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- Summary and Conclusions
- Supporting Information
Purpose: To determine whether abnormal cardiac repolarization and other electrocardiography (ECG) predictors for cardiac mortality occur in epilepsy patients and whether they are associated with an increased risk for sudden unexpected death in epilepsy (SUDEP).
Methods: In a matched-pair case–control study, recordings of adult patients with pharmacoresistant focal epilepsies who died from SUDEP and who had previously had presurgical video-EEG (electroencephalography) telemetry were reviewed. Living controls were matched for age, gender, and date of admission for video-EEG telemetry. Periictal heart rate (HR), corrected QT interval (QTc), postictal HR recovery, HR variability, and cardiac rhythm were assessed. QT dispersion was analyzed with 12-lead ECG.
Results: A total of 38 patients (19 per group) had 91 recorded seizures. QTc was prolonged above pathologic upper limits in 9 of 89 seizures and 5 of 38 patients. Nine of 34 patients displayed pathologic QT dispersion. Presence of neither pathologic cardiac repolarization nor other ECG features were specifically associated with SUDEP. SUDEP patients were, however, more likely to lack pathologic cerebral magnetic resonance imaging (MRI) findings, less likely to experience antiepileptic drug reduction during telemetry, and had more secondarily generalized tonic–clonic seizures (SGTCS) per year.
Discussion: Our study did not reveal a clear-cut ECG predictor for SUDEP. Pathologic cardiac repolarization is not uncommon in adult patients with pharmacoresistant focal epilepsy and could favor occurrence of fatal tachyarrhythmia as one plausible cause for SUDEP. SGTCS are a risk factor for SUDEP, have, as compared to complex-partial seizures, a greater, unfavorable impact on heart activity, and may thereby additionally compromise cardiac function.
Sudden unexpected death in epilepsy (SUDEP) is the major cause of mortality in younger epilepsy patients, with an incidence of 6.3–9.3 per 1,000 person years in patients entering epilepsy surgery programs (Tomson et al., 2008). Epidemiologic studies have consistently identified generalized tonic–clonic seizures as a risk factor, whereas other factors are controversial (Timmings, 1993; Nashef et al., 1995; Langan et al., 2005). The mechanisms underlying SUDEP are still poorly understood, and preventive strategies, apart from good seizure control, are generally lacking. Possible mechanistic explanations include seizure-related respiratory and cardiac dysfunction. Pathologic cardiac repolarization increases the risk of fatal ventricular tachyarrhythmia and is an established predictor of sudden cardiac death (Schouten et al., 1991; Macfarlane et al., 1998; Chiang, 2004). Therefore, seizure-related prolongation of QT intervals has been postulated to be involved in SUDEP (Tavernor et al., 1996; Langan et al., 2000). Conclusive evidence of pathologic cardiac repolarization in adult epilepsy patients, however, is still lacking. We ascertained if adult pharmacoresistant epilepsy patients display pathologic cardiac repolarization or other electrocardiography (ECG) predictors for cardiac mortality during or after seizures and whether these are associated with an increased risk for SUDEP. This is an important issue as it would have implication for the formulation of preventative measures.
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- Summary and Conclusions
- Supporting Information
A total of 38 people with pharmacoresistant epilepsy (19 SUDEP, 19 control patients) with available video-EEG data (total of 51 and 40 seizures in SUDEP and control group) were included. The SUDEP group comprised one probable (Patient 13) and 18 definite SUDEP events (Nashef, 1997). One SUDEP patient (Patient 18) had sarcoidosis as a potentially competing comorbidity for sudden cardiac death, but postmortem did not reveal any structural cardiac abnormalities. Two SUDEP patients (Patients 4 and 11) also had an implanted vagal nerve stimulator (VNS). A contribution of vagal nerve stimulation to sudden death cannot be ruled out in these patients. To date, however, there is no strong evidence to indicate an increased risk of SUDEP after VNS implantation (Annegers et al., 2000). Further clinical characteristics of individual patients are given in Tables 1 and 2.
Table 1. Clinical details of individual patients
|Patient no.||Sex||Age/Epilepsy durationa||Comorbidity||Epilepsy type||MRI finding||Seizure lateralization||Surgery/ Outcomeb|
|1||F||33/25||0||TLE||Postischemic lesion temporoparietal R||R||0/na|
|3||M||36/26||Depression||TLE||Gangliocytoma/hamartoma frontal lobe L||L||1/4|
|4||M||28/12||Depression Ictal bradycardia Cardiac pacemaker (VVI) VNS||Cryptogenic TLE||0||R/B||0/na|
|5||M||41/40||Anxiety disorder||TLE||HS L||R/L||0/na|
|6||M||28/26||Alcoholism||Cryptogenic partial epilepsy||0||R/L||1/4|
|8||M||44/26||Exocrine pancreatic deficiency||FLE||Traumatic lesion frontal lobe R||R||0/na|
|10||F||39/35||Psychosis||Cryptogenic partial epilepsy||0||R||0/na|
|15||M||29/16||Mental retardation||Partial and generalized epilepsy||0||L||1/4|
|16||F||41/15||0||TLE||Secondary lesions (arachnoid cyst) temporal lobe L||L||0/na|
|18||F||49/40||Depression, Sarcoidosis||Cryptogenic FLE||0||R||1/unknown|
|19||M||43/34||Depression||TLE||HS and dysplastic amygdala L||L||1/4|
|20||F||32/11||Depression||TLE||Diffuse postradiation defect, resection defect (medulloblastoma)||R||0/na|
|21||F||29/22||Systemic LE I, TP Antiphospholipid antibodies||FLE||Unspecific white matter lesions frontal lobe L||L||0/na|
|24||M||42/33||0||TLE||Glioma temporal lobe L||L||0/na|
|30||F||19/7||Depression||Partial TLE||Astrocytoma frontotemporal R||Undecided||1/4|
|36||M||39/38||Hypertension||TLE||Hemiatrophy and HS L||L||0/na|
|37||F||46/45||0||TLE||Diffuse cerebral atrophy L>R after perinatal hemorrhage and HS L||L||0/na|
|38||M||44/30||Depression||Bilateral TLE||HS B||R/L||0/na|
Using a conditional logistic regression model, three of the analyzed clinical parameters were significantly different in SUDEP compared to control patients (Table 2). First, the presence of pathologic cerebral MRI findings was associated with a lower SUDEP risk [p = 0.037, 95% confidence interval (CI) 0.01–0.88; OR = 0.11]. This association was independent of performed epilepsy surgery, as it was still statistically significant after adjusting for epilepsy surgery. Second, patients in whom AED reduction was instituted during telemetry were less likely to die suddenly later on (p = 0.0156, 95% CI 0–0.69; OR = 0.10). Third, the rate of SGTCS per year per patient was significantly higher in SUDEP than in their counterparts (p = 0.035, per SGTCS per year 95% CI 1.00–1.09), with an OR of 1.044 per tonic–clonic seizure (i.e., each secondarily generalized tonic–clonic seizure increased the risk of SUDEP by 4.4%); this was independent of the maximally observed overall seizure frequency. In contrast, none of the analyzed electrocardiographic predictors for cardiac mortality and sudden cardiac death was significantly different between SUDEP and control patients (conditional logistic regression analysis, Table 3).
Table 3. Electrocardiographic predictors for cardiac mortality
| ||Controla||SUDEPa||p-Valuea||95% CI||OR|
|Maximal preictal HR (bpm)||80 ± 15||75 ± 14||0.232||0.17 to 3.35|| |
|Maximal ictal HR (bpm)||115 ± 30||118 ± 23||0.688||−0.04 to 0.02|| |
|Relative ictal change of HR||1.46 ± 0.37||1.62 ± 0.32||0.208||−0.04 to 0.06|| |
|Maximal postictal HR (bpm)||84 ± 14||88 ± 17||0.385||0.14 to 7.1|| |
|HRR (bpm)||4 ± 17||14 ± 13||0.102||−0.08 to 0.02|| |
|Preictal HRV (10 s SDNN, ms)||29 ± 17||31 ± 19 (17)||0.971 (17)||−0.02 to 0.03|| |
|Ictal HRV (10 s SDNN, ms)||18 ± 15 (18)||22 ± 17 (15)||0.498 (14)||−0.70 to 3.22|| |
|Postictal HRV (10 s SDNN, ms)||31 ± 16||38 ± 28 (17)||0.474 (17)||−0.03 to 0.07|| |
|Preictal HRV (30 s SDNN, ms)||33 ± 19 (18)||35 ± 19 (17)||0.93 (16)||−0.01 to 0.1|| |
|Postictal HRV (30 s SDNN, ms)||34 ± 16 (18)||45 ± 30 (17)||0.303 (16)||−0.04 to 0.04|| |
|Preictal QTc (ms)b||414 ± 27||420 ± 25||0.483||−0.04 to 0.09|| |
|Ictal QTc (ms)||402 ± 31 (18)||417 ± 38 (18)||0.24 (17)||−0.02 to 0.04|| |
|Postictal QTc (ms)||415 ± 21||420 ± 25||0.368||−0.04 to 0.04|| |
|QRS (12-lead, ms)||97 ± 24 (18)||93 ± 28 (16)||0.418 (15)||−0.01 to 0.04|| |
|QTd (12-lead, ms)b||45 ± 16 (18)||50 ± 19 (16)||0.748 (15)||0.25 to 8.98|| |
|Pathologic QTd (12-lead, no. pat.)||4 (18)||5 (16)||1.0 (15)|| || |
|Pathologic QTc (no. pat.)||2||3||0.657||−0.01 to 0.03||1.5|
|Cardiac arrhythmias (no. pat.)||5||4||0.739||−0.02 to 0.05||0.8|
|Any ECG abnormality (no. pat.)||6 (18)||6 (16)||0.706 (15)||0.21 to 2.98||0.75|
Because a single seizure can result in sudden death, individual outliers are perhaps more relevant than population means. Therefore, we also considered electrocardiographic data at the level of individual patients and seizures. As exemplified in Fig. S1A,B, HR transiently increased in most patients during seizures (35 of 38 patients, see also Fig. 1A). HR was not affected by seizure-activity in only three control patients. HR showed marked ictal instability (Fig. S1B), with initial tachycardia and pronounced transient bradycardia in one SUDEP patient (Patient 4). Brief episodes of asystole were also noted in this patient, and these led to subsequent implantation of a VVI cardiac pacemaker, which was replaced after some years and still present at the time of his death 10 years after telemetry. Ultra short-term HRV decreased during seizures in both control and SUDEP patients to the same extent (Fig. 1B). Postictally, however, HRV increased in SUDEP patients more than in controls, although this difference did not reach statistical significance (Fig. 1B, mixed logistic regression model, HRV expressed as 30 s SDNN, p = 0.262).
Figure 1. Higher ictal heart rates preferentially occurred during SGTCS. No difference in absolute changes of HRV or QTc during and after seizures between SUDEP and control patients. (A) Left y-axis indicates number of seizures and patients with HR >100 bpm and >120 bpm. Right y-axis refers to number of seizures and patients with HR >150 bpm. (B) Ultra short-term HRV decreased during seizures (expressed as SDNN in a 10 s interval) in both groups (left bars) and returned to baseline levels after seizure cessation in controls, whereas HRV slightly increased in SUDEP group. However, differences in HRV change between controls and SUDEP patients did not reach statistical significance. Number of seizures from left to right: 30, 29, 31, 33, 30, and 33. (C) Left panel displays absolute QTc changes during seizures with respect to preictal QTc using all four correction formulas (Baz, Bazett’s; Fri, Fridericia’s; Fra, Framingham; Hod, Hodges) in controls and SUDEP patients. Difference in QTc according to Bazett’s reached statistical significance (p = 0.036), most likely due to overcorrection for higher ictal HR. Right panel displays absolute postictal QTc changes. 37 seizures in control and 48 seizures in SUDEP group. Data expressed as mean ± SEM. For all panels: blue bars control patients, red bars SUDEP patients.
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Seizure-related QTc prolongation >10 ms (according to all four correction formulas, see Supporting Information) occurred in 43 of 89 seizures (∼48%, 25 seizures from SUDEP patients) in 24 patients (∼63%, 13 SUDEP patients). Figure 1C summarizes the absolute changes in QTc according to all four correction formulas during and after seizures. It is important to note that five patients displayed seizure-induced QTc lengthening beyond upper normal limits in nine seizures (see Tables S1 and S2: three SUDEP, two controls; mixed logistic regression model, p = 0.657, 95% CI −0.01 to 0.03, OR = 1.5). Lateralization of seizure onset did not have an effect on occurrence of QTc prolongation (mixed logistic regression model, p = 0.545, 95% CI 0.15–34). In none of the patients did all four correction formulae give a short QTc. QTc values below normal limits were, however, observed in some patients before (three seizures in one control and two SUDEP patients), during (four seizures in three control patients), and 5 min after a seizure (two seizures in two SUDEP patients).
12-Lead ECG recordings were available in 34 patients. Abnormalities were found in 12 patients (six SUDEP, six controls). Incomplete or complete right bundle branch block was found in three patients (two controls), bradycardia in one control, tachycardia in two control patients, and a shifted electrical heart axis in two SUDEP patients (one to either side). Nine patients displayed pathologic QTd beyond 50 ms (with all four formulas): four control (22% of control patients with available 12-lead ECG), and five SUDEP patients (31% of SUDEP patients with available 12-lead ECG, Table S3).
No significant correlation between presence of pathologic QTd and age, epilepsy duration, age of first seizure, gender, and seizure-lateralization was detected (mixed logistic regression model). The presence of both pathologic QTd and QTc prolongation was found in two patients and was not associated with a higher risk of SUDEP (mixed logistic regression model, p = 1.0). One SUDEP patient also exhibited pathologic interictal QTc, as assessed by one-lead ECG recordings and a P mitrale–like configuration (Fig. S2D), without any known cardiac or pulmonary cause. In this patient, QTc prolongation might be related to comedication with citalopram, although there were no signs or indications of overdose.
Cardiac arrhythmias occurred in nine people (five controls), mainly postictally. They were benign and included premature atrial (Fig. S2A,B; two controls, one SUDEP patient) or ventricular (two controls) beats as well as marked postictal sinus arrhythmia (Fig. S2C; three controls, four SUDEP patients).
We next assessed if seizure type influenced intra- and postictal electrocardiographic features (mixed logistic regression model, Table 4). SGTCS lasted longer than nongeneralized seizures (p = 0.018, 95% CI 3.67–39.9), and led to greater absolute ictal HR (p = 0.002, 95% CI 6.23–28.86) and a more impaired HRR (p < 0.001, 95% CI 13.03–31.14). Ictal and postictal HRV were also significantly lower in SGTCS (e.g., postictal HRV expressed as 30 s SDNN: p = 0.002, 95% CI −51.63 to −11.50). Likewise, cardiac arrhythmias tended to occur more frequently after SGTCS, but this difference did not reach statistical significance (mixed logistic regression model, p = 0.091, 95% CI 0.79–21.38, OR = 4.125). Together these findings seem to indicate a significantly greater impact of SGTCS on ECG parameters.
Table 4. Electrocardiographic predictors for cardiac mortality in SGTCS
| ||Nongen. seizures (63 seizures/32 pat.)a||SGTCS (28 seizures/11 pat.)a|| p-Valueb|| 95% CI||OR|
|Duration (s)||77 ± 38||97 ± 31||0.018a||3.67 to 39.9|| |
|No. of seizures arising from sleep||14 in 8 pat.||18 in 5 pat.||0.205 (90)||−0.87 to 4.1|| |
|Preictal HR (bpm)||77 ± 15||76 ± 12||0.991||−9.39 to 9.29|| |
|Ictal HR (bpm)||110 ± 23||135 ± 27||0.002 (90)b||6.23 to 28.86|| |
|Postictal HR (bpm)||81 ± 13||107 ± 24||<0.001b||18.04 to 34.65|| |
|Relative ictal change HR||1.46 ± 0.32||1.82 ± 0.37||<0.001 (90)b||0.16 to 0.56|| |
|HRR (bpm)||4 ± 14||31 ± 24||<0.001b||13.03 to 31.14|| |
| 10 s SDNN pre||32 ± 18||24 ± 14 (7)||0.138 (63)||−26.46 to 3.65|| |
| 10 s SDNN ictal||21 ± 16 (30)||9 ± 6 (5)||0.024 (58)b||−26.93 to −1.89|| |
| 10 s SDNN post||37 ± 24||20 ± 6 (7)||0.014 (63)b||−39.26 to −4.44|| |
| 30 s SDNN pre||35 ± 18 (31)||31 ± 20 (7)||0.478 (62)||−20.23 to 9.47|| |
| 30 s SDNN post||43 ± 27 (31)||20 ± 5 (7)||0.002 (62)b||−51.63 to −11.50|| |
|QTc Fridericia’s (ms)|
| Preictal||419 ± 29||418 ± 26||0.93||−14.42 to 15.83|| |
| Ictal||413 ± 35||412 ± 42 (10)||0.64 (85)||−14.70 to 24.00|| |
| Postictal||418 ± 22||410 ± 30||0.064 (89)||−28.58 to −0.93|| |
|No. of seizures with QTc prolongation||7 in 4 pat.||2 in 2 pat.||1.0|| || |
|No. of seizures with cardiac arrhythmia||9 in 4 pat.||11 in 6 pat.||0.091||0.79 to 21.38||4.125|
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- Summary and Conclusions
- Supporting Information
Supplementary Table 1. Details of patients with seizure-related QTc lengthening on which all 4 correction formulations agreed.
Supplementary Table 2. Number of seizures and patients with seizure-related QTc lengthening.
Supplementary Table 3. Details of patients with pathologic QTd in 12-lead ECG on which all 4 correction formulations agreed
Supplemental Fig 1. Time course of instantaneous HR in individual patients. (A) Time course of instantaneous HR in patient no. 19. (B) Time course of instantaneous HR in patient no. 4. Arrows indicate start and end of seizure.
Supplemental Fig 2. Examples of ECG abnormalities as assessed by one-lead (I) ECG recordings. (A) Postictal premature atrial beat (asterisk) with compensatory pause (lower traces) in a control patient (no. 38). (B) Postictal supraventricular trigeminy (premature supraventricular beats marked with asterisks in lower traces) in a SUDEP patient (no. 7). (C) Postictal sinus arrhythmia (RR interval variability > 0.12 s, lower traces) in a SUDEP patient (no. 4). (D) Interictal prolonged QTc (QT 495 ms, RR interval 1100 ms; QTc Friderici 480 ms) and P mitrale-like configuration (P wave duration 125 ms) in a SUDEP patient (no. 2). Scaling in all panels 1 s.
Supplemental Fig 3. Weak negative correlation between HRV and HR. (A) The two measures of HRV, RMSSD and SDNN, are highly correlated (r2 = 0.81). Therefore, we only presented SDNN data. (B) SDNN values obtained in time intervals of 10 and 30 s in the same seizures are highly correlated (r2 = 0.80). Thus, 10 s intervals may give a good estimate of ultra-short-term HRV. Inset: SDNN values obtained during a 30 s interval are significantly higher than during a 10 s interval (n=60 seizures, paired t-test, p < 0.001). (C) HRV shows a weak negative correlation with HR (r2 = 0.18, slope is significantly different from zero). This may partially explain lower HRV during and after SGTCS.
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Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.