Risk factors of poor prognosis in patients with acute ischemic stroke after bridging therapy

Risk factors of poor prognosis in patients with acute ischemic stroke after bridging therapy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Risk factors of poor prognosis in patients with acute ischemic stroke after bridging therapy wan wei, Kefan Qiu, Tian Nie, Danyu Feng, Fei Liu, Jiahui Zhu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4731325/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The poor prognosis of patients with acute ischemic stroke (AIS) after bridging therapy (BT) imposes a heavy burden on their families. This study decided to investigate the risk factors for poor prognosis and establish a predictive model. Objective: To explore the risk factors of poor prognosis in patients with AIS after BT. Methods: The study included AIS patients treated with BT (intravenous thrombolysis with alteplase prior to endovascular thrombectomy) from January 2020 to December 2023 in the Hangzhou First People's Hospital. Modified Rankin scale (mRS)was used to assess the patient’s prognosis after 3 months, and these patients were divided into the poor prognosis group (mRS > 2) and good prognosis group (mRS ≤ 2) according to the mRS.The patients' history of chronic diseases and the laboratory testing data were recorded. SPSS 25 was used for statistical analysis.Receiver operating characteristics (ROC) curves and logistic regression analysis were used to explore associated factors of AIS treated with BT. Results: We studied 120 AIS patients treated with BT.The poor prognosis group included 65 cases and good prognosis group included 55 cases.In the poor prognosis group, the patients with higher proportion of stroke-associated pneumonia (SAP), Symptomatic intracranial hemorrhage(sICH) and intracranial hemorrhage (ICH), and with higher NIHSS score at admission were older, concomitantly, the fasting plasma glucose (FBG) was significantly higher than those of the good prognosis group (P < 0.05). Multivariate logistic regression analysis showed SAP and NIHSS score were independent risk factors for poor prognosis of patients with AIS after BT (P < 0.05).The ROC analysis showed that the area under curve (AUC) of SAP was 0.717 (95% CI = 0.622–0.811), for the NIHSS score, the AUC was 0.716 (95% CI = 0.624–0.807), and the optimal cutoff threshold, sensitivity, and specificity were 15.4, 0.754, 0.564 respectively.When SAP combined with NIHSS score,we created a 2-item prediction model.In this model, the AUC increased to 0.809 (95% CI = 0.732–0.886), and the optimal cut-off, sensitivity, and specificity were 0.522,0.831, 0.691 respectively. Conclusion: Age, FBG, SAP, sICH ,ICH, and NIHSS score at admission were associated with poor prognosis of AIS patients after BT, while SAP and NIHSS score were independent risk factors for poor prognosis. The NIHSS score plus the SAP had a high diagnostic performance and predictive value for poor prognosis in patients with AIS treated with BT. Acute ischemic stroke Bridging therapy Risk factors poor prognosis Intravenous thrombolysis Endovascular thrombectomy Figures Figure 1 1. Introduction Bridging therapy(BT) has been used in clinical practice and can improve functional outcomes [ 1 ] , and it refers to intravenous thrombolysis (IVT) prior to endovascular thrombectomy (EVT) for most patients with large vessel occlusion [ 2 ] . IVT can recanalize the occluded blood vessel, save ischemic penumbra, promote early recanalization and achieve reperfusion [ 3 – 5 ] . EVT was used to treat AIS with large vessel occlusion, while BT is recommended in treatment guidelines for patients with AIS caused by large vessel occlusion [ 6 ] ,but it is also a complicated procedure that can cause more cerebral hemorrhages [ 7 ] . IVT and EVT are two classic treatments for AIS patients. Previous studies have only focused on the safety and efficacy of BT [ 8 – 9 ] , however,few studies have been conducted on the risk factors for poor prognosis in BT.Given the various risks and uncertainties factors associated with poor prognosis by BT, the aim of our study is to investigate the risk factors, and prognosis of AIS after BT,and establish a predictive model to explore their predictive value. 2. Materials and methods 2.1. Study participants We retrospectively analyzed the clinical data of AIS patients treated with BT in Hangzhou City First People's Hospital from January 2020 to October 2023.Written informed consent was waived, All patients received BT according to current acute stroke management guidelines [ 6 ] . These patients were divided into the poor prognosis group (mRS > 2) and good prognosis group (mRS ≤ 2) according to the mRS.Inclusion criteria:all patients were treated with BT; clinical data were complete; exclusion criteria: combined malignant tumor; the dose of IVT with alteplase did not use the standard dose;surgical contraindications; lack of clinical data. 2.2. Clinical and Biochemical Measurements. Clinical information and baseline demographic for all enrolled patients included gender,age and medical history (hypertension, diabetes mellitus, coronary artery disease, atrial fibrillation, current smoking). Laboratory data included blood glucose at admission, FBG, neutrophil-to-lymphocyte ratio (NLR), serum Amyloid A (SAA) ,C-reactive protein(CRP), HbAIc, triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), homocysteine (HCY). Clinical findings included systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index(BMI) ,NIHSS score at admission,SAP,sICH ,ICH, TOAST classification(including large artery atherosclerosis(LAA),cardioembolism and others), site of vascular territories, symptom onset to thrombolysis time (OTT), symptom onset to groin puncture time (OTP), symptom onset to first recanalization time (OTR), puncture to first recanalization time (PTR), thrombolysis to puncture time(TTP), TOAST classification [ 10 ] . Ischemic stroke was classified as anterior circulation stroke (ACS) and posterior circulation stroke (PCS) according to the vascular territories in which infarction occurs [ 11 ] . Clinical outcomes after 3 months included good outcomes(mRS ≤ 2) and poor outcomes(mRS>2) [ 12 ] . 2.3 Statistical analysis SPSS Statistics 25 was used for statistical analyse.Continuous data were expressed as mean ± standard deviation, and analyzed with Student t-test or Mann-Whitney U test according to the normality of data distribution. Categorical variables were described as counts (percentages) and were compared using Pearson χ 2 or Fisher exact tests. Multivariate logistic regression analysis was performed to assess the independent risk factors of poor prognosis in patients with AIS after BT (P < 0.05).The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of risk factors for poor prognosis of patients with AIS after BT ,meanwhile the criterion for selecting the optimum cutoff point depended on the Youden’s index. A P value < 0.05 (two-tailed) was considered to be statistically significant. 3. Result 3.1 Patients’ Demographic and Clinical Characteristics A total of 120 eligible patients were included, with an average age of 68.68 ± 11.16 years, including 74 males (66.7%) and 46 females (38.3%). The poor prognosis group include 65 patients,with an average age of 70.89 ± 10.97 years, including 37 males (56.90%) and 28 females (43.10%), and good prognosis group include 55 cases, with an average age of 66.07 ± 10.91 years, including 37 males (67.30%) and 18 females (32.70%). Univariate analysis of the clinical data from the two groups demonstrated that members of the poor prognosis group were older, with a higher NIHSS score on admission, SAP,sICH and ICH,concomitantly, FBG of poor prognosis group were significantly higher than those of good prognosis group (P 0.05). See Table 1 for details. 3.2 Multivariate logistic regression analysis risk factors for poor prognosis in patients with AIS after BT. Multiple logistic regression analysis risk factors for AIS after BT showed that SAP(OR = 4.110, 95% CI 1.511–11.179, P = 0.006) and NIHSS score (OR = 1.199, 95% CI 1.083–1.326, P = 0.000) were independent risk factors for poor prognosis.See Table 2 for details. 3.3 ROC curve analyses the diagnostic performance of poor prognosis in patients with AIS after BT. The AUC of the ROC curve was calculated to measure the sensitivity and specificity of the variables with statistical significance, as shown in Table 3 and Fig. 1 , we found that the calculated AUC was 0.717 for SAP, 0.716 for the NIHSS score, and 0.809 for SAP plus the NIHSS score. The cut-off value for detecting AIS after BT based on the distribution of specificities and sensitivities was also calculated. For NIHSS score, a cutoff value of ≥ 15.40 with a sensitivity of 75.40% and a specificity of 56.40% were used to detect poor prognosis in patients AIS after BT. For the SAP plus NIHSS score, that the sensitivity was 83.10% and specificity was 69.10% which indicate a better diagnostic potential than the index of SAP or NIHSS score alone. 4. Discussion Stroke is the leading cause of death and disability in China, with high rates of incidence, disability, mortality and recurrence. The key to treating AIS is to dredge the occluded blood vessels as soon as possible [ 13 ] . According to national and international guidelines [ 14 – 15 ] , IVT should be performed prior to EVT for AIS patients who are eligible for IVT and EVT,in addition, previous studies have consistently shown that patients with anterior circulation arterial occlusions benefit from EVT after IVT [ 16 – 18 ] . Timely application of IVT can recanalize the occluded vessels, save ischemic penumbra and ultimately reduce mortality and disability rate of ischemic stroke.However, IVT has limited thrombolytic effect on larger thrombi, especially cardiogenic cerebral embolism, which is more common in clinic. In order to overcome the deficiency of IVT, more attention has been paid to EVT when the effect of IVT treatment is not obvious,therefore,BT has become the current mainstream treatment option for patients with AIS caused by large vessel occlusion. It is well known that BT treatment is relatively expensive and brings heavy economic burden to families, and good prognosis can reduce the burden for patients in the future. However, some patients still have poor prognosis after BT timely, as a result,early identification and management of high-risk patients are necessary to prevent the poor prognosis of AIS after BT. The aim of this study was to determine which clinical risk factors independently were related to poor prognosis,and establish a predictive model to explore their predictive value.The earlier studies [ 19 ] have reported that age, SBP, FBG, LAA, atrial fibrillation were risk factors of early neurological deterioration (END) after BT, and END was associated with poor prognosis for patients with AIS by BT.Partly consistent with previous report,addition to age and FBG,we also found that SAP, sICH ,ICH, and NIHSS score at admission were risk factors, and we did not find the impact of SBP, LAA and atrial fibrillation in these risk factors of our current study. In this study, the poor prognosis group were older, with a higher proportion of SAP,sICH and ICH,concomitantly, FBG and NIHSS score on admission were significantly higher than those of good prognosis group,the reason was considered to be related to aging-related comorbidities. With an increase in age, a decrease of immune function result in an increased risk of infectious diseases, especially SAP. Patients with a high NIHSS score indicated that their conditions were more serious (often complicated with disturbance of consciousness and dysphagia), were relatively bedridden, were more likely to cause aspiration, and were more likely to experience serious complications, leading to poor prognosis. Concurrently, the level of FBG in the poor prognosis group was significantly higher than the good prognosis group, which was consistent with previous reports [ 20 – 21 ] . In that report, due to stress reaction, acute stroke patients’ blood glucose was increased, and their body immunity was reduced. A study by Kamada H et al. found that hyperglycemia can aggravate the deterioration of neurological function, and lead to blood-brain barrier dysfunction after ischemia reperfusion injury through blood oxidative stress [ 22 ] . Desiles et al. proposed that hyperglycemia triggers a thromboinflammatory cascade and stimulate distal microthrombosis, which lead to poor reperfusion and impaired neurological dysfunction [ 23 ] . In addition, gender, chronic disease history, lipids, blood pressure, other inflammatory markers, TOAST classification, occlusion vascular territories, IVT, and EVT window time did not have any significance between good and poor prognosis groups. SAP and NIHSS score were independent risk factors of poor prognosis for AIS after BT. IVT is the mainstay of treatment for AIS when administered within 4.5 hours of symptom onset [ 24 ] . Despite its efficacy is excellent, the most feared complication of intravenous alteplase is hemorrhagic transformation(HT), particularly sICH. Previous studies have shown superior efficacy and safety of EVT compared to conservative treatment alone and have not shown an increased incidence of clinically relevant HT [ 25 ] . HT is a common complication in patients with AIS, especially after IVT [ 26 ] ,which can lead to acute neurological deterioration.What’s more, mild HT can cause poor outcomes [ 27 ] . HT can be classified as ICH or sICH [ 28 – 29 ] , and sICH is associated with a higher risk of clinical complications, prolonged hospital stay, and worse clinical outcomes at discharge [ 30 ] .It is consistent with our study that HT is a risk factor of poor prognosis for AIS after BT. Multiple regression analysis demonstrated that NIHSS score,SAP were independent risk factors for poor prognosis. Moreover,when the SAP combined with NIHSS score, which have higher AUC ,sensitivity and specificity than its individual, Therefore, we created a combined model including SAP and NIHSS score that is more sensitive to predict poor outcomes of AIS patients with BT.these findings may contribute to distinguishing AIS patients with a high risk of poor prognosis after BT, thereby facilitating timely clinical intervention and appropriate treatment. This study has some limitations. First, the research object was a small sample, and the risk factors for poor prognosis of AIS patients after BT were not adequately representative. Additionally, there may not exclude residual confounding effects interfering with ability of NIHSS score and SAP to predict poor prognosis, although we adjusted for multiple potential confounders such as age, FBG,sICH,ICH. Finally, this study was a retrospective analysis. the occurrence of poor prognosis in a small number of patients was mainly judged by telephone follow-up, and there was a certain bias.We would need to expand further the sample size for subgroup analysis and etiological analysis. In conclusion, the risk factors of poor prognosis in patients with AIS after BT for SAP were multifaceted,age,FBG,SAP, sICH ,ICH, and NIHSS score at admission. SAP and NIHSS score were independent risk factors. we created a combined model including SAP and NIHSS score that is more sensitive to predict poor outcomes of AIS patients with BT. Those findings are beneficial to identify high-risk patients, control the risk factors actively, reduce the occurrence of poor prognosis, and improve the prognosis of patients with AIS. Abbreviations AIS, acute ischemic stroke BT, bridging therapy mRS, modified Rankin scale ROC, receiver operating characteristics SAP, stroke-associated pneumonia sICH, symptomatic intracranial hemorrhage ICH, intracranial hemorrhage NIHSS, National Institutes of Health Stroke Scale FBG , fasting blood glucose AUC, area under the curve IVT , intravenous thrombolysis EVT, endovascular thrombectomy NLR， neutrophil-to-lymphocyte ratio SAA， serum Amyloid A CRP， c-reactive protein TG, triglycerides TC, total cholesterol HDL, high-density lipoprotein LDL, low-density lipoprotein HCY, homocysteine SBP, systolic blood pressure DBP, diastolic blood pressure BMI, body mass index LAA, large artery atherosclerosis OTT, symptom onset to thrombolysis time OTP, symptom onset to groin puncture time OTR, symptom onset to first recanalization time PTR, puncture to first recanalization time TTP， thrombolysis to puncture time ACS, anterior circulation stroke PCS, posterior circulation stroke END, neurological deterioration HT, hemorrhagic transformation Declarations Authors’ contributions Wan Wei ,Kefan Qiu and Tian Nie conceived and designed the research; Danyu Feng and Fei Liu collected the data; Jiahui Zhu，Chao Huang and Xiaoqin Hong were responsible for the statistical analysis. Liuhai Zhang composed the figures and tables. All authors contributed to data interpretation and approved the final manuscript. Ethic s approval and consent to participate Not applicable. Consent for publication Written informed consent was waived, given the retrospective nature of the study by the ethics committee of affiliated Hangzhou First People's Hospital, School of Medicine,Westlake University . Availability of data and materials All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author. Funding This work was funded by the Hangzhou Biomedical and Health Industry Development Support Science and Technology Special Project (2022WJC143), Medical and health project (2021KY727), Medical and health science project (A20210510). Conflict of interest The authors declare no conflict of interest, financial or otherwise. Acknowledgements Declared none. References Chen H, Qiu Y, Wang Z, et al. 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Variable Good prognosis Group (n=55) P oor prognosis group (n=65) P Value Gender,male,n(%) Age(year) Hypertension,n(%) Diabetes mellitus,n(%) Coronary artery disease,n(%) Atrial fibrillation,n(%) Current smoking,n(%) Admission blood glucose FBG(mmol/l) NLR SAA CRP HbAIc TG (mmol/L) TC(mmol/L) HDL (mmol/L) LDL (mmol/L) HCY (umol/L) SBP at admission DBP at admission BMI NIHSS score at admission SAP,n(%) sICH,n(%) ICH,n(%) TOAST Classification LAA,n (%) Cardioembolism ,n (%) Others,n (%) Occlusion Vascular Territories ACS,n(%) PCS,n(%) OTT(min) OTP(min) OTR(min) PTR (min) TTP(min) 37(67.30) 66.07±10.91 43(78.20) 11(20.00) 4(7.30) 22(40.00) 17(30.90) 7.76 ±2.56 6.08 ±1.97 8.32±6.79 64.11±77.98 18.88±20.70 5.92±0.81 1.51± 1.19 4.01 ±0.81 1.09 ±0.25 2.19 ±0.62 15.49± 13.08 145.60± 25.01 83.85 ±15.22 23.30 ±2.90 14.36± 4.72 21(38.2) 1(1.80） 9(16.40) 26(47.30) 26(47.30) 3(5.50) 49(89.10) 6(10.90) 105.65±46.98 436.60±337.4 475.91±341.0 39.31±17.95 350.74±315.3 37(56.90) 70.89 ±10.97 48(73.80) 13(20.00) 4(6.20) 37(56.90) 17(26.20) 8.36 ±2.42 7.18 ±2.69 8.42±5.30 69.26±87.41 22.80±28.98 6.01±0.93 1.23± 0.91 4.06± 0.90 1.16± 0.29 2.24 ±0.71 16.62± 15.65 144.34 ±23.38 81.68 ± 12.83 22.55± 3.26 18.95± 6.36 53(81.5) 12(18.50) 27(41.50) 23(35.40) 33(50.80) 9(13.80) 55(84.60) 10(15.40) 131.88±69.67 487.97±360.80 532.83±361.74 487.97±360.80 532.83±361.74 0.245 0.020 0.580 1.000 0.807 0.065 0.565 0.093 0.010 0.497 0.451 0.837 0.963 0.025 0.632 0.161 0.600 0.827 0.927 0.495 0.185 0.000 0.000 0.003 0.003 0.202 0.472 0.143 0.153 0.103 0.841 0.828 Note: FBG,fasting blood glucose; NLR, neutrophil-to-lymphocyte ratio; SAA, serum amyloid A; CRP，C-reactive protein;TG, triglycerides; TC, total cholesterol; HDL, high-density lipoprotein; LDL, low-density lipoprotein;HCY, homocysteine; SBP,systolic blood pressure;DBP,diastolic blood pressure;BMI ,Body mass index;NIHSS,national institutes of health stroke scale;SAP, stroke-associated pneumonia; sICH, symptomatic intracranial hemorrhage;ICH , intracranial hemorrhage; LAA, large artery atherosclerosis; ACS, anterior circulation stroke;PCS, posterior circulation stroke; OTT, symptom onset to thrombolysis time;OTP, symptom onset to groin puncture time;OTR, symptom onset to first recanalization time ; PTR, puncture to first recanalization time；TTP，thrombolysis to puncture time. Table 2. Multivariate logistic regression analysis of risk factors for poor prognosis with AIS after BT. Variables OR value 95%CI P value Age 1.041 0.994-1.091 0.089 FBG 1.187 0.928-1.520 0.173 SAP 4.110 1.511-11.179 0.006 sICH 6.400 0.700-58.522 0.100 ICH 2.270 0.869-5.926 0.094 NIHSS 1.199 1.083-1.326 0.000 Note: FBG,fasting blood glucose; SAP,stroke-associated pneumonia; sICH,symptomatic intracranial hemorrhage; ICH , intracranial hemorrhage; NIHSS, national institutes of health stroke scale;OR, odds ratio;CI, confidence interval. Table 3.ROC Curve Analyses . Parameter AUC Cut-off value 95%CI sensitivity Specificity P-value SAP 0.717 - 0.622-0.811 - - 0.000 NIHSS 0.716 15.4 0.624-0.807 0.754 0.564 0.000 SAP+NIHSS 0.809 0.522 0.732-0.886 0.831 0.691 0.000 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4731325","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":328189186,"identity":"4b63b015-6dc8-4269-b113-8a9971c41a30","order_by":0,"name":"wan wei","email":"","orcid":"","institution":"Affiliated Hangzhou First People's Hospital，School of Medicine，Westlake University","correspondingAuthor":false,"prefix":"","firstName":"wan","middleName":"","lastName":"wei","suffix":""},{"id":328189187,"identity":"3c7ccad1-ecd9-4004-8ccc-29c2740f0044","order_by":1,"name":"Kefan Qiu","email":"","orcid":"","institution":"Affiliated Hangzhou First People's Hospital，School of Medicine，Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Kefan","middleName":"","lastName":"Qiu","suffix":""},{"id":328189188,"identity":"b892d5ac-f76d-4cec-9d69-5b478b5a1a1a","order_by":2,"name":"Tian Nie","email":"","orcid":"","institution":"Affiliated Hangzhou First People's Hospital，School of Medicine，Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Tian","middleName":"","lastName":"Nie","suffix":""},{"id":328189189,"identity":"4284d5b6-50fd-4f2c-b7e3-843d36ade613","order_by":3,"name":"Danyu Feng","email":"","orcid":"","institution":"Affiliated Hangzhou First People's Hospital，School of Medicine，Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Danyu","middleName":"","lastName":"Feng","suffix":""},{"id":328189190,"identity":"91bfe225-358f-4351-86d7-a3bc14989ac4","order_by":4,"name":"Fei Liu","email":"","orcid":"","institution":"Affiliated Hangzhou First People's Hospital，School of Medicine，Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Liu","suffix":""},{"id":328189191,"identity":"b705e1b9-0eec-4017-85dd-c7672a4aa68b","order_by":5,"name":"Jiahui Zhu","email":"","orcid":"","institution":"Affiliated Hangzhou First People's Hospital，School of Medicine，Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Jiahui","middleName":"","lastName":"Zhu","suffix":""},{"id":328189192,"identity":"219940ac-e463-40ca-b4ad-def788dcbab4","order_by":6,"name":"Chao Huang","email":"","orcid":"","institution":"Affiliated Hangzhou First People's Hospital，School of Medicine，Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Huang","suffix":""},{"id":328189193,"identity":"b9f02c9c-bdff-4145-8225-ffbc94d8fcc7","order_by":7,"name":"Xiaoqin Hong","email":"","orcid":"","institution":"Affiliated Hangzhou First People's Hospital，School of Medicine，Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoqin","middleName":"","lastName":"Hong","suffix":""},{"id":328189194,"identity":"a77642ee-ec7e-478f-8188-b22104948b50","order_by":8,"name":"Liuhai Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYDACCRBRIMFgwMDYcCChwoaHn7+BGC0GYC2NBz6cSZORnHGAKC1gxHxwZtthG4OGBPw65Gc3P3v4xcAicTv74YbDPGfO8xgwHGD88DEHtxbGOcfMjWUMJBJ39iQCtVTc5jFnbmCWnLkNtxZmiQQzaQmglg0HQFrO3OaxbDjAxsyLRwubRPo3iJbzDxsO87ad4zE4kIBfC49EjpnkB5CWG4kNQO8fIKxFQiKnTBoYyMYbbjxsAAZyMo/kjIPNeP0iPyN9m+SPijrZDefTH39IqLCz5+dvPvjhIx4t4CDgQeUzNuBXD1Lyg6CSUTAKRsEoGNEAAAjQWG54K/k1AAAAAElFTkSuQmCC","orcid":"","institution":"Affiliated Hangzhou First People's Hospital，School of Medicine，Westlake University","correspondingAuthor":true,"prefix":"","firstName":"Liuhai","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-07-12 15:36:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4731325/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4731325/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62222815,"identity":"e5a28441-1a38-4ba6-b49e-7dbce8c471b2","added_by":"auto","created_at":"2024-08-11 12:40:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":43461,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curve\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: \u003c/strong\u003eNIHSS, National Institutes of Health Stroke Scale; SAP,stroke-associated pneumonia;AUC,area under the curve;The cutoff value were obtained by maximizing the sum of sensitivity and specificity (maximum Youden index).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4731325/v1/5780434bfebd919f690ef9e4.png"},{"id":63284624,"identity":"8347a79c-7c8d-43cf-a93f-22fa3c2fb56e","added_by":"auto","created_at":"2024-08-26 13:31:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":678919,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4731325/v1/67211f10-5088-4ec2-a953-54a754965f27.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk factors of poor prognosis in patients with acute ischemic stroke after bridging therapy","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBridging therapy(BT) has been used in clinical practice and can improve functional outcomes\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e, and it refers to intravenous thrombolysis (IVT) prior to endovascular thrombectomy (EVT) for most patients with large vessel occlusion\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. IVT can recanalize the occluded blood vessel, save ischemic penumbra, promote early recanalization and achieve reperfusion\u003csup\u003e[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. EVT was used to treat AIS with large vessel occlusion, while BT is recommended in treatment guidelines for patients with AIS caused by large vessel occlusion\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e,but it is also a complicated procedure that can cause more cerebral hemorrhages\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. IVT and EVT are two classic treatments for AIS patients. Previous studies have only focused on the safety and efficacy of BT\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e, however,few studies have been conducted on the risk factors for poor prognosis in BT.Given the various risks and uncertainties factors associated with poor prognosis by BT, the aim of our study is to investigate the risk factors, and prognosis of AIS after BT,and establish a predictive model to explore their predictive value.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study participants\u003c/h2\u003e \u003cp\u003eWe retrospectively analyzed the clinical data of AIS patients treated with BT in Hangzhou City First People's Hospital from January 2020 to October 2023.Written informed consent was waived, All patients received BT according to current acute stroke management guidelines\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. These patients were divided into the poor prognosis group (mRS\u0026thinsp;\u0026gt;\u0026thinsp;2) and good prognosis group (mRS\u0026thinsp;\u0026le;\u0026thinsp;2) according to the mRS.Inclusion criteria:all patients were treated with BT; clinical data were complete; exclusion criteria: combined malignant tumor; the dose of IVT with alteplase did not use the standard dose;surgical contraindications; lack of clinical data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Clinical and Biochemical Measurements.\u003c/h2\u003e \u003cp\u003eClinical information and baseline demographic for all enrolled patients included gender,age and medical history (hypertension, diabetes mellitus, coronary artery disease, atrial fibrillation, current smoking). Laboratory data included blood glucose at admission, FBG, neutrophil-to-lymphocyte ratio (NLR), serum Amyloid A (SAA) ,C-reactive protein(CRP), HbAIc, triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), homocysteine (HCY). Clinical findings included systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index(BMI) ,NIHSS score at admission,SAP,sICH ,ICH, TOAST classification(including large artery atherosclerosis(LAA),cardioembolism and others), site of vascular territories, symptom onset to thrombolysis time (OTT), symptom onset to groin puncture time (OTP), symptom onset to first recanalization time (OTR), puncture to first recanalization time (PTR), thrombolysis to puncture time(TTP), TOAST classification\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Ischemic stroke was classified as anterior circulation stroke (ACS) and posterior circulation stroke (PCS) according to the vascular territories in which infarction occurs\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Clinical outcomes after 3 months included good outcomes(mRS\u0026thinsp;\u0026le;\u0026thinsp;2) and poor outcomes(mRS\u0026gt;2)\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e \u003cp\u003e SPSS Statistics 25 was used for statistical analyse.Continuous data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and analyzed with Student t-test or Mann-Whitney U test according to the normality of data distribution. Categorical variables were described as counts (percentages) and were compared using Pearson χ 2 or Fisher exact tests. Multivariate logistic regression analysis was performed to assess the independent risk factors of poor prognosis in patients with AIS after BT (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of risk factors for poor prognosis of patients with AIS after BT ,meanwhile the criterion for selecting the optimum cutoff point depended on the Youden\u0026rsquo;s index. A P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (two-tailed) was considered to be statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Result","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Patients\u0026rsquo; Demographic and Clinical Characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 120 eligible patients were included, with an average age of 68.68\u0026thinsp;\u0026plusmn;\u0026thinsp;11.16 years, including 74 males (66.7%) and 46 females (38.3%). The poor prognosis group include 65 patients,with an average age of 70.89\u0026thinsp;\u0026plusmn;\u0026thinsp;10.97 years, including 37 males (56.90%) and 28 females (43.10%), and good prognosis group include 55 cases, with an average age of 66.07\u0026thinsp;\u0026plusmn;\u0026thinsp;10.91 years, including 37 males (67.30%) and 18 females (32.70%). Univariate analysis of the clinical data from the two groups demonstrated that members of the poor prognosis group were older, with a higher NIHSS score on admission, SAP,sICH and ICH,concomitantly, FBG of poor prognosis group were significantly higher than those of good prognosis group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). There was no significant difference in other indicators between the two groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). See Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e for details.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Multivariate logistic regression analysis risk factors for poor prognosis in patients with AIS after BT.\u003c/h2\u003e\n \u003cp\u003eMultiple logistic regression analysis risk factors for AIS after BT showed that SAP(OR\u0026thinsp;=\u0026thinsp;4.110, 95% CI 1.511\u0026ndash;11.179, P\u0026thinsp;=\u0026thinsp;0.006) and NIHSS score (OR\u0026thinsp;=\u0026thinsp;1.199, 95% CI 1.083\u0026ndash;1.326, P\u0026thinsp;=\u0026thinsp;0.000) were independent risk factors for poor prognosis.See Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e for details.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 ROC curve analyses the diagnostic performance of poor prognosis in patients with AIS after BT.\u003c/h2\u003e\n \u003cp\u003eThe AUC of the ROC curve was calculated to measure the sensitivity and specificity of the variables with statistical significance, as shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, we found that the calculated AUC was 0.717 for SAP, 0.716 for the NIHSS score, and 0.809 for SAP plus the NIHSS score. The cut-off value for detecting AIS after BT based on the distribution of specificities and sensitivities was also calculated. For NIHSS score, a cutoff value of \u0026ge;\u0026thinsp;15.40 with a sensitivity of 75.40% and a specificity of 56.40% were used to detect poor prognosis in patients AIS after BT. For the SAP plus NIHSS score, that the sensitivity was 83.10% and specificity was 69.10% which indicate a better diagnostic potential than the index of SAP or NIHSS score alone.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eStroke is the leading cause of death and disability in China, with high rates of incidence, disability, mortality and recurrence. The key to treating AIS is to dredge the occluded blood vessels as soon as possible\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. According to national and international guidelines\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e, IVT should be performed prior to EVT for AIS patients who are eligible for IVT and EVT,in addition, previous studies have consistently shown that patients with anterior circulation arterial occlusions benefit from EVT after IVT \u003csup\u003e[\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Timely application of IVT can recanalize the occluded vessels, save ischemic penumbra and ultimately reduce mortality and disability rate of ischemic stroke.However, IVT has limited thrombolytic effect on larger thrombi, especially cardiogenic cerebral embolism, which is more common in clinic. In order to overcome the deficiency of IVT, more attention has been paid to EVT when the effect of IVT treatment is not obvious,therefore,BT has become the current mainstream treatment option for patients with AIS caused by large vessel occlusion.\u003c/p\u003e \u003cp\u003eIt is well known that BT treatment is relatively expensive and brings heavy economic burden to families, and good prognosis can reduce the burden for patients in the future. However, some patients still have poor prognosis after BT timely, as a result,early identification and management of high-risk patients are necessary to prevent the poor prognosis of AIS after BT. The aim of this study was to determine which clinical risk factors independently were related to poor prognosis,and establish a predictive model to explore their predictive value.The earlier studies \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003ehave reported that age, SBP, FBG, LAA, atrial fibrillation were risk factors of early neurological deterioration (END) after BT, and END was associated with poor prognosis for patients with AIS by BT.Partly consistent with previous report,addition to age and FBG,we also found that SAP, sICH ,ICH, and NIHSS score at admission were risk factors, and we did not find the impact of SBP, LAA and atrial fibrillation in these risk factors of our current study.\u003c/p\u003e \u003cp\u003eIn this study, the poor prognosis group were older, with a higher proportion of SAP,sICH and ICH,concomitantly, FBG and NIHSS score on admission were significantly higher than those of good prognosis group,the reason was considered to be related to aging-related comorbidities. With an increase in age, a decrease of immune function result in an increased risk of infectious diseases, especially SAP. Patients with a high NIHSS score indicated that their conditions were more serious (often complicated with disturbance of consciousness and dysphagia), were relatively bedridden, were more likely to cause aspiration, and were more likely to experience serious complications, leading to poor prognosis. Concurrently, the level of FBG in the poor prognosis group was significantly higher than the good prognosis group, which was consistent with previous reports\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. In that report, due to stress reaction, acute stroke patients\u0026rsquo; blood glucose was increased, and their body immunity was reduced. A study by Kamada H \u003cem\u003eet al.\u003c/em\u003e found that hyperglycemia can aggravate the deterioration of neurological function, and lead to blood-brain barrier dysfunction after ischemia reperfusion injury through blood oxidative stress \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Desiles et al. proposed that hyperglycemia triggers a thromboinflammatory cascade and stimulate distal microthrombosis, which lead to poor reperfusion and impaired neurological dysfunction \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. In addition, gender, chronic disease history, lipids, blood pressure, other inflammatory markers, TOAST classification, occlusion vascular territories, IVT, and EVT window time did not have any significance between good and poor prognosis groups. SAP and NIHSS score were independent risk factors of poor prognosis for AIS after BT.\u003c/p\u003e \u003cp\u003eIVT is the mainstay of treatment for AIS when administered within 4.5 hours of symptom onset\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Despite its efficacy is excellent, the most feared complication of intravenous alteplase is hemorrhagic transformation(HT), particularly sICH. Previous studies have shown superior efficacy and safety of EVT compared to conservative treatment alone and have not shown an increased incidence of clinically relevant HT\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. HT is a common complication in patients with AIS, especially after IVT\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e,which can lead to acute neurological deterioration.What\u0026rsquo;s more, mild HT can cause poor outcomes\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. HT can be classified as ICH or sICH \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e, and sICH is associated with a higher risk of clinical complications, prolonged hospital stay, and worse clinical outcomes at discharge\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e.It is consistent with our study that HT is a risk factor of poor prognosis for AIS after BT.\u003c/p\u003e \u003cp\u003eMultiple regression analysis demonstrated that NIHSS score,SAP were independent risk factors for poor prognosis. Moreover,when the SAP combined with NIHSS score,\u003c/p\u003e \u003cp\u003ewhich have higher AUC ,sensitivity and specificity than its individual, Therefore, we created a combined model including SAP and NIHSS score that is more sensitive to predict poor outcomes of AIS patients with BT.these findings may contribute to distinguishing AIS patients with a high risk of poor prognosis after BT, thereby facilitating timely clinical intervention and appropriate treatment.\u003c/p\u003e \u003cp\u003eThis study has some limitations. First, the research object was a small sample, and the risk factors for poor prognosis of AIS patients after BT were not adequately representative. Additionally, there may not exclude residual confounding effects interfering with ability of NIHSS score and SAP to predict poor prognosis, although we adjusted for multiple potential confounders such as age, FBG,sICH,ICH. Finally, this study was a retrospective analysis. the occurrence of poor prognosis in a small number of patients was mainly judged by telephone follow-up, and there was a certain bias.We would need to expand further the sample size for subgroup analysis and etiological analysis.\u003c/p\u003e \u003cp\u003eIn conclusion, the risk factors of poor prognosis in patients with AIS after BT for SAP were multifaceted,age,FBG,SAP, sICH ,ICH, and NIHSS score at admission. SAP and NIHSS score were independent risk factors. we created a combined model including SAP and NIHSS score that is more sensitive to predict poor outcomes of AIS patients with BT. Those findings are beneficial to identify high-risk patients, control the risk factors actively, reduce the occurrence of poor prognosis, and improve the prognosis of patients with AIS.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAIS, \u0026nbsp; acute ischemic stroke\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBT, \u0026nbsp; \u0026nbsp;bridging therapy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003emRS, \u0026nbsp; modified Rankin scale\u003c/p\u003e\n\u003cp\u003eROC, \u0026nbsp; receiver operating characteristics\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSAP, \u0026nbsp; stroke-associated pneumonia\u0026nbsp;\u003c/p\u003e\n\u003cp\u003esICH, \u0026nbsp; symptomatic intracranial hemorrhage\u003c/p\u003e\n\u003cp\u003eICH, \u0026nbsp; \u0026nbsp;intracranial hemorrhage\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNIHSS, \u0026nbsp;National Institutes of Health Stroke Scale\u003c/p\u003e\n\u003cp\u003eFBG , \u0026nbsp; fasting blood glucose\u003c/p\u003e\n\u003cp\u003eAUC, \u0026nbsp; area under the curve\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIVT\u0026nbsp;, \u0026nbsp;\u0026nbsp;intravenous thrombolysis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEVT,\u0026nbsp;\u0026nbsp;\u0026nbsp;endovascular thrombectomy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNLR，\u0026nbsp;neutrophil-to-lymphocyte ratio\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSAA，\u0026nbsp;serum Amyloid A \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCRP，\u0026nbsp;c-reactive protein\u003c/p\u003e\n\u003cp\u003eTG, \u0026nbsp; triglycerides\u003c/p\u003e\n\u003cp\u003eTC, \u0026nbsp; total cholesterol\u003c/p\u003e\n\u003cp\u003eHDL, \u0026nbsp;high-density lipoprotein\u003c/p\u003e\n\u003cp\u003eLDL, \u0026nbsp;low-density lipoprotein\u003c/p\u003e\n\u003cp\u003eHCY, \u0026nbsp;homocysteine\u003c/p\u003e\n\u003cp\u003eSBP, \u0026nbsp; systolic blood pressure\u003c/p\u003e\n\u003cp\u003eDBP, \u0026nbsp; diastolic blood pressure\u003c/p\u003e\n\u003cp\u003eBMI, \u0026nbsp;body mass index\u003c/p\u003e\n\u003cp\u003eLAA, \u0026nbsp;large artery atherosclerosis\u003c/p\u003e\n\u003cp\u003eOTT, \u0026nbsp;symptom onset to thrombolysis time\u003c/p\u003e\n\u003cp\u003eOTP, \u0026nbsp;symptom onset to groin puncture time\u003c/p\u003e\n\u003cp\u003eOTR, \u0026nbsp;symptom onset to first recanalization time\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePTR, \u0026nbsp;puncture to first recanalization time\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTTP，\u0026nbsp;thrombolysis to puncture time\u003c/p\u003e\n\u003cp\u003eACS, \u0026nbsp;anterior circulation stroke\u003c/p\u003e\n\u003cp\u003ePCS, \u0026nbsp;posterior circulation stroke\u003c/p\u003e\n\u003cp\u003eEND, \u0026nbsp;neurological deterioration\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHT, \u0026nbsp; hemorrhagic transformation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWan Wei ,Kefan Qiu and Tian Nie\u0026nbsp;conceived and designed the research;\u0026nbsp;Danyu Feng and Fei Liu\u0026nbsp;collected the data;\u0026nbsp;Jiahui Zhu，Chao Huang and Xiaoqin Hong\u0026nbsp;were responsible for the statistical analysis.\u0026nbsp;Liuhai Zhang\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ecomposed the figures and tables. All authors contributed to data interpretation and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthic\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was waived, given the retrospective nature of the study by the ethics committee of affiliated Hangzhou First People\u0026apos;s Hospital,\u0026nbsp;School of Medicine,Westlake University\u0026nbsp;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the Hangzhou Biomedical and Health Industry Development Support Science and Technology Special Project (2022WJC143), Medical and health project (2021KY727), Medical and health science project (A20210510).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest, financial or otherwise.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDeclared none.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChen H, Qiu Y, Wang Z, et al. Bridging Therapy Improves Functional Outcomes and Reduces 90-Day Mortality Compared with Direct Endovascular Thrombectomy in Patients with Acute Posterior Ischemic Stroke: A Systematic Review and Meta-Analysis[J]. Neurol Sci. 2024;45(2):495\u0026ndash;506.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShafique MA, Ali S, Mustafa MS, et al. Meta-Analysis of Direct Endovascular Thrombectomy Vs Bridging Therapy in the Management of Acute Ischemic Stroke with Large Vessel Occlusion[J]. Clin Neurol Neurosurg. 2024;236:108070.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDesilles JP, Loyau S, Syvannarath V, et al. Alteplase Reduces Downstream Microvascular Thrombosis and Improves the Benefit of Large Artery Recanalization in Stroke[J]. Stroke. 2015;46(11):3241\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTurc G, Bhogal P, Fischer U, et al. European Stroke Organisation (ESO) - European Society for Minimally Invasive Neurological Therapy (ESMINT) Guidelines on Mechanical Thrombectomy in Acute Ischaemic StrokeEndorsed by Stroke Alliance for Europe (SAFE)[J]. Eur Stroke J. 2019;4(1):6\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFischer U, Kaesmacher J, Strbian D, et al. Thrombectomy Alone Versus Intravenous Alteplase Plus Thrombectomy in Patients with Stroke: An Open-Label, Blinded-Outcome, Randomised Non-Inferiority Trial[J]. Lancet. 2022;400(10346):104\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePowers WJ, Rabinstein AA, Ackerson T, et al. Guidelines for the Early Management of Patients with Acute Ischemic Stroke: 2019 Update to the 2018 Guidelines for the Early Management of Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association[J]. Stroke. 2019;50(12):e344\u0026ndash;418.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNouh A, Remke J, Ruland S. Ischemic Posterior Circulation Stroke: A Review of Anatomy, Clinical Presentations, Diagnosis, and Current Management[J]. Front Neurol. 2014;5:30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJi X, Song B, Zhu H, et al. A Study On Endovascular Treatment Alone and Bridging Treatment for Acute Ischemic Stroke[J]. Eur J Med Res. 2023;28(1):12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu W, Zhao J, Liu H, et al. Safety and Efficacy of Direct Thrombectomy Versus Bridging Therapy in Patients with Acute Ischemic Stroke Eligible for Intravenous Thrombolysis: A Meta-Analysis of Randomized Controlled Trials[J]. World Neurosurg. 2023;175:113\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdams HJ, Bendixen BH, Kappelle LJ, et al. Classification of Subtype of Acute Ischemic Stroke. Definitions for Use in a Multicenter Clinical Trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment[J]. Stroke. 1993;24(1):35\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCui Y, Meng WH, Chen HS. Early Neurological Deterioration After Intravenous Thrombolysis of Anterior Vs Posterior Circulation Stroke: A Secondary Analysis of INTRECIS[J]. Sci Rep. 2022;12(1):3163.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim JM, Bae JH, Park KY, et al. Incidence and Mechanism of Early Neurological Deterioration After Endovascular Thrombectomy[J]. J Neurol. 2019;266(3):609\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePowers WJ, Rabinstein AA, Ackerson T, et al. 2018 Guidelines for the Early Management of Patients with Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association[J]. Stroke. 2018;49(3):e46\u0026ndash;110.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLou M, Ding J, Hu B, et al. Chinese Stroke Association Guidelines for Clinical Management of Cerebrovascular Disorders: Executive Summary and 2019 Update On Organizational Stroke Management[J]. Stroke Vasc Neurol. 2020;5(3):260\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorrection to: Guidelines for the Early Management of Patients with Acute Ischemic Stroke. Stroke. 2019;50(12):e440\u0026ndash;1. : 2019 Update to the 2018 Guidelines for the Early Management of Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association[J].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBracard S, Ducrocq X, Mas JL, et al. Mechanical Thrombectomy After Intravenous Alteplase Versus Alteplase Alone After Stroke (THRACE): A Randomised Controlled Trial[J]. Lancet Neurol. 2016;15(11):1138\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Souza AC, Martins SO, Polanczyk CA et al. Cost-Effectiveness of Mechanical Thrombectomy for Acute Ischemic Stroke in Brazil: Results From the RESILIENT Trial[J]. Int J Stroke, 2021: 1068788028.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoyal M, Demchuk AM, Menon BK, et al. Randomized Assessment of Rapid Endovascular Treatment of Ischemic Stroke[J]. N Engl J Med. 2015;372(11):1019\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie Y, Li S, Liu L, et al. Risk Factors and Prognosis of Early Neurological Deterioration after Bridging Therapy[J]. Curr Neurovasc Res; 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJi R, Shen H, Pan Y, et al. Novel Risk Score to Predict Pneumonia After Acute Ischemic Stroke[J]. Stroke. 2013;44(5):1303\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Zhang Y, Ma L, et al. Risk of Stroke-Associated Pneumonia During Hospitalization: Predictive Ability of Combined A(2)DS(2) Score and Hyperglycemia[J]. BMC Neurol. 2019;19(1):298.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamada H, Yu F, Nito C, et al. Influence of Hyperglycemia On Oxidative Stress and Matrix Metalloproteinase-9 Activation After Focal Cerebral Ischemia/Reperfusion in Rats: Relation to Blood-Brain Barrier Dysfunction[J]. Stroke. 2007;38(3):1044\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDesilles JP, Syvannarath V, Ollivier V, et al. Exacerbation of Thromboinflammation by Hyperglycemia Precipitates Cerebral Infarct Growth and Hemorrhagic Transformation[J]. Stroke. 2017;48(7):1932\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFurie KL, Jayaraman MV. 2018 Guidelines for the Early Management of Patients with Acute Ischemic Stroke[J]. Stroke, 2018, 49(3): 509\u0026ndash;510.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoyal M, Menon BK, van Zwam WH, et al. Lancet. 2016;387(10029):1723\u0026ndash;31. Endovascular Thrombectomy After Large-Vessel Ischaemic Stroke: A Meta-Analysis of Individual Patient Data From Five Randomised Trials[J].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang J, Yang Y, Sun H, et al. Hemorrhagic Transformation After Cerebral Infarction: Current Concepts and Challenges[J]. Ann Transl Med. 2014;2(8):81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Kranendonk KR, Treurniet KM, Boers A, et al. Hemorrhagic Transformation is Associated with Poor Functional Outcome in Patients with Acute Ischemic Stroke Due to a Large Vessel Occlusion[J]. J Neurointerv Surg. 2019;11(5):464\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHacke W, Kaste M, Fieschi C, et al. Randomised Double-Blind Placebo-Controlled Trial of Thrombolytic Therapy with Intravenous Alteplase in Acute Ischaemic Stroke (ECASS II). Second European-Australasian Acute Stroke Study Investigators[J]. Lancet. 1998;352(9136):1245\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evon Kummer R, Broderick JP, Campbell BC, et al. The Heidelberg Bleeding Classification: Classification of Bleeding Events After Ischemic Stroke and Reperfusion Therapy[J]. Stroke. 2015;46(10):2981\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndrade J, Mohr JP, Lima FO, et al. The Role of Hemorrhagic Transformation in Acute Ischemic Stroke upon Clinical Complications and Outcomes[J]. J Stroke Cerebrovasc Dis. 2020;29(8):104898.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Baseline characteristics of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eg\u003c/strong\u003e\u003cstrong\u003eood\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eprognosis\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;g\u003c/strong\u003e\u003cstrong\u003eroup\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;poor\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eprognosis\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;g\u003c/strong\u003e\u003cstrong\u003eroup\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ein patients with AIS after BT.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.77328646748682%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.780316344463973%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGood\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eprognosis\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eGroup (n=55)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.022847100175746%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003eoor prognosis group\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(n=65)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.423550087873462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP Value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.77328646748682%\" valign=\"top\"\u003e\n \u003cp\u003eGender,male,n(%)\u003c/p\u003e\n \u003cp\u003eAge(year)\u003c/p\u003e\n \u003cp\u003eHypertension,n(%)\u003c/p\u003e\n \u003cp\u003eDiabetes mellitus,n(%)\u003c/p\u003e\n \u003cp\u003eCoronary artery disease,n(%)\u003c/p\u003e\n \u003cp\u003eAtrial fibrillation,n(%)\u003c/p\u003e\n \u003cp\u003eCurrent smoking,n(%)\u003c/p\u003e\n \u003cp\u003eAdmission blood glucose\u003c/p\u003e\n \u003cp\u003eFBG(mmol/l)\u003c/p\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003cp\u003eSAA\u003c/p\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003cp\u003eHbAIc\u003c/p\u003e\n \u003cp\u003eTG (mmol/L)\u003c/p\u003e\n \u003cp\u003eTC(mmol/L)\u003c/p\u003e\n \u003cp\u003eHDL (mmol/L)\u003c/p\u003e\n \u003cp\u003eLDL (mmol/L)\u003c/p\u003e\n \u003cp\u003eHCY (umol/L)\u003c/p\u003e\n \u003cp\u003eSBP at admission\u003c/p\u003e\n \u003cp\u003eDBP at admission\u003c/p\u003e\n \u003cp\u003eBMI\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNIHSS score at admission\u003c/p\u003e\n \u003cp\u003eSAP,n(%)\u003c/p\u003e\n \u003cp\u003esICH,n(%)\u003c/p\u003e\n \u003cp\u003eICH,n(%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTOAST Classification\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eLAA,n (%)\u003c/p\u003e\n \u003cp\u003eCardioembolism ,n (%)\u003c/p\u003e\n \u003cp\u003eOthers,n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eOcclusion Vascular Territories\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eACS,n(%)\u003c/p\u003e\n \u003cp\u003ePCS,n(%)\u003c/p\u003e\n \u003cp\u003eOTT(min)\u003c/p\u003e\n \u003cp\u003eOTP(min)\u003c/p\u003e\n \u003cp\u003eOTR(min)\u003c/p\u003e\n \u003cp\u003ePTR (min)\u003c/p\u003e\n \u003cp\u003eTTP(min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.780316344463973%\" valign=\"top\"\u003e\n \u003cp\u003e37(67.30)\u003c/p\u003e\n \u003cp\u003e66.07\u0026plusmn;10.91\u003c/p\u003e\n \u003cp\u003e43(78.20)\u003c/p\u003e\n \u003cp\u003e11(20.00)\u003c/p\u003e\n \u003cp\u003e4(7.30)\u003c/p\u003e\n \u003cp\u003e22(40.00)\u003c/p\u003e\n \u003cp\u003e17(30.90)\u003c/p\u003e\n \u003cp\u003e7.76\u0026nbsp;\u0026plusmn;2.56\u003c/p\u003e\n \u003cp\u003e6.08\u0026nbsp;\u0026plusmn;1.97\u003c/p\u003e\n \u003cp\u003e8.32\u0026plusmn;6.79\u003c/p\u003e\n \u003cp\u003e64.11\u0026plusmn;77.98\u003c/p\u003e\n \u003cp\u003e18.88\u0026plusmn;20.70\u003c/p\u003e\n \u003cp\u003e5.92\u0026plusmn;0.81\u003c/p\u003e\n \u003cp\u003e1.51\u0026plusmn;\u0026nbsp;1.19\u003c/p\u003e\n \u003cp\u003e4.01\u0026nbsp;\u0026plusmn;0.81\u003c/p\u003e\n \u003cp\u003e1.09\u0026nbsp;\u0026plusmn;0.25\u003c/p\u003e\n \u003cp\u003e2.19\u0026nbsp;\u0026plusmn;0.62\u003c/p\u003e\n \u003cp\u003e15.49\u0026plusmn;\u0026nbsp;13.08\u003c/p\u003e\n \u003cp\u003e145.60\u0026plusmn;\u0026nbsp;25.01\u003c/p\u003e\n \u003cp\u003e83.85\u0026nbsp;\u0026plusmn;15.22\u003c/p\u003e\n \u003cp\u003e23.30\u0026nbsp;\u0026plusmn;2.90\u003c/p\u003e\n \u003cp\u003e14.36\u0026plusmn;\u0026nbsp;4.72\u003c/p\u003e\n \u003cp\u003e21(38.2)\u003c/p\u003e\n \u003cp\u003e1(1.80）\u003c/p\u003e\n \u003cp\u003e9(16.40)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e26(47.30)\u003c/p\u003e\n \u003cp\u003e26(47.30)\u003c/p\u003e\n \u003cp\u003e3(5.50)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e49(89.10)\u003c/p\u003e\n \u003cp\u003e6(10.90)\u003c/p\u003e\n \u003cp\u003e105.65\u0026plusmn;46.98\u003c/p\u003e\n \u003cp\u003e436.60\u0026plusmn;337.4\u003c/p\u003e\n \u003cp\u003e475.91\u0026plusmn;341.0\u003c/p\u003e\n \u003cp\u003e39.31\u0026plusmn;17.95\u003c/p\u003e\n \u003cp\u003e350.74\u0026plusmn;315.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.022847100175746%\" valign=\"top\"\u003e\n \u003cp\u003e37(56.90)\u003c/p\u003e\n \u003cp\u003e70.89\u0026nbsp;\u0026plusmn;10.97\u003c/p\u003e\n \u003cp\u003e48(73.80)\u003c/p\u003e\n \u003cp\u003e13(20.00)\u003c/p\u003e\n \u003cp\u003e4(6.20)\u003c/p\u003e\n \u003cp\u003e37(56.90)\u003c/p\u003e\n \u003cp\u003e17(26.20)\u003c/p\u003e\n \u003cp\u003e8.36\u0026nbsp;\u0026plusmn;2.42\u003c/p\u003e\n \u003cp\u003e7.18\u0026nbsp;\u0026plusmn;2.69\u003c/p\u003e\n \u003cp\u003e8.42\u0026plusmn;5.30\u003c/p\u003e\n \u003cp\u003e69.26\u0026plusmn;87.41\u003c/p\u003e\n \u003cp\u003e22.80\u0026plusmn;28.98\u003c/p\u003e\n \u003cp\u003e6.01\u0026plusmn;0.93\u003c/p\u003e\n \u003cp\u003e1.23\u0026plusmn;\u0026nbsp;0.91\u003c/p\u003e\n \u003cp\u003e4.06\u0026plusmn;\u0026nbsp;0.90\u003c/p\u003e\n \u003cp\u003e1.16\u0026plusmn;\u0026nbsp;0.29\u003c/p\u003e\n \u003cp\u003e2.24\u0026nbsp;\u0026plusmn;0.71\u003c/p\u003e\n \u003cp\u003e16.62\u0026plusmn;\u0026nbsp;15.65\u003c/p\u003e\n \u003cp\u003e144.34\u0026nbsp;\u0026plusmn;23.38\u003c/p\u003e\n \u003cp\u003e81.68\u0026nbsp;\u0026plusmn;\u0026nbsp;12.83\u003c/p\u003e\n \u003cp\u003e22.55\u0026plusmn;\u0026nbsp;3.26\u003c/p\u003e\n \u003cp\u003e18.95\u0026plusmn;\u0026nbsp;6.36\u003c/p\u003e\n \u003cp\u003e53(81.5)\u003c/p\u003e\n \u003cp\u003e12(18.50)\u003c/p\u003e\n \u003cp\u003e27(41.50)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23(35.40)\u003c/p\u003e\n \u003cp\u003e33(50.80)\u003c/p\u003e\n \u003cp\u003e9(13.80)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e55(84.60)\u003c/p\u003e\n \u003cp\u003e10(15.40)\u003c/p\u003e\n \u003cp\u003e131.88\u0026plusmn;69.67\u003c/p\u003e\n \u003cp\u003e487.97\u0026plusmn;360.80\u003c/p\u003e\n \u003cp\u003e532.83\u0026plusmn;361.74\u003c/p\u003e\n \u003cp\u003e487.97\u0026plusmn;360.80\u003c/p\u003e\n \u003cp\u003e532.83\u0026plusmn;361.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.423550087873462%\" valign=\"top\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003cp\u003e0.580\u003c/p\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003cp\u003e0.565\u003c/p\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003cp\u003e0.837\u003c/p\u003e\n \u003cp\u003e0.963\u003c/p\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003cp\u003e0.927\u003c/p\u003e\n \u003cp\u003e0.495\u003c/p\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.472\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003cp\u003e0.841\u003c/p\u003e\n \u003cp\u003e0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u0026nbsp;\u003c/strong\u003eFBG,fasting blood glucose; NLR, neutrophil-to-lymphocyte ratio; SAA, serum amyloid A; CRP，C-reactive protein;TG, triglycerides; TC, total cholesterol; HDL, high-density lipoprotein; LDL, low-density lipoprotein;HCY, homocysteine; SBP,systolic blood pressure;DBP,diastolic blood pressure;BMI ,Body mass index;NIHSS,national institutes of health stroke scale;SAP, stroke-associated pneumonia; sICH, symptomatic intracranial hemorrhage;ICH , intracranial hemorrhage; LAA, large artery atherosclerosis; ACS, anterior circulation stroke;PCS, posterior circulation stroke; OTT, symptom onset to thrombolysis time;OTP, symptom onset to groin puncture time;OTR, symptom onset to first recanalization time ; PTR, puncture to first recanalization time；TTP，thrombolysis to puncture time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMultivariate logistic regression analysis of risk factors for\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003epoor\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eprognosis\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ewith AIS after BT.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"562\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.45907473309609%\" valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.90391459074733%\" valign=\"bottom\"\u003e\n \u003cp\u003eOR value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.750889679715304%\" valign=\"bottom\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.88612099644128%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;P value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.45907473309609%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.90391459074733%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.750889679715304%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.994-1.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.88612099644128%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.45907473309609%\" valign=\"top\"\u003e\n \u003cp\u003eFBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.90391459074733%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.750889679715304%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.928-1.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.88612099644128%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.45907473309609%\" valign=\"top\"\u003e\n \u003cp\u003eSAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.90391459074733%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.750889679715304%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.511-11.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.88612099644128%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.45907473309609%\" valign=\"top\"\u003e\n \u003cp\u003esICH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.90391459074733%\" valign=\"bottom\"\u003e\n \u003cp\u003e6.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.750889679715304%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.700-58.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.88612099644128%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.45907473309609%\" valign=\"top\"\u003e\n \u003cp\u003eICH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.90391459074733%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.750889679715304%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.869-5.926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.88612099644128%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.45907473309609%\" valign=\"top\"\u003e\n \u003cp\u003eNIHSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.90391459074733%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.750889679715304%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.083-1.326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.88612099644128%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u0026nbsp;\u003c/strong\u003eFBG,fasting blood glucose; SAP,stroke-associated pneumonia; sICH,symptomatic intracranial hemorrhage; ICH , intracranial hemorrhage; NIHSS, national institutes of health stroke scale;OR, odds ratio;CI, confidence interval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.ROC Curve Analyses\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.298555377207062%\" valign=\"top\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.309791332263242%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.125200642054574%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCut-off value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.569823434991974%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.088282504012842%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003esensitivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.841091492776886%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.76725521669342%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.298555377207062%\" valign=\"top\"\u003e\n \u003cp\u003eSAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.309791332263242%\" valign=\"top\"\u003e\n \u003cp\u003e0.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.125200642054574%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.569823434991974%\" valign=\"top\"\u003e\n \u003cp\u003e0.622-0.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.088282504012842%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.841091492776886%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.76725521669342%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.298555377207062%\" valign=\"top\"\u003e\n \u003cp\u003eNIHSS\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.309791332263242%\" valign=\"top\"\u003e\n \u003cp\u003e0.716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.125200642054574%\" valign=\"top\"\u003e\n \u003cp\u003e15.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.569823434991974%\" valign=\"top\"\u003e\n \u003cp\u003e0.624-0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.088282504012842%\" valign=\"top\"\u003e\n \u003cp\u003e0.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.841091492776886%\" valign=\"top\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.76725521669342%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.298555377207062%\" valign=\"top\"\u003e\n \u003cp\u003eSAP+NIHSS\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.309791332263242%\" valign=\"top\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.125200642054574%\" valign=\"top\"\u003e\n \u003cp\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.569823434991974%\" valign=\"top\"\u003e\n \u003cp\u003e0.732-0.886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.088282504012842%\" valign=\"top\"\u003e\n \u003cp\u003e0.831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.841091492776886%\" valign=\"top\"\u003e\n \u003cp\u003e0.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.76725521669342%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acute ischemic stroke, Bridging therapy, Risk factors, poor prognosis, Intravenous thrombolysis, Endovascular thrombectomy","lastPublishedDoi":"10.21203/rs.3.rs-4731325/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4731325/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe poor prognosis of patients with acute ischemic stroke (AIS) after bridging therapy (BT) imposes a heavy burden on their families. This study decided to investigate the risk factors for poor prognosis and establish a predictive model.\u003c/p\u003e\u003cp\u003e\u003cb\u003eObjective:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo explore the risk factors of poor prognosis in patients with AIS after BT.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe study included AIS patients treated with BT (intravenous thrombolysis with alteplase prior to endovascular thrombectomy) from January 2020 to December 2023 in the Hangzhou First People's Hospital. Modified Rankin scale (mRS)was used to assess the patient\u0026rsquo;s prognosis after 3 months, and these patients were divided into the poor prognosis group (mRS\u0026thinsp;\u0026gt;\u0026thinsp;2) and good prognosis group (mRS\u0026thinsp;\u0026le;\u0026thinsp;2) according to the mRS.The patients' history of chronic diseases and the laboratory testing data were recorded. SPSS 25 was used for statistical analysis.Receiver operating characteristics (ROC) curves and logistic regression analysis were used to explore associated factors of AIS treated with BT.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe studied 120 AIS patients treated with BT.The poor prognosis group included 65 cases and good prognosis group included 55 cases.In the poor prognosis group, the patients with higher proportion of stroke-associated pneumonia (SAP), Symptomatic intracranial hemorrhage(sICH) and intracranial hemorrhage (ICH), and with higher NIHSS score at admission were older, concomitantly, the fasting plasma glucose (FBG) was significantly higher than those of the good prognosis group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Multivariate logistic regression analysis showed SAP and NIHSS score were independent risk factors for poor prognosis of patients with AIS after BT (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).The ROC analysis showed that the area under curve (AUC) of SAP was 0.717 (95% CI\u0026thinsp;=\u0026thinsp;0.622\u0026ndash;0.811), for the NIHSS score, the AUC was 0.716 (95% CI\u0026thinsp;=\u0026thinsp;0.624\u0026ndash;0.807), and the optimal cutoff threshold, sensitivity, and specificity were 15.4, 0.754, 0.564 respectively.When SAP combined with NIHSS score,we created a 2-item prediction model.In this model, the AUC increased to 0.809 (95% CI\u0026thinsp;=\u0026thinsp;0.732\u0026ndash;0.886), and the optimal cut-off, sensitivity, and specificity were 0.522,0.831, 0.691 respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAge, FBG, SAP, sICH ,ICH, and NIHSS score at admission were associated with poor prognosis of AIS patients after BT, while SAP and NIHSS score were independent risk factors for poor prognosis. The NIHSS score plus the SAP had a high diagnostic performance and predictive value for poor prognosis in patients with AIS treated with BT.\u003c/p\u003e","manuscriptTitle":"Risk factors of poor prognosis in patients with acute ischemic stroke after bridging therapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-11 12:40:04","doi":"10.21203/rs.3.rs-4731325/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d4849e5e-1d51-449d-abed-414f4f6d2904","owner":[],"postedDate":"August 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-26T13:23:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-11 12:40:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4731325","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4731325","identity":"rs-4731325","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}