Abstract
Background
Patient informed consent and decision-making continue to be significant factors impeding the efficiency of fast tacking of acute ischemic stroke (AIS). To date, no studies have explored the role of accompanying authorized surrogates in the early emergency care timelines and outcomes.
Methods
This study retrospectively reviewed patients with stroke and suspected patients with stroke presenting to the emergency department of a stroke center (2023–2026), to assess the effects of authorized surrogate on time intervals and prognostic indicators.
Results
Among 381 patients with AIS, the rate of adequate to medical order time (< 10 min) was 84.5% (322 of 381), and the rate of adequate to CT imaging time (< 25 min) was 46.5% (177 of 381). Thrombolysis and interventional therapy were performed in 64 (62.1%) and 12 (23.5%) patients, respectively, exclusively when an authorized surrogate was present. Analysis of the time metrics revealed the longest delays across all measured intervals (medical order, CT imaging, thrombolysis, interventional therapy, and total emergency care times) in patients who presented alone, followed by those with a spouse as a surrogate. ΔNIHSS scores showed significant differences among patients with different types of accompanying authorized surrogates (P = 0.038). Initial NIHSS scores were significantly higher in patients with AIS who agreed to thrombolysis and endovascular intervention than in those who refused these procedures (P < 0.05).
Conclusions
This study provides evidence that early in-hospital delay in patients with AIS is multifactorial and that the type of accompanying authorized surrogate is a critical and often overlooked factor influencing the efficiency of emergency treatment pathways in patients with AIS. The accompanying authorized surrogate plays a crucial role throughout the entire treatment process for patients with AIS. Meanwhile, the effect of the type of authorized accompanying surrogate on outcomes in AIS needs to be further validated.
Keywords: Acute ischemic stroke, Accompanying authorized surrogate, Informed consent, In-hospital delay, Outcomes
Introduction
Acute ischemic stroke (AIS) is the leading cause of stroke and represents a major threat to public health owing to its high incidence, disability, and mortality rates [1–4]. Studies have shown that intravenous thrombolysis (IVT) administered within 4.5 h of stroke onset can improve neurological outcomes. However, the efficacy of IVT diminishes with treatment delays, and the risk of adverse events increases [5–7]. Early treatment is universally recognized as the most critical factor for successful reperfusion and is the key to improving outcomes in patients with AIS.
Nevertheless, clinical features alone cannot reliably distinguish between hemorrhagic and ischemic strokes. All patients with suspected acute stroke should undergo emergency neuroimaging upon initial hospital arrival [8–10], typically via non-contrast computed tomography (CT) or magnetic resonance imaging (MRI). Procedures such as CT scanning, reperfusion therapy, and hospital admission generally require understanding and consent from patients or their legally authorized representative [11]. Since patients with acute stroke often have neurological impairments that preclude their participation in decision-making, surrogate decision-making has become an essential component of acute stroke care. Current guidelines emphasize time constraints and treatment timeliness but lack detailed recommendations regarding the informed consent process, overlooking its substantial impact on in-hospital emergency time metrics [12]. An acute ischemic stroke is the ultimate medical emergency, in which time management in the emergency department constitutes a pivotal component of clinical practice [13]. The emergency department timeline management for AIS is comparable to, and may carry even greater clinical significance than, that for acute hemorrhagic stroke [14].
Time is the brain, and CT imaging is a critical first step in saving time [13, 15, 16]. When performing CT, especially CT angiography and perfusion (CTA/CTP) or magnetic resonance imaging (MRI), or initiating reperfusion therapy, obtaining patient-side consent is mandatory. Therefore, expediting the informed consent process to shorten the in-hospital emergency time is crucial in the care pathway [17]. The establishment of stroke centers has significantly reduced delays attributable to the healthcare system within the stroke treatment workflow [18–20]. However, the time required for patient-side informed consent remains highly variable and uncontrollable and is influenced by numerous factors such as illness severity, health literacy, payment capacity, patient decision-making capacity, and family dynamics [21, 22]. To date, no studies have explored the role of accompanying authorized surrogates in the early emergency care timelines and outcomes of AIS. This study aimed to retrospectively collect and analyze clinical data from patients with AIS to investigate whether decision-making by accompanying authorized surrogates affects early in-hospital emergency time metrics and prognosis. These findings are intended to provide evidence-based guidance and a clinical reference for stroke center healthcare workers to facilitate effective communication with patients and their families, thereby optimizing emergency stroke treatment pathways and further shortening the in-hospital time to treatment.
Materials and methods
Research design
This retrospective study, which utilized data from patients with stroke and suspected patients with stroke at an emergency stroke center (January 2023- February 2026), investigated the influence of surrogate decision-making on early in-hospital emergency care to provided stratified communication guidance for healthcare workers, optimizing clinical workflows and resource allocation, and ensuring timely and effective treatment for patients with stroke.
Research participants
Patients who presented with AIS or suspected AIS and were treated at our stroke center between January 1, 2023, and February 28, 2026. This study included consecutive patients who presented with confirmed or suspected ischemic stroke at the designated stroke center between January 2023 and February 2026, were aged 14 years or older, and arrived at the hospital within 24 h of symptom onset. The exclusion criteria included missing clinical data, referral from other hospitals where prior intervention had been administered, or the absence of a brain CT scan.
Patients with a disease course exceeding 24 h were almost exclusively triaged to areas outside the stroke center, such as the emergency resuscitation or consultation rooms. Additionally, some patients with an initial presentation that was difficult to recognize but ultimately diagnosed with acute stroke may not have been triaged to the stroke center. Given the impact of their treatment priority on this study, the patients were not included in the study.
This study was conducted at a tertiary Grade A hospital, the highest level of hospital in China. Its stroke center is equipped to provide 24-hour thrombolysis and endovascular intervention. The Department of Neurology has over 120 beds. However, due to high patient volume, routine outpatients typically face admission wait times ranging from days to weeks, and even emergency department patients often experience delays of 1 to 3 days before admission. To address this, the department has designated specific beds for AIS to ensure timely access for patients requiring urgent care or those with severe, high-risk conditions.
Data collection
We retrospectively collected data from patients with stoke (from January 1, 2023 to February 28, 2025) on the following variables: sex, age, comorbidities, disease course, presentation time, medical order time, CT imaging time, thrombolysis therapy time, interventional therapy time, emergency treatment time, presence of an authorized surrogate, and the surrogate-patient relationship. The prognostic indicators assessed were hospital stay, neurological outcomes (Glasgow-Pittsburgh Cerebral Performance Category [CPC]), the National Institute of Health Stroke Scale (NIHSS) score, ΔNIHSS score, or the incidence of adverse events. The documented adverse events documented included hemorrhagic transformation, endotracheal intubation, intensive care unit (ICU) admission, and death. The prognostic indicators assessed were hospital stay, neurological outcomes (Glasgow-Pittsburgh Cerebral Performance Category, CPC), with an unfavorable outcome (CPC score ≥ 3) and a favorable outcome group (CPC score ≤ 2).
Definition of time metrics
The disease course was defined as the onset-to-door time, which refers to the interval between symptom onset and the patient’s arrival at the stroke center. Medical order time was defined as the interval from patient arrival (door) to the issuance of the first medical order by a stroke center physician, as recorded in the Hospital Information System (HIS). The CT imaging time was defined as the interval from patient arrival to completion of the CT localizer scan. The emergency treatment time was defined as the interval from patient arrival to the completion of hospital admission.
Grouping criteria
According to the stroke center construction requirements and guidelines, patients were categorized into adequate and inadequate groups based on whether the order time was completed within 10 min [14]. Similarly, patients were classified into CT-adequate and a CT-inadequate groups based on whether the CT imaging time was completed within 25 min [14]. The patients were categorized according to the following criteria: based on the time of presentation: they were divided into daytime (08:00–18:00) and nighttime (18:01–07:59) groups. The accompanying surrogate: divided into groups representing those who arrived alone, accompanied by a spouse, family, or others (such as relatives, colleagues and friends).
Outcomes
The primary outcomes were the CT imaging, medical order, and emergency treatment times. The secondary outcomes were length of hospital stay, adverse events, ΔNIHSS score and favorable neurological outcome with CPC ≤ 2.
Statistical analysis
Continuous variables with a normal distribution are presented as means ± standard deviations and were compared via Student’s t-test. Continuous variables with a nonnormal distribution were expressed as medians and interquartile ranges, with comparisons between two groups performed via the Mann─Whitney U test and comparisons among multiple groups via the Kruskal─Wallis test. Categorical data are summarized as frequencies and percentages, and group differences were assessed using the chi-square test. Multivariable logistic regression analysis was used to identify the factors influencing the timeline of early emergency care. All statistical analyses were performed using with SPSS 27.0 and ORIGIN 2025 software. Statistical significance was set at P < 0.05.
Results
Between January 1, 2023, and February 28, 2026, a total of 765 patients presented to our stroke center (Fig. 1). After screening, 651 patients were evaluated by stroke center physicians and enrolled in the stroke fast-track. Among them, 381 patients (58.5%) were diagnosed with AIS, all of whom met the criteria for hospital admission. The rate of adequate to medical order time (< 10 min) was 84.5% (322 of 381), and the rate of adequate to CT imaging time (< 25 min) was 46.5% (177 of 381). However, 46 patients (12.1%) refused admission, and only 243 (63.8%) were ultimately admitted via the fast-track pathway. After evaluation by neurologists, 103 patients were identified as candidates for thrombolytic therapy in patients admitted through the fast-track pathway, of whom only 64 (62.1%) consented to the treatment. Similarly, among the 51 patients who were candidates for emergency interventional therapy, only 12 (23.5%) provided consent for the procedure.
Fig. 1.
Flow of patients through the study. During a 38-month study period, 765 patients were triaged to the emergency stroke center. Among these, 651 patients presented within 24 h of symptom onset and were managed through the emergency fast-track pathway. Acute ischemic stroke was confirmed in 381 patients, among whom 243 were immediately admitted for further treatment in accordance with the fast-track pathway admission criteria
In this study, when evaluating the differences in compliance rates of medical order time and CT imaging time between groups, the type of accompanying authorized surrogate had a statistically significant impact on whether the CT imaging time met the standard for AIS patients (P = 0.023) (Table 1). Additionally, patients visiting during daytime hours and those with a disease course exceeding 4.5 h were more likely to experience delays in both medical order time and CT imaging time (P < 0.05). Furthermore, patients who were ultimately admitted via the fast tracking had higher compliance rates for medical order time and CT imaging time than those who refused admission or were admitted via common pathways (P < 0.05). Among these patients, those with AIS who ultimately refused admission were more prone to delays in both medical order and CT imaging times (Table 2). Among the 381 patients with AIS, the type of accompanying authorized surrogate showed statistically significant differences in relation to the time from disease course, CT imaging times (P < 0.05). Multivariate logistic regression analysis revealed that visit time influenced CT imaging times (P = 0.001), while the type of accompanying authorized surrogate significantly affected the CT imaging time (P = 0.023). No statistically significant differences were observed in the medical order or CT imaging times in relation to age, sex, disease course (P > 0.05). Final admission status was identified as one of the factors influencing medical order and CT imaging time (P < 0.05) (Table 2; Fig. 2). As shown in Fig. 2, indicated that the type of accompanying authorized surrogate had a significant influence on the medical order and CT imaging times in patients with AIS (P < 0.05). Patients with AIS who arrived alone exhibited longer disease course, medical order, CT imaging, and emergency treatment times than those with an accompanying authorized surrogate. The second-longest duration was observed when the spouse served as the accompanying authorized surrogate
Table 1.
Demographic characteristics of patients with AIS
| Medication Order Time (minutes) | CT Imaging Time (minutes) | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Adequate group ( n = 322) | Inadequate group ( n = 59) | P* | P** | Adequate group ( n = 177) | Inadequate group ( n = 204) | P* | P** | ||
| Sex | Male | 210(65.2%) | 37 (62.7%) | 0.408 | 115(65.0%) | 132(64.7%) | 0.957 | ||
| Age(years) | 67.509 ± 13.427 | 66.712 ± 14.606 | 0.679 | 67.090 ± 13.646 | 67.642 ± 13.586 | 0.693 | |||
| ≥ 60 | 215 (66.8%) | 36 (61.0%) | 0.238 | 108 (61.0%) | 143(70.1%) | 0.066 | |||
| Visit time | Daytime | 191(59.3%) | 43(72.9%) | 0.032 | 0.355 | 92 (52.0%) | 142(69.6%) | < 0.001 | 0.001 |
| History of diseases | Yes | 229(71.1%) | 39(66.1%) | 0.265 | 120(67.8%) | 148 (72.5%) | 0.314 | ||
| History of stroke | Yes | 52(16.1%) | 10(16.9%) | 0.503 | 25(14.1%) | 37(18.1%) | 0.331 | ||
| Disease course(hours) | 4.118 ± 5.127 | 8.316 ± 7.583 | < 0.001 | 0.115 | 3.780 ± 4.512 | 5.609 ± 6.568 | 0.002 | 0.361 | |
| ≤ 4.5 h | 228 (79.8%) | 24 (40.7%) | < 0.001 | 0.849 | 25 (14.1%) | 37(18.1%) | 0.331 | ||
| Type of surrogate | |||||||||
| Alone | 10(3.1%) | 5 (8.5%) | 7 (4.0%) | 8(3.9%) | |||||
| Spouse | 91(28.3%) | 18 (30.5%) | 0.135 | 0.777 | 36 (20.3%) | 73(35.8%) | 0.003 | 0.023 | |
| Family | 193(59.9%) | 34 (57.6%) | 114 (64.4%) | 113(55.4%) | |||||
| Others | 28 (8.7%) | 2(3.4%) | 20 (11.3%) | 10(4.9%) | |||||
| Admission situation | |||||||||
| Refused | 31 (9.6%) | 15 (25.4%) | 18(10.2%) | 28 (13.7%) | |||||
| Common pathways | 67 (20.8%) | 25 (42.4%) | < 0.001 | 0.001 | 31(17.5%) | 61(29.9%) | 0.005 | 0.591 | |
| Fast-track | 224 (69.6%) | 19 (32.2%) | 128(72.3%) | 115(56.4%) | |||||
| Medical order time (minutes) | 4.593 ± 2.183 | 15.169 ± 7.149 | - | - | 4.537 ± 3.523 | 7.701 ± 5.846 | < 0.001 | < 0.001 | |
| CT imaging time (minutes) | 25.506 ± 9.631 | 40.712 ± 20.028 | < 0.001 | < 0.001 | 18.774 ± 4.278 | 35.745 ± 12.826 | - | ||
P*: P-value from univariate analysis; P**: P-value from multivariate logistic regression analysis
Based on the admission status, patients were divided into an agreement and refusal group. The agreement group was further categorized into a fast-track and common pathways group. Patients with fast-track pathway required immediate emergency admission and were typically placed in specialized beds designated for AIS upon hospitalization. In contrast, patients with common pathways usually had to wait in the emergency department for general neurology ward beds, often remaining in the emergency department until the next day or longer
Table 2.
Demographic characteristics of patients with AIS stratified by admission status
| Admission situation | Admission situation | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Agreement (n = 335) | Refusal (n = 46) |
P | Fast-track (n = 243) |
Common pathways (n = 92) | Refusal (n = 46) |
P | |||
| Sex | Male | 218(65.1%) | 29 (63.0%) | 0.869 | 156(64.2%) | 62(67.4%) | 29(63.0%) | 0.830 | |
| Age(years) | 67.472 ± 13.295 | 66.761 ± 15.791 | 0.740 | 67.779 ± 13.679 | 66.663 ± 12.259 | 66.761 ± 15.790 | 0.121 | ||
| ≥ 60 | 220(65.7%) | 31(67.4%) | 0.870 | 161 (66.3%) | 59(64.1%) | 31(67.4%) | 0.911 | ||
| Visit time | Daytime | 203(60.6%) | 31(67.4%) | 0.422 | 152(62.6%) | 51(55.4%) | 31(67.4%) | 0.331 | |
| History of diseases | Yes | 234(69.9%) | 34 (73.9%) | 0.611 | 167(68.7%) | 67(72.8%) | 34 (73.9%) | 0.651 | |
| History of stroke | Yes | 48(14.3%) | 14(30.4%) | 0.010 | 35 (14.4%) | 13(14.1%) | 14(30.4%) | 0.021 | |
| Disease course(hours) | 4.747 ± 5.774 | 4.920 ± 5.800 | 0.849 | 3.096 ± 3.949 | 9.108 ± 7.374 | 4.920 ± 5.800 | < 0.001 | ||
| ≤ 4.5 h | 222(66.3%) | 30(65.2%) | 0.870 | 19680.7(%) | 26(28.3%) | 30(65.2%) | < 0.001 | ||
| Type of surrogate | |||||||||
| Alone | 12(3.6%) | 3(6.5%) | 8(3.3%) | 4(4.3%) | 3(6.5%) | ||||
| Spouse | 95(28.4%) | 14(30.5%) | 0.745 | 60(24.7%) | 35(38.0%) | 14(30.5%) | 0.203 | ||
| Family | 202(60.3%) | 25(54.3%) | 153(63.0%) | 49(53.3%) | 25(54.3%) | ||||
| Others | 26(7.8%) | 4(8.7%) | 22(9.1%) | 4(4.4%) | 4(8.7%) | ||||
| Medical order time (minutes) | 5.910 ± 4.675 | 8.565 ± 7.435 | < 0.001 | 4.992 ± 3.209 | 8.337 ± 6.680 | 8.565 ± 7.435 | < 0.001 | ||
| < 10 min | 291(86.9%) | 31 (67.4%) | 0.002 | 224(92.2%) | 67(72.8%) | 31 (67.4%) | < 0.001 | ||
| CT imaging time (minutes) | 27.534 ± 13.025 | 30.239 ± 13.004 | 0.187 | 25.415 ± 9.618 | 33.130 ± 18.250 | 30.239 ± 13.004 | < 0.001 | ||
| < 25 min | 159(47.5%) | 18(39.1%) | 0.288 | 128(52.7%) | 31(33.7%) | 18(39.1%) | 0.005 | ||
Based on the admission status, patients were divided into an agreement and refusal group. The agreement group was further categorized into a fast-track and common pathways group. Patients with fast-track pathway required immediate emergency admission and were typically placed in specialized beds designated for AIS upon hospitalization. In contrast, patients with common pathways usually had to wait in the emergency department for general neurology ward beds, often remaining in the emergency department until the next day or longer
Fig. 2.
Distribution of patients with AIS stratified by surrogate decision-maker type and admission status at key time points. Panels A shows the distribution of medical order time among patients with AIS, stratified by disease course and types of accompanying authorized surrogate. Panels B shows the distribution of CT imaging time in the same patient population, categorized by disease course and types of accompanying authorized surrogate. Panels C shows the distribution of disease course based on different medical order time and types of accompanying authorized surrogate. Panels D shows the distribution of CT imaging time according to medical order time and types of accompanying authorized surrogate. Panels E shows the distribution of disease courses stratified by CT imaging time and types of accompanying authorized surrogate. Panels F shows the distribution of medical order time categorized by CT imaging time and types of accompanying authorized surrogate. Panels (G) presents the distribution of medical order time for patients with AIS categorized by admission status and types of accompanying authorized surrogate. Panels (H) depicts the distribution of CT imaging time in patients with AIS grouped according to admission status and types of accompanying authorized surrogate
In a further study investigating the impact of the type of accompanying authorized surrogates on the early emergency treatment timeline and prognosis of patients (243 cases), an analysis of demographic characteristics revealed that age was a significant factor influencing the type of accompanying authorized surrogates (P < 0.001) (Table 3). A statistically significant difference was also observed between disease course and the type of accompanying authorized surrogates (P < 0.05). The disease course for patients with AIS who arrived alone was significantly longer than that for patients accompanied by someone, often exceeding 8 h. When a colleague or friend served as the accompanying authorized surrogates, the patient’s disease course was the shortest.
Table 3.
Demographic characteristics and outcomes among different accompanying authorized surrogate groups for patients with AIS admitted via the fast-track
| Alone (n = 8) |
Spouse (n = 60) |
Family (n = 153) |
Others (n = 22) |
P | |
|---|---|---|---|---|---|
| Sex | |||||
| Male | 7(87.5%) | 39(65.0%) | 94(61.4%) | 16(72.7%) | 0.375 |
| Age | 46.125 ± 16.898 | 62.250 ± 10.008 | 73.229 ± 10.008 | 52.818 ± 15.111 | < 0.001 |
| ≥ 60 | 3(37.5%) | 27(45.0%) | 125(81.7%) | 6(27.3%) | < 0.001 |
| Visit time | |||||
| Daytime | 7(87.5%) | 40(66.7%) | 92(60.1%) | 13(59.1%) | 0.383 |
| Disease history | |||||
| Yes | 5(62.5%) | 43(71.7%) | 109(71.2%) | 12(45.5%) | 0.095 |
| Stroke history | |||||
| Yes | 1(12.5%) | 9(15.0%) | 23(15.0%) | 2(9.1%) | 0.898 |
| Disease course(h) | 8.063 ± 7.504 | 2.767 ± 3.663 | 3.043 ± 3.813 | 2.554 ± 2,825 | 0.003 |
| ≤ 4.5 h | 3(37.5%) | 51(85.0%) | 124(81.0%) | 18(81.8%) | 0.016 |
| Medical order time(minutes) | 7.000 ± 3.545 | 4.900 ± 2.995 | 5.000 ± 3.334 | 4.455 ± 2.632 | 0.285 |
| CT imaging time(minutes) | 30.375 ± 10.501 | 28.850 ± 10.856 | 24.242 ± 8.994 | 23.727 ± 7.796 | 0.005 |
| Thrombolysis time(minutes) | - | 67.692 ± 22.581 | 57.255 ± 19.471 | 55.000 ± 8.831 | 0.227 |
| Interventional times(minutes) | - | 94.333 ± 16.166 | 91.500 ± 24.395 | 96.667 ± 5.686 | 0.932 |
| Emergency care time(minutes) | 89.250 ± 30.023 | 75.567 ± 27.409 | 75.235 ± 39.143 | 72.136 ± 26.396 | 0.701 |
| Hospital stay(days) | 7.750 ± 4.334 | 11.117 ± 8.618 | 12.412 ± 9.758 | 12.818 ± 9.277 | 0.448 |
| Adverse events | |||||
| Hemorrhagic transformation | 0(0%) | 2(3.3%) | 3(2%) | 0(0%) | 0.772 |
| Endotracheal intubation | 0(0%) | 5(8.3%) | 5(3.3%) | 1(4.5%) | 0.399 |
| ICU admission | 0(0%) | 6(10.0%) | 6(3.9%) | 3(13.6%) | 0.139 |
| Death | 0(0%) | 6(10.0%) | 7(4.6%) | 1(4.5%) | 0.402 |
| Overall incidence | 0(0%) | 8(13.3%) | 12(7.8%) | 2(9.1%) | 0.493 |
| NIHSS score | |||||
| Initial NIHSS score | 2.750 ± 2.712 | 5.650 ± 6.073 | 7.072 ± 6.419 | 8.864 ± 8.305 | 0.058 |
| NIHSS score at discharge | 1.125 ± 1.356 | 7.000 ± 12.305 | 5.386 ± 9.237 | 6.682 ± 9.978 | 0.389 |
| ΔNIHSS | 1.625 ± 2.200 | -1.300 ± 8.677 | 1.745 ± 6.761 | 2.181 ± 6.013 | 0.038 |
| Increase cases | 0(0%) | 10(16.7%) | 13(8.5%) | 1(4.5%) | 0.171 |
| Neurological outcome | |||||
| CPC score | 1.250 ± 0.462 | 2.100 ± 1.272 | 1.955 ± 1.133 | 1.958 ± 1.138 | 0.448 |
| Favorable neurological outcome | 8(100%) | 36(60.0%) | 109(71.2%) | 14(63.6%) | 0.090 |
ΔNIHSS score was defined as the difference between the NIHSS score at admission to the stroke center and the NIHSS score at discharge
This study found that the type of accompanying authorized surrogates was associated with significant differences in the CT imaging time in patients with AIS (P < 0.05) (Tables 1 and 3). Alone or spouse accompaniment, as opposed to accompaniment by other individuals, was associated with significantly longer CT imaging times in patients with AIS. Furthermore, patients who presented alone had the longest times for medical orders, CT imaging, and emergency treatment times. In contrast, when others served as the accompanying authorized surrogates, the patient’s medical order, CT imaging, and emergency treatment times were the shortest. This study revealed no statistically significant differences in the length of hospital stay, neurological outcomes, NIHSS score, or incidence of adverse events between the groups based on the type of accompanying authorized surrogates (P > 0.05). However, ΔNIHSS scores showed significant differences among patients with different types of accompanying authorized surrogates (P = 0.038). When the spouse served as the accompanying authorized surrogate for patients with AIS, there was an increased risk of short-term deterioration. In addition, this study found that patients who sought medical care alone had the shortest length of hospital stay, the lowest incidence of adverse events, and the best neurofunctional outcomes.
For patients with AIS, both thrombolysis and endovascular intervention were conducted only when an accompanying authorized surrogate was present (Tables 3 and 4). Further analysis revealed that spousal accompaniment resulted in the longest treatment times. When the spouse served as the accompanying authorized surrogate, the times to thrombolysis was the longest (67 min). Significant differences were observed in both medical order and CT imaging times between patients with AIS who ultimately received thrombolytic therapy and those who did not (P = 0.003 vs. P = 0.011). Similarly, significant differences were found in both medical order and CT imaging times between patients who underwent endovascular intervention and those who refused the procedure (P = 0.019 vs. P = 0.050). Initial NIHSS scores were significantly higher in AIS patients who agreed to thrombolysis and endovascular intervention than in those who refused these procedures (9.891 vs. 6.051, 16.667 vs. 8,769, respectively, P < 0.05). However, no significant differences were observed in the NIHSS score at discharge or in the ΔNIHSS score.
Table 4.
Demographic characteristics of patients with AIS via the fast-track pathways and treated with thrombolysis or endovascular intervention
| Thrombolysis | Endovascular Intervention | ||||||
|---|---|---|---|---|---|---|---|
| Agreement (n = 64) | Refusal (n = 39) | P | Agreement (n = 12) | Refusal (n = 39) | P | ||
| Sex | Male | 36(56.3%) | 22(56.4%) | 0.987 | 8(66.7%) | 19(48.7%) | 0.335 |
| Age(years) | 69.676 ± 12.710 | 68.308 ± 14.606 | 0.615 | 64.333 ± 18.357 | 68.513 ± 14.931 | 0.426 | |
| ≥ 60 | 44(68.8%) | 24(61.5%) | 0.522 | 9(75.0%) | 24(61.5%) | 0.502 | |
| Visit time | Daytime | 34(53.1%) | 27(69.2%) | 0.148 | 9(75.0%) | 25(64.1%) | 0.728 |
| History of diseases | Yes | 42(65.6%) | 26(66.7%) | 0.914 | 5(41.7%) | 28(71.8%) | 0.056 |
| History of stroke | Yes | 8(12.5%) | 7(17.9%) | 0.447 | 1(8.3%) | 7(17.9%) | 0.662 |
| Disease course(hours) | 1.424 ± 0.824 | 1.835 ± 2.080 | 0.160 | 2.778 ± 3.517 | 2.270 ± 2.104 | 0.540 | |
| ≤ 4.5 h | 63(98.4%) | 38(97.4%) | 0.721 | 9(75.0%) | 38(97.4%) | 0.036 | |
| Type of surrogate | |||||||
| Alone | 0(0%) | 0(0%) | 0(0%) | 0(0%) | |||
| Spouse | 13(20.3%) | 11(28.2%) | 0.274 | 3(25.0%) | 10(25.6%) | ||
| Family | 47(73.4%) | 23(59.0%) | 6(50.0%) | 23(59.0%) | 0.727 | ||
| Others | 4(6.3%) | 5(12.8%) | 3(25.0%) | 5(12.8%) | |||
| Medical order time | 3.908 ± 2.301 | 5.872 ± 4.118 | 0.003 | 3.167 ± 1.030 | 5.385 ± 3.083 | 0.019 | |
| < 10 min | 63(98.4%) | 33(84.6%) | 0.011 | 12(100%) | 34(87.2%) | 0.192 | |
| CT imaging time | 22.594 ± 9.729 | 28.000 ± 10.964 | 0.011 | 20.833 ± 7.259 | 25.576 ± 7.232 | 0.050 | |
| < 25 min | 40(62.5%) | 19(48.7%) | 0.219 | 11(91.7%) | 21(53.8%) | 0.020 | |
| Emergency care time | 56.468 ± 19.520 | 74.436 ± 22.686 | < 0.001 | 69.000 ± 19.799 | 76.256 ± 31.626 | 0.458 | |
| Hospital stay(days) | 13.281 ± 10.767 | 12.949 ± 9.032 | 0.872 | 15.417 ± 12.109 | 13.307 ± 8.624 | 0.505 | |
| Overall adverse events | 11(17.2%) | 4(10.3%) | 0.400 | 2(16.7%) | 6(15.4%) | 0.915 | |
| NIHSS score | |||||||
| Initial NIHSS score | 9.891 ± 6.986 | 6.051 ± 6.022 | 0.005 | 16.667 ± 6.035 | 8.769 ± 6.807 | < 0.001 | |
| NIHSS score at discharge | 9.203 ± 13.621 | 4.744 ± 7.830 | 0.065 | 11.500 ± 14.878 | 9.128 ± 10.887 | 0.549 | |
| ΔNIHSS | 0.781 ± 10.854 | 1.308 ± 6.416 | 0.784 | 5.167 ± 13.630 | -0.308 ± 7.561 | 0.080 | |
| Increase cases | 13(20.3%) | 2(5.1%) | 0.044 | 2(16.7%) | 7(17.9%) | 0.919 | |
| Neurological outcome | |||||||
| CPC score | 2.297 ± 1.387 | 1.846 ± 1.065 | 0.085 | 2.500 ± 1.446 | 2.539 ± 1.120 | 0.923 | |
| Favorable neurological outcome | 38(59.4%) | 27(69.2%) | 0.401 | 6(50.0%) | 15(38.5%) | 0.478 | |
Finally, based on the aforementioned impact of the type of accompanying authorized surrogates on the patient’s early treatment timeline, we analyzed the interrelationships among these timeline factors (Fig. 3). This study revealed a linear correlation between disease course and CT imaging, medical order, and emergency treatment times. In conclusion, medical order time was weakly correlated with CT imaging, emergency treatment, and thrombolysis times. In contrast, CT imaging time demonstrated a significant positive correlation with both thrombolysis and emergency treatment times.
Fig. 3.
Modeling of key early time intervals in patients with AIS, Correlation analysis among disease course, medical order, CT imaging, emergency treatment, and thrombolysis times in 243 patients with AIS. Panels (A) revealed no significant correlation between disease course and either medical order or CT imaging times; however, a positive correlation was observed between disease course and emergency treatment time within a certain range. Panels (B) demonstrated a positive correlation between medical order time and both CT imaging and emergency treatment times. Panels (C) showed a positive correlation between CT imaging time and emergency treatment time. Panels (D) indicated that, among the 64 patients who received thrombolysis, there was no significant correlation between medical order and CT imaging, thrombolysis, and emergency treatment times. Panels (E) revealed a positive correlation between CT imaging time and both thrombolysis and emergency treatment times in the 64 patients who underwent thrombolysis
Discussion
This study achieved the ideal results, signifying its innovative value. This study revealed that early in-hospital delay in patients with AIS is multifactorial and that the type of authorized surrogate present upon patient arrival influences the disease course, medical order, CT imaging, thrombolysis therapy, interventional therapy, and emergency treatment times. The absence of a surrogate or a spouse acting as a surrogate has a considerable impact on in-hospital emergency timelines, resulting in prolonged treatment delays. Furthermore, the analysis of early prognostic indicators revealed that patients with AIS who presented to the hospital unaccompanied exhibited the shortest length of hospital stay, the lowest incidence of adverse events, the lowest NIHSS scores on admission and at discharge, the greatest improvement in NIHSS scores, and the most favorable neurological outcomes.
Our investigation identified a delay in CT imaging as a significant contributor to overall in-hospital delay, with the CT imaging time of less than 25 min achieved in only 46.5%. Furthermore, this delay was positively correlated with both the thrombolysis and emergency treatment times. Consistent with the literature, delayed neuroimaging was a major contributor to in-hospital delays [23]. We speculate that this may be partly attributable to the healthcare resource allocation. During daytime hours, radiology departments are responsible for performing CT scans not only for emergency cases, but also for outpatients and inpatients. Only a minority of hospitals are equipped with CT scanners dedicated solely to emergency use. To address this challenge, stroke centers have established fast-track protocols aimed at minimizing the CT imaging time for patients with stroke [18–20]. However, this issue has not been fully resolved. In most hospitals, optimizing strategies to further shorten the CT imaging time for patients with stroke presenting during the day remains a priority. Shortening the CT imaging time is crucial, as it provides the necessary time window for thorough discussion with the patients and their surrogates regarding the risks and benefits of thrombolysis or interventional therapy [24].
Importantly, the CT imaging time is not solely determined by the healthcare system. Patients and their surrogates often have concerns regarding the radiation exposure associated with CT [25], and face decisions about whether to undergo non-contrast CT, CTA/CTP, or MRI, as well as considering the affordability of advanced imaging, such as CTA/CTP. Current clinical protocols require obtaining and documenting informed consent for contrast-enhanced CT or MRI, which can inherently extend the CT imaging time. Healthcare providers should be mindful of the significant correlation between educational level and risk comprehension, and tailor their communication accordingly [26]. Although digitized informed patient consent is feasible, patient age is a relevant factor [27]. Current guidelines suggest that in cases of patient indecision, directly recommending the completion of a routine non-contrast CT scan first may be beneficial [28].
The patient-side informed consent process for thrombolysis and interventional therapy substantially influence treatment decisions. Patients and their surrogates have the absolute right to consent or refuse, with surrogate decision-making playing a dominant role in these time-sensitive interventions [29–31]. Studies have indicated that the patient preference for thrombolysis increases with stroke severity [32, 33]. These observations are in line with the results from the current investigation, further supporting our conclusions. Obtaining more reasonable and standardized informed consent within a limited time window remains a persistent challenge in stroke care [34]. The decision-making model in China differs from the Western shared decision-making model. In China, although informed consent is mandated by law and regulations, family members typically dominate the process, raising concerns regarding its true nature [35]. Communication upon patient arrival must cover the medical history, examinations, treatment options, plans, and costs, with all procedures requiring informed consent. As most patients with stroke have cognitive impairment, consent must often be obtained from their close relatives [36, 37]. Even when patients retain decision-making capacity, advanced age (of both the patients and their spouses) often necessitates prolonged communication to obtain history, consent for examinations, and agreement to cover costs [38]. Frequently, elder adult patients require consultation with their adult children before making decisions. For patients with AIS, seeking multiparty consent before treatment appears to challenge the principle of “early treatment within the limited time window.” These factors contribute to prolonged doctor-patient communication and treatment delays, explaining our finding that treatment timelines were significantly longer when patients had no surrogate or when the spouse was the surrogate.
This study also revealed that patients who refused thrombolysis or interventional therapy had longer medical orders, CT imaging, and emergency treatment times, which are consistent with the findings of several previous studies [39]. Although studies have suggested that the decision to perform thrombolysis is influenced by physician assessment and communication [40, 41], healthcare systems in our context have already implemented multiple measures to minimize pre-hospital and in-hospital delays. In this study, all stroke center physicians were experienced emergency physicians with years or decades of experience, and assessments for thrombolysis and intervention were conducted by specialized neurologists (at least two, including one senior physician with substantial procedural experience). This structure has largely mitigated the negative impacts of healthcare providers on treatment timelines. Therefore, we reasonably conclude that the timeliness of decision-making by patients and their authorized surrogates in an AIS setting is a primary contributor to delays in emergency treatment.
This study revealed the longest disease course in patients who presented alone, and the shortest disease course in those accompanied by colleagues or friends. The latter group also demonstrated significant advantages in terms of medical order, CT imaging, and emergency treatment times. This may be related to the environment in which the symptoms occurred. For example, when the onset occurs in the workplace, patients typically seek help and medical care promptly to avoid negative impacts, and their subsequent treatment courses are generally proactive. Furthermore, patients accompanied by colleagues or friends are often younger and exhibit more positive attitudes toward treatment. In contrast, patients who are alone during onset experience longer delays due to objective factors (e.g., age, sex, regional economic status) and subjective factors (e.g., stroke awareness) [42]. Patients without surrogates may have difficulty in providing clear histories, complicating physician assessment and potentially requiring repeated verification or contact with witnesses or caregivers before making treatment decisions. When obtaining consent, if patients cannot decide or have difficulty understanding it, complex assessments, such as seeking police assistance to contact family members, may be needed, further prolonging the process.
Moreover, this study revealed that patients with AIS who presented to the hospital unaccompanied exhibited the shortest length of hospital stay, the lowest incidence of adverse events, the lowest NIHSS scores on admission and at discharge, the greatest improvement in NIHSS scores, and the most favorable neurological outcomes. Meanwhile, ΔNIHSS scores showed significant differences among patients with different types of accompanying authorized surrogates. However, several other prognostic indicators failed to show significant differences between the groups. Although not reaching the conventional threshold for statistical significance, certain indicators demonstrated a trend toward significance (P < 0.1). This outcome may be partially attributed to the modest sample size within the subgroups, which could have predisposed the results to bias. It is also plausible that the early prognostic indicators utilized were insufficient to comprehensively assess the full spectrum of patient recovery. Finally, the absence of a statistically significant impact of patient-authorized surrogates on AIS prognosis may be attributed to the lack of time-critical emergencies after admission. This allowed sufficient time for shared decision-making among the patients and their family members. Future investigations designed with adequately powered subgroup samples and prolonged prognostic assessment windows, such as 3- month and 6-month follow-ups, are essential to potentially delineate intergroup disparities.
Therefore, expediting the informed consent process is critical to reduce in-hospital emergency times. In general, involving both patients and surrogates in medical decisions, including discussing treatment risks and benefits, and visually communicating the advantages and risks of stroke thrombolysis, is recommended to optimize surrogate decision-making [43–45]. Communication strategies should be tailored to divers populations with stroke, considering racial, ethnic, socioeconomic, and cultural differences [46]. For older adult individuals with limited literacy or writing ability, digital informed consent may reduce door-to-needle time [47]. Furthermore, some studies have suggested that replacing written consent with verbal consent significantly improves thrombolysis timeliness in patients with AIS [48]. However, no single measure has completely resolved this issue.
The novelty of this study lies in its pioneering investigation of how accompanying authorized surrogates influence the early emergency care timeline and outcomes in AIS, yielding positive results. However, this study had a few limitations. First, it was a single-center retrospective analysis. Second, it did not involve on-site investigations or assessments of the complexity and specific reasons behind patient-side decision-making. Additionally, the prognostic outcomes of patients who declined hospital admission were not assessed. The modest sample sizes within subgroups may have also compromised the statistical power to detect potential differences. In response to these methodological constraints, we are currently conducting a prospective investigation with a more rigorous and detailed protocol. This ongoing study aims to inform and refine clinical practice and the informed consent framework for AIS, with the objective of minimizing emergency treatment delays and enhancing the quality of patient care.
Conclusion
Early in-hospital delays in patients with AIS are multifactorial, CT imaging delay remained one of the contributing factors to in-hospital delay. The type of accompanying authorized surrogates significantly influenced both the pre-hospital and in-hospital emergency timelines. The patients with AIS who presented to the hospital unaccompanied exhibited the shortest length of hospital stay, the lowest incidence of adverse events, the lowest NIHSS scores on admission and at discharge, the greatest improvement in NIHSS scores, and the most favorable neurological outcomes. ΔNIHSS scores showed significant differences among patients with different types of accompanying authorized surrogates. In conclusion, the accompanying authorized surrogate plays a crucial role throughout the entire treatment process for patients with AIS. These findings can be used to prioritize strategies for promptly activating informed consent contingency protocols in patients with AIS, thereby shortening the consent process and enabling earlier treatment initiation within a critical therapeutic time window.
Acknowledgements
All authors have fulfilled the authorship criteria and have approved the final manuscript. We thank all of them for their assistance and guidance.
Author contributions
Haoyu Wang and Yarong researched the literature and conceived the study. They were involved in the protocol development, ethical approval, patient recruitment and data analysis. Wei Ni was involved in patient recruitment. Haoyu Wang wrote the first draft of the manuscript. All authors reviewed and edited the manuscript and approved the final version.
Funding
This study was supported by the Foundation of Noncommunicable Chronic Diseases-National Science and Technology Major Project (Grant No. 2024ZD0527700 and 2024ZD0527701) and Science and Technology Department of Sichuan Province (Grant No. 2023NSFSC1472).
Data availability
Further inquiries can be directed to the corresponding authors.
Declarations
Ethical approval
The study was carried out in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki) and approved by the Ethics Committee on Biomedical Research, West China Hospital of Sichuan University approval number/ID (2000) of Oct.13, 2025.
Informed consent
This study was a retrospective observation and did not require informed consent from the patients.
Confirmation statement
The study was conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki) and approved by the Ethics Committee on Biomedical Research, West China Hospital of Sichuan University (approval number/ID (2000) of 2025 Oct. 13, 2025). Given the retrospective, observational nature of this study, which involved the analysis of de-identified data from medical records, the requirement for written informed consent from participants was waived. All patient data were anonymized prior to analysis to protect patient confidentiality and privacy.
Generative AI declaration statement
The authors did not use a generative artificial intelligence (AI) tool or service to assist in the preparation or editing of this study. The author(s) take full responsibility for the contents of this manuscript.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Haifang Yu, Email: yuhaifang@wchscu.cn.
Yarong He, Email: heyarong@gmail.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Citations
- William J, Powers AA, Rabinstein T, Ackerson, et al. Guidelines for the early management of patients with acute ischemic stroke: 2019 Update to the 2018 Guidelines for the early management of acute ischemic stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke. Association. Stroke. 2019;50(12):e344–418. 10.1161/STR.0000000000000211. [DOI] [PubMed]
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Data Availability Statement
Further inquiries can be directed to the corresponding authors.