Increased risk of epilepsy among
patients
diagnosed with chronic
osteomyelitis
Chun-Hung Tseng
a
,
d
,
1
, Wei-Shih Huang
a
,
d
,
1
,
Chih-Hsin Muo
b
,
Chia-Hung Kao
c
,
d
,
∗
Introduction
Epilepsy is one of the most prevalent chronic neurological disorders worldwide (De Boer et al., 2008; Pugliatti et al., 2007; Vezzani et al., 2011). The early identification of risk factors for epilepsy, and its subsequent prevention, is a favored method for the lowering of epilepsy-related economic and health care burdens. Epilepsy can be triggered
in some diseases by immune responses or inflammation processes that destabilize brain neuron membrane potentials
(Vezzani et al., 2011; Riazi et al., 2008) and subsequently elicit, in these neurons, the spontaneous firing of excessively synchronous and sustained discharges (Vezzani et al., 2011; Riazi et al., 2008; Engelborghs et al., 2000). Similar pathological discharges of brain neurons can also be
induced by conventional risk factors of epilepsy, such as diabetes (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al.,
2013), hypertension (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013), head injury (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013), stroke (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013), and cancer (Avila and Graber, 2010; Villanueva et al., 2008). However, no risk factors are evident for 20—80% of epilepsy patients, particularly in young populations (Ottman et al., 1996; Mac et al., 2007). Risk factors for epilepsy should be more rigorously investigated, in addition to the aforementioned well-documented
factors.
Epilepsy caused by the pathogenic influence of chronic inflammatory processes on brain neurons has been observed in certain systemic or focal infectious diseases, such as sepsis (Chelazzi et al., 2008; Lamar et al., 2011) and viral
hepatitis infections (Weissenborn et al., 2005; Blei, 2008; Cheung et al., 2012), and autoimmune disorders, such as rheumatoid arthritis (RA) (Cojocaru et al., 2011; Chin and Latov, 2004) and systemic lupus erythematosus (SLE) (Cojocaru et al., 2011; Chin and Latov, 2004; Borchers et al., 2005). The pathogenic influence of chronic inflammation on destabilizing neuronal membrane potentials of the brain is an established mechanism in the development of epilepsy (Vezzani et al., 2011; Riazi et al., 2008). However, previous studies have not completely determined the extent to which diseases delineating chronic inflammation participate in the pathogenesis of epilepsy through the possible mechanism of inflammation-related membrane instability and the spontaneous discharge of brain neurons, apart from conventional
epilepsy risk factors.
Chronic osteomyelitis (COM), a disease with powerful chronic inflammation induced by bone infection, can continue for a period of weeks, months, or even years, with persisting pathological characteristics that exhibit strong inflammatory activity in the foci because of the formation of abscesses, bone debris, and sinus tracts (Lankarani-Fard et al., 2009). To the best of our knowledge, there has been no research linking COM, an established chronic inflammatory disease, to the development of epilepsy. In this national study, we used a large number of enrollees in the National Health Insurance (NHI) claims database, available in Taiwan, to explore the link between COM and epilepsy in a cohort of more than 22 million enrollees for a period of 11 years starting on January 1, 2000 and ending on December 31, 2010.
Methods
Data source
files of an inpatient claims database obtained for the period of 2000—2010 from the NHI program in Taiwan, which began in 1995. The inpatient claims database employed in this research was extracted from the NHI Research Database (NHIRD) (Wang et al., 2013). NHI covers more than 98% of the total population of Taiwan. The identification numbers of the patients in the NHI program are randomized prior to NHIRD assembling. But, we still obtained approval of the institutional review board (or ethics committee) in China Medical University Hospital. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)
codes were used for coding diseases of interest in this study.
Study patients
Based on the NHI database, enrollees who were newly diagnosed with COM (ICD-9-CM code 730.1) between January 1,
2000 and December 31, 2010, but had no previous medical history of epilepsy (ICD-9-CM code 345), were collected. The dates of their diagnosis were defined as the entry dates. A total of 20,996 patients with COM comprised the study group. The control group was composed of a random selection of age- and gender-matched patients without COM and epilepsy, with corresponding entry dates, and was 4 times the size of the study group (n = 83,973).
Outcome and relevant variables
The end point of this study was epilepsy diagnosis (ICD-9-CM code 345) during the study period (2000—2010). The relevant variables for epilepsy were age, gender, and comorbidities such as diabetes CM code 250), hypertension (ICD-9-CM codes 401—405), head injury (ICD-9-(ICD-9-CM codes 310.2, 800, 801, 803, 804, 850, 851, 853, and 854), stroke (ICD-9-CM codes 430—438) and cancer (ICD-9-CM codes 140—208).
Statistical analysis
A chi-square test and t-test were used to evaluate the differences
of discrete and continuous variables between the COM cohort and the control group. Person-years (person-y) were
calculated from the entry dates to the first dates of epilepsy onset, withdrawal from the insurance program, or the end of 2010. The gender- and age-specific incidence rates (per
1000 person-y) of epilepsy were compared between the study and control groups. In the Cox proportional hazards regression model, hazard ratios (HRs) were derived to compare the risk of epilepsy development between groups.
The demographic factors and correlating comorbidities were identified for comparison between groups. HRs for epilepsy, with stratification by age, gender, and each of the 5 relevant comorbidities, were compared individually between groups. Using a COM severity index, the correlation between the severity of COM and epilepsy was analyzed. This severity index was defined as the division of total length of hospital stay due to COM during the follow-up period by the
length of the follow-up (Tseng et al., 2014). Using the tertile method, the COM severity was further divided into mild (the first tertile in the COM severity), moderate (the second tertile in the COM severity), and severe (the third tertile in the COM severity). The epilepsy-free rates were plotted in a Kaplan—Meier model and the difference between groups was analyzed using a log-rank test (Fig. 1). A two-tailed pvalue
<.05 was considered significant. SAS Version 9.1 (SAS Institute Inc., Carey, NC, USA) was used in the investigation.
Results
Male patients were more susceptible to COM than female patients (65.1% vs. 34.9%) (Table 1). In comparison with
the control group, the familiar comorbidities that are considered risk factors for epilepsy, such as hypertension,
diabetes, head injury, stroke, and cancer, were clearly
higher in the COM group (p < .0001) (Table 1). With adjustment for age, gender, hypertension, diabetes, head injury,
stroke, and cancer, using the Cox proportional hazards regression, the overall epilepsy risk was 2.63-fold (95% confidence interval [CI]: 2.20—3.14) in the COM group;
significantly higher than the control cohort (Table 2). Agespecific epilepsy risk was highest in the youngest age group
(≤39 years: 6.10, 95% CI: 4.00—9.30), with a constant decrease with increasing age (≥65 years: 1.66, 95% CI: 1.28—2.16) (Table 3). The epilepsy risk in COM group without comorbidities is 3.87 times (95% CI: 3.01—4.98) higher than
controls without comorbidities (Table 4). The Kaplan—Meier assessment of the two groups revealed that the risk of epilepsy increased during the follow-up period for both groups, with the epilepsy-free rate in the control group being significantly higher than that of the COM group (logrank
p < .0001) (Fig. 1). Based on the Cox proportional hazards regression model, with adjustment for age, gender, and relevant comorbidities,
the stratification analyses of gender and comorbidities are displayed in Table 2. Comorbidities that are known to augment epilepsy risk might affect COM as a risk factor of epilepsy. In patients with diabetes, head injury, stroke, cancer, or hypertension, patients with COM still exhibited a significantly higher risk of epilepsy (aHRs: diabetes, 1.64 [95% CI: 1.14—2.36]; head injury, 2.07 [95%
CI: 1.35—3.19]; stroke, 1.45 [95% CI: 1.02—2.07]; cancer, 2.07 [95% CI: 0.96—4.47]; hypertension, 1.85 [95% CI: 1.38—2.47]) (Table 4), in agreement with previous studies (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013; Avila and Graber, 2010; Villanueva et al., 2008). In comparison with the control group, a severity-dependent risk
for epilepsy was observed with the stratifications of COM severity (mild: aHR = 1.40, 95% CI: 1.09—1.80; moderate: aHR = 3.45, 95% CI: 2.67—4.45; severe: aHR = 13.2, 95% CI: 10.1—17.3) (Table 5). Using the same severity-stratification method, similar severity-dependent risks have been seen as well in some other reports, including studies about stroke risk among COM patients (Tseng et al., 2014), risk of coronary artery disease in COM population (Hsiao et al., 2014) and stroke risk in patients with multiple sclerosis (unpublished data).
Discussion
In addition to the traditional risk factors for epilepsy, previous studies have disclosed that several diseases characterized by infectious processes, for example, sepsis (Chelazzi et al., 2008; Lamar et al., 2011) and viral hepatitis infections (Weissenborn et al., 2005; Blei, 2008; Cheung et al., 2012), and by inflammatory courses, such as RA (Cojocaru et al., 2011; Chin and Latov, 2004) and SLE
(Cojocaru et al., 2011; Chin and Latov, 2004; Borchers et al., 2005), might increase the risk of epilepsy. By using the large patient population in the Taiwan’s NHI claims dataset,
we investigated whether COM, a condition with persistentlong-term and high-intensity inflammation, increases
epilepsy risk in patients with or without relevant comorbidities of epilepsy.
Similarly to published reports (Smith et al., 2006; Zuluaga
et al., 2006), the COM group was characterized by male predominance with the majority of COM patients being aged
40 years or older (Table 1). This might be because males and younger people were more susceptible to accidents and traumas. These findings demonstrate the applicability of the COM patient population from the Taiwan’s NHI database. The diagnosis of COM was correlated with a higher risk of epilepsy (aHR = 2.63, 95% CI: 2.20—3.14) (Table 2). Although male gender was predominant in the COM group, COM increased the epilepsy risk for both genders (Table 3). Age is an important risk factor for epilepsy (De Boer et al., 2008; Pugliatti et al., 2007; Cloyd et al., 2006; Ngugi et al., 2013; Avila and Graber, 2010; Ottman et al., 1996, 2011; Mac et al., 2007). The absolute risk of epilepsy increased constantly with age (Table 2). However, the relative weight of
COM in augmenting risk of epilepsy was higher in the younger age group, with the highest aHR (6.10) observed in
≤39-year age group, which decreased steadily to the lowest aHR (1.66) observed in
≥65-year age group (Table 3). Because
the comorbidities known to increase the risk of epilepsy were less common in the younger population, COM stood out as a more prominent risk factor than in the older patient groups in whom such comorbidities played more substantial roles as age progressed (Table 3). The risk of epilepsy increased steadily with the increase of COM severity, from the lowest risk in the mildest subgroup (aHR = 1.40, 95% CI: 1.09—1.80) to the highest risk in the most severe subgroup (aHR = 13.2, 95% CI: 10.1—17.3) (Table 5). These findings
strengthen the causal role of COM in the generation of epilepsy.
Comorbidities of epilepsy
Many risk factors for epilepsy have been identified (De Boer et al., 2008; Pugliatti et al., 2007; Cloyd et al., 2006; Ngugi et al., 2013; Avila and Graber, 2010; Villanueva et al., 2008; Ottman et al., 1996, 2011; Mac et al., 2007). Among these, age (De Boer et al., 2008; Pugliatti et al., 2007; Cloyd et al., 2006; Ngugi et al., 2013; Avila and Graber, 2010; Ottman et al., 1996, 2011; Mac et al., 2007), male gender (Pugliatti et al., 2007; Ottman et al., 2011; Ngugi et al., 2013; Mac et al., 2007), hypertension (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013), diabetes (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013), head injury (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013), stroke (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013), and cancer (Avila and Graber, 2010; Villanueva et al., 2008) have been observed to be of varying weights. The prevalence of these comorbidities was all much higher in COM group than controls (Table 1). Since in different COM patients, some of the comorbidities began before and some after COM, in this study, we were not sure if these comorbidities caused COM, vice versa, or COM and these comorbidities shared a common etiology. The risk of epilepsy increased to various levels in both the COM and control cohorts with superimposed comorbidities (Table 4). These results confirmed the validity of the NHI database for exploring supplementary risk factors of epilepsy, such as COM. COM patients without comorbidities that are known to increase epilepsy risk exhibited higher risk of epilepsy (aHR = 3.87, 95% CI: 3.01—4.98) than the control group without the same comorbidities did (Table 4). These findings imply that COM is an independent causal factor of epilepsy, affecting younger patients in particular (Tables 2—4).
The strengths and limitations
This population-based cohort study had numerous strengths. First, patients with COM and age- and gender-matched controls were selected from a large dataset of over 22 million
enrollees, in a national insurance program comprising more than 98% of the entire population of Taiwan. Insurance claims for reimbursement for inhospital management undergo rigorous NHI supervision to prevent health care fraud. The NHI monitoring system increases the reliability of diagnoses. Since the NHI system captures 98% of the population of Taiwan, this study is almost a total population study. Therefore, with a cases-to-controls ratio of 1:4, it
should have higher precision, validity, reliability and generalization in this study. The demographic profiles revealing a
male predominance and age distribution are similar to previous studies (De Boer et al., 2008; Pugliatti et al., 2007;
Cloyd et al., 2006; Ngugi et al., 2013; Avila and Graber, 2010; Ottman et al., 1996, 2011; Mac et al., 2007). The well-organized display of risk factors of epilepsy, including hypertension (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013; LaRoche and Helmers, 2003; Phabphal et al., 2013), diabetes (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013; Phabphal et al., 2013), head injury (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013; LaRoche and Helmers, 2003), stoke (Ottman et al., 2011; Cloyd et al., 2006; Ngugi et al., 2013; LaRoche and Helmers, 2003), and cancer (Avila and Graber, 2010; Villanueva et al., 2008; Kargiotis et al., 2011), in combination with increased incidence rates of epilepsy in both the COM and control groups, supports the reliability of the data used in this study. Second, the large sample size allowed for categorization into subgroups for further statistical analyses, enabling us to confirm the effect of COM on the risk of epilepsy, particularly
in younger people for whom the cause of epilepsy might be less clear.
The length of the follow-up, showing time and severitydependent effects on the epilepsy risk, intensify the
role of COM as a risk factor for epilepsy. Finally, the increased incidence of comorbidities that are known to be risk factors of epilepsy, among patients with COM,
increases the possibility that the underlying chronic inflammation might also affect patients with COM, leading to a
higher risk of developing the pertinent comorbidities of epilepsy.
However, there are still numerous limitations. First, we were unable to exclude the possibility that other vascular risk factors, such as medications prescribed for COM, reduced physical activity and altered immunity, might also increase the risk of epilepsy. Thus, the risks determined in the study might present factors mixed with COM. Second, personal habits that might affect health, including smoking and alcohol consumption, were not obtainable in the Taiwan’s NHI dataset. Their effect on the increased risk of epilepsy in the COM group could not be analyzed. However, COM increased the risk of epilepsy for both genders (Table 3), and the considerably low smoking rate (<4.5%) among women in Taiwan (Bureau of Health Promotion, 2012) suggests that although smoking is unlikely to be a dominant variable for a noticeable increase in epilepsy risk in patients with COM, but it could still be one of the factors. The higher risk for epilepsy in younger COM patients (Table 3), who potentially have less cumulative smoking and alcohol exposures than their elders, also reduces the likelihood of cigarette smoking and alcohol consumption as factors in epilepsy development in the COM population. Third, this study intended to display an increase in the risk of epilepsy in patients with COM. We noticed a higher prevalence of comorbidities among patients with COM in comparison with those without (Table 1). Results disclosed that even among those without risk factors for epilepsy, COM still imposed higher risk for the development of epilepsy. However,
it remains to be established whether there is a causal relationship between COM and epilepsy. Further research is
required to resolve this matter.
Conclusion
Results obtained from this study demonstrated, for the first time, that COM is a risk factor of epilepsy. Patients with COM were observed to have higher prevalence rates of comorbidities that are known to be risk factors of epilepsy. The relative value of COM as a predictor of epilepsy was more significant
in the younger patient groups. The rigorous provision of prevention assessments for epilepsy in patients with COM, such
as treatment with adequate antibiotics, effective abscess drainage and wound debridement of the infected bones, hyperbaric oxygen therapy and, if needed, limb amputation as early as possible (Lankarani-Fard et al., 2009), is prudent, particularly for those of a younger age. Since COM was more commonly seen in males and younger people who were more susceptible to accidents and trauma, vigorous casualty prevention in these two populations might be helpful in epilepsy
