Heterozygous mutations in the C-terminal domain of COPA underlie a complex autoinflammatory syndrome.

Mutations in the N-terminal WD40 domain of coatomer protein complex subunit α (COPA) cause a type I interferonopathy, typically characterized by alveolar hemorrhage, arthritis, and nephritis. We described 3 heterozygous mutations in the C-terminal domain (CTD) of COPA (p.C1013S, p.R1058C, and p.R1142X) in 6 children from 3 unrelated families with a similar syndrome of autoinflammation and autoimmunity. We showed that these CTD COPA mutations disrupt the integrity and the function of coat protein complex I (COPI). In COPAR1142X and COPAR1058C fibroblasts, we demonstrated that COPI dysfunction causes both an anterograde ER-to-Golgi and a retrograde Golgi-to-ER trafficking defect. The disturbed intracellular trafficking resulted in a cGAS/STING-dependent upregulation of the type I IFN signaling in patients and patient-derived cell lines, albeit through a distinct molecular mechanism in comparison with mutations in the WD40 domain of COPA. We showed that CTD COPA mutations induce an activation of ER stress and NF-κB signaling in patient-derived primary cell lines. These results demonstrate the importance of the integrity of the CTD of COPA for COPI function and homeostatic intracellular trafficking, essential to ER homeostasis. CTD COPA mutations result in disease by increased ER stress, disturbed intracellular transport, and increased proinflammatory signaling.

Reversible Hypothalamic Obesity in a Girl with Suprasellar Tuberculoma.

INTRODUCTION: Suprasellar tuberculoma are extremely rare in children and most of those patients present with headache, vomiting, visual disturbances, and hypofunction of the pituitary gland. In this case report, we present a girl with tuberculosis, who developed significant weight gain in combination with pituitary dysfunction, which recovered after antituberculosis treatment. CASE PRESENTATION: An 11-year old girl presented with headache, fever and anorexia that progressively evolved into an encephalopathic status with cranial nerves III and VI paresis. Brain MRI showed meningeal contrast capture along cranial nerves II (including optic chiasm), III, V and VI bilaterally and multiple contrast enhancing brain parenchyma lesions. Tuberculin skin test was negative but interferon-gamma release assay was positive. The clinical and radiological working diagnosis was consistent with tuberculous meningoencephalitis. Pulse corticosteroids for 3 days and quadruple antituberculosis therapy were started and the girl demonstrated obvious improvement of her neurological symptoms. However, after a few months of therapy she developed remarkable weight gain (+20 kg in 1 year) and growth arrest. Her hormone profile revealed insulin resistance (homeostasis model assessment-estimated insulin resistance [HOMA-IR] 6.8) despite putative growth hormone deficiency (circulating insulin-like growth factor-I [IGF-I] 104 µg/L [-2.4 SD]). Follow-up brain MRI showed a decrease in basal meningitis, but increased parenchymal lesions in the suprasellar region extending medially into the nucleus lentiformis, with now a voluminous tuberculoma at this site. Antituberculosis treatment was continued for a total of 18 months. The patient improved clinically, she regained her pre-illness Body Mass Index (BMI) SDS and her growth rate increased slightly. On the hormonal side, disappearance of insulin resistance (HOMA-IR 2.5) and an increase in IGF-I (175 µg/L, -1.4 SD) was noted, and her last brain MRI showed a remarkable volume reduction of the suprasellar tuberculoma. CONCLUSION: Suprasellar tuberculoma can have a very dynamic presentation during the active stage of the disease, which can be reversed by prolonged antituberculosis treatment. Previous studies showed that the tuberculous process can also cause long term and irreversible changes in the hypothalamic-pituitary axis. Prospective studies are however needed in the pediatric population to know the exact incidence and type of pituitary dysfunction.

Outcome of partial agenesis of corpus callosum.

BACKGROUND: The diagnosis of corpus callosum anomalies by prenatal ultrasound has improved over the last decade because of improved imaging techniques, scanning skills, and the routine implementation of transvaginal neurosonography. OBJECTIVE: Our aim was to investigate all cases of incomplete agenesis of the corpus callosum and to report the sonographic characteristics, the associated anomalies, and the perinatal outcomes. STUDY DESIGN: We performed a retrospective analysis of cases from January 2007 to December 2017 with corpus callosum anomalies, either referred for a second opinion or derived from the prenatal ultrasound screening program in a single tertiary referral center. Cases with complete agenesis were excluded from the analysis. Standardized investigation included a detailed fetal ultrasound including neurosonogram, fetal karyotyping (standard karyotype or array comparative genomic hybridization) and fetal magnetic resonance imaging. The pregnancy outcome was collected, and pathologic investigation in case of termination of the pregnancy or fetal or neonatal loss was compared with the prenatal findings. The pregnancy and fetal or neonatal outcomes were reported. The neurologic assessment was conducted by a pediatric neurologist using the Bayley Scales of Infant Development-II and the standardized Child Development Inventory when the Bayley investigation was unavailable. RESULTS: Corpus callosum anomalies were diagnosed in 148 cases during the study period, 62 (41.9%) of which were excluded because of complete agenesis, and 86 fetuses had partial agenesis (58.1%). In 20 cases, partial agenesis (23.2%) was isolated, whereas 66 (76.7%) presented with different malformations among which 29 cases (43.9%) were only central nervous system lesions, 21 cases (31.8%) were non-central nervous system lesions, and 16 cases (24.3%) had a combination of central nervous system and non-central nervous system lesions. The mean gestational age at diagnosis for isolated and non-isolated cases was comparable (24.29 [standard deviation, 5.05] weeks and 24.71 [standard deviation, 5.35] weeks, respectively). Of the 86 pregnancies with partial agenesis, 46 patients opted for termination of the pregnancy. Neurologic follow-up data were available for 35 children. The overall neurologic outcome was normal in 21 of 35 children (60%); 3 of 35 (8.6%) showed mild impairment and 6 of 35 (17.1%) showed moderate impairment. The remaining 5 of 35 (14.3%) had severe impairment. The median duration of follow-up for the isolated form was 45.6 months (range, 36-52 months) and 73.3 months (range, 2-138 months) for the nonisolated form. CONCLUSION: Partial corpus callosum agenesis should be accurately investigated by neurosonography and fetal magnetic resonance imaging to describe its morphology and the associated anomalies. Genetic anomalies are frequently present in nonisolated cases. Efforts must be taken to improve ultrasound diagnosis of partial agenesis and to confirm its isolated nature to enhance parental counseling. Although 60% of children with prenatal diagnosis of isolated agenesis have a favorable prognosis later in life, they often have mild to severe disabilities including speech disorders at school age and behavior and motor deficit disorders that can emerge at a later age.

Wearable detection of tonic seizures in childhood epilepsy: An exploratory cohort study.

OBJECTIVE: To investigate the performance of a multimodal wearable device for the offline detection of tonic seizures (TS) in a pediatric childhood epilepsy cohort, with a focus on patients with Lennox-Gastaut syndrome. METHODS: Parallel with prolonged video-electroencephalography (EEG), the Plug 'n Patch system, a multimodal wearable device using the Sensor Dot and replaceable electrode adhesives, was used to detect TS. Multiple biosignals were recorded: behind-the-ear EEG, surface electromyography, electrocardiography, and accelerometer/gyroscope. Biosignals were annotated blindly by a neurologist. Seizure characteristics were described, and performance was assessed by sensitivity, positive predictive value (PPV), F1 score, and false alarm rate (FAR) per hour. Performance was compared to seizure diaries kept by the caretaker. RESULTS: Ninety-nine TS were detected in 13 patients. Seven patients (54%) had Lennox-Gastaut syndrome and six patients (46%) had other forms of (developmental) epileptic encephalopathies or drug-resistant epilepsy. All but one patient had intellectual disability. Overall sensitivity was 41%, with a PPV of 9%, an F1 score of 14%, and a median FAR per hour of 0.75. Performance increased to an F1 score of 66% for nightly seizures lasting at least 10 s (sensitivity 66%, PPV 66%) and 71% for nightly seizures lasting at least 20 s (sensitivity 62%, PPV 82%). For these seizures there were no false alarms in 10 of 13 patients. Sensitivity of seizure diaries reached a maximum of 52% for prolonged (≥20 s) nightly seizures, even though caretakers slept in the same room. SIGNIFICANCE: We showed that it is feasible to use a multimodal wearable device with multiple adhesive sites in children with epilepsy and intellectual disability. For prolonged nightly seizures, offline manual detection of TS outperformed seizure diaries. The recognition of seizure-specific signatures using multiple modalities can help in the development of automated TS detection algorithms.

A novel GABRG2 variant in Sunflower syndrome: A case report and video EEG monitoring.

OBJECTIVE: Sunflower syndrome is a unique photosensitive epilepsy, characterized by heliotropism and stereotyped seizures associated with handwaving. These handwaving events (HWE) are thought to be an ictal phenomenon, although current data are contrasting. Photosensitive epilepsy occurs in 2%-5% of the epilepsy forms and several pathogenic gene variants have been associated with photosensitive epilepsy. However, the genetic etiology of Sunflower syndrome remains unknown. Antiseizure medications (ASM) efficacious in treating photosensitive epilepsy are valproic acid (VPA) and levetiracetam (LEV) although some forms, such as Sunflower syndrome, can be drug-resistant. METHODS AND RESULTS: Here, we report an 8-year-old boy with an early onset of episodes of HWE that was initially categorized as behavioral problems for which risperidone was started. However, the medical history was suggestive of Sunflower syndrome, and subsequent video EEG showed focal mostly temporal and frontotemporal (right and left) epileptiform activity and confirmed the epileptic nature of the HWE. Thus, VPA was started and initially led to seizure frequency reduction. Molecular analyses showed a pathogenic variant in GABRG2 (c.1287G>A p.(Trp429Ter)), which has been associated with photosensitive and generalized epilepsy. SIGNIFICANCE: Overall, clinicians worldwide should be cautious by interpreting HWE and/or other tic-like movements, since an epileptic origin cannot be ruled out. A prompt and correct diagnosis can be made by performing a video EEG early on in the diagnostic process when epileptic seizures are part of the differential diagnosis. Even though the genetic etiology of Sunflower syndrome remains poorly understood, this constellation supports further genetic testing since the detection of a pathogenic variant can help in making correct decisions regarding ASM management.

A Narrative Review of the Neurological Manifestations of Human Adenosine Deaminase 2 Deficiency.

Deficiency of human adenosine deaminase type 2 (DADA2) is a complex systemic autoinflammatory disorder characterized by vasculopathy, immune dysregulation, and hematologic abnormalities. The most notable neurological manifestations of DADA2 are strokes that can manifest with various neurological symptoms and are potentially fatal. However, neurological presentations can be diverse. We here present a review of the neurological manifestations of DADA2 to increase clinical awareness of DADA2 as the underlying diagnosis. We reviewed all published cases of DADA2 from 1 January 2014 until 19 July 2022 found via PubMed. A total of 129 articles describing the clinical features of DADA2 were included in the analysis. Six hundred twenty-eight patients diagnosed with DADA2 were included in the review. 50.3% of patients had at least signs of one reported neurological event, which was the initial or sole manifestation in 5.7% and 0.6%, respectively. 77.5% of patients with neurological manifestations had at least signs of one cerebrovascular accident, with lacunar strokes being the most common and 35.9% of them having multiple stroke episodes. There is a remarkable predilection for the brain stem and deep gray matter, with 37.3% and 41.6% of ischemic strokes, respectively. Other neurological involvement included neuropathies, focal neurological deficits, ophthalmological findings, convulsions, and headaches. In summary, neurological manifestations affect a significant proportion of patients with DADA2, and the phenotype is broad. Neurological manifestations can be the first and single manifestation of DADA2. Therefore, stroke, encephalitis, posterior reversible encephalopathy syndrome, mononeuropathy and polyneuropathy, and Behçet's disease-like presentations should prompt the neurologist to exclude DADA2, especially but not only in childhood.

Fetal-onset Alexander disease with radiological-neuropathological correlation.

Alexander disease is a leukodystrophy caused by mutations in the GFAP gene, primarily affecting the astrocytes. This report describes the prenatal and post-mortem neuroimaging findings in a case of genetically confirmed, fetal-onset Alexander disease with pathological correlation after termination of pregnancy. The additional value of fetal brain magnetic resonance imaging in the third trimester as a complementary evaluation tool to neurosonography is shown for suspected cases of fetal-onset Alexander disease. Diffuse signal abnormalities of the periventricular white matter in association with thickening of the fornix and optic chiasm can point towards the diagnosis. Furthermore, the presence of atypical imaging findings such as microcephaly and cortical folding abnormalities in this case broadens our understanding of the phenotypic variability of Alexander disease.

A multi-task and multi-channel convolutional neural network for semi-supervised neonatal artefact detection.

Objective. Automated artefact detection in the neonatal electroencephalogram (EEG) is crucial for reliable automated EEG analysis, but limited availability of expert artefact annotations challenges the development of deep learning models for artefact detection. This paper proposes a semi-supervised deep learning approach for artefact detection in neonatal EEG that requires few labelled data by training a multi-task convolutional neural network (CNN).Approach. An unsupervised and a supervised objective were jointly optimised by combining an autoencoder and an artefact classifier in one multi-output model that processes multi-channel EEG inputs. The proposed semi-supervised multi-task training strategy was compared to a classical supervised strategy and other existing state-of-the-art models. The models were trained and tested separately on two different datasets, which contained partially annotated multi-channel neonatal EEG. Models were evaluated using the F1-statistic and the relevance of the method was investigated in the context of a functional brain age (FBA) prediction model.Main results. The proposed multi-task and multi-channel CNN methods outperformed state-of-the-art methods, reaching F1 scores of 86.2% and 95.7% on two separate datasets. The proposed semi-supervised multi-task training strategy was shown to be superior to a classical supervised training strategy when the amount of labels in the dataset was artificially reduced. Finally, we found that the error of a brain age prediction model correlated with the amount of automatically detected artefacts in the EEG segment.Significance. Our results show that the proposed semi-supervised multi-task training strategy can train CNNs successfully even when the amount of labels in the dataset is limited. Therefore, this method is a promising semi-supervised technique for developing deep learning models with scarcely labelled data. Moreover, a correlation between the error of FBA estimates and the amount of detected artefacts in the corresponding EEG segments indicates the relevance of artefact detection for robust automated EEG analysis.

Partial wavelet coherence as a robust method for assessment of neurovascular coupling in neonates with hypoxic ischemic encephalopathy.

In neonates with hypoxic ischemic encephalopathy, the computation of wavelet coherence between electroencephalogram (EEG) power and regional cerebral oxygen saturation (rSO2) is a promising method for the assessment of neurovascular coupling (NVC), which in turn is a promising marker for brain injury. However, instabilities in arterial oxygen saturation (SpO2) limit the robustness of previously proposed methods. Therefore, we propose the use of partial wavelet coherence, which can eliminate the influence of SpO2. Furthermore, we study the added value of the novel NVC biomarkers for identification of brain injury compared to traditional EEG and NIRS biomarkers. 18 neonates with HIE were monitored for 72 h and classified into three groups based on short-term MRI outcome. Partial wavelet coherence was used to quantify the coupling between C3-C4 EEG bandpower (2-16 Hz) and rSO2, eliminating confounding effects of SpO2. NVC was defined as the amount of significant coherence in a frequency range of 0.25-1 mHz. Partial wavelet coherence successfully removed confounding influences of SpO2 when studying the coupling between EEG and rSO2. Decreased NVC was related to worse MRI outcome. Furthermore, the combination of NVC and EEG spectral edge frequency (SEF) improved the identification of neonates with mild vs moderate and severe MRI outcome compared to using EEG SEF alone. Partial wavelet coherence is an effective method for removing confounding effects of SpO2, improving the robustness of automated assessment of NVC in long-term EEG-NIRS recordings. The obtained NVC biomarkers are more sensitive to MRI outcome than traditional rSO2 biomarkers and provide complementary information to EEG biomarkers.

Cerebral oxygenation and body position in the preterm infant: A systematic review and meta-analysis.

AIM: After preterm birth, supine head midline position is supported for stable cerebral blood flow (CBF) and prevention of intraventricular haemorrhage (IVH), while prone position supports respiratory function and enables skin-to-skin care. The prone compared to supine position could lead to a change in near-infrared derived cerebral tissue oxygen saturation (rScO2), which is a surrogate for cerebral blood flow (CBF). By monitoring rScO2 neonatologists aim to stabilise CBF during intensive care and prevent brain injury. In this systematic review and meta-analysis, we investigate the effect of the body position on rScO2. METHODS: A comprehensive literature search was performed to identify all trials that included preterm infants in the first 2 weeks after birth and compared rScO2 in the prone versus supine head in midline position of the infant. A meta-analysis, including two subgroup analyses based on postnatal age (PNA) and gestational age (GA), was performed. RESULTS: Six observational cohort studies were included. In the second, but not the first week after birth, a significant higher rScO2 in the prone position was found with a mean difference of 1.97% (95% CI 0.87-3.07). No rScO2 difference was observed between positions in the extremely preterm nor the preterm group. CONCLUSION: No consistent evidence was found that body position influences rScO2 in the first 2 weeks after preterm birth. Subgroup analysis suggests that in the second week after birth, the prone position might result in higher cerebral rScO2 than the supine position with head in midline. Multiple factors determine the best body position in preterms.

Assessing Neurovascular Coupling Using Wavelet Coherence in Neonates with Asphyxia.

Brain monitoring is important in neonates with asphyxia in order to assess the severity of hypoxic ischaemic encephalopathy (HIE) and identify neonates at risk of adverse neurodevelopmental outcome. Previous studies suggest that neurovascular coupling (NVC), quantified as the interaction between electroencephalography (EEG) and near-infrared spectroscopy (NIRS)-derived regional cerebral oxygen saturation (rSO2) is a promising biomarker for HIE severity and outcome. In this study, we explore how wavelet coherence can be used to assess NVC. Wavelet coherence was computed in 18 neonates undergoing therapeutic hypothermia in the first 3 days of life, with varying HIE severities (mild, moderate, severe). We compared two pre-processing methods of the EEG prior to wavelet computation: amplitude integrated EEG (aEEG) and EEG bandpower. Furthermore, we proposed average real coherence as a biomarker for NVC. Our results indicate that NVC as assessed by wavelet coherence between EEG bandpower and rSO2 can be a valuable biomarker for HIE severity in neonates with peripartal asphyxia. More specifically, average real coherence in a very low frequency range (0.21-0.83 mHz) tends to be high (positive) in neonates with mild HIE, low (positive) in neonates with moderate HIE, and negative in neonates with severe HIE. Further investigation in a larger patient cohort is needed to validate our findings.

Child Neurology: Familial Hemophagocytic Lymphohistiocytosis Underlying Isolated CNS Inflammation.

Encephalitis and encephalopathy in children represent a diagnostic challenge. We describe a patient with relapsing encephalitis in whom the differential diagnosis included acute disseminated encephalomyelitis, human herpesvirus 6 encephalitis, and hemophagocytic lymphohistiocytosis (HLH). Because of its rarity, HLH is often overlooked as a differential diagnosis in encephalitis, especially in the isolated CNS forms. As this case illustrates, inborn errors of immunity can underlie isolated encephalitis and should be included in the differential diagnosis of these presentations.

Automated detection and removal of flat line segments and large amplitude fluctuations in neonatal electroencephalography.

Background: Artefact removal in neonatal electroencephalography (EEG) by visual inspection generally depends on the expertise of the operator, is time consuming and is not a consistent pre-processing step to the pipeline for the automated EEG analysis. Therefore, there is the need for the automated detection and removal of artefacts in neonatal EEG, especially of distinct and predominant artefacts such as flat line segments (mainly caused by instrumental error where contact between electrodes and head box is lost) and large amplitude fluctuations (related to neonatal movements). Method: A threshold-based algorithm for the automated detection and removal of flat line segments and large amplitude fluctuations in neonatal EEG of infants at term-equivalent age is developed. The algorithm applies thresholds to the absolute second difference, absolute amplitude, absolute first difference and the ratio between the frequency content above 50 Hz and the frequency content across all frequencies. Results: The algorithm reaches a median accuracy of 0.91, a median hit rate of 0.91 and a median false discovery rate of 0.37. Also, a significant improvement (≈10%) in the performance of a four-stage sleep classifier is observed after artefact removal with the proposed algorithm as compared to before its application. Significance: An automated artefact removal method contributes to the pipeline of automated EEG analysis. The proposed algorithm has shown to have good performance and to be effective in neonatal EEG applications.

Brain overgrowth associated with megalencephaly-capillary malformation syndrome causing progressive Chiari and syringomyelia.

Background: Megalencephaly-capillary malformation (M-CM) syndrome is a rare overgrowth syndrome characterized by macrocephaly, port-wine stains, asymmetric brain growth, hydrocephalus, and developmental delay. Cerebellar tonsil herniation is often seen, but rarely with syringomyelia. Case Description: A newborn with M-CM syndrome developed a progressive Chiari malformation type I (CM-I) with syringomyelia. At 4 months, he was treated for subdural hematomas, while at 10 months, he required a shunt for hydrocephalus. At 16 years of age, he newly presented a left hemiparesis and ataxia. Notably, successive volumetric measurements of the posterior fossa/cerebellum showed disproportionate cerebellar growth over time that correlated with the appearance of a CM-I. Following a suboccipital craniectomy with C1-laminectomy and duraplasty, he neurologically improved. Conclusion: M-CM with CM-I and syringomyelia rarely present together. Here, we treated an infant with M-CM who developed a progressive CM-I malformation and syringomyelia reflecting disproportionate growth of the cerebellum/posterior fossa over a 16-year period.

Automated detection of absence seizures using a wearable electroencephalographic device: a phase 3 validation study and feasibility of automated behavioral testing.

OBJECTIVE: Our primary goal was to measure the accuracy of fully automated absence seizure detection, using a wearable electroencephalographic (EEG) device. As a secondary goal, we also tested the feasibility of automated behavioral testing triggered by the automated detection. METHODS: We conducted a phase 3 clinical trial (NCT04615442), with a prospective, multicenter, blinded study design. The input was the one-channel EEG recorded with dry electrodes embedded into a wearable headband device connected to a smartphone. The seizure detection algorithm was developed using artificial intelligence (convolutional neural networks). During the study, the predefined algorithm, with predefined cutoff value, analyzed the EEG in real time. The gold standard was derived from expert evaluation of simultaneously recorded full-array video-EEGs. In addition, we evaluated the patients' responsiveness to the automated alarms on the smartphone, and we compared it with the behavioral changes observed in the clinical video-EEGs. RESULTS: We recorded 102 consecutive patients (57 female, median age = 10 years) on suspicion of absence seizures. We recorded 364 absence seizures in 39 patients. Device deficiency was 4.67%, with a total recording time of 309 h. Average sensitivity per patient was 78.83% (95% confidence interval [CI] = 69.56%-88.11%), and median sensitivity was 92.90% (interquartile range [IQR] = 66.7%-100%). The average false detection rate was .53/h (95% CI = .32-.74). Most patients (n = 66, 64.71%) did not have any false alarms. The median F1 score per patient was .823 (IQR = .57-1). For the total recording duration, F1 score was .74. We assessed the feasibility of automated behavioral testing in 36 seizures; it correctly documented nonresponsiveness in 30 absence seizures, and responsiveness in six electrographic seizures. SIGNIFICANCE: Automated detection of absence seizures with a wearable device will improve seizure quantification and will promote assessment of patients in their home environment. Linking automated seizure detection to automated behavioral testing will provide valuable information from wearable devices.

A Deep Shared Multi-Scale Inception Network Enables Accurate Neonatal Quiet Sleep Detection With Limited EEG Channels.

In this paper, we introduce a new variation of the Convolutional Neural Network Inception block, called Sinc, for sleep stage classification in premature newborn babies using electroencephalogram (EEG). In practice, there are many medical centres where only a limited number of EEG channels are recorded. Existing automated algorithms mainly use multi-channel EEGs which perform poorly when fewer numbers of channels are available. The proposed Sinc utilizes multi-scale analysis to place emphasis on the temporal EEG information to be less dependent on the number of EEG channels. In Sinc, we increase the receptive fields through Inception while by additionally sharing the filters that have similar receptive fields, overfitting is controlled and the number of trainable parameters dramatically reduced. To train and test this model, 96 longitudinal EEG recordings from 26 premature infants are used. The Sinc-based model significantly outperforms state-of-the-art neonatal quiet sleep detection algorithms, with mean Kappa 0.77 ± 0.01 (with 8-channel EEG) and 0.75 ± 0.01 (with a single bipolar channel EEG). This is the first study using Inception-based networks for EEG analysis that utilizes filter sharing to improve efficiency and trainability. The suggested network can successfully detect quiet sleep stages with even a single EEG channel making it more practical especially in the hospital setting where cerebral function monitoring is predominantly used.

Antiseizure medications and thyroid hormone homeostasis: Literature review and practical recommendations.

Thyroid hormones play an essential role in central nervous system development, normal physiological brain function, and repair mechanisms. On one hand, thyroid hormone alterations influence cortical excitability, and on the other hand antiseizure medications (ASMs) are associated with alterations in thyroid hormone metabolism. Although this interaction has long been described, and epilepsy is a common and chronic neurological disease, studies describing the interplay are often small and retrospective. We performed a systematic review of the current literature on epilepsy, ASMs, and thyroid hormone metabolism according to PRISMA guidelines. Forty-seven studies were included. Most studies were retrospective cross-sectional studies (n = 25) and investigated thyroid function alterations in patients on older ASMs such as phenobarbital, phenytoin, carbamazepine, and valproate. Overall, almost one third of patients with epilepsy had thyroid hormone alterations, especially patients on valproate (25%) and carbamazepine (10%-25%). Studies with patients receiving polytherapy are scarce, but reported a higher risk for hypothyroidism in patients with older age (p = .004), female sex (p = .014), longer duration of epilepsy (p = .001), intractable epilepsy (p = .009), and polytherapy. Studies on newer ASMs are also limited, and further studies on an interplay with thyroid hormone homeostasis are essential to improve the care for epilepsy patients. ASMs are associated with alterations in thyroid hormone metabolism. Thyroid function monitoring is indicated in patients on ASMs, especially those with refractory epilepsy and those on polytherapy. We provide a practical guidance for thyroid function monitoring for the clinician taking care of patients on ASMs.