Direct bilirubin: A predictor of hematoma expansion after intracerebral hemorrhage.

BACKGROUND: Previous evidence demonstrated that several biomarkers involved in the pathological process of coagulation/hemostasis dysfunction, impairment of brain vascular integrity and inflammation are associated with hematoma expansion (HE) after intracerebral hemorrhage (ICH). We aimed to explore whether there were unreported laboratory biomarkers associated with HE that were readily and commonly available in clinical practice. METHODS: We retrospectively analyzed consecutive acute ICH patients from 2012 to 2020 with admission laboratory tests and baseline and follow-up computed tomography (CT) scans. Univariate and multivariate regression analyses were used to evaluate associations between conventional laboratory indicators and HE. The results were verified in a prospective validation cohort. The relationship of candidate biomarker and 3-month outcomes was also investigated and mediation analysis was undertaken to determine causal associations among candidate biomarker, HE and outcome. RESULTS: Of 734 ICH patients, 163 (22.2%) presented HE. Among the included laboratory indicators, higher direct bilirubin (DBil) was associated with HE (adjusted odds ratio [OR] of per 1.0 µmol/L change 1.082; 95% confidence interval [CI] 1.011-1.158). DBil >5.65 µmol/L was a predictor of HE in validation cohort. Higher DBil was also associated with poor 3-month outcomes. The mediation analysis indicated that the association of higher DBil and poor outcomes was partially mediated by HE. CONCLUSIONS: DBil is a predictor of HE and poor 3-month outcomes after ICH. DBil's metabolic process and involvement in the pathological mechanism of HE are likely to contribute to the association between DBil and HE. Interventions targeting DBil to improve post-ICH prognosis may be meaningful and worthy of further exploration.

A 6-month prognostic nomogram incorporating hemoglobin level for intracerebral hemorrhage in younger adults.

OBJECTIVE: Intracerebral hemorrhage (ICH) is the second most common subtype of stroke, with high mortality and morbidity. At present, there are no effective 6-month prognostic markers, particularly for younger patients. The aim of this research was to construct a new valuable prognostic nomogram model incorporating haemoglobin levels for adult patients with ICH. METHODS: Patients aged between 18 and 50 presenting with intracerebral haemorrhage at the Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology between January 1st 2012 and December 31st 2018 were included in this retrospective study. Independent factors of prognosis were identified by univariate and multivariate logistic regression analyses, and a new nomogram model was constructed and validated. The clinical value of the nomogram model was subsequently explored utilizing decision curve analysis and clinical impact curves. RESULTS: In total, 565 patients were enrolled in this study, 117 (20.7%) of whom developed an unfavourable prognosis. Infratentorial lesion (adjusted odds ratio [aOR] = 3.708, 95% confidence interval [CI], 1.490-9.227; P = 0.005) was the most significant unfavourable outcome. Age ([aOR] = 1.054; 95% CI, 1.014-1.096; P = 0.008), hematoma volume (aOR = 1.014, 95% CI, 1.002-1.027; P = 0.024), haemoglobin (aOR = 0.981, 95% CI, 0.969-0.993; P = 0.002), blood glucose (aOR = 1.135, 95% CI, 1.037-1.241; P = 0.005) and NIHSS (aOR = 1.105, 95% CI, 1.069-1.141; P < 0.001) were independent risk factors. Based on these 6 factors, the nomogram can be employed to predict early functional prognosis with high accuracy (AUC 0.791). Decision curve analysis and clinical impact curves showed an increased net benefit for utilizing the nomogram. CONCLUSION: The haemoglobin level at admission may be an easily overlooked factor in clinical work. This new nomogram model could be a promising and convenient tool to predict the early functional prognosis of adults with ICH. More prospective multicentre studies are needed to validate these findings.

Apolipoprotein E ɛ2 Is Associated with the White Matter Hyperintensity Multispot Pattern in Spontaneous Intracerebral Hemorrhage.

The white matter hyperintensity (WMH) multispot pattern, as multiple punctate subcortical foci, could differentiate cerebral amyloid angiopathy (CAA) from hypertensive arteriolopathy. Nevertheless, the pathophysiology underlying the multispot sign is still inexplicit. We aimed to explore risk factors for multispot patterns in cerebral small vessel disease (CSVD)-related intracerebral hemorrhage (ICH). Between June 2018 and January 2020, we retrospectively rated the WMH multispot pattern while blinded to our prospective spontaneous ICH cohort's clinical data. Demographic, genetic, and neuroimaging characteristics were applied in establishing the multispot pattern models via multiple logistic regression. In total, 268 participants were selected from our cohort. The possession of apolipoprotein E (APOE) ε2 (P = 0.051) was associated with multispot WMH in univariate analysis. Multispot WMHs were accompanied by multiple CAA features, such as centrum semiovale (CSO)-perivascular space (PVS) predominance (P = 0.032) and severe CSO-PVS (P < 0.001). After adjusting for confounding factors, APOE ε2 possession (OR 2.99, 95% CI [1.07, 8.40]; P = 0.037), severe CSO-PVS (OR 2.39, 95% CI [1.09, 5.26]; P = 0.031), and large posterior subcortical patches (P = 0.001) were independently correlated with the multispot pattern in multivariate analysis. Moreover, APOE ε2 possession (OR 4.34, 95% CI [1.20, 15.62]; P = 0.025) and severe CSO-PVS (OR 3.39, 95% CI [1.23, 9.34]; P = 0.018) remained statistically significant among the participants older than 55 years of age and with categorizable CSVD. APOE ε2 and severe CSO-PVS contribute to the presence of WMH multispot patterns. Because the multispot pattern is a potential diagnostic biomarker in CAA, genetics-driven effects shed light on its underlying vasculopathy. Clinical Trial Registration: URL- http://www.chictr.org.cn . Unique identifier: ChiCTR-ROC-2000039365. Registration date 2020/10/24 (retrospectively registered).

SMASH-U aetiological classification: A predictor of long-term functional outcome after intracerebral haemorrhage.

BACKGROUND: SMASH-U is a systematic aetiological classification system for intracerebral haemorrhage (ICH) proven to be a predictor of post-ICH haematoma expansion and mortality. However, its role in predicting functional outcome remains elusive. Therefore, we aimed to investigate whether SMASH-U is associated with long-term functional outcome after ICH and improves the accuracy of prediction when added to max-ICH score. METHODS: Consecutive acute ICH patients from 2012 to 2018 from the neurology department of Tongji Hospital were enrolled. ICH aetiology was classified according to the SMASH-U system. The association of SMASH-U with 12-month functional outcome after ICH and the predictive value were evaluated. RESULTS: Of 1938 ICH patients, the aetiology of 1295 (66.8%) patients were classified as hypertension, followed by amyloid angiopathy (n = 250, 12.9%), undetermined (n = 159, 8.2%), structural lesions (n = 149, 7.7%), systemic disease (n = 74, 3.8%) and medication (n = 11, 0.6%). The baseline characteristics were different among the six aetiologies. In multivariate analysis, SMASH-U was proven to be a predictor of 12-month unfavourable functional outcome. When adding the SMASH-U system, the predictive performance of max-ICH score was improved (area under the receiver operating characteristic curve from 0.802 to 0.812, p = 0.010) and the predictive accuracy was enhanced (integrated discrimination improvement [IDI]: 1.60%, p < 0.001; continuous net reclassification improvement [NRI]: 28.16%, p < 0.001; categorical NRI: 3.34%, p = 0.004). CONCLUSIONS: SMASH-U predicted long-term unfavourable functional outcomes after acute ICH and improved the accuracy of prediction when added to max-ICH score. Integrating the aetiology to a score model to predict the post-ICH outcome may be meaningful and worthy of further exploration.

Long QT syndrome with potassium voltage-gated channel subfamily H member 2 gene mutation mimicking refractory epilepsy: case report.

BACKGROUND: Epileptic seizures can be difficult to distinguish from other etiologies that cause cerebral hypoxia, especially cardiac diseases. Long QT syndrome (LQTS), especially LQTS type 2 (LQT2), frequently masquerades as seizures because of the transient cerebral hypoxia caused by ventricular arrhythmia. The high rate of sudden death in LQTS highlights the importance of accurate and early diagnosis; correct diagnosis of LQTS also prevents inappropriate treatment with anti-epileptic drugs (AEDs). CASE PRESENTATION: We report a case of congenital LQT2 with potassium voltage-gated channel subfamily H member 2 gene (KCNH2) mutation misdiagnosed as refractory epilepsy and treated with various AEDs for 22 years. The possibility of cardiac arrhythmia was suspected after the patient presented to the emergency room and the electrocardiograph (ECG) monitor showed paroxysmal ventricular tachycardia during attacks. Atypical seizure like attacks with prodromal uncomfortable chest sensation and palpitation, triggered by auditory stimulation, and typical ventricular tachycardia monitored by ECG raised suspicion for LQT2, which was confirmed by exome sequencing and epileptic seizure was ruled out by 24-h EEG monitoring. Although the patient rejected implantation of an implantable cardioverter defibrillator, ß blocker was given and the syncope only attacked 1-2 per year when there was an incentive during the 5 years follow up. CONCLUSIONS: Our case illustrates how long LQTS can masquerade convincingly as epilepsy and can be treated wrongly with AEDs, putting the patient at high risk of sudden cardiac death. Careful ECG evaluation is recommend for both patients with first seizure and those with refractory epilepsy.

Apolipoprotein E genotype predicts subarachnoid extension in spontaneous intracerebral haemorrhage.

BACKGROUND AND PURPOSE: Spontaneous intracerebral haemorrhage (ICH) with subarachnoid extension (SAHE) predicts poor outcomes and haematoma expansion in spontaneous ICH and is also a potential predictor of the severity of vascular amyloid deposition. The biological underpinnings of SAHE remain elusive. A study was conducted to identify risk factors associated with SAHE. METHODS: A retrospective analysis was performed of an ongoing prospective cohort of primary spontaneous supratentorial ICH patients admitted to Tongji Hospital. SAHE was rated on baseline noncontrast computed tomography images by investigators blinded to the clinical data. RESULTS: A total of 189 patients were enrolled. Apolipoprotein E (APOE) ε2 copies (p = 0.020), but not APOE ε4 copies (p > 0.2), were more common in patients with SAHE in univariate analysis. After controlling for confounding factors in multiple logistic regression, lobar haematoma (odds ratio [OR] 14.21, 95% confidence interval [CI] 5.89-34.33; p < 0.001), large haematoma volume (OR 1.04, 95% CI 1.02-1.06; p < 0.001) and APOE ε2 copies (OR 3.07, 95% CI 1.05-8.97; p = 0.041) were three independent predictors of SAHE. For subgroup analysis stratified by location, APOE ε2 showed a possible association with SAHE in lobar ICH (p = 0.026) but not in deep ICH (p > 0.2). No significant association was found between APOE ε4 copies and either lobar (p > 0.2) or deep ICH (p > 0.2). CONCLUSIONS: The APOE ε2 allele predicts SAHE in spontaneous supratentorial ICH. The association may predominantly apply to lobar ICH. Given the established relationship between the APOE ε2 allele and pathological cerebrovascular changes, our findings suggest that SAHE involves genetically driven vessel pathology.

COVID-19 outbreak: The impact of stress on seizures in patients with epilepsy.

OBJECTIVE: Stress is a known trigger for seizures in patients with epilepsy (PWE). However, the association between stress and seizures has not been thoroughly investigated. In December 2019, an outbreak of coronavirus disease (COVID-19) occurred in Wuhan, Hubei province, China, causing tremendous collateral stress. This study was designed to evaluate the influence of the COVID-19 outbreak on seizures in PWE in the most severely affected area, Wuhan, and its surrounding cities. METHODS: In this single-center, cross-sectional study, PWE were surveyed via online questionnaires between February 23 and March 5, 2020. Collected data included demographic information, epilepsy-related characteristics (seizure type, frequency, antiepileptic drugs [AEDs], and medication management), direct and perceived threat of COVID-19, and changes in seizures during the outbreak. Psychological comorbidities were evaluated by the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7 items, and Insomnia Severity Index (ISI). Multivariate logistic regression was used to identify precipitants for seizure exacerbation. RESULTS: We received 362 completed questionnaires after excluding 12 duplicates (response rate = 63.51%). A total of 31 (8.56%) patients had increased seizures during the outbreak. Exposure history to COVID-19 (P = .001), uncontrolled seizure after AED therapy (P = .020), seizure frequency of two or more times per month before the outbreak (P = .005), change of AED regimen during the outbreak (AED reduction, withdrawal, replacement, skipping altogether; P = .002), and worry about the adverse effect of the outbreak on overall seizure-related issues (severity = moderate to critical; P = .038) were risk factors for increased seizures. SIGNIFICANCE: A minority of PWE experienced seizure exacerbation during the outbreak of COVID-19. Stress, uncontrolled seizures, and inappropriate change in AED regimen were associated with increased seizures. Based on these findings, stress might be an independent precipitant for triggering seizures in some PWE.

Band optimization of passive methane gas leak detection based on uncooled infrared focal plane array: publisher's note.

This publisher's note amends the author listing in Appl. Opt.57, 3991 (2018)APOPAI0003-693510.1364/AO.57.003991.

Band optimization of passive methane gas leak detection based on uncooled infrared focal plane array.

Current methane gas leak detection technology uses infrared imaging in the medium wave (MW) or long wave (LW) bands, essentially applying cooled infrared detectors. In this study, a simplified three-layer radiative transfer model is adopted based on methane gas detection theory, considering background radiation, atmospheric infrared absorption, gas absorption, and emission characteristics to analyze the contrast of methane gas thermography in different infrared bands. The analysis results suggest that under certain conditions, the 6.6-8.6 µm LW band provides higher contrast compared to the 3-5 µm MW band. The optimal imaging wavelength band is selected according to imaging contrast advantages and disadvantages, and infrared optical systems and infrared filters are designed and optimized. We build a passive methane gas leak detection system based on uncooled infrared focal plane array detectors. By collecting gas images under different conditions, the imaging detection capabilities for methane gas leaks in the MW and LW bands in a laboratory environment are compared. Finally, the developing trends in methane gas detection technology are analyzed.