The Impact of Circadian Rhythms on Reperfusion Therapy Efficacy in Acute Ischemic Stroke: A retrospective cohort study

The Impact of Circadian Rhythms on Reperfusion Therapy Efficacy in Acute Ischemic Stroke: A retrospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of Circadian Rhythms on Reperfusion Therapy Efficacy in Acute Ischemic Stroke: A retrospective cohort study Yiqing Wang, Shenghao Fan, Shicun Huang, Man Lu, Yi Yang, Haifeng Lu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7640381/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background Ischemic acute stroke displays a well-recognized circadian pattern. However, whether stroke onset time affects the therapeutic efficacy of standard interventions (intravenous thrombolysis) remain uncertain. Methods This retrospective cohort study included 712 patients with acute ischemic stroke receiving reperfusion therapy (intravenous thrombolysis or combined endovascular therapy). Patients were categorized into two groups (day-onset [06:00–18:00] and night-onset [18:00–06:00]) and into 6 groups by 4-hour intervals. The primary outcome was the 3-month functional status, evaluated using the modified Rankin Scale, with scores of 0–2 classified as favorable and scores of 3–6 as unfavorable outcomes. Propensity scores matching (PSM), inverse probability of treatment weighting (IPTW), overlap weighting were used for analyses. Results 148 out of 286 patients (51.7%) in night-onset group and 182 out of 426 patients (42.7%) in day-onset group experienced unfavorable outcome at 3 months. Night-onset stroke was associated with a significantly risk of unfavorable outcome compared to day-onset stroke (OR = 1.44; 95%CI, 1.06–1.94; P = 0.018). This association remained significant after adjustment using PSM (OR = 1.45; 95% CI, 1.01–2.08; P = 0.044), and was further confirmed in analyses using IPTW (OR = 1.42; 95% CI,1.02–1.96; P = 0.036) and overlap weighting (OR = 1.42; 95% CI,1.03–1.96; P = 0.032). Nighttime strokes during 22:00–02:00 (OR = 2.44; 95% CI, 1.34–4.43; P = 0.003) was significantly associated with a higher likelihood of unfavorable outcome in adjusted analysis. Conclusions Night-onset strokes are associated with poorer 3-month functional outcomes compared to day-onset strokes. Optimization of stroke treatment workflows is particularly important for patients with nighttime-onset stroke to reduce delays in reperfusion therapy. Further prospective studies are warranted to validate these findings. Trial Registration: Chinese Clinical Trial Registry Identifier: ChiCTR2500101844. ischemic acute stroke circadian modified Rankin Scale unfavorable outcome propensity scores matching Figures Figure 1 Figure 2 Figure 3 Introduction Cerebrovascular and cardiovascular events such as stroke and myocardial infarction, exhibit a well-recognized circadian pattern. 1 – 4 Numerous physiological processes that influence stroke outcomes, including blood pressure, metabolic activity, platelet aggregation, endothelial function, and immune mechanisms, are modulated by circadian clock. 5 – 8 In acute ischemic stroke, growing evidence suggests that the timing of stroke onset may influence clinical outcomes by affecting the progression of the ischemic core, susceptibility to reperfusion injury, and thrombotic risk. 9 – 11 Circadian rhythms may influence the efficacy of treatment in acute ischemic stroke. An experimental study has demonstrated that neuroprotective agents are more effective during the daytime (the inactive phase for rodents) compared to the nighttime active period. 12 However, whether the therapeutic efficacy of intravenous thrombolysis (IVT) or endovascular therapy (EVT), the standard interventions for acute ischemic stroke, is modulated by circadian mechanisms—particularly in relation to long-term functional outcomes—remains inadequately understood. Recent studies have investigated the impact of stroke onset time on clinical outcomes following IVT or EVT, yielding inconsistent results. 13 – 17 In this study, we aimed to assess the association between stroke onset time and 3-month neurological outcomes in patients treated with IVT alone or in combination with EVT. We hypothesized that stroke onset time would significantly influence mid-term neurological outcomes in this population. Methods Study design and participants This retrospective, single-centre study included 712 consecutive patients diagnosed with acute ischemic stroke at the First Affiliated Hospital of Soochow University from October 2018 to March 2022. This study was approved by the Ethics Committee of the First Affiliated Hospital of Soochow University on April 2025 (Approval No:2025 − 293) and was registered with the Chinese Clinical Trial Registry (identifier: ChiCTR2500101844). Informed consent was waived by the local Ethics Committee according to regulations for retrospective clinical studies. This study followed the Declaration of Helsinki and adhered to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines. The inclusion criteria were: (1) acute ischemic stroke receiving intravenous thrombolysis (2) the modified Rankin Scale (mRS) score before the onset of stroke was 0 or 1. The exclusion criteria were: (1) occlusion in the posterior circulation; (2) the exact time of onset is unclear; (3) missing clinical data. Clinical data collection Two researchers independently reviewed the Health Information System to extract patient demographics, medical history, and clinical characteristics. Demographic variables included age and sex. Medical history variables encompassed hypertension, diabetes mellitus, coronary artery disease, peripheral vascular disease, atrial fibrillation, transient ischemic attack (TIA), hyperglycaemia, prestrike antiplatelet use, prestrike statin use, and current smoking status. Clinical characteristics included stroke subtype (large artery atherosclerosis [LAA], cardioembolism [CE], small vessel occlusion [SVO], other-determined, and undetermined), onset-to-door time, door-to-needle time, the National Institutes of Health Stroke Scale (NIHSS) score, Alberta Stroke Program Early CT Score (ASPECTS), endovascular thrombectomy, and modified Rankin Scale (mRS) score. Stroke onset time was determined by a neurologist via interviews with patients and/or witnesses who observed the symptoms onset. For patients presenting with wake-up strokes, defined as those last seen normal at bedtime, the estimated onset time was calculated as the average time between the time last seen well and time of symptom recognition. Based on the time of symptom onset, all patients were categorized into a day-onset group (06:00–18:00) and a night-onset group (18:00–06:00). For a more detailed temporal analysis, patients were further stratified into 4-hour onset intervals. The 3-month mRS score was collected via structured follow-up by designated personnel and documented in the electronic medical records. Study outcomes The primary outcome was the 3-month functional status, evaluated using the mRS, with scores of 0–2 classified as favorable and scores of 3–6 as unfavorable outcomes. Exploratory outcomes included hemorrhagic transformation, the status of collateral circulation, the volume of the ischemic core, mismatch ratio, and the volume of the penumbra. The collateral circulation status was evaluated using the regional leptomeningeal collateral (rLMC) score. 18 The volume of the ischemic core was defined as the region of hypoperfusion where the relative cerebral blood flow (rCBF) was less than 30%. 19 The mismatch ratio was calculated as the ratio of the total and core volume. 13 The ischemic penumbra was identified as tissue with an initial cerebral blood flow (CBF) below 25mL/100g/min that did not progress to infarction on follow-up computed tomography perfusion (CTP) imaging performed 5 to 7 days later. 20 Statistical analysis To account for baseline differences between groups, propensity scores were estimated using multivariable logistic regression incorporating patient and clinical characteristics. 21 Three propensity score-based adjustment methods were applied: propensity score matching (PSM), inverse probability of treatment weighting (IPTW), and overlap weighting. 22 Treatment effects were evaluated in one-to-one matched cohorts using PSM with a greedy matching algorithm and a caliper width of 0.2 times the pooled standard deviation. IPTW and overlap weighting were further employed to estimate the average treatment effect in the overall study population. 23 For IPTW, patients with daytime onset were weighted by the inverse of their propensity score, while those with nighttime onset were weighted by the inverse of one minus the propensity score. In overlap weighting, patients with daytime onset were assigned a weight of one minus the propensity score, whereas those with nighttime onset were weighted by the propensity score. Covariate balance after adjustment was assessed using standardized mean differences (SMDs) and visualized through propensity score density plots. Continuous variables are reported as mean (standard deviation [SD]) or median (interquartile range [IQR]), as appropriate, while categorical variables are expressed as frequencies and percentages. The primary and exploratory outcomes were analyzed using univariate logistic regression or generalized linear models, with log 10 transformation applied to variables exhibiting skewed distributions. For the primary outcome, subgroup analysis was further conducted in term of age (< 60 vs ≥ 60 years), sex (male vs female), history of hypertension (yes vs no), diabetes mellitus (yes vs no), atrial fibrillation (yes vs no), TIA (yes vs no), and stroke subtype (LAA vs CE vs SVO vs other-determined vs undetermined) in the unmatched cohort. Logistic regression model was used to investigate the association between stroke onset time and function outcome at 3 months. There were no missing data for the primary outcome. Covariates (Coronary artery disease, transient ischemic attack) exhibited less than 5% missing data, and multiple imputation was performed using the mice package in R. A two-tailed P value of < 0.05 was considered indicative of statistical significance. All statistical analyses were conducted using R software (version 4.4.1; R Foundation for Statistical Computing, Vienna, Austria). Results A total of 1061 patients presenting with acute ischemic stroke and treated with recombinant alteplase (rt-PA) infusion were screened for eligibility (Fig. 1 ). Of these, 712 patients were finally included: 426 experienced symptom onsets during daytime hours and 286 during nighttime hours. The median patient age was 70 years (IQR, 58–76), and 466 patients (65.4%) were male. Among the included patients, 98 additionally underwent endovascular thrombectomy. Patient demographic, medical history, and clinical characteristics were summarized in Table 1 . Several baseline characteristics, including age, history of hypertension, atrial fibrillation, prestroke antiplatelet use, onset-to-door time, and endovascular thrombectomy were differed between groups (SMD > 0.1). After adjustment using PSM, IPTW, and overlap weighting method, the baseline covariates were balanced between groups (Table 1 , Table S1 ), as further confirmed by the SMD distribution plot (Figure S1 ) and the propensity score distribution plot (Figure S2). Table 1 Patient characteristics before and after propensity score matching. Unadjusted, No. (%) SMD PSM adjusted, No. (%) SMD Night-onset ( n = 286) Day-onset ( n = 426) Night-onset ( n = 241) Day-onset ( n = 241) Demographic Age, median [IQR], y 69 (57,76) 70 (61, 77) 0.178 69 (57, 76) 69 (57, 76) 0.040 Sex 0.072 0.009 Female 93 (32.5) 153 (35.9) 83 (34.4) 82 (34.0) Male 193 (67.5) 273 (64.1) 158 (65.6) 159 (66.0) Medical history Hypertension 194 (67.8) 268 (62.9) 0.104 156 (64.7) 161 (66.8) 0.044 Diabetes 59 (20.6) 93 (21.8) 0.029 50 (20.8) 52 (21.6) 0.020 Coronary artery disease 24 (8.4) 33 (7.8) 0.024 21 (8.7) 25 (10.4) 0.057 Peripheral vascular disease 13 (4.6) 12 (2.8) 0.092 10 (4.2) 7 (2.9) 0.068 Atrial fibrillation 70 (24.5) 68 (16.0) 0.213 53 (22.0) 52 (21.6) 0.010 Transient ischemic attack 15 (5.2) 23 (5.4) 0.007 13 (5.4) 12 (5.0) 0.019 Current smoking 59 (20.6) 92 (21.6) 0.024 50 (20.8) 53 (22.0) 0.030 Hyperlipidemia 100 (35) 134 (31.5) 0.075 79 (32.8) 79 (32.8) < 0.001 Prestroke antiplatelet use 93 (32.5) 107 (25.1) 0.164 72 (29.9) 63 (26.1) 0.083 Prestroke statin use 61 (21.3) 92 (21.6) 0.007 50 (20.8) 59 (24.5) 0.089 Stroke subtype 0.078 0.045 LAA 66 (23.1) 107 (25.1) 56 (23.2) 59 (24.5) CE 40 (14.0) 64 (15.0) 37 (15.4) 38 (15.8) SVO 91 (31.8) 127 (29.8) 75 (31.1) 71 (29.5) Other-determined 18 (6.3) 22 (5.2) 13 (5.4) 14 (5.8) Undetermined 71 (24.8) 106 (24.9) 60 (24.9) 59 (24.5) Clinical characteristic Onset-to-door time, median [IQR], h 2.0 (1.4, 2.5) 2.4 (1.9, 2.8) 0.596 2.1 (1.6, 2.6) 2.0 (1.7, 2.5) 0.033 Door-to-needle time, median [IQR], min 48 (42, 55) 48 (42, 54) 0.017 49 (42, 55) 48 (42, 55) 0.032 NIHSS, median [IQR] 7 (2,13) 6 (2, 12) 0.091 6 (2, 13) 6 (2, 13) 0.008 ASPECT score, median [IQR] 9 (7.3, 10) 9 (8, 10) 0.006 9 (8, 10) 9 (8, 10) 0.008 Endovascular thrombectomy 49 (17.1) 49 (11.5) 0.161 34 (14.1) 34 (14.1) < 0.001 ASPECT: Alberta Stroke Program Early CT; CE, cardioembolism; IQR, interquartile range; LAA, large artery atherosclerosis; NIHSS, National Institutes of Health Stroke Scale; PSM, propensity score matching; SD, standard deviation; SMD, standardized mean difference; SVO, small vessel occlusion. Primary outcome In the unadjusted cohort, 148 out of 286 patients (51.7%) in night-onset group and 182 out of 426 patients (42.7%) in day-onset group experienced unfavorable outcome at 3 months. Night-onset stroke was associated with a significantly risk of unfavorable outcome compared to day-onset stroke (OR = 1.44; 95%CI, 1.06–1.94; P = 0.018) (Fig. 2 ). This association remained significant after adjustment using PSM (OR = 1.45; 95% CI, 1.01–2.08; P = 0.044), and was further confirmed in analyses using IPTW (OR = 1.42; 95% CI,1.02–1.96; P = 0.036) and overlap weighting (OR = 1.42; 95% CI,1.03–1.96; P = 0.032). When stroke onset times were grouped by 4-hour intervals, 169 patients (23.7%) presented between 06:00 and 10:00, 118 (16.6%) between 10:00 and 14:00, 139 (19.5%) between 14:00 and 18:00, 167 (23.5%) between 18:00 and 22:00, 69 (9.7%) between 22:00 and 02:00, and 50 (7.0%) between 02:00 and 06:00 (Table 2 ). Compared with the reference period of 06:00–10:00, nighttime strokes during 22:00–02:00 (OR = 2.44; 95% CI, 1.34–4.43; P = 0.003) had a higher likelihood of 3-month unfavorable outcomes in adjusted analysis. Regarding the association between night-onset stroke and 3-month function outcomes, no significant heterogeneity was observed across subgroups stratified by age, sex, hypertension status, diabetes, atrial fibrillation, TIA, or stroke subtype ( Fig. 3 ). Table 2 Multivariable associations of stroke onset time (at 4-hour intervals) with 3-month function outcome. CI, confidence interval. Onset time Total Events (%) Unadjusted Adjusted a OR (95% CI) P -value OR (95% CI) P -value 06:00−10:00 169 66 (39.1) 1 (reference) 1 (reference) 10:00−14:00 118 47 (39.8) 1.03 (0.64−1.67) 0.895 1.10 (0.67−1.81) 0.704 14:00−18:00 139 69 (49.6) 1.54 (0.98−2.42) 0.063 1.52 (0.95−2.44) 0.081 18:00−22:00 167 86 (51.5) 1.66 (1.07−2.56) 0.022 1.60 (1.01−2.56) 0.050 22:00−02:00 69 38 (55.1) 1.91 (1.09−3.37) 0.025 2.44 (1.34−4.43) 0.003 02:00−06:00 50 24 (48.0) 1.44 (0.76−2.72) 0.260 1.63 (0.83−3.18) 0.156 a Multivariable logistic regression was performed with adjustment for age, hypertension, atrial fibrillation, prestrike antiplatelet use, onset-to-door time, endovascular thrombectomy Exploratory analysis Patients with symptom onset at night exhibited higher ischemic core volume compared to those with daytime onset, both in the unadjusted and after adjustment using PSM, IPTW, and overlap weighting method. (Table 3 , Table S2). No significant differences were observed between groups in hemorrhagic transformation, collateral score, mismatch ratio, or penumbra volume both in unadjusted and adjusted cohort. Table 3 Exploratory outcomes in the unadjusted and PSM adjusted cohorts. CI, confidence interval; IQR, interquartile range; PSM, propensity score matching. Unadjusted, Median (IQR) PSM adjusted, Median (IQR) Night-onset ( n = 286) Day-onset ( n = 426) OR or difference (95% CI) a P -value Night ( n = 241) Day ( n = 241) OR or difference (95% CI) P -value Hemorrhagic transformation, No (%) 40 (14.0) 50 (11.7) 1.22 (0.78–1.91) 0.377 34 (14.1) 27 (11.2) 1.30 (0.76–2.23) 0.338 Collateral score 16 (13.3–19.0) 17 (14–19) 0.00 (-0.02-0.02) 0.801 16 (14–19) 17 (13–19) 0.00 (-0.03-0.03) 0.954 Core volume 4 (1-17.8) 2 (0-15.8) 0.85 (0.66–1.04) < 0.001 4 (1–15) 3 (0–17) 0.80 (0.58–1.01) < 0.001 Mismatch-ratio 5 (1.2–15.7) 4.3 (0-14.9) 0.11 (-0.13-0.34) 0.362 5.2 (1.2–16.0) 3.5 (0–13) 0.24 (-0.04-0.51) 0.089 Penumbra volumes 50.5 (3.3–87.8) 35 (0–80) 0.14 (-0.11-0.39) 0.267 48 (3–90) 35 (0–84) 0.15 (-0.15-0.44) 0.333 a Difference is presented after Log 10 transformation. Discussion In this retrospective cohort study of 712 patients with acute ischemic stroke who underwent intravenous thrombolysis, we found that night-onset stroke was significantly associated with an increased risk of unfavorable functional outcomes at 3 months compared to day-onset stroke. Further temporal stratification revealed that symptom onset between 22:00-02:00 particularly had a lower likelihood of favorable 3-month outcomes. Patients with nighttime symptom also exhibited significantly larger ischemic core volume than those with daytime onset. No significant intergroup differences were observed in terms of hemorrhagic transformation, collateral circulation, mismatch ratio, or penumbra volume. Circadian regulation is increasingly recognized as an important contributor to stroke progression. Fundamental stroke risk factors, including blood pressure and metabolic homeostasis, along with key mechanisms involved in stroke onset and injury progression—such as endothelial function, platelet aggregation, and thrombus formation—are all modulated by circadian rhythms. 8, 10, 24-26 Core clock genes regulate the expression of up to 40% of all genes, including those involved in inflammation, metabolism and cell death. 10, 27 An experimental study using mouse neurons subjected to oxygen and glucose deprivation demonstrated that the inactive phase (daytime in rodents) induced greater release of glutamate and reactive oxygen species, as well as enhanced activation of apoptotic pathways, compared to the active phase (nighttime in rodents). 12 Philipp Mergenthaler proposed that the brain is more susceptible to ischemic damage and neurodegeneration during sleep. 10 Many clinical studies have investigated the association between circadian rhythms and stroke outcomes. 11, 13, 14, 28-30 A recent cohort study demonstrated that strokes occurring at night, compared to those with daytime onset, are associated with greater neurological severity at presentation, a higher incidence early neurological deterioration, and poorer functional outcome at 3 months. 14 However, as only approximately 35% of patients in that study received revascularization therapy, the findings may have been influenced by potential confounding factors. In our study, we specifically included patients who underwent intravenous thrombolysis or combined intra-arterial therapy for revascularization. In addition, we applied four distinct statistical methods to adjust for potential confounders, consistently confirming the association between night-onset strokes and worse outcomes. Another retrospective cohort study involving 1558 acute ischemic stroke patients treated with endovascular therapy (EVT) demonstrated that EVT procedures initiated in the morning (08:00-10:20) were associated with more favorable mid-term functional outcomes, whereas those starting at the end of the working day (15:54-17:15) were associated with less favorable neurological results. 28 In our study, the majority of patients received intravenous thrombolysis alone, with only 13% undergoing additional EVT. Our findings revealed that stroke onset during the periods of 22:00–02:00 was associated with a lower likelihood of achieving favorable functional outcomes at 3 months. Nevertheless, the evidence remains inconclusive. A retrospective cohort study conducted in China demonstrated that circadian rhythms had no significant impact on the clinical outcomes in acute ischemic stroke patients treated with rt-PA, although nighttime onset was associated with more pronounced neurological deficits before thrombolysis. 16 Consistent with that study, our cohort also showed short onset-to-door intervals and poor baseline neurological status for nighttime onsets stroke. Crucially, we tracked the functional outcomes at 3 months, whereas the earlier study evaluated only 7-day neurological improvement and mortality. Differences in initial stroke severity, reflected by the lower admission NIHSS scores in our population, may contribute to the divergent findings. The ischemic core, representing irreversibly infarcted brain tissue in acute ischemic stroke, plays a pivotal role in guiding therapeutic decisions and predicting clinical outcomes. Chen et al. demonstrated that larger baseline core volumes were significantly associated with poorer functional outcomes in patients receiving intravenous thrombolysis alone. 29 Specifically, patients with a baseline ischemic core volume of 30 ml. A retrospective study further indicated that stroke symptom onset during nighttime was associated with larger ischemic core volumes at admission relative to daytime onset, with the most extensive core volumes observed in patients whose symptoms began around 11:00 PM. 13 Consistently, another large cohort study based on a national database reported that nighttime stroke onset was associated with greater ischemic core volumes and poorer collateral status relative to daytime onset, with the peaked imaging typically obtained around the same time in the night (03:00-04:00). 30 In line with previous reports, our study also investigated the association between stroke onset time and ischemic core volume, revealing larger core volumes in patients with nighttime stroke onset. Nevertheless, no significant between-group difference was found in collateral status. This divergence from earlier studies may stem from methodological differences in collateral assessment: we quantified collateral flow with the straightforward and clinically practical regional leptomeningeal collateral score rather than the hypoperfusion intensity ratio. Acute ischemic stroke with large vessel occlusion, the core infarct volume grows more rapidly at night compared to during the day 31 . A faster core infarct growth rate is associated with worse 90-day functional clinical outcomes in these patients 32 . This suggests that stroke treatment workflows should be further expedited for patients with nighttime onset to minimize time to reperfusion therapy. It is recommended that patients with acute ischemic stroke due to large vessel occlusion occurring at night be directly transferred to an endovascular-capable stroke center 33 . Our study has some limitations. First, despite the use of PSM, IPTW and overlap weighting to minimize selection bias between day-onset and night-onset groups, inherent limitations of this nonrandomized study design may still introduce residual confounding. Second, early neurological deterioration, which reflects infarct progression, was not assessed. However, we examined the penumbra volume, which may serve as an indirect indicator of the potential for infarct growth. 20 Third, achieving greater data granularity requires a larger sample size, which may facilitate a more precise delineation of the associations between stroke onset time and clinical outcomes across narrower temporal intervals. In conclusion, night-onset strokes are associated with poorer 3-month functional outcomes compared to day-onset strokes. Optimization of stroke treatment workflows is particularly important for patients with nighttime-onset stroke to reduce delays in reperfusion therapy. Further prospective studies are warranted to validate these findings. Declarations Data availability statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Authors’ contributions Study design: YQW, HFL, QF Data acquisition: YQW, SHF, SCH, YY Manuscript drafting: YQW, SHF, SCH, YY Manuscript revision: HFL, QF Data interpretation: all authors Final approval of the version to be published: all authors Funding: This study was supported by institutional and departmental sources at the First Affiliated Hospital of Soochow University, and by National Natural Science Foundation of China (82471323), The funders were not involved in the design or execution of the study or in the analysis and interpretation of the data. References Lo EH, Albers GW, Dichgans M, et al. Circadian Biology and Stroke. Stroke 2021;52:2180–2190. Muller JE, Tofler GH, Stone PH. 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Neurology 2021;96:e1124-e1136. Chen C, Parsons MW, Levi CR, et al. Exploring the relationship between ischemic core volume and clinical outcomes after thrombectomy or thrombolysis. Neurology 2019;93:e283-e292. Lun R, Sreekrishnan A, Liu HY, Albers GW. Ischemic core volumes and collateral status have diurnal fluctuations - A retrospective cohort study of 18,137 patients. J Stroke Cerebrovasc Dis 2024;33:107965. Seners P, Mlynash M, Sreekrishnan A, et al. Infarct Core Growth During Interhospital Transfer For Thrombectomy Is Faster At Night. Stroke 2023;54:2167–2171. Chen S, Chen G, Zhao C, et al. Infarct core growth rate and 90-day outcomes in ischemic stroke: subgroup analysis based on onset-to-recanalization time. Frontiers in Neurology 2025;16. García-Tornel Á, Flores A, Terceño M, et al. Association of Time of Day With Outcomes Among Patients Triaged for a Suspected Severe Stroke in Nonurban Catalonia. Stroke 2023;54:770–780. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7640381","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":536718729,"identity":"9de78e4e-479c-4c05-908c-7d6e0e684293","order_by":0,"name":"Yiqing Wang","email":"","orcid":"","institution":"First Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Yiqing","middleName":"","lastName":"Wang","suffix":""},{"id":536718730,"identity":"b5c81de7-3530-4652-841e-c4d40e5aa6d8","order_by":1,"name":"Shenghao Fan","email":"","orcid":"","institution":"First Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Shenghao","middleName":"","lastName":"Fan","suffix":""},{"id":536718731,"identity":"2ade7b7e-350e-40dd-a2fb-722bec69fc16","order_by":2,"name":"Shicun Huang","email":"","orcid":"","institution":"First Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Shicun","middleName":"","lastName":"Huang","suffix":""},{"id":536718732,"identity":"9b0cac6d-da30-4966-b44c-8252da1cdaae","order_by":3,"name":"Man Lu","email":"","orcid":"","institution":"First Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Man","middleName":"","lastName":"Lu","suffix":""},{"id":536718733,"identity":"b919a4f2-948f-4f9e-bb10-ce593e69074e","order_by":4,"name":"Yi Yang","email":"","orcid":"","institution":"First Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Yang","suffix":""},{"id":536718734,"identity":"4932e90d-0b4b-41f4-ae50-3b69c3350504","order_by":5,"name":"Haifeng Lu","email":"","orcid":"","institution":"First Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Haifeng","middleName":"","lastName":"Lu","suffix":""},{"id":536718735,"identity":"479c877f-8742-4117-bbcd-1d877a9fbed2","order_by":6,"name":"Qi Fang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYBAC9gYQacDAw8befODAhwoitPAcgGiR4+c5lnhwxhmitTAwGEvOyDE+zNtCjBb2s4dfvClgSNxw5syHA7wNDPL8YgcIaOHJS7OcYwDUcrx3wwHJHQyGM2cn4Ndiz5BjZswD0nLm7IYDhmcYEgxuE9DCw/8GquVGzoMDiW3EaJHIMX4M1ALyPsOBg8RpeWPGOAcSyAYHG85IEPYLD3+O8Yc3f8BR+fjznwobeX5pAlqAgE2Ch+E/jCNBUDkIMH/gIUrdKBgFo2AUjFgAAHjKR9+GWuQVAAAAAElFTkSuQmCC","orcid":"","institution":"First Affiliated 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07:10:43","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":85443,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7640381/v1/8f4e390f5f5d43985e08c735.png"},{"id":94923847,"identity":"ea5430da-5050-404c-b6b1-ca8cbd2dad42","added_by":"auto","created_at":"2025-11-01 14:58:42","extension":"xml","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101739,"visible":true,"origin":"","legend":"","description":"","filename":"87a5dd8c7ccf41d09a67ba97adfa6af41structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7640381/v1/35b3713b8c52db73890337bb.xml"},{"id":94923845,"identity":"0be3b7f9-f7cc-435b-8cb9-02d41d95b88c","added_by":"auto","created_at":"2025-11-01 14:58:42","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":112147,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7640381/v1/8345e3f1890cd8840580b067.html"},{"id":94923833,"identity":"abe9ec6c-f254-4f9f-8fca-e51f1c0da0ac","added_by":"auto","created_at":"2025-11-01 14:58:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":161071,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow diagram.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7640381/v1/aea805a7c93a72e60edee21b.png"},{"id":94988283,"identity":"e7c791d0-f994-4b4d-a6b5-d691b68a5ea7","added_by":"auto","created_at":"2025-11-03 07:08:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":76561,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations of night-onset stroke with 3-month function outcome in unadjusted, PSM, IPTW, and OW cohorts.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7640381/v1/d682d775f7f03b6dac3ccd4c.png"},{"id":94923834,"identity":"fe695cbb-04e4-4e68-a6db-075911589c19","added_by":"auto","created_at":"2025-11-01 14:58:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":423885,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analyses of 3-month unfavourable outcome\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7640381/v1/7d15076075b26751d2f647cf.png"},{"id":94991004,"identity":"96f5688a-2e9d-4425-ab9a-da227c57d6ff","added_by":"auto","created_at":"2025-11-03 07:18:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1401768,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7640381/v1/12f58610-414f-47f4-90fc-75ff60f6af02.pdf"},{"id":94923838,"identity":"6c468d2c-4b15-4eec-a14d-25007a3e78f1","added_by":"auto","created_at":"2025-11-01 14:58:42","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":566347,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-7640381/v1/9824dde008cd92dc66abed5a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Circadian Rhythms on Reperfusion Therapy Efficacy in Acute Ischemic Stroke: A retrospective cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCerebrovascular and cardiovascular events such as stroke and myocardial infarction, exhibit a well-recognized circadian pattern.\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Numerous physiological processes that influence stroke outcomes, including blood pressure, metabolic activity, platelet aggregation, endothelial function, and immune mechanisms, are modulated by circadian clock.\u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e In acute ischemic stroke, growing evidence suggests that the timing of stroke onset may influence clinical outcomes by affecting the progression of the ischemic core, susceptibility to reperfusion injury, and thrombotic risk.\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eCircadian rhythms may influence the efficacy of treatment in acute ischemic stroke. An experimental study has demonstrated that neuroprotective agents are more effective during the daytime (the inactive phase for rodents) compared to the nighttime active period.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e However, whether the therapeutic efficacy of intravenous thrombolysis (IVT) or endovascular therapy (EVT), the standard interventions for acute ischemic stroke, is modulated by circadian mechanisms\u0026mdash;particularly in relation to long-term functional outcomes\u0026mdash;remains inadequately understood. Recent studies have investigated the impact of stroke onset time on clinical outcomes following IVT or EVT, yielding inconsistent results.\u003csup\u003e\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn this study, we aimed to assess the association between stroke onset time and 3-month neurological outcomes in patients treated with IVT alone or in combination with EVT. We hypothesized that stroke onset time would significantly influence mid-term neurological outcomes in this population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and participants\u003c/h2\u003e\u003cp\u003eThis retrospective, single-centre study included 712 consecutive patients diagnosed with acute ischemic stroke at the First Affiliated Hospital of Soochow University from October 2018 to March 2022. This study was approved by the Ethics Committee of the First Affiliated Hospital of Soochow University on April 2025 (Approval No:2025\u0026thinsp;\u0026minus;\u0026thinsp;293) and was registered with the Chinese Clinical Trial Registry (identifier: ChiCTR2500101844). Informed consent was waived by the local Ethics Committee according to regulations for retrospective clinical studies. This study followed the Declaration of Helsinki and adhered to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.\u003c/p\u003e\u003cp\u003eThe inclusion criteria were: (1) acute ischemic stroke receiving intravenous thrombolysis (2) the modified Rankin Scale (mRS) score before the onset of stroke was 0 or 1. The exclusion criteria were: (1) occlusion in the posterior circulation; (2) the exact time of onset is unclear; (3) missing clinical data.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eClinical data collection\u003c/h3\u003e\n\u003cp\u003eTwo researchers independently reviewed the Health Information System to extract patient demographics, medical history, and clinical characteristics. Demographic variables included age and sex. Medical history variables encompassed hypertension, diabetes mellitus, coronary artery disease, peripheral vascular disease, atrial fibrillation, transient ischemic attack (TIA), hyperglycaemia, prestrike antiplatelet use, prestrike statin use, and current smoking status. Clinical characteristics included stroke subtype (large artery atherosclerosis [LAA], cardioembolism [CE], small vessel occlusion [SVO], other-determined, and undetermined), onset-to-door time, door-to-needle time, the National Institutes of Health Stroke Scale (NIHSS) score, Alberta Stroke Program Early CT Score (ASPECTS), endovascular thrombectomy, and modified Rankin Scale (mRS) score.\u003c/p\u003e\u003cp\u003eStroke onset time was determined by a neurologist via interviews with patients and/or witnesses who observed the symptoms onset. For patients presenting with wake-up strokes, defined as those last seen normal at bedtime, the estimated onset time was calculated as the average time between the time last seen well and time of symptom recognition. Based on the time of symptom onset, all patients were categorized into a day-onset group (06:00\u0026ndash;18:00) and a night-onset group (18:00\u0026ndash;06:00). For a more detailed temporal analysis, patients were further stratified into 4-hour onset intervals. The 3-month mRS score was collected via structured follow-up by designated personnel and documented in the electronic medical records.\u003c/p\u003e\n\u003ch3\u003eStudy outcomes\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was the 3-month functional status, evaluated using the mRS, with scores of 0\u0026ndash;2 classified as favorable and scores of 3\u0026ndash;6 as unfavorable outcomes.\u003c/p\u003e\u003cp\u003eExploratory outcomes included hemorrhagic transformation, the status of collateral circulation, the volume of the ischemic core, mismatch ratio, and the volume of the penumbra.\u003c/p\u003e\u003cp\u003eThe collateral circulation status was evaluated using the regional leptomeningeal collateral (rLMC) score.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e The volume of the ischemic core was defined as the region of hypoperfusion where the relative cerebral blood flow (rCBF) was less than 30%.\u003csup\u003e19\u003c/sup\u003e The mismatch ratio was calculated as the ratio of the total and core volume.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e The ischemic penumbra was identified as tissue with an initial cerebral blood flow (CBF) below 25mL/100g/min that did not progress to infarction on follow-up computed tomography perfusion (CTP) imaging performed 5 to 7 days later.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eTo account for baseline differences between groups, propensity scores were estimated using multivariable logistic regression incorporating patient and clinical characteristics.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Three propensity score-based adjustment methods were applied: propensity score matching (PSM), inverse probability of treatment weighting (IPTW), and overlap weighting.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Treatment effects were evaluated in one-to-one matched cohorts using PSM with a greedy matching algorithm and a caliper width of 0.2 times the pooled standard deviation. IPTW and overlap weighting were further employed to estimate the average treatment effect in the overall study population.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e For IPTW, patients with daytime onset were weighted by the inverse of their propensity score, while those with nighttime onset were weighted by the inverse of one minus the propensity score. In overlap weighting, patients with daytime onset were assigned a weight of one minus the propensity score, whereas those with nighttime onset were weighted by the propensity score. Covariate balance after adjustment was assessed using standardized mean differences (SMDs) and visualized through propensity score density plots.\u003c/p\u003e\u003cp\u003eContinuous variables are reported as mean (standard deviation [SD]) or median (interquartile range [IQR]), as appropriate, while categorical variables are expressed as frequencies and percentages. The primary and exploratory outcomes were analyzed using univariate logistic regression or generalized linear models, with log\u003csub\u003e10\u003c/sub\u003e transformation applied to variables exhibiting skewed distributions. For the primary outcome, subgroup analysis was further conducted in term of age (\u0026lt;\u0026thinsp;60 vs\u0026thinsp;\u0026ge;\u0026thinsp;60 years), sex (male vs female), history of hypertension (yes vs no), diabetes mellitus (yes vs no), atrial fibrillation (yes vs no), TIA (yes vs no), and stroke subtype (LAA vs CE vs SVO vs other-determined vs undetermined) in the unmatched cohort. Logistic regression model was used to investigate the association between stroke onset time and function outcome at 3 months. There were no missing data for the primary outcome. Covariates (Coronary artery disease, transient ischemic attack) exhibited less than 5% missing data, and multiple imputation was performed using the \u003cem\u003emice\u003c/em\u003e package in R. A two-tailed \u003cem\u003eP\u003c/em\u003e value of \u0026lt;\u0026thinsp;0.05 was considered indicative of statistical significance. All statistical analyses were conducted using R software (version 4.4.1; R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 1061 patients presenting with acute ischemic stroke and treated with recombinant alteplase (rt-PA) infusion were screened for eligibility (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Of these, 712 patients were finally included: 426 experienced symptom onsets during daytime hours and 286 during nighttime hours. The median patient age was 70 years (IQR, 58\u0026ndash;76), and 466 patients (65.4%) were male. Among the included patients, 98 additionally underwent endovascular thrombectomy. Patient demographic, medical history, and clinical characteristics were summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Several baseline characteristics, including age, history of hypertension, atrial fibrillation, prestroke antiplatelet use, onset-to-door time, and endovascular thrombectomy were differed between groups (SMD\u0026thinsp;\u0026gt;\u0026thinsp;0.1). After adjustment using PSM, IPTW, and overlap weighting method, the baseline covariates were balanced between groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), as further confirmed by the SMD distribution plot (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) and the propensity score distribution plot (Figure S2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePatient characteristics before and after propensity score matching.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eUnadjusted, No. (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSMD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003ePSM adjusted, No. (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSMD\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNight-onset (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;286)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDay-onset\u003c/p\u003e\u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;426)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNight-onset\u003c/p\u003e\u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;241)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDay-onset\u003c/p\u003e\u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;241)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, median [IQR], y\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69 (57,76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70 (61, 77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e69 (57, 76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e69 (57, 76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e93 (32.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e153 (35.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e83 (34.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e82 (34.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e193 (67.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e273 (64.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e158 (65.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e159 (66.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMedical history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e194 (67.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e268 (62.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e156 (64.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e161 (66.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59 (20.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93 (21.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50 (20.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e52 (21.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoronary artery disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (7.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21 (8.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25 (10.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.057\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeripheral vascular disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (4.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7 (2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAtrial fibrillation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70 (24.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68 (16.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.213\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e53 (22.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e52 (21.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransient ischemic attack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13 (5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12 (5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent smoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59 (20.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92 (21.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50 (20.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e53 (22.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHyperlipidemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100 (35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (31.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79 (32.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e79 (32.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrestroke antiplatelet use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e93 (32.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107 (25.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e72 (29.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e63 (26.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.083\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrestroke statin use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61 (21.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92 (21.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50 (20.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e59 (24.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStroke subtype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66 (23.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107 (25.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56 (23.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e59 (24.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40 (14.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64 (15.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e37 (15.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e38 (15.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSVO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e91 (31.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e127 (29.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75 (31.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e71 (29.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther-determined\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (6.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13 (5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e14 (5.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUndetermined\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e71 (24.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e106 (24.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60 (24.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e59 (24.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eClinical characteristic\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOnset-to-door time, median [IQR], h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.0 (1.4, 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.4 (1.9, 2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.596\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.1 (1.6, 2.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.0 (1.7, 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDoor-to-needle time, median [IQR], min\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48 (42, 55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48 (42, 54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e49 (42, 55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e48 (42, 55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNIHSS, median [IQR]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (2,13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (2, 12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (2, 13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6 (2, 13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eASPECT score, median [IQR]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (7.3, 10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (8, 10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9 (8, 10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9 (8, 10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEndovascular thrombectomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49 (17.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49 (11.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34 (14.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e34 (14.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eASPECT: Alberta Stroke Program Early CT; CE, cardioembolism; IQR, interquartile range; LAA, large artery atherosclerosis; NIHSS, National Institutes of Health Stroke Scale; PSM, propensity score matching; SD, standard deviation; SMD, standardized mean difference; SVO, small vessel occlusion.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003ePrimary outcome\u003c/h2\u003e\u003cp\u003eIn the unadjusted cohort, 148 out of 286 patients (51.7%) in night-onset group and 182 out of 426 patients (42.7%) in day-onset group experienced unfavorable outcome at 3 months. Night-onset stroke was associated with a significantly risk of unfavorable outcome compared to day-onset stroke (OR\u0026thinsp;=\u0026thinsp;1.44; 95%CI, 1.06\u0026ndash;1.94; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This association remained significant after adjustment using PSM (OR\u0026thinsp;=\u0026thinsp;1.45; 95% CI, 1.01\u0026ndash;2.08; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.044), and was further confirmed in analyses using IPTW (OR\u0026thinsp;=\u0026thinsp;1.42; 95% CI,1.02\u0026ndash;1.96; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036) and overlap weighting (OR\u0026thinsp;=\u0026thinsp;1.42; 95% CI,1.03\u0026ndash;1.96; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.032).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWhen stroke onset times were grouped by 4-hour intervals, 169 patients (23.7%) presented between 06:00 and 10:00, 118 (16.6%) between 10:00 and 14:00, 139 (19.5%) between 14:00 and 18:00, 167 (23.5%) between 18:00 and 22:00, 69 (9.7%) between 22:00 and 02:00, and 50 (7.0%) between 02:00 and 06:00 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Compared with the reference period of 06:00\u0026ndash;10:00, nighttime strokes during 22:00\u0026ndash;02:00 (OR\u0026thinsp;=\u0026thinsp;2.44; 95% CI, 1.34\u0026ndash;4.43; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) had a higher likelihood of 3-month unfavorable outcomes in adjusted analysis.\u003c/p\u003e\u003cp\u003eRegarding the association between night-onset stroke and 3-month function outcomes, no significant heterogeneity was observed across subgroups stratified by age, sex, hypertension status, diabetes, atrial fibrillation, TIA, or stroke subtype \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariable associations of stroke onset time (at 4-hour intervals) with 3-month function outcome. CI, confidence interval.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOnset time\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEvents (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eUnadjusted\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eAdjusted \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e06:00\u0026minus;10:00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e169\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e66 (39.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10:00\u0026minus;14:00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e47 (39.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.03 (0.64\u0026minus;1.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.895\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.10 (0.67\u0026minus;1.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.704\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14:00\u0026minus;18:00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e69 (49.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.54 (0.98\u0026minus;2.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.063\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.52 (0.95\u0026minus;2.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.081\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18:00\u0026minus;22:00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e86 (51.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.66 (1.07\u0026minus;2.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.60 (1.01\u0026minus;2.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22:00\u0026minus;02:00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38 (55.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.91 (1.09\u0026minus;3.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.44 (1.34\u0026minus;4.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e02:00\u0026minus;06:00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24 (48.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.44 (0.76\u0026minus;2.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.63 (0.83\u0026minus;3.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.156\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003e Multivariable logistic regression was performed with adjustment for age, hypertension, atrial fibrillation, prestrike antiplatelet use, onset-to-door time, endovascular thrombectomy\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eExploratory analysis\u003c/h3\u003e\n\u003cp\u003ePatients with symptom onset at night exhibited higher ischemic core volume compared to those with daytime onset, both in the unadjusted and after adjustment using PSM, IPTW, and overlap weighting method. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table S2). No significant differences were observed between groups in hemorrhagic transformation, collateral score, mismatch ratio, or penumbra volume both in unadjusted and adjusted cohort.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExploratory outcomes in the unadjusted and PSM adjusted cohorts. CI, confidence interval; IQR, interquartile range; PSM, propensity score matching.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eUnadjusted, Median (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003ePSM adjusted, Median (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNight-onset (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;286)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDay-onset (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;426)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOR or difference (95% CI) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNight (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;241)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDay (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;241)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eOR or difference (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemorrhagic transformation, No (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e40 (14.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50 (11.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.22 (0.78\u0026ndash;1.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e34 (14.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e27 (11.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.30 (0.76\u0026ndash;2.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.338\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollateral score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16 (13.3\u0026ndash;19.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (14\u0026ndash;19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.00 (-0.02-0.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16 (14\u0026ndash;19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17 (13\u0026ndash;19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.00 (-0.03-0.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.954\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCore volume\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4 (1-17.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (0-15.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.85 (0.66\u0026ndash;1.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (1\u0026ndash;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3 (0\u0026ndash;17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.80 (0.58\u0026ndash;1.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMismatch-ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5 (1.2\u0026ndash;15.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.3 (0-14.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.11 (-0.13-0.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.362\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.2 (1.2\u0026ndash;16.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.5 (0\u0026ndash;13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.24 (-0.04-0.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePenumbra volumes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e50.5 (3.3\u0026ndash;87.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35 (0\u0026ndash;80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.14 (-0.11-0.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e48 (3\u0026ndash;90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e35 (0\u0026ndash;84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.15 (-0.15-0.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.333\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Difference is presented after Log\u003csub\u003e10\u003c/sub\u003e transformation.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this retrospective cohort study of 712 patients with acute ischemic stroke who underwent intravenous thrombolysis, we found that night-onset stroke was significantly associated with an increased risk of unfavorable functional outcomes at 3 months compared to day-onset stroke. Further temporal stratification revealed that symptom onset between 22:00-02:00 particularly had a lower likelihood of favorable 3-month outcomes. Patients with nighttime symptom also exhibited significantly larger ischemic core volume than those with daytime onset. No significant intergroup differences were observed in terms of hemorrhagic transformation, collateral circulation, mismatch ratio, or penumbra volume.\u003c/p\u003e\n\u003cp\u003eCircadian regulation is increasingly recognized as an important contributor to stroke progression. Fundamental stroke risk factors, including blood pressure and metabolic homeostasis, along with key mechanisms involved in stroke onset and injury progression—such as endothelial function, platelet aggregation, and thrombus formation—are all modulated by circadian rhythms.\u003csup\u003e8, 10, 24-26\u003c/sup\u003e Core clock genes regulate the expression of up to 40% of all genes, including those involved in inflammation, metabolism and cell death.\u003csup\u003e10, 27\u003c/sup\u003e An experimental study using mouse neurons subjected to oxygen and glucose deprivation demonstrated that the inactive phase (daytime in rodents) induced greater release of glutamate and reactive oxygen species, as well as enhanced activation of apoptotic pathways, compared to the active phase (nighttime in rodents).\u003csup\u003e12\u003c/sup\u003e Philipp Mergenthaler proposed that the brain is more susceptible to ischemic damage and neurodegeneration during sleep.\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eMany clinical studies have investigated the association between circadian rhythms and stroke outcomes.\u003csup\u003e11, 13, 14, 28-30\u003c/sup\u003e A recent cohort study demonstrated that strokes occurring at night, compared to those with daytime onset, are associated with greater neurological severity at presentation, a higher incidence early neurological deterioration, and poorer functional outcome at 3 months.\u003csup\u003e14\u003c/sup\u003e However, as only approximately 35% of patients in that study received revascularization therapy, the findings may have been influenced by potential confounding factors. In our study, we specifically included patients who underwent intravenous thrombolysis or combined intra-arterial therapy for revascularization. In addition, we applied four distinct statistical methods to adjust for potential confounders, consistently confirming the association between night-onset strokes and worse outcomes. Another retrospective cohort study involving 1558 acute ischemic stroke patients treated with endovascular therapy (EVT) demonstrated that EVT procedures initiated in the morning (08:00-10:20) were associated with more favorable mid-term functional outcomes, whereas those starting at the end of the working day (15:54-17:15) were associated with less favorable neurological results.\u003csup\u003e28\u003c/sup\u003e In our study, the majority of patients received intravenous thrombolysis alone, with only 13% undergoing additional EVT. Our findings revealed that stroke onset during the periods of 22:00–02:00 was associated with a lower likelihood of achieving favorable functional outcomes at 3 months. Nevertheless, the evidence remains inconclusive. A retrospective cohort study conducted in China demonstrated that circadian rhythms had no significant impact on the clinical outcomes in acute ischemic stroke patients treated with rt-PA, although nighttime onset was associated with more pronounced neurological deficits before thrombolysis.\u003csup\u003e16\u003c/sup\u003e Consistent with that study, our cohort also showed short onset-to-door intervals and poor baseline neurological status for nighttime onsets stroke. Crucially, we tracked the functional outcomes at 3 months, whereas the earlier study evaluated only 7-day neurological improvement and mortality. Differences in initial stroke severity, reflected by the lower admission NIHSS scores in our population, may contribute to the divergent findings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe ischemic core, representing irreversibly infarcted brain tissue in acute ischemic stroke, plays a pivotal role in guiding therapeutic decisions and predicting clinical outcomes. Chen et al. demonstrated that larger baseline core volumes were significantly associated with poorer functional outcomes in patients receiving intravenous thrombolysis alone.\u003csup\u003e29\u003c/sup\u003e Specifically, patients with a baseline ischemic core volume of \u0026lt;5 ml had a markedly higher probability of being disability-free at 90 days compared to those with core volumes \u0026gt;30 ml. A retrospective study further indicated that stroke symptom onset during nighttime was associated with larger ischemic core volumes at admission relative to daytime onset, with the most extensive core volumes observed in patients whose symptoms began around 11:00 PM.\u003csup\u003e13\u003c/sup\u003e Consistently, another large cohort study based on a national database reported that nighttime stroke onset was associated with greater ischemic core volumes and poorer collateral status relative to daytime onset, with the peaked imaging typically obtained around the same time in the night (03:00-04:00).\u003csup\u003e30\u003c/sup\u003e In line with previous reports, our study also investigated the association between stroke onset time and ischemic core volume, revealing larger core volumes in patients with nighttime stroke onset. Nevertheless, no significant between-group difference was found in collateral status. This divergence from earlier studies may stem from methodological differences in collateral assessment: we quantified collateral flow with the straightforward and clinically practical regional leptomeningeal collateral score rather than the hypoperfusion intensity ratio. Acute ischemic stroke with large vessel occlusion, the core infarct volume grows more rapidly at night compared to during the day\u003csup\u003e31\u003c/sup\u003e. A faster core infarct growth rate is associated with worse 90-day functional clinical outcomes in these patients\u003csup\u003e32\u003c/sup\u003e. This suggests that stroke treatment workflows should be further expedited for patients with nighttime onset to minimize time to reperfusion therapy. It is recommended that patients with acute ischemic stroke due to large vessel occlusion occurring at night be directly transferred to an endovascular-capable stroke center\u003csup\u003e33\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eOur study has some limitations. First, despite the use of PSM, IPTW and overlap weighting to minimize selection bias between day-onset and night-onset groups, inherent limitations of this nonrandomized study design may still introduce residual confounding. Second, early neurological deterioration, which reflects infarct progression, was not assessed. However, we examined the penumbra volume, which may serve as an indirect indicator of the potential for infarct growth.\u003csup\u003e20\u003c/sup\u003e Third, achieving greater data granularity requires a larger sample size, which may facilitate a more precise delineation of the associations between stroke onset time and clinical outcomes across narrower temporal intervals.\u003c/p\u003e\n\u003cp\u003eIn conclusion, night-onset strokes are associated with poorer 3-month functional outcomes compared to day-onset strokes. Optimization of stroke treatment workflows is particularly important for patients with nighttime-onset stroke to reduce delays in reperfusion therapy. Further prospective studies are warranted to validate these findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding\u003c/p\u003e\n\u003cp\u003eauthor upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy design: YQW, HFL, QF\u003c/p\u003e\n\u003cp\u003eData acquisition: YQW, SHF, SCH, YY\u003c/p\u003e\n\u003cp\u003eManuscript drafting: YQW, SHF, SCH, YY\u003c/p\u003e\n\u003cp\u003eManuscript revision: HFL, QF\u003c/p\u003e\n\u003cp\u003eData interpretation: all authors\u003c/p\u003e\n\u003cp\u003eFinal approval of the version to be published: all authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by institutional and departmental sources at the First Affiliated Hospital of Soochow University, and by National Natural Science Foundation of China (82471323), The funders were not involved in the design or execution of the study or in the analysis and interpretation of the data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLo EH, Albers GW, Dichgans M, et al. 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Circulation Research 2024;134:770\u0026ndash;790.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMergenthaler P, Balami JS, Neuhaus AA, et al. Stroke in the Time of Circadian Medicine. Circ Res 2024;134:770\u0026ndash;790.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGottlieb E, Landau E, Baxter H, Werden E, Howard ME, Brodtmann A. The bidirectional impact of sleep and circadian rhythm dysfunction in human ischaemic stroke: A systematic review. Sleep Med Rev 2019;45:54\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEsposito E, Li W, E TM, et al. Potential circadian effects on translational failure for neuroprotection. Nature 2020;582:395\u0026ndash;398.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReidler P, Brehm A, Sporns PB, et al. Circadian rhythm of ischaemic core progression in human stroke. 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J Stroke Cerebrovasc Dis 2024;33:107965.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeners P, Mlynash M, Sreekrishnan A, et al. Infarct Core Growth During Interhospital Transfer For Thrombectomy Is Faster At Night. Stroke 2023;54:2167\u0026ndash;2171.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen S, Chen G, Zhao C, et al. Infarct core growth rate and 90-day outcomes in ischemic stroke: subgroup analysis based on onset-to-recanalization time. Frontiers in Neurology 2025;16.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarc\u0026iacute;a-Tornel \u0026Aacute;, Flores A, Terce\u0026ntilde;o M, et al. Association of Time of Day With Outcomes Among Patients Triaged for a Suspected Severe Stroke in Nonurban Catalonia. Stroke 2023;54:770\u0026ndash;780.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"ischemic acute stroke, circadian, modified Rankin Scale, unfavorable outcome, propensity scores matching","lastPublishedDoi":"10.21203/rs.3.rs-7640381/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7640381/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eIschemic acute stroke displays a well-recognized circadian pattern. However, whether stroke onset time affects the therapeutic efficacy of standard interventions (intravenous thrombolysis) remain uncertain.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis retrospective cohort study included 712 patients with acute ischemic stroke receiving reperfusion therapy (intravenous thrombolysis or combined endovascular therapy). Patients were categorized into two groups (day-onset [06:00\u0026ndash;18:00] and night-onset [18:00\u0026ndash;06:00]) and into 6 groups by 4-hour intervals. The primary outcome was the 3-month functional status, evaluated using the modified Rankin Scale, with scores of 0\u0026ndash;2 classified as favorable and scores of 3\u0026ndash;6 as unfavorable outcomes. Propensity scores matching (PSM), inverse probability of treatment weighting (IPTW), overlap weighting were used for analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003e148 out of 286 patients (51.7%) in night-onset group and 182 out of 426 patients (42.7%) in day-onset group experienced unfavorable outcome at 3 months. Night-onset stroke was associated with a significantly risk of unfavorable outcome compared to day-onset stroke (OR\u0026thinsp;=\u0026thinsp;1.44; 95%CI, 1.06\u0026ndash;1.94; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018). This association remained significant after adjustment using PSM (OR\u0026thinsp;=\u0026thinsp;1.45; 95% CI, 1.01\u0026ndash;2.08; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.044), and was further confirmed in analyses using IPTW (OR\u0026thinsp;=\u0026thinsp;1.42; 95% CI,1.02\u0026ndash;1.96; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036) and overlap weighting (OR\u0026thinsp;=\u0026thinsp;1.42; 95% CI,1.03\u0026ndash;1.96; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.032). Nighttime strokes during 22:00\u0026ndash;02:00 (OR\u0026thinsp;=\u0026thinsp;2.44; 95% CI, 1.34\u0026ndash;4.43; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) was significantly associated with a higher likelihood of unfavorable outcome in adjusted analysis.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eNight-onset strokes are associated with poorer 3-month functional outcomes compared to day-onset strokes. Optimization of stroke treatment workflows is particularly important for patients with nighttime-onset stroke to reduce delays in reperfusion therapy. Further prospective studies are warranted to validate these findings.\u003c/p\u003e\u003ch2\u003eTrial Registration:\u003c/h2\u003e\u003cp\u003eChinese Clinical Trial Registry Identifier: ChiCTR2500101844.\u003c/p\u003e","manuscriptTitle":"The Impact of Circadian Rhythms on Reperfusion Therapy Efficacy in Acute Ischemic Stroke: A retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-01 14:58:37","doi":"10.21203/rs.3.rs-7640381/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-10-21T14:12:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-21T14:15:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-21T12:35:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Medical Research","date":"2025-09-17T12:38:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d967b71b-fe2f-427f-898d-f258a9b3ebd4","owner":[],"postedDate":"November 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-01T14:58:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-01 14:58:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7640381","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7640381","identity":"rs-7640381","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}