Muscle Strength at Discharge as Predictor of Functional Outcome in Ischemic Stroke Patients Following Endovascular Therapy: Observational Study in Two Comprehensive Stroke Centers

Muscle Strength at Discharge as Predictor of Functional Outcome in Ischemic Stroke Patients Following Endovascular Therapy: Observational Study in Two Comprehensive Stroke Centers | 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 Article Muscle Strength at Discharge as Predictor of Functional Outcome in Ischemic Stroke Patients Following Endovascular Therapy: Observational Study in Two Comprehensive Stroke Centers Sijie Zhou, Zhikai Chen, Jinyan Tang, Gan Chen, Ziqi Ouyang, Jian Wang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4893440/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 Endovascular thrombectomy (EVT) has emerged within the last few years as a safe and efficacious method to achieve arterial recanalization in patients with acute ischemic stroke (AIS). However, there are few clinical methods to predict functional outcome. We aimed to investigate whether the muscle strength (MS) at discharge assessed by the Medical Research Council (MRC) scale for muscle strength/weakness predicted functional outcome in patients with AIS undergoing EVT. Methods We enrolled 264 consecutive patients from two large comprehensive stroke centers in China from 2018 to 2022. A total of 248 patients were analyzed. We measured and analyzed muscle strength by means of the MRC scale at discharge. Patients were divided in two groups: normal to mildly abnormal muscle strength (MRC ≥ 4), and markedly decreased muscle strength (MRC < 4). A poor outcome was defined as a modified Ranking Score (mRS) of 3–6 at 90-days. Results Logistic regression showed that older age ( p = 0.014), higher pre-EVT NIHSS score ( p = 0.006), greater ASPECTS ( p = 0.052), longer door-to-recanalization time ( p = 0.016) and post-EVT revascularization ≥ 2b ( p = 0.025), were independently associated with MRC < 4. Patients with poor muscle strength at discharge (MRC < 4) had a significantly higher frequency of poor outcome at 90-days: 91.37% vs. 13.76% ( p < 0.001). Both lower and upper limb strength in the most paretic side showed high accuracy in predicting the functional outcome at 90 days: area under the curve: 0.924 and 0.874, respectively. An MRC of 0 (plegia or complete paralysis), was associated with a 70% mortality rate within 3 months of AIS. Conclusion Muscle strength is a reliable, easy to assess and reproducible clinical method to predict functional outcome and mortality at 90-days in patients treated with EVT and it is influenced by age, NIHSS score, extend of tissue involvement and time for recanalization. Health sciences/Medical research/Study design/Clinical trials Health sciences/Medical research/Experimental models of disease Endovascular therapy Muscle strength Patient outcome Stroke Thrombectomy Figures Figure 1 Figure 2 Figure 3 Introduction Acute ischemic stroke (AIS) following large vessel occlusion is one of the most devastating neurological emergencies associated with high mortality and disability [ 1 ]. Reperfusion therapies have revolutionized the treatment of acute ischemic stroke in the last 30 years. Before 2014, intravenous (IV) recombinant tissue-type plasminogen activator (rt-PA –alteplase-) was the mainstay therapy in AIS patients. However, since publication of multiple endovascular thrombectomy (EVT) trials in 2015; EVT has become the standard of care for arterial recanalization in large vessel occlusion patients, as this therapy improved functional outcomes [ 2 ]. These trials used new-generation stent-retriever devices, which showed a clear superiority for EVT compared with previous generation devices or standard medical care alone [ 2 , 3 ]. Currently, EVT is recommended in major practice guidelines from Europe and North America for patients with proximal middle cerebral artery or internal carotid artery occlusions who have received treatment with IV rt-PA within 4.5 hours of onset, who can undergo the procedure within 6 hours of symptom onset. Further studies have shown that mechanical thrombectomy could improve outcomes in selected AIS patients with large vessel occlusions up-to 24-hour from symptom onset [ 2 ]. Patients achieving maximal clinical benefit with EVT are those with a greater probability for early recanalization limiting irreversible ischemic damage [ 4 ]. A proxy for such hemodynamic outcome would be regaining function in the affected cortical area, for example recovering muscle strength (MS). We hypothesized that AIS patients undergoing EVT who showed an early recovery in MS will have a better outcome at 90 days according to the modified Ranking Scale (mRS). We also aimed to assess which variables were predictors for early recovery of MS in these patients. We conducted a study aimed to assess the functional outcome in AIS patients undergoing EVT. Materials and Methods Study population We retrospectively analyzed prospectively collected data of 264 consecutive AIS patients treated with EVT from 2018 to 2022 in two comprehensive tertiary care stroke centers in China, the Foshan Sanshui District People’s Hospital and the First People's Hospital of Foshan. Patients with AIS and large vessel occlusion on neuroimaging or by clinical presentation were triaged for EVT. Thrombus aspiration or a combined approach using a stent retriever plus aspiration was used in most cases. The approach varied according to the thrombus location and individual vascular anatomy. Patients received standard care with IV rt-PA, if they presented within the 4.5-hour time-window and no contraindications for this therapy were present. The data was derived from the Bigdata observatory platform for stroke in China ( https://ss.chinasdc.cn ) and the individual hospitals’ data platforms. Inclusion criteria were the following: 1) patients aged 18 years-old or older, 2) patients with AIS who underwent EVT within 24 hours of symptom onset, and 3) pre-morbid mRS ≤ 2. Exclusion criteria were the following: 1) patients with missing follow-up, and 2) death during hospitalization. Data Collection The followed clinical data were collected for each patient: age, sex, risk factors for cerebrovascular disease and history of prior stroke. The pre-treatment National Institutes of Health Stroke Scale (NIHSS) and mRS scores were determined. We used the pre-treatment Alberta Stroke Program Early CT Score (ASPECTS) method in order to assess the infarct core volume. The sites of arterial occlusion were also registered. In order to assess the speed and quality of recanalization, we used the onset-to-needle time (ONT), door-to-needle time (DNT) for IV rt-PA and door-to-puncture time (DPT), door-to-recanalization time (DRT) and last known normal-to-puncture-time (LKNPT) for EVT. The modified thrombolysis in cerebral infarction (mTICI) score was used to evaluate the degree of arterial reperfusion (0/1: No or minimal reperfusion; 2a: partial filling 50%; 3: complete perfusion) after thrombectomy; an mTICI post-EVT scores of 2b or 3 were considered as successful recanalization [ 5 ]. The MS in the more severely affected side was registered for each patient and determined according to the Medical Research Council (MRC) scale [ 6 ] (Panel). In order to use a simple quantitative metric, the MS of knee-joint extension and elbow joint bicep were recorded and analyzed in this study. Panel. Medical Research Council (MRC) scale for muscle strength/weakness grading Grade Description 0 No contraction 1 Trace of muscle contraction only 2 Active movement with gravity eliminated 3 Active movement against gravity 4 Active movement against gravity and resistance 5 Normal strength Outcome Evaluation The frequency of symptomatic intracranial hemorrhage (sICH) was assessed for individual cases, defined as any hemorrhage related to transient neurological worsening, manifested by an increase in the NIHSS score ≥ 4 points [ 7 ]. The mRS score at 90 days after EVT was used to evaluate patients’ functional outcomes [ 8 ]. The mRS was followed-up routinely by professional stroke nurses and neurologists by telephone calls or by in-person consultations during the 90-day follow-up period. Favorable outcome was defined as mRS score of 0–2 at 90 days. Poor outcome was defined as mRS score of 3–5 at 90 days. Death corresponded to mRS score of 6. Statistical Analysis Normally distributed data were summarized in means ± standard deviations (SD); proportions were expressed in percentages. Non-normally distributed continuous variables were reported as medians along with the interquartile range (IQR). The independent t-test was used to compare means between groups. The chi-square (χ2) test and Fisher exact test were used to compare proportions between groups. The non-parametric Mann-Whitney U test was used to contrasts medians between groups. Variables showing statistically significance ( P value < than 0.05) in the bivariate analysis were included in a multivariate logistic regression model using a Wald backwards method to assess the effect of independent variables on the dichotomized dependent variable: MS by MRC: <4 vs. ≥4. Variables with P value ≥ 0.10 were eliminated from the final regression model. Independent variables that would covariate between them were excluded from the final regression model. Exponential B (Exp B ) with 95% confidence intervals (CI) were calculated to estimate the weight of independent variables. Goodness of fit in the regression model was evaluated with the Hosmer-Lemeshow test, p value < 0.05 was considered poor fit. Determination coefficient (R 2 ) was calculated for the final model. We calculated the area under the curve (AUC) of receiver operating characteristic (ROC) along with standard errors (SE) in order to estimate the accuracy of upper and lower limb muscle strength to predict the functional outcomes. The statistical evaluations were performed using IBM SPSS version 26 (IBM-Armonk, NY), a P -value less than 0.05 was considered statistically significant. Results We enrolled 264 patients who met the inclusion criteria; however, 16 patients were eventually excluded from the final analysis (4 patients had incomplete data as they were missed at follow-up and 12 patients died during hospitalization). A total 248 patients were included in the final analysis of this study. There were 173 males (69.75%) and 75 females (30.24%). A total of 139 patients had a MS lower than 4 according to the MRC scale and 109 had a MS≥ 4 in the affected side. Patients had a mean ( ±SD ) hospital stay of 15.74 ± 13.04 days. In the bivariate analysis ( Table 1 ), patients with low MS (MRC< 4) at discharge were older ( p = 0.007), had a higher frequency of coronary artery disease (CAD) ( p = 0.022), higher NIHSS pretreatment score ( p < 0.001), lower ASPECTS ( p = 0.017), longer DNT for IV thrombolysis ( p = 0.001), longer DRT for EVT ( p = 0.02) and lower frequency of mTICI post-EVT ≥2b ( p = 0.003). Table 1. Comparison of discharge lower limb MS in the most paretic side ＜ 4 and Lower Limb MS ≥ 4 MRC < 4 MRC ≥ 4 x 2 /t/U p value Number 139 109 Age mean ± SD 65.89 ± 12.96 61.28 ± 13.83 2.703 0.007 Female, n, % 42（30.22） 33（30.28） 0.000 0.992 Hypertension, n, % 83（59.71） 58（53.21） 1.053 0.305 Diabetes, n, % 36（25.90） 18（16.51） 3.159 0.075 CAD, n, % 29（22.86） 11（10.09） 5.240 0.022 Prior Stroke, n, % 29（20.86） 19（17.43） 0.461 0.497 CKD, n, % 11（7.91） 8（7.34） 0.028 0.866 Smoker, n, % 26（18.71） 26（23.85） 0.977 0.323 AF, n, % 52 (37.41) 37 (33.94) -0.319 0.572 NIHSS Pre-treatment (IQR) 16.00 (14.00, 21.00) 14.00 (10.00, 18.00) -4.329 0.000 ASPECTS pre-treatment (IQR) 8.00 (8.00,9.00) 9.00 (8.00, 9.00) -2.394 0.017 mRS pre-treatment (IQR) 0.00 (0.00, 0.00) 0.00 (0.00, 0.00) -2.268 0.023 IV thrombolysis, n, % 54（38.85） 45（41.28） 0.151 0.697 DNT (IQR) 52.50 (38.00, 64.50) 38.00 (28.00, 48.00) -3.441 0.001 ONT (IQR) 146.00 (120.00, 204.00) 135.00 (104.00, 192.50) -0.911 0.362 Occlusion sites Distal/terminal ICA n, % 30（21.58） 14（12.84） 12.286 0.028 MCA-M1 n, % 44（31.65） 58（53.21） MCA-M2 n, % 8（5.76） 6（5.50） Tandem n, % 25（17.99） 15（13.76） Basilar n, % 27（19.42） 14（12.84） Others n, % 5（3.60） 2（1.83） DPT (IQR), min 151.0 (120.00, 200.00) 138.00 (107.00, 2005.00) -1.189 0.235 DRT (IQR), min 246.00 (189.00, 308.00) 220.00 (156.00, 273.00) -2.319 0.02 LKNPT (M±SD), min 381.82 ± 232.00 373.06 ± 253.93 0.283 0.777 mTICI post ≥2b, n, % 110（79.14） 101（92.66） 8.803 0.003 sICH, n, % 21（15.11) 0（0.00) 17.991 < 0.001 Abbreviations: AF, atrial fibrillation; CAD, coronary artery disease; CKD, chronic kidney disease; DM, diabetes mellitus; DNT, door-to-needle time; DPT, door-to-puncture time; DRT, door-to-recanalization time; LKNPT, last-known normal-to-puncture time; mTICI, modified thrombolysis in cerebral infarction; NIHSS, National Institute of Health Stroke Scale/Score; ONT, onset-to-needle time. The multivariate regression model showed that age, pretreatment NIHSS, ASPECTS, DRT were still significant in the final model, whereas the presence of coronary artery disease (CAD) and sICH were excluded from the final statistical model as they did not reach significance (Table 2). Variables such as DNT, mRS with pretreatment and occlusion sites were not included in the regression model as they covariate with DRN, pretreatment NIHSS and ASPECTS, respectively. Table 2. Multivariate analysis of statistically significant variables in the bivariate analysis. Variables in the final equation B Exp B coefficient Exp B 95% C.I. p value Age -0.030 0.971 0.948-0.994 0.014 NIHSS pre-treatment -0.106 0.900 0.856-0.946 0.000 ASPECTS score 0.336 1.399 0.997-1.962 0.052 DRT -0.004 0.996 0.992-0.999 0.016 mTICI post-EVT≥ 2b 1.110 3.035 1.151-8.003 0.025 Constant: B=0.808, Exp B : 2.224, P =0.644. Hosmer-Lemeshow: ( P =0.501). Variables excluded in the final model: sICH ( P =0.998) and CAD ( P =0.232). Cox and Snell R 2 =0.265. Study outcomes The proportion of patients with a poor functional outcome at 90 days was much higher in patients with MRC < 4 in the lower limb ( p < 0.001); whereas mortality was much higher in patients with MRC < 4 at discharge ( Table 3 ). Table 3. Comparison of outcome of discharge lower limb muscle strength ＜ 4 and discharge lower limb muscle strength ≥4 MRC＜ 4 n = 139 MRC≥ 4 n = 109 X 2 /t/U p value Poor outcome at 90 days, n, % 127（91.37） 15（13.76） 150.343 < 0.001 Mortality at 90 days, n, % 58（41.73） 5（4.59） 44.468 < 0.001 Poor outcome: mRS ≥ 3 at 3 months. sICH: symptomatic Intracranial Hemorrhage The distribution of outcomes (mRS) along the MRC scale is displayed in Figure 1 and Table 4 . Table 4. Relationship between functional outcomes 90 days after EVT and lower limb muscle strength at discharge MRC= 0 MRC= 1 MRC= 2 MRC= 3 MRC= 4 MRC= 5 p value mRS= 0, n, % 0 (0.00) 0 (0.00) 0 (0.00) 1（3.70） 3（8.82） 31（41.33） < 0.001 mRS= 1, n, % 1（1.72） 0 (0.00) 0 (0.00) 3（11.11） 10（29.41） 28（37.33） mRS= 2, n, % 1（1.72） 0 (0.00) 1（4.76） 5（18.52） 12（35.29） 10（13.33） mRS= 3, n, % 2（3.45） 2（6.06） 2（9.52） 3（11.11） 3（8.82） 2（2.67） mRS= 4, n, % 8（13.79） 16（48.48） 9（42.86） 8（29.63） 2（5.88） 1（1.33） mRS= 5, n, % 5（8.62） 7（21.21） 5（23.81） 2（7.41） 1（2.94） 1（1.33） mRS= 6, n, % 41（70.69） 8（24.24） 4（19.05） 5（18.52） 3（8.82） 2（2.67） Poor outcome (mRS 3-6), n, % 56（96.55） 33（100.00） 20（95.24） 18（66.67） 9（26.47） 6（8.00） < 0.001 Figure 1. Relationship between lower limb muscle strength at discharge and mRS score at 90 days. Patients with decreased MS at discharge (MRC <4) had a 77.6% higher probability to have a poor functional outcome at 3 months compared with patients with MRC ≥4: 91.37% vs. 13.76%, respectively. Patients with very poor MS consistent with MRC scale of 0 at discharge had a very high frequency of poor outcome (mRS ≥3) and much higher mortality rate (70%), compared with patients having higher MRC scores figures 1 and 2 . Figure 2. Percentage of patients with favorable outcome (mRS: 0-2), poor outcome (mRS: 3-6) and mortality at 90 days, according to lower limb strength at discharge. Accuracy of study variable When assessing outcomes accuracy, lower limb strength at discharge showed the highest predictive value for unfavorable outcome: AUC of ROC: 0.924 ± 0.019 ( p <0.001), followed by the upper limb strength: AUC of ROC: 0.874 ± 0.024 ( p <0.001). The NIHSS score 24 hours after EVT also showed an optimal predictive value for unfavorable outcome: AUC of ROC: 0.873 ± 0.023 ( p <0.001), figure 3 . Figure 3: Predictive ROC curves for A) lower limb muscle strength at discharge (AUC: 0.924); B) upper limb muscle strength at discharge (AUC: 0.874); C) NIHSS score 24 hours after EVT to predict unfavorable outcomes (AUC: 0.873). Discussion Our study shows that MS measured by a widely used and universally accepted clinical scale (MRC) has a high accuracy to predict the functional outcome, determined by the mRS at 90 days in patients who underwent arterial revascularization with EVT. In our study, lower limb strength showed a slightly higher prediction accuracy for functional outcome compared with upper limb strength, but both had similar high diagnostic yields; these clinical outcomes provided a similar diagnostic accuracy to predict the mRS compared with the NIHSS score 24 hours after EVT ( Figure 3 ). The NIHSS score on 24 hours after EVT relates to the compromised ischemic brain parenchyma during the hyper-acute period, which includes the area of reversible brain ischemia (i.e., penumbra zone); whereas the MS at discharge should reflect the established irreversible ischemic damage following the event. This motor deficit may be influenced by a higher percentage of sICH in patients with poor (MRC< 4) compared with good MS (MRC≥ 4) at discharge: 15.1% vs 0% in our study . However, sICH was not statistically significant after controlling for other variables in the regression model, suggesting that this event does not have a major influencefor independently predicting the outcome.It is important to note that the assessment of MS by MRC scale is easier, less time-consuming and requires less training compared to NIHSS assessment. Therefore, in terms of practicality, assessment of MS at discharge in post-EVT patients seems a better option than more complex clinical evaluations to predict functional outcome. When the data was retrospectively evaluated according to the MS at discharge, patients in the group of poor muscle strength (MRC< 4) were older, had higher NIHSS pre-treatment scores, and lower ASPECTS score, indicating a higher severity and greater infarct core volume on admission to the emergency room. Moreover, they also had a higher frequency of CAD suggesting more frequent and severe atherosclerosis, although this variable was excluded in the final regression model ( Table 1 ). Patients with poor MS at discharge (MRC< 4) had longer DRT compared with patients achieving good MS (MRC≥ 4): 246 vs. 220 minutes, respectively ( p < 0.001). This time delay may lead to a greater compromise in neural tissue resulting in greater volume of irreversible tissue damage and more severe neurological deficit. Regaining MS in the lower limbs may play an important role in gait in patients with brain ischemic damage. Gait is a major consideration when classifying patients according to the mRS, besides capacity for performing daily activities and need for assistance [8]. Recovering from walking disability has been associated with the degree of damage to corticospinal tracts assessed by diffusion tensor imaging using fractional anisotropy [9]. The ipsilateral corticospinal tracts, cortico-reticulospinal tract and contralateral superior cerebellar peduncle pathways seem to play a major role in functional recovery in walking scores in patients who have suffered an ischemic stroke [9]. Muscle strength in the paretic leg has been related to deficits in forward propulsion, power generation during gait and swing initiation with impairment in short-distance walking capability in patients who suffered an ischemic stroke [10, 11]. Additionally, muscle tone and strength of the lower limbs along with coordination abilities are related with walking speed-reserve in such patients [12]. Both, gait speed and walking distance have shown to be predictors of rehabilitation and reintegration back to community in patients who recover from stroke [13]. In this regard, the 6-minute walk test has shown to provide the best clinical discrimination for future home vs. community discharge following stroke [14]. Walking speed has been identified as the strongest predictor for return to work after stroke with a threshold of 0.93 m/s [15]. These considerations are crucial, as a strong correlation between the degree of walking disability and MS (-0.70, 95%CI= -0.42 to -086) was determined in a recent meta-analysis [16]. These data highlight the importance of muscle strength in the future impact of walking abilities and functional independence, which significantly influence the functional status 3 months after the cerebral ischemic event [17]. In our study, there was a striking relationship between MS at discharge and mortality. Patients with a MS at discharge of 0 (plegia or complete paralysis) had a 70.7% mortality, whereas patients with a MS between 1 and 3 had a mortality rate between 24.2 and 18.5% ( Figures 1 and 2 ). This suggests that MS may be a mortality predictor in AIS patients following EVT. Another study enrolling 764 patients with large vessel occlusion reported a mortality rate of 26% at 3 months [18]. Older age, higher NIHSS score at presentation and greater mRS at discharge were predictors of mortality [18]. As MS and mRS are indicators of irreversible ischemic damage in brain parenchyma, they may depend on the degree of arterial revascularization. Indeed, successful revascularization has been reported to have paramount influence on functional outcome and mortality in AIS patients undergoing EVT [18, 19]. Our study has some limitations. One is the lack of blinded evaluations at discharge; however, evaluators were not aware of the study hypothesis, making unlikely to have affected any of the evaluations. We did not compare the post-stroke NIHSS score and MS that would permit to compare directly the predictability of both variables. Another limitation is that we were able to assess the ischemic penumbra in a small proportion of cases (n=10); therefore, we were not able to include this variable in the logistic regression.Although our study included two large comprehensive stroke centers, further large-scale, multi-center investigations with larger sample size will be required to verify these findings. Despite these limitations, we believe our study can prompt other centers to consider MS at discharge as a predictor for functional outcome in AIS patients treated with EVT. Conclusion Patients with decreased MS on the affected side had a poorer functional outcome at 90 days compared with patients with normal or mildly abnormal MS at discharge who suffered an acute ischemic stroke and underwent revascularization by EVT. Muscle strength seems a reliable, easy to assess and reproducible clinical method to predict the functional outcome in such patients. Abbreviations AIS Acute ischemic stroke AUC Area under the curve ASPECTS Alberta stroke program early CT score CAD Coronary artery disease CI Confidence intervals DNT Door-to-needle time DPT Door-to-puncture time DRT Door-to-recanalization time EVT Endovascular thrombectomy IQR Interquartile range IV Intravenous LKNPT Last known normal-to-puncture-time MRC Medical Research Council MS Muscle strength mRS Modified ranking score mTICI Modified thrombolysis in cerebral infarction NIHSS National Institutes of Health stroke scale ONT Onset-to-needle time ROC Receiver operating characteristic rt-PA Recombinant tissue-type plasminogen activator SE Standard errors sICH Symptomatic intracranial hemorrhage Declarations Ethics approval The study was approved by the review board of the First People's Hospital of Foshan City, Guangdong Province, China. Written informed consent from the participants’ legal guardian/next of kin to perform the EVT. All participants’ information were unidentifiable. The study was conducted in accordance with the 1964 Helsinki Declaration or comparable standards. Conflict of interest The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding The study was supported by Foshan Competitive Talent Support Project Fund (Brain-Heart Talent Project-Build the Brain-Heart Comorbidity Muti-disciplinary Medical Center), China. Author Contribution sijie Zhou and zhikai Chen wrote the main manuscript text and all authors reviewed the manuscript. Acknowledgement We would like to thank all colleagues for data collection and patients for their contribution. Data Availability Data and materials are available by contacting corresponding authors on reasonable request. References -Adamson, J., Beswick, A. & Ebrahim, S. Is stroke the most common cause of disability? J. Stroke Cerebrovasc. Dis. 13 , 171–177. 10.1016/j.jstrokecerebrovasdis.2004.06.003 (2004). 2007/10/02. -Goyal, M. et al. 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Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIie3PMWrDMBTGcQmBvDyaVcElucIXBCGDSa9iYVAXDzmCg6CTDxBoDpEjOBX11ANkCCQl0KlDxgyG1gcItrt10H940/sNH2Oh0H9McccYEhpFa3e+IlkOJXYyLn0926xsNoAw0V6vcbBpTNc3XvSJ6atzuK2EKaocOkElWOTfd12Eb/fOlJBmXXzgkuP4wMjaQxcRyriKQMbxEjrHl2CK5p1EtmTfQJkXQYgX8LzoI9SSjABNUqYxG0JUS/Qj0okiUc9K2Ez2bZluni/j7+aHnk6f7nxrkuUo8nUnubPub++hUCgUutcvVD1I1d0IsBMAAAAASUVORK5CYII=","orcid":"","institution":"Guangdong Medical University","correspondingAuthor":true,"prefix":"","firstName":"Zhikai","middleName":"","lastName":"Chen","suffix":""},{"id":359226230,"identity":"20996c7c-3e45-47d4-9afa-2a63b16c0372","order_by":2,"name":"Jinyan Tang","email":"","orcid":"","institution":"The First Clinical Medical College of Guangdong Medical University, Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jinyan","middleName":"","lastName":"Tang","suffix":""},{"id":359226231,"identity":"3dc345d4-5286-482d-b707-4809eed2e203","order_by":3,"name":"Gan Chen","email":"","orcid":"","institution":"The Sixth People's Hospital of Nanhai District","correspondingAuthor":false,"prefix":"","firstName":"Gan","middleName":"","lastName":"Chen","suffix":""},{"id":359226232,"identity":"6e7f25a5-2a34-4349-bb41-3a9efdb528e9","order_by":4,"name":"Ziqi Ouyang","email":"","orcid":"","institution":"Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ziqi","middleName":"","lastName":"Ouyang","suffix":""},{"id":359226233,"identity":"27180371-396b-4aca-81da-13f1bb10c3bf","order_by":5,"name":"Jian Wang","email":"","orcid":"","institution":"Foshan Sanshui District People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Wang","suffix":""},{"id":359226234,"identity":"e6c8e330-a545-414c-a06c-da351aaf1204","order_by":6,"name":"Senrong Luo","email":"","orcid":"","institution":"Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Senrong","middleName":"","lastName":"Luo","suffix":""},{"id":359226235,"identity":"7d7e5924-fd7b-4117-9b68-3f9e31008607","order_by":7,"name":"Minyi Su","email":"","orcid":"","institution":"Foshan Sanshui District People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Minyi","middleName":"","lastName":"Su","suffix":""},{"id":359226236,"identity":"0d278560-1247-4fe4-801e-2b3a17d71847","order_by":8,"name":"Jianhui Huang","email":"","orcid":"","institution":"First People's Hospital of Foshan","correspondingAuthor":false,"prefix":"","firstName":"Jianhui","middleName":"","lastName":"Huang","suffix":""},{"id":359226237,"identity":"e8976620-e062-4871-b852-1ba6459a7eea","order_by":9,"name":"Adam A Dmytriw","email":"","orcid":"","institution":"Harvard Medical School","correspondingAuthor":false,"prefix":"","firstName":"Adam","middleName":"A","lastName":"Dmytriw","suffix":""},{"id":359226238,"identity":"dad0146e-7cb2-4afb-9404-5dbc1f3c4df1","order_by":10,"name":"José Fidel Baizabal Carvallo","email":"","orcid":"","institution":"Baylor College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"Fidel Baizabal","lastName":"Carvallo","suffix":""},{"id":359226239,"identity":"dfccb715-fd7c-4135-beb2-d35475e2df51","order_by":11,"name":"Xuxing Liao","email":"","orcid":"","institution":"First People's Hospital of Foshan","correspondingAuthor":false,"prefix":"","firstName":"Xuxing","middleName":"","lastName":"Liao","suffix":""}],"badges":[],"createdAt":"2024-08-11 02:23:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4893440/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4893440/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66948976,"identity":"cb9616e4-6832-4f2f-93cb-66411114d3c7","added_by":"auto","created_at":"2024-10-18 09:59:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":31693,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between lower limb muscle strength at discharge and mRS score at 90 days.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4893440/v1/3052f11f6330b2154b0fed6d.png"},{"id":66947092,"identity":"6b4a09cd-a662-43fa-b413-2f4660ca36f1","added_by":"auto","created_at":"2024-10-18 09:51:10","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":251826,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of patients with favorable outcome (mRS: 0-2), poor outcome (mRS: 3-6) and mortality at 90 days, according to lower limb strength at discharge.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4893440/v1/41b17384c794050a8ae983df.jpeg"},{"id":66947091,"identity":"e850a191-0f4b-4244-97a9-dbc3a9223ec2","added_by":"auto","created_at":"2024-10-18 09:51:10","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":32234,"visible":true,"origin":"","legend":"\u003cp\u003ePredictive ROC curves for A) lower limb muscle strength at discharge (AUC: 0.924); B) upper limb muscle strength at discharge (AUC: 0.874); C) NIHSS score 24 hours after EVT to predict unfavorable outcomes (AUC: 0.873).\u003c/p\u003e","description":"","filename":"groupimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4893440/v1/b579aa32ec6d63ffc6cfb0dd.jpeg"},{"id":69807839,"identity":"14b68309-7cc4-4ad7-9570-301c3f703002","added_by":"auto","created_at":"2024-11-25 12:09:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1022277,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4893440/v1/f1c50cc0-2999-4ecd-8fc9-61b14ce06698.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Muscle Strength at Discharge as Predictor of Functional Outcome in Ischemic Stroke Patients Following Endovascular Therapy: Observational Study in Two Comprehensive Stroke Centers","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute ischemic stroke (AIS) following large vessel occlusion is one of the most devastating neurological emergencies associated with high mortality and disability [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Reperfusion therapies have revolutionized the treatment of acute ischemic stroke in the last 30 years. Before 2014, intravenous (IV) recombinant tissue-type plasminogen activator (rt-PA \u0026ndash;alteplase-) was the mainstay therapy in AIS patients. However, since publication of multiple endovascular thrombectomy (EVT) trials in 2015; EVT has become the standard of care for arterial recanalization in large vessel occlusion patients, as this therapy improved functional outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These trials used new-generation stent-retriever devices, which showed a clear superiority for EVT compared with previous generation devices or standard medical care alone [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e Currently, EVT is recommended in major practice guidelines from Europe and North America for patients with proximal middle cerebral artery or internal carotid artery occlusions who have received treatment with IV rt-PA within 4.5 hours of onset, who can undergo the procedure within 6 hours of symptom onset. Further studies have shown that mechanical thrombectomy could improve outcomes in selected AIS patients with large vessel occlusions up-to 24-hour from symptom onset [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePatients achieving maximal clinical benefit with EVT are those with a greater probability for early recanalization limiting irreversible ischemic damage [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. A proxy for such hemodynamic outcome would be regaining function in the affected cortical area, for example recovering muscle strength (MS). We hypothesized that AIS patients undergoing EVT who showed an early recovery in MS will have a better outcome at 90 days according to the modified Ranking Scale (mRS). We also aimed to assess which variables were predictors for early recovery of MS in these patients. We conducted a study aimed to assess the functional outcome in AIS patients undergoing EVT.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003e We retrospectively analyzed prospectively collected data of 264 consecutive AIS patients treated with EVT from 2018 to 2022 in two comprehensive tertiary care stroke centers in China, the Foshan Sanshui District People\u0026rsquo;s Hospital and the First People's Hospital of Foshan. Patients with AIS and large vessel occlusion on neuroimaging or by clinical presentation were triaged for EVT. Thrombus aspiration or a combined approach using a stent retriever plus aspiration was used in most cases. The approach varied according to the thrombus location and individual vascular anatomy. Patients received standard care with IV rt-PA, if they presented within the 4.5-hour time-window and no contraindications for this therapy were present.\u003c/p\u003e \u003cp\u003eThe data was derived from the Bigdata observatory platform for stroke in China (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ss.chinasdc.cn\u003c/span\u003e\u003cspan address=\"https://ss.chinasdc.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the individual hospitals\u0026rsquo; data platforms. Inclusion criteria were the following: 1) patients aged 18 years-old or older, 2) patients with AIS who underwent EVT within 24 hours of symptom onset, and 3) pre-morbid mRS\u0026thinsp;\u0026le;\u0026thinsp;2. Exclusion criteria were the following: 1) patients with missing follow-up, and 2) death during hospitalization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eThe followed clinical data were collected for each patient: age, sex, risk factors for cerebrovascular disease and history of prior stroke. The pre-treatment National Institutes of Health Stroke Scale (NIHSS) and mRS scores were determined. We used the pre-treatment Alberta Stroke Program Early CT Score (ASPECTS) method in order to assess the infarct core volume. The sites of arterial occlusion were also registered.\u003c/p\u003e \u003cp\u003eIn order to assess the speed and quality of recanalization, we used the onset-to-needle time (ONT), door-to-needle time (DNT) for IV rt-PA and door-to-puncture time (DPT), door-to-recanalization time (DRT) and last known normal-to-puncture-time (LKNPT) for EVT. The modified thrombolysis in cerebral infarction (mTICI) score was used to evaluate the degree of arterial reperfusion (0/1: No or minimal reperfusion; 2a: partial filling\u0026thinsp;\u0026lt;\u0026thinsp;50%; 2b: partial filling\u0026thinsp;\u0026gt;\u0026thinsp;50%; 3: complete perfusion) after thrombectomy; an mTICI post-EVT scores of 2b or 3 were considered as successful recanalization [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe MS in the more severely affected side was registered for each patient and determined according to the Medical Research Council (MRC) scale [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] (Panel). In order to use a simple quantitative metric, the MS of knee-joint extension and elbow joint bicep were recorded and analyzed in this study.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePanel.\u003c/b\u003e Medical Research Council (MRC) scale for muscle strength/weakness grading\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo contraction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrace of muscle contraction only\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActive movement with gravity eliminated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActive movement against gravity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActive movement against gravity and resistance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal strength\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eOutcome Evaluation\u003c/h2\u003e \u003cp\u003eThe frequency of symptomatic intracranial hemorrhage (sICH) was assessed for individual cases, defined as any hemorrhage related to transient neurological worsening, manifested by an increase in the NIHSS score\u0026thinsp;\u0026ge;\u0026thinsp;4 points [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The mRS score at 90 days after EVT was used to evaluate patients\u0026rsquo; functional outcomes [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The mRS was followed-up routinely by professional stroke nurses and neurologists by telephone calls or by in-person consultations during the 90-day follow-up period. Favorable outcome was defined as mRS score of 0\u0026ndash;2 at 90 days. Poor outcome was defined as mRS score of 3\u0026ndash;5 at 90 days. Death corresponded to mRS score of 6.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eNormally distributed data were summarized in means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations (SD); proportions were expressed in percentages. Non-normally distributed continuous variables were reported as medians along with the interquartile range (IQR). The independent t-test was used to compare means between groups. The chi-square (χ2) test and Fisher exact test were used to compare proportions between groups. The non-parametric Mann-Whitney U test was used to contrasts medians between groups. Variables showing statistically significance (\u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;than 0.05) in the bivariate analysis were included in a multivariate logistic regression model using a Wald backwards method to assess the effect of independent variables on the dichotomized dependent variable: MS by MRC: \u0026lt;4 vs. \u0026ge;4. Variables with \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026ge;\u0026thinsp;0.10 were eliminated from the final regression model. Independent variables that would covariate between them were excluded from the final regression model. Exponential B (Exp\u003csup\u003eB\u003c/sup\u003e) with 95% confidence intervals (CI) were calculated to estimate the weight of independent variables. Goodness of fit in the regression model was evaluated with the Hosmer-Lemeshow test, \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered poor fit. Determination coefficient (R\u003csup\u003e2\u003c/sup\u003e) was calculated for the final model. We calculated the area under the curve (AUC) of receiver operating characteristic (ROC) along with standard errors (SE) in order to estimate the accuracy of upper and lower limb muscle strength to predict the functional outcomes. The statistical evaluations were performed using IBM SPSS version 26 (IBM-Armonk, NY), a \u003cem\u003eP\u003c/em\u003e-value less than 0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe enrolled 264 patients who met the inclusion criteria; however, 16 patients were eventually excluded from the final analysis (4 patients had incomplete data as they were missed at follow-up and 12 patients died during hospitalization).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA total 248 patients were included in the final analysis of this study. There were 173 males (69.75%) and 75 females (30.24%). A total of 139 patients had a MS lower than 4 according to the MRC scale and 109 had a MS\u0026ge; 4 in the affected side. Patients had a mean \u003cstrong\u003e(\u003c/strong\u003e\u0026plusmn;SD\u003cstrong\u003e)\u003c/strong\u003e hospital stay of 15.74 \u0026plusmn; 13.04 days. In the bivariate analysis (\u003cstrong\u003eTable 1\u003c/strong\u003e), patients with low MS (MRC\u0026lt; 4) at discharge were older (\u003cem\u003ep\u003c/em\u003e= 0.007), had a higher frequency of coronary artery disease (CAD) (\u003cem\u003ep\u003c/em\u003e= 0.022), higher NIHSS pretreatment score (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001), lower ASPECTS (\u003cem\u003ep\u003c/em\u003e= 0.017), longer DNT for IV thrombolysis (\u003cem\u003ep\u003c/em\u003e= 0.001), longer DRT for EVT (\u003cem\u003ep\u003c/em\u003e= 0.02) and lower frequency of mTICI post-EVT \u0026ge;2b (\u003cem\u003ep\u003c/em\u003e= 0.003).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Comparison of discharge lower limb MS in the most paretic side\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e4 and Lower Limb MS\u003c/strong\u003e\u003cstrong\u003e\u0026ge;\u003c/strong\u003e\u003cstrong\u003e4\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eMRC \u0026lt; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eMRC \u0026ge; 4\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003ex\u003csup\u003e2\u003c/sup\u003e/t/U\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eNumber\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eAge mean \u0026plusmn; SD \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e65.89\u0026nbsp;\u0026plusmn; 12.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e61.28\u0026nbsp;\u0026plusmn; 13.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eFemale, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e42（30.22）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e33（30.28）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eHypertension, n, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e83（59.71）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e58（53.21）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eDiabetes, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e36（25.90）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e18（16.51）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eCAD, n, % \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e29（22.86）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e11（10.09）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003ePrior Stroke, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e29（20.86）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e19（17.43）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eCKD, n, % \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e11（7.91）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8（7.34）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eSmoker, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e26（18.71）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e26（23.85）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.323\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eAF, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e52 (37.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e37 (33.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.572\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eNIHSS Pre-treatment (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e16.00 (14.00, 21.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e14.00 (10.00, 18.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-4.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eASPECTS pre-treatment (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.00 (8.00,9.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e9.00 (8.00, 9.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-2.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003emRS pre-treatment (IQR) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.00 (0.00, 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.00 (0.00, 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-2.268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eIV thrombolysis, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e54（38.85）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e45（41.28）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eDNT (IQR)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e52.50 (38.00, 64.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e38.00 (28.00, 48.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-3.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eONT (IQR)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e146.00 (120.00, 204.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e135.00 (104.00, 192.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOcclusion sites\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eDistal/terminal ICA n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e30（21.58）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e14（12.84）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" style=\"width: 85px;\"\u003e\n \u003cp\u003e12.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;MCA-M1 n, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e44（31.65）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e58（53.21）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;MCA-M2 n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8（5.76）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e6（5.50）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eTandem n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e25（17.99）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e15（13.76）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eBasilar n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e27（19.42）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e14（12.84）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eOthers n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e5（3.60）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2（1.83）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eDPT (IQR), min\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e151.0 (120.00, 200.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e138.00 (107.00, 2005.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-1.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eDRT (IQR), min\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e246.00 (189.00, 308.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e220.00 (156.00, 273.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-2.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eLKNPT (M\u0026plusmn;SD), min\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e381.82\u0026nbsp;\u0026plusmn; 232.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e373.06\u0026nbsp;\u0026plusmn; 253.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003emTICI post \u0026ge;2b, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e110（79.14）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e101（92.66）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e8.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003esICH, n, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e21（15.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0（0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e17.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: AF, atrial fibrillation; CAD, coronary artery disease; CKD, chronic kidney disease; DM, diabetes mellitus; DNT, door-to-needle time; DPT, door-to-puncture time; DRT, door-to-recanalization time; LKNPT, last-known normal-to-puncture time; mTICI, modified thrombolysis in cerebral infarction; NIHSS, National Institute of Health Stroke Scale/Score; ONT, onset-to-needle time.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe multivariate regression model showed that age, pretreatment NIHSS, ASPECTS, DRT were still significant in the final model, whereas the presence of coronary artery disease (CAD) and sICH were excluded from the final statistical model as they did not reach significance (Table 2). Variables such as DNT, mRS with pretreatment and occlusion sites were not included in the regression model as they covariate with DRN, pretreatment NIHSS and ASPECTS, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Multivariate analysis of statistically significant variables in the bivariate analysis.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"622\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.723%;\"\u003e\n \u003cp\u003eVariables in the final equation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.1369%;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003eExp\u003csup\u003eB\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ecoefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003eExp\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e95% C.I.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2979%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1.44928%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.723%;\"\u003e\n \u003cp\u003eAge \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.1369%;\"\u003e\n \u003cp\u003e-0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003e0.971\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003e0.948-0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 16.7472%;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.723%;\"\u003e\n \u003cp\u003eNIHSS pre-treatment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.1369%;\"\u003e\n \u003cp\u003e-0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003e0.856-0.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 16.7472%;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.723%;\"\u003e\n \u003cp\u003eASPECTS score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.1369%;\"\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003e1.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003e0.997-1.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 16.7472%;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.723%;\"\u003e\n \u003cp\u003eDRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.1369%;\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003e0.992-0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 16.7472%;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.723%;\"\u003e\n \u003cp\u003emTICI post-EVT\u0026ge;\u0026nbsp;2b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.1369%;\"\u003e\n \u003cp\u003e1.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003e3.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1965%;\"\u003e\n \u003cp\u003e1.151-8.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 16.7472%;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eConstant: B=0.808, Exp\u003csup\u003eB\u003c/sup\u003e: 2.224, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e=0.644. Hosmer-Lemeshow: (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e=0.501). Variables excluded in the final model: sICH (\u003cem\u003eP\u003c/em\u003e =0.998) and CAD (\u003cem\u003eP\u003c/em\u003e =0.232). Cox and Snell R\u003csup\u003e2\u003c/sup\u003e=0.265. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe proportion of patients with a poor functional outcome at 90 days was much higher in patients with MRC \u0026lt; 4 in the lower limb (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001); whereas mortality was much higher in patients with MRC \u0026lt; 4 at discharge (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Comparison of outcome of discharge lower limb muscle strength\u003c/strong\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;4 and discharge lower limb muscle strength \u0026ge;4\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.5476%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.0557%;\"\u003e\n \u003cp\u003eMRC＜\u0026nbsp;4\u003c/p\u003e\n \u003cp\u003e\u003cem\u003en\u003c/em\u003e= 139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.8761%;\"\u003e\n \u003cp\u003eMRC\u0026ge;\u0026nbsp;4\u003c/p\u003e\n \u003cp\u003e\u003cem\u003en\u003c/em\u003e= 109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.2603%;\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e/t/U\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.2603%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.5476%;\"\u003e\n \u003cp\u003ePoor outcome at 90 days, n, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.0557%;\"\u003e\n \u003cp\u003e127（91.37）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.8761%;\"\u003e\n \u003cp\u003e15（13.76）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.2603%;\"\u003e\n \u003cp\u003e150.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.2603%;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.5476%;\"\u003e\n \u003cp\u003eMortality at 90 days, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.0557%;\"\u003e\n \u003cp\u003e58（41.73）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.8761%;\"\u003e\n \u003cp\u003e5（4.59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.2603%;\"\u003e\n \u003cp\u003e44.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.2603%;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePoor outcome: mRS \u0026ge; 3 at 3 months. sICH: symptomatic Intracranial Hemorrhage\u003c/p\u003e\n\u003cp\u003eThe distribution of outcomes (mRS) along the MRC scale is displayed in \u003cstrong\u003eFigure 1\u0026nbsp;\u003c/strong\u003eand\u003cstrong\u003e\u0026nbsp;Table 4\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. \u0026nbsp; Relationship between functional outcomes 90 days after EVT and lower limb muscle strength at discharge\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"647\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003eMRC= 0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eMRC= 1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003eMRC=\u0026nbsp;2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eMRC= 3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003eMRC=\u0026nbsp;4\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003eMRC=\u0026nbsp;5\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003emRS= 0, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1（3.70）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e3（8.82）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e31（41.33）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" style=\"width: 52px;\"\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\u0026lt; 0.001\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003emRS= 1, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1（1.72）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3（11.11）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e10（29.41）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e28（37.33）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003emRS= 2, n, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1（1.72）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1（4.76）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e5（18.52）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e12（35.29）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e10（13.33）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003emRS= 3, n, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e2（3.45）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2（6.06）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e2（9.52）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3（11.11）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e3（8.82）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e2（2.67）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003emRS= 4, n, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e8（13.79）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e16（48.48）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e9（42.86）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8（29.63）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e2（5.88）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1（1.33）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003emRS= 5, n, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e5（8.62）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e7（21.21）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e5（23.81）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2（7.41）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1（2.94）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1（1.33）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003emRS= 6, n, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\n \u003cp\u003e41（70.69）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8（24.24）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e4（19.05）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e5（18.52）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e3（8.82）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e2（2.67）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003ePoor outcome\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(mRS 3-6), n, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e56（96.55）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e33（100.00）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e20（95.24）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e18（66.67）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e9（26.47）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e6（8.00）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFigure 1.\u0026nbsp;\u003c/strong\u003eRelationship between lower limb muscle strength at discharge and mRS score at 90 days.\u003c/p\u003e\n\u003cp\u003ePatients with decreased MS at discharge (MRC \u0026lt;4) had a 77.6% higher probability to have a poor functional outcome at 3 months compared with patients with MRC \u0026ge;4: 91.37% vs. 13.76%, respectively. Patients with very poor MS consistent with MRC scale of 0 at discharge had a very high frequency of poor outcome (mRS \u0026ge;3) and much higher mortality rate (70%), compared with patients having higher MRC scores \u003cstrong\u003efigures 1 and 2\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 2.\u0026nbsp;\u003c/strong\u003ePercentage of patients with favorable outcome (mRS: 0-2), poor outcome (mRS: 3-6) and mortality at 90 days, according to lower limb strength at discharge.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAccuracy of study variable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhen assessing outcomes accuracy, lower limb strength at discharge showed the highest predictive value for unfavorable outcome: AUC of ROC: 0.924 \u0026plusmn; 0.019 (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt;0.001), followed by the upper limb strength: AUC of ROC: 0.874 \u0026plusmn; 0.024 (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt;0.001). The NIHSS score 24 hours after EVT also showed an optimal predictive value for unfavorable outcome: AUC of ROC: 0.873 \u0026plusmn; 0.023 (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt;0.001), \u003cstrong\u003efigure 3\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 3:\u0026nbsp;\u003c/strong\u003ePredictive ROC curves for A) lower limb muscle strength at discharge (AUC: 0.924); B) upper limb muscle strength at discharge (AUC: 0.874); C) NIHSS score 24 hours after EVT to predict unfavorable outcomes (AUC: 0.873).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study shows that MS measured by a widely used and universally accepted clinical scale (MRC) has a high accuracy to predict the functional outcome, determined by the mRS at 90 days in patients who underwent arterial revascularization with EVT. In our study, lower limb strength showed a slightly higher prediction accuracy for functional outcome compared with upper limb strength, but both had similar high diagnostic yields; these clinical outcomes provided a similar diagnostic accuracy to predict the mRS compared with the NIHSS score 24 hours after EVT (\u003cstrong\u003eFigure 3\u003c/strong\u003e). The NIHSS score on 24 hours after EVT relates to the compromised ischemic brain parenchyma during the hyper-acute period, which includes the area of reversible brain ischemia (i.e., penumbra zone); whereas the MS at discharge should reflect the established irreversible ischemic damage following the event. This motor deficit may be influenced by a higher percentage of sICH in patients with poor (MRC\u0026lt; 4) compared with good MS (MRC\u0026ge; 4) at discharge: 15.1% vs 0% in our study\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eHowever, sICH was not statistically significant after controlling for other variables in the regression model, suggesting that this event does not have a major influencefor independently predicting the outcome.It is important to note that the assessment of MS by MRC scale is easier, less time-consuming and requires less training compared to NIHSS assessment. Therefore, in terms of practicality, assessment of MS at discharge in post-EVT patients seems a better option than more complex clinical evaluations to predict functional outcome. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;When the data was retrospectively evaluated according to the MS at discharge, patients in the group of poor muscle strength (MRC\u0026lt; 4) were older, had higher NIHSS pre-treatment scores, and lower ASPECTS score, indicating a higher severity and greater infarct core volume on admission to the emergency room. Moreover, they also had a higher frequency of CAD suggesting more frequent and severe atherosclerosis, although this variable was excluded in the final regression model (\u003cstrong\u003eTable 1\u003c/strong\u003e). Patients with poor MS at discharge (MRC\u0026lt; 4) had longer DRT compared with patients achieving good MS (MRC\u0026ge; 4): 246 vs. 220 minutes, respectively (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001). This time delay may lead to a greater compromise in neural tissue resulting in greater volume of irreversible tissue damage and more severe neurological deficit.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegaining MS in the lower limbs may play an important role in gait in patients with brain ischemic damage. Gait is a major consideration when classifying patients according to the mRS, besides capacity for performing daily activities and need for assistance [8]. Recovering from walking disability has been associated with the degree of damage to corticospinal tracts assessed by diffusion tensor imaging using fractional anisotropy [9]. The ipsilateral corticospinal tracts, cortico-reticulospinal tract and contralateral superior cerebellar peduncle pathways seem to play a major role in functional recovery in walking scores in patients who have suffered an ischemic stroke [9]. Muscle strength in the paretic leg has been related to deficits in forward propulsion, power generation during gait and swing initiation with impairment in short-distance walking capability in patients who suffered an ischemic stroke [10, 11]. Additionally, muscle tone and strength of the lower limbs along with coordination abilities are related with walking speed-reserve in such patients [12]. Both, gait speed and walking distance have shown to be predictors of rehabilitation and reintegration back to community in patients who recover from stroke [13]. In this regard, the 6-minute walk test has shown to provide the best clinical discrimination for future home vs. community discharge following stroke [14]. Walking speed has been identified as the strongest predictor for return to work after stroke with a threshold of 0.93 m/s [15]. These considerations are crucial, as a strong correlation between the degree of walking disability and MS (-0.70, 95%CI= -0.42 to -086) was determined in a recent meta-analysis [16]. These data highlight the importance of muscle strength in the future impact of walking abilities and functional independence, which significantly influence the functional status 3 months after the cerebral ischemic event [17]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn our study, there was a striking relationship between MS at discharge and mortality. Patients with a MS at discharge of 0 (plegia or complete paralysis) had a 70.7% mortality, whereas patients with a MS between 1 and 3 had a mortality rate between 24.2 and 18.5% (\u003cstrong\u003eFigures 1 and 2\u003c/strong\u003e). This suggests that MS may be a mortality predictor in AIS patients following EVT. Another study enrolling 764 patients with large vessel occlusion reported a mortality rate of 26% at 3 months [18]. Older age, higher NIHSS score at presentation and greater mRS at discharge were predictors of mortality [18]. As MS and mRS are indicators of irreversible ischemic damage in brain parenchyma, they may depend on the degree of arterial revascularization. Indeed, successful revascularization has been reported to have paramount influence on functional outcome and mortality in AIS patients undergoing EVT [18, 19].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study has some limitations. One is the lack of blinded evaluations at discharge; however, evaluators were not aware of the study hypothesis, making unlikely to have affected any of the evaluations. We did not compare the post-stroke NIHSS score and MS that would permit to compare directly the predictability of both variables. Another limitation is that we were able to assess the ischemic penumbra in a small proportion of cases (n=10); therefore, we were not able to include this variable in the logistic regression.Although our study included two large comprehensive stroke centers, further large-scale, multi-center investigations with larger sample size will be required to verify these findings. Despite these limitations, we believe our study can prompt other centers to consider MS at discharge as a predictor for functional outcome in AIS patients treated with EVT.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePatients with decreased MS on the affected side had a poorer functional outcome at 90 days compared with patients with normal or mildly abnormal MS at discharge who suffered an acute ischemic stroke and underwent revascularization by EVT. Muscle strength seems a reliable, easy to assess and reproducible clinical method to predict the functional outcome in such patients. \u0026nbsp; \u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute ischemic stroke\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASPECTS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlberta stroke program early CT score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCoronary artery disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence intervals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDNT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDoor-to-needle time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDPT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDoor-to-puncture time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDoor-to-recanalization time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEVT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEndovascular thrombectomy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntravenous\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLKNPT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLast known normal-to-puncture-time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMedical Research Council\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMuscle strength\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003emRS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eModified ranking score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003emTICI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eModified thrombolysis in cerebral infarction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNIHSS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Institutes of Health stroke scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eONT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOnset-to-needle time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ert-PA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRecombinant tissue-type plasminogen activator\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard errors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003esICH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSymptomatic intracranial hemorrhage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval\u003c/strong\u003e \u003cp\u003e The study was approved by the review board of the First People's Hospital of Foshan City, Guangdong Province, China. Written informed consent from the participants\u0026rsquo; legal guardian/next of kin to perform the EVT. All participants\u0026rsquo; information were unidentifiable. The study was conducted in accordance with the 1964 Helsinki Declaration or comparable standards.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe study was supported by Foshan Competitive Talent Support Project Fund (Brain-Heart Talent Project-Build the Brain-Heart Comorbidity Muti-disciplinary Medical Center), China.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003esijie Zhou and zhikai Chen wrote the main manuscript text and all authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank all colleagues for data collection and patients for their contribution.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData and materials are available by contacting corresponding authors on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e-Adamson, J., Beswick, A. \u0026amp; Ebrahim, S. 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Endovascular Thrombectomy for Acute Ischemic Stroke: A Meta-analysis. \u003cem\u003eJama\u003c/em\u003e. \u003cb\u003e314\u003c/b\u003e, 1832\u0026ndash;1843. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2015.13767\u003c/span\u003e\u003cspan address=\"10.1001/jama.2015.13767\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015). 2015/11/04.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Scopelliti, G. et al. Outcome of a Real-World Cohort of Patients Subjected to Endovascular Treatment for Acute Ischemic Stroke. \u003cem\u003eJ. Stroke Cerebrovasc. Dis.\u003c/em\u003e \u003cb\u003e31\u003c/b\u003e, 106511. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jstrokecerebrovasdis.2022.106511\u003c/span\u003e\u003cspan address=\"10.1016/j.jstrokecerebrovasdis.2022.106511\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Dargazanli, C. et al. Modified Thrombolysis in Cerebral Infarction 2C/Thrombolysis in Cerebral Infarction 3 Reperfusion Should Be the Aim of Mechanical Thrombectomy: Insights From the ASTER Trial (Contact Aspiration Versus Stent Retriever for Successful Revascularization). \u003cem\u003eStroke\u003c/em\u003e. \u003cb\u003e49\u003c/b\u003e, 1189\u0026ndash;1196. 2018/04/08 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Paternostro-Sluga, T. et al. 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Evolution of the Modified Rankin Scale and Its Use in Future Stroke Trials. \u003cem\u003eStroke\u003c/em\u003e. \u003cb\u003e48\u003c/b\u003e, 2007\u0026ndash;2012. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/strokeaha.117.017866\u003c/span\u003e\u003cspan address=\"10.1161/strokeaha.117.017866\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017). 2017/06/20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Soulard, J. et al. Motor tract integrity predicts walking recovery: A diffusion MRI study in subacute stroke. \u003cem\u003eNeurology\u003c/em\u003e. \u003cb\u003e94\u003c/b\u003e, e583\u0026ndash;e593. 2020/01/04 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Hall, A. L. et al. Relationships between muscle contributions to walking subtasks and functional walking status in persons with post-stroke hemiparesis. \u003cem\u003eClin. Biomech. (Bristol Avon)\u003c/em\u003e. \u003cb\u003e26\u003c/b\u003e, 509\u0026ndash;515. 2011/01/22 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Patterson, S. L. et al. Determinants of walking function after stroke: differences by deficit severity. \u003cem\u003eArch. Phys. Med. Rehabil\u003c/em\u003e. \u003cb\u003e88\u003c/b\u003e, 115\u0026ndash;119. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.apmr.2006.10.025\u003c/span\u003e\u003cspan address=\"10.1016/j.apmr.2006.10.025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007). 2007/01/09.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Nascimento, L. R. et al. Deficits in motor coordination of the paretic lower limb limit the ability to immediately increase walking speed in individuals with chronic stroke. \u003cem\u003eBraz J. Phys. Ther.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e, 496\u0026ndash;502. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.bjpt.2019.09.001\u003c/span\u003e\u003cspan address=\"10.1016/j.bjpt.2019.09.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020). 2019/09/29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Bijleveld-Uitman, M., van de Port, I. \u0026amp; Kwakkel, G. Is gait speed or walking distance a better predictor for community walking after stroke? \u003cem\u003eJ Rehabil Med\u003c/em\u003e ; 45: 535\u0026ndash;540. 2013 (2013). \u003cdiv class=\"ExternalRefDOI\"\u003e/04/16\u003c/div\u003e. DOI: 10.2340/16501977-1147.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Fulk, G. D. et al. Predicting Home and Community Walking Activity Poststroke. \u003cem\u003eStroke\u003c/em\u003e. \u003cb\u003e48\u003c/b\u003e, 406\u0026ndash;411. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/strokeaha.116.015309\u003c/span\u003e\u003cspan address=\"10.1161/strokeaha.116.015309\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017). 2017/01/07.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Jarvis, H. L. et al. Return to Employment After Stroke in Young Adults: How Important Is the Speed and Energy Cost of Walking? \u003cem\u003eStroke\u003c/em\u003e. \u003cb\u003e50\u003c/b\u003e, 3198\u0026ndash;3204. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/strokeaha.119.025614\u003c/span\u003e\u003cspan address=\"10.1161/strokeaha.119.025614\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019). 2019/09/27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Dorsch, S. et al. The Relationship Between Strength of the Affected Leg and Walking Speed After Stroke Varies According to the Level of Walking Disability: A Systematic Review. \u003cem\u003ePhys. Ther.\u003c/em\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e1012021/10/13\u003c/span\u003e\u003cspan address=\"1012021/10/13\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Peniche, P. D. C. et al. The Distance Covered in Field Tests is more Explained by Walking Capacity than by Cardiorespiratory Fitness after Stroke. \u003cem\u003eJ. Stroke Cerebrovasc. Dis.\u003c/em\u003e \u003cb\u003e30\u003c/b\u003e, 105995. 2021/07/22 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Karamchandani, R. R. et al. Mortality after large artery occlusion acute ischemic stroke. \u003cem\u003eSci. Rep.\u003c/em\u003e ; 1 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e-Awad, A. W. et al. Predicting Death After Thrombectomy in the Treatment of Acute Stroke. \u003cem\u003eFront. Surg.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e, 16. 2020/04/24 (2020).\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"Endovascular therapy, Muscle strength, Patient outcome, Stroke, Thrombectomy","lastPublishedDoi":"10.21203/rs.3.rs-4893440/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4893440/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEndovascular thrombectomy (EVT) has emerged within the last few years as a safe and efficacious method to achieve arterial recanalization in patients with acute ischemic stroke (AIS). However, there are few clinical methods to predict functional outcome. We aimed to investigate whether the muscle strength (MS) at discharge assessed by the Medical Research Council (MRC) scale for muscle strength/weakness predicted functional outcome in patients with AIS undergoing EVT.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe enrolled 264 consecutive patients from two large comprehensive stroke centers in China from 2018 to 2022. A total of 248 patients were analyzed. We measured and analyzed muscle strength by means of the MRC scale at discharge. Patients were divided in two groups: normal to mildly abnormal muscle strength (MRC\u0026thinsp;\u0026ge;\u0026thinsp;4), and markedly decreased muscle strength (MRC\u0026thinsp;\u0026lt;\u0026thinsp;4). A poor outcome was defined as a modified Ranking Score (mRS) of 3\u0026ndash;6 at 90-days.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eLogistic regression showed that older age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014), higher pre-EVT NIHSS score (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), greater ASPECTS (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.052), longer door-to-recanalization time (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016) and post-EVT revascularization\u0026thinsp;\u0026ge;\u0026thinsp;2b (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025), were independently associated with MRC\u0026thinsp;\u0026lt;\u0026thinsp;4. Patients with poor muscle strength at discharge (MRC\u0026thinsp;\u0026lt;\u0026thinsp;4) had a significantly higher frequency of poor outcome at 90-days: 91.37% vs. 13.76% (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Both lower and upper limb strength in the most paretic side showed high accuracy in predicting the functional outcome at 90 days: area under the curve: 0.924 and 0.874, respectively. An MRC of 0 (plegia or complete paralysis), was associated with a 70% mortality rate within 3 months of AIS.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eMuscle strength is a reliable, easy to assess and reproducible clinical method to predict functional outcome and mortality at 90-days in patients treated with EVT and it is influenced by age, NIHSS score, extend of tissue involvement and time for recanalization.\u003c/p\u003e","manuscriptTitle":"Muscle Strength at Discharge as Predictor of Functional Outcome in Ischemic Stroke Patients Following Endovascular Therapy: Observational Study in Two Comprehensive Stroke Centers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-18 09:51:05","doi":"10.21203/rs.3.rs-4893440/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":"aa9cbbf3-9cd6-4463-a884-f03df620e12f","owner":[],"postedDate":"October 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":38223622,"name":"Health sciences/Medical research/Study design/Clinical trials"},{"id":38223623,"name":"Health sciences/Medical research/Experimental models of disease"}],"tags":[],"updatedAt":"2024-11-25T12:09:03+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-18 09:51:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4893440","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4893440","identity":"rs-4893440","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}