Seizure recurrence after first epileptic episode in ischemic stroke: Risk factors and their association with cognition and mood

Abstract

BACKGROUND

Ischemic stroke (IS) survivors face an elevated risk of epileptic seizures, and recurrent seizures following the first episode often signal worsening functional outcomes.

AIM

To investigate risk factors associated with seizure recurrence after a first episode in patients with IS and explore their associations with cognitive function, anxiety, and depression.

METHODS

A total of 100 patients with IS admitted to Shaanxi Provincial People’s Hospital between January 2017 and January 2024 were enrolled in this study. After a 1-5-year follow-up, patients were categorized into recurrence (n = 43) and non-recurrence (n = 57) groups. Their medical records were collected and analyzed using univariate and multivariate analyses to determine potential predictors of seizure recurrence. Variables with statistical significance in the univariate analysis were incorporated into a binary logistic regression model for multivariate analysis. The risk model’s predictive performance was evaluated using the receiver operating characteristic curve. How independent risk factors, identified in multivariate analysis, related to cognitive [Montreal Cognitive Assessment (MoCA)] and emotional [Self-Rating Anxiety Scale (SAS)/Self-Rating Depression Scale (SDS)] outcomes, were assessed.

RESULTS

Recurrent seizures were significantly associated with age, stroke severity (National Institutes of Health Stroke Scale), late-onset seizures, electroencephalogram abnormalities, cortical involvement, hemorrhagic infarction, and extensive cerebral infarctions, with late-onset seizures, cortical involvement, and hemorrhagic infarction serving as independent predictors. The risk model revealed an area under the curve of 0.732, with 88.37% specificity and 42.11% sensitivity. These three were also correlated with lower MoCA scores and higher SAS and SDS scores.

CONCLUSION

In patients with IS, recurrent seizures after the first episode can be independently predicted by late-onset seizures, cortical involvement, and hemorrhagic cerebral infarction-factors also correlating with cognitive impairment and emotional distress. These findings underscore the need for close clinical monitoring and targeted interventions (e.g., cognitive rehabilitation and psychological support) to mitigate seizure recurrence in high-risk individuals.

Key Words: Ischemic stroke; First seizure; Recurrence; Risk factors; Cognitive function; Anxiety; Depression

Core Tip: In a cohort of 100 patients with ischemic stroke, we identified delayed seizure onset, cortical lesions, and hemorrhagic infarction as key predictors of recurrent seizures following a first episode. These risk factors also showed strong associations with cognitive impairment and emotional distress.

INTRODUCTION

Stroke ranks as the second leading cause of death worldwide and the third major contributor to disability[1]. Ischemic stroke (IS), the predominant subtype, accounts for approximately 70% of all stroke cases, with incidence escalating with age[2,3]. It also carries a high long-term recurrence risk, significantly influencing prognosis and functional outcomes[4]. Common therapeutic strategies for IS include thrombolysis, anticoagulation, thrombectomy, and antiplatelet therapy[5]. However, post-stroke complications-such as epilepsy, motor deficits, and sensory impairments (e.g., partial hearing or vision loss-affect a substantial number of patients[6]. Post-stroke epilepsy, caused by paroxysmal and uncontrolled neuronal discharges, is a profoundly serious complication. Although both hemorrhagic and ISs can precipitate seizures, IS is particularly associated with a greater propensity for initial and recurrent seizures[7-9]. This heightened risk is likely due to the complex pathophysiology of IS, which includes hypoxic brain injury, metabolic disturbances, compromised blood-brain barrier, sustained neuroinflammation, and glial scarring[10,11]. Recurrent seizures following an initial episode strongly correlates with functional deterioration, underscoring the importance of preventive strategies to improve long-term recovery[12]. Moreover, cognitive impairment and emotional distress (anxiety/depression) are prevalent in patients with IS. These neuropsychiatric sequelae are attributed to neural network disruption and functional deficits and exacerbate clinical outcomes while profoundly diminishing quality of life[13,14]. Therefore, optimal patient recovery depends on a multifaceted approach that addresses seizure recurrence, cognitive deterioration, and psychological distress.

Focusing on patients with IS, this study aimed to identify independent predictors of seizure recurrence after the initial episode, thereby supporting the development of targeted preventive and rehabilitative strategies for smoother recovery. Furthermore, we investigated how these risk factors affect cognitive function and anxiety/depression, with the goal of improving patient prognosis through integrated cognitive and psychological interventions.

MATERIALS AND METHODS

Case selection

A total of 100 patients with IS admitted to Shaanxi Provincial People’s Hospital between January 2017 and January 2024 were retrospectively analyzed. Participants were divided into two groups based on seizure recurrence following the initial episode: Recurrence (n = 43) and non-recurrence (n = 57) groups. Seizure recurrence was defined as a second or subsequent unprovoked (or reflex) seizure occurring more than 24 hours after the initial episode.

Sample size requirement analysis

Post-hoc power analysis using G*Power 3.1 showed 75.2% power (α = 0.05) for the current cohort (43 recurrent/57 non-recurrent cases) to identify a difference in exposure rates (55.81% vs 35.09%; OR = 2.36).

Inclusion and exclusion criteria

Inclusion criteria: (1) Confirmed diagnosis of IS via neuroimaging (computed tomography, computed tomography) or histopathological examination[15]; (2) No history of epilepsy or seizure disorders; (3) Seizures occurring either at stroke onset or during the post-stroke period, with clear temporal and etiological linkage; (4) Preserved cognitive and communicative abilities to ensure reliable study participation; and (5) Complete and accessible clinical records.

Exclusion criteria: (1) Use of antidepressant or anti-anxiety medications within the preceding month; (2) Secondary epilepsy due to other neurological conditions, including encephalitis, meningitis, intracranial neoplasms, cerebral hemorrhage, or traumatic brain injury; (3) Mortality within 7 days following stroke onset; and (4) Presence of severe systemic comorbidities, including advanced hepatic, cardiovascular, or other major organ diseases.

Data collection and outcome measures

(1) Comprehensive clinical and demographic data, including age, sex, comorbidities (hypertension and diabetes), smoking and alcohol history, National Institutes of Health Stroke Scale (NIHSS) scores[16], seizure type (late-onset or partial), electroencephalogram (EEG) findings, cortical involvement, hemorrhagic cerebral infarction, and large-area cerebral infarction, were collected for both groups. NIHSS scores were categorized as < 16 (mild to moderate neurological impairment) or ≥ 16 (severe neurological impairment). Late-onset seizures were defined as those occurring more than 7 days after stroke onset. Partial seizures were identified based on clinical symptoms and EEG findings indicating focal onset within one cerebral hemisphere. EEG abnormalities included epileptiform discharges (e.g., spikes, spike-and-wave complexes, sharp waves, and sharp-and-slow-wave complexes) or focal/unilateral slow-wave activity. Cortical involvement was defined as ischemic lesions within the supratentorial cortex. Large-area cerebral infarction was defined as lesion size ≥ 50 mm × 50 mm; (2) Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) scale[17], which provides scores ranging from 0 to 30. Scores ≥ 26 indicated normal cognition, whereas scores < 26 indicated cognitive dysfunction; and (3) Emotional status was evaluated using the Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS)[18]. Each scale comprises 20 items rated on a 4-point Likert scale (1-4), with higher total scores indicating more severe anxiety or depression.

Statistical analysis

Statistical analyses were conducted using SPSS 22.0 and GraphPad Prism 7. Categorical variables were expressed as frequencies and percentages; intergroup comparisons were performed using the χ² or Fisher’s exact tests, where appropriate. Variables significant in univariate analysis were entered into a binary logistic regression model for multivariate assessment. The point-biserial correlation coefficient was used to analyze the associations between seizure recurrence risk factors post-first episode and MoCA, SAS, and SDS scores. A significance criterion of P < 0.05 was applied.

RESULTS

Univariate analysis of risk factors for seizure recurrence after the initial episode

Univariate analysis identified significant associations between seizure recurrence and patient age, NIHSS score, late-onset seizures, EEG abnormalities, cortical involvement, hemorrhagic infarction, and large-area cerebral infarction (all P < 0.05). In contrast, no significant associations were found for sex, hypertension, diabetes, smoking and alcohol consumption history, or partial seizures (all P > 0.05; Table 1).

Table 1 Univariate analysis of risk factors for seizure recurrence after the first episode, n (%).

Variable	n	Recurrence group (n = 43)	Non-recurrence group (n = 57)	χ2	P value
Age (years)				4.938	0.026
< 60	38	11 (25.58)	27 (47.37)
≥ 60	62	32 (74.42)	30 (52.63)
Gender				0.317	0.574
Male	59	24 (55.81)	35 (61.40)
Female	41	19 (44.19)	22 (38.60)
Hypertension	60	28 (65.12)	32 (56.14)	0.823	0.364
Diabetes	72	32 (74.42)	40 (70.18)	0.219	0.640
Smoking history	30	15 (34.88)	15 (26.32)	0.857	0.355
Alcohol consumption history	12	8 (18.60)	4 (7.02)	3.116	0.078
NIHSS (points)				5.200	0.023
< 16	48	15 (34.88)	33 (57.89)
≥ 16	52	28 (65.12)	24 (42.11)
Seizure type
Late-onset	44	24 (55.81)	20 (35.09)	4.273	0.039
Partial	47	22 (51.16)	25 (43.86)	0.525	0.469
Abnormal EEG findings	41	24 (55.81)	17 (29.82)	6.844	0.009
Cortical involvement	32	20 (46.51)	12 (21.05)	7.301	0.007
Hemorrhagic infarction	23	16 (37.21)	7 (12.28)	8.600	0.003
Large-area cerebral infarction	33	19 (44.19)	14 (24.56)	4.269	0.039

NIHSS: National Institutes of Health Stroke Scale; EEG: Electroencephalogram.

Multivariate analysis of risk factors for seizure recurrence after the initial episode

Variables with significant differences in the univariate analysis were assigned specific values and included in a binary logistic regression model for multivariate analysis. The results revealed that age, NIHSS score, abnormal EEG findings, and large-area cerebral infarction were not independent risk factors for seizure recurrence after the initial episode. In contrast, late-onset seizures, cortical involvement, and hemorrhagic cerebral infarction were significant independent risk factors (Tables 2 and 3).

Table 2 Assignment of variables with significant differences.

Factor	Variable	Assignment
Age (years)	X1	< 60 = 0, ≥ 60 = 1
NIHSS (points)	X2	< 16 = 0, ≥ 16 = 1
Late-onset seizures	X3	No = 0, yes = 1
Abnormal EEG findings	X4	None = 0, yes = 1
Cortical involvement	X5	None = 0, yes = 1
Hemorrhagic cerebral infarction	X6	No = 0, yes = 1
Large-area cerebral infarction	X7	No = 0, yes = 1
Seizure recurrence after the first episode	Y	No = 0, yes = 1

NIHSS: National Institutes of Health Stroke Scale; EEG: Electroencephalogram.

Table 3 Multivariate analysis of risk factors for seizure recurrence after the first episode.

Factor	β	SE	Wald	P value	OR	95%CI
Age (years)	0.623	0.530	1.384	0.239	1.865	0.660-5.268
NIHSS (points)	0.829	0.505	2.697	0.101	2.290	0.852-6.159
Late-onset seizures	1.131	0.512	4.887	0.027	3.099	1.137-8.445
Abnormal EEG findings	0.713	0.504	1.999	0.157	2.039	0.759-5.477
Cortical involvement	1.507	0.542	7.730	0.005	4.513	1.560-13.057
Hemorrhagic cerebral infarction	1.539	0.617	6.223	0.013	4.659	1.391-15.610
Large-area cerebral infarction	1.007	0.530	3.609	0.057	2.739	0.969-7.743

NIHSS: National Institutes of Health Stroke Scale; EEG: Electroencephalogram.

Predictive value of the risk model for seizure recurrence following the initial episode

The predictive performance of the logistic regression model was evaluated using receiver operating characteristic (ROC) curve analysis. The model yielded an area under the curve (AUC) of 0.732 (95%CI: 0.633-0.831), with an optimal cutoff of 0.732, a specificity of 88.37%, and a sensitivity of 42.11% (Figure 1).

Figure 1 Predictive value of the risk model for seizure recurrence following the initial episode.

Correlation between recurrence-related risk factors and cognitive function

Correlation analysis revealed significant negative correlations between MoCA scores and late-onset seizures (r_pb = -0.410, P < 0.001), cortical involvement (r_pb = -0.262, P = 0.009), and hemorrhagic cerebral infarction (r_pb = -0.225, P = 0.025), indicating greater cognitive impairment associated with these factors (Table 4).

Table 4 Correlation between recurrence-related risk factors and cognitive function.

Correlation	rpb	P value
Late-onset seizures vs MoCA	-0.410	< 0.001
Cortical involvement vs MoCA	-0.262	0.009
Hemorrhagic cerebral infarction vs MoCA	-0.225	0.025

MoCA: Montreal Cognitive Assessment.

Correlation between recurrence-related risk factors and anxiety/depression

Significant positive correlations were found between recurrence-related risk factors and anxiety scores (SAS): Late-onset seizures (r_pb = 0.286, P = 0.004), cortical involvement (r_pb = 0.341, P = 0.001), and hemorrhagic cerebral infarction (r_pb = 0.227, P = 0.024). Similar positive correlations were observed with depression scores (SDS): Late-onset seizures (r_pb = 0.247, P = 0.014), cortical involvement (r_pb = 0.249, P = 0.013), and hemorrhagic cerebral infarction (r_pb = 0.226, P = 0.024), indicating increased anxiety/depression risks (Table 5).

Table 5 Correlation between recurrence-related risk factors and anxiety/depression.

Correlation	rpb	P value
Late-onset seizures vs SAS	0.286	0.004
Cortical involvement vs SAS	0.341	0.001
Hemorrhagic cerebral infarction vs SAS	0.227	0.024
Late-onset seizures vs SDS	0.247	0.014
Cortical involvement vs SDS	0.249	0.013
Hemorrhagic cerebral infarction vs SDS	0.226	0.024

SAS: Self-Rating Anxiety Scale; SDS: Self-Rating Depression Scale.

DISCUSSION

The risk factors for seizure recurrence or epileptic episodes following IS have been extensively investigated. Abe et al[19] identified interictal epileptiform discharges as a key predictor of seizure recurrence in post-stroke epilepsy. Hemorrhagic transformation, cortical lesions, elevated NIHSS scores, and younger age have also been associated with post-IS seizures[20]. Similarly, Alet et al[21] linked the development of post-IS epilepsy to acute symptomatic seizures, cortical involvement, Fazekas scale scores, and modified Rankin Scale scores at discharge. Nonetheless, the factors contributing to recurrent seizures after an initial episode in patients with IS remain to be characterized.

In this study, univariate analysis identified age, NIHSS score, late-onset seizures, EEG abnormalities, cortical involvement, hemorrhagic infarction, and large-area cerebral infarction as significant predictors of post-initial episode seizure recurrence. Of these, late-onset seizures, cortical involvement, and hemorrhagic cerebral infarction remained statistically significant in multivariate analysis. Late-onset seizures, often associated with aberrant glial proliferation, may facilitate neuronal circuit remodeling and formation of hyperexcitable scar tissue, thereby increasing the risk of spontaneous seizures[22,23]. Cortical involvement-given the cortex’s high density of cortical neurons and the low seizure thresholds of axons, pyramidal cells, and astrocytes-predisposes the brain to hyperexcitability and epileptogenesis[24]. Hemorrhagic cerebral infarction may trigger seizures through the irritating effects of blood metabolites (e.g., hemosiderin), which deposit in perilesional brain tissue and excite adjacent neural circuits[25]. Tomari et al[26] identified status epilepticus and younger age as predictors of seizure recurrence following a first episode in both early and late post-stroke epilepsy, respectively. Additionally, Zhang et al[27] reported that interleukin (IL)-1β is independently associated with seizure recurrence after the initial episode in patients with IS, suggesting its potential as a biomarker for predicting recurrence in these patients. Alet et al[21] also reported associations between post-IS epilepsy progression and acute symptomatic seizures, Fazekas scale scores, cortical involvement, and modified Rankin Scale scores at discharge. These findings provide additional support for the present findings. According to the ROC curve analysis in the present study, late-onset seizures, cortical involvement, and hemorrhagic cerebral infarction collectively predicted seizure recurrence with an AUC of 0.732; specificity and sensitivity were 88.37% and 42.11%, respectively, at the optimal cutoff. Correlation analysis revealed that these factors were closely and inversely correlated with cognitive function (assessed using the MoCA) in patients with IS. Late-onset seizures are typically associated with more extensive brain damage, which can impair cognition. Cortical involvement directly affects higher-order brain functions-including memory, attention, and executive processes-while also disrupting neural network connectivity, thereby contributing to cognitive dysfunction. Hemorrhagic cerebral infarction may further exacerbate brain injury through inflammatory responses and oxidative stress, accelerating cognitive deterioration. Furthermore, late-onset seizures, cortical involvement, and hemorrhagic cerebral infarction showed significant positive correlations with anxiety and depression, as assessed by the SAS and SDS, respectively. We postulate that cognitive impairments caused by the aforementioned factors may contribute to the exacerbation of anxiety and depressive symptoms. Previous studies have also investigated the potential associations between cognition, anxiety, and depression in patients with IS. For example, Li et al[28] demonstrated significant correlations between tumor necrosis factor-α, IL-1β, and IL-17 Levels and cognitive impairment, anxiety, and depression in this patient population. Similarly, Wang et al[29] found that reduced serum levels of Jun N-terminal kinase pathway-associated phosphatase are closely associated with anxiety and cognitive dysfunction in patients with acute IS. Caller et al[30] reported that cognitive-behavioral interventions improve the quality-of-life attention-related cognitive performance in adults with epilepsy. Similarly, Zhang et al[31] found that intensive psychological care benefits patients with epilepsy by improving their treatment adherence, quality of life, and emotional stability. These findings suggest that behavioral and emotional support strategies can help optimize therapeutic outcomes and enhance daily functioning.

This study has several limitations. First, although binary classifications (e.g., age ≥ 60 years, NIHSS ≥ 16) helped identify high-risk individuals, the analysis did not account for the potential dose-dependent effects of continuous variables. Future prospective studies using continuous-scale analysis of age and NIHSS, with larger sample sizes, could establish granular risk increments (e.g., per-year or per-point OR changes), thereby enhancing precision in clinical decision-making. Second, the study’s accuracy may be limited by geographical bias due to reliance on a single-institution dataset. Broader, multicenter sampling in future research could help mitigate such bias. Third, the analysis did not differentiate between stroke subtypes (e.g., cardioembolic stroke vs atherosclerotic stroke). Examining these variations could better determine how specific stroke mechanisms independently affect seizure recurrence.

CONCLUSION

Collectively, patients with IS presenting with late-onset seizures, cortical involvement, and hemorrhagic cerebral infarction are at heightened risk of seizure recurrence after the first episode. These factors also demonstrate significant associations with cognitive impairment, anxiety, and depression, suggesting their potential role as biomarkers for neuropsychiatric complications in IS. This underscores their value in monitoring disease progression and informing more effective clinical management strategies. Early identification and intervention addressing these risk factors-including cognitive rehabilitation and psychological support-may significantly improve patient outcomes and quality of life.