Abstract
The impact of intracerebral hemorrhage (ICH) onset time (night vs. day) on in-hospital mortality, in-hospital complications, and early functional outcomes remains inconclusive. This study aimed to explore the associations between night and day ICH onset and these critical endpoints. Using data extracted from the China Stroke Center Alliance, this cohort study included 81,913 patients within 24 h of ICH onset. Multivariable logistic regressions assessed the associations between ICH onset time and in-hospital mortality, hematoma expansion, early poor neurological outcomes, and in-hospital complications. The onset times of ICH showed a major peak between 08:00 and 11:00 and a minor peak between 15:00 and 18:00. Compared to patients with night-onset ICH (18:00–06:00), those with day-onset ICH (06:00–18:00) had lower risks of in-hospital mortality (adjusted odds ratio [aOR] = 0.87; 95% confidence interval [CI], 0.78 to 0.96, P = 0.01), early poor neurological outcomes (aOR = 0.93; 95% CI 0.90 to 0.97, P < 0.01), and stroke-associated infections (aOR = 0.93; 95% CI 0.90 to 0.97, P < 0.01). The natural indirect effects of night-onset ICH on in-hospital mortality via admission National Institutes of Health Stroke Scale and baseline Glasgow Coma Scale scores were highly significant (aOR = 1.07 and 1.08, respectively; both P < 0.0001). Patients with ICH occurring between 22:00 and 02:00 who did not undergo hematoma evacuation were more likely to experience in-hospital mortality (aOR = 1.12; 95% CI 1.04 to 1.21, P < 0.001) and early poor neurological outcomes (aOR = 1.09; 95% CI 1.01 to 1.19, P = 0.03). However, night-onset did not significantly affect in-hospital mortality for patients with ICH undergoing hematoma evacuation. Night-onset ICH was associated with more severe strokes and higher risks of in-hospital mortality, stroke-associated infections, and early poor neurological outcomes. However, undergoing hematoma evacuation may mitigate the detrimental effect of night-onset ICH on in-hospital mortality.
Supplementary Information
The online version contains supplementary material available at 10.1038/s41598-026-46172-y.
Keywords: Intracerebral hemorrhage, Onset time, In-hospital mortality, Early poor neurological outcomes, Stroke-associated infections
Subject terms: Diseases, Medical research, Neurology, Neuroscience, Risk factors
Introduction
Acute primary intracerebral hemorrhage (ICH), a devastating type of stroke, causes over 2 million deaths worldwide annually1,2. Evidence suggests that circadian biology significantly affects stroke treatment and outcomes3,4. Investigating the relationship between stroke and circadian rhythm could yield novel clinical insights. Previous studies have explored the link between ICH onset time and clinical outcomes, but findings on circadian rhythm’s impact on ICH prognosis remain inconsistent5–8. This inconsistency likely results from the small sample sizes in these studies. Conducting a large, multicenter cohort study could provide more robust insights into ICH onset patterns.
According to the Takashima Stroke Registry (1990–2003), patients with morning strokes (06:00–12:00) had a higher chance of 28-day mortality compared to those with strokes at other times9. Fabbian et al. reported that among patients with oral anticoagulant-induced ICH, in-hospital mortality was higher for those admitted at night (20:00–07:59) or in the morning (08:00–13:59) compared to those admitted in the afternoon (14:00–19:59)10. However, the association between circadian rhythm and in-hospital mortality among patients with primary ICH not caused by anticoagulant therapy remains unknown. Additionally, the relationships between ICH onset time and hematoma expansion, severity, and early neurological outcomes are unclear. To address this gap, the present study analyzed registry data from the China Stroke Center Alliance (CSCA), encompassing 1,476 hospitals nationwide.
Methods
Study population
The CSCA is a multicenter consortium initiative aimed at enhancing the standard of care for patients with acute stroke and transient ischemic attack. Patients were enrolled from 1,476 secondary or tertiary hospitals across 31 provinces, autonomous regions, and municipalities in mainland China between August 1, 2015, and July 31, 2019. The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. The CSCA program received ethical approval from the ethical review board of Beijing Tiantan Hospital (No: KY 2018–061-02). Due to the retrospective nature of the study, ethical review board of Beijing Tiantan Hospital waived the need of obtaining informed consent11. Procedures were followed in accordance with the ethical standards of the responsible committee on human experimentation and the Helsinki Declaration of 1975.
Enrolled patients satisfied the following criteria: (1) age ≥ 18 years; (2) primary diagnosis of acute primary ICH, confirmed by brain computed tomography (CT) or magnetic resonance imaging (MRI); and (3) arrival at the hospital within 24 h of onset. For patients with wake-up stroke, the time last known to be normal was used as the onset time12. Patients lacking data on in-hospital mortality or ICH onset time were excluded from the study.
Covariates
Baseline data collected from participants included age, sex, body mass index, blood pressure, medical history (including transient ischemic stroke, cerebral infarction, cerebral hemorrhage, subarachnoid hemorrhage, myocardial infarction, hypertension, dyslipidemia, diabetes mellitus, atrial fibrillation, heart failure, chronic obstructive pulmonary disease (COPD), and peripheral vascular disease), pre-admission medications (antiplatelet agents, anticoagulant agents, lipid-lowering agents, antihypertensive agents, and antidiabetic agents), hematoma evacuation, pre-stroke modified Rankin Scale (mRS), Glasgow Coma Scale (GCS) after onset, baseline National Institutes of Health Stroke Scale (NIHSS) score (admission NIHSS score), laboratory results (low-density lipoprotein, fasting blood glucose, glycosylated hemoglobin A1C [HbA1c], homocysteine, creatinine, blood urea nitrogen, uric acid, and C-reactive protein), and the grade of the admitting hospital. For patients unable to accurately provide their medical and medication histories due to language barriers, neurological physicians consulted their spouses, parents, or children to ensure accuracy. Laboratory data were obtained from accredited central hospitals. Baseline data also included the season of ICH onset (spring: March, April, May; summer: June, July, August; autumn: September, October, November; winter: December, January, February).
NIHSS and mRS scores were evaluated by two certified neurologists blinded to the study protocol. In cases of scoring discrepancies, a third experienced senior neurologist performed adjudication to determine the final scores. Clinical data were extracted and imported into the database by trained researchers based on admission medical records diagnosed and recorded by certified neurologists at participating hospitals. At the study’s outset, each participating unit underwent training to ensure consistency in data collection. Hematoma evacuation was performed at the discretion of a licensed neurologist according to clinical guidelines and with informed consent of the patient or family. Data were collected and managed through a web-based tool designed (Medicine Innovation Research Center, Beijing, China)11, extracted through chart review, coded, de-identified, and securely transmitted in compliance with national privacy regulations to ensure patient confidentiality.
Outcomes
The primary outcome of this study was in-hospital mortality, while secondary outcomes included hematoma enlargement, early poor neurological outcomes, and in-hospital complications such as deep vein thrombosis, pulmonary embolism, stroke-associated infections, and other complications. Early poor neurological outcomes were defined as a discharge mRS score of 3–613. Hematoma enlargement was defined as a > 33% increase or an absolute increase of > 6 mL in parenchymal hematoma from the initial hematoma, confirmed by follow-up CT or MRI at 72 h14. Hematoma volumes were measured using the ABC/2 method15. Stroke-associated infections included pneumonia or urinary tract infection during hospitalization. Other complications encompassed epileptic seizure, hydrocephalus, bedsore, depression, gastrointestinal bleeding, respiratory failure, and cardiopulmonary arrest.
Sample size calculation
Due to the retrospective cohort design of this investigation, sample size calculations were not conducted. The cohort size was determined by the selected inclusion and exclusion criteria, and the statistical outcomes indicate that the final sample size was adequate.
Statistical analysis
The ICH onset time was categorized into distinct periods of night (18:00–06:00) and day (06:00–18:00), further stratified into 4-h segments. Continuous variables are presented as medians with interquartile ranges (IQR), while categorical variables are shown as counts and proportions. The Wilcoxon rank-sum and Kruskal–Wallis tests were used for comparing continuous variables between two and multiple groups, respectively. The χ2 test or Fisher exact tests were used to compare categorical variables.
Associations between ICH onset time and outcome variables (including in-hospital mortality, hematoma expansion, early poor neurological outcomes, and in-hospital complications) were analyzed using unadjusted and adjusted logistic regression models. Linear regression was employed to analyze associations between ICH onset time and stroke severity indices. With the NIHSS score and GCS score as separate mediating variables, mediation analysis was performed to estimate the total effect, natural direct effect (NDE), and natural indirect effect (NIE) of night-onset ICH on in-hospital mortality. All effect estimates were reported as odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Additionally, the mediation proportion (i.e., the percentage of the total effect mediated by either the NIHSS or GCS score) was calculated to quantify the contribution of each mediating variable to the observed association. The outcome model was adjusted for age, sex, body mass index (BMI), systolic and diastolic blood pressure, history of subarachnoid hemorrhage, hypertension, diabetes, atrial fibrillation, COPD, fasting blood glucose, homocysteine, creatinine levels, season, and time from onset to arrival, as these exhibited statistical significance in baseline characteristic comparisons between night-onset and day-onset groups. Logistic regression analyses reported associations as ORs with 95% CIs, while linear regression analyses reported associations as regression coefficients with 95% CIs. Categorical variables had either no missing values or missing values of less than 5%, treated as non-occurring events. Missing values for continuous variables, if lower than 20%, were addressed through multiple imputations.
To assess the stability of the results of this study, we performed sensitivity analyses. Since weekend and previous history of stroke may affect the outcome of ICH with onset at different times, we evaluated whether weekend and previous history of stroke affect the effect of ICH onset time on outcome separately, keeping other conditions unchanged. Two sensitivity analyses were conducted to explore: (1) all patients were stratified by their time of hospital admission to explore whether weekend affected outcomes of ICH with different onset times; (2) patients with a prior history of stroke (including ICH, transient ischemic stroke, cerebral infarction and subarachnoid hemorrhage) were excluded to explore whether the effect of onset time on ICH outcomes differed according to a prior history of stroke. To further investigate whether the time from onset to arrival influenced the effect of onset time on various outcomes, patients were stratified according to onset time, and the relationship between time from onset to arrival and various outcomes was analyzed.
All analyses were performed using SAS 9.4 software (SAS Institute, Inc, Cary, NC). All significance tests were two-sided, with Ps values < 0.05 considered statistically significant.
Results
Study population
The CSCA contains data on 1,006,798 patients. After excluding patients who arrived at the hospital more than 24 h after ICH onset (n = 3438), those without a recorded diagnosis of ICH (n = 921,093), those without recorded in-hospital survival status (n = 303), and those without recorded onset time (n = 51), a total of 81,913 ICH patients were included in this study (Fig. 1).
Fig. 1.
Study flowchart. CSCA, Chinese Stroke Center Alliance; ICH, intracerebral hemorrhage.
Baseline characteristics of patients
The median age of the 81,913 patients was 63.0 (53.0–72.0) years, with 62.4% (51,112) being male (Table 1). ICH onset times displayed a clear trend, with most cases occurring in the morning and a major peak at 08:00–11:00, followed by a smaller peak at 15:00–18:00 (Supplementary Fig. 1).
Table1.
Baseline characteristics of patients according to 12-h periods of ICH onset.
| Variables | Total (n = 81,913 [100%]) |
18:00–06:00 (n = 25,880 [31.6%]) |
06:00–18:00 (n = 56,033 [68.4%]) |
P value | ASD (%) |
|---|---|---|---|---|---|
| Demographic | |||||
| Age, y | 63.0 (53.0–72.0) | 62.0 (53.0–71.0) | 64.0 (54.0–73.0) | < 0.001 | 10.9 |
| Male, n (%) | 51 112 (62.4) | 16 056 (62.0) | 35 056 (62.6) | 0.15 | 1.1 |
| Physical examination | |||||
| BMI | 23.5 (21.7–25.4) | 23.7 (21.8–25.5) | 23.5 (21.6–25.4) | < 0.001 | 3.2 |
| Systolic blood pressure, mmHg | 162.0 (145.0–181.0) | 165.0 (147.0–184.0) | 160.0 (144.0–180.0) | < 0.001 | 10.4 |
| Diastolic blood pressure, mmHg | 95.0 (84.0–105.0) | 96.0 (85.0–106.0) | 94.0 (83.0–104.0) | < 0.001 | 9.8 |
| Behavioral history, n (%) | |||||
| Current smoking | 16 142 (19.7) | 5068 (19.6) | 11 074 (19.8) | 0.55 | 0.5 |
| Drinking | 19 922 (24.3) | 6299 (24.3) | 13 623 (24.3) | 0.93 | 0.1 |
| Medical history | |||||
| Transient ischemic stroke | 472 (0.6) | 161 (0.6) | 311 (0.6) | 0.24 | 0.9 |
| Cerebral infarction | 10 654 (13.0) | 3338 (12.9) | 7316 (13.1) | 0.53 | 0.5 |
| ICH | 14 328 (17.5) | 4439 (17.2) | 9889 (17.6) | 0.08 | 1.3 |
| Subarachnoid hemorrhage | 450 (0.5) | 165 (0.6) | 285 (0.5) | 0.02 | 1.7 |
| Myocardial infarction | 717 (0.9) | 225 (0.9) | 492 (0.9) | 0.90 | 0.1 |
| Hypertension | 58 455 (71.4) | 18 833 (72.8) | 39 622 (70.7) | < 0.001 | 4.6 |
| Dyslipidemia | 3371 (4.1) | 1072 (4.1) | 2299 (4.1) | 0.79 | 0.2 |
| Diabetes mellitus | 7765 (9.5) | 2529 (9.8) | 5236 (9.3) | 0.05 | 1.5 |
| Atrial fibrillation | 1236 (1.5) | 360 (1.4) | 876 (1.6) | 0.06 | 1.4 |
| Heart failure | 380 (0.5) | 128 (0.5) | 252 (0.4) | 0.38 | 0.7 |
| COPD | 1199 (1.5) | 351 (1.4) | 848 (1.5) | 0.08 | 1.3 |
| Peripheral vascular disease | 768 (0.9) | 252 (1.0) | 516 (0.9) | 0.47 | 0.5 |
| Treatment, n (%) | |||||
| Antiplatelet agents | 5593 (6.8) | 1745 (6.7) | 3848 (6.9) | 0.51 | 0.5 |
| Anticoagulant agents | 1528 (1.9) | 458 (1.8) | 1070 (1.9) | 0.17 | 1.0 |
| Lipid-lowering | 2413 (2.9) | 730 (2.8) | 1683 (3.0) | 0.15 | 1.1 |
| Antihypertensive agents | 38 614 (47.1) | 12 310 (47.6) | 26 304 (46.9) | 0.10 | 1.2 |
| Antidiabetic agents | 5664 (6.9) | 1837 (7.1) | 3827 (6.8) | 0.16 | 1.1 |
| Hematoma evacuation | 8554 (10.4) | 3136 (12.1) | 5418 (9.7) | < 0.001 | 4.6 |
| Scales and laboratory result | |||||
| Baseline mRS | 1.0 (1.0–3.0) | 1.0 (1.0–3.0) | 1.0 (1.0–3.0) | 0.74 | 0.2 |
| Baseline GCS | 13.0 (8.0–15.0) | 13.0 (8.0–15.0) | 14.0 (8.0–15.0) | < 0.001 | 9.5 |
| Low-density lipoprotein, mmol/L | 2.6 (2.0–3.2) | 2.6 (2.0–3.2) | 2.6 (2.0–3.2) | 0.16 | 0.8 |
| Fasting blood glucose, mmol/L | 5.9 (5.1–7.1) | 6.0 (5.2–7.4) | 5.8 (5.1–7.0) | < 0.001 | 13.5 |
| Hemoglobin A1C, % | 5.6 (5.1–6.1) | 5.6 (5.1–6.1) | 5.6 (5.1–6.1) | 0.07 | 3.0 |
| Homocysteine, µmol/L | 13.7 (10.0–20.0) | 13.4 (9.8–20.0) | 13.8 (10.0–20.2) | < 0.001 | 4.1 |
| Creatinine, µmol/L | 67.5 (55.0–84.6) | 67.0 (54.0–84.6) | 68.0 (55.0–84.6) | 0.001 | 2.4 |
| Blood urea nitrogen, mmol/L | 5.1 (4.0–6.6) | 5.2 (4.1–6.6) | 5.1 (4.0–6.6) | 0.26 | 2.8 |
| Uric acid, µmol/L | 277.0 (210.0–353.5) | 277.0 (211.0–355.0) | 277.0 (210.0–353.0) | 0.26 | 0.3 |
| C-reactive protein, mg/L | 3.6 (1.0–9.6) | 3.4 (1.0–9.0) | 3.8 (1.0–10.0) | 0.03 | 3.9 |
| Other information | |||||
| Hospital grade, n (%) | 0.27 | 0.8 | |||
| Secondary | 34 466 (42.1) | 10 817 (41.8) | 23 649 (42.2) | ||
| Tertiary | 47 447 (57.9) | 15 063 (58.2) | 32 384 (57.8) | ||
| Season, n (%) | < 0.001 | 8.2 | |||
| Spring | 22 352 (27.3) | 7160 (27.7) | 15 192 (27.1) | ||
| Summer | 15 506 (18.9) | 5395 (20.8) | 10 111 (18.0) | ||
| Autumn | 36 262 (44.3) | 11 073 (42.8) | 25 189 (45.0) | ||
| Winter | 7793 (9.5) | 2252 (8.7) | 5541 (9.9) | ||
| Time from onset to arrival, h | 3.0 (1.0–17.0) | 3.0 (1.0–11.0) | 4.0 (1.0–23.0) | < 0.001 | 18.0 |
Compared to night-onset patients (n = 25,880), day-onset patients (n = 56,033) were more likely to be older (median, 64.0 vs. 62.0, P < 0.001), and had lower systolic (median, 160.0 vs. 165.0, P < 0.001) and diastolic blood pressure (median, 94.0 vs. 96.0, P < 0.001). They were less likely to have a medical history of subarachnoid hemorrhage (0.5% vs. 0.6%, P = 0.02) and hypertension (70.7% vs. 72.8%, P < 0.001), exhibited lower fasting blood glucose levels (median, 5.8 vs. 6.0, P < 0.001), and had higher homocysteine (median, 13.8 vs. 13.4, P < 0.001), creatinine (median, 68.0 vs. 67.0, P = 0.001), and C-reactive protein levels (median, 3.8 vs. 3.4, P = 0.03). Analysis of seasonality showed that night onsets were more frequent in spring and summer, while day onsets were more common in autumn and winter (P < 0.001). Hematoma evacuation was less common among day-onset patients (9.7% vs. 12.1%, P < 0.001). Finally, day-onset ICH patients were likely to visit the hospital later (median, 4.0 vs. 3.0, P < 0.001; Table 1).
Segmenting the night- and day-onset groups into 4-h subgroups showed that the ICH patients with night-onset (18:00–22:00, 22:00–2:00, 2:00–6:00) were more likely to have a history of hypertension than those with day-onset (P < 0.001). The shortest time from ICH onset to hospital admission occurred for patients experiencing ICH between 18:00 and 22:00, with a median of 2 h (P < 0.001). Furthermore, hematoma evacuation was most frequently performed during the 22:00–02:00 interval, followed by the 02:00–06:00 interval, with the respective proportions being 13.6% and 11.8% (P < 0.001; Supplementary Table 1).
Associations between ICH onset time and outcome variables
Logistic regression analyses indicated that daytime ICH onset was associated with lower risks of in-hospital mortality (adjusted OR = 0.87, 95% CI 0.78 to 0.96, P = 0.01), early poor neurological outcomes (adjusted OR = 0.93, 95% CI 0.90 to 0.97, P < 0.01), and stroke-associated infections (adjusted OR = 0.93, 95% CI 0.90 to 0.97, P < 0.01; Fig. 2) compared to nighttime onset. However, no significant correlation was found between ICH onset time and hematoma expansion (adjusted OR = 1.02, 95% CI 0.96 to 1.08, P = 0.61; Fig. 2).
Fig. 2.
Associations between ICH onset time (grouped by 12-h intervals) and outcome variables. OR and 95% CI were calculated using logistic regression analyses. Adjusted variables include age, gender, body mass index, systolic blood pressure, diastolic blood pressure, history of subarachnoid hemorrhage, hypertension, diabetes, atrial fibrillation, chronic obstructive pulmonary disease, and fasting blood glucose, homocysteine, creatinine, season, and time from onset to arrival.
Analyzing ICH onset time in 4-h intervals revealed no significant association with risks of in-hospital mortality, hematoma expansion, or early poor neurological outcomes. Nonetheless, the risk of in-hospital mortality and early poor neurological outcomes tended to increase from day to night (Fig. 3). Multiple linear regression analysis showed that night-onset ICH was associated with a higher admission NIHSS score compared to day-onset ICH (NIHSS score, 9.4 ± 9.4 vs. 8.5 ± 8.8, P = 0.03; Table 2). Additionally, patients with an ICH onset time of 22:00–2:00 were most likely to experience stroke-associated infections (adjusted OR = 1.13, 95% CI 1.05 to 1.21, P < 0.01; Supplementary Fig. 2).
Fig. 3.
Associations between ICH onset time (grouped by 4-h intervals) and outcome variables. OR and 95% CI were calculated using logistic regression analyses. Adjusted variables include age, gender, body mass index, systolic blood pressure, diastolic blood pressure, history of subarachnoid hemorrhage, hypertension, diabetes, atrial fibrillation, chronic obstructive pulmonary disease, and fasting blood glucose, homocysteine, creatinine, season, and time from onset to arrival.
Table 2.
Association between ICH onset time and admission NIHSS score.
| 06:00–10:00 | 10:00–14:00 | 14:00–18:00 | 18:00–22:00 | 22:00–02:00 | 02:00–06:00 | |
|---|---|---|---|---|---|---|
| Admission NIHSS score (Mean ± SD) | 8.5 ± 8.8 | 8.0 ± 8.8 | 8.4 ± 8.9 | 9.4 ± 9.4 | 9.2 ± 9.1 | 9.2 ± 9.0 |
| Unadjusted r (95% CI) | Reference | − 0.4 (− 0.6, − 0.2) | − 1.3 (− 1.6, − 1.1) | − 1.2 (− 1.5, − 0.8) | − 1.2 (− 1.5, − 0.8) | − 0.4 (− 0.7, − 0.2) |
| Unadjusted P value | Reference | < 0.01 | < 0.01 | < 0.01 | < 0.01 | < 0.01 |
| Adjusted r (95% CI) | Reference | − 0.2 (− 0.5, 0.1) | − 0.5 (− 0.8, − 0.1) | − 0.5 (− 0.9, − 0.0) | − 0.2 (− 0.6, 0.2) | − 0.0 (− 0.3, 0.3) |
| Adjusted P value | Reference | 0.28 | 0.01 | 0.03 | 0.40 | 0.97 |
Adjusted variables: age, gender, body mass index, systolic blood pressure, diastolic blood pressure, history of subarachnoid hemorrhage, hypertension, diabetes, atrial fibrillation, chronic obstructive pulmonary disease, and fasting blood glucose, homocysteine, creatinine, season and time from onset to arrival.
To evaluate whether the severity of ICH modulates the association between night-onset ICH and in-hospital mortality, we performed mediation analyses with the admission NIHSS score and baseline GCS score as separate mediating variables. The results showed that, without adjustment for confounding factors, night-onset was significantly correlated with an elevated risk of in-hospital mortality from ICH (NIHSS score model: OR = 1.22, 95% CI 1.05 to 1.40, P = 0.0135; GCS score model: OR = 1.23, 95% CI 1.09 to 1.38, P = 0.0018; Table3). After adjusting for confounding factors, the overall effect in the NIHSS score model remained significant (adjusted OR = 1.21, 95% CI 1.01 to 1.40, P = 0.0361), and the overall effect in the GCS model was nearly significant (adjusted OR = 1.14, 95% CI 0.99 to 1.29, P = 0.0639), with the direction of the effect consistently suggesting an increased risk (Table3). In adjusted models, the NIEs of night-onset ICH on in-hospital mortality via admission NIHSS and baseline GCS scores were highly significant (adjusted OR = 1.07 and 1.08, respectively; both P < 0.0001), indicating that night-onset ICH indirectly elevates mortality risk by increasing admission NIHSS and decreasing baseline GCS scores (Table3). The admission NIHSS and baseline GCS scores mediated 37.51% and 58.41% of the total effect of night-onset ICH on in-hospital mortality, respectively, and adjusting for these mediators reduced night-onset ICH’s impact on mortality by 52.99–77.30% (Table3). Collectively, these results confirm that night-onset ICH is significantly associated with a higher in-hospital mortality risk, a relationship likely mediated by exacerbated neurological deficits and disturbances in consciousness that indirectly trigger and amplify this risk.
Table 3.
Mediation effects of admission NIHSS and baseline GCS scores on the association between night-onset ICH and in-hospital mortality.
| Unadjusted model | Adjusted model | |||
|---|---|---|---|---|
| OR (95% CI) or % (95% CI) | P value | OR (95% CI) or % (95% CI) | P value | |
| Mediating variables: admission NIHSS score | ||||
| Total effect | 1.22 (1.05, 1.40) | 0.0135 | 1.21 (1.01, 1.40) | 0.0361 |
| CDE | 1.11 (0.95, 1.27) | 0.1732 | 1.13 (0.95, 1.31) | 0.1598 |
| NDE | 1.11 (0.95, 1.27) | 0.1732 | 1.12 (0.95, 1.31) | 0.1598 |
| NIE | 1.10 (1.08, 1.12) | < 0.0001 | 1.07 (1.05, 1.09) | < 0.0001 |
| Percentage mediated, % | 50.25 (17.46, 83.04) | 0.0027 | 37.51 (7.89, 67.13) | 0.0131 |
| Percentage due to interaction, % | 20.05 (6.96, 33.14) | 0.0027 | 19.76 (10.45, 29.07) | < 0.0001 |
| Percentage eliminated. % | 65.25 (42.21, 88.29) | < 0.0001 | 52.99 (30.51, 75.46) | < 0.0001 |
| Mediating variables: baseline GCS score | ||||
| Total effect | 1.23 (1.09, 1.38) | 0.0018 | 1.14 (0.99, 1.29) | 0.0639 |
| CDE | 1.10 (0.97, 1.23) | 0.118 | 1.06 (0.92, 1.19) | 0.3981 |
| NDE | 1.10 (0.97, 1.23) | 0.118 | 1.06 (0.92, 1.19) | 0.3981 |
| NIE | 1.12 (1.09, 1.15) | < 0.0001 | 1.08 (1.05, 1.10) | < 0.0001 |
| Percentage mediated, % | 56.07 (27.36, 84.78) | 0.0001 | 58.41 (4.50, 112.32) | 0.0337 |
| Percentage due to interaction, % | 27.56 (9.77, 45.35) | 0.0024 | 22.13 (-6.39, 50.65) | 0.1284 |
| Percentage eliminated. % | 78.47 (64.23, 92.71) | < 0.0001 | 77.30 (47.77, 106.83) | < 0.0001 |
NIHSS National Institutes of Health Stroke Scale, CDE controlled direct effect, NDE natural direct effect, NIE natural indirect effect, GCS Glasgow Coma Scale. Adjusted variables: age, gender, body mass index, systolic blood pressure, diastolic blood pressure, history of subarachnoid hemorrhage, hypertension, diabetes, atrial fibrillation, chronic obstructive pulmonary disease, and fasting blood glucose, homocysteine, creatinine, season and time from onset to arrival.
Subgroup analyses stratified by the presence of hematoma evacuation
To determine the relationship between onset time and outcome variables, patients with ICH were stratified by whether they underwent hematoma evacuation. As shown in Supplementary Table 2, a total of 8554 patients underwent hematoma evacuation, among whom 3,136 had night-onset and 5,418 had day-onset. Further subgroup analysis of these surgical patients revealed that those with night-onset exhibited a significantly younger age (median, 58.0 vs. 60.0, P < 0.001), elevated systolic blood pressure (median, 175.0 vs. 172.0, P = 0.02), and a higher prevalence of hypertension history relative to patients with day-onset (72.1% vs. 69.1%, P = 0.003; Supplementary Table 2). Logistic regression analysis revealed that patients with ICH onset between 22:00 and 02:00 who did not undergo hematoma evacuation faced the highest risks of in-hospital mortality (adjusted OR = 1.12, 95% CI 1.04 to 1.21, P < 0.001) and early poor neurological outcomes (adjusted OR = 1.09, 95% CI 1.01 to 1.19, P = 0.03). Conversely, when hematoma evacuation was performed, night-onset did not significantly impact in-hospital mortality (adjusted OR = 1.11, 95% CI 0.98 to 1.26, P = 0.1) or early poor neurological outcomes (adjusted OR = 0.98, 95% CI 0.84 to 1.14, P = 0.81). Furthermore, patients experiencing ICH between 14:00 and 18:00 without hematoma evacuation had the lowest risk of hematoma expansion (adjusted OR = 0.86, 95% CI 0.75 to 0.99, P = 0.04; Supplementary Table 3).
Sensitivity analyses
To explore the effect of changes attributable to weekday and weekend care on study results, all ICH patients were stratified by their time of hospital admission. Day-onset patients exhibited a lower risk of in-hospital mortality compared to night-onset patients, but this was significant only on weekdays (adjusted OR = 0.88, 95% CI 0.77 to 0.99, P = 0.04; Supplementary Fig. 3). The risk of early poor neurological outcomes was lower for day-onset patients on both weekdays and weekends (weekday, adjusted OR = 0.94, 95% CI 0.90 to 0.98, P = 0.01; weekend, adjusted OR = 0.91, 95% CI 0.85 to 0.97, P = 0.01; Supplementary Fig. 3). Sensitivity analyses that excluded patients with prior history of stroke still showed a lower risk of in-hospital mortality for day-onset patients (adjusted OR = 0.92, 95% CI 0.88 to 0.97, P < 0.01; Supplementary Fig. 4).
Furthermore, the relationship between the time from onset to arrival and various outcomes was examined, stratified by ICH onset time. Results indicated that the effect of time from onset to hospital on in-hospital mortality, early poor neurological outcomes, and stroke-associated infections was independent of the onset time (Supplementary Fig. 5).
Discussion
Based on CSCA data collected from 2015 to 2019, the study found that ICH onset peaked in the morning, with a secondary peak in the afternoon. Patients with night-onset ICH had higher admission NIHSS scores and faced greater risks of in-hospital mortality, early poor neurological outcomes, and stroke-associated infections compared to those with day-onset ICH. Night-onset may indirectly affect the risk of in-hospital death by potentially exacerbating the severity of ICH. Subgroup analyses further demonstrated that hematoma evacuation could potentially mitigate the adverse impacts of nocturnal episodes.
Consistent with previous studies, our results have reported a bimodal distribution of ICH onset times, with a high peak in the morning and a lower peak in the late afternoon5,16. Several plausible explanations exist for these two peaks. First, since hypertensive ICH accounts for over 50% of cases, rhythmic changes in hypertension likely contribute to this pattern17,18. Blood pressure also peaks twice in 24 h: a major peak in the morning due to the activity of the sympathetic nervous system and the renin–angiotensin–aldosterone axis, and a minor peak in the early evening influenced by endothelial vasodilators and hemodynamic rhythms19,20. The 24-h blood pressure distribution aligns with the observed ICH onset times. Seasonal variations also affect diurnal blood pressure patterns; for instance, the proportion of individuals with higher nighttime blood pressure than daytime blood pressure increases in summer, while the reverse is true in winter21. This seasonality may explain the higher frequency of night-onset ICH in summer and day-onset in winter. Second, vascular endothelial function is reduced in the early morning, potentially due to increased endothelin-1 and oxidative stress during these hours22,23. Third, fibrinolytic activity in the blood peaks between 17:00 and 20:00, which may account for the observed minor evening peak in ICH incidence24,25. Therefore, the circadian pattern of ICH incidence suggests that hypertensive patients should monitor their blood pressure closely in the morning and evening and be prepared to use antihypertensive medications as needed.
In our study, patients with night-onset ICH faced higher risks of in-hospital mortality. Fabbian et al.10. reported night-onset associated with risk of in-hospital mortality of ICH caused by oral anticoagulants. Our findings suggested that onset-time of ICH is related to in-hospital mortality without regard to cause. And night-onset is still associated with a high risk of in-hospital mortality after excluding the influence of prior history of stroke, which may imply that the effect of ICH night-onset on in-hospital mortality is independent of disability status after previous stroke. In our results, patients with night-onset ICH experienced more severe strokes, which may help explain the association between night-onset ICH and in-hospital mortality. Studies have shown that stroke severity (admission NIHSS score ) is an independent risk factor of mortality26. High admission NIHSS scores correlate with hematoma volume: the larger the hematoma volume, the more severe the brain swelling, and the higher the risk of mortality27,28. More severe neurological dysfunction also means an increased risk of deep vein thrombosis and pulmonary embolism29. Our study investigated the association between ICH onset-time and in-hospital mortality, emphasizing the importance of rapid diagnosis and treatment of ICH patients with night-onset.
In this study, patients with night-onset ICH have early poor neurological outcomes. Early rehabilitation treatment is particularly important for the recovery of neurological function in patients with ICH30. The 2022 AHA guidelines on ICH recommend that early rehabilitation, including stretching exercises, neuromuscular electrical stimulation, and functional training, be initiated within 24 to 48 h after ICH onset31. The night-onset of ICH means that these patients may receive early rehabilitation later than patients with day-onset. Second, patients with night-onset have more severe neurological dysfunctions, resulting in a higher risk for various complications and therefore a poorer early neurological outcomes. Therefore, it is necessary to grasp the timing of rehabilitation treatment for ICH night-onset patients, carry out comprehensive rehabilitation training as soon as patients go through stably, and adjust the rehabilitation intensity according to patient’s condition.
In our analysis, we found that patients with night-onset ICH were at increased risk of stroke-associated infections. Stratifying the data into 4-h increments revealed that patients with ICH onset between 22:00 and 02:00 had a relatively higher risk of stroke-associated infections. These associations may be linked to sleep disruption or deprivation32. Animal studies have shown that sleep disruption increases inflammatory cell infiltration and the neural expression of inflammatory factors in mice with traumatic brain injury, leading to prolonged neuroinflammation and behavioral impairments33,34. Sleep disruption can also cause gut microbiota disorders, increase systemic inflammatory responses, compromise the body’s defense system, and ultimately raise the risk of infection35–37. Insufficient staffing and inadequate night-time care may also be one of the reasons for the increased risk of infection in night-onset patients38. Insufficient staffing level during the night may contributed to patients with dysphagia not being screened and treated in a timely manner, which increased the risk of pneumonia. For patients with ICH, especially those with night-onset, effective prevention and treatment of stroke-associated infections have important clinical significance for prognosis of patients.
In critical situations, hematoma evacuation controls intracranial hypertension in patients with ICH39. Stratification of patients based on hematoma evacuation status revealed that those with ICH onset between 22:00 and 02:00 who did not undergo the procedure faced higher risks of in-hospital mortality and early poor neurological outcomes, whereas hematoma evacuation mitigated these adverse effects. Our findings underscore the critical importance of expedited surgical intervention in optimizing outcomes for ICH patients, with particular emphasis on minimizing delays between diagnosis and operative management. For non-operative candidates, implementation of nocturnal intensive care protocols involving enhanced neuromonitoring and proactive intervention appears crucial for risk mitigation. The data further support prioritizing hematoma evacuation in patients demonstrating circadian vulnerability to neurological deterioration, while advocating for personalized management strategies tailored to individual clinical profiles. Future investigations should focus on elucidating the pathophysiological interplay between surgical decompression and circadian-driven pathological cascades, potentially informing time-sensitive therapeutic algorithms to improve neurological recovery.
Stratifying patients by whether their ICH occurred on weekdays or weekends revealed that day-onset ICH was associated with a lower risk of in-hospital mortality compared to night-onset ICH on weekdays. This circadian variation was not observed on weekends. The disparity in quality of care and staffing intensity between weekdays and weekends contributes to a significantly higher in-hospital mortality rate for patients with stroke on weekends, a common issue globally40–44. Similarly, the difference in care quality and staffing between day and night may result in day-onset patients receiving more adequate medical attention when admitted on weekdays, accounting for their lower risk of in-hospital mortality. Additionally, on weekdays, family members often provide less emergency care support due to work commitments, possibly explaining the higher in-hospital mortality risk for patients with night-onset ICH compared to their day-onset counterparts, while this circadian variation in in-hospital mortality was not seen on weekends.
This study has several limitations. First, individual habits related to rest, such as lunch breaks, bedtime, and wake times, could influence ICH outcomes at different onset times, but data on these variables were not collected. Second, due to the lack of data on anatomical characteristics of hematomas, this study could not further adjust for these confounding factors, future prospective studies can incorporate imaging parameters to more accurately verify the independent effect of onset time on ICH prognosis. Third, ICH onset time and adverse outcomes may vary by ethnicity and geographic region. Despite the large sample size, all patients were Chinese, limiting the generalizability of the results. Lastly, the study only included data on early poor neurological outcomes, without considering 3-month or longer-term outcomes.
Conclusions
Compared with day-onset ICH, night-onset ICH is associated with more severe neurological dysfunction and higher risks of in-hospital mortality, early poor neurological outcomes, and stroke-associated infections. Crucially, undergoing hematoma evacuation may mitigate the detrimental effects of night-onset ICH on in-hospital mortality. Researchers should further unravel molecular chronobiology underlying ICH progression, and develop more accurate therapeutic measures tailored to the time of ICH onset.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors thank all participating centers in the Chinese Stroke Center Alliance program for their hard work in data collection, and EditChecks (https://editchecks.com.cn/) for providing linguistic assistance during the preparation of this manuscript.
Author contributions
Conceptualization: Minping Wei, Jian Xia, Xianjing Feng. Data curation: Kejin Du, Zeyu Liu, Qin Huang, Kaixuan Yang, Hongqiu Gu, Zixiao Li, Jie Feng. Formal analysis: Kejin Du, Kaixuan Yang. Validation: Zixiao Li, Xianjing Feng, Jian Xia. Writing—original draft: Minping Wei. Writing—review & editing: Jian Xia, Xianjing Feng.
Funding
Sources of funding: This study was supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project (2024ZD0527700, 2024ZD0527704), the National Key R&D Program of China (2017YFC1310900; 2022YFC2504904), the National Natural Science Foundation of China (82271369; 82301514; 82471365), and the Natural Science Foundation of Hunan Province (2021JJ31109; 2023JJ41018), the Hunan Provincial Key Research and Development Program (2021SK2027).
Data availability
The data supporting this study are from the China Stroke Center Alliance (CSCA) database, a national, hospital-based, multicenter, voluntary quality improvement initiative. The data coordinating center is located at the China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital. Data are available from the corresponding author (Prof. Jian Xia, email: xjian1216@csu.edu.cn) upon reasonable request and with permission of the CSCA.
Declarations
Competing interests
The authors declare no competing interests.
Ethical approval
The CSCA program received ethical approval from the ethical review board of Beijing Tiantan Hospital (No: KY 2018-061-02). Due to the retrospective nature of the study, ethical review board of Beijing Tiantan Hospital waived the need of obtaining informed consent.
Consent for publication
All authors reviewed the final version of the manuscript and approved it for publication.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Jian Xia and Xianjing Feng contributed equally to this work.
Contributor Information
Xianjing Feng, Email: 1039247090@qq.com.
Jian Xia, Email: xjian1216@csu.edu.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data supporting this study are from the China Stroke Center Alliance (CSCA) database, a national, hospital-based, multicenter, voluntary quality improvement initiative. The data coordinating center is located at the China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital. Data are available from the corresponding author (Prof. Jian Xia, email: xjian1216@csu.edu.cn) upon reasonable request and with permission of the CSCA.