Artificial intelligence performance in clinical neurology queries: the ChatGPT model.

INTRODUCTION: The use of artificial intelligence technology is progressively expanding and advancing in the health and biomedical literature. Since its launch, ChatGPT has rapidly gained popularity and become one of the fastest-growing artificial intelligence applications in history. This study evaluated the accuracy and comprehensiveness of ChatGPT-generated responses to medical queries in clinical neurology. METHODS: We directed 216 questions from different subspecialties to ChatGPT. The questions were classified into three categories: multiple-choice, descriptive, and binary (yes/no answers). Each question in all categories was subjectively rated as easy, medium, or hard according to its difficulty level. Questions that also tested for intuitive clinical thinking and reasoning ability were evaluated in a separate category. RESULTS: ChatGPT correctly answered 141 questions (65.3%). No significant difference was detected in the accuracy and comprehensiveness scale scores or correct answer rates in comparisons made according to the question style or difficulty level. However, a comparative analysis assessing question characteristics revealed significantly lower accuracy and comprehensiveness scale scores and correct answer rates for questions based on interpretations that required critical thinking (p = 0.007, 0.007, and 0.001, respectively). CONCLUSION: ChatGPT had a moderate overall performance in clinical neurology and demonstrated inadequate performance in answering questions that required interpretation and critical thinking. It also displayed limited performance in specific subspecialties. It is essential to acknowledge the limitations of artificial intelligence and diligently verify medical information produced by such models using reliable sources.

A bibliometric evaluation of the top 100 cited articles on ocrelizumab.

BACKGROUND: To analyze the 100 most cited articles (T100) on ocrelizumab using bibliometric methods to determine the current situation and identify research hotspots. METHODS: Articles with "ocrelizumab" in their title were searched for in the Web of Science (WoS) database, identifying 900 articles. After the exclusion criteria were applied, 183 original articles and reviews were obtained. The T100 were selected from among these articles. Data on these articles (author, source, institution, country, scientific category, citation number, and citation density) were analyzed. RESULTS: The number of articles showed a fluctuating upward trend from 2006 to 2022. The total number of citations for the T100 ranged from two to 923. The average number of citations per article was 45.11. The most articles were published in 2021 (n = 31). The "Ocrelizumab versus Placebo in Primary Progressive Multiple Sclerosis" study (T1) was the most cited article among the T100 and had the highest annual average number of citations. T1, T2, and T3 were clinical trials on treating multiple sclerosis. The USA was the most productive and influential research country, with 44 articles. Multiple Sclerosis and Related Disorders was the most productive journal (n = 22). Clinical neurology ranked first among the WoS categories (n = 70). Hauser Stephen and Kappos Ludwig were the most influential authors, with 10 articles each. Biotechnology company Roche was at the top of the publication list, with 36 articles. CONCLUSION: This study's results can give researchers an idea about current developments and research collaborations on ocrelizumab. These data can help researchers easily obtain publications that have become classics. We conclude that the clinical and academic communities have shown a growing interest in ocrelizumab for treating primary progressive multiple sclerosis in recent years.

Digital Danger in Our Pockets: Effect of Smartphone Overuse on Mental Fatigue and Cognitive Flexibility.

ABSTRACT: Smartphones have become essential to life in Western society. This situation reached its peak, especially during the pandemic period. The possibility that smartphone use has negative impact on brain activity has attracted increasing interest among researchers. Medical faculty students were contacted via e-mail and invited to participate in the study. Participants completed the Smartphone Addiction Scale (SAS), the Mental Fatigue Scale (MFS), and the Cognitive Flexibility Inventory (CFI). The total SAS scores of participants with mental fatigue were significantly higher than those of participants without mental fatigue ( p < 0.001). In the smartphone addiction tendency group, the total MFS scores were significantly higher, and the total CFI scores were significantly lower than the scores of the control group ( p < 0.001 for both). In the logistic regression analysis, the total SAS score was associated with the development of mental fatigue ( B coefficient, 0.031, p < 0.001). This study identified potential relationships between smartphone addiction, mental fatigue, and cognitive flexibility. We suggest that smartphone overuse may be an independent risk factor for the development of mental fatigue.

ExHiF: Alzheimer's disease detection using exemplar histogram-based features with CT and MR images.

PURPOSE: The classification of medical images is an important priority for clinical research and helps to improve the diagnosis of various disorders. This work aims to classify the neuroradiological features of patients with Alzheimer's disease (AD) using an automatic hand-modeled method with high accuracy. MATERIALS AND METHOD: This work uses two (private and public) datasets. The private dataset consists of 3807 magnetic resonance imaging (MRI) and computer tomography (CT) images belonging to two (normal and AD) classes. The second public (Kaggle AD) dataset contains 6400 MR images. The presented classification model comprises three fundamental phases: feature extraction using an exemplar hybrid feature extractor, neighborhood component analysis-based feature selection, and classification utilizing eight different classifiers. The novelty of this model is feature extraction. Vision transformers inspire this phase, and hence 16 exemplars are generated. Histogram-oriented gradients (HOG), local binary pattern (LBP) and local phase quantization (LPQ) feature extraction functions have been applied to each exemplar/patch and raw brain image. Finally, the created features are merged, and the best features are selected using neighborhood component analysis (NCA). These features are fed to eight classifiers to obtain highest classification performance using our proposed method. The presented image classification model uses exemplar histogram-based features; hence, it is called ExHiF. RESULTS: We have developed the ExHiF model with a ten-fold cross-validation strategy using two (private and public) datasets with shallow classifiers. We have obtained 100% classification accuracy using cubic support vector machine (CSVM) and fine k nearest neighbor (FkNN) classifiers for both datasets. CONCLUSIONS: Our developed model is ready to be validated with more datasets and has the potential to be employed in mental hospitals to assist neurologists in confirming their manual screening of AD using MRI/CT images.

Quantitative analysis of the olfactory system in pediatric epilepsy: a magnetic resonance imaging study

PURPOSE: Olfactory dysfunction is a well-known complication in epilepsy. Studies have demonstrated that olfactory bulb volume (OBV), olfactory tract length (OTL), and olfactory sulcus depth (OSD) can be reliably evaluated using magnetic resonance imaging (MRI). In this study, we compared the OBV, OTL, and OSD values of children with epilepsy and those of healthy children (controls) of similar age. Our aim was to determine the presence of olfactory dysfunction in children with epilepsy and demonstrate the effects of the epilepsy type and treatment on olfactory function in these patients. METHODS: Cranial MRI images of 36 patients with epilepsy and 108 controls (3-17 years) were evaluated. The patients with epilepsy were divided into groups according to the type of disease and treatment method. Subsequently, OBV and OSD were measured from the coronal section and OTL from the sagittal section. The OBV, OTL, and OSD values were compared between the epilepsy group, subgroups, and controls. RESULTS: OBV was significantly reduced in the children with epilepsy compared with the control group (P < 0.001). No significant difference between the healthy children and those with epilepsy was determined in terms of OTL and OSD. Although OBV was moderately positively correlated with age in the control group (r = 0.561, P < 0.001), it was poorly correlated with age in children with epilepsy (r = 0.393, P = 0.018). CONCLUSION: The results of our study indicate that OBV decreases in children with epilepsy, but epilepsy type and treatment method do not affect OBV, OTL, or OSD (P > 0.05).

Quality analysis of YouTube videos on mechanical thrombectomy for acute ischemic stroke.

OBJECTIVES: Acute ischemic stroke is a leading cause of mortality and long-term disability. Mechanical thrombectomy can effectively treat large artery occlusions. This study aimed to evaluate the quality, reliability, and usefulness of videos on mechanical thrombectomy on YT using quantitative and qualitative analyses. MATERIALS AND METHODS: Video searches were performed by entering the following keywords into the YT search bar: "endovascular thrombectomy," "endovascular treatment of acute stroke," "mechanical thrombectomy," "stroke stent retriever," and "stent retriever thrombectomy." For each search term, the top 35 videos were reviewed. The videos were analyzed by two independent raters using the DISCERN and JAMA scoring systems. Qualitative and quantitative data were recorded for each video. RESULTS: A total of 150 videos were analyzed. The mean DISCERN score was 41.26, and the mean JAMA score was 1.42. Of the videos, 5.3% were categorized as very poor, 33.3% as poor, 44% as fair, 12% as good, and 5.3% as excellent. The videos that included qualitative features, such as clear information, symptomatology, diagnosis, treatment response, prognosis, etiology, epidemiology, diagram, and radiological image, had significantly higher DISCERN and JAMA scores than their counterparts. CONCLUSION: A reliable and useful content is not available for individuals searching for information on mechanical thrombectomy on YT. In this paper, we highlighted key points for content creators to increase the quality and audience engagement statistics of their videos. Information provided in YT videos should be verified using more reliable sources.

Effects of the Lunar Cycle, Seasons and the Meteorological Factors on Peripheral Vertigo.

Objective: This study aimed to determine whether peripheral vertigo is related to the lunar cycle, the seasons, or meteorological factors, in patients who presented to the ear, nose, and throat clinic. Methods: All the patients, diagnosed with vertigo between January 2020 and January 2022, were identified through a retrospective review of our hospital database. The clinical and demographic data of the patients were recorded. Daily humidity (minimum, average, and maximum; %), daily temperature (minimum, average, and maximum; °C), daily average and maximum wind speed (m/min), daily air pressure (minimum and average maximum; hPa) and wind direction (degrees) values were noted. Also, the phases of the moon, i.e., first quarter, new moon, last quarter, and full moon periods were determined. Results: A total of 5,432 patients were included in the study. No statistically significant differences were noted among them with respect to the lunar cycle (p=0.233). However, patient density was found to increase in the winter months. Conclusion: This study concluded that the frequency of diseases is related to meteorological factors, nonetheless, no statistical relationship was found between the lunar cycle and the frequency of patient entries.

Quality and Reliability Analysis of Essential Tremor Disease Information on Social Media: The Study of YouTube.

Background: YouTube has evolved into an important educational tool and information source for patients and their families. YouTube videos have the potential to influence the patients' health-related diagnosis and treatment decision-making. We aimed to evaluate the quality and usefulness of videos on essential tremor available on YouTube using quantitative instruments. Methods: Video searches were performed by typing the keywords 'essential tremor', 'postural tremor', 'action tremor', 'essential tremor hand', and 'essential tremor head' into the YouTube search bar. The top 30 videos were reviewed for each search term. The videos were analyzed by two independent raters using the DISCERN and Global Quality Scale (GQS) scoring systems. Qualitative and quantitative data were recorded for each video. Results: A total of 83 videos were analyzed. The mean DISCERN score was 41.96 out of 75 possible points, and the mean GQS score was 2.97 out of 5 possible points. Twelve percent of the videos were categorized as very poor, 38.6% as poor, 20.5% as fair, 19.3% as good, and 9.6% as excellent. The videos containing qualitative content features, such as clear information, symptoms, etiology, diagnosis, treatment, treatment response, epidemiology, diagrams, and radiological images had significantly higher DISCERN and GQS scores. Discussion: We consider that reliable and useful content is not provided on YouTube for individuals searching for information on essential tremor. We listed the best-quality videos on this topic as a reference for healthcare practitioners and patients. Patients should always verify information provided in such videos through more reliable sources.

Novel nested patch-based feature extraction model for automated Parkinson's Disease symptom classification using MRI images.

OBJECTIVE: Parkinson's disease (PD) is a common neurological disorder with variable clinical manifestations and magnetic resonance imaging (MRI) findings. We propose a handcrafted image classification model that can accurately (i) classify different PD stages, (ii) detect comorbid dementia, and (iii) discriminate PD-related motor symptoms. METHODS: Selected image datasets from three PD studies were used to develop the classification model. Our proposed novel automated system was developed in four phases: (i) texture features are extracted from the non-fixed size patches. In the feature extraction phase, a pyramid histogram-oriented gradient (PHOG) image descriptor is used. (ii) In the feature selection phase, four feature selectors: neighborhood component analysis (NCA), Chi2, minimum redundancy maximum relevancy (mRMR), and ReliefF are used to generate four feature vectors. (iii) Two classifiers: k-nearest neighbor (kNN) and support vector machine (SVM) are used in the classification step. A ten-fold cross-validation technique is used to validate the results. (iv) Eight predicted vectors are generated using four selected feature vectors and two classifiers. Finally, iterative majority voting (IMV) is used to attain general classification results. Therefore, this model is named nested patch-PHOG-multiple feature selectors and multiple classifiers-IMV (NP-PHOG-MFSMCIMV). RESULTS: Our presented NP-PHOG-MFSMCIMV model achieved 99.22, 98.70, and 99.53% accuracies for the collected PD stages, PD dementia, and PD symptoms classification datasets, respectively. SIGNIFICANCE: The obtained accuracies (over 98% for all states) demonstrated the performance of developed NP-PHOG-MFSMCIMV model in automated PD state classification.

Content and quality analysis of videos about multiple sclerosis on social media: The case of YouTube.

BACKGROUND: YouTube (YT) has grown into the largest online video platform across the world. Known to have more than two billion users of all ages, YT also serves as an important educational tool and information source for patients and their families. YT videos have the potential to influence patients' understanding of their diagnoses and treatment decision-making. METHODS: Videos were identified using the keywords "multiple sclerosis," "multiple sclerosis treatment," "relapsing remitting MS," and "central demyelinating disorder" in the YT search bar. For each search term, the top 30 videos were reviewed. The videos were analyzed by two independent raters using the DISCERN and Global Quality Scale (GQS) scoring systems. Qualitative and quantitative data were recorded for each video. RESULTS: A total of 99 videos were analyzed. The mean DISCERN score was 43.44 out of 75 possible points, and the mean Global Quality Scale (GQS) score was 2.77 out of 5 possible points. Of all the videos, 14.1, 29.3, 15.2, and 29.3% were categorized as very poor, poor, moderate, good, and excellent, respectively. Videos that included qualitative features such as clear information; information related to symptomatology, etiology, diagnosis, treatment, treatment response, and epidemiology; and diagrams and radiological images had significantly higher scale scores. Audience engagement parameters were significantly higher for videos containing animation, treatment response, and radiological images. CONCLUSION: We maintain that sufficient, reliable, and useful content is not provided for those seeking information on YT about MS. Everyone seeking information about MS should always verify information provided in YT videos using more reliable sources of information. Video producers should optimize their videos to contain high-quality and reliable data and to attract larger audiences.

Decreased Serum Uric Acid Level as an Indicator of Altered Oxidative Balance in Patients With Migraine.

INTRODUCTION: Migraine is one of the most common neurological diseases. The pathophysiology of migraine has not yet been fully elucidated. There is increasing evidence supporting the relationship between oxidative stress and migraine. METHOD: This is a retrospective, cross-sectional and observational study. The patients were divided into two groups, episodic migraine and chronic migraine. Episodic migraine patients were divided into two subgroups, migraine with aura and migraine without aura. Serum Albumin, total bilirubin, uric acid levels, and migraine clinical findings were obtained from medical records. RESULTS: A total of 181 participants, 88 patients and 93 controls, were included in the study. Serum albumin levels were lower in the patient group than in the control group, they did not reach statistical significance (p=0.082). There was no significant difference between the patient and control groups for total bilirubin levels (p=0.785). Serum uric acid levels in the patient group were found to be significantly lower than in the control group (p<0.001). Measured levels were similar in chronic and episodic migraine groups, and migraine with aura and migraine without aura subgroups. CONCLUSION: We thought this oxidative stress marker may be associated with the presence of migraine, but this is not significant for migraine subtypes and migraine progression.

Retinal Neurovascular Structural Changes in Optical Coherence Tomography and the Relationship between These Changes and White Matter Hyperintensities in Patients with Migraine.

INTRODUCTION: This study aimed to reveal whether retinal nerve fiber layer (RNFL), ganglion cell layer (GCL) inner plexiform layer, and choroidal layer (CL) thicknesses differed in patients with migraine. Optical coherence tomography (OCT) was used to measure these neurovascular structural changes and determine the relationship between these structures and cranial white matter hyperintensities (WMHs). METHODS: This retrospective comparative registry study included a total of 155 individuals aged 18-55 (mean, 33.50 ± 8.34), consisting of 110 migraine patients and 45 healthy controls. RESULTS: RNFLs were thinner in the migraine group than the control group but not to a statistically significant degree. However, in both eyes, peripapillary RNLF thickness in some specific quadrants was found to be significantly thinner in the patient group than the control group. GCLs were significantly thinner in the migraine group than the control group. CLs were significantly thicker in the migraine group than in the control group. There was no significant difference between the OCT parameters of patients with and without WMH. An inverse correlation was found between disease duration and CL thickness. CLs were significantly thicker in patients in attack periods than those in attack-free periods. There was no significant difference between the OCT parameters of the migraine with aura and migraine without aura subgroups. DISCUSSION/CONCLUSIONS: Retinal neural and vascular structures might be affected in migraine sufferers, including those in subgroups. Rebound vasodilation may cause alterations in CL thickness during a migraine attack. Factors other than hypoperfusion may contribute to the pathophysiology responsible for the formation of WMH.

Feed-forward LPQNet based Automatic Alzheimer's Disease Detection Model.

BACKGROUND: Alzheimer's disease (AD) is one of the most commonly seen brain ailments worldwide. Therefore, many researches have been presented about AD detection and cure. In addition, machine learning models have also been proposed to detect AD promptly. MATERIALS AND METHOD: In this work, a new brain image dataset was collected. This dataset contains two categories, and these categories are healthy and AD. This dataset was collected from 1070 subjects. This work presents an automatic AD detection model to detect AD using brain images automatically. The presented model is called a feed-forward local phase quantization network (LPQNet). LPQNet consists of (i) multilevel feature generation based on LPQ and average pooling, (ii) feature selection using neighborhood component analysis (NCA), and (iii) classification phases. The prime objective of the presented LPQNet is to reach high accuracy with low computational complexity. LPQNet generates features on six levels. Therefore, 256 × 6 = 1536 features are generated from an image, and the most important 256 out 1536 features are selected. The selected 256 features are classified on the conventional classifiers to denote the classification capability of the generated and selected features by LPQNet. RESULTS: The presented LPQNet was tested on three image datasets to demonstrate the universal classification ability of the LPQNet. The proposed LPQNet attained 99.68%, 100%, and 99.64% classification accuracy on the collected AD image dataset, the Harvard Brain Atlas AD dataset, and the Kaggle AD dataset. Moreover, LPQNet attained 99.62% accuracy on the Kaggle AD dataset using four classes. CONCLUSIONS: Moreover, the calculated results from LPQNet are compared to other automatic AD detection models. Comparisons, results, and findings clearly denote the superiority of the presented model. In addition, a new intelligent AD detector application can be developed for use in magnetic resonance (MR) and computed tomography (CT) devices. By using the developed automated AD detector, new generation intelligence MR and CT devices can be developed.

Is Increased Intracranial Pressure a Factor in Persistent Headache After Coronavirus Disease 2019?

ABSTRACT: This study aimed to determine pain characteristics in patients with persistent headache after COVID-19 and to investigate the role of increased intracranial pressure (ICP) in the pathogenesis of this headache. This is a case-control study comparing the parameters and measurements indicating increased ICP based on magnetic resonance imaging between COVID-19-diagnosed patients with persistent headache and a control group. Optic nerve sheath diameter (ONSD) and eyeball transverse diameter (ETD) were performed on the left eye of each participant. Seventeen of the patients (53.12%) met the diagnostic criteria for new daily persistent headache. Seven patients (21.87%) had migraine, and eight (25%) had tension headache characteristics. No significant difference was observed between the patient and control groups in terms of the ONSD and ETD values. It is possible that the etiopathogenesis is multifactorial. We consider that future studies that will evaluate ICP measurements in large patient groups can present a different perspective for this subject.

Does levetiracetam use affect Visual Evoked Potentials (VEP) in the treatment of childhood epilepsy?

BACKGROUND: Side effects of antiepileptic drugs vary depending on the drug itself, drug dose and duration of use. One of these side effects is related to vision. METHODS: Patients who had been ordered visual evoked potential (VEP) measurements for various reasons between the dates of 01.10.2017 and 01.10.2019 at a pediatric neurology outpatient clinic and who were on levetiracetam monotherapy for at least six months for the treatment of focal/generalized epilepsy were included in the study and their files were scanned retrospectively (Study Group: SG). Patient files were evaluated for age, gender, dose and duration of levetiracetam use, presence of a family history of epilepsy, EEG result, cranial magnetic resonance imaging and VEP test results and the parameters were recorded. Twenty-four patients of similar age range without epilepsy were included in the study as the control group (CG). RESULTS: Eighteen patients 8 boys (44.4%), 10 girls (54.6%) and 24 healthy controls 9 boys (37.5%), 15 girls (62.5%) were included in the study and control groups, respectively. No statistically significant difference was found when the mean VEP latencies were compared between the patient and control groups for the right (p: 0.451) and left (p: 0.323) eyes. There was a statistically significant difference between the groups, respectively, when VEP amplitudes of the right and left eyes of the SG and CG were compared (p: 0.001; p: 0.001). There is no correlation between levetiracetam dose and duration of treatment and VEP parameters. CONCLUSIONS: The data obtained in this study showed that levetiracetam use affected VEP amplitude outcome but did not affect VEP latency outcome in pediatric patients.

Effect of omalizumab treatment on peripheral nerves in patients with chronic spontaneous urticaria.

Aim: Chronic spontaneous urticaria (CSU) is characterised by itchy, red and raised lesions that appear as an attack without any cause and last for six weeks or longer. Omalizumab is a humanised monoclonal antibody that selectively binds to the Ce3 moiety of circulating IgE and is indicated for the treatment of resistant CSU. In this study, we aimed to investigate whether there was peripheral nervous system involvement in patients with chronic urticaria receiving omalizumab treatment.Methods: Forty-seven patients who were treated with omalizumab for CSU were included in the study. Electrophysiological measurements were performed following a neurological examination before treatment and at three months after omalizumab treatment. In nerve conduction tests, eight different nerves were studied in four extremities (total 16 nerves). During these studies, two motor and two sensory nerves (median and ulnar) in the upper extremities, and two motor (tibial and common peroneal) and two sensory nerves (sural and superficial peroneal) in the lower extremities were analysed.Results: No pathological electrophysiological findings supporting neuropathy were detected in any of the measurements performed before and after treatment. When the nerve conduction velocity, amplitude and latency values ​​of all examined nerves were compared, no significant difference was found between the pre- and post-treatment values.Conclusions: It can be considered that omalizumab has no effect on peripheral nerves, and it is a safe and well tolerated agent in terms of both peripheral nerves and neurological structure.

Comparison of the Olfactory Bulb Volume and the Olfactory Tract Length Between Patients Diagnosed with Essential Tremor and Healthy Controls: Findings in Favor of Neurodegeneration.

Purpose Essential tremor (ET) is the most common movement disorder. In recent years, an increasing number of studies have shown that this disease also has a variety of non-motor findings and may be of a neurodegenerative nature. This study aimed to evaluate the olfactory bulb volume (OBV) and the olfactory tract length (OTL) and to demonstrate possible neurodegeneration in ET patients using magnetic resonance imaging (MRI). Methods The study included 30 ET patients (mean age=29.53±11.82 years) and 30 healthy controls (mean age=30.00±11.68 years). In the cranial MRI examination of both groups, the right, left and total OBV values ​​were measured in mm3 and the right and left OTL values ​​were calculated manually in mm. Results There was no significant difference between the patient and control groups in the measured OBV values, but the OTL value of the patient group was statistically significantly lower than the control group. Conclusion Our study showed that the olfactory system might be involved in ET cases. We think that olfactory dysfunction, one of the non-motor symptoms in ET, can be clearly elucidated through both anatomical and functional studies, to be conducted with larger patient groups.

Plasma urotensin-2 level and Thr21Met but not Ser89Asn polymorphisms of the urotensin-2 gene are associated with migraines.

BACKGROUND: Urotensin-II (U-II) is a peptide recognized by its potent vasoconstrictor activity in many vascular events, however the role of urotensin-II in migraine has not been considered yet. The molecular mechanisms and genetics of migraine have not been fully clarified yet, but it is well-known that vascular changes considerably contribute in pathophysiology of migraine and also its complications. The aim of this study was to analyze the plasma U-II levels along with genotype distributions and allele frequencies for UTS2 Thr21Met and Ser89Asn polymorphisms among the patients with migraine without aura (MWoA). METHODS: One hundred eighty-six patients with MWoA and 171 healthy individuals were included in this study. Plasma U-II levels were measured in attack free period. The genotype and allele frequencies for the Thr21Met (T21M) and Ser89Asn (S89N) polymorphisms in the UTS2 gene were analyzed. RESULTS: Plasma U-II levels were significantly higher in MWoA patients (p = 0.002). We detected a significant association between the T21M polymorphism in the UTS2 gene and migraine (53.8 % in patients, 40.4 % in controls, p = 0.035), but not with S89N polymorphism (p = 0.620). A significant relationship was found between U-II levels and MIDAS score (ß = 0.508, p = 0.001). CONCLUSION: Our study suggests that U-II may play a role in migraine pathogenesis; also Thr21Met polymorphism was associated with the risk of migraine disease. Further studies are needed for considering the role of U-II in migraine pathophysiology and for deciding if UTS2 gene may be a novel candidate gene in migraine cases.