Association of environmental factors with the onset of status epilepticus

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Epilepsy & Behavior 12 (2008) 66–73 www.elsevier.com/locate/yebeh

Association of environmental factors with the onset of status epilepticus Stephan Ru¨egg a

a,*

, Patrick Hunziker b, Stephan Marsch b, Christian Schindler

c

Division of Clinical Neurophysiology, Department of Neurology, University Hospital Basel, Petersgraben 4, CH-4031 Basel, Switzerland b Clinic of Intensive Medicine, University Hospital Basel, Basel, Switzerland c Institute of Social and Preventive Medicine, University of Basel, Basel, Switzerland Received 24 July 2007; revised 25 August 2007; accepted 28 August 2007 Available online 17 October 2007

Abstract Objective. The goal of the work described here was to investigate the influence of environmental factors on admissions of patients with status epilepticus (SE) to the intensive care unit (ICU). Methods. This retrospective cohort study analyzed all admissions to a university hospital ICU because of SE. Poisson regression and likelihood ratio tests were employed to determine associations between environmental factors and the incidence of SE. Results. Data on 184 patients (mean age: 57, range: 18–89) indicated a significant ðP < 0:0001Þ diurnal pattern, with admissions peaking between 4 and 5 PM and reaching a minimum in the early morning. No significant weekly, monthly, or seasonal pattern was observed. Admissions varied significantly across the lunar cycle ðP ¼ 0:003Þ, peaking at Day 3 after new moon and being minimal 3 days before new moon. The incidence of SE increased on bright days ðP ¼ 0:04Þ and with the duration of daily sunshine ðP ¼ 0:03Þ. High relative humidity ðP < 0:01Þ, high temperature ðP < 0:05Þ, and dark days ðP ¼ 0:02Þ were significantly protective factors. The incidence of SE on weekends was significantly lower in the subgroup of patients with known epilepsy ðP ¼ 0:004Þ, and the risk of nonconvulsive SE was significantly higher in summer ðP ¼ 0:04Þ. Conclusions. Admissions of patients with SE to the ICU are significantly associated with several environmental protective and precipitating factors, such as diurnal, weekly, and lunar cycles and weather variables. Ó 2007 Elsevier Inc. All rights reserved. Keywords: Status epilepticus; Intensive care unit; Environment; Circadian; Moon phase; Weather

1. Introduction Status epilepticus (SE) is the most serious manifestation of an epileptic disorder and one of the important neurological emergencies requiring admission to an intensive care unit (ICU), with an annual incidence of about 15–20/100,000 Caucasians per year [1,2]. The annual financial burden of SE in the United States has been estimated to reach about US$ 4 billion in 1994, and the reimbursement per case was 30 to 60% higher than those for other acute conditions like myocardial infarction [3]. Several medical factors causing and facilitating the onset of SE have been identified so far. Two main groups of adult patients with SE may be differen*

Corresponding author. Fax: +41 61 265 56 38. E-mail address: [email protected] (S. Ru¨egg).

1525-5050/$ - see front matter Ó 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.yebeh.2007.08.020

tiated when considering causes of onset of SE: (1) those with preexisting epilepsy; (2) those without it, that is, where SE represents prolonged new-onset seizures. Although problems with antiepileptic drugs (nonadherence, interactions, intoxication) are the most frequent cause in the first group, acute critical illness (stroke, sepsis, intoxication, (illicit) drugs, trauma, etc.) or insidiously progressing neurodegenerative disorders and tumors induce SE in the latter [4–7]. The influence of nonmedical, chronobiological, and environmental factors, like time of the day, season, and air pollution, on the frequency of onset of SE has not been studied yet. The impact of these factors, however, was studied in several other important medical emergency conditions, for example, cardio- and cerebrovascular disease, chronic obstructive pulmonary disease (COPD), and asthma [8–17].

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In addition, the lunar cycle, especially full or new moon, has been implicated as a contributory cause of different emergency conditions, such as cardiorespiratory arrest, labor, psychiatric exacerbations (‘‘lunacy’’), and seizures [18–20]. This belief has been widespread among laypeople since ancient times; more recently, 43% of laypeople, two of three emergency physicians, and even four of five emergency nurses presume that lunar cycling influences human mental health [18,19]. However, there are few, equivocal scientific data on this topic [21–25]. With respect to epileptic disorders, only one study by Polychronopoulos et al. recently suggested a proconvulsive effect of full moon [26]. The authors evaluated an association between emergency admissions for seizures in 859 patients and the lunar phase (divided into four quarters per moon cycle) during a 4-year observation period. They found an almost double odds ratio for the quarter period around full moon when compared with each of the other quarters. Additionally, admissions peaked between 10 and 11 PM and were lowest between 3 and 4 PM. Another study, published 2 years before, however, does not support this hypothesis [27]. Benbadis and colleagues observed the onset of seizures in their epilepsy monitoring unit over 3 years and searched for an association with the lunar phase, which they also subdivided into four quarters. An overall analysis did not reveal a significant association, but when analyzing the data for the two subgroups of epileptic and psychogenic nonepileptic seizures, they found a peak for the former among the last quarter and for the latter during the full moon quarter, respectively. In the present study, we aimed to assess potential associations of several nonmedical, environmental factors with the onset of SE in adult patients urgently admitted to the medical ICU of a single tertiary care center. We wanted to test two hypotheses: first, that the probability of admission varies across the diurnal cycle, and second, that the probability of admission varies across the days of the week. We additionally examined whether the onset of SE exhibits a specific monthly or seasonal pattern. We also investigated the hypothesis of systematic fluctuations in the rate of SE events during lunar cycles. Eventually, we also aimed to detect potential influences of local meteorological conditions on the frequency of admissions for SE. 2. Methods 2.1. Collection of data We collected by chart review all episodes of patients with SE admitted between July 2003 and June 2006 to the single medical ICU of an urban university hospital treating exclusively adult patients and serving as a tertiary care center. The hospital’s geographic location in the middle of the city allows for admission of patients to the ICU within 15 to 30 minutes of the onset of an emergency condition, like SE, from almost every location in town. As a standard, patients with SE having received benzodiazepines during transportation or just at arrival in the emergency room were immediately transferred to the ICU for safety reasons and optimal clinical and technical monitoring; the same is true for already hospitalized patients who experience SE on the wards. The ICU has to take care of patients at

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any time, 24 hours a day, 365 days a year. Exact time of admission to and exit from the ICU were compulsorily noted in the ICU control log sheet within 5 minutes. A patient who had a second episode of SE after discharge from the ICU, and was readmitted, was considered a ‘‘new’’ case. Status epilepticus was defined, according to the currently published national (Swiss) and international standards, as continuous overt convulsive or nonconvulsive seizures and/or electroencephalographic epileptic activity lasting more than 5 minutes or a series of seizures without clinical recovery to baseline between the attacks [28,29]. Status epileptici were categorized into convulsive SE (CSE) and nonconvulsive SE (NCSE); the latter included absence status, simple and complex partial status, subtle status (after transition from CSE), and critical illness status of severely affected patients in coma [6,30]. This cohort was also subdivided into groups of primarily generalized, focal, and secondarily generalized SE. Primarily generalized SE included patients with known or clear electroencephalographic evidence of an idiopathic generalized epilepsy (IGE) syndrome, as well as patients with toxic, metabolic, or drug-induced SE. Analyses of subgroups included patients with known epilepsy (EPI) versus those without known epilepsy (NON-EPI), and patients with CSE versus NCSE. Data on local (Central European Time) moon phases during the study period were collected by using the moon phase calendar provided by http://www.zenowatch.ch/de/Pilot/KlSpez/Mondphase/ body_mondphase.html. Hourly information on local (Basel area) weather conditions was provided by Meteo Switzerland (Zurich, Switzerland).

2.2. Statistical methods Poisson regression was used to study associations between admission counts and different potential predictors. To identify potential diurnal cycles, we cumulated cases by hour of admission. We then regressed the 24 resulting counts against cos(hour Æ 2p/24), sin(hour Æ 2p/24), cos(hour Æ 4p/24), sin(hour Æ 4p/24), cos(hour Æ 6p/24), and sin(hour Æ 6p/24) and used backward selection to find the model with the lowest Akaike information criterion (AIC) value. The model initially considered was thus of the form EðYjhourÞ ¼ exp½a þ R3k¼1 bk cosðhour k2p=24Þ þ R3k¼1 ck  sinðhour k2p=24Þ; where EðY j hourÞ denotes the expected number of cases admitted during the given hour. Adjustment of standard errors for potential overdispersion was based on the Pearson residuals [31]. To study potential influences of season and day of the week, we used Poisson regression models for the daily admission counts containing natural spline functions of calendar time and dummy variables for the days of the week [32]. We considered models of decreasing complexity with spline functions having 8, 7, 6, 5, 4, 3, 2, 1, and 0 knot per year (the last model being devoid of any influence of calendar time) and used the AIC criterion to select the core model for subsequent analyses. The statistical significance of weekly cycles was assessed in this same model. To identify potential incidence patterns across the lunar cycle, we extended the core model by sine and cosine functions of calendar time, with period lengths being fractions of 29.53 days. We started with a model containing cosine and sine terms of period lengths 29.53, 29.53/2, 29.53/3, 29.53/4, and 29.53/5 days, respectively, and then performed a backward selection guided by the AIC criterion; that is, we always removed the remaining sine and cosine terms of highest order. The initial model with its 10 trigonometric terms thus contained about 1 degree of freedom per 3 days. Because the model without any trends or seasonal patterns proved to have the lowest value of AIC in the preceding step, the initial model for the analysis of lunar cycle patterns was of the form

 EðY jtÞ ¼ exp R7k¼1 ak W k ðtÞ þ R5k¼1 bk cosðtk2p=29:53Þ  þR5k¼1 ck sinðtk2p=29:53Þ ;

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where t was defined as the difference in days between the respective calendar date and the 1st of May 2003 (i.e., a day when the new moon was around noon), and W k ðtÞ is the binary variable indicating the kth day of the week. To study potential influences of weather, we extended the core model by meteorological variables. The basic meteorological variables considered were the daily means of temperature ðT Þ, relative humidity (RH), barometric pressure (BP), and wind force (WF). To capture potential nonlinearities and interactions with their effects on daily admissions, we also included the terms T 2 , RH2 , BP2 , T  RH, T  BP, and RH*BP. We then simplified this model using backward selection. Because changes in weather from Day t 1 to Day t might be more influential for the risk of a seizure on Day t than the weather conditions on Day t, we also replaced the variables T, RH, and BP by their first differences DT , DRH, and DBP. In a second round, we replaced the variables of barometric pressure by their analogs of wind force. P values were calculated using likelihood ratio tests by comparing models with and without the factors of interest. A Bonferroni correction was made only for the P values of the two hypothesis-driven tests (for diurnal and weekly cycles). The study was approved by the local institutional review board, which waived the need for written consent of the patients included in this purely epidemiological, observational analysis.

3. Results During the observation period, 3121 patients were admitted to the ICU. One hundred eighty-four patients had SE, that is, 5.90% of all admissions. Nineteen patients (10.33%) were admitted twice, and 4 patients (2.17%) three times for SE. There were 107 cases of SE in men (58%) and 77 (42%) in women, who had a mean age of 56.6 (SD = 18.0, range = 18–89). The distribution of age and sex is shown in Fig. 1. Patients between 40 and 49 years of age accounted for the largest number of admissions, followed by those 70–79 and 60–69 years. Mean length of stay in the ICU was 56.4 (SD = 118.9, range = 1.5–1410) hours. Ninety-three of the 184 patients (50.54 %) had a preexisting known epileptic disorder, which is in line with current knowledge of the epidemiology of SE [2,7]. One hundred (54.35%) of the patients with SE were classified as having GCSE and 84 (45.65%) as having NCSE, 21 (11.41%) of whom with subtle status. With respect to the spread pat-

Fig. 1. Age distribution by gender and decades of patients with SE admitted to the ICU.

tern, 35 (19.02%) SE cases were primarily generalized, 65 (35.33%) SE cases remained focally, and 84 (45.65%) SE cases started focally but secondarily generalized. Only 7 (3.80%) patients had primary generalized SE on the basis of an IGE syndrome; the remaining 28 (15.22%) patients had primary generalized SE resulting from intoxication, (illicit) drugs, or metabolic disturbances. Refractory SE was present in 78 patients (42.39%), similar to previously published data [33,34]. Our data demonstrated a highly significant ðP < 0:001Þ diurnal pattern with a peak in admissions between 4 and 5 PM and a minimum of admissions in the early morning (Fig. 2). This pattern persisted in the subgroups of patients with CSE and NCSE, as well as in EPI and NON-EPI patients. There was a slight, but significant shift of the peak to 4 PM in EPI patients and to 6 PM in NON-EPI patients, whereas the pattern was unchanged in both subgroups of patients with CSE and NCSE. The likelihood ratio test also revealed at first sight a significant ðP ¼ 0:045Þ weekly pattern of admissions peaking on Wednesdays and Thursdays and being lowest over the weekends. When the Bonferroni correction for multiple testing was made, however, this pattern lost significance ðP ¼ 0:09Þ. This pattern did not change when the subgroups of patients with CSE or NCSE were examined. But EPI patients had SE significantly less frequently on weekends compared with NON-EPI patients ðP ¼ 0:004Þ. There was no indication of any trend toward a monthly or seasonal pattern during the observation period for all patients in general and the subgroups of EPI and NON-EPI patients. However, the patients with NCSE had a significant seasonal pattern ðP ¼ 0:04Þ. Compared with summer (June to August), the relative risk of NCSE was 0.27 ðP ¼ 0:02Þ in winter, 0.38 ðP ¼ 0:03Þ in fall, and 0.66 ðP ¼ 0:35Þ in spring. The model with the lowest AIC value was the one without any seasonal variables and time trends. Moreover, we found statistically significant changes in admission rates across lunar cycles. The peak in this pattern occurred neither at full nor at new moon, but a few (about 3–4) days after new moon ðP ¼ 0:003Þ. There was a second smaller, yet not significant ðP ¼ 0:09Þ, second peak a few days before new moon. The lowest rates were observed shortly before new moon; however, this failed statistical significance ðP ¼ 0:06Þ (Fig. 3). The incidence pattern remained the same for the subgroups of EPI and NON-EPI patients and for those with NCSE; however, there was a trend ðP ¼ 0:13Þ toward a weak third peak in patients with CSE around full moon. A slight rise in admissions toward the beginning and end of our observation period made us suspect a connection with the heat waves that occurred both at the beginning and the end of our selected 3-year period. However, high temperature did not show up as a risk factor for SE admissions in our analyses. On the contrary, daily temperature showed a significant negative association with admissions in a model that contained relative humidity and wind force in parallel (Table 1). According to the subgroup analysis,

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Fig. 2. Diurnal pattern of admissions of patients with SE to the ICU. Displayed are the observed and expected numbers of cases during each 1-hour period of the day. Expected numbers were estimated using a Poisson regression model of the form EðY jhourÞ ¼ exp½a þ b1 cosð2p  hour=24Þþ b2 sinð2p  hour=24Þ, where p ¼ 3:14159. The model is statistically significant ðP < 0:001Þ, even after Bonferroni’s correction ðP  < 0:0001Þ for multiple testing.

factor. On average, a 1% higher level of relative humidity was associated with a 2% lower rate of admissions across observation days. This also became apparent in the analysis of day-to-day weather changes and after replacement of wind force by barometric pressure. Here, daily admissions decreased by about 1% for each additional 1% increment in relative humidity ðP < 0:01Þ. This effect was confirmed also for all subgroups; whereas there was no intergroup difference between EPI and NON-EPI patients, the analysis revealed a significantly ðP < 0:01Þ stronger protective effect of temperature in patients with NCSE. In an alternative model combining temperature, sunshine duration, and barometric pressure, an increment in relative sunshine duration of 10% (i.e., corresponding to 72 minutes on a day with 12 hours of sunshine) was associated with a 5% increase in the incidence of SE ðP < 0:01Þ. This was also Fig. 3. Lunar cycle starting at new moon. Estimated relative risk (diamonds, with 95% confidence interval (dots)) of admission for status epilepticus by half-days across the lunar cycle (new moon serving as the reference with a relative risk of 1 (red line)). The function is defined by:

Table 1 Influence of temperature, relative humidity, and wind force on the incidence of admission of patients with SE to the ICU Incidence rate ratio (95% CI)a

y ¼ expf½0:0147  ðcosð2px=29:53Þ  1Þ þ 0:1355  sinð2px=29:53Þ 0:1183  ½cosð4px=29:53Þ  1 þ 0:1837  sinð4px=29:53Þ  0:1159 ½cosð6px=29:53Þ  1 þ 0:3487  sinð6px=29:53Þg; where x = day and p ¼ 3:14159. The P value of this model was 0.005.

Temperature (°C) Relative humidity (%) Wind force (m/s) a

Adjustedc

0.997 (0.979, 1.015) 0.986d (0.979, 0.998) 0.891 (0.761, 1.043)

0.98d (0.961, 1.000) 0.979e (0.961, 0.993) 0.865f (0.966, 1.016)

Associated with a unit increment in the respective covariate. Adjusted only for weekly cycles. c Adjusted for weekly cycles and influences of the other two meteorological variables. d P < 0.05. e P < 0.01. f P < 0.1. b

this effect was statistically significant ðP ¼ 0:01Þ for NONEPI patients and patients with NCSE, but not for EPI patients and patients with CSE, respectively. Surprisingly, relative humidity turned out to be a significant protective

Unadjustedb

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reflected in a significantly increased risk on bright days (< 20% cloud cover) and a significantly decreased risk on dark days (> 80% cloud cover) (results not shown). 4. Discussion This is the first study looking at the possible influence of chronobiological and environmental factors on the frequency of ICU admissions of patients with SE. The results demonstrate a significant diurnal pattern of admissions with a peak in late afternoon and a minimum in the early morning. The subgroup analysis of patients with NCSE, CSE, EPI, and NON-EPI confirmed a very stable low in the morning, whereas the evening peak showed some variability around 4 and 6 PM. This circadian pattern does not fit in with any of the known critical periods for different types of epileptic seizures, for example, the period of awakening for idiopathic generalized epilepsy with tonic–clonic seizures and nighttime for seizure clusters in adult dominant nocturnal frontal lobe epilepsy, benign rolandic epilepsy, and electric status epilepticus during sleep [35–40]. The small number of patients with SE and an IGE syndrome—most likely resulting from the adult hospital setting—compared with those with focal epilepsies did not allow for statistical analysis of intergroup differences. Despite a partial coincidence with a peak in late afternoon, the diurnal pattern of SE observed in the present study is also substantially different from that seen in cardio- und cerebrovascular emergencies, like myocardial infarction and stroke, where the first of two peaks occurs in the early morning [8,12]. This distribution of onset of strokes and myocardial infarctions suggests a strong influence of the pulsatile circadian activation of the hypothalamic–pituitary–adrenal stress axis and an important upregulation of sympathetic outflow while getting up in the morning [41,42]. Such a causative role of a sympathetic-adrenotropic stress reaction is unlikely for the onset of SE; but, conversely, SE may trigger an up-to-maximal sympathetic activation as a result. The exact reason(s) for the diurnal pattern observed in this study remains unclear. However, it might be appropriate to point to the role of the level of vigilance as an important factor influencing the propensity of the brain to seize. Whereas a high level of alertness protects from seizures, low vigilance and drowsiness are well-recognized states in which seizure threshold may be lowered [43,44]. Accordingly, the low admission rate of patients with SE in the morning and the high rate at the end of the working/active hours are inversely correlated to the levels of vigilance during the day. Therefore, we suggest that the diurnal pattern of admissions of patients with SE seen in this study might, at least partly, result from physiological changes in alertness over the day. This explanation also may hold true for the observed weekday pattern, with significant peaks on Wednesdays and Thursdays and a declining rate toward the weekend. This decline was most likely influenced by the significantly lower incidence of SE on weekends in EPI

patients when compared with NON-EPI patients. As a possible explanation, SE in NON-EPI patients results more often from symptomatic medical conditions, in which the influence of the state of vigilance may be less important as in EPI patients. In contrast to the different diurnal pattern of SE and cardiovascular events, a study looking for the relationship between environmental factors and stroke onset showed an almost identical weekly distribution [15]. The study did not reveal any time trends or monthly or seasonal patterns among the whole study population. This lack of a significant seasonal peak in SE events is particularly interesting because it fails to support the hypothesis that fever (being more prevalent during periods of infectious diseases in the winter) would act as a trigger for seizures or SE. Although a recent study also failed to detect a seasonal pattern of stroke incidence [45], several other reports have described an increased frequency of strokes, myocardial infarctions, and respiratory infections during winter [46,47] or at times with high environmental temperature [15]. These results contrast with our findings and further indicate that the mechanisms underlying the onset of SE may be different from those operating in vascular or infectious diseases. Additionally, the influence of other nonmedical, environmental factors like weather and pollution on well-being or disease onset in humans has been studied [9,13,15]. Presence of fog or pollution in urban areas was an independent risk factor for the onset of an acute exacerbation in patients with COPD and asthma or of death from ischemic and hemorrhagic stroke, rupture of aortic aneurysm, and myocardial infarction [10,11,13,15–17]. The lack of a significant seasonal variation in ICU admissions of patients with SE in the present study could suggest that weather and seasonal factors, like temperature, wind force, barometric pressure, and relative humidity, might not play an important role in the onset of SE. However, when meteorological variables were included in the regression models of daily admission counts, relative humidity turned out to be a significant protective factor, and temperature also showed a weakly significant negative association with the risk of SE events. In addition, there was a statistically significant increase in the incidence rate of SE with daily sunshine duration as well as during bright days; and, conversely, a statistically significant decrease in the risk of SE onset was observed during dark days. Other factors, like rain, amount of precipitation, and global radiation (measured in watts/square meter), did not show a significant association. In the present study, we also did not observe the results described in Doherty and colleagues’ most recent work: an increased seizure frequency among EPI patients in an epilepsy monitoring unit during changes in barometric pressure of >5.5 mBar per day [48]. When analyzing the CSE/NCSE and EPI-/NON-EPI subgroups with respect to seasonal patterns and weather variables, the overall results were almost completely confirmed. The single exception consists of a significantly increased risk of SE in summer exclusively for the subgroup

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of patients with NCSE, whereas the protective effect of high temperatures was even more important in this subgroup when compared with the group of patients with CSE. This seemingly equivocal result may be explained by the assumption that very high temperatures were in fact protective, but that summer days with cool temperatures bear an especially important risk to be associated specifically with NCSE. Most of these findings were unexpected. They suggest that high relative humidity, high temperature, short daily sunshine duration, and a cloudy sky are protective with respect to SE. These weather conditions were best met by a hot, humid, cloudy summer day. In contrast, low temperature and relative humidity, a bright and cloudless sky, and long a raise of more than 10% of mean sunshine duration daily sunshine duration are likely to precipitate the onset of SE. A cold, sunny winter day may most closely fit these weather conditions. This hypothesis, however, contradicts the assumption that a lower level of vigilance, fostered by dark light, cloudy skies, fog, and short lengths of daylight, may increase the incidence of seizures or SE. Additionally, the protective effect of higher temperatures is rather surprising, because higher body temperature may lower seizure threshold. A speculative explanation for the observed associations might be that high relative humidity could decrease fluid intake and prevent hypoosmolarity and hyponatremic states, although the seizure-provoking factors hyponatremia and alcohol consumption conditions were not a main cause of admission to the ICU in our cohort of patients with SE [49–52]. Nevertheless, even subtle shifts in levels of fluids and electrolytes during specific weather conditions might perhaps exert some influence on the risk of developing SE. The influence of the moon on the onset and frequency of seizures has the longest history of interest concerning nonmedical factors associated with seizures. Since ancient times, moon phases, especially full moon, were suspected to augment the onset, frequency, and intensity of several medical conditions like birth rate, emergency admissions for acute vascular disorders, and especially mood disorders (‘‘lunacy’’) [18–20]. This also holds true for seizures in patients known to have epilepsy, a belief shared by the lay population as well as by some (para-)medical professionals [19]. The heightened brightness during full moon inducing sleep disruption, more sleep in superficial stages, and consecutively increased daily drowsiness leading to a lowered seizure threshold was proposed as an explanation for seizures clustering at full moon. Nevertheless, this assumption still lacks sound statistical substantiation, and only one study recently reported an association of full moon with an increased frequency of seizures and clusters of seizures [26]; this observation contrasts with another earlier published study that did not support this hypothesis [27]. The present study confirmed a significant association of a specific part of the moon cycle, that is, about 3 to 4 days after new moon, with the rate of admission of patients with SE. This result, though contrary to the public belief of

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clustering at full moon, is in line with several studies and reviews from different fields of medicine that refuted the hypothesis of a specific lunar influence at full or new moon on different medical problems; however, it is noteworthy that the data available are of modest quality and the level of evidence low [21–25]. Why the admissions of patients with SE to the ICU peaked a few days after new moon remains unclear. One hypothesis may argue that the increasing intensity of light after the dark phase might alter the pattern of sleep stages from the deeper stages III and IV to the more superficial stages I and II, where spiking occurs more frequently and eventually may result in overt seizure activity or even SE [53]. Another hypothesis may focus on melatonin, which seems to exert an antiepileptic, antiepileptogenic, and neuroprotective effect [54–57]. This neurohormone is secreted by the pineal gland, a central regulator of adaptations to dark/light cycling, in response to darkness. Increasing light intensity resulting from crescent moon could reduce melatonin secretion and, therefore, lower seizure protection. However, the changes in light intensity only 3 days after new moon are minimal and are unlikely to contribute to the peak in onset of SE observed in this study. There are several weaknesses of this study: The number of cases may have been too small to detect any robust overall seasonal patterns, although a subgroup analysis pointed to a summer peak in NCSE. Moreover, we did not include data on influenza epidemics in our analyses. Thus, potential increases in the rate of SE events during or after influenza epidemics might have gone undetected. Nevertheless, we could identify several factors that were significantly related to SE admissions. The retrospective character of our study made it impossible to assess individual risk factors of individual medical history (e.g., low antiepileptic drug levels, symptomatic etiologies, and refractoriness of SE), as well as nonenvironmental personal risk factors (such as stress, menses, exercise, sleep deprivation, alcohol consumption, and fever) that have been shown to influence the risk of epileptic seizures [58–60]. For example, stress related to the end of the working day and to the evening rush hour may have contributed to the observed diurnal evening and mid-/end-week peak. It is possible that the results of this study are additionally influenced by the combination of such multiple (non-)medical and (non-)environmental factors. Appropriate control for these factors would probably have increased the statistical power of our analyses. Moreover, some of our results might at least in part reflect changes in behavioral patterns associated with environmental conditions and temporal cycles. Therefore, our observed associations may in part have been mediated by such temporal individual factors. To conclude, the frequency of admissions of patients with SE to a tertiary care center ICU is not randomly distributed over time, but exhibits a significant pattern peaking in the late afternoon and a nonsignificant (after adding Bonferroni’s correction for multiple testing) trend toward increasing admissions on Wednesdays/Thursdays.

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There was no monthly or seasonal pattern except for the subgroup of patients with NCSE, which showed a peak in summer. The onset of SE also significantly increased about 3 days after new moon, but neither at full nor at new moon precisely. Whereas a cloudy, hot, and humid day in summer may protect against the onset of SE, a bright, sunny, and cold day in winter is likely to increase the frequency of SE. A variety of other individual medical, behavioral, and environmental factors not controlled for may have contributed to the study results. The results of our study were cautiously proposed to add to the knowledge of some, that is, chronobiological and environmental, factors influencing SE that may help to identify conditions under which patients may become more or less susceptible to the onset of SE. The present data also might have an impact on resource allocation of ICUs, and, in addition, may potentially influence the use of (continuous) EEG monitoring and the workload of neurocritical care staff. Beyond determining or excluding chronobiological or environmental factors associated with the onset of SE, this work may help to discard some of the alleged associations as scientifically unjustified beliefs, for example, overestimation of the effect of a full moon on human disease. The shortcomings of this study kept in mind, the associations observed are not completely understood and their exact pathomechanism warrants further investigations. Ethical approval The authors confirm that they have read the Journal’s position on issues involved in ethical publication and affirm that this article is consistent with those guidelines. Conflict of interest statement All authors declare that they do not have to disclose any conflict of interest related to the material reported in this article. References [1] Hesdorffer D, Logroscino G, Cascino G, Annegers JF, Hauser WA. Incidence of status epilepticus in Rochester, Minnesota 1965–84. Neurology 1998;50:735–41. [2] Coeytaux A, Jallon P, Galobardes B, Morabia A. Incidence of status epilepticus in French-speaking Switzerland (EPISTAR). Neurology 2000;55:693–7. [3] Penberthy LT, Towne A, Garnett LK, Perlin JB, DeLorenzo RJ. Estimating the economic burden of status epilepticus to the health care system. Seizure 2005;14:46–51. [4] DeLorenzo RJ, Hauser WA, Towne AR, et al. A prospective, population-based epidemiologic study of status epilepticus in Richmond, Virginia. Neurology 1996;46:1029–35. [5] Delanty N, French JA, Labar DR, Pedley TA, Rowan AJ. Status epilepticus arising de novo in hospitalized patients: an analysis of 41 patients. Seizure 2001;10:116–9. [6] Ru¨egg SJ, Dichter MA. Diagnosis and management of nonconvulsive status epilepticus in an intensive care unit setting. Curr Treat Options Neurol 2003;5:91–110.

[7] Walker MC. Status epilepticus in the intensive care unit. J Neurol 2003;250:401–6. [8] Elliott WJ. Circadian variation in the timing of stroke onset: a metaanalysis. Stroke 1998;29:992–6. [9] Desqueyroux H, Pujet JC, Prosper M, Le Moullec Y, Momas I. Effects of air pollution on adults with chronic obstructive pulmonary disease. Arch Environ Health 2002;57:554–60. [10] Hong YC, Lee JT, Kim H, Kwon HJ. Air pollution: a new risk factor in ischemic stroke mortality. Stroke 2002;33:2165–9. [11] Manfredini R, Boari B, Gallerani M, et al. Chronobiology of rupture and dissection of aortic aneurysms. J Vasc Surg 2004;40:382–8. [12] Manfredini R, Boari B, Smolensky MH, et al. Circadian variation in stroke onset: identical temporal pattern in ischemic and hemorrhagic events. Chronobiol Int 2005;22:417–53. [13] Wellenius GA, Schwartz J, Mittleman MA. Air pollution and hospital admissions for ischemic and hemorrhagic stroke among Medicare beneficiaries. Stroke 2005;36:2549–53. [14] Ruidavets JB, Cournot M, Cassadou S, Giroux M, Meybeck M, Ferrie`res J. Ozone air pollution is associated with acute myocardial infarction. Circulation 2005;111:563–9. [15] Low RB, Bielory L, Qureshi AI, Dunn V, Stuhlmiller DFE, Dickey DA. The relation of stroke admissions to recent weather, airborne allergens, air pollution, seasons, upper respiratory infections, asthma incidence, September 11, 2001, and day of the week. Stroke 2006;37:951–7. [16] Bayer-Oglesby L, Schindler C, Hazenkamp-von Arx ME, et alfor the SAPALDIA Team. Living near main streets and respiratory symptoms in adults: the Swiss Cohort Study on Air Pollution and Lung Diseases in Adults. Am J Epidemiol 2006;164:1190–8. [17] Yamazaki S, Nitta H, Ono M, Green J, Fukuhara S. Intracerebral hemorrhage associated with hourly concentration of ambient matter: case-crossover analysis. Occup Environ Med 2007;64:17–24. [18] Danzl DF. Lunacy. J Emerg Med 1987;5:91–5. [19] Vance DE. Belief in lunar effects of human behaviour. Psychol Rep 1995;76:32–4. [20] Raison CL, Klein HM, Steckler M. The moon and madness reconsidered. J Affect Disord 1999;53:99–106. [21] Rotton J, Kelly IW. Much ado about the full moon: a meta-analysis of lunar-lunacy research. Psychol Bull 1985;197:286–306. [22] Amaddeo F, Bisoffi G, Micciolo R, Piccinelli M, Tansella M. Frequency of contact with community-based psychiatric services and the lunar cycle: a 10-year case-register study. Soc Psychiatry Psychiatr Epidemiol 1997;32:323–6. [23] Ghiandoni G, Secli R, Rocchi MBL, Ugolini G. Does lunar position influence the time of delivery? A statistical analysis. Eur J Obstet Gynecol Reprod Biol 1998;77:47–50. [24] Alves DW, Allegra JR, Cochrane DG, Cable G. Effect of lunar cycle on temporal variation in cardiopulmonary arrest in seven emergency departments during 11 years. Eur J Emerg Med 2003;10:225–8. [25] Eisenburger P, Schreiber W, Vergeiner G, et al. Lunar phases are not related to the occurrence of acute myocardial infarction and sudden cardiac death. Resuscitation 2003;56:187–9. [26] Polychronopoulos P, Argyriou AA, Sirrou V, et al. Lunar phases and seizure occurrence: just an ancient legend? Neurology 2006;66:1442–3. [27] Benbadis SR, Chang S, Hunter J, Wang W. The influence of the full moon on seizure frequency: myth or reality? Epilepsy Behav 2004;5:596–7. [28] Lowenstein DH, Bleck T, MacDonald RL. It’s time to revise the definition of status epilepticus. Epilepsia 1999;40:120–2. [29] Leppert D, Sto¨ckli HR, Fuhr P. Richtlinien zur Behandlung des Status epilepticus. Schweiz Aerzte Zeitung 2005;86: 2097–100. Full text (in German) provided by: www.saez.ch/status_epilepticus_d.pdf. [30] Meierkord H, Holtkamp M. Non-convulsive status epilepticus in adults: clinical forms and treatment. Lancet Neurol 2007;6:329–39. [31] McCullagh P, Nelder JA. Generalized linear models. Monographs on Statistiscs and Applied Probability 37. Boca Raton, FL: Chapman & Hall/CRC; 1989.

S. Ru¨egg et al. / Epilepsy & Behavior 12 (2008) 66–73 [32] Harrel Jr FE. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. New York: Springer-Verlag; 2001. [33] Mayer SA, Claassen J, Lokin J, Mendelsohn F, Dennis LJ, Fitzsimmons BF. Refractory status epilepticus: frequency, risk factors, and impact on outcome. Arch Neurol 2002;59:205–10. [34] Rossetti AO, Logroscino G, Bromfield EB. Refractory status epilepticus: effect of treatment aggressiveness on prognosis. Arch Neurol 2005;62:1698–16702. [35] Wirrell EC. Benign epilepsy of childhood with centrotemporal spikes. Epilepsia 1998;39(Suppl 4):S32–41. [36] Quigg M. Circadian rhythms: interactions with seizures and rhythms. Epilepsy Res 2000;42:43–55. [37] Pavlova MK, Shea SA, Bromfield EB. Day/night patterns of focal seizures. Epilepsy Behav 2004;5:44–9. [38] Janz D. Epilepsy with grand mal on awakening and sleep-waking cycle. Clin Neurophysiol 2000;111(Suppl. 2):S103–10. [39] Tassinari CA, Rubboli G, Volpi L, et al. Encephalopathy with electrical status epilepticus during slow sleep or ESES syndrome including the acquired aphasia. Clin Neurophysiol 2000;111(Suppl. 2): S94–S102. [40] Combi R, Dalpra` L, Tenchini ML, Ferini-Strambi L. Autosomal dominant nocturnal frontal lobe epilepsy: a critical overview. J Neurol 2004;251:923–34. [41] Singh RB, Kartik C, Otsuka K, Pella D, Pella J. Brain–heart connection and the risk of heart attack. Biomed Pharmacother 2002;56:257–65. [42] Stergiou GS, Vemmos KN, Pilarchopoulou KM, Synetos AG, Roussias LG, Mountokalakis TD. Parallel morning and evening surge in stroke onset, blood pressure, and physical activity. Stroke 2002;33:1480–6. [43] Amzica F. Physiology of sleep and wakefulness as it relates to the physiology of epilepsy. J Clin Neurophysiol 2002;19:488–503. [44] Dinner DS. Effect of sleep on epilepsy. J Clin Neurophysiol 2002;19:504–13. [45] Khan FA, Engstrom G, Jerntorp I, Pessah-Rasmussen H, Janzon L. Seasonal patterns of incidence and case fatality of stroke in Malmo¨, Sweden: the STROMA Study. Neuroepidemiology 2005;24:26–31. [46] Nakaji S, Parodi S, Fontana V, et al. Seasonal changes in mortality rates from main causes of death in Japan (1970–1999). Eur J Epidemiol 2004;19:905–13.

73

[47] Frost L, Vukelic Andersen L, Spange Mortensen L, Dethlefsen C. Seasonal variation in stroke and stroke-associated mortality in patients with a hospital diagnosis of nonvalvular atrial fibrillation or flutter. Neuroepidemiology 2006;26:220–5. [48] Doherty MJ, Youn C, Gwinn RP, Haltiner AM. Atmospheric pressure and seizure frequency in the Epilepsy Unit: preliminary observations. Epilepsia 2007;48:1764–7. [49] Alldredge BK, Lowenstein DH. Status epilepticus related to alcohol abuse. Epilepsia 1993;34:1033–7. [50] Wijdicks EF, Sharbrough FW. New-onset seizures in critically ill patients. Neurology 1993;43:1042–4. [51] Primavera A, Fonti A, Giberti L, Cocito L. Recurrent absence status epilepticus and hyponatremia in a patient with polydipsia. Biol Psychiatry 1995;38:189–91. [52] Delanty N, Vaughan CJ, French JA. Medical causes of seizures. Lancet 1998;352:383–90. [53] Vieth J. Vigilance, sleep, and epilepsy. Eur Neurol 1986;25(Suppl. 2): S128–33. [54] Lapin IP, Mirzaev SM, Ryzon IV, Oxenkrug GF. Anticonvulsant activity of melatonin against seizures induced by quinolinate, kainate, glutamate, NMDA, and pentylenetetrazole in mice. J Pineal Res 1998;24:215–8. [55] Mevissen M, Ebert U. Anticonvulsant effect of melatonin in amygdala-kindled rats. Neurosci Lett 1998;257:13–6. [56] Skaper SD, Ancona B, Facci L, Franceschini D, Giusti P. Melatonin prevents the delayed death of hippocampal neurons induced by enhanced excitatory neurotransmission and the nitridergic pathway. FASEB J 1998;12:725–31. [57] De Lima E, Soares Jr JM, del Carmen Sanabria Garrido Y, et al. Effects of pinealectomy and the treatment with melatonin on the temporal lobe epilepsy of rats. Brain Res 2005;1043:24–31. [58] Spatt J, Langbauer G, Mamoli B. Subjective perception of seizure precipitants: results of a questionnaire study. Seizure 1998;7: 391–5. [59] Frucht MM, Quigg M, Schwaner C, Fountain NB. Distribution of seizure precipitants among epilepsy syndromes. Epilepsia 2000;41:1534–9. [60] Nakken KO, Solaas MH, Kjeldsen MJ, Friis ML, Pellock JM, Corey LA. Which seizure-precipitating factors do patients with epilepsy most frequently report? Epilepsy Behav 2005;6: 85–9.