) compared to those that are Non-enzyme-inducing (NEIAED) [
]. Thus, there is a strong association between AED use and osteoporosis where the odds of fracture have been shown to increase by 4–6 % with every year of AED use [
The exact mechanism by which AEDs cause osteoporosis is not known. However, a common hypothesis is that EIAEDs (e.g. phenytoin, carbamazepine and phenobarbital) induce the hepatic cytochrome P450 (CYP 450) isoenzyme system responsible for the hydroxylation of vitamin D. This results in an increased hydroxylation and catabolism of vitamin D leading to hypovitaminosis D and subsequent decreased calcium uptake from the intestine. This process would lead to secondary hyperparathyroidism and an increased rate of bone resorption to restore calcium homeostasis, which in turn would cause decreased BMD and eventually osteoporosis [
The current literature on the association between AED use and osteoporosis in patients with epilepsy is primarily done in smaller and selected patient populations. Thus, the aim of this study was to investigate the association between the use of AEDs and decreased BMD in a large unselected population of Danish patients with epilepsy.
2. Methods
2.1 Study design and patient demographics
The study was a cross-sectional study carried out at the outpatient Epilepsy Clinic, Department of Neurology, Rigshospitalet Glostrup, Greater Copenhagen Area, Denmark. Patients with epilepsy can be referred to our clinic from general practice, from neurologists in the primary service section or from other hospitals in the Greater Copenhagen Area covering approximately 400.000 inhabitants. We collected data from patients who had been followed and treated for their epilepsy at our clinic between January 1st, 2006 and January 31st, 2018, but only patients who underwent Dual Energy X-ray Absorptiometry (DXA) scan in this period were included.
As a part of our general management patients were offered a DXA earliest 2 years after initiated antiepileptic treatment. Not all of our patients in the study period accepted to be scanned or were offered a scan, which can explain the relatively low number of included patients when compared to the total number of patients in the epilepsy clinic. Patients are offered a DXA every subsequent two to three years as a follow-up. In case of multiple scans only the latest was included in the study.
Demographic data were gathered from the patients’ medical records from the date closest to the DXA scan. This included information on sex, age, body mass index (BMI), duration of epilepsy, duration of seizure remission (classified as no remission, remission for 6 months or remission for 12 months or longer), epilepsy classification (focal, generalized or unclassified) and comorbidities known to be associated with osteoporosis (taken from FRAX) [
]. This included pulmonary disease, chronic liver disease, organ transplantation, gastrointestinal disease, hypogonadism, hyperthyroidism, type 1 diabetes mellitus and rheumatoid arthritis. Further demographic information included alcohol consumption habits defined as either less or equivalent to the maximum amount suggested by the National Danish Board of Health (<7 units/week for women and <14 units/week for men) or above these suggestions. Information about smoking habits were included and classified as ‘never smoked’ or ‘currently or previous smoking’.
Information on current AED use was also obtained from the medical records, including number of AEDs used, and whether the patients received EIAEDs. The following AEDs were classified as EIAEDs: phenobarbital, primidone, phenytoin, carbamazepine, oxcarbazepine, eslicarbazepine, brivaracetam, perampanel > 12 mg, topiramate, and zonisamide both in doses > 200 mg. The following AEDs were classified as NEIAEDs: benzodiazepine, levetiracetam, ethosuximide, valproic acid (valproate), lamotrigine, rufinamide, pregabalin, gabapentin, lacosamide, zonisamide and topiramate both in doses ≤ 200 mg and perampanel ≤ 12 mg
The DXA scans were used to assess BMD and T-scores of the three regions of interest, lumbar spine (L1-L4), femoral neck, and total hip. The hip with the lowest BMD and T-score was chosen. Osteoporosis was defined according to the WHO’s definition of a T-score ≤ -2.5 SD [
]. All scans were done on the same Lunar Prodigy™ scanner (GE Healthcare, Chicago, USA). The scanner underwent daily, and weekly calibration and quality control and all scans were performed by trained technicians.
The study was approved by the Danish Data Protection Agency (2012-58-0004), and the Danish Patient Safety Authority (3-3013-1459/1 and 3-3013-2456/1). Experiments and procedures were done in alignment with the Helsinki Declaration of 1975 (revised 2013). Demographic information and the T-scores of their DXA scans for lumbar spine L1-L4, and lowest femoral neck and total hip for this subpopulation has previously been published [
Patient data was anonymized prior to analysis. A Shapiro Wilk test was performed to test normal distribution of all the variables in the dataset. Based on distribution, parametric and non-parametric description and tests were used. Continuous non-normally distributed independent variables were described using median and interquartiles (IQs). Continuous normally distributed independent variables were described using mean and SD. For categorical variables, a Pearson chi-square test was carried out, and for continuous variables a Kruskal-Wallis test was done if the data were not normally distributed. For ordinal variables, a trend test was performed and for normally distributed continuous variables, a linear model analysis of variance (ANOVA) was calculated. The outcome variable was expressed as a dichotomy of whether the patient had osteoporosis or not per previous definition. Furthermore, an odds ratio (OR) was calculated with the outcome being osteoporosis comparing the number of AEDS prescribed.
Additionally, two different logistic regressions were calculated to investigate the correlation between osteoporosis and AED use, while accounting for the effect of different confounding variables. There are certain variables that are shared between the two models. The only difference are that the first one includes individual AEDs, while in the other they are classified into EIAED and NEIAED.
RStudio Team, 2015 (Boston, MA) was used for statistical analyses. A p-value < 0.05 (two-sided) was considered statistically significant.
3. Results
3.1 Descriptives
The database included 835 patients with epilepsy, 452 (54 %) females. The median age of the total population is 48 years (IQR: 28) (Range: 17–91). A total of 91 (11 %) of the patients had osteoporosis. Patient characteristics are summarized in Table 1 both for the entire cohort and for the patients with and without osteoporosis, respectively.
Table 1Characteristics of the study population.
No osteoporosis t-score> -2.5 (n = 733−744)
Osteoporosis, t-score≤ -2.5 (n = 88−91)
Total (n = 821−835)
p value
Sex
0.541a
Male n (%)
344 (46.2 %)
39 (42.9 %)
383 (45.9 %)
Female n (%)
400 (53.8 %)
52 (57.1 %)
452 (54.1 %)
BMI (Kg/m2)
0.022b
Median (Q1, Q3)
25.5 (22.6, 29.2)
24.4 (22, 27)
25.2 (22.6, 29)
Age (years)
< 0.001b
Median (Q1, Q3)
46 (33, 61)
60 (52, 69.5)
48 (34, 62)
Drug class
< 0.001a
EIAED n (%)
191 (25.7 %)
41 (45.1 %)
232 (27.8 %)
NEIAED n (%)
553 (74.3 %)
50 (54.9 %)
603 (72.2 %)
Years lived with epilepsy
0.003b
Median (Q1, Q3)
12.5 (5.2, 26)
19.5 (5, 45)
13 (5, 28)
Age at diagnosis of epilepsy
0.379b
Median (Q1, Q3)
21 (12, 47)
32.5 (7, 57.5)
22 (12, 48.2)
Alcohol consumption (units)
0.518a
None or within recommendations n (%)
647 (87.8 %)
76 (85.4 %)
723 (87.5 %)
Current or previous overconsumption n (%)
90 (12.2 %)
13 (14.6 %)
103 (12.5 %)
Tobacco
0.806a
Non smoker n (%)
542 (73.9 %)
64 (72.7 %)
606 (73.8 %)
Smoker n (%)
191 (26.1 %)
24 (27.3 %)
215 (26.2 %)
Comorbidities
0.969a
Not osteoporosis related n (%)
564 (76 %)
69 (75.8 %)
633 (76 %)
Osteoporosis related n (%)
178 (24 %)
22 (24.2 %)
200 (25 %)
Number of AED's prescribed
< 0.001a
1 n (%)
511 (68.7 %)
43 (47.3 %)
554 (66.3 %)
2 n (%)
161 (21.6 %)
34 (37.4 %)
195 (23.4 %)
3+ n (%)
72 (9.7 %)
14 (15.3 %)
86 (10.3 %)
Table 1 : Characteristics of the total study population, for patients with or without osteoporosis. a: Pearson’s Chi-squared test. b: Kruskal-Wallis rank sum test. For categorical variables the percentages are column percentages, and for the continuous variables median, Q1 and Q3. EIAED: Enzyme inducing antiepileptic drug. NEIAED: Non-enzyme inducing antiepileptic drug. BMI: body mass index. Alcohol overconsumption was defined as an alcohol intake above the recommended amount suggested by the National Danish Board of Health (<7 units/week for women and <14 units/week for men).
3.2 Association between type and number of AED and osteoporosis
First, we assessed the risk of having osteoporosis when taking EIAEDs. Patients taking EIAED had an increased OR of 2.4 (95 % CI: 1.4–4.0, P < 0.001) of osteoporosis compared to patients using NEIAED (Table 1).
Next, we assessed whether the number of AEDs prescribed was associated with the risk of osteoporosis (Fig. 1) and found that the OR for having osteoporosis when taking two AEDs compared to one was 2.7 (95 % CI: 1.7–4.4, P < 0.001). Likewise, the OR for having osteoporosis when taking three or more AEDs compared to one was 2.3 (CI: 1.2–4.4, P = 0.01). However, we found no increased odds for having osteoporosis when taking three or more AEDs compared to two 0.9 (95 % CI: 0.5–1.8, P = 0.81). In the logistic regression analysis, a significant difference between three or more AEDs versus one AED in the odds of having osteoporosis was not found.
Fig. 1The odds ratios for having osteoporosis when taking one, two or three or more anti-epileptic drugs (AEDs) with 95 % CI error bars. 2 vs 1: OR = 2.7 (95 % CI: 1.7 – 4.4) P < 0.001. 3+ vs 1: OR = 2.3 (95 % CI: 1.2 – 4.4) P = 0.01. 3+ vs 2: OR: 0.9 (95 % CI: 0.5 – 1.8) P = 0.81. * represents significant results.
3.3 Effects of confounding factors on the association between AEDs and osteoporosis
Next, we wanted to determine which confounding variables affected the risk of osteoporosis in patients with epilepsy. Therefore, we performed two different logistic models. For both tests three different methods (McFadden, Cox and Snell and Nagelkerke) were used to calculate pseudo R2-values for the models to quantify how well they predicted the outcome. For each model, the main descriptive independent variables were included: sex, age, duration of epilepsy, BMI, alcohol consumption, smoking, osteoporosis-related comorbidity, epilepsy classification and the number of AEDs used.
In this model (Table 2), nine independent variables (nine different types of drugs) were added to the model in addition to the demographic independent variables. It is worth mentioning that both EIAED and NEIAED were present among drugs listed here. This model (Table 2) found four independent variables with a significant association with the outcome: Age at the time of the DXA scan, BMI, number of AEDs prescribed, and the dose at which topiramate becomes enzyme inducing, while the remaining covariates (sex, duration of epilepsy, alcohol consumption, smoking, osteoporosis-related comorbidity and epilepsy classification) were not associated with having osteoporosis. For this logistic regression model, depending on the chosen method, different pseudo R2 were obtained, ranging from 0.14 to 0.28. This indicates that the model solely accounts for 14–28 % of the variation seen between the two groups (osteoporosis and not osteoporosis), meaning that there are confounding variables not accounted for.
Table 2Logistic regression model fitted for individual AEDs.
Independent variable
Coefficient (95 % CI)
p value
Sex (female)
1.0 (0.6, 1.7)
0.88
Age (years)
1.1 (1.0, 1.1)
<0.001
Duration of epilepsy
1.0 (1.0, 1.0)
0.065
BMI (Kg/m2)
0.9 (0.8, 1.0)
<0.001
Alcohol overconsumption
1.2 (0.4, 3.2)
0.76
Smoking
1.1 (0.5, 2.1)
0.83
Osteoporosis related comorbidity
0.8 (0.3, 1.9)
0.54
Generalised epilepsy
1.0 (0.6, 1.7)
0.99
Unspecified epilepsy
2.7 (0.9, 7.8)
0.07
Polytherapy (2 AEDs)
2.4 (1.1, 5.3)
0.03
Polytherapy (3+ AEDs)
1.4 (0.3, 5.0)
0.64
Benzodiazepine
1.4 (0.6, 3.4)
0.43
Valproate
1.2 (0.5, 2.7)
0.68
Carbamazepine
1.5 (0.5, 3.9)
0.44
Oxcarbazepine
2.4 (0.9, 6.1)
0.08
Topiramate (enzyme inducing)
4.1 (1.4, 11.6)
0.008
Topiramate (non enzyme inducing)
1.8 (0.5, 6.1)
0.34
Levetiracetam
0.6 (0.3, 1.5)
0.28
Lamotrigine
0.6 (0.3, 1.3)
0.15
Zonisamide
1.4 (0.4, 4.6)
0.63
Table 2: Logistic model fitted for individual drugs as additional independent variables to the basic variables. Correlation coefficients (with associated 95 % confidence intervals (CI)) and the associated P values are presented. Alcohol overconsumption was defined as an alcohol intake above the recommended amount suggested by the National Danish Board of Health (<7 units/week for women and <14 units/week for men).
In summary, being older, having a lower BMI, being treated with 2 AEDs and using the enzyme inducing dose of topiramate were all associated with an increased risk of osteoporosis.
Our logistic regression model (Table 3) found that five independent variables (age, duration of epilepsy, BMI, number of AEDs used and drug class) had a significant association with osteoporosis. For this logistic regression model (Table 3), depending on the chosen method, different pseudo R2-values were obtained, ranging from 0.13−0.25. This means that there are other risk factors not accounted for in the model.
Table 3Logistic regression model fitted for various independent variables.
Independent variable
Coefficient (95 % CI)
p value
Sex (female)
1.0 (0.6, 1.7)
0.92
Age (years)
1.1 (1.0, 1.1)
<0.001
Duration of epilepsy
1.0 (1.0, 1.0)
0.001
BMI
0.9 (0.9, 1.0)
<0.001
Alcohol overconsumption
1.0 (0.4, 2.7)
0.99
Smoking
1.0 (0.5, 1.9)
0.99
Osteoporosis related comorbidity
0.8 (0.3, 2.0)
0.65
Generalised epilepsy
1.1 (0.6, 1.8)
0.85
Unspecified epilepsy
2.7 (0.9, 7.7)
0.07
Polytherapy (2 AEDs)
2.4 (1.3, 4.1)
0.003
Polytherapy (3+ AEDs)
1.6 (0.7, 3.5)
0.25
EIAED
2.2 (1.2, 3.8)
0.007
Table 3 : Logistic model fitted for various independent variables, their correlation coefficients (with associated 95 % confidence intervals (CI)) and the associated p values. Alcohol overconsumption was defined as an alcohol intake above the recommended amount suggested by the National Danish Board of Health (<7 units/week for women and <14 units/week for men).
In summary, increasing age, duration of epilepsy, low BMI, using two AEDs as well as using EIAEDs were all associated with an increased risk of osteoporosis. However, this model only accounts for 13–25 % of all the osteoporosis outcomes in this cohort, indicating that other risk factors play a large role.
4. Discussion
The results of this study showed a significant correlation between having osteoporosis and the use of EIAEDs compared to the use of NEIAEDs. Additionally, different confounding variables were found, including increasing age, the duration of epilepsy as well as low BMI were significantly correlated with having osteoporosis. Female sex was not correlated with having osteoporosis in this study population.
This study found that patients with epilepsy using EIAEDs had higher odds of having osteoporosis than those using NEIAEDs. This response was dose dependent for some drugs, e.g. topiramate showed no significant effect on increasing the risk of osteoporosis in lower non-enzyme-inducing doses. However, in higher enzyme-inducing doses (>200 mg), there was a significantly increased risk of osteoporosis. Our results are in line with other studies demonstrating that EIAEDs increase the risk of bone loss and of osteoporosis. A possible mechanism is that EIAEDs induce CYP 450 enzymes, leading to an increased catabolism of vitamin D, and potentially leading to osteoporosis, as it has been proposed in the literature [
]. Meanwhile other studies have shown that NEIAEDs also cause osteoporosis through other mechanisms the research on this topic is, however, still scarce [
]. Nevertheless, are the NEIAEDs, such as lamotrigine currently seen as the better and safer choice in regard to the development of osteoporosis secondary to the use of AEDs [
Several studies have shown that specific AEDs (e.g. carbamazepine, phenobarbital, and phenytoin) in in vitro studies can induce osteoporosis-promoting mechanisms such as reducing osteoblastic activity, increasing the activity of osteoclasts and degradation of the bone matrix [
]. However, in our study, it was not possible to pinpoint specific AEDs that correlated to osteoporosis due to the large number of different AEDs and a range of different combinations used by the patients. However, that AEDs have adverse effects on bone health is supported by studies on patients using AEDs for other reasons than epilepsy where similar effects are found [
A significant correlation was found between the prevalence of osteoporosis and the number of AEDs taken. As shown in Fig. 1 the odds of having osteoporosis is 2.7 times higher when taking two AEDs compared to one. Likewise, the odds of having osteoporosis is 2.3 times higher when taking three or more AEDs compared to one. These results indicate that using more than one AED significantly increases the risk of having osteoporosis. For some patients polytherapy is the only way to achieve sufficient seizure control and hence cannot be avoided. However, different types of AEDs are currently available and guidelines could help in combining AEDs in order to optimize seizure control while minimizing adverse effects, for example the risk of decreasing BMD [
When it comes to the duration of epilepsy and osteoporosis, the results showed a significant correlation between years lived with epilepsy and the risk of having osteoporosis (Table 1). Age was found to be a confounding factor in this regard. Nevertheless, in the regression model (Table 2), where confounding variables were accounted for, we did find a significant result indicating that a longer duration of epilepsy, increases the risk of having osteoporosis (Table 3). The treatment of epilepsy is usually started right after a diagnosis is given [
]. However, the increased fracture risk in patients with epilepsy can also be related to the socioeconomic consequences of having a chronic disease. A study found that adult patients with epilepsy had increased alcohol consumption and smoking as well as being less likely to exercise. All of this leads to a worse general health status which consequently also affects the bone health of the individual. Furthermore, the study found that the patients with epilepsy were more likely to have a lower educational status, more likely to be unemployed and have a low household income which could be surrogate markers for a vulnerable group with worse general health [
The large population consisting of 835 participants was one of the strengths in this study, which increases the validity of the results. Another strength related to the sample size was the equal distribution of men and women which is generally found in epilepsy. Furthermore, was the large number of variables such as age, sex, years lived with epilepsy, use of AED and lifestyle factors which can all possibly act as confounders in relation to the effect of AED on osteoporosis, which was the aim of this study. By including several variables, the risk, of the results of the statistical analysis being affected by confounding factors, was reduced.
This study also has several limitations including the study design being cross-sectional which is prone to both confounding factors and not being representative of the population. Consequently, the results and conclusions of this study may not represent all patients with epilepsy and osteoporosis. Patients with epilepsy that already had an osteoporosis diagnosis would be less likely to consent to a DXA scan, since they already knew the result. Additionally, those patients with bilateral hip-replacement surgeries were also not included. This was due to the fact that these prostheses yield incorrect DXA-scans. Those who have had bilateral hip-replacement surgeries due to a fracture caused by osteoporosis were thus not included in the study.
Additionally, data on medication switch and duration of the intake of the various AEDs were not included in this study. The lack of history of AED treatment is consequently a limitation and hence, prevents us from determining the effect size of a specific AED on the risk of lowering BMD. Lastly, this study could not control for vitamin D and calcium supplements (as data were not available) which can mask the adverse effect of AEDs on BMD. Furthermore, does the study lack information on concomitant medications with possible adverse effects on bone health eg. use of glucocorticoids, which could be a counfounding factor.
Age is known to cause osteoporosis and elderly patients in this study were underrepresented. This could be explained by the fact that obtaining information on elderly patients in this study have more barriers. The higher occurrence of institutionalization, mental and physical comorbidities, the inability to give consent and social barriers in the patient group all pose challenges in completing the DXAscan. Furthermore, are intellectual disability and stroke factors associated with epilepsy that might also impaire mobility and constitute a barrier in completing the DXA scan.
Furthermore, none of the participants in this study were below the age of 17. An insight into the bone health in the pediatric sub-population of the total epileptic population would give a broader picture on how AEDs affect BMD in all age groups.
Further studies and preferably prospective long-term follow-up cohort studies would help increase our knowledge on the topic.
5. Conclusion
We conclude that there is an association between the risk of osteoporosis and polytherapy with AEDs, the use of EIAEDs and the duration of epilepsy in a large unselected Danish patient-population with epilepsy. Due to the large size of the population it is likely that a certain degree of generalizability exists with other patient populations with epilepsy. Thus the use of several AEDs, EIAEDs and long duration of epilepsy should warrant for examination of the patinets bone health. Further studies, ideally prospective, are needed to increase our knowledge on risk factors for osteoporosis in epilepsy so that preventive measures can be taken and incorporated in to daily clinical practice.
Funding
The study has received an unrestricted research grants from Eisai Co, Ltd. The sponsor had no role in study design, collection of data, analysis or interpretation of data.
Declaration of Competing Interest
SSD has received unrestricted research grants from Eisai Co, Ltd. NBA is a lecturer at scientific meetings organized by Eisai Co, Ltd, and has received unrestricted research grants from Eisai Co, Ltd. DRB, AAM, RBK, HA-M and NRJ have no conflicts of interest to declare.
Acknowledgments
We would like to offer our gratitude to Parisa Gazerani (PharmD, PhD), Aalborg University, for being of great help and support in writing this article.
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