J Stroke Search


J Stroke > Volume 25(1); 2023 > Article
Aboul-Nour, Maraey, Jumah, Khalil, Elzanaty, Elsharnoby, Al-Mufti, Chebl, Miller, and Mayer: Mechanical Thrombectomy for Acute Ischemic Stroke in Metastatic Cancer Patients: A Nationwide Cross-Sectional Analysis


Background and Purpose

Mechanical thrombectomy (MT) is the standard treatment for large vessel occlusion (LVO) acute ischemic stroke. Patients with active malignancy have an increased risk of stroke but were excluded from MT trials.


We searched the National Readmission Database for LVO patients treated with MT between 2016-2018 and compared the characteristics and outcomes of cancer-free patients to those with metastatic cancer (MC). Primary outcomes were all-cause in-hospital mortality and favorable outcome, defined as a routine discharge to home (regardless of whether home services were provided or not). Multivariate regression was used to adjust for confounders.


Of 40,537 LVO patients treated with MT, 933 (2.3%) had MC diagnosis. Compared to cancer-free patients, MC patients were similar in age and stroke severity but had greater overall disease severity. Hospital complications that occurred more frequently in MC included pneumonia, sepsis, acute coronary syndrome, deep vein thrombosis, and pulmonary embolism (P<0.001). Patients with MC had similar rates of intracerebral hemorrhage (20% vs. 21%) but were less likely to receive tissue plasminogen activator (13% vs. 23%, P<0.001). In unadjusted analysis, MC patients as compared to cancer-free patients had a higher in-hospital mortality rate and were less likely to be discharged to home (36% vs. 42%, P=0.014). On multivariate regression adjusting for confounders, mortality was the only outcome that was significantly higher in the MC group than in the cancerfree group (P<0.001).


LVO patients with MC have higher mortality and more infectious and thrombotic complications than cancer-free patients. MT nonetheless can result in survival with good outcome in slightly over one-third of patients.


Acute ischemic stroke (AIS) is common in patients with active malignancy, occurring in 15% of all cancer patients [1]. The incidence of cancer-related AIS is proportional to survival time, which exposes patients to an increased risk of cancer-related hypercoagulability [1].
Patients with cancer tend to be excluded from receiving tissue plasminogen activator (tPA) as they carry a high risk for bleeding secondary to brain metastases, thrombocytopenia, coagulopathy, therapeutic anticoagulation, and recent surgeries [2,3]. Given these limitations, understanding the outcomes and risks of mechanical thrombectomy (MT) in cancer patients may help make decision for MT.
Patients with cancer and reduced life expectancy were excluded or underrepresented from the seminal clinical trials that established the efficacy of MT for large vessel occlusion (LVO) stroke [4-8]. Several small single-center cohort studies have addressed MT in cancer patients, with the number of patients treated with MT ranging from 19 to 27 [9-12]. These studies have demonstrated that MT is feasible, but have shown inconsistent results with regard to procedural effectiveness, mortality, disability, and the rate of hemorrhagic transformation compared to non-cancer MT-treated patients [9-12]. In a more recent analysis of the multicenter European MR CLEAN (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in The Netherlands) registry; 4.8% of patients undergoing MT had active cancer [3]. Despite similar technical success, cancer patients had higher mortality and greater disability than cancer-free patients, but nonetheless about one-quarter of the patients regained functional independence.
Our study aimed to investigate the outcomes and in-hospital complications of patients with metastatic cancer (MC) treated with MT for LVO AIS in a large, cross-sectional USA nationwide database. Our hypothesis was that thrombectomy in MC patients results in a comparable rate of discharge to home compared to cancer-free LVO patients, despite higher in-hospital mortality.


Data source

This is a retrospective cohort study using the Agency for Healthcare Cost and Utilization Project (HCUP) Nationwide Readmission Database (NRD) for the years 2016-2018 [13]. The NRD is the largest publicly-available all-payer inpatient health care readmission database in the USA. The NRD is drawn from HCUP state inpatient databases containing verified patient linkage numbers that can be used to track a person across hospitals within a state while adhering to strict privacy guidelines. It provides longitudinal information about patients’ initial hospitalization and subsequent readmissions in a calendar year. It contains a weighted sample of hospitalizations in the USA, which can be used to derive national estimates of various hospitalizations directly. All authors who worked directly with the data set underwent a data handling and training module required by HCUP. Data are available to be shared by the authors upon reasonable request. A checklist of the REporting of studies Conducted using Observational Routinely collected health Data (RECORD) items to be reported in observational studies using routinely collected health data is provided in Supplementary Table 1. Due to the anonymous nature of this administrative database of hospital admissions, neither local institutional review board nor patient consent were required.

Study population

Our primary study population was all USA admissions for incident AIS who underwent MT during the 3-year study period. Index admission was defined as the first admission with the primary diagnosis of AIS during the study period; subsequent admissions for stroke were not included. Admissions were excluded if age was <18 years, the patient had a prior history of stroke, or the file had missing data. In the NRD, patient identifiers cannot be linked across years; hence index admissions on October 1st or beyond were excluded to allow a minimum of 3 months of follow-up. In accordance with the HCUP data user agreement, we excluded reporting any variables containing a small number of observations (≤10) that could pose a risk of personal identification or a data privacy violation.
For analysis, we divided the cohort into two groups. We selected MC as the diagnosis of interest to ensure that we would focus on a more homogeneous population of cancer patients with advanced disease. Patients with a cancer diagnosis without metastases were excluded to allow us to focus only on patients with the most severe disease. The diagnosis of interest (n=933) was patients with MC and LVO stroke who were treated with MT. This group was compared to LVO stroke cancer-free patients who were treated with MT (n=38,166). International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) codes were utilized to capture the diagnoses of interest, including MC (Supplementary Table 2). An independent audit comparing ICD-10 codes to hospital discharge records showed that the former was highly reliable and accurate [14].

Baseline illness and stroke severity

Baseline demographic data including age and sex were collected. Race was not included as it is not available in the NRD. Baseline illness severity was determined using All Patient Refined Diagnosis Related Group (APR-DRG) subclasses. This system uses weighted diagnostic codes to capture admission diagnosis, complications, and risk of mortality at discharge, and classifies patients into four clinically meaningful severity groups ranging from 1 (mild illness) to 4 (extreme illness) [15]. Stroke severity was determined as the presence of one or more of the following elements: paralysis/paresis, aphasia, coma, cerebral edema, cerebral herniation, and/or requiring mechanical ventilation, in accordance with prior published research [16].

Study outcomes

The primary outcomes were all cause in-hospital mortality and favorable outcome, which was defined as a routine discharge to home (regardless of whether home services were provided or not). Secondary outcomes included hospital length of stay, non-home discharge (defined as non-routine discharge to a rehabilitation hospital; a short, intermediate, or long term nursing facility; or hospice), development of intracerebral hemorrhage (ICH), the need to undergo decompressive hemicraniectomy, and 90-day hospital readmission. Tertiary outcomes included the frequency of a variety of acute hospital complications, which were captured by their corresponding ICD-10 codes (Supplementary Table 2). In-hospital mortality and length of stay are directly coded in the NRD.

Statistical analysis

We compared MT-treated patients with MC and MT-treated cancer-free patients. Continuous variables were compared using Student’s t-test, and categorical variables were compared using the χ2 test. Multivariate linear and logistic regression analyses were used to adjust for confounders (age, sex, severe stroke, APR-DRG=4, and tPA use) and calculate adjusted odds ratio (aOR) for the association of MC with all primary and secondary outcome measures. To explore the independent role of MC in explaining death or discharge to a facility after MT, we constructed a stepwise backward regression model accounting for demographics, stroke and disease severity, and specific complications and procedures. Admissions that ended with in-hospital mortality were excluded from readmissions analysis. All P-values were 2-sided, with 0.01 as the threshold for statistical significance to adjust for multiple comparisons. Data Analysis was performed using Stata version 17 (StataCorp., College Station, TX, USA).


Our analysis identified 1,056,011 eligible patients admitted for AIS during the 3-year study period, 40,537 (3.8%) of whom underwent MT (Figure 1). Of those who underwent MT, 933 (2.3%) had MC. The different types of cancer that were represented are shown in Supplementary Table 3.
We compared the 933 MT-treated patients with MC to 38,166 cancer-free stroke patients treated with MT (Table 1). Stroke severity was highly comparable between the two groups. MC patients were less likely to receive tPA (13% vs. 23%, P<0.001) but had a similar frequency of ICH (about 20%). MC patients had a higher frequency of severe medical illness based on APR-DRG coding (52% vs. 39%, P<0.001). Specific medical complications that occurred more frequently in the MC cohort included pneumonia, sepsis, deep vein thrombosis, pulmonary embolism, and acute coronary syndromes (all P<0.001). MC patients were significantly less likely to undergo placement of a percutaneous endoscopic gastrostomy (PEG) tube or tracheostomy. The frequency of hemicraniectomy was <1% in both groups.
In-hospital mortality was significantly higher in MC patients (26% vs. 14%, P<0.001). The overall proportion of MC patients with a favorable outcome (discharged to home) was slightly lower, but highly comparable to the cancer-free group (36% vs. 42%, P=0.014). Hospital length of stay and 90-day readmission rates were similar. On multivariate regression adjusting for confounders, the only outcome variable that was significantly different between the MC and cancer-free groups was mortality (Table 2). Among cancer patients who underwent thrombectomy, there was no significant difference in mortality between those with or without brain metastases.
To explore the independent role of MC in explaining death or discharge to a facility among MT-treated stroke patients, we created a stepwise backward multivariate logistic regression model that included demographics, MC, stroke and illness severity, and specific complications and procedures (Table 3). After accounting for ten variables that were significantly associated in the final model, the adjusted odds ratio for the association between MC and poor outcome was nonsignificant (Table 3). Variables that did predict death or discharge to a facility included age, female sex, overall medical disease severity, severe stroke, deep vein thrombosis, pneumonia, sepsis, ICH, urinary tract infection, and placement of a PEG or tracheostomy. There was no interaction between MC and overall disease severity (APR-DRG=4) with regard to mortality.


AIS is the second most common complication that involves the central nervous system in cancer patients, the first being cerebral metastases [17]. Viewed another way, one-in-ten patients with AIS have a history of remote or active cancer, making it critical to establish the best management strategies for LVO in this vulnerable group of patients [18]. In an autopsy study, it was reported that almost 15% of cancer patients had a stroke on post-mortem examination, with hemorrhagic and ischemic strokes being equally prevalent [1].
Hypercoagulability in patients with cancer is hypothesized to be due to tumor cell-derived cytokines, elevated D-dimer levels, tumor embolism, chemotherapy, as well as vascular risk factors like diabetes and hypertension [9,10,19], and it is believed that embolism secondary to hypercoagulability is the most important cause of stroke in cancer patients [20]. In a recent retrospective cross-sectional study, the most common stroke mechanism in cancer patients was cryptogenic (embolic stroke of unknown source), followed by large vessel disease [17,21]. Conventional stroke risk factors such as hypertension, diabetes, and atrial fibrillation are underrepresented in cancer-related stroke, invoking hypercoagulability and other cancer-specific causes of stroke [10,22,23].
Stroke patients with cancer are often excluded from receiving thrombolytic therapy due to concerns about brain metastasis, thrombocytopenia, coagulopathy, recent surgery, or overall poor prognosis [24,25]. That is reflected in our study, as significantly fewer MC patients received bridging lytic therapy than cancer-free patients (13% vs. 23%, P<0.001), despite similar stroke severity. The rate of ICH was similar (about 20%) in MC and non-MC patients treated with thrombectomy.
The most important question addressed by our study is whether it is worthwhile and beneficial to perform MT in MC patients who experience LVO stroke, given their poor prognosis and comorbidities. The two groups were highly comparable with regard to age, sex, and stroke severity (Table 1). By contrast, the MC patients had significantly higher comorbidity indices overall, including higher rates of infection (pneumonia, sepsis) and thrombosis (acute coronary syndrome, DVT, and pulmonary embolism). Hospital length of stay and all-cause 90-day readmission rates were similar.
In-hospital death was significantly greater in the MC cohort treated with thrombectomy (26% vs. 14%). It is also notable that tracheostomy and PEG were performed significantly less frequently in MC patients, presumably due to more withholding of life sustain therapy. Despite this, the frequency of home discharge was only slightly lower in MC versus non-MC patients: 36% versus 42% overall, which translates into a 49% versus 48% rate of discharge home among those who survived their hospitalization. These encouraging results are consistent with other studies that have addressed clinical and safety outcomes in patients with AIS and active cancer after endovascular treatment. Of 2,583 stroke patients who underwent MT in the MR CLEAN registry, 4.8% had active cancer (diagnosed <12 months prior to stroke, with metastases, or under active treatment), which is comparable to the 2.3% frequency of MC that we observed [3]. In this study, successful reperfusion and ICH rates did not differ between cancer and cancer-free patients. Other studies have also shown that there is no difference in recanalization rates, procedural time metrics, or choice of anesthesia in cancer compared to cancer-free patients who undergo thrombectomy [26-28]. Although mortality was higher and functional outcome was worse in the cancer cohort at 90 days, about 25% had regained functional independence [3].
A smaller single-center study from Korea reported a 7.1% frequency of current malignancy out of a total of 378 AIS patients treated with MT [11]. There was no difference in the rate of good functional outcome (37% vs. 40%) or ICH between those with and without cancer. Other smaller single-center registries and case-control studies have reported a frequency of cancer among MT-treated stroke ranging from 2.7% to 10.3%, and inconsistent results regarding procedural success, the risk of ICH, and clinical outcome compared to cancer-free patients [9-12,29-31]. In our secondary analysis, we showed that 3.5% of MC patients hospitalized for AIS were treated with MT, which is comparable to the rate of 3.8% among cancer-free stroke patients (Figure 1).
Our study has many limitations. First, inherent to the use of administrative databases such as the NRD, diagnostic accuracy may be affected by coding errors, the absence of detailed neurological and imaging data, and the lack of independent auditing and verification of key outcome measures. Also, temporal relationships that occur during hospitalization cannot be elucidated. Second, the NRD lacks data on stroke and medical illness severity scales, location and size of ischemic lesions, baseline or discharge destination, procedural success, timing of acute treatment, concurrent medical treatments such as anticoagulation, and long-term functional outcome. Hence, the results of our regression analysis should be interpreted with caution. Third, we could not distinguish between mortality as a result of stroke complications or from mortality due to withdrawal of care due to patients and family wishes. Fourth, our results are applicable to patients with advanced cancer with metastases, and may not accurately reflect the clinical course of stroke patients with early stage non-MC. Fifth, MC patients were less likely to undergo PEG or tracheostomy placement, which may have confounded the outcome, most likely reflecting decisions to pursue comfort care. Sixth, the NRD does not link patients identifiers across years. Seventh, in the NRD it is not possible to differentiate whether a diagnosis of MC is a new or historical diagnosis. Finally, discharge to home hospice is included under the routine discharge to home classification (inpatient hospice is in a separate category under non-routine discharge) in the NRD, which does not constitute a favorable outcome as we defined it. However, discharge to home hospice is rare in our clinical experience. Despite these limitations and lack of granularity in the NRD, administrative database studies offer strength in numbers, generalizability, and insight into real-world practices, especially for uncommon conditions in which randomized clinical trials are not practical to conduct.


In summary, MC patients with LVO stroke treated with MT are discharged home at a similar rate to cancer-free patients, suggesting that they can benefit from the procedure. Given the many limitations of an administrative database such as the NRD, this analysis should be viewed as preliminary and inconclusive. Pending the publication of more detailed prospective registries and clinical trials, our data may hopefully help clinicians, patients, and caregivers alike make more thoughtful and informed decisions regarding the risks and benefits of MT in stroke patients with MC.

Supplementary materials

Supplementary materials related to this article can be found online at https://doi.org/10.5853/jos.2022.02334.
Supplementary Table 1.
The RECORD statement: checklist of items, extended from the STROBE statement, that should be reported in observational studies using routinely collected health data*
Supplementary Table 2.
International Classification of Disease, Tenth Revision (ICD-10) codes
Supplementary Table 3.
Breakdown of cancer types


S.A.M. receives consulting fees from Biogen for effort as a member of the independent safety monitoring committee for the CHARM trial. The other authors have no relationships to disclose.


Dr. Aboul-Nour created the idea of the project, contributed to methodology, design, statistical planning, and manuscript writing. Dr. Maraey contributed by analyzing the NRD data, statistical planning and analysis. Dr. Jumah contributed to methodology and design, literature review, and manuscript writing. Dr. Khalil contributed by statistical planning and analysis, ICD-10 codes extractions, and revision. Dr. Elzanaty contributed by analyzing the NRD data. Dr. Elsharnoby contributed by analyzing the NRD data. Dr. Almufti, Dr. Chebl, Dr. Miller, and Dr. Mayer contributed to scientific writing and project supervision. Dr. Mayer supervised the entire project, contributed to methodology, design, statistical planning, and manuscript writing. All authors contributed to data interpretation, composition and revision of the article. The manuscript was approved by all authors.

Figure 1.
Cascade diagram showing patient grouping. Of all acute ischemic stroke (AIS) patients who underwent thrombectomy, the primary analysis compared 933 patients with 38,166 patients with no cancer. The 1,438 patients with a cancer diagnosis but no metastases were excluded. The secondary analysis of metastatic cancer patients compared the 933 thrombectomy-treated patients with 25,731 patients treated medically for AIS.
Table 1.
Hospital complications, interventions, and outcomes among stroke patients treated with mechanical thrombectomy, with or without metastatic cancer
Metastatic cancer (n=933) Cancer-free (n=38,166) P
 Age (yr) 68.6±10.7 68.5±14.0 0.932
 Female sex 483 (52) 19,277 (50) 0.685
Disease severity
 APR-DRG severity=4* 488 (52) 14,992 (39) <0.001
 Severe stroke 895 (96) 36,121 (95) 0.331
 Paralysis/paresis 813 (87) 31,261 (82) 0.003
 Aphasia 627 (67) 26,397 (69) 0.405
 Cerebral edema 204 (22) 8,128 (21) 0.812
 Herniation 64 (7) 3,214 (8) 0.257
Hospital complications
 Intracerebral hemorrhage 186 (20) 8,017 (21) 0.605
 Acute kidney injury 134 (14) 5,891 (15) 0.367
 Urinary tract infection 118 (13) 5,330 (14) 0.446
 Pneumonia 125 (13) 2,702 (7) <0.001
 Sepsis 102 (11) 1,823 (5) <0.001
 Deep vein thrombosis 191 (20) 1,735 (5) <0.001
 Acute coronary syndrome 92 (10) 1,721 (5) <0.001
 Pulmonary embolism 117 (13) 601 (2) <0.001
 Coagulopathy 373 (40) 3,456 (9) <0.001
 Thrombocytopenia 155 (17) 2,108 (6) <0.001
 tPA use 120 (13) 8,939 (23) <0.001
 Mechanical ventilation 207 (22) 9,581 (25) 0.147
 PEG 43 (5) 4,288 (11) <0.001
 Tracheostomy 11 (<1) 1,466 (4) <0.001
 In-hospital death 247 (26) 5,243 (14) <0.001
 Discharge to a facility 352 (38) 17,021 (45) 0.005
 Discharge to home 334 (36) 15,902 (42) 0.014
 LOS ≥75th percentile 275 (29) 11,031 (29) 0.833
 90-day readmission 195 (21) 7,486 (20) 0.026
Data are mean±SD or n (%).
APR-DRG, All Patient Refined Diagnosis Related Group; tPA, tissue plasminogen activator; PEG, percutaneous endoscopic gastrostomy; LOS, length of stay.
* Baseline illness severity determined using APR-DRG subclass of 4 is used as an indicator of severe illness (see Methods for more details);
Severe stroke was defined as having one or more of the following elements: paralysis/paresis, aphasia, cerebral edema, cerebral herniation, requiring mechanical ventilation, and/or coma;
Refer to Methods for definitions of poor and favorable outcome.
Table 2.
Multivariate logistic regression analysis comparing mechanical thrombectomy-treated stroke patients with versus without metastatic cancer
Outcome measure Unadjusted OR P Adjusted OR P
In-hospital mortality 2.26 (1.81-2.83) <0.001 2.83 (2.21-3.64) <0.001
Death and discharge to facility 1.28 (1.05-1.56) 0.014 1.11 (0.89-1.37) 0.343
Discharge to home* 1.01 (0.81-1.26) 0.918 1.13 (0.89-1.44) 0.314
Intracerebral hemorrhage 0.94 (0.73-1.20) 0.605 0.79 (0.60-1.02) 0.074
Hemicraniectomy 0.92 (0.13-6.46) 0.931 1.11 (0.16-7.68) 0.918
All-cause 90-day readmission 1.35 (1.04-1.75) 0.027 1.30 (0.99-1.71) 0.052
LOS >75th percentile 1.03 (0.81-1.31) 0.832 0.93 (0.71-1.20) 0.573
OR, odds ratio; LOS, length of stay; APR-DRG, All Patient Refined Diagnosis Related Group; tPA, tissue plasminogen activator.
* Excluding in-hospital mortality;
75th percentile corresponds to 14 days;
Adjusted for age, sex, stroke severity, APR-DRG=4, and tPA use.
Table 3.
Multivariate model for prediction of death or discharge to a facility
Variable Adjusted OR (95% CI) P
Age, per year 1.035 (1.032-1.038) <0.001
Female sex 1.14 (1.05-1.24) 0.001
Metastatic cancer 0.96 (0.76-1.20) 0.711
Severe stroke* 1.94 (1.64-2.29) <0.001
Deep vein thrombosis 1.46 (1.22-1.76) <0.001
Pneumonia 1.59 (1.34-1.91) <0.001
Sepsis 1.70 (1.36-2.13) <0.001
Urinary tract infection 1.34 (1.21-1.49) <0.001
PEG 5.63 (4.79-6.62) <0.001
Tracheostomy 7.01 (4.90-10.02) <0.001
Intracerebral hemorrhage 1.88 (1.69-2.07) <0.001
Variables that were excluded from the final model due to lack of significance included acute kidney injury, pulmonary embolism, and acute coronary syndrome.
OR, odds ratio; CI, confidence interval; PEG, percutaneous endoscopic gastrostomy.
* Severe stroke was defined as having one or more of the following elements: paralysis/paresis, aphasia, cerebral edema, cerebral herniation, requiring mechanical ventilation, and/or coma.


1. Graus F, Rogers LR, Posner JB. Cerebrovascular complications in patients with cancer. Medicine (Baltimore) 1985;64:16-35.
crossref pmid
2. Casado-Naranjo I, Calle ML, Falcón A, Serrano A, Portilla JC, Ramírez-Moreno JM. Intravenous thrombolysis for acute stroke in patients with cancer. J Neurol Neurosurg Psychiatry 2011;82:1404-1405.
crossref pmid
3. Verschoof MA, Groot AE, de Bruijn SFTM, Roozenbeek B, van der Worp HB, Dippel DWJ, et al. Clinical outcome after endovascular treatment in patients with active cancer and ischemic stroke: a MR CLEAN registry substudy. Neurology 2022;98:e993e1001.
crossref pmid
4. Jovin TG, Chamorro A, Cobo E, de Miquel MA, Molina CA, Rovira A, et al. Thrombectomy within 8 hours after symptom onset in ischemic stroke. N Engl J Med 2015;372:2296-2306.
crossref pmid
5. Campbell BC, Mitchell PJ, Kleinig TJ, Dewey HM, Churilov L, Yassi N, et al. Endovascular therapy for ischemic stroke with perfusion-imaging selection. N Engl J Med 2015;372:1009-1018.
crossref pmid
6. Goyal M, Demchuk AM, Menon BK, Eesa M, Rempel JL, Thornton J, et al. Randomized assessment of rapid endovascular treatment of ischemic stroke. N Engl J Med 2015;372:1019-1030.
crossref pmid
7. Saver JL, Goyal M, Bonafe A, Diener HC, Levy EI, Pereira VM, et al. Stent-retriever thrombectomy after intravenous t-PA vs. t-PA alone in stroke. N Engl J Med 2015;372:2285-2295.
crossref pmid
8. Berkhemer OA, Fransen PS, Beumer D, van den Berg LA, Lingsma HF, Yoo AJ, et al. A randomized trial of intraarterial treatment for acute ischemic stroke. N Engl J Med 2015;372:11-20.
9. Lee D, Lee DH, Suh DC, Kwon HS, Jeong DE, Kim JG, et al. Intra-arterial thrombectomy for acute ischaemic stroke patients with active cancer. J Neurol 2019;266:2286-2293.
crossref pmid pdf
10. Jung S, Jung C, Kim JH, Choi BS, Bae YJ, Sunwoo L, et al. Procedural and clinical outcomes of endovascular recanalization therapy in patients with cancer-related stroke. Interv Neuroradiol 2018;24:520-528.
crossref pmid pmc pdf
11. Cho BH, Yoon W, Kim JT, Choi KH, Kang KW, Lee JH, et al. Outcomes of endovascular treatment in acute ischemic stroke patients with current malignancy. Neurol Sci 2020;41:379-385.
crossref pmid pdf
12. Sallustio F, Mascolo AP, Marrama F, Koch G, Alemseged F, Davoli A, et al. Safety and efficacy of reperfusion therapies for acute ischemic stroke patients with active malignancy. J Stroke Cerebrovasc Dis 2019;28:2287-2291.
crossref pmid
13. Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project (HCUP) [Internet]. Rockville, MD: Agency for Healthcare Research and Quality; 2022. [cited 2022 October 10]. Available from: https://www.hcup-us.ahrq.gov/.

14. Henderson T, Shepheard J, Sundararajan V. Quality of diagnosis and procedure coding in ICD-10 administrative data. Med Care 2006;44:1011-1019.
crossref pmid
15. Averill RF, Goldfield N, Hughes JS, Bonazelli J, McCullough EC, Steinbeck BA, et al. All Patient Refined Diagnosis Related Groups (APR-DRGs): version 20.0. Methodology overview [Internet]. Wallingford, CT: 3M Health Information Systems; 2003. [cited 2022 October 10]. Available from: https://www.hcup-us.ahrq.gov/db/nation/nis/APR-DRGsV20MethodologyOverviewandBibliography.pdf.

16. Dicpinigaitis AJ, Sursal T, Morse CA, Briskin C, Dakay K, Kurian C, et al. Endovascular thrombectomy for treatment of acute ischemic stroke during pregnancy and the early postpartum period. Stroke 2021;52:3796-3804.
crossref pmid
17. Motataianu A, Maier S, Andone S, Barcutean L, Serban G, Bajko Z, et al. Ischemic stroke in patients with cancer: a retrospective cross-sectional study. J Crit Care Med (Targu Mures) 2021;7:54-61.
crossref pmid pmc
18. Navi BB, Iadecola C. Ischemic stroke in cancer patients: a review of an underappreciated pathology. Ann Neurol 2018;83:873-883.
crossref pmid pmc pdf
19. Grisold W, Oberndorfer S, Struhal W. Stroke and cancer: a review. Acta Neurol Scand 2009;119:1-16.
crossref pmid
20. Rickles FR, Edwards RL. Activation of blood coagulation in cancer: Trousseau’s syndrome revisited. Blood 1983;62:14-31.
crossref pmid pdf
21. Adams HP Jr, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, et al. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke 1993;24:35-41.
crossref pmid
22. Kim SG, Hong JM, Kim HY, Lee J, Chung PW, Park KY, et al. Ischemic stroke in cancer patients with and without conventional mechanisms: a multicenter study in Korea. Stroke 2010;41:798-801.
crossref pmid
23. Murthy SB, Karanth S, Shah S, Shastri A, Rao CP, Bershad EM, et al. Thrombolysis for acute ischemic stroke in patients with cancer: a population study. Stroke 2013;44:3573-3576.
crossref pmid
24. Khorana AA, Francis CW, Culakova E, Fisher RI, Kuderer NM, Lyman GH. Thromboembolism in hospitalized neutropenic cancer patients. J Clin Oncol 2006;24:484-490.
crossref pmid
25. Selvik HA, Naess H, Kvistad CE. Intravenous thrombolysis in ischemic stroke patients with active cancer. Front Neurol 2018;9:811.
crossref pmid pmc
26. Lee EJ, Bae J, Jeong HB, Lee EJ, Jeong HY, Yoon BW. Effectiveness of mechanical thrombectomy in cancer-related stroke and associated factors with unfavorable outcome. BMC Neurol 2021;21:57.
crossref pmid pmc pdf
27. Yoo J, Kim YD, Park H, Kim BM, Bang OY, Kim HC, et al. Immediate and long-term outcomes of reperfusion therapy in patients with cancer. Stroke 2021;52:2026-2034.
crossref pmid
28. Ciolli L, Bigliardi G, Ferraro D, Maffei S, Vandelli L, Dell’Acqua ML, et al. Efficacy of mechanical thrombectomy in patients with ischemic stroke and cancer. J Clin Neurosci 2021;91:20-22.
crossref pmid
29. Joshi KC, Grewal P, Beer-Furlan A, Vargas A, Osteraas N, Dafer R, et al. Endovascular thrombectomy for acute ischemic stroke in patients with cancer: a propensity-matched analysis. J Neurointerv Surg 2022;14:1161-1165.
crossref pmid
30. Oki S, Kawabori M, Echizenya S, Shimoda Y, Shimbo D, Osanai T, et al. Long-term clinical outcome and prognosis after thrombectomy in patients with concomitant malignancy. Front Neurol 2020;11:572589.
crossref pmid pmc
31. Ren C, Xu G, Liu Y, Liu G, Wang J, Gao J. Effect of conscious sedation vs. general anesthesia on outcomes in patients undergoing mechanical thrombectomy for acute ischemic stroke: a prospective randomized clinical trial. Front Neurol 2020;11:170.
crossref pmid pmc


Browse all articles >

Editorial Office
Department of Neurology, Asan Medical Center,Ulsan University College of Medicine
88, Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Korea
Submission, status and progress, etc ⟫ E-mail: editor@j-stroke.org
Website and system ⟫ E-mail: journal@m2community.co.kr
Publishing company ⟫ E-mail: jin@ijpnc.com
Developed in M2PI
Copyright © 2023 by Korean Stroke Society.
Close layer
prev next