Abstract
Aim: To determine whether the severity of cerebral small vessel disease (SVD) is associated with prehospital delay in acute ischemic stroke.
Methods: Consecutive patients with ischemic stroke were included in this study. We evaluated the SVD burden using the total SVD score. Patients were divided into 2 groups: onset-to-door time within 4.5 hours (early arrival group) and onset-to-door time over 4.5 hours (delayed arrival group). First, we assessed whether the total SVD score was related to prehospital delay using a logistic regression analysis. Second, we assessed which item of the score was independently associated with delays. Finally, we determined whether the item had a linear association with the delay.
Results: Of the 2,112 screened patients, 1,754 were enrolled in the study (1,253 males [71%]; median age, 69 years). There were 1,105 patients (63%) in the delayed arrival group. The total SVD score was independently associated with delay (OR 1.11, 95% CI 1.01–1.21, p=0.025). Among the 4 items of the score, only enlarged perivascular spaces (EPVS) in the basal ganglia was independently associated with delay (OR 1.37, 95% CI 1.05–1.80, p=0.022). A linear trend was observed between EPVS grade and delay with reference to EPVS grade 0–1 (EPVS grade 2: OR 1.22, 95% CI 0.92–1.62, p=0.170, EPVS grade 3: OR 1.69, 95% CI 1.20–2.38, p=0.002, EPVS grade 4: OR 2.17, 95% CI 1.37–3.44, p=0.001).
Conclusions: Prehospital delay in acute ischemic stroke could be associated with the severity of SVD, particularly EPVS in the basal ganglia.
Abbreviations: CI: confidence interval, CMBs: cerebral microbleeds , DWI: diffusion weighted imaging, EMS: emergency medical services, EPVS: enlarged perivascular spaces, FOV: field of view, MRA: magnetic resonance angiography, mRS: modified Rankin Scale, NIHSS: National Institutes of Health Stroke Scale, OR: odds ratio, SVD: small vessel disease, SWI: susceptibility-weighted imaging, T2WI: T2-weighted imaging, TE: echo time, TR: repetition time, VCI: vascular cognitive impairment, VIF: variable inflation factors, WMH: white matter hyperintensity
1. Introduction
Prehospital delay in acute ischemic stroke has a tremendous impact on both prognosis and healthcare economics1). The modified Rankin Scale (mRS) score at 3 months is correlated with both the neurological prognosis at 5 years and health/social care costs, which gradually increase with each mRS grade2). Thus, educating people about stroke before they actually develop it is extremely important; however, educating the entire population carries an enormous cost burden3, 4). It would be more cost-effective to focus education on patients with features that make them more prone to stroke, who have a worse prognosis, and who are more prone to prehospital delay.
Several factors that cannot be identified before onset are associated with prehospital delay. These include the National Institutes of Health Stroke Scale (NIHSS) score at admission5, 6), nighttime onset5, 6), impaired consciousness7, 8), and ischemic stroke in the anterior circulation5, 9). However, its association with factors that can be identified before the onset remains unclear.
The present study focused on cerebral small vessel disease (SVD), which is associated with a high risk of stroke and indicates a poor prognosis. SVD is often asymptomatic but gradually worsens with age and atherosclerotic risk factors, increases the risk of stroke, and worsens the outcome10-12). If SVD and prehospital delay are found to be associated, then SVD prevention itself could be helpful in preventing prehospital delay, and patients with severe SVD and their families could receive focused education prior to the onset of stroke.
Hence, we hypothesized that SVD is associated with prehospital delay. We performed a study using the total SVD score, a well-established severity score for SVD13, 14). The total SVD score is defined as the sum of the grades for the 4 items of old lacunes, white matter hyperintensity (WMH), cerebral microbleeds (CMBs), and enlarged perivascular spaces (EPVS) in the basal ganglia. The aim of this study was to evaluate the association between total SVD score and prehospital delay and to investigate which items of the total SVD score would be associated with prehospital delay.
2. Methods
2.1. Patient Selection
Patients were selected from the Jikei University School of Medicine Stroke Registry (Jikei Stroke Registry), a prospective database of patients with acute stroke who were admitted to Jikei University Hospital, a tertiary medical center in the Tokyo metropolitan area. Consecutive patients with ischemic stroke were retrospectively screened between October 2012 and February 2022.
We included patients who had arrived at our hospital within 14 days from the definite symptom onset or the last known well time15, 16). The exclusion criteria were: 1) in-hospital onset of ischemic stroke and 2) inability to evaluate the total SVD score.
Patients who arrived at our hospital within 4.5 hours from the definite symptom onset or the last known well time were classified into the early arrival group, and those who arrived more than 4.5 hours afterwards were classified into the delayed arrival group1, 6, 8). This article follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.
2.2. Clinical Characteristics
Baseline data included sex, age, mRS score before onset, definite symptom onset or last known well time, nighttime stroke onset (defined as onset between 7 p.m. and 7 a.m.)17), direct use of emergency medical services (EMS)7, 18), use of antiplatelet drugs before admission, use of anticoagulants before admission, comorbidities and risk factors for stroke, history of stroke, body mass index, NIHSS score at admission, impaired consciousness defined as score of more than one point in items 1a–c of the NIHSS, laboratory data (hemoglobin, creatinine, total protein, albumin, plasma glucose, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, glycosylated hemoglobin, brain natriuretic peptide), location of ischemic lesions on MRI (limited to anterior circulation, posterior circulation, or both), ischemic stroke subtype (cardioembolism, large artery atherosclerosis, small vessel occlusion, others19), and transient ischemic attack), total SVD score13, 14) based on SVD markers20), and mRS score 3 months after the onset.
The following comorbidities and risk factors for stroke were evaluated: 1) atrial fibrillation diagnosed before or during hospitalization; 2) hypertension, defined as the use of antihypertensive agents before admission or a history of diagnosis of hypertension but not on any medication; 3) diabetes mellitus, defined as the use of oral hypoglycemic agents or insulin, or performing dietary therapy before admission, a history of diagnosis of diabetes but not on any medication, or glycosylated hemoglobin level (National Glycohemoglobin Standardization Program) ≥ 6.5% on admission; 4) dyslipidemia, defined as the use of cholesterol-lowering drugs or performing diet therapy before admission,z a history of diagnosis of hypercholesterolemia but not on any medication, or serum LDL-cholesterol level ＞140 mg/dL on admission; 5) current smoking; and 6) excessive alcohol intake defined as daily alcohol consumption ＞60 g.
2.3. SVD Markers and Total SVD Score
The following SVD markers were used in the present study: presence of old lacunes, WMH scale (scored separately as periventricular hyperintensity [PVH] and deep and subcortical white matter hyperintensity [DSWMH])21), the number of CMBs, and severity of EPVS22, 23). Old lacune was defined as a round or ovoid hypointense area with a hyperintense rim on FLAIR imaging or as a hyperintense area on T2-weighted imaging (T2WI) of 3–15 mm20) in the following sites: deep subcortical white matter including the corona radiata, caudate head, lentiform, posterior limb and genu of the internal capsule, thalamus, or brainstem including the midbrain, pons and medulla24). PVH and DSWMH were evaluated using the Fazekas grading scale, as modified by Shinohara (separately rating the deep and periventricular regions on a scale ranging from 0 to 4) for lesions showing hyperintensity on FLAIR imaging20, 21). CMBs were defined as small voids having a hypointense area of 2–10 mm in diameter that were visible on susceptibility-weighted imaging (SWI)25). EPVS was defined as high-linear intensity on T2WI or low-linear intensity on FLAIR in the basal ganglia and centrum semiovale20, 26). The severity of EPVS in the basal ganglia was graded according to the number of EPVS observed, as follows: grade 0, no EPVS; grade 1, 1–10 EPVS; grade 2, 11–20 EPVS; grade 3, 21–40 EPVS; and grade 4, ≥ 41 EPVS (Fig.1)27). Total SVD score was calculated as the sum of points for each of the following four imaging findings (each scored as 1 point): ≥ 1 old lacunes, the presence of WMH (periventricular: Fazekas grade 3 and/or deep white matter: Fazekas grade 2–3), ≥ 1 CMBs, and ≥ 11 basal ganglia EPVS (EPVS grade ≥ 2). The maximum (most severe) score was 4.
The MRI platforms used in this study were the 1.5 T. Sequence parameters for diffusion weighted images (DWI) were: repetition time (TR), 2700 ms; echo time (TE), 90 ms; matrix, 128×128; and field of view (FOV), 21 cm. Sequence parameters for T2 were as follows: TR, 4070 ms; echo time (TE), 92 ms; matrix, 232×320; field of view (FOV), 22 cm. The sequence parameters for FLAIR were as follows: TR, 8000 ms; TE, 103 ms; matrix, 256×256; and FOV, 21 cm. The sequence parameters for SWI were as follows: TR, 49 ms; TE, 40 ms; matrix, 256×230; and FOV, 23 cm. The sequence parameters for MRA were as follows: TR, 23 ms; TE, 7.15 ms; matrix, 320×288; and FOV, 18 cm. We also used a MAGNETOM Skyra system (Siemens, Forchheim, Germany) at 3.0 T. With this machine, the sequence parameters for DWI were TR=5000 ms, TE=65 ms, matrix=160×160, and FOV=22 cm. The sequence parameters for T2 imaging were as follows: TR, 4500 ms; TE, 87 ms; matrix, 256×256; and FOV, 22 cm. The sequence parameters for FLAIR imaging were as follows: TR, 9000 ms; TE, 103 ms; matrix, 192×384; and FOV, 21 cm. The sequence parameters for SWI imaging were as follows: TR=28 ms, TE=20 ms, matrix=200×320, and FOV=24 cm. The sequence parameters for MRA were as follows: TR, 21 ms; TE, 3.69 ms; matrix, 202×320; and FOV, 18 cm.
2.5. Statistical Analysis
Clinical characteristics were compared between the early and delayed arrival groups using the χ2 test or Mann–Whitney U test, as appropriate.
Multivariable logistic regression with the forced entry method was performed to assess whether the total SVD score was associated with prehospital delay. The analysis was adjusted for sex, age, and the following pre-specified risk factors for prehospital delay: mRS score before onset1, 5), NIHSS score at admission5, 6), nighttime onset5, 6), direct EMS use7, 18), impaired consciousness7, 8), and ischemic stroke in the anterior circulation5, 9).
Multivariable logistic regression was performed to determine which items of the total SVD score were associated with prehospital delay. This multivariable logistic regression analysis with the forced entry method was adjusted for sex, age, and the components of the total SVD score (p＜0.05) in the above univariable analysis comparing 2 groups and above-mentioned prespecified risk factors for prehospital delay.
Next, we aimed to check the linear association between prehospital delay and the items of the total SVD score related to prehospital delay, which were revealed in the multivariable analyses. We generated indicator variables for items of the total SVD score that were related to prehospital delay and built another logistic regression model that included these indicator variables, with adjustment for sex, age, and the prespecified risk factors for prehospital delay, as mentioned above.
We also performed sensitivity analyses excluding patients with transient ischemic attack (139 patients in the early arrival group and 75 patients in the delayed arrival group) because patients with transient ischemic attack tended to have a lower SVD burden in comparison to patients with other subtypes of ischemic stroke28). The same model was used to perform the 3 above-mentioned multivariable analyses.
In addition, we also performed a stratified analysis for 2 major SVD risk factors (age ＞60 years and hypertension) to examine the interaction between these factors and the total SVD score between the early and delayed arrival groups29, 30). In these analyses, we analyzed whether the total SVD score was associated with prehospital delay in each group, with adjustment for sex, age, and the above-mentioned pre-specified risk factors for prehospital delay.
To avoid multicollinearity among the independent variables, we checked the variable inflation factors (VIF) among the variables. Only 1 variable was entered into the multivariable regression modelling procedure for variables that were highly correlated (VIF ≥ 10). Statistical significance was set at P＜0.05. All statistical analyses were performed using IBM SPSS Statistics version 25 (IBM-Armonk, Armonk, NY, USA) and ESUMI (ESUMI CO., Ltd., Tokyo, Japan).
2.5. Standard Protocol Approvals and Registrations
The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki. The Regional Ethics and Hospital Management Committee of the Jikei University School of Medicine approved the study from the Jikei Stroke Registry (approval Nos. 29-195 (8811), 29-196 (8812), and 29-197 (8813)). The board waived the need for patient consent and instead made arrangements to give the patients from whom data had been collected the opportunity to opt out of this study.
3. Results
Among the 1,754 patients with ischemic stroke, 649 (37%) arrived at the hospital within 4.5 hours of stroke onset (Fig.2). The median age of all patients was 69 years, and 71% of the patients were male.
The patient characteristics were compared between the early and delayed groups (Table 1). In the univariate analysis, the total SVD score was significantly associated with prehospital delay (p＜0.001). Fig.3 shows the proportion of patients with each total SVD score in the 2 groups. Among the 4 items comprising the total SVD score, all except CMBs were associated with prehospital delay (old lacunae, p=0.003; basal ganglia, p＜0.001; WMH, p=0.001).
Table 1.Clinical characteristics of acute ischemic stroke according to hospital arrival group
| Variable |
Total cohort
(n = 1,754)
|
Early arrival group
(n = 649)
|
Delayed arrival group
(n = 1,105)
|
p Value
|
| Male sex |
1,253 (71) |
483 (74) |
770 (70) |
0.034 |
| Age (years) |
69 (57–79) |
67 (55–77) |
70 (58–80) |
0.005 |
| mRS score before onset |
0 (0–0) |
0 (0–0) |
0 (0–0) |
0.202 |
| Onset-to-door time (hours) |
10.6 (2.1–35.5) |
1.4 (0.8–2.6) |
24.5 (12.0–57.5) |
＜0.001 |
| Nighttime onset |
761 (43) |
173 (27) |
588 (53) |
＜0.001 |
| Direct EMS use |
779 (44) |
435 (67) |
344 (31) |
＜0.001 |
| Use of antiplatelet drugs before admission |
418 (24) |
135 (21) |
283 (26) |
0.022 |
| Use of anticoagulants before admission |
180 (10) |
77 (12) |
103 (9) |
0.090 |
| Comorbidities and risk factors for stroke |
| Atrial fibrillation |
353 (20) |
162 (25) |
191 (17) |
＜0.001 |
| Hypertension |
1,188 (68) |
410 (63) |
778 (70) |
0.002 |
| Diabetes mellitus |
509 (29) |
161 (25) |
348 (32) |
0.003 |
| Dyslipidemia |
1,013 (58) |
356 (55) |
657 (60) |
0.060 |
| Current smoking |
478 (27) |
182 (28) |
296 (27) |
0.568 |
| Excessive alcohol intake |
91 (5) |
33 (5) |
58 (5) |
0.881 |
| History of any stroke |
415 (24) |
159 (25) |
256 (23) |
0.526 |
| Body mass index (kg/m2)
|
23.6 (21.1–25.9) |
23.4 (20.9–25.7) |
23.6 (21.3–26.0) |
0.447 |
| NIHSS score at admission |
2 (1–4) |
2 (0–6) |
2 (1–4) |
0.029 |
| Impaired consciousness |
324 (19) |
150 (23) |
174 (16) |
0.034 |
| Laboratory data |
| Hemoglobin (g/dL) |
14.2 (12.7–15.3) |
14.2 (12.7–15.3) |
14.2 (12.7–15.4) |
0.820 |
| Creatinine (mg/dL) |
0.83 (0.69–1.02) |
0.84 (0.71–1.03) |
0.83 (0.67–1.02) |
0.079 |
| Total protein (g/dL) |
7.0 (6.6–7.4) |
7.0 (6.6–7.4) |
7.1 (6.7–7.4) |
0.028 |
| Albumin (g/dL) |
4.1 (3.7–4.3) |
4.1 (3.8–4.3) |
4.1 (3.7–4.3) |
0.613 |
| Plasma glucose (mg/dL) |
115.0 (101.0–142.0) |
119.0 (103.0–144.0) |
113.0 (99.8–141.0) |
0.003 |
| Triglycerides (mg/dL) |
108.5 (75.0–168.0) |
115.0 (77.8– 179.3) |
106.0 (74.0–162.0) |
0.054 |
| High-density lipoprotein cholesterol (mg/dL) |
57.0 (46.0–69.0) |
56.0 (46.0–69.0) |
57.0 (46.0–70.0) |
0.442 |
| Low-density lipoprotein cholesterol (mg/dL) |
119.0 (94.0–143.0) |
111.0 (90.0–138.0) |
122.0 (96.0–145.0) |
＜0.001 |
| Glycosylated hemoglobin (%) |
5.8 (5.5–6.3) |
5.8 (5.5–6.2) |
5.8 (5.5–6.4) |
0.006 |
| Brain natriuretic peptide (pg/mL) |
33.0 (12.8–92.5) |
32.5 (12.3–99.5) |
33.1 (13.2–88.3) |
0.767 |
| Ischemic lesion location |
| Limited to anterior circulation |
908 (52) |
320 (49) |
588 (53) |
0.114 |
| Limited to posterior circulation |
469 (27) |
140 (22) |
329 (30) |
＜0.001 |
| Both |
151 (9) |
43 (7) |
108 (10) |
0.023 |
| Ischemic stroke subtype |
| Cardioembolism |
327 (19) |
140 (22) |
187 (17) |
0.016 |
| Large artery atherosclerosis |
185 (11) |
69 (11) |
116 (11) |
0.930 |
| Small vessel occlusion |
242 (14) |
52 (8) |
190 (17) |
＜0.001 |
| Other |
786 (45) |
249 (38) |
537 (49) |
＜0.001 |
| Transient ischemic attack |
214 (12) |
139 (21) |
75 (7) |
＜0.001 |
| Total SVD score |
2 (1–3) |
2 (1–3) |
2 (1–4) |
＜0.001 |
| Score for old lacunes |
1,010 (58) |
344 (53) |
666 (60) |
0.003 |
| Score for WMH |
807 (46) |
265 (41) |
542 (49) |
0.001 |
| Score for CMBs |
970 (55) |
349 (54) |
621 (56) |
0.324 |
| Score for basal ganglia EPVS |
915 (52) |
294 (45) |
621 (56) |
＜0.001 |
| mRS score 3 months after onset |
1 (0–2) |
1 (0–2) |
1 (0–2) |
0.100 |
Data are presented as medians (interquartile ranges) or numbers (%). CMBs, cerebral microbleeds; EMS, emergency medical services; EPVS, enlarged perivascular spaces; mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; SVD, small vessel disease; WMH, white matter hyperintensity.
In the multivariable analysis, the total SVD score was independently associated with prehospital delay (odds ratio (OR) 1.11, 95% confidence interval (CI) 1.01–1.21; p=0.025; Fig.4). In the multivariable analysis that included the 3 total SVD score items that with p values of ＜0.05, in the above univariate analysis, only basal ganglia EPVS was independently and significantly associated with prehospital delay (OR 1.37, 95% CI 1.05–1.80; p=0.022; Fig.5).
In multivariable logistic regression analysis of factors associated with prehospital delay using the EPVS grades as indicator variables, a linear trend was observed between EPVS grade and prehospital delay with reference to EPVS grade 0–1 (EPVS grade 2: OR 1.22, 95% CI 0.92–1.62, p=0.170; EPVS grade 3: OR 1.69, 95% CI 1.20–2.38, p=0.002; EPVS grade 4: OR 2.17, 95% CI 1.37–3.44, p=0.001; Fig.6)27, 31).
The results of the sensitivity analysis excluding patients with transient ischemic attacks were as follows: in the multivariable analysis, the total SVD score was still independently associated with prehospital delay (OR 1.12, 95% CI 1.01–1.23; p=0.026; Supplemental Table 1); in the multivariable analysis that included the 3 items of total SVD score with p values of ＜0.05 in a univariable analysis, the basal ganglia EPVS showed a tendency toward an association (OR 1.33, 95% CI 0.99–1.79, p=0.057; Supplemental Table 2); and in the multivariable logistic regression analysis of factors associated with prehospital delay using the EPVS grades as indicator variables, a linear trend was still observed between EPVS grade and prehospital delay with reference to EPVS grade 0–1 (EPVS grade 2: OR 1.20, 95% CI 0.88–1.63, p=0.246; EPVS grade 3: OR 1.56, 95% CI 1.08–2.26, p=0.017; EPVS grade 4: OR 2.29, 95% CI 1.39–3.78, p=0.001; Supplemental Table 3).
Supplemental Table 1.Logistic regression analysis of factors associated with prehospital delay in the group excluding patients diagnosed with transient ischemic stroke
|
Crude |
Multivariable |
| OR |
95% CI |
p value
|
OR |
95% CI |
p value
|
| Male |
0.79 |
0.62 to 1.00 |
0.053 |
0.72 |
0.54 to 0.96 |
0.026 |
| Age/10 (years) |
1.09 |
1.01 to 1.17 |
0.027 |
1.12 |
1.01 to 1.24 |
0.031 |
| mRS score before onset |
1.03 |
0.93 to 1.13 |
0.604 |
1.08 |
0.96 to 1.22 |
0.201 |
| Nighttime onset |
3.36 |
2.66 to 4.24 |
＜0.001 |
4.33 |
3.33 to 5.62 |
＜0.001 |
| Direct EMS use |
0.22 |
0.18 to 0.28 |
＜0.001 |
0.20 |
0.15 to 0.26 |
＜0.001 |
| NIHSS score at admission /10 |
0.53 |
0.45 to 0.63 |
＜0.001 |
0.53 |
0.41 to 0.69 |
＜0.001 |
| Impaired consciousness |
0.51 |
0.40 to 0.66 |
＜0.001 |
1.14 |
0.76 to 1.72 |
0.520 |
| Lesion in anterior circulation |
0.95 |
0.76 to 1.20 |
0.685 |
1.07 |
0.82 to 1.39 |
0.622 |
| Total SVD score |
1.16 |
1.07 to 1.24 |
＜0.001 |
1.12 |
1.01 to 1.23 |
0.026 |
Adjusted for sex, age, total SVD score and the prespecified factors for prehospital delay1, 5-9, 18).
CI, confidence interval; EMS, emergency medical services; mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; OR, odds ratio; SVD, small vessel disease.
Supplemental Table 2.Logistic regression analysis of factors associated with prehospital delay including items of the total small vessel disease score in the group excluding patients diagnosed with transient ischemic stroke
|
Crude |
Multivariable |
| OR |
95% CI |
p value
|
OR |
95% CI |
p value
|
| Male |
0.79 |
0.62 to 1.00 |
0.053 |
0.72 |
0.54 to 0.96 |
0.026 |
| Age/10 (years) |
1.09 |
1.01 to 1.17 |
0.027 |
1.11 |
1.00 to 1.22 |
0.054 |
| mRS score before onset |
1.03 |
0.93 to 1.13 |
0.604 |
1.08 |
0.96 to 1.22 |
0.201 |
| Nighttime onset |
3.36 |
2.66 to 4.24 |
＜0.001 |
4.34 |
3.34 to 5.65 |
＜0.001 |
| Direct EMS use |
0.22 |
0.18 to 0.28 |
＜0.001 |
0.20 |
0.15 to 0.26 |
＜0.001 |
| NIHSS score at admission /10 |
0.53 |
0.45 to 0.63 |
＜0.001 |
0.54 |
0.41 to 0.70 |
＜0.001 |
| Impaired consciousness |
0.51 |
0.40 to 0.66 |
＜0.001 |
1.14 |
0.76 to 1.72 |
0.522 |
| Lesion in anterior circulation |
0.95 |
0.76 to 1.20 |
0.685 |
1.07 |
0.82 to 1.40 |
0.617 |
| Lacune |
1.39 |
1.12 to 1.73 |
0.003 |
1.05 |
0.79 to 1.40 |
0.727 |
| WMH |
1.37 |
1.11 to 1.70 |
0.004 |
1.14 |
0.85 to 1.54 |
0.374 |
| EPVS |
1.55 |
1.25 to 1.92 |
＜0.001 |
1.33 |
0.99 to 1.79 |
0.057 |
Adjusted for sex, age, items with SVD score p＜0.05 in the univariable analysis regarding prehospital delay and the prespecified factors for prehospital delay1, 5-9, 18).
CI, confidence interval; EMS, emergency medical services; EPVS, enlarged perivascular spaces; mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; OR, odds ratio; WMH, white matter hyperintensity.
Supplemental Table 3.Logistic regression analysis regarding prehospital delay using EPVS grade as the indicator variable in the group excluding patients diagnosed with transient ischemic stroke
|
Crude |
Multivariable |
| OR |
95% CI |
p value
|
OR |
95% CI |
p value
|
| EPVS grade 0-1 |
0.65 |
0.52 to 0.80 |
＜0.001 |
1.00 |
- |
- |
| EPVS grade 2 |
1.01 |
0.79 to 1.29 |
0.920 |
1.30 |
0.88 to 1.63 |
0.246 |
| EPVS grade 3 |
1.49 |
1.11 to 1.98 |
0.007 |
1.56 |
1.08 to 2.26 |
0.017 |
| EPVS grade 4 |
1.87 |
1.25 to 2.79 |
0.002 |
2.29 |
1.39 to 3.78 |
0.001 |
To check the linear association between prehospital delay and EPVS grades, we built another logistic regression model that included EPVS grades taking EPVS grade 0–1 as the reference, 29,33 also adjusted for sex, age, and the prespecified factors for prehospital delay1, 5-9, 18).
CI, confidence interval; EPVS, enlarged perivascular spaces; OR, odds ratio.
In a stratified analysis by age, we found a significant association between a higher total SVD score and prehospital delay in patients of ≥ 60 years and of age (OR 1.13, 95% CI 1.01-1.25, p=0.026), whereas no significant association was observed in patients of ＜60 years of age (OR 1.05, 95% CI 0.88-1.25, p=0.600). In a stratified analysis by hypertension, we found a significant association between a higher total SVD score and prehospital delay in the hypertensive group (OR 1.11, 95% CI 1.00–1.24, p=0.049), while no significant association was observed in the non-hypertensive group (OR 1.05, 95% CI 0.88–1.24, p=0.611).
4. Discussion
The major finding of this study was that the total SVD score was associated with prehospital delay in patients with acute ischemic stroke. Furthermore, among the 4 items comprising the total SVD score, only basal ganglia EPVS was independently and significantly associated with prehospital delay, and a linear trend was observed between EPVS grade and prehospital delay with reference to EPVS grades 0–1. These results might provide new insights into the relationship between SVD and prehospital delay and the mechanisms of prehospital delay in patients with SVD.
Several previous studies have reported that high mRS scores before onset and nighttime onset were positively associated with delayed arrival of stroke patients to the hospital, whereas a negative association was found for high NIHSS score at admission, direct EMS use, impaired consciousness, and ischemic stroke in the anterior circulation1, 5-9, 18). However, there have been few investigations regarding a possible correlation between SVD and prehospital delay. The distinctive feature of the present study is that we scrutinized the relationship between each SVD item and prehospital delay in detail, in addition to evaluating the sum effect of SVD on prehospital delay using the total SVD score. Our insights may be helpful in identifying the clinical significance of SVD in relation to prehospital delay, potentially playing a crucial role in decreasing such delay.
We believe that executive dysfunction, a type of higher brain dysfunction, is a key factor that explains the correlation between a high total SVD score and prehospital delay, regarding the underlying mechanism. SVD is associated with cognitive dysfunction and is particularly likely to impair higher brain dysfunction, such as the executive function32-34). Patients with executive dysfunction have difficulty in making appropriate decisions35). Delayed decision-making has been reported to be associated with prehospital delay in stroke36), which supports the present result of an association of high total SVD score with prehospital delay.
Our second finding was that, among the 4 items of the total SVD score, only basal ganglia EPVS was associated with prehospital delay. This result could be attributed to disturbance in the circuit between the basal ganglia and the frontal lobe, which is an essential neurological pathway for maintaining a normal executive function37). The basal ganglia are a major component of this pathway (termed frontal-subcortical circuits), which consists of 5 different circuits38, 39). Among the 5 circuits of the pathway, the dorsolateral prefrontal circuit loops through the caudate nucleus and globus pallidus and is highly responsible for controlling the executive function39). Indeed, previous reports have indicated that EPVS in the basal ganglia may disturb the basal ganglia function and that executive dysfunction worsens with increasing severity of EPVS34, 37). These studies suggest that a linear trend was observed between the EPVS grade and prehospital delay. Hence, EPVS damages the function of the basal ganglia and disturbs the dorsolateral prefrontal circuit, leading to executive dysfunction and resulting in prehospital delay.
Our findings have several clinical implications, and suggest directions for future research. First, although patients with an SVD burden are known to have an unfavorable prognosis in ischemic stroke40), this study also emphasized the importance of SVD prevention from the viewpoint of avoiding prehospital delay. Second, regarding patient education from the perspective of preventing delayed arrival after stroke, it is important to focus on those in the general population who would benefit the most from stroke education. Targeting education at high-risk people would also contribute to improving healthcare economics. Our results suggest that a high total SVD score, especially in those who demonstrate a severe basal ganglia EPVS burden, is a simple and useful indication that individuals should be intensively educated to avoid prehospital delay before developing symptomatic stroke. Stratified analyses indicated that elderly and hypertensive patients with higher SVD scores were significantly more likely to experience prehospital delays. These findings suggest that these factors should also be considered when selecting target populations for education. Finally, in future work, it would be of great interest to conduct a prospective study to clarify whether SVD prevention or intensive education in people with an SVD burden could reduce prehospital delay. In addition, it would be interesting to study whether and how the cognitive function prior to the onset of stroke and the SVD burden are related to prehospital delays.
The key strengths of this study are the relatively large sample size and the strict review of MRI to identify SVD items in all participants. This study also had several limitations. First, as described above, cognitive impairment, especially executive dysfunction and attention impairment due to SVD burden, is a key mechanism of prehospital delay. However, we were not able to assess the patients’ cognitive function prior to the onset of stroke and we were not able to accurately collect information on their history of dementia and mild cognitive impairment. Therefore, a prospective study is necessary to confirm this hypothesis. Second, we were unable to obtain various factors that would have affected the onset-to-door time: whether the patient lived alone or in an institution, whether they had health insurance, whether the patient had knowledge of ischemic stroke, and the period between the initial call to EMS and transportation of the patient to the hospital. We adjusted for these factors in the statistical analyses. Third, the results of the analysis of the original data may have been influenced by the inclusion of patients with transient ischemic attack, which usually has a lower SVD burden than other types of ischemic stroke. However, the results were generally similar in the analysis, excluding patients with transient ischemic attacks. Finally, the retrospective nature of the investigation and the fact that we included only Asian patients might have affected the results and limited their generalizability.
5. Conclusions
The total SVD score, especially the EPVS in the basal ganglia, could be related to prehospital delay in patients with acute ischemic stroke. Our results emphasize the clinical importance of SVD prior to the onset of stroke and provide clues for elucidating the biological mechanism of the delay and preventing further delays.
Acknowledgements
The authors thank FORTE Science Communications (https://www.forte-science.co.jp/) for the English language editing.
Notice of Grant Support
None.
Conflicts of Interest
Mitsumura H reports grants/research funding from JSPS KAKENHI.
Iguchi Y reports personal fees from Bayer Healthcare Co. Ltd.; grants and personal fees from Pfizer Japan Inc.; grants and personal fees from Nippon Boehringer Ingelheim Co. Ltd.; grants and personal fees from Takeda Pharmaceutical Co. Ltd.; grants and personal fees from Otsuka Pharmaceutical Co. Ltd.; and grants and personal fees from Daiichi Sankyo Co. Ltd.
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