Hemorrhagic Transformation In Patients Research Articles

Hypoperfusion intensity ratio and hemorrhagic transformation in patients with successful recanalization after thrombectomy.

Hemorrhagic transformation remains a potentially devastating complication of acute ischemic stroke. We aimed to evaluate whether the hypoperfusion intensity ratio (HIR), a parameter derived from CT perfusion imaging, is associated with the development of hemorrhagic transformation in patients with anterior large-artery occlusion who had undergone thrombectomy. We retrospectively reviewed data from consecutive acute ischemic stroke patients who had achieved successful recanalization (thrombolysis in cerebral infarction score ≥ 2b) between January 2020 and December 2023. HIR was defined as the ratio of the volume of lesions with a time-to-maximum (TMax) > 6 s to those with a Tmax > 10 s delay. The primary outcome, based on the European Cooperative Acute Stroke Study, was hemorrhagic transformation (HT), diagnosed by follow-up imaging assessment in 24 h windows, and radiologically classified as hemorrhagic infarction (HI) and parenchymal hematoma (PH). The secondary outcome was a 3-month mRS score of ≥3. Among 168 patients, 35/168 developed hemorrhagic transformation HT; 14/168 developed hemorrhagic infarction HI, and 21/168 developed parenchymal hematoma PH. After adjusting the latent covariates, increased hypoperfusion intensity ratio (per 0.1, adjusted OR [aOR] 1.68, 95% CI 1.26-2.25), ASPECTS (aOR 0.44, 95% CI 0.27-0.72), onset-to-puncture (aOR 1.01, 95% CI 1.00-1.02), and cardioembolism (aOR 5.6, 95% CI 1.59-19.7) were associated with hemorrhagic transformation in multivariable regression. The receiver operating characteristic curve indicated that HIR can predict HT accurately (area under the curve = 0.81; 95% CI, 0.738-0.882; P < 0.001) and predict PH (area under the curve = 0.801; 95% CI, 0.727-0.875; P < 0.001). Upon admission, hypoperfusion intensity ratio, an imaging parameter, predicted hemorrhagic transformation after reperfusion therapy in this patient population.ABBREVIATIONS: HT = hemorrhagic transformation; HIR = hypoperfusion intensity ratio; LVO = left vessel occlusion; EVT = endovascular thrombectomy; AIS = arterial ischemic stroke; OTP = onset-to-puncture; HI = hemorrhagic infarction; PH = parenchymal hematoma.

Đặc điểm vi xuất huyết não và nguy cơ chuyển dạng xuất huyết ở bệnh nhân nhồi máu não cấp có điều trị tái thông

Objective: Evaluate the characteristics of cerebral microbleeds and factors related to hemorrhagic transformation in patients with acute cerebral infarction undergoing revascularization treatment at University Medical Center, Ho Chi Minh City. Subjects and methods: Cross-sectional descriptive study combined with medical record monitoring on 79 patients diagnosed with acute cerebral infarction who were admitted and treated at the Department of Neurology, University Medical Center, Ho Chi Minh City. Results: Patients with microhemorrhage (VXH) accounted for 37.97%. The number of 1-4 VXH accounted for the highest rate of 31.65%, only 01 case had more than 10 VXH, accounting for 1.27% %. The location of social lesions is mainly in the deep brain area, accounting for 21.52%. There is an association between VXH and dyslipidemia with p = 0.16 (OR 4.12, CL 1.14-18.47), white matter pathology according to Fazekas classification with p = 0.041. The main complications of hemorrhagic transformation after revascularization are HI, accounting for 26.58%, followed by PH, accounting for 6.33%, and ICH+, accounting for 3.8%. There is an association between Glasgow scale (OR = 1.66, CI 0.79 - 3.51) with symptomatic ICH and PH with p &lt; 0.05. Found an association between NIHSS Scale and ICH with p = 0.037 (OR = 5.46 CI 1.10 – 19.00). There is not enough evidence to conclude about the relationship between the number and location of microbleeds and complications of hemorrhagic transformation after revascularization. Conclusion: VXH is not a factor to delay recanalization interventions in acute myocardial infarction patients with indications for intervention. Patients at high risk of multiple VHs should have an MRI scan before intervention.

Retracted: Predictive Value of Apelin and Vaspin on Hemorrhagic Transformation in Patients with Acute Ischemic Stroke after Intravenous Thrombolysis and Analysis of Related Factors.

[This retracts the article DOI: 10.1155/2021/5020622.].

Abstract 006: Glenzocimab Is Associated With Less Haemorrhagic Transformation Using Artificial Intelligence Imaging In Mechanical Thrombectomy Patients

Introduction Lesion volume measurement provides an objective and quantitative assessment of stroke severity and it is often used as a surrogate endpoint of clinical outcome in therapeutic trials. ACTIMIS (NCT03803007) was a randomized phase 1b/2a clinical trial evaluating glenzocimab, a monoclonal antibody fragment targeting platelet receptor glycoprotein VI, versus placebo in patients with acute ischemic stroke treated by thrombolysis alone or associated with mechanical thrombectomy (MT), both subgroups being well balanced. Primary analysis demonstrated a significant reduction in intracranial hemorrhage occurrence stroke‐related mortality and a trend towards reduction in severe disability. In this sub‐analysis, Artificial Intelligence (AI) imaging biomarkers were used to assess efficacy of glenzocimab in the subgroup undergoing MT in the pooled phase 1b (dose escalation) and phase 2a (dose confirmation) studies. Methods In the phase 1b study, patients were randomized to an escalating dose of glenzocimab or placebo (4:1, n=12 per group, 125mg, 250mg, 500mg, 1000mg). In the phase 2 dose confirmation study, patients were randomized (1:1) with 1000mg glenzocimab or placebo. CT scan or MRI was acquired at baseline with CT at 24 hours and MRI at 7 days (CT if MRI not available) for safety and efficacy analysis, respectively. Baseline and follow up imaging were processed using Brainomix software (Oxford, UK). AI output was reviewed for accuracy by an expert clinician (DC) blinded to treatment allocation. Results Of 166 patients in the trial, 81 patients underwent MT and had follow up non‐contrast CT imaging available at 24 hours (48 glenzocimab, 33 placebo) and 72 had Day‐7 imaging (47 glenzocimab, 25 placebo). Day‐7 imaging was available for 8 fewer placebo patients and 1 glenzocimab patient than at 24 hours. All except 2 patients (1 placebo, 1 glenzocimab) with missing data at Day‐7 died during the study. Multivariate regression modelling showed a significant interaction between patients undergoing MT and receiving glenzocimab. Glenzocimab had a greater effect on reducing the risk of haemorrhagic transformation in the MT subgroup (exploratory p=0.001). Presenting acute infarct volume was similar between glenzocimab and placebo arms (mean [SD]; 16.27mL [30.2] vs. 19.62mL [28.98], non‐significant). There was a significantly smaller volume of haemorrhagic transformation in the glenzocimab group at 24 hours compared to placebo (1.83mL [6.59] vs 33.46mL [75.07], exploratory p&lt;0.01) and a trend towards smaller volume of ischemic injury in the glenzocimab group (52.32mL [82.07] vs 62.93mL [79.4]). Similar significant trend at Day‐7 for haemorrhagic transformation was seen but less marked due to the unbalanced loss to follow up at Day‐7 (2.99mL [12.35] vs 4.19mL [10.83], exploratory p&lt;0.05). Conclusion Glenzocimab reduces likelihood of haemorrhagic transformation in patients undergoing MT. Haemorrhage volumes were smaller in the glenzocimab group and encouragingly there was a trend to smaller volumes of ischemic injury. There was a greater drop‐out rate in the placebo group between 24 hours and Day‐7, which resulted in a smaller difference in haemorrhagic volumes at Day‐7. Those results, which are to be further analysed in ACTIMIS overall population of AIS patients, could highlight glenzocimab mechanism in the reperfusion injury mitigation.

Predictive effects of S100β and CRP levels on hemorrhagic transformation in patients with AIS after intravenous thrombolysis: A concise review based on our center experience.

Hemorrhagic transformation (HT) is one of the most dangerous complications after intravenous thrombolysis in patients with acute ischemic stroke (AIS). Therefore, we want to explore the predictive effects of peripheral blood S100β and C-Reactive Protein (CRP) levels on hemorrhagic transformation after intravenous thrombolysis in AIS patients. Ninety-two AIS patients who had been treated in Huai'an Second People's Hospital from January 2018 to December 2021 were retrospectively selected. Patients were divided into hemorrhagic transformation (HT) groups (24 cases) and no HT groups (68 cases) based on whether there was hemorrhagic transformation within 24 h after intravenous thrombolysis. General clinical data from the HT group and no HT group were compared. A multivariate logistic regression model was used to analyze the potential risk factors of HT after intravenous thrombolysis in patients with AIS. A receiver operating curve (ROC) was used to analyze the predictive value of risk factors for HT. High serum S100β, CRP levels, and National Institutes of Health Stroke Scale (NIHSS) scores were found to be risk factors for HT after intravenous thrombolysis in patients with AIS (all P < .05). The ROC curve analysis showed that critical value of S100β, CRP level, and NIHSS score for predicting intravenous thrombolytic HT in AIS patients were 0.335, 8.700, and 14.50, respectively, and their sensitivities were 0.750, 0.971, and 0.333 (P < .05), respectively. High serum S100β and CRP levels are risk factors for HT after intravenous thrombolysis in AIS patients and have predictive influence of the occurrence of HT in AIS patients.

Hemorrhagic transformation in patients with large-artery atherosclerotic stroke is associated with the gut microbiota and lipopolysaccharide.

Abstract JOURNAL/nrgr/04.03/01300535-202407000-00032/figure1/v/2023-11-20T171125Z/r/image-tiff Hemorrhagic transformation is a major complication of large-artery atherosclerotic stroke (a major ischemic stroke subtype) that worsens outcomes and increases mortality. Disruption of the gut microbiota is an important feature of stroke, and some specific bacteria and bacterial metabolites may contribute to hemorrhagic transformation pathogenesis. We aimed to investigate the relationship between the gut microbiota and hemorrhagic transformation in large-artery atherosclerotic stroke. An observational retrospective study was conducted. From May 2020 to September 2021, blood and fecal samples were obtained upon admission from 32 patients with first-ever acute ischemic stroke and not undergoing intravenous thrombolysis or endovascular thrombectomy, as well as 16 healthy controls. Patients with stroke who developed hemorrhagic transformation (n = 15) were compared to those who did not develop hemorrhagic transformation (n = 17) and with healthy controls. The gut microbiota was assessed through 16S ribosomal ribonucleic acid sequencing. We also examined key components of the lipopolysaccharide pathway: lipopolysaccharide, lipopolysaccharide-binding protein, and soluble CD14. We observed that bacterial diversity was decreased in both the hemorrhagic transformation and non-hemorrhagic transformation group compared with the healthy controls. The patients with ischemic stroke who developed hemorrhagic transformation exhibited altered gut microbiota composition, in particular an increase in the relative abundance and diversity of members belonging to the Enterobacteriaceae family. Plasma lipopolysaccharide and lipopolysaccharide-binding protein levels were higher in the hemorrhagic transformation group compared with the non-hemorrhagic transformation group. lipopolysaccharide, lipopolysaccharide-binding protein, and soluble CD14 concentrations were associated with increased abundance of Enterobacteriaceae. Next, the role of the gut microbiota in hemorrhagic transformation was evaluated using an experimental stroke rat model. In this model, transplantation of the gut microbiota from hemorrhagic transformation rats into the recipient rats triggered higher plasma levels of lipopolysaccharide, lipopolysaccharide-binding protein, and soluble CD14. Taken together, our findings demonstrate a noticeable change in the gut microbiota and lipopolysaccharide-related inflammatory response in stroke patients with hemorrhagic transformation. This suggests that maintaining a balanced gut microbiota may be an important factor in preventing hemorrhagic transformation after stroke.

Computed Tomography Perfusion Parameters Predictive of Symptomatic Intracranial Hemorrhage After Mechanical Thrombectomy in Patients With Cerebral Large Vessel Occlusion

Background Hemorrhagic transformation after recanalization is a severe complication in patients with a large ischemic core due to cerebral large vessel occlusion. Risk assessment using perfusion imaging to predict hemorrhagic infarction has not been established. Thus, we aimed to investigate the association between perfusion imaging findings and hemorrhagic transformation in patients with acute cerebral large vessel occlusion who had undergone preoperative perfusion imaging evaluation and mechanical thrombectomy. Methods We enrolled consecutive patients who received mechanical thrombectomy after undergoing perfusion imaging for anterior large vessel occlusion from May 2019 to March 2022. The patients in whom recanalization were not achieved and who experienced procedure‐related bleeding were excluded. We investigated the predictors of symptomatic intracranial hemorrhage (sICH) by exploring preoperative perfusion imaging parameters (relative cerebral blood flow, relative cerebral blood volume, time of maximum concentration, and hypoperfusion index ratio). Results Among the 167 patients (median age 79 years, 47% female) enrolled, 63 (38%) and 14 (8%) patients had any intracranial hemorrhage and sICH (sICH group), respectively. The sICH group had a shorter puncture‐recanalization time than the non‐sICH group (median [interquartile range (IQR)]; 43 [34–55] versus 61 [37–88]; P =0.046), whereas the modified Rankin scale at 90 days showed a worse prognosis (median [IQR]; 5 [5–6] versus 3 [1–4]; P &lt;0.01). All perfusion imaging parameters were significantly predicting the sICH group in multiple logistic regression analysis. The value of relative cerebral blood volume was the parameter most strongly associated with sICH in receiver operating characteristic curve analysis (area under the curve=0.90, 95% CI [0.83–0.98]; cutoff 43 mL; sensitivity, 86 %; specificity, 87%). Conclusion Among perfusion computed tomography parameters, relative cerebral blood volume is highly associated with sICH after mechanical thrombectomy for cerebral large vessel occlusion. In patients with low relative cerebral blood volume regions, the indication of mechanical thrombectomy should be carefully considered for postoperative intracranial hemorrhage.

In-Hospital Aspirin Dose as a Risk Factor for Hemorrhagic Transformation in Patients Not Treated With Thrombolysis.

Aspirin is widely used as secondary prophylaxis for acute ischemic stroke. However, its influence on the risk of spontaneous hemorrhagic transformation (HT) is still unclear. Predictive scores of HT have been proposed. We hypothesized that an increased aspirin dose might be harmful in patients at a high risk of HT. This study aimed to analyze the relationship between in-hospital daily aspirin dose (IAD) and HT in patients with acute ischemic stroke. We conducted a retrospective cohort study of patients admitted to our comprehensive stroke center between 2015 and 2017. The attending team defined IAD. All included patients underwent either computed tomography or magnetic resonance imaging within 7 days of admission. The risk of HT was assessed using the predictive score of HT in patients not undergoing reperfusion therapies. Regression models were used to evaluate the correlations between HT and IAD. A total of 986 patients were included in the final analysis. The prevalence of HT was 19.2%, and parenchymatous hematomas type-2 (PH-2) represented 10% (n=19) of these cases. IAD was not associated with HT ( P =0.09) or PH-2 ( P =0.06) among all patients. However, in patients at a higher risk for HT (patients not undergoing reperfusion therapies ≥3), IAD was associated with PH-2 (odds ratio 1.01,95% CI 1.001-1.023, P =0.03) in an adjusted analysis. Taking 200 versus 300mg aspirin was protective against PH-2 (odds ratio 0.102, 95% CI 0.018-0.563, P =0.009). An increased in-hospital aspirin dose is associated with intracerebral hematoma in patients at a high risk of HT. Stratifying the risk of HT may lead to individualized daily aspirin dose choices. However, clinical trials on this topic are required.

The association between malnutrition status and hemorrhagic transformation in patients with acute ischemic stroke receiving intravenous thrombolysis

ObjectivesWe evaluated the impact of malnutrition as estimated by the controlling nutritional status (CONUT) score and prognostic nutritional index (PNI) on hemorrhagic transformation (HT) and stroke outcomes after intravenous thrombolysis (IVT).Materials and methodsUsing a multicenter registry database, we enrolled 808 patients with acute ischemic stroke who received IVT between August 2013 and May 2021. We defined malnutrition as a CONUT score ≥ 2 and low PNI. The primary outcome measure was the occurrence of symptomatic HT contributing to early neurologic deterioration (END-SHT) after IVT. Multivariable analysis was performed to analyze the association between CONUT score, PNI, and END-SHT after IVT.ResultsThe rate of END-SHT was higher with increasing CONUT scores and PNI values. In the multivariable analysis, CONUT score ≥ 5 and low PNI were significantly associated with END-SHT (odds ratio [95% confidence interval], CONUT score ≥ 5: 12.23 [2.41–62.07], p = 0.003; low PNI: 4.98 [1.76–14.09], p = 0.003). The receiver operating characteristic curve showed that both the CONUT score and PNI had good predictive ability. The cutoff values for CONUT and PNI were 5 and 42.3, respectively, for END-SHT.ConclusionMalnutrition, as denoted by a higher CONUT score and lower PNI, was associated with END-SHT. The joint application of both nutritional markers could be useful in predicting END-SHT after IVT.

Higher serum homocysteine levels are associated with an increased risk of hemorrhagic transformation in patients with acute ischemic stroke

BackgroundHemorrhagic transformation (HT) is a common complication of acute ischemic stroke (AIS), and may develop into parenchyma hemorrhage (PH). We aimed to investigate the association between serum homocysteine levels and HT as well as PH in all AIS patients, and in those with and without thrombolysis by subgroup analysis.MethodsAIS patients who were admitted within 24 h after onset were enrolled and categorized into the higher homocysteine level group (≥ 15.5 µmol/L) and the lower homocysteine level group (< 15.5 µmol/L). HT was determined by a second round of brain imaging within 7 days during hospitalization, and PH was defined as hematoma in the ischemic parenchyma. Multivariate logistic regression was used to investigate the associations between serum homocysteine levels and HT and PH, respectively.ResultsOf the 427 included patients (mean age 67.35 years, 60.0% males), 56 (13.11%) developed HT and 28 (6.56%) had PH. Serum homocysteine levels were significantly associated with HT (adjusted OR 1.029, 95%CI 1.003–1.055) and PH (adjusted OR 1.041, 95%CI 1.013–1.070). The higher homocysteine group was more likely to have HT (adjusted OR 1.902, 95% CI 1.022–3.539) and PH (adjusted OR 3.073, 95% CI 1.327–7.120) than the lower homocysteine group. Subgroup analysis of patients without thrombolysis also showed the significant differences in HT (adjusted OR 2.064, 95% CI 1.043–4.082) and PH (adjusted OR 2.926, 95% CI 1.196–7.156) between the two groups.ConclusionHigher serum homocysteine levels are associated with an increased risk of HT and PH in AIS patients, especially in those without thrombolysis. Monitoring the serum homocysteine may be conducive to determining individuals at a high risk of HT.

Sex-dependent association analysis between serum uric acid and spontaneous hemorrhagic transformation in patients with ischemic stroke.

The association between serum uric acid (UA) and spontaneous hemorrhagic transformation (HT) has been seldom studied, and the role of UA in spontaneous HT remains unclear. This study aims to investigate the sex-dependent association between UA and spontaneous HT in patients with ischemic stroke. We retrospectively included patients with ischemic stroke in a tertiary academic hospital between December 2016 and May 2020. Patients were included if they presented within 24 h after the onset of symptoms and did not receive reperfusion therapy. Spontaneous HT was determined by an independent evaluation of neuroimaging by three trained neurologists who were blinded to clinical data. A univariate analysis was performed to identify factors related to spontaneous HT. Four logistic regression models were established to adjust each factor and assess the association between UA and spontaneous HT. A total of 769 patients were enrolled (64.6% were male patients and 3.9% had HT). After adjusting the confounders with a P < 0.05 (model A) in the univariate analysis, the ratio of UA and its interquartile range (RUI) was independently associated with spontaneous HT in male patients (OR: 1.85; 95% CI: 1.07-3.19; P = 0.028), but not in female patients (OR: 1.39; 95% CI: 0.28-6.82; P = 0.685). In models B-D, the results remain consistent with model A after the adjustment for other potential confounders. Higher serum UA was independently associated with a higher occurrence of spontaneous HT in male patients who were admitted within 24 h after the stroke onset without receiving reperfusion therapy.

Progress in stratified stroke characterization-associated with better diagnosis, accurate prognosis and improved treatment strategies.

In this special issue, focussed on novel stroke biomarkers, we invited world-leading researchers to submit novel findings from work originating from the Asian provinces of China. As we move towards an era of stratified and personalised medicine with a significant input from large data sets and artificial intelligence (AI) algorithms, a complete understanding of the clinical background, risk factors, genetics and epigenetic markers and pathophysiological biomarkers that inform and therefore predict response to treatment and ultimately, outcome, are still needed [1]. Therefore, here, are included several articles that provide further novel insight into this complex disease process, and which will contribute to the synthesis of data resulting in our transcendence to optimized treatment and rehabilitation with associated reduced morbidity and mortality. The contribution of inflammation and the neuroinflammatory response to stroke volume, neuronal cell death and outcome is undeniable [2], with activation of local microglia stimulating and pre-empting the arrival of an ‘army’ of inflammatory M2-polarised monocytes/macrophages through the damaged blood–brain barrier secreting damaging cytokines such as interleukins 1-β/6/8, as well as tumour necrosis factor-α, and others including the more recently identified plasma-borne monomeric C-reactive protein [3, 4]. In this series, Zhang et al. [5], provided a comprehensive review of the role of the mononuclear phagocyte system in ischaemic stroke, summarizing that the effects are time dependent and influence the processes of stroke volume development, angiogenesis and remodelling and plasticity, as well as being potential markers of long-term prognosis and outcome. Hence as recently described by Monsour et al. [6], targeting critical early inflammatory pathways such as pro-inflammatory IL-6 but protecting the inactive IL-6-soluble IL-6 receptor 130 complex might form part of a future combinational therapeutic effort. Within this series, and in an original and more translational study, Han-Yu et al. [7], analysed the impact of reactive astrogliosis following transient global cerebral perfusion using a rat model of stroke. They showed that conditional knockout of the lysosomal-associated membrane protein 2A (LAMP-2A), protected CA1 hippocampal neurones from death also ameliorating spatial learning and memory deficits, by inhibiting astrocyte activation. They proposed this as a potential novel neuroprotective strategy. Whilst additional protective mechanisms include the prevention of apoptotic protein translocation (Bax/Bad), both the previous findings that LAMPs are involved in mediating proper autophagy that could protect the brain against toxic plaque build up-also associated with the medium to long-term consequences after stroke, as well as the known limitations in translation of rodent models to the human condition [8]. Nevertheless this work represents an important finding within the field. As mentioned earlier, AI algorithms and deep-learning predictive big-data-derived technology will be essential to improve our understanding of how to manage stroke at the individual level, for example, by providing MRI-lesion segmentation datasets that will help in treatment decision-making and evaluating outcome. In this series, Jiang et al. [9] showed that a multiparameter model using deep-learning automated processes, measuring datasets of the volume of interest and segment slices, together, significantly better predicted haemorrhagic transformation in patients following endovascular thrombectomy after ischaemic stroke, compared with single parameter models. One of the less common causes of cerebral infarction is susceptibility due to vertebrobasilar dolichoectasia (VBD), where abnormalities in the basilar artery predispose to premature development of atherosclerosis. Mortality rates are high due to the non-specific symptoms and delay in diagnosis. Here, Tao et al. (2023), used high-resolution MRI (HR-MRI), to fully characterise the arterial structure and function in 24 patients and concluded that risk of stroke was associated with bifurcation height and arterial turbulence and inferior diameters [10]. This work should help to enable more effective stratified risk assessment following larger-scale clinical studies. In conclusion, this special series of articles reflects the broad and extremely complex nature of stroke pathophysiology. Importantly, it indicates how a series of small advances could eventually support an optimised programme of stratification and personalised approach to understanding risk, diagnosis prognosis and outcome. This would probably be achieved using a combination of data-driven deep learning AI together with point-of-care rapid testing, through advanced imaging and likely a combinational approach to targeting early tissue damage regulating inflammation and apoptosis and eliciting neuroprotective pathways thereby maintaining patency of neurovascular units. Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Lactate Dehydrogenase Predicts Hemorrhagic Transformation in Patients with Acute Ischemic Stroke

Introduction: Hemorrhagic transformation (HT) is a severe but frequent complication of acute ischemic stroke (AIS). This study aimed to evaluate the relationship between serum lactate dehydrogenase (LDH) levels and HT. Methods: We retrospectively included 542 AIS patients with HT and 1,091 age- and gender-matched patients without HT. Demographic and clinical data were obtained from medical records, and blood samples were obtained within 24 h after admission. The characteristics of the groups were compared. With the receiver operating characteristic (ROC) curve analysis, we assessed the discriminating capacity of LDH levels in predicting HT in patients with AIS. The logistic regression model was used to determine the connection between LDH and HT. Results: The HT group had considerably higher LDH levels than the non-HT group (263.0 [216.0–323.3] U/L versus 178.0 [162.0–195.0] U/L, p < 0.001). We also observed that the levels of LDH in the parenchymal hemorrhage subgroup were significantly higher than those in the hemorrhagic infarction subgroup (281.0 [230.0–340.0] U/L versus 258.0 [209.0–311.0] U/L, p < 0.001). The area under the ROC curve of LDH was 0.890 (95% confidence level [CI] 0.874–0.905, p < 0.001). Besides, logistic regression revealed that high LDH levels (LDH >215 U/L) showed a higher risk of HT (odds ratio = 10.958, 95% CI 7.964–15.078, p < 0.001). Conclusion: High LDH levels were linked with an increased risk of HT in AIS patients. Practical measures should be considered in patients with increased LDH levels (LDH >215 U/L).

Predictors of 7-day symptomatic hemorrhagic transformation in patients with acute ischemic stroke and proposal of a novel screening tool: A retrospective cohort study.

Hemorrhagic transformation (HT) is significantly related to poor neurological outcomes and mortality. Although variables and models that predict HT have been reported in the literature, the need for a model with high diagnostic performance continues. We aimed to propose a model that can accurately predict symptomatic HT within 7 days of acute ischemic stroke (AIS). Patients with AIS admitted to the emergency department of a tertiary training and research hospital between November 07, 2021, and August 26, 2022, were included in this single-center retrospective study. For the model, binary logistics with the forced-entry method was used and the model was validated with 3-fold cross-validation. After the final model was created, the optimal cutoff point was determined with Youden's index. Another cut-off point was determined at which the sensitivity was the highest. The mean age of the 423 patients included in the study was 70 (60-81) and 53.7% (n = 227) of the patients were male. Symptomatic HT was present in 31 (7.3%) patients. Mechanical thrombectomy, atrial fibrillation, and diabetes mellitus were the independent predictors (P < 0.001, P = 0.003, P = 0.006, respectively). The mean area under the curve of the receiver operating characteristics of the model was 0.916 (95% confidence interval [CI] = 0.876-0.957). The sensitivity for the optimal cut-off point was 90.3% (95% CI = 74.3%-97.9%) and specificity was 80.6% (95% CI = 76.4%-84.4%). For the second cutoff point where the sensitivity was 100%, the specificity was 60.5% (95% CI = 55.4%-65.3%). The diagnostic performance of our model was satisfactory and it seems to be promising for symptomatic HT. External validation studies are required to implement our results into clinical use.

The Effect of Atrial Fibrillation on Recanalization and Prognosis in Patients with Acute Ischemic Stroke Undergoing Mechanical Thrombectomy and/or Intravenous Thrombolysis

ABSTRACT Background: Atrial fibrillation (AF) is the most common cause of cardioembolic ischemic strokes. It causes large-vessel occlusions and a poor prognosis. Regardless of ischemic stroke etiology, hyperacute therapy strategies are effective treatment modalities. Methods: Patients who were diagnosed as having AF were classified as AF (+) and others without AF were classified as AF (-). It is not clear which treatment should be preferred in patients with stroke who are AF (+). We studied demographic characteristics, recanalization rates, and clinical outcomes in acute patients with ischemic stroke with or without nonvalvular AF who underwent hyperacute treatments. Results: We detected that clinical findings were more severe and the NIHSS scores were significantly higher at admission inpatients who were AF (+). In our study, mechanical thrombectomy rates were high in patients who were AF (+), whereas intravenous tissue plasminogen activator treatment rates were higher in patients who were AF (-). Thrombolysis in cerebral infarction scores were similar in our patient groups. We found high rates of both symptomatic (PH 2) and asymptomatic hemorrhagic transformation in patients who were AF (+) in 24th-h cranial computed tomography. A positive correlation was found between symptom-admission, symptom-needle, and symptom-groin times and discharge-modified Rankin Scale scores regardless of the hyperacute treatments in all patient groups. Conclusion: As a result, physicians should focus on the diagnosis of AF, and appropriate anticoagulant treatment is important for primary prevention.

Association between Infarct Location and Hemorrhagic Transformation of Acute Ischemic Stroke following Successful Recanalization after Mechanical Thrombectomy.

The association between infarct location and hemorrhagic transformation of acute ischemic stroke after mechanical thrombectomy is not understood. We aimed to evaluate the association between CTP-based ischemic core variables at admission and hemorrhagic transformation after a successful thrombectomy. We retrospectively analyzed patients who underwent endovascular thrombectomy for acute anterior circulation large-vessel occlusion between October 2019 and June 2021. We enrolled 146 patients with visible ischemic core on pretreatment CTP who had successful reperfusion. The ischemic core infarct territories were classified into the cortical and subcortical areas and then qualitatively and quantitatively analyzed by CTP. Logistic regression and receiver operating characteristic curve analyses were performed to determine the association between ischemic core variables and hemorrhagic transformation. Of the 146 patients analyzed, 72 (49.3%) had hemorrhagic transformation and 23 (15.8%) had symptomatic intracerebral hemorrhage. Multivariate analysis showed that subcortical infarcts were independently associated with hemorrhagic transformation (OR, 8.06; 95% CI, 2.31-28.10; P = .001) and subcortical infarct volume was independently linked to symptomatic intracerebral hemorrhage (OR, 1.05; 95% CI, 1.01-1.09; P = .039). The receiver operating characteristic curve indicated that subcortical infarcts can predict hemorrhagic transformation accurately (area under the curve = 0.755; 95% CI, 0.68-0.82; P < .001) and subcortical infarct volume can predict symptomatic intracerebral hemorrhage (area under the curve = 0.694; 95% CI, 0.61-0.77; P = .002). Subcortical infarcts seen on CTP at admission are associated with hemorrhagic transformation in patients after successful thrombectomy, and subcortical infarct volume may influence the risk of symptomatic intracerebral hemorrhage.

Neutrophil to High-Density Lipoprotein Ratio is Associated with Hemorrhagic Transformation in Patients with Acute Ischemic Stroke.

Hemorrhagic transformation (HT) is one of the most common and severe complications in patients with acute ischemic stroke (AIS). It indicates a poor prognosis in AIS patients. However, the association of neutrophil to high-density lipoprotein ratio (NHR) with HT remains unclear. This study examined whether the NHR has a predictive effect on HT in AIS patients and explored the predictive cutoff value of the NHR. This is a retrospective study and consecutively included AIS patients admitted to the Department of Neurology of the First Affiliated Hospital of Wannan Medical College between December 2019 and January 2022. All subjects had blood samples collected within 24 h of admission, and neutrophil counts and high-density lipoprotein counts were detected. HT was diagnosed with hemorrhage on subsequent magnetic resonance imaging (MRI) or computed tomography (CT) of the brain. Univariate logistic regression analysis was performed to identify confounding factors, and multivariate logistic regression analysis determined the correlation between NHR and HT. Receiver operating characteristic (ROC) curves were used to evaluate the clinical predictive value of NHR. A total of 725 patients were finally included in this study, of which 87 (12%) developed HT. The median NHR value in the HT group was 4.31, which was significantly higher than that in the non-HT group, and the difference was statistically significant [4.31 (3.54-6.24) vs 3.63 (2.68-4.64), p < 0.001]. The binary logistic regression analysis showed that NHR was independently associated with HT in AIS patients (OR: 1.180, 95% CI: 1.036-1.344, p = 0.013). The area under ROC curve (AUC) of NHR for predicting HT in AIS patients was 0.633 (95% CI: 0.567-0.699, p < 0.001), and its optimal cutoff were 3.52. The NHR was a reliable and simple independent predictor of HT in AIS patients.

Association between malnutrition risk and hemorrhagic transformation in patients with acute ischemic stroke.

Background and aimsMalnutrition is a prevalent problem occurring in different diseases. Hemorrhagic transformation (HT) is a severe complication of acute ischemic stroke (AIS). Few studies have evaluated the association between malnutrition risk and hemorrhagic transformation in patients with acute stroke. We aim to investigate the influence of malnutrition risk on the risk of hemorrhagic transformation in patients with AIS.MethodsA total of 182 consecutive adults with HT and 182 age- and sex-matched patients with stroke were enrolled in this study. The controlling nutritional status (CONUT) score was calculated to evaluate the malnutrition risk. HT was detected by follow-up imaging assessment and was radiologically classified as hemorrhagic infarction type 1 or 2 or parenchymal hematoma type 1 or 2. Logistic regression models were conducted when participants were divided into different malnutrition risk groups according to the objective nutritional score to assess the risk for HT.ResultsThe prevalence of moderate to severe malnutrition risk in patients with AIS was 12.5%, according to the CONUT score. Univariate analysis showed that the CONUT score is significantly higher in patients with HT than those without HT. After adjusting for potential covariables, the patients with mild risk and moderate to severe malnutrition risk were associated with a higher risk of HT compared to the patients in the normal nutritional status group [odds ratio, 3.180 (95% CI, 1.139–8.874), P = 0.027; odds ratio, 3.960 (95% CI, 1.015–15.453), P = 0.048, respectively].ConclusionMalnutrition risk, measured by CONUT score, was significantly associated with an increased risk of hemorrhagic transformation in patients with AIS.

Radiomics-based infarct features on CT predict hemorrhagic transformation in patients with acute ischemic stroke.

ObjectiveTo develop and validate a model based on the radiomics features of the infarct areas on non-contrast-enhanced CT to predict hemorrhagic transformation (HT) in acute ischemic stroke.Materials and methodsA total of 118 patients diagnosed with acute ischemic stroke in two centers from January 2019 to February 2022 were included. The radiomics features of infarcted areas on non-contrast-enhanced CT were extracted using 3D-Slicer. A univariate analysis and the least absolute shrinkage and selection operator (LASSO) were used to select features, and the radiomics score (Rad-score) was then constructed. The predictive model of HT was constructed by analyzing the Rad-score and clinical and imaging features in the training cohort, and it was verified in the validation cohort. The model was evaluated with the receiver operating characteristic curve, calibration curve and decision curve, and the prediction performance of the model in different scenarios was further discussed hierarchically.ResultsOf the 118 patients, 52 developed HT, including 21 cases of hemorrhagic infarct (HI) and 31 cases of parenchymal hematoma (PH). The Rad-score was constructed from five radiomics features and was the only independent predictor for HT. The predictive model was constructed from the Rad-score. The area under the curve (AUCs) of the model for predicting HT in the training and validation cohorts were 0.845 and 0.750, respectively. Calibration curve and decision curve analyses showed that the model performed well. Further analysis found that the model predicted HT for different infarct sizes or treatment methods in the training and validation cohorts with 78.3 and 71.4% accuracy, respectively. For all samples, the model predicted an AUC of 0.754 for HT in patients within 4.5 h since stroke onset, and predicted an AUC of 0.648 for PH.ConclusionThis model, which was based on CT radiomics features, could help to predict HT in the setting of acute ischemic stroke for any infarct size and provide guiding suggestions for clinical treatment and prognosis evaluation.

Glucose to Platelet Ratio: A Potential Predictor of Hemorrhagic Transformation in Patients with Acute Ischemic Stroke.

Glucose and platelet are two easily obtained clinical indicators; the present research aimed to demonstrate their association with hemorrhagic transformation (HT) in acute ischemic stroke (AIS) patients without thrombolytic or thrombectomy therapy. This was a single-center retrospective study. Patients who were diagnosed with HT after AIS were included in the HT group. Meanwhile, using the propensity score matching (PSM) approach, with a ratio of 1:2, matched patients without HT were included in the non-HT group. Serum G/P levels were measured on the first morning after admission (at least eight hours after the last meal). Characteristics were compared between the two groups. Multivariate logistic regression was used to determine the independent relationship between G/P and HT after AIS, with G/P being divided into quartiles. From January 2013 to March 2022, we consecutively included 643 AIS patients with HT (426/643 [66.25%] with HI and 217/643 [33.75%] with PH), and 1282 AIS patients without HT, at the First Affiliated Hospital of Wenzhou Medical University. The HT group had higher G/P levels than the non-HT group (0.04 ± 0.02 vs. 0.03 ± 0.02, p < 0.001). However, there was no difference in G/P levels between HI and PH subgroups (0.04 ± 0.02 vs. 0.04 ± 0.02, p > 0.05). Moreover, the G/P levels were divided into quartiles (Q1 ≤ 0.022; Q2 = 0.023–0.028; Q3 = 0.029–0.039; Q4 ≥ 0.040), with Q1 being settled as the reference layer. After controlling the confounders, multivariate regression analyses showed that the Q4 layer (Q4: G/P ≥ 0.040) was independently associated with elevated HT risk (odds ratio [OR] = 1.85, 95% CI = 1.31–2.63, p < 0.001). G/P levels on admission were independently associated with HT risk in AIS patients. In clinical practice, adequate attention should be paid to AIS patients with elevated G/P levels (G/P ≥ 0.040).