Title: Association of Off‐Hour Admission With Treatment Delay and Unfavorable Outcomes in Patients With Stroke: A Systematic Review and Meta‐Analysis
Subject: JAHA 2026.15:e043006

Lou et al	Off- Hour Stroke Admission, Treatment, and Prognosis

Journal of the American Heart Association
ORIGINAL RESEARCH
Association of Off- Hour Admission
With Treatment Delay and Unfavorable
Outcomes in Patients With Stroke:
A Systematic Review and Meta- Analysis
Yiling Lou, PhD; Shiqi Wang, MS*; Hengchang Wang, MPH; Yulin Xie, MPH; Yan Guo , MS;

Y. Lou and S. Wang contributed equally as co- first authors.
This manuscript was sent to Jose R. Romero, MD, Associate Editor, for review by expert referees, editorial decision, and final disposition.
Supplemental Material is available at https://www. ahajo urnals. org/doi/suppl/ 10. 1161/JAHA. 125. 043006
For Sources of Funding and Disclosures, see page 12 and 13.
© 2026 The Author(s). Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
JAHA is available at: www.ahajournals.org/journal/jaha

Linlin Wang , MS; Rongxia Zhong, MPH; Zuxun Lu, PhD; Fujian Song , PhD; Furong Wang , PhD;
Qingqing Jiang, PhD; Shiyi Cao , PhD
BACKGROUND: Despite numerous efforts to reduce the elevated mortality rate of patients with stroke admitted to the hospital during weekends or nights, it remains unclear whether the off- hour treatment has been improved. We aim to assess the treatment delay and outcomes of patients with stroke admitted to the hospital during off- hours.
METHODS: Searches were conducted of PubMed, Embase, Medline, and Web of Science from inception to July 2022. Cohort studies reporting the door- to- treatment time, short- term mortality rate, and 90- day function of adult patients with stroke admitted to the hospital on weekends or at night were included. A random- effect meta- analysis model was applied to pool the odds ratio (OR) and mean difference with 95% CI.

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RESULTS: A total of 84 studies were included. Treatment delay on weekends or nights was significant, with extended door-to- needle time (mean difference, 5.93 [95% CI, 1.88–9.98] minutes) and door-to- groin time (mean difference, 13.54 [95% CI, 5.02–22.06] minutes). Off- hour patients were less likely to receive intravenous thrombolysis within 60 minutes (OR, 0.65 [95% CI, 0.46–0.92]). Off- hour admission was associated with an increased short-term mortality rate for patients with ischemic stroke (OR, 1.07 [95% CI, 1.03–1.11]), intracerebral hemorrhage (OR, 1.10 [95% CI, 1.03–1.18]), and subarachnoid hemorrhage (OR, 1.05 [95% CI, 1.02–1.09]).
CONCLUSIONS: This review indicates that off- hour admission was associated with treatment delay and increased risk of stroke death. Patients with stroke admitted on weekends and nights may require more attention, especially those with more severe and complex conditions.
Key Words: after- hours care ■ meta- analysis ■ death ■ stroke

Stroke remains the second-l eading cause of death worldwide and the third-l eading cause of disability in adults. According to the Global Burden
Study 2019, there were 12.2 million incident cases, 101 million prevalent cases, and 6.55 million deaths

from stroke.^1 Previous studies have reported increased risks of unfavorable outcomes and short- term mortality rate in patients with stroke admitted during off- hours (weekends, nights, or public holidays), which is called the “weekend effect.”^2–6 Due to the high morbidity and
Correspondence to: Qingqing Jiang, PhD, School of Nursing, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, China. Email: 15084450940@163.com and Shiyi Cao, PhD, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, China. Email: caoshiyi@hust.edu.cn

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CLINICAL PERSPECTIVE
What Is New?
•		The off- hour admission was associated with higher risk of treatment delay and increased short- term mortality rate of stroke.
•		A decreasing trend by year of the short- term mortality risk of patients with ischemic stroke was observed.
What Are the Clinical Implications?
•		The “weekend effect” may indeed be present, highlighting the targeted optimization of treatment and care strategies for patients with stroke admitted during off- hours may be needed to further reduce treatment delay and stroke mortality risk.
Nonstandard Abbreviations and Acronyms
ICH	intracerebral hemorrhage
IS	ischemic stroke
mRS	modified Rankin Scale
NIHSS	National Institute of Health Stroke Scale
SAH	subarachnoid hemorrhage mortality rate of stroke, even the modest increases in the risk of death and disability from the weekend effect may pose an enormous global health challenge.
However, controversial results on the weekend effect have been reported in studies from different regions over the years. Cohorts from the Canada Stroke Network found that patients with stroke admitted on weekends had higher mortality risk than those admitted on weekdays (odds ratio [OR], 1.12 [95% CI, 1.00–1.25]), while cohorts from a multicenter stroke registry in Korea indicated that weekend admission was not significantly associated with a higher stroke mortality rate (OR, 1.09 [95% CI, 0.77–1.54]).^7,8 A systematic review and metaanalysis pooled studies on off- hour presentation and outcomes of patients with ischemic stroke (IS) published before August 2013 and reported that patients with IS admitted during off- hours were associated with a significantly higher short-term mortality rate and higher modified Rankin Scale (mRS) score at discharge.^9 However, the meta- analysis did not assess the treatment delay of off- hour patients, and it was possible that the weekend effect was due to the potential cofounding factors such as stroke severity at admission. Patients presented to the hospital on weekends or at night might have more severe disease or longer prehospital delay, compared with those admitted during regular hours on weekdays. After adjusting for stroke severity, some studies found that there was no significant difference in mortality rates between patients admitted during off- hours and patients admitted during regular hours.^10–12
With the spread of stroke centers and telemedicine in recent years, stroke treatment has been improved, and off- hour patients with stroke may have received more attention. A large number of new studies on the weekend effect have been published, which has generated widespread interest in reassessing the present out- of- hours care of patients with stroke comprehensively. This systematic review aimed to synthesize the available studies on the weekend effect in patients with ischemic and hemorrhagic stroke and to assess stroke severity and other factors associated with the treatment delay and unfavorable outcomes due to off- hour admissions.
METHODS
Data Availability
This study adheres to the Journal of the American Heart Association’s (JAHA) implementation of the Transparency and Openness Promotion Guidelines. This systematic review was conducted according to the Meta- Analysis of Observational Studies in Epidemiology guidelines and the Preferred Reporting Items for Systematic Reviews and Meta- Analyses 2020 guidelines.^13,14 The protocol of this study was registered on the International Prospective Register of Systematic Reviews (CRD42022356134). All analyses were based on data from previously published literature, so no approval from the institutional review board was required. The data used in this study are available upon request by contacting the corresponding author.
Search Strategies
We searched PubMed, Embase, Medline, and Web of Science through July 18, 2022, for relevant studies published in English, using subject heading and keywords related to weekend effect of patients with stroke. The search strategy is available in Data S1. We also manually scanned references of all included articles for relevant studies.
Study Selection
We included studies that met the following criteria:
1.		The study population was adult patients with IS, intracerebral hemorrhage (ICH), or subarachnoid hemorrhage (SAH).
2.		The comparison was between patients admitted during off- hours (weekends, nights, or public holidays) and those admitted during regular working hours.
3.		Outcomes included short- term mortality rate (inhospital, 7- day, or 30- day), 90- day mRS score, and

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the door-to- needle time for intravenous thrombolysis or door- to- groin time for endovascular treatment of patients with IS.
4.		Studies provided statistic metrics of OR, risk ratio, and hazard ratio (HR) with 95% CI, or offered sufficient data to calculate the effects.
5.		The study design was cohort. Letters, reviews, commentaries, meeting abstracts, and editorials were excluded. Two researchers independently performed initial screening of titles and abstracts of the search records and excluded clearly ineligible studies.
We then conducted full text screening to assess the eligibility of possibly relevant studies and those with discrepant decisions in the title/abstract screening. The full- text screening for eligibility was conducted by 2 independent reviewers, and any discrepancies were resolved through consensus.
Data Extraction
Two researchers independently extracted the following data from included studies: name of first author, publication year, country, cohort years, data source, type of off- hours, sample size, definition of outcomes, effect size, and adjustment of covariate.
Quality Appraisal
Two researchers independently assessed the quality of all included studies using the Newcastle–Ottawa Scale for cohort studies.^15 The scale consists of 9 points (4 for cohort selection, 2 for comparability, and 3 for outcome) to evaluate the risk of bias in observational studies. The quality of studies with a total score of 0 to 3, 4 to 6, and 7 to 9 was considered, respectively, to be low, moderate, and high.
Outcomes
For patients with IS, the door- to- needle time and door- to- groin time were used to evaluate the treatment delay. We also analyzed the proportion of patients with IS who received intravenous thrombolysis within 60 minutes after admission. In- hospital death was used to represent the short- term mortality rate of all patients with subtypes of stroke because it was the most commonly reported death. If a study did not report the inhospital mortality rate, the 7- day or 30- day mortality rate would be used instead. The function status was classified through the mRS score at 90 days after admission. Patients with an mRS score <3 were regarded to have a favorable function, and those with an mRS score ≥3 had unfavorable function. If a study reported outcomes drawn on the same set of participants from different time points, we restricted the time of study inclusion to the first time point to ensure the independence of study effects. Meanwhile, for the varied sets of participants (eg, distinct stroke subtypes, off- hour types, or regions) that may affect the effect estimates, we extracted and included the outcomes separately in the meta-analyses and subsequent subgroup analyses and meta- regressions.
Statistical Analysis
For the door-to- needle time and door-to- groin time, we estimated mean difference and its 95% CI, measured by minutes. If a study reported the median and quartile, we used the metacont function of the meta package to assess the differences of medians. This function is based on the assumption of symmetric distribution of data and can convert the median (interquartile range) to the mean±SD (mean≈median, SD≈interquartile range/1.35) for subsequent effect pooling, although it may have limitations such as reliance on distribution assumptions, poor sensitivity to correlation coefficients (fixed interquartile range to SD coefficients), and inability to capture extreme skewness. For mortality and proportion outcomes, we preferentially extracted or calculated adjusted OR and its 95% CI for each study to estimate the effect size more accurately. When the adjusted effect size from the covariate- adjusted model was unavailable, we used the unadjusted estimate. If a study reported HR, we considered it approximate to OR and tested the assumption in sensitive analyses by excluding the study’s reported HR rather than OR.^16 Considering the potential heterogeneity and exchangeability assumptions of the included studies,^17,18 we used random- effect meta- analysis to pool results of multiple studies.^19 Taking into account the influence of some confounding factors in previous relevant literature and the data information of the included studies,^20,21 subgroup analyses and meta- regression analyses were conducted by the areas of cohorts, off- hour types, data sources (administrative data or clinical registry), stroke centers (yes or no), cohort years, and adjustments of previous stroke and stroke severity (yes or no). Cohorts from comprehensive stroke centers, primary stroke centers, and stroke units were all classified as stroke center cohorts. To assess the time trend of short- term mortality rate across studies, we also conducted meta- regression by the midyear of each cohort. We used the I^2 statistics to estimate the percentage of total variation across studies that was due to heterogeneity rather than sampling error (from 0% to 100%).^22 The Q statistics, τ statistics, and 95% prediction intervals were used to evaluate the heterogeneity. τ was the estimated value of the between- study SD in true study ef- fects,^23 which could be used to calculate the maximum expected difference in effect values (2τ) between any pair of studies within the analysis. The prediction interval was used to measure the range of expected effect sizes in future research. To assess the potential publication bias, we examined the asymmetry of the funnel plot and used contour- enhanced funnel plots analyses and Egger’s

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Figure 1. Flowchart for selection of eligible studies.

test.^24,25 For outcome with evidence of asymmetry, the trim- and-f ill method was used to assess the impact of potential publication bias on pooled results. Sensitivity analysis was conducted by omitting individual studies one at a time, combining the effect sizes of a study if it included >1 outcome measure before pooling the effect sizes from different studies and pooling the effect sizes of each study by performing fixed- effects analysis. We used R version 4.2.1 (R Foundation for Statistical Computing, Vienna, Austria) and Comprehensive Meta-Analysis version 4.0 (Biostat Software Development, Englewood, NJ) for statistical analyses. All P values were 2- tailed, and P<0.05 was set as statistically significant.
Certainty Assessment
The Grading of Recommendations Assessment, Development, and Evaluation method was used to assess the certainty of the evidence for each pooled analysis with 8 criteria.^26,27 Among them, 5 were downgrading criteria, including risk of bias, inconsistency, indirectness, imprecision, and publication bias; and 3 were upgrading criteria, including significant effect size without reasonable confounding factors, dose–response relationship, and all reasonable residual confounding factors. After assessment with the Grading of Recommendations Assessment, Development, and Evaluation method, evidence credibility could be divided into 4 categories: very low, low, medium, and high. Because of the observational nature of the included studies, the credibility of the evidence was initially low and could be further evaluated according to upgraded or downgraded criteria. In addition, the 2 researchers who evaluated the quality of the included studies also independently assessed the credibility of the evidence.
RESULTS
Identification and Description of Studies From 4981 records, we identified 84 cohort studies that met the inclusion criteria, including 3 880 969

Figure 2. Door- to-treatment time of patients with ischemic stroke.
A, The mean difference of door- to- needle time (minutes) between patients with ischemic stroke admitted during off- hours and regular hours. B, The mean difference of door- to- groin time (minutes) between patients with ischemic stroke admitted during off- hours and regular hours. C, The odds ratio of intravenous thrombolysis within 60 minutes after admission between patients with ischemic stroke admitted during off- hours and regular hours.

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participants. The searching process is shown in Figure 1, and the characteristics of all included studies are listed in Table S1. The publication year ranged from 2004 to 2022, and the earliest cohort started in 1985. Although the subtypes of stroke were not distinguished in 15 studies, patients with IS, ICH, and SAH were included, respectively, in 58, 15, and 7 studies. Twenty studies reported the door- to- needle time and door- to- groin time, 64 studies reported the short- term mortality rate, and 23 studies reported the 90- day functional status. The studies were from multiple countries and regions, including 28 from North America (United States and Canada), 35 from Europe, 18 from Asia, 1 from Australia, and 2 from other regions. All studies were published in English. Clinical registry and administrative data were the primary data source for 60 and 24 studies, respectively. According to the Newcastle– Ottawa Scale, 71 studies were deemed to have high quality (7–9 scores of the scale; Table S2).
Door- to-Treatment Time
The door- to- treatment time of patients with IS was reported in 27 cohorts (door- to- needle time, 19 cohorts; door- to- groin time, 8 cohorts). Five cohorts reported the OR of intravenous thrombolysis within 60 minutes after admission between off- hour patients and regularhour patients. Patients with IS admitted during off- hours were less likely to receive intravenous thrombolysis within 60 minutes after admission (OR, 0.65 [95% CI, 0.46–0.92]). High heterogeneity was noted (I^2=95%; τ=0.35), indicating that any pair of study effects might differ by as much as 0.70 in OR units, and the prediction interval (0.18–2.36) also highlighted substantial variability in future effects. Compared with patients admitted during regular hours, the door- to- needle time (mean difference, 5.93 [95% CI, 1.88–9.98] minutes; I^2=90%; prediction interval, -2.89 to 12.96 minutes) and door- to- groin time (mean difference, 13.54 [95% CI, 5.02–22.06] minutes; I^2=59%; prediction interval, -10.43 to 37.40 minutes) were significantly increased for off- hour patients (Figure 2), while any pair of study effects might differ by as much as 16.80 minutes (τ for door- to- needle time, 8.40) and 18.52 minutes (τ for door- to- groin time, 9.26), respectively.
There were no statistically significant subgroup effects in door- to- needle time between study subgroups by cohort areas (P=0.56), type of off- hours (P=0.34), stroke unit or not (P=0.42), and stroke severity (P=0.17; Table S3). However, subgroup analysis showed that there was statistically significant interaction between the adjustment of previous stroke and the estimated off- hour effect (P<0.001), meaning the adjustment of previous stroke was a powerful modifying factor for the off- hour effect. The mean difference in door- to- needle time was close to 0 (-0.63 [95% CI -2.71 to 1.47]; I^2=60%) in studies that adjusted previous stroke, compared with 9.73 minutes (95% CI, 4.81–14.65 minutes]; I^2=91%) in studies that did not. No time trend was found on the door- to- needle time or door- to- groin time from meta- regression analysis. In the subgroup analyses stratified by the midyear of cohorts, the treatment delay of the most recent cohorts (2015 to the present) remained substantial (mean difference, 12.96 [95% CI, 3.63–22.30] minutes; I^2=93%).
Short-Term Mortality Rate
The short- term mortality rate was defined as in- hospital death, 7- day death, or 30- day death. If a study reported >1 short- term mortality outcome, we preferred in- hospital death as short- term mortality rate, followed by 30- day death, and finally 7- day death. A total of 64 studies reported the short- term mortality risk of off- hour

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Figure 3. Short- term mortality risk of patients with ischemic stroke, patients with intracerebral hemorrhage, and patients with subarachnoid hemorrhage admitted during off-hours.
A, The short- term mortality risk between patients with ischemic stroke admitted during off- hours and regular hours. B, The shortterm mortality risk between patients with intracerebral hemorrhage admitted during off- hours and regular hours. C, The short- term mortality risk between patients with subarachnoid hemorrhage admitted during off- hours and regular hours.

patients with stroke, including 40 studies that reported the short- term mortality rate of patients with IS, 15 of patients with ICH, and 7 of patients with SAH. Off- hour admission was associated with higher short- term mortality risk (OR, 1.09 [95% CI, 1.06–1.12]; I^2=78%; Figure S1, τ, 0.08; prediction interval, 0.96–1.23), including patients with IS (OR, 1.07 [95% CI, 1.03–1.11]; I^2=76%; τ, 0.10; prediction interval, 0.91–1.25), patients with ICH (OR, 1.10 [95% CI, 1.03–1.18; I^2=71%; τ, 0.11; prediction interval, 1.03–1.22), and patients with SAH (OR, 1.05 [95% CI, 1.02–1.09; I^2=35%; Figure 3; τ, <0.01; prediction interval, 0.93–1.20). The substantial heterogeneity results indicate that the maximum expected difference in effect values of short- term mortality risk between any pair of studies was 0.16 OR units. For patients with IS and patients with ICH, the maximum expected differences were 0.20 and 0.22 OR units, respectively. The 7- day, 30- day, and in- hospital mortality risk of patients with IS, patients with ICH, patients with SAH, and all patients with stroke, respectively, are reported in Table S4.
Among all the included studies, only 7 studies assessed the short-term mortality risk in patients with different stroke severity. Four of the studies used the National Institute of Health Stroke Scale (NIHSS) to evaluate the stroke severity at admission. Angerer et al,^10 Karliński et al,^84 and Haeusler et al^106 found that higher NIHSS scores were associated with increased 7- day death, 30- day death, and in- hospital death of patients with stroke, and Hasegawa et al^103 divided the NIHSS scores into quartiles and found that only the fourth quartile (NIHSS scores >14) was associated with significantly increased case fatality. Similar results were reported in studies used the Canadian Neurological Scale, Scandinavian Stroke Scale, self- developed stroke severity index, and conscious level to assess the stroke severity at admission. In subgroup analyses, the weekend effect was found in cohorts unadjusted for the stroke severity of patients with IS and patients with ICH at admission (IS, 1.08 [95% CI, 1.04–1.12]; I^2=83%; ICH, 1.14 [95% CI, 1.06–1.21]; I^2=95%). In cohorts adjusted for the stroke severity at admission, the short- term mortality risk of off- hour patients was not significant (IS, 1.04 [95% CI, 0.95– 1.12]; I^2=48%; ICH, 0.96 [95% CI, 0.81–1.10]; I^2=54%). However, no subgroup effects in the short- term mortality rate were found by the adjustment of stroke severity (IS,

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Subgroups | Number of cohorts | Odds ratio | 95% CI | I^2, % | P value for interaction | R^2,* %
Area | | | | | 0.69 | 0.00
North America | 16 | 1.05 | 1.01–1.09 | 60 | |
Europe | 22 | 1.09 | 1.02–1.17 | 84 | |
Asia | 13 | 1.06 | 0.98–1.15 | 65 | |
Others | 1 | 1.14 | 0.92–1.41 | 0 | |
Off- hour type^† | | | | | 0.71 | 0.00
Weekend | 25 | 1.08 | 1.02–1.13 | 80 | |
Night | 12 | 1.08 | 1.00–1.18 | 79 | |
Weekend and night | 15 | 1.04 | 0.95–1.12 | 59 | |
Data source | | | | | 0.46 | 0.00
Administrative data | 18 | 1.05 | 1.00–1.11 | 84 | |
Clinical registry | 34 | 1.08 | 1.03–1.14 | 68 | |
Stroke center | | | | | 0.85 | 0.00
Yes | 11 | 1.08 | 0.91–1.30 | 41 | |
No | 41 | 1.07 | 1.03–1.11 | 79 | |
Previous stroke | | | | | 0.09 | 12.90
Adjusted | 10 | 1.14 | 1.05–1.23 | 59 | |
Unadjusted | 42 | 1.06 | 1.01–1.10 | 71 | |
Stroke severity | | | | | 0.39 | 2.23
Adjusted | 21 | 1.04 | 0.95–1.12 | 48 | |
Unadjusted | 31 | 1.08 | 1.04–1.12 | 83 | |
Cohort decades | | | | | 0.45 | 4.63
1995–2004 | 13 | 1.10 | 1.04–1.16 | 83 | |
2005–2014 | 34 | 1.06 | 1.01–1.11 | 72 | |
2015 to present | 5 | 0.99 | 0.81–1.21 | 47 | |

Table 1. Subgroup Analyses of the Short-Term Mortality Rate of Patients With Ischemic Stroke Admitted During Off- Hours

*The R^2 statistical value was obtained from univariate meta- regression analysis.
^†In the subgroups of “off- hour type,” public holidays were included in the subgroup of “weekends.”

P=0.39; ICH, P=0.13), as well as by area (IS, P=0.69; ICH, P=0.81), off- hour types (IS, P=0.71; ICH, P=0.62), data sources (IS, P=0.46; ICH, P=0.86), stroke center or not (IS, P=0.85; ICH, P=0.58), and adjustment of previous stroke (IS, P=0.09; ICH, P=0.89; Tables 1 and 2).
Meta- regression showed that the OR of the shortterm mortality rate for patients with IS decreased by year (P=0.01; Figure 4). In subgroup analyses stratified by the midyear of cohorts, off-h our admission was associated with an increased short- term mortality risk for patients with IS in the 1995 to 2004 cohorts and the 2005 to 2014 cohorts but was not in cohorts after 2015 (Table 1). No significant time trend was found on short- term mortality risk for patients with ICH from meta- regression. According to subgroup analyses, the weekend effect of patients with ICH was reported in all the 3 decades (Table 2).

Ninety- Day Functional Status
The 90- day functional status was identified with the mRS score at 90- day follow- up after admission. We classified patients with an mRS score <3 as having good function and patients with an mRS score ≥3 as having unfavorable function. A total of 30 cohorts reported the 90- day functional status of patients with IS, and 4 cohorts reported that of patients with ICH. No significant favorable function was found for off- hour patients with IS (OR, 0.96 [95% CI, 0.91–1.01]; I^2=78%; prediction interval, 0.84–1.06; Figure 5), while any pair of study effects might differ by as much as 0.16 (τ, 0.08) in OR units. Similar results were also observed in the patients with ICH (OR, 1.00 [95% CI, 0.93–1.07; I^2=0), while the estimation of τ and the prediction intervals could not be made due to the insufficient number of included studies.

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Subgroups | Number of cohorts | Odds ratio | 95% CI | I^2, % | P value for interaction | R^2,* %
Area | | | | | 0.81 | 0.00
North America | 8 | 1.11 | 1.10–1.12 | 0 | |
Europe | 6 | 1.07 | 0.80–1.33 | 85 | |
Asia | 3 | 1.06 | 0.96–1.16 | 0 | |
Off- hour type^† | | | | | 0.62 | 0.00
Weekend | 12 | 1.11 | 1.10–1.12 | 0 | |
Night | 2 | 1.29 | 0.75–1.83 | 96 | |
Weekend and night | 3 | 1.08 | 0.90–1.26 | 64 | |
Data source | | | | | 0.86 | 0.00
Administrative data | 6 | 1.11 | 1.10–1.12 | 0 | |
Clinical registry | 11 | 1.08 | 0.94–1.23 | 85 | |
Stroke centers | | | | | 0.58 | 0.00
Yes | 3 | 1.03 | 0.85–1.22 | 0 | |
No | 14 | 1.10 | 1.02–1.12 | 97 | |
Stroke severity | | | | | 0.13 | 25.39
Adjusted | 4 | 0.96 | 0.81–1.10 | 54 | |
Unadjusted | 13 | 1.14 | 1.06–1.21 | 95 | |
Cohort decades | | | | | 0.89 | 0.00
1995–2004 | 3 | 1.12 | 1.05–1.19 | 0 | |
2005–2014 | 15 | 1.09 | 1.02–1.17 | 81 | |
2015 to present | 1 | 1.11 | 1.10–1.12 | 0 | |
Table 2. Subgroup Analyses of the Short-Term Mortality Rate of Patients With Intracerebral Hemorrhage Admitted During Off- Hours
*The R^2 statistical value was obtained from univariate meta- regression analysis.
^†In the subgroups of “off- hour type,” public holidays were included in the subgroup of “weekends.”
Only 7 studies reported the association between NIHSS scores at admission and the 90- day mRS scores. Most of the studies found that high NIHSS
scores at admission were associated with worse 90- day function, but a cohort from stroke centers in France reported the opposite view that patients
Figure 4. Meta- regression for time trend of the short- term mortality rate of patients with ischemic stroke.

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Figure 5. Ninety- d functional status of patients with ischemic stroke and patients with intracerebral hemorrhage admitted during off- hours.
A, The 90- d functional status between patients with ischemic stroke admitted during off- hours and regular hours. B, The 90- d functional status between patients with intracerebral hemorrhage admitted during off- hours and regular hours.
admitted in nighttime hours with higher NIHSS scores had better functional outcomes at 90 days. In subgroup analyses, both cohorts adjusted for stroke severity at admission and cohorts unadjusted for stroke severity, the off- hours admission was not significantly associated with favorable 90- day function, and no significant subgroup effect was observed by the adjustment for stroke severity (P=0.77). There were also no statistically significant differences in off- hour effect on 90- day functional status of patients with IS between subgroups by cohort area (P=0.43), off- hour types (P=0.74), data sources (P=0.60), stroke
center or not (P=0.45), and adjustment of previous stroke (P=0.77; Table S5). No time trend was found in meta- regression analysis, but off- hour admission was associated with favorable 90- day function in the post- 2015 cohorts (OR, 0.87 [95% CI, 0.79–0.97]; I^2=20%; Table S5).
Publication Bias and Sensitivity Analyses The contour- enhanced funnel plots are shown in Figure S2. Visual examination revealed asymmetric plots in the short- term mortality rate of patients with IS

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and patients with ICH and 90- day function of patients with IS. According to the subsequent Egger test, significant asymmetry was observed for 90- day function of patients with IS (P<0.01), but not for the short- term mortality rate of patients with IS (P=0.06) or patients with ICH (P=0.69). In the analyses with the trim- and- fill method, the newly pooled results with added studies were similar to the previous results of patients with IS and patients with ICH, suggesting the potential publication bias had little effect on the pooled results, and other reasons for the asymmetry might exist. Among all 84 studies, 8 used HR to assess the short- term mortality risk, and others used ORs. By excluding studies reporting HRs rather than ORs,^28,29 we found that all the pooled results remained similar (IS: OR, 1.06 [95% CI, 1.02–1.10]; I^2=77%; ICH: OR, 1.10 [95% CI, 1.04–1.17; I^2=78%; SAH: OR, 1.05 [95% CI, 1.02–1.09]; I^2=5%). Other sensitivity analyses also indicated the robustness of the results of this study (Tables S6 through S8).
Certainty of Evidence
Table S9 showed the credibility of evidence after the Grading of Recommendations Assessment, Development, and Evaluation assessment. The certainty in our pooled estimates was “very low” for the association of off- hour admission with treatment delay or 90- day functional status in patients with stroke. Similarly, evidence for the short- term mortality rate in patients with stroke and in those with the IS subtype and ICH subtype was rated “very low.” The reasons for downgrading were mainly due to inconsistency, imprecision, and potential publication bias. Because of the observational nature of the included studies and the absence of other reasons for downgrading, the certainty of the evidence for short- term mortality rate among patients with SAH was “low.”
DISCUSSION
This is the first meta- analysis that comprehensively assessed the association between off- hour admission with the treatment delay and unfavorable stroke outcomes. Evidence from the included studies suggested that the door- to- treatment time of patients with stroke admitted on weekends or nights were significantly extended, and off- hour admission was associated with increased short- term mortality risk.
Many guidelines and practices recommended that receiving intravenous thrombolysis within 60 minutes after admission was beneficial to patients with IS, as timeliness of thrombolytic treatment was directly related to the outcomes.^30–33 A large cohort study of patients with IS treated with intravenous tissue plasminogen activator reported that patients with the door-to- needle time >60 minutes had a higher risk of all- cause death and all- cause readmission, and every 15- minute extension in the door-to- needle time was significantly associated with 4% higher risk of all- cause death within 90 minutes after hospital arrival.^30 In this systematic review, patients with IS admitted during off- hours were significantly less likely to receive intravenous thrombolysis within 60 minutes, compared with those admitted during regular hours. Besides the direct clinical outcomes, the extension of door- to- needle time and door-to- groin time reflected the hospital organizational efficiency and their stroke treatment process during off- hours, which could be the focus of future improvement.
Interestingly, we observed that the extended door- to- needle time risk of patients with IS admitted during off- hours without adjusted stroke history was more evident, while the off- hour effect was close to 0 in the subgroup of adjusted previous stroke. This might be because patients with previous stroke often have more serious complications, higher NIHSS, and longer door- to- needle time,^34 which tended to make the absolute effect difference between off- hours and on- hours less obvious. Meanwhile, the subgroup analysis and meta- regression on the adjustment for previous stroke showed that the heterogeneity in the outcome of door- to- needle time decreased obviously (I^2 from 91% to 60%, with R^2=36.78%), indicating that the adjustment of the previous stroke might account for the differences among the studies. Similarly, for the short- term mortality outcome among patients with IS, we also found that the adjustment for previous stroke might partially explain the source of heterogeneity. Due to the fact that the baseline mortality risk of patients with previous strokes is often higher,^35–37 the relative shortage of medical resources during off- hours may be further exacerbated. Moreover, the adjustment for previous stroke and the weekend effect may have a synergistic amplifying effect on the mortality rate of patients with IS, although the interaction was not significant. Therefore, taking measures such as establishing a 120 prehospital warning system, synchronizing the emergency triage desk and stroke emergency response system with the hospital’s electronic medical record system or the regional health information platform, and further optimizing the medical resources during off- hours, may be of crucial significance.^38
Some studies indicated that the weekend effect could be partly contributed to confounding factors, and the increased mortality rate of patients admitted to hospitals urgently on weekend or at night was related to their more severe stroke, rather than the specific time of admission.^39,40 According to our systematic review of studies reporting the short- term mortality risk and 90- day functional status of patients with different stroke severity at admission, except a cohort about the 90- day mRS scores of patients from comprehensive stroke centers, all the studies indicated that higher

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NIHSS (or other stroke severity scales) scores were associated with increased short- term mortality risk and unfavorable function. In particular, for short- term mortality risk in patients with stroke, subgroup analysis and meta- regression showed that adjusting for stroke severity could substantially reduce the heterogeneity of the pooled effect and explain 12.90% (patients with IS) and 25.39% (patients with ICH) of the between- study variability. This may be because a high NIHSS score directly reflects a larger infarct volume or blood loss, creates a chain reaction of complications, and limits the reperfusion treatment window, leading to an increased short- term mortality risk. Moreover, high baseline damage can lead to irreversible loss of neurons and a significant decrease in rehabilitation potential, leading to poor prognosis.^41 After adjustment for stroke severity, the confounding factor of severe weekend clustering was controlled, and sources of heterogeneity were substantially eliminated.^42 Although our results of subgroup analyses did not reveal significant subgroup effects in the short- term mortality rate between studies that adjusted for stroke severity at admission and those that did not, the results of this meta- analysis should be interpreted cautiously. Existing scales may not capture all of the differences in severity or baseline characteristics, such as patients’ behavior, prehospital measures, diagnostic criteria, and the treatment capacity of various regions, which may affect the weekend effect.
We did not observe statistically significant subgroup effects by stroke centers or not, but this should not be simply interpreted as a failure of comprehensive stroke center construction for stroke treatment. Patients in comprehensive stroke centers may have more complex conditions (eg, transfers, prehospital delay, more severe stroke). The complexity of disease and patient may cause longer pretreatment diagnostic time and increased treatment difficulty, which may counteract the therapeutic advantage of comprehensive stroke centers when assessing the outcomes.^43,44 This may explain why comprehensive stroke centers did not perform significantly better than non–stroke centers in the measure of mortality risk and treatment delay.^45,46 Of note, the heterogeneity of short- term mortality risk in the stroke center group decreased substantially, and the off- hour effect became less significant. This indicates that the category of stroke centers may be potential factors for heterogeneity in the off- hour effect. Studies have shown that the structural quality of stroke centers is beneficial to improve the availability of point- of- care brain imaging, immediate care by stroke specialists, and the effectiveness of prevention and treatment, thereby diluting the off- hour effect. Therefore, regardless of the time patients visit, medical resources, clinical pathways, and the professional knowledge of medical staff should be continuously optimized to further improve the quality of care.^9
In the meta- regression analyses on midyear of cohorts, a decreasing trend of short- term mortality risk was found in patients with IS, which could be related to medical progress and attention to the weekend effect in recent years.^47,48 Meanwhile, univariate metaregression also showed that the time period of cohorts accounted for 4.63% of the interstudy variance. In subgroup analyses grouped by every 10 years, the weekend effect was significant in 1995 to 2004 and 2005 to 2014 but not in the IS cohort from 2015 to the present, which may suggest that we have made progress in off- hour care of IS. Correspondingly, the heterogeneity of the pooled effects decreased over time across the subgroups of the time period of cohorts. The results of subgroup analysis and meta- regression indicated that “cohort decades” may partly explain the heterogeneity of short- term mortality risk in patients with IS. However, for the patients with ICH and patients with SAH, no time trend was found in their short- term mortality risk and long- term functional status. In addition, the metaregression results of door- to- needle time in patients with IS supported the variation explanatory power of “cohort decades” (R^2=17.97%). While we also did not find a temporal trend in the risk of door- to- needle time delay, and heterogeneity across subgroups of the time period of cohorts was high, possibly owing to limitations in the number of studies and study sample size. More high- quality studies are needed to further explore the temporal trends of the risk of door- to- needle time delay. In recent years, the attention and the quality of care to off- hour patients with stroke have strengthened, but no significant improvement was observed in dealing with more complex and severe strokes. Therefore, finding ways to reduce treatment delay and continuing to improve the quality of care should remain goals for health care organizations.
Strength and Limitations
This systematic review pooled a large number of original articles about treatment delay, short-term mortality rate, and 90- day functional status of patients with IS, ICH, and SAH admitted during off- hours, comprehensively considered the weekend effect over time, and provided a new perspective for further stroke care studies. However, this study has some limitations. First, according to the contour- enhanced funnel plot and Egger test, there might be publication bias in the result of the 90- day functional status of patients with IS. At present, the significant results of 90- day functional outcome in included studies are mostly derived from small sample or single- center studies, whereas large sample or multicenter studies are generally negative. Therefore, although the main effect was negative in the published literature, the extreme values of small samples were missing, leading to the amplification of the conclusion

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that off- hours had no effect on functional outcome. On the basis of “no difference” results, policy makers may underestimate potential subgroup benefit or mild harm and trigger the wrong allocation of resources and policy relaxation, ultimately resulting in worse actual patient outcomes. However, the analyses with the trim- and-f ill method still supported our results. We believe the potential publication bias would not significantly affect the results, but caution is needed in interpreting the results. Other factors such as heterogeneity of included studies, differences in study quality, and discrimination of underlying mechanisms or background factors might also contribute to asymmetry.
Second, due to various measurement of treatment time in studies, the treatment delay was measured through the most commonly used door- to- needle time for intravenous thrombolysis and door- to- groin time for endovascular treatment, which could apply to only a small number of patients. In addition, as the in- hospital mortality rate was the most commonly reported outcome among all studies and the only outcome of many studies, we chose the in-hospital mortality risk as one of the main results of our meta- analysis, which may be affected by the length of hospital stay. We will try to include a more comprehensive measurement of treatment delay and outcomes in future studies.
Third, due to the small number of original articles about the outcomes of patients with different stroke severity at admission, we could perform subgroup analyses only on whether studies adjusted for stroke severity or not, rather than accurately analyze how different stroke severities influence the weekend effect. Although the subgroup analyses did not show any statistically significant difference between the 2 subgroups, the results of this metaanalysis should be interpreted cautiously. Future studies about the weekend effect should pay more attention to these potential influencing factors.
Fourth, the high level of heterogeneity in our metaanalysis may limit the generalizability of pooled off- hours effects. This may be due to differences in the types of health systems, models of medical service provision, and efficiency of medical and health care resource allocation in different countries and regions. The study characteristics of each included study, such as the design type, cohort period, data source, and the definition of weekends or nights, could potentially be a source of heterogeneity. However, our study does not provide direct evidence to support these hypotheses. Moreover, due to the information limitations of the included studies, we were unable to examine the unobserved confounding factors such as the different demographic, sociological, and clinical characteristics of the patients, which might constitute a part of the residual heterogeneity. Researchers and policy makers should be aware of the high heterogeneity of pooled values and use research evidence with caution. In the future, we should further explore the optimization of each element of structure and process attributes in the regional acute stroke nursing system, thereby improving the overall treatment quality.
CONCLUSIONS
This systematic review indicated that the short- term mortality rate of patients with stroke admitted on weekends or at nights was higher than those admitted during regular working hours. For patients with IS, the shortterm mortality risk during off- hours decreased by year, and the weekend effect was not statistically significant in cohorts after 2015. The weekend effect may be partly attributed to the extended door- to- needle time and door- to- groin time during off- hours. Hospitals still need to improve the quality of care for patients with stroke who are hospitalized during off- hours by implementing strategies such as establishing a 24/7 team and carrying out telestroke services, especially for patients with severe and complex conditions.^49,50 To conduct more extensive and effective high- quality treatment initiatives for patients with stroke admitted during off- hours and eliminate time- based inequalities in medical services, measures such as signing regional stroke transfer agreements, establishing mobile stroke units, strengthening the linkage between families and communities during off- hours, and enhancing financial and performance incentives may be viable approaches.^51,52
ARTICLE INFORMATION
Received April 10, 2025; accepted December 16, 2025.
Affiliations
School of Public Health, Tongji Medical College (Y.L., H.W., Y.X., Y.G., L.W., R.Z., Z.L., S.C.), Department of Neurology, Tongji Hospital, Tongji Medical College (F.W.) and School of Nursing, Tongji Medical College (F.W., Q.J.), Huazhong University of Science and Technology, Wuhan, Hubei, China; Wuhan Third Hospital, Tongren Hospital of Wuhan University, Wuhan, Hubei, China (S.W.); and Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, UK (F.S.).
Acknowledgments
The authors thank all the authors of the studies included in their meta- analysis.
Author contributions: Y.L. and S.C. conceived and designed the study. Y.L. and S.W. designed the database searches. S.W. and Q.J. carried out the searches. Y.L., S.W., Q.J., Y.G., H.W., R.Z., L.W., and Y.X. contributed to evaluation of study eligibility and data extraction. S.W. and Y.L. analyzed the data and drafted the manuscript. Z.L., F.W., and F.S. contributed to interpretation of results. All authors provided a critical review and approved the final manuscript. S.C. is the guarantor. He had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analyses. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.
Sources of Funding
This work was funded by the Double First- Class Funds for the Universities (2024WKYXQN008), and the Key Research and Development Program of Hubei Province (2020BCA089).

Disclosures
None.
Supplemental Material
Data S1. Supplemental Methods Tables S1–S9
Figures S1–S2
References 52–119

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J Am Heart Assoc. 2026;15:e043006. DOI: 10.1161/JAHA.125.043006