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01.12.2017 | Research article | Ausgabe 1/2017 Open Access

BMC Neurology 1/2017

Development and validation of a score for evaluating comprehensive stroke care capabilities: J-ASPECT Study

Zeitschrift:
BMC Neurology > Ausgabe 1/2017
Autoren:
Akiko Kada, Kunihiro Nishimura, Jyoji Nakagawara, Kuniaki Ogasawara, Junichi Ono, Yoshiaki Shiokawa, Toru Aruga, Shigeru Miyachi, Izumi Nagata, Kazunori Toyoda, Shinya Matsuda, Akifumi Suzuki, Hiroharu Kataoka, Fumiaki Nakamura, Satoru Kamitani, Koji Iihara, the J-ASPECT Study Collaborators
Abbreviations
BC
Board-certified
CI
Confidence interval
CSC
Comprehensive stroke center
DPC
Diagnosis combination procedure
GCS
Glasgow coma scale
IA
Intracranial aneurysm
ICH
Intracerebral hemorrhage
IS
Ischemic stroke
ISAT
International subarachnoid trial
JCS
Japan coma scale
NIHSS
National institute of health stroke
OR
Odds ratio
PSC
Primary stroke center
SAH
Subarachnoid hemorrhage

Background

Stroke is the fourth leading cause of mortality and the most common cause of permanent morbidity in Japan, causing an enormous socioeconomic burden. The public health implications of stroke care globally, including in Japan, are profound. Despite accelerating progress in stroke therapy, implementation of appropriate acute treatment remains essential for decreasing the associated mortality and permanent morbidity. In 2000, the Brain Attack Coalition discussed the concept of primary stroke centers and later proposed the design of comprehensive stroke centers (CSCs) [1, 2]. Most stroke patients can be adequately treated at a primary stroke center (PSC), and the Joint Commission established programs for the certification and performance measurement of PSCs [3]. The concept and recommended key components of a CSC enable intensive patient care and the use of specialized techniques that are not available at most PSCs [1, 4]. To continuously monitor the efficiency of care, reliable measures of hospital capabilities and performance are needed. Although the Joint Commission and several US states have started certification processes for PSCs and CSCs [58], an established, simple scoring system does not exist to evaluate the comprehensive acute stroke care capabilities of CSCs. To this end, a simple tool for assessing CSC capabilities would be useful for monitoring service quality and enabling its improvement [4]. In 2010, we started the J-ASPECT study (Nationwide survey of Acute Stroke care capacity for Proper dEsignation of Comprehensive stroke cenTer in Japan) to establish optimal nationwide implementation of stroke centers to improve acute stroke outcomes. We modified the above recommendations to reflect the specific circumstances in Japan and developed a CSC score; this tool was validated using the nationwide Diagnosis Combination Procedure (DPC) database, created during the first year of this study.

Methods

Content validity

In the first step of the J-ASPECT study, we investigated the current conditions of stroke hospitals in Japan. We created a 49-item questionnaire examining various aspects of stroke care, including medical systems, emergency systems, stroke rehabilitation, education, and medical performance. Some recommended items, such as ventriculostomy availability, were excluded from our questionnaire for the sake of simplicity and to increase the survey response rate since the items seemed identical to the recommendations of board-certified (BC) neurosurgeons in Japan. Other items, such as availability of transesophageal echocardiography, were excluded because of their very low expected usage, which would make an evaluation of their impact on mortality rates difficult. In February 2011, the questionnaire was mailed to 1369 certified training institutions belonging to the Japan Neurosurgical Society, the Japanese Society of Neurology, and the Japan Stroke Society. Based on this questionnaire, the overall organizational and staffing levels of the hospitals, in terms of CSC capacity, were scored following the Brain Attack Coalition recommendations, after reviewing the literature describing CSCs and conducting a thorough discussion with an expert panel [9]. Advanced acute stroke care capabilities were assessed based on 25 items divided into 5 subcategories (listed in Table 1). One point was assigned for each recommended item that the hospital met, resulting in a maximum total score of 25; subcategory scores were also calculated.
Table 1
The availability of comprehensive stroke center score components
Components
Items
Item No
Number
Percent
Personnel
Neurologists
1
358
47.8
Neurosurgeons
2
694
92.7
Endovascular physicians
3
272
36.3
Critical care medicine
4
162
21.6
Physical medicine and rehabilitation
5
113
15.1
Rehabilitation therapy
6
742
99.1
Stroke rehabilitation nurses
7
102
13.6
Diagnostics (24/7)
CTa
8
742
99.1
MRIb with diffusion
9
647
86.4
Digital cerebral angiography
10
602
80.4
CT angiography
11
627
83.7
Carotid duplex ultrasound
12
257
34.3
TCDc
13
121
16.2
Specific expertise
Carotid endarterectomy
14
603
80.5
Clipping of intracranial aneurysm
15
685
91.5
Hematoma removal/draining
16
689
92.0
Coiling of intracranial aneurysm
17
360
48.1
Intra-arterial reperfusion therapy
18
498
66.5
Infrastructure
Stroke unit
19
132
17.6
Intensive care unit
20
445
59.4
Operating room staffed 24/7
21
451
60.2
Interventional services coverage 24/7
22
279
37.2
Stroke registry
23
235
31.4
Education
Community education
24
369
49.3
Professional education
25
436
58.2
acomputed tomography; bmagnetic resonance imaging; ctranscranial Doppler

Consistency

Cronbach’s α was calculated to evaluate the consistency between the 5 CSC score subcategories used for assessing CSC capabilities. To determine the influence of each subcategory, α-values were also calculated for all combinations of the four subcategories. Correlations between the 25 CSC score items were determined using tetrachoric correlation coefficients to evaluate individual items measured with different constructs.

Construct validity

Factorial analysis, based on tetrachoric correlation coefficients [10], was performed using principal factor analysis to explore possible potential groupings of the 25 items into a more limited number of components. The selection of the number of components was based on the Eigen values. To understand the meaning of the components, promax rotation was used.

Predictive validity

Using the Japanese DPC database for patients hospitalized with strokes during the 2011 fiscal year, we examined the differential effects of the items on mortality and poor outcomes (modified Rankin Scale: 3–6, at discharge) associated with ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). This cross-sectional survey used the DPC discharge database for the institutions participating in the J-ASPECT study. The DPC database is a mixed-case classification system that is linked with the lump-sum payment system, launched in 2002 by the Ministry of Health, Labor and Welfare of Japan [11]. In 2010, approximately 1388 acute care hospitals, representing about 50% of the total hospital beds, had adopted the DPC data system. Data regarding practices were obtained from the DPC database; the attending physician is responsible for each patient’s clinical data entry. The details of this database have been described elsewhere [12].
Of the 749 hospitals that responded to the institutional survey of advanced stroke care capabilities, 256 agreed to participate in the DPC discharge database study. Consecutive patients, hospitalized between April 1, 2010 and March 31, 2011, were identified in the annual discharge database using the International Classification of Diseases (ICD)-10 diagnosis codes related to IS (I63.0-9), nontraumatic ICH (I61.0-9, I62.0-1, I62.9), and SAH (I60.0-9). Patients with scheduled admissions were excluded from analysis. This research was approved by the Institutional Review Board of the National Cerebral and Cardiovascular Center and, if required, by the participating hospitals.
We used hierarchical logistic regression models to determine relationships between hospital CSC scores, reflecting the capacities they were equipped with, and mortality. Each model had two levels of hierarchy (hospital and patient), and considered the random effects of hospital variables as well as the fixed effects of CSC scores, patient age and sex, and Japan Coma Scale (JCS) scores. Interactions such as those between the JCS and CSC scores were not included in the model. The analyses were performed using SAS, version 9.3 (SAS Institute, Cary, NC, USA), and R, version 3.2.0 (R Core Team, R Foundation for Statistical Computing, Vienna, Austria).

Results

Of the selected 1369 certified training institutions, 749 (55%) responded to the acute stroke care capability survey. Among the surveyed hospitals, 62% had more than 300 beds, and 51% had more than 200 acute patients (Table 2). Clipping of intracranial aneurysms (IAs) was performed more frequently than any other procedure (median/hospital, 15), followed by craniotomy removal of ICH (6), intravenous infusion of recombinant tissue plasminogen activator (5), and coiling of IAs (3). The availability of each item is shown in Table 1. Even within the same component, the availability of each item varied. Low availability values were noted for IA coiling (48.1%) in the specific expertise component and for stroke units (17.6%) in the infrastructure component.
Table 2
Hospital characteristics
Beds per hospital, n (%)
 20–49
16 (2.1)
 50–99
30 (4.0)
 100–299
232 (31.0)
 300–499
260 (34.7)
  > 500
207 (27.6)
 Unknown
4 (0.5)
Acute stroke patients per hospital, n (%)
  ≤ 49
51 (6.8)
 50–99
78 (10.4)
 100–199
199 (26.6)
 200–299
155 (20.7)
  > 300
228 (30.4)
 Unknown
38 (5.1)
Treated patients per hospital, median (IQRa)
 Tissue plasminogen activator
5 (2–10)
 Intra-arterial thrombolysis/percutaneous angioplasty
0 (0–2)
 Carotid endarterectomy
1 (0–4)
 Carotid stenting
1 (0–7)
 Extracranial-intracranial bypass surgery
1 (0–5)
 Clipping of intracranial aneurysm
15 (6–27)
 Coiling of intracranial aneurysm
3 (0–11)
 Craniotomy hematoma removal
6 (2–12)
 Stereotactic hematoma removal
0 (0–3)
 Endoscopic hematoma removal
0 (0–0)
ainterquartile range
The distribution of CSC score components, by hospital, is shown in Table 3. The median CSC score was 14 (interquartile range, 11–18). These components showed moderate consistency (Cronbach’s α = 0.765, for the total score). Removal of any one component resulted in Cronbach’s α falling in the range of 0.668–0.776, indicating the absence of substantial influence of individual components. High correlations between the survey components pertaining to personnel and specific expertise were observed (Table 4). For example, there were high correlations between neurosurgeon availability and carotid endarterectomy (r = 0.821; items 2 and 14), clipping of IAs (r = 0.936; items 2 and 15), and hematoma removal/drainage (r = 0.949; items 2 and 16). Similarly, endovascular physician availability was strongly correlated with coiling of IAs (r = 0.932; items 3 and 17) and intra-arterial reperfusion therapy (r = 0.842; items 3 and 18). Other relationships regarding diagnostics, infrastructure, and education did not stand out.
Table 3
The distribution of comprehensive stroke center score components and their consistency
Components
Mean
SD
Median
IQRa
Cronbach’s α
Personnel
3.26
1.25
3
2–4
0.724
Diagnostic
4.00
1.28
4
4–5
0.741
Specific expertise
3.79
1.48
4
3–5
0.668
Infrastructure
2.06
1.43
2
1–3
0.674
Education
1.07
0.83
1
0–2
0.776
Total Score
14.18
4.57
14
11–18
0.765
ainterquartile range
Table 4
Correlation coefficients between the 25 survey items
Item Noa
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
1
1.000
                        
2
-0.071
1.000
                       
3
0.201
0.671
1.000
                      
4
0.282
0.243
0.244
1.000
                     
5
0.520
0.063
0.259
0.476
1.000
                    
6
0.334
0.282
0.239
-0.190
0.140
1.000
                   
7
0.171
0.072
0.248
0.054
0.117
0.125
1.000
                  
8
0.300
0.451
0.265
0.202
0.037
0.392
0.007
1.000
                 
9
-0.018
0.500
0.325
0.054
-0.025
0.043
0.047
0.636
1.000
                
10
-0.027
0.827
0.490
0.255
0.058
0.132
-0.005
0.616
0.594
1.000
               
11
-0.132
0.701
0.264
0.201
-0.050
0.017
0.055
0.632
0.614
0.830
1.000
              
12
0.120
0.215
0.118
0.198
0.016
-0.196
0.158
0.306
0.357
0.332
0.295
1.000
             
13
0.155
0.435
0.361
0.156
0.036
-0.142
0.102
0.194
0.287
0.492
0.372
0.713
1.000
            
14
0.095
0.821
0.639
0.238
0.155
0.234
0.138
0.281
0.363
0.694
0.492
0.196
0.305
1.000
           
15
0.029
0.936
0.669
0.208
0.073
0.253
0.123
0.414
0.405
0.840
0.675
0.253
0.521
0.885
1.000
          
16
0.010
0.949
0.709
0.227
0.053
0.263
0.105
0.431
0.429
0.831
0.663
0.256
0.512
0.865
0.987
1.000
         
17
0.215
0.648
0.932
0.283
0.270
0.228
0.373
0.262
0.288
0.486
0.243
0.220
0.386
0.648
0.695
0.729
1.000
        
18
0.092
0.784
0.842
0.209
0.226
0.215
0.289
0.234
0.407
0.646
0.391
0.247
0.418
0.754
0.793
0.821
0.874
1.000
       
19
0.185
0.378
0.277
0.109
0.045
0.049
0.373
0.197
0.333
0.340
0.193
0.206
0.260
0.345
0.408
0.395
0.307
0.357
1.000
      
20
0.154
0.358
0.256
0.237
0.086
-0.230
0.012
0.451
0.197
0.416
0.374
0.187
0.229
0.325
0.403
0.416
0.265
0.243
0.291
1.000
     
21
0.291
0.599
0.603
0.205
0.155
0.314
0.180
0.484
0.287
0.583
0.429
0.193
0.386
0.714
0.756
0.718
0.564
0.515
0.443
0.382
1.000
    
22
0.273
0.515
0.912
0.226
0.218
0.229
0.376
0.347
0.277
0.464
0.224
0.217
0.400
0.538
0.594
0.626
0.895
0.762
0.321
0.283
0.697
1.000
   
23
0.203
0.314
0.360
0.145
0.210
0.014
0.213
0.059
0.342
0.357
0.253
0.287
0.406
0.373
0.425
0.451
0.385
0.405
0.381
0.165
0.369
0.362
1.000
  
24
0.193
0.346
0.298
0.080
0.134
0.188
0.104
0.179
0.219
0.234
0.079
0.249
0.414
0.266
0.337
0.334
0.293
0.314
0.408
0.174
0.303
0.344
0.315
1.000
 
25
0.038
0.425
0.230
0.025
0.073
-0.114
0.055
0.012
0.312
0.292
0.260
0.193
0.289
0.373
0.422
0.395
0.267
0.359
0.417
0.101
0.282
0.221
0.311
0.576
1.000
aItem No in Table 1
Factorial analysis, based on promax rotation, revealed four constructs (Table 5). The first pattern contained items pertaining to neurovascular surgery and intervention, such as endovascular physician availability, coiling of IAs, intra-arterial reperfusion therapy, 24/7 interventional services coverage, carotid endarterectomy, hematoma removal/drainage, clipping of IAs, neurosurgeon availability, rehabilitation therapy, 24/7 operating room staffing, and stroke rehabilitation nurse availability. The first pattern had the largest explained variance (43% of total variance). The second pattern included imaging modalities mainly associated with diagnostic neuroradiology (e.g., computed tomography, computed tomography angiography, digital cerebral angiography, and diffusion-weighted magnetic resonance imaging) and intensive care units. The third pattern contained items related to vascular neurology: transcranial Doppler, carotid duplex ultrasound, professional education, community education, stroke registry, and available stroke units. The fourth pattern represented neurocritical care and rehabilitation, and included the availability of neurologists, physical medicine and rehabilitation, and critical care medicine.
Table 5
Factor analysis
  
Factor 1
Factor 2
Factor 3
Factor 4
  
Neurovascular surgery and intervention
Diagnostic neuroradiology
Vascular neurology
Neurocritical care and rehabilitation
 
Proportion explained
0.43
0.25
0.19
0.14
Item No
Items
Standardized loadings (pattern matrix)
  
3
Endovascular physicians
0.91 d
-0.07
-0.04
0.12
17
Coiling of intracranial aneurysm
0.89
-0.11
0.04
0.15
18
Intra-arterial reperfusion therapy
0.88
0.00
0.10
-0.05
22
Interventional services coverage 24/7
0.80
-0.09
0.05
0.23
14
Carotid endarterectomy
0.76
0.24
-0.01
-0.10
16
Hematoma removal/draining
0.75
0.37
0.06
-0.16
15
Clipping of intracranial aneurysm
0.73
0.37
0.08
-0.16
2
Neurosurgeons
0.69
0.43
0.02
-0.22
6
Rehabilitation therapy
0.59
0.07
-0.63
0.18
21
Operating room staffed 24/7
0.59
0.28
0.00
0.18
7
Stroke rehabilitation nurses
0.34
-0.36
0.21
0.20
8
CTa
-0.03
0.89
-0.21
0.34
11
CT angiography
0.08
0.84
0.06
-0.17
10
Digital cerebral angiography
0.36
0.70
0.08
-0.10
9
MRIb with diffusion
0.03
0.59
0.23
-0.06
20
Intensive care unit
-0.06
0.50
0.17
0.22
13
TCDc
0.02
0.15
0.71
0.04
12
Carotid duplex ultrasound
-0.31
0.26
0.72
0.16
25
Professional education
0.23
-0.15
0.63
-0.23
24
Community education
0.21
-0.17
0.56
0.07
23
Stroke registry
0.24
-0.08
0.52
0.10
19
Stroke unit
0.23
-0.05
0.49
0.06
1
Neurologists
-0.02
-0.02
0.02
0.85
5
Physical medicine and rehabilitation
0.10
-0.09
0.00
0.72
4
Critical care medicine
-0.09
0.25
0.14
0.55
acomputed tomography; bmagnetic resonance imaging; ctranscranial Doppler; dvalues > 0.300 are shown in bold font
A total of 53,170 patients in the cohort were analyzed; the in-hospital mortality was 7.8% for IS, 16.8% for ICH, and 28.1% for SAH (Table 6). Table 7 shows the impact of hospital capacity for each of the 25 items on mortality. Among the four constructs obtained using factorial analysis, the availability of neurologists in neurocritical care and rehabilitation was significantly associated with reduced mortality of patients with IS (P < 0.05). The 24/7 availability of interventional service coverage in neurovascular surgery and intervention (P < 0.05), availability of intensive care units in diagnostic neurology, and physical medicine and rehabilitation in neurocritical care and rehabilitation (P < 0.05) were related to SAH mortality. The total CSC score was related to the mortality associated with IS (OR, 0.973; 95% CI, 0.958–0.989), ICH (OR, 0.970; 95% CI, 0.950–0.990), and SAH (OR, 0.951; 95% CI, 0.925–0.977).
Table 6
Demographics of the patient cohort at diagnosis, mortality, and severe disability at discharge
 
Total
ISa
ICHb
SAHc
 
(n = 53170)
(n = 32671)
(n = 15699)
(n = 4934)
 
N
%
N
%
N
%
N
%
Male
29353
55.2
18816
57.6
9030
57.5
1584
32.1
Age (years)
 18–50
3515
6.6
1328
4.1
1271
8.1
927
18.8
 51–60
5824
11.0
2742
8.4
2171
13.8
934
18.9
 61–70
11744
22.1
6894
21.1
3640
23.2
1242
25.2
 71–80
15825
29.8
10342
31.7
4466
28.4
1048
21.2
 81–106
16262
30.6
11365
34.8
4151
26.4
783
15.9
Hypertension
39918
75.1
22531
69.0
13281
84.6
4229
85.7
Diabetes mellitus
13725
25.8
9318
28.5
3278
20.9
1174
23.8
Hyperlipidemia
15015
28.2
11104
34.0
2529
16.1
1412
28.6
Smoking (n = 44842)
12761
24.0
8188
25.1
3540
22.5
1074
21.8
Japan Coma Scale
 0
19635
36.9
15027
46.0
3620
23.1
1024
20.8
 1-digit code
19371
36.4
12375
37.9
5934
37.8
1117
22.6
 2-digit code
6937
13.0
3396
10.4
2705
17.2
852
17.3
 3 digit code
7227
13.6
1873
5.7
3440
21.9
1941
39.3
Emergency admission by ambulance
31995
60.2
17336
53.1
10909
69.5
3830
77.6
Mortality
6522
12.3
2535
7.8
2630
16.8
1384
28.1
Poor outcome (modified Rankin Scale 3–6) at discharge. (N = 51719)
28238
54.6
15566
49.2
10044
65.3
2721
56.4
aischemic stroke; bintracerebral hemorrhage; csubarachnoid hemorrhage
Table 7
The effect of items on mortality
Item
  
ISa
  
ICHb
  
SAHc
 
No
Items
(n = 32671)
(n = 15699)
(n = 4934)
  
ORd
95% CIe
OR
95% CI
OR
95% CI
3
Endovascular physicians
0.832
0.653
1.060
0.896
0.671
1.198
1.309
0.906
1.891
17
Coiling of intracranial aneurysm
1.062
0.832
1.355
1.075
0.797
1.451
0.982
0.667
1.444
18
Intra-arterial reperfusion therapy
1.155
0.931
1.434
0.919
0.706
1.194
0.854
0.608
1.201
22
Interventional services coverage 24/7
1.071
0.831
1.379
1.145
0.844
1.555
0.674j
0.458
0.992
14
Carotid endarterectomy
0.945
0.708
1.262
0.833
0.595
1.165
0.789
0.503
1.237
15 and 16
Clipping of intracranial aneurysm and hematoma removal/draining
0.798
0.465
1.368
0.537
0.266
1.088
0.359
0.082
1.564
2
Neurosurgeons
0.905
0.530
1.546
1.513
0.744
3.077
0.840
0.230
3.071
6
Rehabilitation therapy
1.000
  
1.000
  
1.000
  
21
Operating room staffed 24/7
0.986
0.826
1.176
0.956
0.769
1.187
1.217
0.921
1.610
7
Stroke rehabilitation nurses
1.021
0.831
1.253
1.019
0.803
1.293
1.074
0.803
1.436
8
CTf
0.963
0.208
4.462
0.515
0.035
7.590
1.000
  
11
CT angiography
1.127
0.877
1.449
0.820
0.608
1.107
0.978
0.662
1.446
10
Digital cerebral angiography
0.840
0.652
1.082
1.243
0.917
1.684
1.068
0.722
1.580
9
MRIg with diffusion
1.117
0.849
1.471
0.844
0.605
1.176
0.897
0.581
1.383
20
Intensive care unit
1.032
0.897
1.188
0.964
0.813
1.144
0.795j
0.640
0.988
13
TCDh
0.852
0.699
1.038
0.879
0.700
1.105
1.222
0.930
 
12
Carotid duplex ultrasound
1.039
0.889
1.215
1.021
0.849
1.228
1.119
0.891
1.406
25
Professional education
0.907
0.765
1.076
1.061
0.868
1.296
0.954
0.751
1.212
24
Community education
0.948
0.810
1.109
0.908
0.753
1.094
0.800
0.636
1.006
23
Stroke registry
0.895
0.781
1.026
0.861
0.732
1.013
0.915
0.749
1.118
19
Stroke unit
0.993
0.838
1.177
0.887
0.724
1.086
0.871
0.679
1.118
1
Neurologists
0.854j
0.742
0.982
1.043
0.881
1.234
1.110
0.901
1.367
5
Physical medicine and rehabilitation
1.025
0.844
1.245
0.976
0.777
1.225
0.746j
0.562
0.991
4
Critical care medicine
0.967
0.825
1.134
0.993
0.823
1.200
0.895
0.712
1.126
 
Total CSCi score
0.973j
0.958
0.989
0.970j
0.950
0.990
0.951j
0.925
0.977
aischemic stroke; bintracerebral hemorrhage; csubarachnoid hemorrhage; d OR odds ratio adjusted by hierarchical logistic model including patient age, sex, Japan Coma Scale scores, and hospital variables; e CI confidence interval; fcomputed tomography; gmagnetic resonance imaging; htranscranial Doppler; icomprehensive stroke center; j P < 0.05 (hierarchical logistic model)
The proportions of poor outcomes (modified Rankin Scale, 3–6) were 49.2% for IS, 65.3% for ICH, and 56.4% for SAH (Table 6). In contrast to mortality, the total CSC score was not significantly associated with poor outcomes in patients having any type of stroke (Table 8). The impact of hospital capacity for each of the 25 items on poor outcomes differed from that for mortality in some aspects. For example, among patients with IS, stroke unit availability were significantly associated with a reduced proportion of poor outcomes (P < 0.05). Among patients with ICH and SAH, no significant association was observed between the availability of any item and poor outcomes.
Table 8
The effect of items on poor outcome (modified Rankin Scale 3–6)
Item
  
ISa
  
ICHb
  
SAHc
 
No
Items
(n = 31640)
(n = 15391)
(n = 4821)
  
ORd
95% CIe
OR
95% CI
OR
95% CI
3
Endovascular physicians
1.180
0.890
1.563
0.896
0.671
1.198
1.267
0.856
1.875
17
Coiling of intracranial aneurysm
0.838
0.634
1.106
1.075
0.797
1.451
0.933
0.618
1.407
18
Intra-arterial reperfusion therapy
0.990
0.777
1.261
0.919
0.706
1.194
0.704
0.487
1.017
22
Interventional services coverage 24/7
0.969
0.725
1.295
1.145
0.844
1.555
0.928
0.615
1.400
14
Carotid endarterectomy
1.293
0.946
1.768
0.833
0.595
1.165
0.838
0.511
1.376
15 and 16
Clipping of intracranial aneurysm and hematoma removal/draining
0.763
0.427
1.364
0.537
0.266
1.088
0.553
0.065
4.693
2
Neurosurgeons
1.026
0.582
1.807
1.513
0.744
3.077
4.449
0.987
20.041
6
Rehabilitation therapy
1.000
.
.
1.000
.
.
1.000
.
.
21
Operating room staffed 24/7
0.883
0.723
1.078
0.956
0.769
1.187
0.959
0.712
1.290
7
Stroke rehabilitation nurses
0.874
0.693
1.101
1.019
0.803
1.293
0.877
0.641
1.200
8
CTf
1.328
0.296
5.956
0.515
0.035
7.590
1.000
.
.
11
CT angiography
1.227
0.931
1.617
0.820
0.608
1.107
0.877
0.579
1.329
10
Digital cerebral angiography
0.912
0.685
1.213
1.243
0.917
1.684
1.274
0.842
1.928
9
MRIg with diffusion
0.940
0.706
1.252
0.844
0.605
1.176
0.793
0.490
1.284
20
Intensive care unit
0.987
0.842
1.156
0.964
0.813
1.144
1.000
0.795
1.259
13
TCDh
0.966
0.773
1.208
0.879
0.700
1.105
1.152
0.858
1.547
12
Carotid duplex ultrasound
1.183
0.988
1.415
1.021
0.849
1.228
1.206
0.945
1.538
25
Professional education
0.892
0.737
1.079
1.061
0.868
1.296
1.015
0.782
1.317
24
Community education
1.144
0.957
1.368
0.908
0.753
1.094
0.871
0.680
1.116
23
Stroke registry
0.981
0.840
1.146
0.861
0.732
1.013
0.860
0.695
1.065
19
Stroke unit
0.783j
0.645
0.952
0.887
0.724
1.086
0.878
0.676
1.141
1
Neurologists
1.137
0.969
1.335
1.043
0.881
1.234
1.096
0.877
1.370
5
Physical medicine and rehabilitation
1.163
0.934
1.449
0.976
0.777
1.225
0.979
0.725
1.322
4
Critical care medicine
1.113
0.929
1.334
0.993
0.823
1.200
1.062
0.830
1.360
 
Total CSCi score
0.995
0.977
1.014
1.007
0.984
1.030
0.978
0.950
1.008
aischemic stroke; bintracerebral hemorrhage; csubarachnoid hemorrhage; d OR odds ratio adjusted by hierarchical logistic model including patient age, sex, Japan Coma Scale scores, and hospital variables; eCI: confidence interval; fcomputed tomography; gmagnetic resonance imaging; htranscranial Doppler; icomprehensive stroke center; j P < 0.05 (hierarchical logistic model)

Discussion

We evaluated the consistency and validity of the CSC score; based on the Cronbach’s α value of 0.765, the five components were moderately consistent [13]. The validity of the score was evaluated using factorial analysis, which revealed four major constructs. Although the four constructs were determined by the five components: personnel, diagnostic techniques, specific expertise, infrastructure, and education, this study showed a high correlation between the survey components pertaining to personnel and specific expertise. The unique fact that BC neurosurgeons comprise more than 95% of BC endovascular physicians, in Japan, may explain why personnel, specific expertise, and infrastructure components closely related to these different treatment aspects were grouped into the same construct (neurovascular surgery and intervention). Considering their influence on the variance of the CSC scores, temporal trends and geographical disparities focused on this construct may provide critical information for proper accreditation and implementation of CSCs.
With regard to the predictive validity of the CSC score, the four constructs had different effects on mortality and poor outcomes in patients with IS, ICH, and SAH. The availability of neurologists involved in neurocritical care and rehabilitation was significantly associated with reduced in-hospital morality in patients with IS. Recently, the treatment paradigm for acute IS has been changing rapidly, such that the critical role of endovascular intervention following tissue plasminogen activator infusion, for acute IS, has been established by several recent randomized controlled trials (MR Clean, ESCAPE, EXTEND-IA) [1416]. Of note, however, the acute stroke care survey used in this study and the DPC database were both implemented before these evidences were published in 2015. The availability of BC neurosurgeons at more than 90% of the participating hospitals suggests the importance of multidisciplinary acute stroke care [17].
The association between the availability of a stroke care unit and the increased proportion of favorable outcomes after IS, observed in this study, is consistent with a 2009 Cochrane review conducted by the Stroke Unit Trialists' Collaboration that showed the benefits of stroke unit care in terms of reducing death, dependency, and institutional care [18].
The SAH-associated mortality was higher than that associated with IS or ICH, and the condition of the patients with SAH was also more severe and required more urgent intervention. Accordingly, the availability of items representing SAH treatment, such as 24/7 interventional service coverage, intensive care unit, and BC physical medicine and rehabilitation, showed the greatest effects on mortality. The critical role of endovascular coil embolization for ruptured IAs was previously established by the International Subarachnoid Aneurysms Trial [19]. Using Nationwide Inpatient Survey data, Qureshi et al. reported a significant increase in endovascular treatment as well as a decrease in in-hospital mortality (2000–2002, 27%; 2004–2006, 24%) in patients with SAH after publication of the International Subarachnoid Trial (ISAT) in 2002 [20]. However, whether the ISAT results can be generalized to all patients with SAH is questionable because most of the patients enrolled in the study were patients with good clinical grades, having small, anterior circulation aneurysms.
The second common cause of SAH-related death and poor functional outcome is rebleeding [21], and early treatment of the ruptured aneurysm is known to lower the incidence of rebleeding. Intensive care unit and 24/7 interventional coverage availability were significant factors associated with decreasing in-hospital mortality after SAH. These findings are explained by the importance of early obliteration of ruptured aneurysms for preventing rebleeding and by the early detection and appropriate treatment of vasospasms, another important cause of morbidity and mortality in patients with SAH. The study provided additional evidence that the availability of endovascular treatment and surgical clipping may reduce in-hospital mortality in patients with SAH [22]. Another recent study also showed that an early mobilization program for patients with aneurysmal SAH is feasible and safe [23]. In addition, appropriate nutritional care from the acute stage is reported to be essential for improving functional outcomes and reducing post-SAH mortality [24]. Taken together, the significant association between the availability of BC physical medicine and rehabilitation and reduced mortality observed in our study reinforces the importance of comprehensive care capabilities, including early rehabilitation and nutritional care for patients with SAH, to prevent complications. Further investigation is required to understand the role of BC physical medicine and rehabilitation in reducing SAH-associated mortality.
Finally, the total CSC score correlated with reduced mortality for all types of stroke, supporting the usefulness of this score as a comprehensive measure of acute stroke care capabilities. Another study showed that hemorrhagic stroke patients admitted to CSCs were more likely to receive neurosurgical and endovascular treatments and to be alive at 90 days than patients admitted to other hospitals. The authors used certification by the New Jersey Department of Health and Senior Services to identify CSCs. The impacts of CSCs on mortality determined in that study are similar to the results obtained using our simple scoring system [25].
In contrast to its impact on in-hospital mortality, the total CSC score did not show a significant impact on poor functional outcomes in patients with any type of stroke. Similarly, no specific item had a significant impact on poor outcomes in patients with hemorrhagic stroke. In patients with IS, the significant role of the presence of a stroke unit in reducing poor outcomes, observed in the present study, was consistent with the results of a previous report [26]. A validation study investigating functional outcomes using the DPC database may be necessary to explain the disparities between the total CSC scores (and specific items) on mortality and poor functional outcomes.

Strengths and limitations of the present study

First, this study is limited by a possible selection bias because hospitals actively working to improve stroke care were more likely to respond to the questionnaire. However, the coverage of the J-ASPECT Study group, which collaborates with the Japan Neurosurgical Society and the Japanese Congress of Neurological Surgeons, was broad enough to provide a reliable study sample. Second, information bias might have existed (self-reporting, recall, and nonresponse). Third, the CSC score mainly evaluated structural measures and did not consider their utilization, supported with real data. To assess clinical practice quality, the use of process measures is preferred [27], but process measures, such as electrocardiogram monitoring and pulse oximetry, were not considered in this scoring system [4, 28]. However, strong correlations between survey components pertaining to personnel and specific expertise (e.g., availability of neurosurgeons and carotid endarterectomy) were observed in this study, suggesting that these items may not be considered as purely structural, but may have characteristics of both structural and process measures. We are planning to develop a new registry system in the J-ASPECT Study to include key metrics required for certification of CSCs in the US, in addition to the DPC database, to study and monitor the association of such quality metrics on mortality and morbidity of acute stroke patients, in Japan. Fourth, in-hospital mortality was selected as an outcome measure to test the validity of the CSC score. A recent systematic review showed that hospital mortality does not necessarily reflect the quality of clinical practice because mortality is affected to a greater extent by the patients’ condition rather than by the quality of practice [29]. Possible correlations between specific items and mortality in patients with IS may have been missed because of the relatively low in-hospital mortality associated with these patients; a larger study is necessary to resolve this issue. Fifth, the DPC-based payment system contains limited information regarding patient condition severity beyond post-discharge data and the National Institute of Health Stroke (NIHSS) Scale, Glasgow Coma Scale (GCS), ICH-, or Hunt-Hess severity scores, upon admission. Nevertheless, the JCS is a useful tool for evaluating stroke severity. Notably, the importance of the JCS, published in 1974, for predicting stroke outcomes has been recently reconfirmed [9, 30]. Further study is necessary to validate the results of the present study with other patient-level measurements, such as the NIHSS, GCS, etc. Despite the above limitations, clear correlations were revealed between the CSC score and in-hospital mortality in patients with all types of strokes. In future work, the score’s components should be weighted according to stroke type, based on their influence on patient outcomes.

Conclusions

The CSC score is a valid measure for assessing the capabilities of CSCs with regard to the availability of neurovascular surgery and intervention, vascular neurology, diagnostic neuroradiology, and neurocritical care and rehabilitation. The total CSC score was associated with mortality in patients with IS, ICH, and SAH, with varying contributions from the four abovementioned constructs.

Acknowledgements

We thank Drs. Manabu Hasegawa, Tomoatsu Tsuji, and Yasuhiro Nishijima for their helpful discussions, Profs. Takamasa Kayama and Nobuo Hashimoto for their supervision of the Japan Neurosurgical Society collaboration, and Ms. Arisa Ishitoko for her secretarial assistance.

Funding

This work was supported by Grants-in-Aid from the Ministry of Health, Labor and Welfare of Japan and JSPS KAKENHI Grant Number 25293314 (principal investigator: KI). This research was partially supported by the Practical Research Project for Life-Style related Diseases, including Cardiovascular Diseases and Diabetes Mellitus, from the Japan Agency for Medical Research and Development.

Availability of data and materials

The datasets for this manuscript will not be shared, based on agreements between the principal investigator and the presidents of the participating hospitals.

Authors’ contributions

KI initiated the collaborative project. AK, KN, SK, and KI designed the study, drafted and revised the article. AK, KN, SK monitored data collection and analyzed the data. JN, KO, JO, YS, TA, SM, IN, KT, SM, AS, HK, FN designed the study, and validated the survey questions from the views of physicians and experts. All authors read and approved the final manuscript.

Competing interests

KI has received grants from Nihon Medi-Physics, AstraZeneca, and Otsuka Pharmaceutical. JN has received an unrestricted research grant from Nihon Medi-Physics. IN has received lecture honoraria from Otsuka Pharmaceutical and Sanofi.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Ethical approval was provided by National Cerebral and Cardiovascular Center in Japan.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
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