Abstract
Introduction:
White matter lesions (WML) are associated with poor outcome after mechanical thrombectomy (MT) for large vessel stroke; the reasons are uncertain. To elucidate this issue we sought to determine the association of WML with multiple early and late outcome measures after MT.
Methods:
We retrospectively analyzed 183 MT patients prospectively included in our local stroke registry (Jan 2012 to Nov 2016). Using multiple regression modeling, we assessed whether WML was independently associated with early outcomes (successful recanalization, degree of NIHSS improvement, hemorrhagic transformation, duration of hospitalization) as well as an unfavorable 90-day modified Rankin score (≥3) and 90-day survival. Explorative analyses examined the association with the 90-day home-time and 90-day risk for hospital readmission
Results:
WML were not significantly associated with early outcome measure (P>0.05, each). Patients with moderate-to-severe WML had more often an unfavorable mRS (OR 2.93, 95% CI 1.04–8.33) and risk of death (HR 1.98; 95% CI 1.03–3.84) after adjustment for pertinent confounders. Patients with moderate-to-severe WML had a significantly shorter home-time (19±32 versus 47±38 days, P<0.001) and Kaplan-Meier analyses indicated a significantly greater risk for hospital readmission within 90 days (Log-rank P=0.045), with the most frequent reasons being recurrent stroke and TIA.
Conclusion:
Our analyses suggest that poor outcomes among patients with moderate-to-severe WML were related to factors unrelated to procedural success and risk. WML should not be used to render treatment decisions in otherwise eligible patients. Aggressive monitoring of medical complications after MT could represent a viable strategy to improve outcome in affected patients.
Keywords: Leukoaraiosis, home-time, large vessel occlusion, mortality, readmission, small vessel disease, survival analysis
Introduction
Markers of cerebral small vessel disease including chronic ischemic white matter lesions (WML), also termed WML, have been established as a relevant risk factor for an unfavorable outcome after stroke.1,2 There is mounting evidence that WML are associated with worse outcomes after mechanical thrombectomy (MT),3–9 the gold standard treatment approach for eligible patients with acute ischemic stroke (AIS) caused by large vessel occlusion (LVO).10,11 However, the exact reasons remain uncertain. A better understanding of this issue is important as it may improve patient selection for MT as well as post-MT care.
For example, while some studies suggested that patients with extensive WML may be at greater risk for hemorrhagic complications6 the majority of contemporaneous studies have not confirmed this.4,8,9,12,13 Also, few studies have investigated whether procedural success is impacted by WML.3,9,12,14 Moreover, there is a striking lack of data as to whether WML may affect post-MT disability through global health decline and medical complications rather than focal neurological deficit severity,15–18 which may not be captured by standard outcome measures such as the NIHSS or modified Rankin Scale score (mRS).
In this study we sought to obtain a comprehensive understanding of the association of WML with clinical outcome after MT, by assessing the relationship between the severity of pre-existing WML on multiple early (assessed during hospitalization) and subacute (up to 90 days) outcome measures in patients undergoing MT. For early outcomes we sought to determine the rate of successful recanalization, change in NIHSS from admission to discharge, presence of symptomatic hemorrhagic transformation within 36 hours, and duration of hospitalization. For subacute outcome measures we examined the home-time, time to hospital readmission, mRS, and overall survival in the first 90 days after the index admission.
Methods
Study Population
We retrospectively analyzed consecutive patients with acute anterior circulation LVO that were prospectively included in our local stroke registry between January 2012 and November 2016. Of note, a subset of included patients has previously been reported as part of a separate investigations.5,7,19
Data abstraction and analyses were conducted between February 2017 and May 2018. During the study period, patients were generally considered eligible for MT if they had an LVO associated with significant neurological deficit (NIHSS ≥6), small infarct burden on pre-procedural non-contrast head CT (ASPECTS ≥6), good collaterals on admission CT angiogram (CTA), and patient presentation within 24 hours from symptom onset.7 CT perfusion was used to aid decision making at the discretion of the treating physicians. The final decision for endovascular therapy was reached by consensus between the neurointerventional and stroke teams.
Information on patient age, gender, laboratory data (admission serum glucose, INR, platelet count), admission blood pressure, vascular risk factors, pre-admission medications, and stroke etiology (using the Trial of Org 10172 in Acute Stroke Treatment [TOAST] classification) was collected on all patients after completion of diagnostic evaluation (see Table 1 for details).
Table 1.
Baseline characteristics (unadjusted) of the studied patient population as stratified by WML severity
| Characteristics | All patients (n=181) |
VSS 0–2 (n=148) |
VSS 3–4 (n=33) |
P-value |
|---|---|---|---|---|
| Age, years | 68 (57–81) | 66 (54–76) | 82 (74–85) | <0.001 |
| Female gender | 83 (45.9%) | 67 (45.3%) | 16 (48.5%) | 0.847 |
| Admission SBP, mmHg | 140 (124–155) | 139 (124–155) | 144 (131–167) | 0.457 |
| Admission DBP, mmHg | 78 (67–90) | 79 (67–91) | 72 (60–88) | 0.276 |
| Admission NIHSS* | 18 (14–22) | 18 (13–21) | 20 (15–25) | 0.082 |
| Pre-stroke mRS | 0 (0–1) | 0 (0–0) | 1 (0–2) | <0.001 |
| Neuroimaging | ||||
| ASPECTS 6–10** | 165 (91.2%) | 133 (89.9%) | 32 (97%) | 0.311 |
| Good collaterals | 89 (49.2%) | 74 (50.0%) | 15 (45.5%) | 0.702 |
| Posterior circulation stroke | 23 (12.7%) | 18 (12.2%) | 5 (15.2%) | 0.576 |
| Treatment | ||||
| Thrombolysis with iv rtPA | 91 (50.3%) | 72 (48.6%) | 19 (57.6%) | 0.442 |
| Time to iv rtPA, min | 112 (77–160) | 118 (83–165) | 85 (53–140) | 0.033 |
| Time to groin puncture, min | 295 (195–481) | 321 (205–553) | 210 (151–310) | 0.002 |
| Procedure duration, min | 95 (60–150) | 96 (61–150) | 87 (56–156) | 0.422 |
| Laboratory data | ||||
| Admission glucose (random), mg/dL | 122 (106–143) | 122 (107–143) | 121 (97–157) | 1.000 |
| Platelet count, 103/μL | 204 (163–248) | 212 (166–248) | 186 (159–206) | 0.037 |
| Stroke mechanism | 0.002 | |||
| Large artery atherosclerosis | 37 (20.4%) | 33 (22.4%) | 4 (11.8%) | |
| Cardioembolic | 91 (50.3%) | 64 (43.5%) | 27 (79.4%) | |
| ESUS | 32 (17.7%) | 30 (20.4%) | 2 (5.9%) | |
| Other determined | 21 (11.6%) | 20 (13.6%) | 1 (2.9%) | |
| Preexisting risk factors | ||||
| Atrial fibrillation | 82 (45.3%) | 57 (38.5%) | 25 (75.8%) | <0.001 |
| Coronary artery disease | 50 (27.6%) | 37 (25.0%) | 13 (39.4%) | 0.130 |
| Diabetes mellitus | 32 (17.7%) | 26 (17.6%) | 6 (18.2%) | 1.000 |
| Heart failure | 37 (20.4%) | 29 (19.6%) | 8 (24.4%) | 0.633 |
| Hyperlipidemia | 97 (53.6%) | 78 (52.7%) | 19 (57.6%) | 0.701 |
| Hypertension | 132 (72.9%) | 106 (71.6%) | 26 (78.8%) | 0.517 |
| Prior stroke or TIA | 19 (10.5%) | 9 (6.1%) | 10 (30.3%) | <0.001 |
| Preadmission medications | ||||
| Statin | 78 (43.1%) | 61 (41.2%) | 17 (51.5%) | 0.332 |
| Antihypertensive | 124 (68.5%) | 100 (67.6%) | 27 (72.7%) | 0.680 |
| Antiglycemic | 26 (14.4%) | 20 (13.5%) | 6 (18.2%) | 0.582 |
| Antiplatelets | 75 (41.4%) | 57 (38.5%) | 18 (54.5%) | 0.118 |
| Oral anticoagulants | 34 (18.8%) | 24 (16.2%) | 10 (30.3%) | 0.083 |
There was no significant difference in the baseline NIHSS across the individual VSS steps (P=0.140). ASPECTS indicates Alberta Stroke Program Early CT Score (**assessed in the anterior circulation only), DBP=diastolic blood pressure; CTA=CT angiography, ESUS=Embolic stroke of undetermined source, mRS=modified Rankin Scale, NIHSS=National Institutes of Health Stroke Scale, TIA=transient ischemic attack, rtPA=recombinant tissue-type plasminogen activator, SBP=systolic blood pressure; TICI=thrombolysis in cerebral infarction; VSS= van Swieten scale. Data are n (%) or median (25th–75th quartile). Data was complete for all included variables.
We calculated the ΔNIHSS by subtracting the admission NIHSS from the discharge NIHSS. Accordingly, a negative ΔNIHSS indicates an improvement of the NIHSS-assessed deficit between admission and discharge. Conversely, positive numbers indicate worsening of the NIHSS. For patients dying in house or in whom goals of care were changed to comfort measures only (CMO) the last NIHSS before death/CMO status was used as the discharge NIHSS.
The modified Rankin Scale (mRS) was assessed at admission (pre-stroke mRS) and at 90 days by a stroke-trained physician or stroke study nurse certified in mRS via in-person or phone interview using a simplified mRS questionnaire.2 For statistical purposes, we included the pre-stroke mRS as dichotomized to 0–2 versus >2 in multivariable regression models as previously detailed.7 In one patient who was lost to follow up we imputed the 90-day mRS by carrying forward the discharge mRS. We defined a favorable 90-day functional outcome as mRS of 0–2, or return to baseline.7
Details of our neuroimaging protocol and WML analysis have previously been described in detail7 and are summarized in the Supplemental methods.
Contrast extravasation and hemorrhagic transformation
Post-MT hemorrhagic transformation was defined as hyperdensity that persisted longer than 24 hours, was associated with mass effect, or had a characteristic hypoattenuation rim.20 Symptomatic intracranial hemorrhage (sICH) was defined as hemorrhagic transformation that caused clinical deterioration of ≥4 points on the NIHSS within 36 hours. Conversely, contrast extravasation (CE) was defined as hyperdense lesions that disappeared or prominently cleared within 24 h without mass effect on follow-up CT scans.20 Given the inherent difficulty to reliably differentiate CE from true hemorrhagic transformation we conducted additional analyses based on the tissue density (Hounsfield units [H.U.]). For these analyses, we excluded patients without admission head CT (n=14; these patients were transferred from an outside institution direct to our angio suite) and subjects who did not undergo repeat conventional head CT (n=16, all of which underwent immediate post-procedural in-angio CT and survived to 3 months) leaving 151 patients (83%) for analysis. For H.U. measurements, we first defined a region of interest (ROI, ~100 mm3) manually centered in the area of greatest (visually determined) hyperdense area on post-MT on a single CT slice. Then, we calculated H.U. for each patient in the ROIs placed within the corresponding contralateral hemisphere as well as in the corresponding ipsi- and contralateral areas on pre-MT CT for a total of 4 ROIs.
Outcomes of interest and data analysis
We examined associations of WML with the following key outcomes of interest: ΔNIHSS, TICI ≥2b, sICH as well as favorable 90-day mRS and 90-day survival. In addition, we examined associations of WML with the presence of any hemorrhagic transformation, 90 day home-time (defined as the time spent outside of healthcare institutions during the first 90 days after the index stroke) and 90-day readmission rates.
Continuous variables are reported as median (25th–75th percentile) or mean ± s.d. Categorical variables are reported as proportions. Normality of data was examined using Shapiro-Wilk test. Between-group comparisons for continuous variables were made with Mann-Whitney U test. Categorical variables were compared using the χ2-test or Fisher’s Exact test. Correlative analyses were conducted using Spearman rank test. Kaplan-Meier and log-rank test were used for univariate comparisons of the 90-day survival and readmission between the WML severities.
We used multivariable linear regression with backward elimination to determine factors independently associated with the ΔNIHSS. Factors associated with the ΔNIHSS in univariate analysis (including admission SBP, time to groin puncture, procedure duration, TICI ≥2b, cardioembolic stroke, gender, history of hyperlipidemia and atrial fibrillation as well as antihypertensive use) and the dichotomized WML severity were entered into the model.
A multivariable binary logistic regression model was constructed to describe the association of WML severity with successful recanalization (TICI ≥2b) after adjustment for factors associated with TICI ≥2b in univariate analyses (including atrial fibrillation, stroke caused by large artery atherosclerosis, procedure duration, and the dichotomized ASPECTS).
To describe the association of WML severity with unfavorable 90-day mRS (mRS >2), we constructed a multivariable binary logistic regression model adjusted for age and pertinent covariates relating to the outcome in our cohort (including the admission NIHSS, pre-stroke mRS, platelet count, presence of sICH, use of statins, anti-hypertensives and antiglycemics, as well as history of hypertension, stroke/TIA, atrial fibrillation, and coronary artery disease).
To determine whether moderate-to-severe WML were independently associated with the 90-day survival, we constructed a Cox proportional hazards model, adjusted for age and patient characteristics relating to 90-day mortality on univariate analyses (including the admission NIHSS, pre-stroke mRS, and platelet count, presence of sICH, use of statins as well as history of stroke/TIA, atrial fibrillation, coronary artery disease, and cardioembolic stroke mechanism).
To create parsimonious models, predictor variables were sequentially removed (likelihood ratio) from the models at a significance level of 0.1. Collinearity diagnostics were conducted for all multivariable models. For Cox-regression analysis, the proportional hazards assumption was assessed and satisfied for all variables except for statin use and history of coronary artery disease. To avoid model violation, we included the respective covariate-by-time interaction terms into the multivariable model. Model calibration was assessed by the Hosmer-Lemeshow test and model fit determined by examining the −2 log-likelihood statistic and its associated chi-square statistics. Two-sided significance tests were used throughout and a two-sided p<0.05 was considered statistically significant. All statistical analyses were performed using SPSS® Statistics 22 (IBM®-Armonk, NY).
Data Sharing
The investigators will share anonymized data (with associated coding library) used in developing the results presented in this manuscript upon reasonable request to investigators who have received ethical clearance from their host institution.
Results
Study population
Overall, 183 patients were treated with mechanical thrombectomy during the study period. Two patients were excluded because the medical records could not be obtained, leaving 181 patients for analysis. Baseline characteristics of the included 181 patients as stratified by WML severity are summarized in Table 1. Among included patients the majority (n=148) had mild-to-moderate WML (van Swieten Scale [VSS]: VSS0 n=44 [24.3%], VSS1 n=53 [29.3%], VSS2 n=51 [28.2%]). Among subjects with moderate-to-severe WML n=22 (12.2%) were graded as VSS3 and n=11 (6.1%) as VSS4.
WML severity was not associated with early procedural success
First, we sought to determine the potential association of pre-existing WML with early outcome measures after MT. To this end, we investigated whether WML were related to successful recanalization (TICI ≥2b) as well as early neurological recovery as determined by the ΔNIHSS.
On unadjusted analyses, factors associated with TICI ≥2b included ASPECTS ≥6 (93.3% versus 80.6%, P=0.035), history of atrial fibrillation (48.7% versus 29.0%, P=0.05), stroke mechanism other than large artery atherosclerosis (84.0% versus 58.1%, P=0.003), and a shorter procedural duration (88 min versus 129 min; P=0.014). There was no significant difference in the distribution of recanalization grades when stratified by the WML severity (entered as graded or dichotomized variables P>0.05 for all analyses; Table 2 and Figure 1A). Likewise, there was no correlation between the WML severity and TICI grade (Spearman rank test, r=.125, P=0.094). On multivariable regression, only ASPECTS ≥6 (OR 5.06 [95%-CI 1.47–17.38], P=0.010) and stroke mechanism other than large artery atherosclerosis (OR 4.40 [95%-CI 1.53–12.67], P=0.006) were independently associated with TICI ≥2b, whereas atrial fibrillation and procedural duration were not (P>0.05, each). Furthermore, forcing WML into the model did not meaningfully change these associations (not shown).
Table 2.
Outcomes (unadjusted) of the studied patient population as stratified by WML severity
| Characteristics | All patients (n=181) |
VSS 0–2 (n=148) |
VSS 3–4 (n=33) |
P-value |
|---|---|---|---|---|
| Discharge NIHSS | 10 (5–18) | 10 (5–17) | 15 (7–20) | 0.087 |
| ΔNIHSS | −6 (−12 to 0) | −5 (−12 to 0) | −6 (−12 to 0) | 0.777 |
| TICI 2b-3 | 150 (82.9%) | 123 (83.1%) | 27 (81.8%) | 0.803 |
| sICH | 20 (11.0%) | 15 (10.1%) | 5 (15.2%) | 0.372 |
| 90-day mRS <3 | 92 (50.8%) | 84 (57.1%) | 8 (24.2%) | 0.001 |
| 90-day mortality | 44 (24.3%) | 28 (18.9%) | 16 (48.5%) | <0.001 |
| 90-day home time, days | 40 (0–85) | 59 (0–85) | 0 (0–32) | <0.001 |
Figure 1.
Association of pre-existing WML severity with early outcome and imaging measures. (A) There was no significant difference in the distribution of recanalization grades (as assessed by the TICI score) between patients with absent-to-mild (van Swieten Scale [VSS] 0–2) versus moderate-to-severe (VSS 3–4) WML (χ2-Test). (B) There was no significant difference between the ΔNIHSS across VSS grades (P=0.118; one way analysis of variance). Similar CT density within the ischemic core before (C) and after (D) mechanical thrombectomy across WML grades (P>0.05, each; one way analysis of variance).
On unadjusted analysis, factors correlating with a greater early deficit improvement (i.e., lower ΔNIHSS) included a shorter time-to-groin puncture (r=.162, P=0.037), shorter procedural duration (r=.259, P=0.001), TICI ≥2b (r=−.217, P=0.003), female gender (r=−.240, P=0.001), hyperlipidemia (r=−.200, P=0.007), atrial fibrillation (r=−.179, P=0.016), use of antihypertensives (r=−.222, P=0.003), cardioembolic stroke cause (r=−.175, P=0.019), and a lower admission SBP (r=.199, P=0.008). However, we found no significant correlation between the ΔNIHSS and VSS grades (r=−.08, P=0.181, Spearman Rank test, Figure 1B) and, similarly there was no difference in the ΔNIHSS between patients with absent-to-mild versus moderate-to-severe WML (P=0.78, t-Test, Table 2). On multiple linear regression, procedural duration (P=0.012), TICI ≥2b (P=0.046), and the admission SBP (P=0.010) were independently associated with the ΔNIHSS. Forcing WML severity into the model did not change the results (not shown).
WML severity was not associated with sICH and hemorrhagic transformation after MT
Next, we sought to determine whether the degree of WML severity was associated with early procedural risk as determined by the occurrence of sICH, hemorrhagic transformation, as well as CE. Among included subjects, 20 (11.0%) had a sICH within 36 hours. On univariable analysis, none of the studied baseline variables including WML were significantly associated with sICH (P>0.05, each). Specifically, WML severity was not associated with sICH (P=0.372, Table 2). Likewise, WML severity was not associated with any hemorrhagic transformation (P=0.542). Finally, in the unaffected hemisphere we found a trend towards lower H.U. in the ROI corresponding to the ischemic core with increasing WML severity (P=0.020, not shown). However, there was no significant association between WML severity and H.U. within the corresponding ROI in the unaffected hemisphere after MT (P=0.412, not shown) nor within the corresponding ROI in the ischemic hemisphere before (P=0.103, Figure 1C) and after MT (P=0.529, Figure 1D). Excluding patients without visible hemorrhagic transformation or CE did not meaningfully change these results (not shown).
Significantly greater mortality, worse functional disability, shorter home-time, and greater readmission risk after MT in patients with severe WML
Patients with moderate-to-severe WML were significantly more often disabled or dead (mRS >2) by 90 days than patients with absent-to-mild WML (78.8% versus 44.6%, χ2 P<0.001, Figure 2A). After adjustment for pertinent confounders, WML severity remained independently associated with a poor 90-day functional outcome (mRS >2; Table 3). Of note, after exclusion of patients who died by 90 days, there remained a significant association between worse VSS scores and greater 90-day mRS scores on unadjusted analyses (n=137; χ2 P=0.005).
Figure 2.
(A) Patients with moderate-to-severe (van Swieten Scale [VSS] 3–4) WML had significantly worse 90-day functional outcomes than patients with absent-to-mild (VSS 0–2) WML as assessed by the modified Rankin Scale (mRS). (B) Among patients with complete data on the time spent in healthcare institutions, subjects with VSS 3–4 spent significantly less time at home during the first 90 days than patients with VSS 0–2. Kaplan Meier analysis indicated greater (C) 90-day mortality and (D) 90-day readmission probability of patients with VSS 3–4 as comparted to patients with VSS 0–2. Numbers in parenthesis indicate the number of events per the number of patients in each stratum. For readmission analyses patients were excluded if they died during the index admission or were discharged to hospice. Elective readmission for cranioplasty (n=3) was not considered an event.
Table 3. Multivariable logistic regression analyses of factors relating to an unfavorable 90-day outcome.
Point estimates of the multivariable logistic regression model comparing moderate-to-severe WML to absent-to-mild WML for an unfavorable 90-day outcome (defined as modified Rankin Scale score >2). TIA indicates transient ischemic attack. Hosmer-Lemeshow goodness of fit P=0.546.
| Independent variable | Odds ratio (95% confidence interval) | P-value |
|---|---|---|
| Moderate-to-severe WML* | 2.93 (1.04–8.33) | 0.043 |
| admission NIHSS (per point) | 1.09 (1.04–1.15) | 0.001 |
| Symptomatic intracranial hemorrhage | 15.12 (3.04–75.13) | 0.001 |
| Antiglycemic use | 4.04 (1.35–12.14) | 0.013 |
| History of hypertension | 2.93 (1.23–6.98) | 0.015 |
| History of stroke/TIA | 3.11 (0.75–12.93) | 0.119 |
Entering WML as ordinal variable did not substantially change these associations except that history of stroke/TIA was not retained in the final step of the model.
Kaplan Meier analyses indicated significantly greater mortality rates among patients with moderate-to-severe WML as compared to patients with absent-to-mild WML (48.5% versus 18.9%, log rank P<0.001, Figure 2B). Moreover, when patients who died in hospital or were discharged to hospice (n=44) were excluded, Kaplan Meier analysis indicated that patients with moderate-to-severe WML (n=120) had significantly greater mortality rates than subjects with absent-to-mild WML (15.0% versus 4.0%, log rank P=0.035). Importantly, the association between WML severity and 90-day mortality remained significant after adjustment for potential confounders in Cox-regression analysis (n=181; hazard ratio 1.98; 95% CI 1.03–3.84; P=0.042; Supplemental Table 1).
From our cohort, 137 patients had complete data regarding the time spent in healthcare institutions during the first 90 days after the index stroke. Among these, patients with absent-to-mild WML spent on average significantly more time at home during the first 90 days than patients with moderate-to-severe WML (19±32 versus 47±38 days, rank sum test P<0.001; Table 2 and Figure 2C). Results were similar when we excluded patients who died in the hospital or were discharged to hospice (59±33 versus 38±38 days, rank sum test P<0.001; not shown).
Finally, among patients discharged from the hospital (excluding those discharged to hospice) the cumulative probability of readmission within 90 days significantly increased with worse WML (Log rank P=0.045, Figure 2D). Supplemental Table 2 depicts the major reasons leading readmission. Overall, subjects with moderate-to-severe WML had relatively more frequent recurrent stroke/TIA than subjects with absent-to-mild WML (43% vs. 5%, P<0.05). There was no statistically significant difference between groups for any other readmission category (P>0.05, each); though, this analysis was underpowered to detect a true difference.
Discussion
Several imaging surrogate markers of early stroke severity and extent including the ASPECTS and collateral status have been shown to predict outcome after LVO stroke and are routinely used to aid clinical decision making for offering MT to these patients.21–23 In recent years there has been an increased interest in defining additional imaging markers that could potentially refine patient selection for successful MT. Multiple studies have reported that pre-existing WML, which can be easily and reliably identified on routine head CT24, adversely affects outcome after MT.3–5 WML correlate with stroke severity and extent; yet, unlike the ASPECTS it is not a direct proxy of acute brain injury. Nevertheless, we recently demonstrated that among highly selected patients considered good candidates for MT and in whom successful recanalization was achieved, patients with severe WML had significantly worse outcomes.7 This suggested that WML may worsen outcomes after MT through factors that were unrelated to the procedural success. Our present study provides novel insight into this issue by providing a comprehensive analysis of several key outcome parameters.
First, we found no significant association between the severity of pre-existing WML with indices of early procedural success, including achievement of substantial reperfusion (TICI ≥2b) and degree of neurological improvement (ΔNIHSS). Although studies on WML in patients treated with MT routinely reported on TICI scores and admission NIHSS3–7,9,12–14,25 only a small subset examined whether WML were independently associated with substantial reperfusion9,12,14 and early neurological improvement after MT.25 Our finding that WML severity is not associated with recanalization success is consistent with the results from the two contemporary MT studies that specifically examined this issue.9,12 Our observation that WML severity was not associated with the ΔNIHSS after MT contrasts with the report from Guo et al.,25 who reported less frequent early neurological improvement among patients with severe WML. The reasons for this apparent discrepancy are not entirely clear, but potentially related to the different definitions of WML severity and neurological improvement between our studies, the most important being that we considered the entire range of NIHSS improvement, as opposed to a dichotomized outcome.25
A second important observation from our study was that we did not find an association of WML severity with contrast extravasation, any hemorrhagic transformation, and sICH. This is in line with the vast majority of studies investigating this issue.4,5,8,9,12–14 Together, these data emphasize that the severity of WML should not be used to determine whether MT should withheld from otherwise eligible patients for fear of reduced procedural success or increased risk.
Similar to the majority of previous reports, patients with moderate-to-severe WML had worse 90-day outcomes than patients with absent-to-mild WML despite overall comparable early procedural safety and success. Our data suggests that the reason for this is largely related to a more complex disease course as evidenced by greater mortality risk, less time spend outside of healthcare institutions, and greater readmission rates within 90 days. Consistent with existing data, patients with moderate-to-severe WML were at significantly greater risk for recurrent stroke than patients with absent-to-mild WML.18,26 Moreover, though our study was underpowered to reliably detect a significant difference between groups, patient with moderate-to-severe WML were numerically more frequently admitted for infectious complications. This is of interest because severe WML have been independently associated with stroke associated pneumonia.15,16 If confirmed in larger prospective studies, more intense monitoring and aggressive management of potential medical complications has the potential to improve overall outcomes in patients with severe WML. Lastly, it would be very valuable to determine the extent of both pre- and post-MT cognitive impairment and its contribution to outcome. Cerebral small vessel disease including WML represents an established risk factor for cognitive impairment, dementia, and overall frailty and physical decline.27–30 Yet, some MT trials excluded patients with significant pre-existing functional disability31–33 and it has been shown that the degree of WML burden attenuates recovery of cognitive deficits relatively more than motor deficits.34 Accordingly, future studies may benefit from additional assessment of the association between WML, cognitive status, and physical frailty as potential impactful variables to disease burden and self-care after MT.
The present study has several strengths and limitations. Strengths relate to inclusion of consecutive stroke patients with LVO evaluated by clinicians certified in NIHSS and ASPECTS, who were also masked to assessments of WML severity and other imaging variables with respect to clinical variables, plus an additional rigorous statistical adjustment for clinically relevant confounders to that relate to the outcomes of interest by using use of multiple logistic regression analyses. Limitations relate to our modest sample size and those inherent to our retrospective study design. In approximately 25% of patients the home time could not be established, which may have introduced bias. Finally, because our study was a pure endovascular cohort, our results should be considered hypothesis generating only and our findings require confirmation by including non-MT cohorts, ideally from prospective randomized trials.
Conclusion
Severity of WML was not associated with early procedural success or hemorrhagic transformation after MT. For this reason, presence and severity of WML should not be used as a criterion to withhold MT from otherwise eligible patients. Further study is required to determine to what degree medical complications contribute to the worse 90-day outcomes in patients with severe WML to ultimately improve patient care.
Supplementary Material
Sources of Funding:
Dr. Henninger is supported by K08NS091499 from the National Institute of Neurological Disorders and Stroke of the National Institutes of Health and R44NS076272 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Disclosure of potential conflicts of interest:
Dr. Puri is a consultant for Medtronic, CereVasc, Microvention, Stryker Neurovascular, Scientica Vascular, and Cerenovus, receives research support from Stryker Neurovascular and Medtronic Neurovascular, and reports stock options in InNeuroCo. All other authors report no disclosures.
Footnotes
Ethical approval: This study was reviewed and approved by our Institutional Review Board and procedures followed were in accordance with institutional guidelines and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Health Insurance Portability and Accountability Act (HIPAA) waiver of authorization was granted. We adhere to the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guidelines (www.strobe-statement.org).
References
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