Risk Factors and Temporal Patterns of Poststroke Epilepsy across Stroke Subtypes: Insights from a Nationwide Cohort Study in Korea.

INTRODUCTION: We aimed to investigate the risk factors associated with poststroke epilepsy (PSE) among patients with different subtypes of stroke, focusing on age-related risk and time-varying effects of stroke subtypes on PSE development. METHODS: A retrospective, nationwide, population-based cohort study was conducted using Korean National Health Insurance Service-National Sample Cohort data. Patients hospitalized with newly diagnosed stroke from 2005 to 2015 were included and followed up for up to 10 years. The primary outcome was the development of PSE, defined as having a diagnostic code and a prescription for anti-seizure medication. Multivariable Cox proportional hazard models were used to estimate PSE hazard ratios (HRs), and time-varying effects were also assessed. RESULTS: A total of 8,305 patients with ischemic stroke, 1,563 with intracerebral hemorrhage (ICH), and 931 with subarachnoid hemorrhage (SAH) were included. During 10 years of follow-up, 4.6% of patients developed PSE. Among patients with ischemic stroke, significant risk factors for PSE were younger age (HR = 1.47), living in rural areas (HR = 1.35), admission through the emergency room (HR = 1.33), and longer duration of hospital stay (HR = 1.45). Time-varying analysis revealed elevated HRs for ICH and SAH, particularly in the first 2 years following the stroke. The age-specific HRs also showed an increased risk for those under the age of 65, with a noticeable decrease in risk beyond that age. CONCLUSION: The risk of developing PSE varies according to stroke subtype, age, and other demographic factors. These findings underscore the importance of tailored poststroke monitoring and management strategies to mitigate the risk of PSE.

Hypophysitis and central nervous system involvement in association with Sjögren's syndrome along with hypoparathyroidism: a case report.

BACKGROUND: Patients with autoimmune diseases can develop multiple autoimmune diseases over a long period of time, and the presence of more than one autoimmune disease in a single patient is defined as polyautoimmunity. Polyautoimmunity may be clinical evidence that autoimmune diseases share similar immunological mechanisms. CASE PRESENTATION: We report a 30-year-old woman with a unique combination of autoimmune diseases predominantly affecting the central nervous system, with hypoparathyroidism, hypophysitis, medulla involvement, and pons and temporal lobe involvement associated with primary Sjögren's syndrome (pSS), occurring independently over a long period. The patient who had a history of muscle cramps and one seizure incident, presented with vomiting and blurred vision. She was diagnosed with hypophysitis and hypoparathyroidism with calcifications in the basal ganglia and cerebellum. She recovered after four months of corticosteroid treatment for hypophysitis and was started on treatment for hypoparathyroidism. Eight months later, she developed vomiting, hiccups, vertigo, and ataxia with a focal lesion in the medulla. She recovered with immunosuppressive treatment for 2 years. Fifty-eight months after the onset of hypophysitis, she developed diplopia and dry mouth and eyes. MRI showed infiltrative lesions in the left pons and left temporal lobe. Based on positive anti-Sjögren's syndrome-related antigen A antibodies and low unstimulated whole salivary flow rate, pSS was diagnosed. She received corticosteroids and continued mycophenolate mofetil treatment with recovery of neurological symptoms. CONCLUSION: This case highlights the need for long-term follow-up to detect autoimmune disease processes involving various organs.

Validity and Reliability of the Korean Version of Reduced Morningness-Eveningness Questionnaire: Results From a General Population-Based Sample.

BACKGROUND: Chronotype refers to individual variations in diurnal preferences that manifest as everyday behaviors, including sleep patterns. Traditionally, the Horne & Östberg Morningness-Eveningness Questionnaire (MEQ), which comprises of 19 items, has been the standard for determining chronotype. However, its length makes it cumbersome for widespread application. To address this issue, the reduced MEQ (rMEQ), a concise version containing only five items from the MEQ, was developed for a more practical approach to chronotype assessment. This study aimed to evaluate the validity and reliability of Korean version of rMEQ in a sample from the general Korean population. METHODS: The Korean version of the rMEQ comprises of items 1, 7, 10, 18, and 19 of the original MEQ. The validity of the rMEQ was assessed by correlating its scores with those of the MEQ and Munich Chronotype Questionnaire (MCTQ). Its reliability was determined by calculating internal consistency. RESULTS: A total of 3,030 individuals participated in the study, yielding an average rMEQ score of 14.0 ± 3.4. There was a substantial positive correlation between the rMEQ and MEQ scores (r = 0.859, P < 0.001). Furthermore, the rMEQ scores were significantly negatively correlated with the midpoint of sleep on free days corrected for sleep debt as measured by the MCTQ (r = -0.388, P < 0.001), indicating a robust association with chronotype. The internal consistency of rMEQ, measured using Cronbach's alpha, was 0.609. CONCLUSION: This study finds the Korean version of the rMEQ to be a valid and reliable instrument for assessing chronotype in the general population.

MRI-Based Radiomics Approach for Differentiating Juvenile Myoclonic Epilepsy from Epilepsy with Generalized Tonic-Clonic Seizures Alone.

BACKGROUND: The clinical presentation of juvenile myoclonic epilepsy (JME) and epilepsy with generalized tonic-clonic seizures alone (GTCA) is similar, and MRI scans are often perceptually normal in both conditions making them challenging to differentiate. PURPOSE: To develop and validate an MRI-based radiomics model to accurately diagnose JME and GTCA, as well as to classify prognostic groups. STUDY TYPE: Retrospective. POPULATION: 164 patients (127 with JME and 37 with GTCA) patients (age 24.0 ± 9.6; 50% male), divided into training (n = 114) and test (n = 50) sets in a 7:3 ratio with the same proportion of JME and GTCA patients kept in both sets. FIELD STRENGTH/SEQUENCE: 3T; 3D T1-weighted spoiled gradient-echo. ASSESSMENT: A total of 17 region-of-interest in the brain were identified as having clinical evidence of association with JME and GTCA, from where 1581 radiomics features were extracted for each subject. Forty-eight machine-learning combinations of oversampling, feature selection, and classification algorithms were explored to develop an optimal radiomics model. The performance of the best radiomics models for diagnosis and for classification of the favorable outcome group were evaluated in the test set. STATISTICAL TESTS: Model performance measured using area under the curve (AUC) of receiver operating characteristic (ROC) curve. Shapley additive explanations (SHAP) analysis to estimate the contribution of each radiomics feature. RESULTS: The AUC (95% confidence interval) of the best radiomics models for diagnosis and for classification of favorable outcome group were 0.767 (0.591-0.943) and 0.717 (0.563-0.871), respectively. SHAP analysis revealed that the first-order and textural features of the caudate, cerebral white matter, thalamus proper, and putamen had the highest importance in the best radiomics model. CONCLUSION: The proposed MRI-based radiomics model demonstrated the potential to diagnose JME and GTCA, as well as to classify prognostic groups. MRI regions associated with JME, such as the basal ganglia, thalamus, and cerebral white matter, appeared to be important for constructing radiomics models. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

Crystal-clear days and unclear days in migraine: A population-based study.

OBJECTIVE: To investigate crystal-clear days and unclear days in participants with migraine. BACKGROUND: Migraine affects individuals during the headache-free period. Therefore, headache-free days do not indicate migraine symptom-free days. Crystal-clear days can be characterized by days without headache and having minimal or no migraine symptoms. In contrast, days without headache, but with more than minimal migraine symptoms, can be defined as unclear days. METHODS: We used the baseline respondent data set of the Circannual Change in Headache and Sleep study, a nationwide population survey on headache and sleep. This study was a cross-sectional and case-control analysis of longitudinally collected data. The number of crystal-clear days per 30 days was assessed by asking "How many days have you had crystal-clear days without headache during the previous 30 days?". We defined headache-free, but not crystal-clear days, as unclear days. The number of unclear days per 30 days was calculated as follows: 30 - the number of headache days per 30 days - the number of crystal-clear days per 30 days. RESULTS: Of 170 participants with migraine, 165 (97.1%) had unclear days. The numbers of crystal-clear days (median [interquartile range] 20.0 [15.0-25.0] vs. 25.0 [20.0-29.0], p < 0.001) and unclears days (4.0 [0.0-8.0] vs. 1.0 [0.0-7.0], p < 0.001) per 30 days in participants with migraine were significantly lower and higher, respectively, than in those with non-migraine headache. Headache days (incident rate ratio and 95% confidence interval, 0.94 [0.90-0.97], p < 0.001) and weekly average sleep duration (0.95 [0.91-1.00], p = 0.035) were significant factors for crystal-clear days. CONCLUSIONS: The number of crystal-clear days were different from that of headache-free days. Almost all participants with migraine had unclear days. Our findings will facilitate understanding the symptoms and burden of migraine.

Volume change in amygdala enlargement as a prognostic factor in patients with temporal lobe epilepsy: A longitudinal study.

OBJECTIVE: Considering the clinical heterogeneity of temporal lobe epilepsy with amygdala enlargement (TLE-AE), identifying distinct prognostic subgroups of TLE-AE has clinical implications. Until now, baseline volume of the enlarged amygdala (EAV) has consistently failed to predict prognosis in TLE-AE. Based on studies suggesting that patients responsive to antiepileptic drugs (AEDs) exhibit remission of AE on follow-up imaging, we investigated whether reduction rate of EAV is predictive of long-term prognosis in TLE-AE. METHODS: Sixty-one consecutive patients with two separate magnetic resonance imaging (MRI) scans were enrolled. To utilize longitudinally measured biomarkers in prediction, the period beyond the first MRI acquisition was split into two periods: the "observation window" (period between the two MRIs) and "prediction window" (follow-up period beyond the second MRI). Patients were classified according to their AED responsiveness during the observation window, and AED-responsive patients were further subdivided by initial seizure frequency: (a) AED-responsive patients presenting with low-frequency seizures (<5 seizures/3 mo; Group A, n = 25), (b) high-frequency seizures (≥5 seizures/3 mo; Group B, n = 23), and (c) patients with poor initial treatment response (Group C, n = 13). Multivariate logistic regression models were constructed for identification of prognostic factors. Along with factors obtained at baseline, factors derived from the observation window (annual percentage change of EAV [APCEAV] and initial AED responsiveness) were also considered as potential predictors. RESULTS: Favorable initial treatment response and faster volume reduction rate (APCEAV ≤ -5.0%/y) were identified as factors predictive of achieving overall seizure freedom. Among the AED-responsive patients, Group A (low-frequency seizures) showed slower remission of AE and higher rate of seizure recurrence, whereas Group B (high-frequency seizures) exhibited faster remission of AE and lower rate of seizure recurrence. SIGNIFICANCE: Faster recuperation of AE in patients with initial high-frequency seizures may be indicative of seizure-induced changes. As volume reduction rate serves as a prognostic marker in TLE-AE, short-term MRI follow-up may be useful in prognostication.

Family cohesion is differently associated with felt stigma depending on enacted stigma in adults with epilepsy.

PURPOSE: There have been little researches examining the role of family functioning on psychological outcomes in the field of adult epilepsy. We determined whether family functioning is correlated with felt stigma in adults with epilepsy. METHODS: In this cross-sectional study, adults with epilepsy and their caregivers were recruited. Data were collected using the Family Adaptability and Cohesion Evaluation Scale (FACES) III, the Family adaptation, partnership, growth, affection, and resolve (APGAR) questionnaire, the Stigma Scale for Epilepsy (SS-E), the modified questionnaire for episodes of discrimination, and the Beck Depression Inventory. Family functioning was measured by the caregivers. RESULTS: A total of 273 adult patients and their primary caregivers were included. Multivariate logistic analyses showed that family cohesion and excellent family functioning were negatively correlated with felt stigma after controlling for confounding variables. Enacted stigma, depressive symptoms, and university education were also significant. Interaction between enacted stigma and family cohesion on felt stigma was significant (p = 0.049). Family cohesion was negatively correlated with felt stigma only in the patients with enacted stigma (p = 0.011). CONCLUSIONS: Family functioning especially family cohesion may have protective effects against development of felt stigma in adults with epilepsy. Such protecting effects against felt stigma may be different according to enacted stigma. This understanding is helpful for developing effective psychosocial interventions to reduce felt stigma in patients with epilepsy.

A case of dyskinesia after levetiracetam administration.

BACKGROUND: Antiepileptic drug (AED) induced dyskinesia is an unusual manifestation in the medical field. In the previous case reports describing first generation-AED related involuntary movements, the authors suggested that a plausible cause is pharmacokinetic interactions between two or more AEDs. To date, development of dyskinesia after levetiracetam (LEV) has not been reported. CASE PRESENTATION: A 28-year-old woman with a history of brain metastasis from spinal cord glioblastoma presented with several generalized tonic-clonic seizures without restored consciousness. LEV was administered intravenously. Thereafter no more clinical or electroencephalographic seizures were noted on video-EEG monitoring, while chorea movement was observed in her face and bilateral upper limbs. DISCUSSION AND CONCLUSIONS: To our knowledge, there is no case report of dyskinesia after administration of LEV. Considering the temporal relationship and absence of ictal video-EEG findings, we suggest that development of choreoathetosis was closely associated with the undesirable effects of LEV. We propose that dopaminergic system dysregulation and genetic susceptibility might underlie this unusual phenomenon after LEV treatment.

Increased Superoxide Dismutase 2 by Allopregnanolone Ameliorates ROS-Mediated Neuronal Death in Mice with Pilocarpine-Induced Status Epilepticus.

Excessive production of reactive oxygen species (ROS), along with dysfunction of the antioxidant defense system, such as that involving superoxide dismutase (SOD), may play a major role in neuronal death following status epilepticus (SE). Neurosteroids, which are allosteric modulators of the GABAA receptor in cerebral metabolism, have been suggested as being neuroprotective in various animal models; however, their effect to preventing ROS has not been examined. Herein, we investigate the neuroprotective role of allopregnanolone, the prototypical neurosteroid in the brain, in relation to the ROS-mediated neuronal injury. Adult male C57BL/6 mice were subjected to SE and treated with allopregnanolone. Hippocampal cell death was assessed by the terminal deoxynucleotidyl transferase dUTP nick end labeling assay, and ROS production was investigated by in situ detection of oxidized hydroethidine. SOD2 expression was analyzed by both western blot and immunofluorescent staining in the hippocampal subfields. In mice treated with allopregnanolone after SE, hippocampal cell death, DNA fragmentation, oxidative DNA damage, and ROS production were reduced significantly compared to mice subjected to vehicle treatment after SE. Hippocampal SOD2 expression was significantly increased by allopregnanolone. These finding suggest that allopregnanolone plays a neuroprotective role, with not only anticonvulsant but also antioxidant effects, by increasing SOD2 in pilocarpine-induced SE model.

Atrophy of the pedunculopontine nucleus region in patients with sleep-predominant seizures: A voxel-based morphometry study.

Non-rapid eye movement (NREM) sleep increases interictal epileptiform discharges and frequency of seizures, whereas REM sleep suppresses them. The pedunculopontine nucleus (PPN), one of the REM sleep-modulating structures, is postulated to have a potent antiepileptogenic role. We asked if patients with sleep-predominant seizures (SPS) show volume changes in the region of the PPN compared to those with seizures occurring during awake state only (nSPS). The volume of the PPN region was assessed in patients with SPS, those with nSPS, and healthy volunteers, through voxel-based morphometry and automated, nonbiased region of interest (ROI) analysis of T1 magnetic resonance (MR) images. The volume of PPN region was statistically smaller in patients with SPS (n = 33) than in those with nSPS (n = 40) and healthy controls (n = 30) after controlling for covariates. These results suggest that a structural change in the PPN may be associated with sleep-predominant timing of seizure occurrence. Our findings might help understand the intervening pathomechanism that lies between the human sleep-wake cycle and epilepsy.

The effect of recurrent seizures on cognitive, behavioral, and quality-of-life outcomes after 12 months of monotherapy in adults with newly diagnosed or previously untreated partial epilepsy.

PURPOSE: The purpose of this study was to determine whether seizure recurrence has a negative impact on cognition, psychological function, and health-related quality of life (HRQoL) over a 12-month period of monotherapy in adults with newly diagnosed or previously untreated partial epilepsy. METHODS: Seizure freedom (SF) was defined as no seizure recurrence during the 40-week maintenance period of medication. Neuropsychological tests, the Symptom Checklist-90 (SCL-90), and the Quality of Life in Epilepsy-31 (QOLIE-31) were administered at baseline and after 48 weeks of carbamazepine or lamotrigine monotherapy. Seventy-three patients successfully continued treatment until the 48-week follow-up time point. Fifty patients (68.5%) had SF, and the remaining 23 were not seizure-free (NSF). A seizure outcome group-by-time interaction was analyzed using a linear mixed model. RESULTS: A group-by-time interaction was identified for the total QOLIE-31 score (p<0.05) and score on two QOLIE-31 subscales (social function: p<0.001 and seizure worry: p<0.001), with a significant improvement over time only present in the SF group (all p<0.001). There was no significant group-by-time interaction for most cognitive function tests, with the exception of the serial clustering score (p<0.01) and number of recognition hits on the California Verbal Learning Test (p<0.05). Serial clustering did not differ between the SF and NSF groups at baseline, but was significantly more used in the NSF group than in the SF group at 48 weeks (p<0.01). There was no significant group-by-time interaction for any dimension of the SCL-90. CONCLUSION: Recurrent seizures had a significant effect on HRQoL, a subtle effect on cognitive performance, and no effect on psychological symptoms over one year in newly diagnosed or previously untreated adults with partial epilepsy.

Molecular and morphological data reveal hybrid origin of wild Prunus yedoensis (Rosaceae) from Jeju Island, Korea: implications for the origin of the flowering cherry.

PREMISE OF THE STUDY: The subgenus Cerasus of the genus Prunus includes several popular ornamental flowering cherries. Of the hundreds of cultivars, P. ×yedoensis ('Somei-yoshino') is the most popular and familiar cultivar in Korea and Japan and is considered to be of hybrid origin. However, the hybrid origin of P. ×yedoensis and its relationship to wild P. yedoensis, naturally occurring on Jeju Island, Korea, are highly controversial. METHODS: We extensively sampled wild P. yedoensis, cultivated P. ×yedoensis, and numerous individuals from other species belonging to subgenus Cerasus on Jeju Island. Samples from 71 accessions, representing 13 species and one cultivar (P. ×yedoensis), were sequenced for nrDNA ITS/ETS (952 characters) and seven noncoding cpDNA regions (5421 characters) and subjected to maximum parsimony and maximum likelihood analysis. Additive polymorphisms in the ITS/ETS regions were confirmed by cloning amplicons from representative species. KEY RESULTS: The nuclear (ITS/ETS and G3pdh) and cpDNA data, along with several morphological characteristics, provide the first convincing evidence for the hybrid origin of wild P. yedoensis. The maternal parent was determined to be P. spachiana f. ascendens, while the paternal parent was unresolved from the taxonomically complex P. serrulata/P. sargentii clade. The presence of two kinds of ribotypes was confirmed by cloning, and the possible origin of cultivated P. ×yedoensis from wild populations on Jeju Island was also suggested. CONCLUSIONS: Bidirectional and multiple hybridization events were responsible for the origin of wild P. yedoensis. Extensive gene flow was documented in this study, suggesting an important role of reticulate evolution in subgenus Cerasus.

Prophylactic effect of erythropoietin injection to prevent acute mountain sickness: an open-label randomized controlled trial.

This study was performed to evaluate whether increasing hemoglobin before ascent by prophylactic erythropoietin injections prevents acute mountain sickness (AMS). This open-label, randomized, controlled trial involved 39 healthy volunteers with hemoglobin ≤ 15.5 g/dL who were divided randomly into erythropoietin (n=20) and control (n=19) groups. Epoetin alpha 10,000 IU injections were given weekly for four consecutive weeks. On day 1, and 7 days after the last injection (day 29), oxygen saturation (SaO2), and hemoglobin were measured. The subjects departed Seoul on day 30 and arrived at Annapurna base camp (ABC, 4,130 m) on day 34. AMS was diagnosed when headache and Lake Louise score (LLS) of ≥ 3 were present. Immediate descent criteria followed US Army recommendations. Two groups differ in hemoglobin levels on day 29 (15.4 ± 1.1 vs 14.2 ± 1.0 g/dL, P=0.001). At ABC, erythropoietin group had a significantly lower mean LLS, AMS incidence, and number of subjects who met immediate descent criteria. Multiple logistic regression analysis showed that SaO2<87% and control group, but not hemoglobin<15.0 g/dL, independently predicted satisfaction of immediate descent criteria. Erythropoietin-related adverse effects were not observed. In conclusion, erythropoietin may be an effective prophylaxis for AMS.(Clinical Trial Registry Number; NCT 01665781).

Development and Validation of Artificial Intelligence Models for Prognosis Prediction of Juvenile Myoclonic Epilepsy with Clinical and Radiological Features.

Background: Juvenile myoclonic epilepsy (JME) is a common adolescent epilepsy characterized by myoclonic, generalized tonic-clonic, and sometimes absence seizures. Prognosis varies, with many patients experiencing relapse despite pharmacological treatment. Recent advances in imaging and artificial intelligence suggest that combining microstructural brain changes with traditional clinical variables can enhance potential prognostic biomarkers identification. Methods: A retrospective study was conducted on patients with JME at the Severance Hospital, analyzing clinical variables and magnetic resonance imaging (MRI) data. Machine learning models were developed to predict prognosis using clinical and radiological features. Results: The study utilized six machine learning models, with the XGBoost model demonstrating the highest predictive accuracy (AUROC 0.700). Combining clinical and MRI data outperformed models using either type of data alone. The key features identified through a Shapley additive explanation analysis included the volumes of the left cerebellum white matter, right thalamus, and left globus pallidus. Conclusions: This study demonstrated that integrating clinical and radiological data enhances the predictive accuracy of JME prognosis. Combining these neuroanatomical features with clinical variables provided a robust prediction of JME prognosis, highlighting the importance of integrating multimodal data for accurate prognosis.

Long-term outcome of treatment-naïve patients with mesial temporal lobe epilepsy with hippocampal sclerosis: A retrospective study in a single center.

PURPOSE: This study aimed to describe long-term treatment outcomes of treatment-naïve patients with mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS). METHODS: A retrospective review was conducted of treatment-naïve patients with MTLE-HS who visited the Yonsei Epilepsy Clinic from April 2000 to April 2022 and were followed up for at least 2 years. Seizure freedom (SF) was defined as no seizures or auras only for >1 year, and complete SF was defined as no seizures including auras for >1 year. RESULTS: Eighty-four treatment-naïve patients with MTLE-HS with a median follow-up of 122 months were included. Except for one patient who underwent early surgical treatment, of the remaining 83 patients, 31 (37.3 %) achieved SF and remained in remission, 38 (45.8 %) had fluctuations in seizure control, and 14 (16.9 %) never achieved SF. Additionally, 18 (21.7 %) patients achieved complete SF and remained in remission, 42 (50.6 %) showed fluctuations, and 23 (27.7 %) never achieved complete SF. Fifty-three (63.9 %) patients achieved SF and 34 (41.0 %) achieved complete SF at their last visit. Older age at epilepsy onset, male sex, low pretreatment seizure density, history of central nervous system infection before age 5, absence of aura, and fewer antiseizure medications in the final regimen were associated with favorable outcome. Of the 84 patients, 11 (13.1 %) underwent temporal lobectomy. CONCLUSIONS: Medical treatment outcomes in treatment-naïve MTLE-HS were relatively better than previously reported outcomes in MTLE-HS, although frequent fluctuations in seizure control were observed.

Changes in heart rate variability over time from symptom onset of transient global amnesia.

Transient global amnesia (TGA) often involves precipitating events associated with changes in autonomic nervous system (ANS), and heart rate variability (HRV) reflects the ANS state. This study aimed to investigate HRV changes after TGA. A retrospective analysis of HRV included patients diagnosed with TGA between January 2015 and May 2020. The time and frequency domains of HRV were compared among three groups: early (< 1 week after TGA, n = 19), late (1-4 weeks after TGA, n = 38), and healthy control (HC, n = 19). The Pearson's correlation between time and time-domain HRV was also examined. The standard deviation of NN intervals (SDNN) (early, 47.2; late, 35.5; HC, 41.5; p = 0.033) and root mean square of successive RR interval differences (RMSSD) (early, 38.5; late, 21.3; HC, 31.0; p = 0.006) differed significantly among the three groups. Post-hoc analysis showed statistically significant differences only in the early and late groups in both SDNN (p = 0.032) and RMSSD (p = 0.006) values. However, the frequency domain with total power, low-frequency and high-frequency powers, and low-frequency/high-frequency ratio did not differ. SDNN (Pearson correlation coefficient =- 0.396, p = 0.002) and RMSSD (Pearson correlation coefficient =- 0.406, p = 0.002) were negatively correlated with time after TGA. Changes in HRV occurred over time after the onset of TGA, with the pattern showing an increase in the first week and then a decrease within 4 weeks.

Development and Validation of Machine Learning Models to Predict Postoperative Delirium Using Clinical Features and Polysomnography Variables.

Background: Delirium affects up to 50% of patients following high-risk surgeries and is associated with poor long-term prognosis. This study employed machine learning to predict delirium using polysomnography (PSG) and sleep-disorder questionnaire data, and aimed to identify key sleep-related factors for improved interventions and patient outcomes. Methods: We studied 912 adults who underwent surgery under general anesthesia at a tertiary hospital (2013-2024) and had PSG within 5 years of surgery. Delirium was assessed via clinical diagnoses, antipsychotic prescriptions, and psychiatric consultations within 14 days postoperatively. Sleep-related data were collected using PSG and questionnaires. Machine learning predictions were performed to identify postoperative delirium, focusing on model accuracy and feature importance. Results: This study divided the 912 patients into an internal training set (700) and an external test set (212). Univariate analysis identified significant delirium risk factors: midazolam use, prolonged surgery duration, and hypoalbuminemia. Sleep-related variables such as fewer rapid eye movement (REM) episodes and higher daytime sleepiness were also linked to delirium. An extreme gradient-boosting-based classification task achieved an AUC of 0.81 with clinical variables, 0.60 with PSG data alone, and 0.84 with both, demonstrating the added value of PSG data. Analysis of Shapley additive explanations values highlighted important predictors: surgery duration, age, midazolam use, PSG-derived oxygen saturation nadir, periodic limb movement index, and REM episodes, demonstrating the relationship between sleep patterns and the risk of delirium. Conclusions: The artificial intelligence model integrates clinical and sleep variables and reliably identifies postoperative delirium, demonstrating that sleep-related factors contribute to its identification. Predicting patients at high risk of developing postoperative delirium and closely monitoring them could reduce the costs and complications associated with delirium.

Shared comorbidity of depression, migraine, insomnia, and fibromyalgia in a population-based sample.

BACKGROUND: Depression, migraine, insomnia, and fibromyalgia are reportedly comorbidities. Nevertheless, no study has evaluated the comorbidity of all four of these disorders. This study aimed to investigate the comorbidity of these four disorders. METHODS: Cross-sectional analyses were performed using data of the Circannual Change in Headache and Sleep study, an online nationwide population-based survey. Validated questionnaires were used to diagnose the disorders and measure quality of life. The change of clinical characteristics by addition of any comorbidity was analyzed using the Jonckheere-Terpstra trend test. RESULTS: The prevalence rates of depression, migraine, insomnia, and fibromyalgia were 7.2 %, 5.6 %, 13.3 %, and 5.8 %, respectively. Among the 3030 included participants, 494 (16.3 %), 164 (5.4 %), 40 (1.3 %), and 6 (0.2 %) had one, two, three, and four of these conditions, respectively. The number of headache days per 30 days (Jonckheere-Terpstra trend test, p = 0.011) and migraine-related disability (migraine disability assessment score, p = 0.021) increased with an increase in the number of comorbidities but not with the intensity of headache (visual analog scale, p = 0.225) among participants with migraine. The severity of insomnia (Insomnia Severity Index, p < 0.001) and fibromyalgia (fibromyalgia severity score, p = 0.002) increased with additional comorbidities; however, depression (Patient Health Questionnaire-9, p = 0.384) did not show such an increase. LIMITATIONS: The diagnoses of conditions were based on self-reported questionnaires. CONCLUSIONS: The findings confirmed significant comorbidity between depression, migraine, insomnia, and fibromyalgia. Health professionals should be aware of the probable comorbidity of depression, migraine, insomnia, and fibromyalgia when caring for individuals with any of these four disorders.

Development and validation of an artificial intelligence model for the early classification of the aetiology of meningitis and encephalitis: a retrospective observational study.

Background: Early diagnosis and appropriate treatment are essential in meningitis and encephalitis management. We aimed to implement and verify an artificial intelligence (AI) model for early aetiological determination of patients with encephalitis and meningitis, and identify important variables in the classification process. Methods: In this retrospective observational study, patients older than 18 years old with meningitis or encephalitis at two centres in South Korea were enrolled for development (n = 283) and external validation (n = 220) of AI models, respectively. Their clinical variables within 24 h after admission were used for the multi-classification of four aetiologies including autoimmunity, bacteria, virus, and tuberculosis. The aetiology was determined based on the laboratory test results of cerebrospinal fluid conducted during hospitalization. Model performance was assessed using classification metrics, including the area under the receiver operating characteristic curve (AUROC), recall, precision, accuracy, and F1 score. Comparisons were performed between the AI model and three clinicians with varying neurology experience. Several techniques (eg, Shapley values, F score, permutation feature importance, and local interpretable model-agnostic explanations weights) were used for the explainability of the AI model. Findings: Between January 1, 2006, and June 30, 2021, 283 patients were enrolled in the training/test dataset. An ensemble model with extreme gradient boosting and TabNet showed the best performance among the eight AI models with various settings in the external validation dataset (n = 220); accuracy, 0.8909; precision, 0.8987; recall, 0.8909; F1 score, 0.8948; AUROC, 0.9163. The AI model outperformed all clinicians who achieved a maximum F1 score of 0.7582, by demonstrating a performance of F1 score greater than 0.9264. Interpretation: This is the first multiclass classification study for the early determination of the aetiology of meningitis and encephalitis based on the initial 24-h data using an AI model, which showed high performance metrics. Future studies can improve upon this model by securing and inputting time-series variables and setting various features about patients, and including a survival analysis for prognosis prediction. Funding: MD-PhD/Medical Scientist Training Program through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare, Republic of Korea.

Prevalence and impact of visual aura in migraine and probable migraine: a population study.

Visual aura (VA) presents in 98% of cases of migraine with aura. However, data on its prevalence and impact in individuals with migraine and probable migraine (PM) are limited. Data from the nation-wide, population-based Circannual Change in Headache and Sleep Study were collected. Participants with VA rating scale scores ≥ 3 were classified as having VA. Of 3,030 participants, 170 (5.6%) and 337 (11.1%) had migraine and PM, respectively; VA prevalence did not differ between these cohorts (29.4% [50/170] vs. 24.3% [82/337], p = 0.219). Participants with migraine with VA had a higher headache frequency per month (4.0 [2.0-10.0] vs. 2.0 [1.0-4.8], p = 0.014) and more severe cutaneous allodynia (12-item Allodynia Symptom Checklist score; 3.0 [1.0-8.0] vs. 2.0 [0.0-4.8], p = 0.046) than those without VA. Participants with PM with VA had a higher headache frequency per month (2.0 [2.0-8.0] vs. 2.0 [0.6-4.0], p = 0.001), greater disability (Migraine Disability Assessment score; 10.0 [5.0-26.3] vs. 5.0 [2.0-12.0], p < 0.001), and more severe cutaneous allodynia (12-item Allodynia Symptom Checklist score, 2.5 [0.0-6.0] vs. 0.0 [0.0-3.0], p < 0.001) than those without VA. VA prevalence was similar between migraine and PM. Some symptoms were more severe in the presence of VA.