Investigating Outcomes Post–Endovascular Thrombectomy in Acute Stroke Patients With Cancer
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Abstract
Background and Objectives Cancer is a common comorbidity in patients with acute ischemic stroke (AIS). Randomized controlled trials that established endovascular thrombectomy (EVT) as the standard of care for large vessel occlusion generally excluded patients with cancer. As such, the clinical benefits of endovascular thrombectomy in the cancer population are currently poorly established. We examine clinical outcomes of patients with cancer who underwent EVT using a large inpatient database, the National Inpatient Sample (NIS).
Methods The NIS was queried for AIS admission between 2016 and 2019, and patients with cancer were identified. Baseline demographics, comorbidities, reperfusion therapies, and outcomes were compared between patients with AIS with and without cancer. For patients who underwent EVT, propensity score matching was used to study primary outcomes such as risk of intracranial hemorrhage, hospital length of stay, and discharge disposition.
Results During the study period, 2,677,200 patients were hospitalized with AIS, 228,800 (8.5%) of whom had a diagnosis of cancer. A total of 132,210 patients underwent EVT, of which 8,935 (6.8%) had cancer. Over 20% of patients with cancer who underwent EVT had a favorable outcome of a routine discharge home without services. On adjusted propensity score analysis, patients with cancer who underwent EVT had similar rates of intracranial hemorrhage (OR 1.03, CI 0.79–1.33, p = 0.90) and odds of a discharge home, with a significantly higher rate of prolonged hospitalization greater than 10 days (OR 1.34, CI 1.07–1.68, p = 0.01). Compared with patients without cancer, patients with metastatic cancer who underwent EVT also had similar rates of intracranial hemorrhage (OR 1.03, CI 0.64–1.67, p = 1.00) and likelihood of routine discharge (OR 0.83, CI 0.51–1.35, p = 0.54) but higher rates of in-hospital mortality (OR 2.72, CI 1.52–4.90, p < 0.01).
Discussion Our findings show that in contemporary medical practice, patients with acute stroke with comorbid cancer or metastatic cancer who undergo endovascular thrombectomy have similar rates of intracranial hemorrhage and favorable discharges as patients without cancer. This suggests that patients with AIS who meet the criteria for reperfusion therapy may be considered in the setting of a comorbid cancer diagnosis.
Glossary
- AIS=
- acute ischemic stroke;
- EVT=
- endovascular thrombectomy;
- NIS=
- National Inpatient Sample;
- Cancer-AIS=
- cancer–acute ischemic stroke;
- Noncancer-AIS=
- noncancer–acute ischemic stroke;
- Cancer-EVT=
- cancer–endovascular thrombectomy;
- Noncancer-EVT=
- noncancer–endovascular thrombectomy;
- AF=
- atrial fibrillation;
- DM=
- diabetes mellitus;
- HTN=
- hypertension;
- HLD=
- hyperlipidemia;
- CHF=
- chronic heart failure;
- CKD=
- chronic kidney disease;
- NIHSS=
- NIH Stroke Scale;
- DHC=
- decompressive hemicraniectomy;
- PEG=
- percutaneous endoscopic gastrostomy;
- DVT=
- deep venous thrombosis;
- PE=
- pulmonary embolism;
- UTI=
- urinary tract infection;
- MI=
- myocardial infarction;
- AKI=
- acute kidney injury;
- SNF=
- skilled nursing facility;
- CRF=
- chronic renal failure;
- OSA=
- obstructive sleep apnea
Cancer is a commonly occurring comorbidity in patients with acute ischemic stroke (AIS).1,2 Multiple retrospective studies have suggested that between 5% and 10% of patients with AIS will have a known malignancy, with the highest risk period within the first 6 months after cancer diagnosis or during active chemotherapy.1,-,3 For IV thrombolysis, national guidelines suggest that alteplase may be reasonable in patients with life expectancy greater than 6 months.4 However, many patients with cancer are ineligible for thrombolysis given the increased prevalence of contraindications such as concurrent anticoagulation use, recent major surgery, metastatic brain invasion, or hematologic problems such as coagulopathy or thrombocytopenia.5 For such patients, endovascular thrombectomy (EVT) may be the only acute treatment possible; yet, there are limited guidelines or clinical studies to guide practice.
Starting in 2015, when multiple landmark trials demonstrated the powerful benefits of endovascular therapy, endovascular thrombectomy has quickly become the standard of care for select patients with AIS with large vessel occlusions.6,-,10 However, these studies generally excluded patients with cancer, or such patients constituted a small proportion of the overall sample size.6,-,8,11 Most studies on malignancy and endovascular thrombectomy have been single-center case series or retrospective reviews with varying results.12,-,14 Practice trends in the treatment of patients with AIS and cancer had been previously characterized using a large national inpatient database15; however, the study period (1998–2015) was before the modern thrombectomy era, and less than 1% of all patients underwent endovascular thrombectomy. As such, the clinical benefits of endovascular thrombectomy in the cancer population are currently poorly established.
The prevalence of cancer and the ongoing evolution of stroke therapies merit analysis of the 2 together. Given the gap of knowledge on contemporary practice, we sought to examine outcomes for such patients undergoing acute reperfusion therapy. To do so, we examined a representative sample of patients from 2016 to 2019 in the National Inpatient Sample (NIS), a large publicly available inpatient care database. We hypothesized that patients with acute ischemic stroke and comorbid cancer may experience similar benefits from endovascular thrombectomy as patients without cancer. A better understanding of treatment efficacy in the setting of malignancy is important to practitioners when evaluating such patients for emergent interventions.
Methods
Standard Protocol Approvals, Registrations, and Patient Consents
This study did not include any experiments using human participants or live vertebrates and was therefore exempt from approval from an institutional or licensing committee. The NIS is a publicly accessible database that retains anonymity. This study therefore did not meet the requirement for institutional review board approval or patient consent.
Database Characteristics
The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) database is a large, publicly available inpatient care database representing approximately 20% of all community hospital admissions in the United States.16 Captured data elements include demographic characteristics, hospital and regional information, diagnoses, medications, procedures, and discharge diagnosis. The large sample size of the data allows for analysis of national estimates. As the NIS is publicly available and contains no identifiable patient information, no approval by institutional review board or patient consent was required for this study. All diagnostic and procedural codes used can be found in eTables 1 and 2 of the Supplement, links.lww.com/WNL/C358.
Patient Selection
The NIS database of 2016–2019 was queried using International Classification of Diseases, 10th Revision (ICD-10) diagnosis codes to generate a data set of patients with AIS (ICD-10 code: I63). Patients with malignancy were identified using ICD-10 codes that reflect a current diagnosis or malignancy not otherwise documented as resolved. Diagnosis codes suggestive of personal history of cancer or of a previous encounter with a neoplasm were excluded for selection of malignancy (Z85). In this AIS data set, patients with AIS and malignancy (Cancer-AIS) and patients without malignancy (Noncancer-AIS) were defined as separate cohorts. An additional data set was generated from the AIS data set by selecting for endovascular therapy (EVT) using ICD-10 procedure codes. In this EVT data set, patients who received EVT were grouped into those with (Cancer-EVT) or without malignancy (Noncancer-EVT). An additional subgroup analysis was performed on patients with metastatic cancer by ICD-10 procedure codes (eTable 1 of the Supplement, links.lww.com/WNL/C358).
Patient Characteristics
Baseline demographics and clinical characteristics analyzed included patient age, sex, and race. Comorbidities included atrial fibrillation, diabetes mellitus, hypertension, hyperlipidemia, chronic heart failure, chronic kidneys disease, venous thromboembolisms such as deep vein thrombosis or pulmonary embolisms, smoking, and use of anticoagulation or antiplatelet medication. Stroke characteristics included the NIH Stroke Scale (NIHSS), use of IV tissue plasminogen activator (tPA), arterial distribution of stroke, aphasia, hemiplegia, herniation, coma, and mechanical ventilation greater than 24 hours. Neurologic complications included nontraumatic intracranial hemorrhage, requirement of decompressive hemicraniectomy, placement of a percutaneous endoscopic gastrostomy tube, or tracheostomy placement. Medical complications were pneumonia, urinary tract infection, sepsis, acute myocardial infarction, and acute kidney injury (eTable 2 of the Supplement, links.lww.com/WNL/C358).
Outcomes
Primary clinical end points were rates of intracranial hemorrhage, hospitalization length, in-hospital mortality, and discharge dispositions including routine and nonroutine discharges. As per HCUP definition, routine discharges were primarily to home or self-care without special services and were considered a favorable outcome. Nonroutine discharges included home with health care (HHC), transfer to short-term hospital, transfer to skilled nursing facility (SNF), against medical advice (AMA), and missing disposition data. For propensity score matching, we defined prolonged length of stay as ≥10 days. All HCUP definitions can be found in eTable 3 in the Supplement, links.lww.com/WNL/C358.
Statistical Analysis
Categorical variables were compared using the Pearson χ2 test. Continuous variables were evaluated for normality using the Kolmogorov-Smirnov test. Normally and non-normally distributed continuous variables were tested using the Student t test and Mann-Whitney U test, respectively. A propensity score for each case was estimated using covariates in multivariate binary logistic regression. Covariates included baseline characteristics, comorbidities, stroke characteristics, and medical complications to create nearest neighbor 1:1 matching for patients with AIS with or without malignancy and an additional subgroup analysis for patients with known metastatic cancer. Matched baseline characteristics included age, sex, and non-White race. To match for comorbidities, the Elixhauser comorbidities index was utilized, which is an extensive list of 28 common comorbidities identified by HCUP. A full list of all comorbidities in Elixhauser is provided in eTable 4 of the Supplement, links.lww.com/WNL/C358.17 Additional stroke-specific comorbidities (not included in Elixhauser) matched for included atrial fibrillation, hyperlipidemia, active smoking, antithrombotic medications (antiplatelet and anticoagulants), and venous thromboembolisms. Matched stroke characteristics included NIHSS, posterior circulation occlusions, aphasia, hemiplegia, herniation, coma, and mechanical ventilation greater than 24 hours and concurrent administration of thrombolysis. Matched medical complications include pneumonia, urinary tract infection, sepsis, acute myocardial infarction, and acute kidney injury.
Outcome variables included likelihood of a nontraumatic intracranial hemorrhage, prolonged LOS (defined as hospitalization greater than 10 days), routine discharge, nonroutine discharge, and in-hospital mortality. Statistical Product and Service Solutions (SPSS) statistical software was used for analysis, and statistical significance was set at <0.05 (IBM Corp. Released 2020. IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY: IBM Corp).
Data Availability
All data used in this study are available on reasonable request of the corresponding author. Completion of onboarding procedures specified by the Healthcare Cost and Utilization Project will be required.
Results
Baseline Patient Characteristics and Comorbidities
Between January 2016 through December 2019, 2,677,200 patients were hospitalized with a diagnosis of AIS (Table 1). Of these hospitalizations, 228,880 (8.5%) patients had comorbid AIS and cancer (Cancer-AIS). Compared with patients without cancer, Cancer-AIS patients were likely to be older (71.4 vs 69.3 years; p < 0.01) with significantly lower rates of traditional cardiovascular risk factors such as diabetes (OR 0.73, 95% CI 0.72–0.73, p < 0 .01), hypertension (OR 0.77, 95% CI 0.76–0.77, p < 0 .01), hyperlipidemia (OR 0.71, 95% CI 0.71–0.72, p < 0 .01), or congestive heart failure (OR 0.90, 95% CI 0.88–0.92, p < 0 .01). Patients with cancer had significantly higher rates of venous thromboembolisms (OR 3.7, 95% CI 3.60–3.72, p < 0 .01) and anticoagulation use (OR 1.24, 95% CI 1.22–1.25, p < 0 .01) when compared with patients without cancer. Cancer-AIS patients were more likely to present with higher mean stroke NIHSS scores (7.3 vs 6.9, p < 0 .01) and were more likely to require mechanical ventilation (OR 1.24, 95% CI 1.22–1.26, p < 0 .01) during their hospitalization than patients with AIS without cancer.
Baseline Demographics, Comorbidities, Stroke Severity, Treatment Types, and Discharge Dispositions for All Patients Hospitalized With a Diagnosis of Acute Ischemic Stroke With and Without Active Malignancy From 2016 to 2019
In our sample, a total of 132,210 patients underwent EVT, of which 8,935 (6.8%) had cancer (Table 2). Patients with cancer who underwent endovascular thrombectomy (Cancer-EVT) were more likely to be older (69.7 vs 68.9 years, p < 0.01), with lower rates of traditional cardiovascular risk factors, as well as atrial fibrillation (OR 0.85, 95% CI 0.81–0.89, p < 0 .01), compared with patients without cancer who underwent EVT. Cancer-EVT patients had significantly higher rates of venous thromboembolisms (OR 3.10, 95% CI 2.88–3.33, p < 0 .01) and use of anticoagulation (OR 1.22, 95% CI 1.15–1.30, p < 0 .01) than EVT patients without cancer. Both patients without and with cancer undergoing endovascular thrombectomy had similar presenting mean NIHSS scores (14.1 for both groups) and rates of posterior circulation occlusions (5.9% for both groups). In the EVT cohort, the most common primary cancer type was hematopoietic (28.3%), followed by lung (16%) and gastrointestinal (14.8%). Of note, 27.9% of patients had metastatic cancer at the time of index hospitalization (eTable 5 of the Supplement, links.lww.com/WNL/C358).
Baseline Demographics, Comorbidities, Stroke Severity, Treatment Types, and Discharge Dispositions for All Patients Hospitalized Who Underwent Endovascular Thrombectomy With and Without Active Malignancy From 2016 to 2019
Reperfusion Treatments and Trends
The overall rate of thrombolysis with tPA was 2.7% and thrombectomy was 4.9%, with 0.6% of patients with AIS receiving both. Patients with AIS and cancer were less likely to receive reperfusion therapy such as thrombolysis (OR 0.47, 95% CI 0.45–0.48, p < 0 .01), EVT (OR 0.77, 95% CI 0.75–0.78, p < 0 .01), or the combination of both treatments (OR 0.50, 95% CI 0.46–0.54, p < 0 .01). In addition, patients with cancer who underwent EVT were less likely to receive bridging thrombolysis (7.8 vs 12%, OR 0.62, p < 0.01) (Table 1). On a subgroup analysis, patients with metastatic cancer had the lowest rates of thrombolysis with tPA (0.7%) and thrombectomy (3.7%) (Table 3). When controlled for anticoagulation use, patients with cancer or metastatic disease still had lower rates of thrombolysis than patients without cancer. Among patients with cancer and AIS, patients with ICD-10 codes consistent with gastrointestinal (OR 1.16 95% CI 1.10–1.23 p < 0.01), skin (OR 1.19 95% CI 1.04–1.36, p = 0.01), female reproductive (OR 1.46 95% CI 1.34–1.60 p < 0.01), and urologic (OR 1.171 95% CI 1.10–1.25, p < 0.01) cancers were associated with increased rates of EVT. Patients with ICD-10 codes consistent with metastatic (OR 0.94 95% CI 0.89–0.98, p = 0.01), male reproductive (OR 0.31, 95% CI 0.13–0.75, p = 0.01), endocrine (OR 0.79 95% CI 0.69–0.90, p < 0.01), and neurologic (OR 0.59 95% CI 0.54–0.64, p < 0.01) cancers were less likely to undergo EVT.
Annual Rates of Thrombolysis and Endovascular Thrombectomy for All Patients With Acute Ischemic Stroke, Patients With AIS With Active Cancer, and Patients With AIS With Metastatic Cancer From 2016 to 2019
Over the study period, administration of tPA remained constant at 2.7% in all patients with AIS and increased from 1.3% to 1.4% in patients with AIS with cancer (Table 3). There were continuous annual increases in the rates of EVT (Figure). The overall rate in all patients increased from 3.8% in 2016 to 6.0% in 2019, equating to a 58% increase in just 3 years. Among patients with cancer, the rate increased from 2.8% in 2016 to 4.9% in 2019, resulting in a 75% increase. Patients with metastatic cancer had similar temporal trends as the overall cohort, with a pronounced increase in the annual thrombectomy rates, from 2.3% in 2016 to 4.5% by 2019, resulting in an 87% increase in 3 years. However, despite the annual increases, treatment rates still differed between patient groups in 2019—patients with cancer or metastatic cancer were 18% and 25%, respectively, less likely to undergo thrombectomy than patients without cancer on unadjusted analysis.
Annual rates of thrombolysis and endovascular thrombectomy from 2016 to 2019 in all patients with stroke, patients with active cancer, and patients with metastatic cancer. tPA = thrombolysis with tissue plasminogen activator; EVT = endovascular thrombectomy; All EVT = overall thrombectomy rate; CA-EVT = thrombectomy rate in patients with active cancer, MET-EVT = thrombectomy rate in patients with metastatic cancer; All tPA = overall thrombolysis rate; CA tPA = = thrombolysis rate in patients with active cancer; MET tPA = thrombolysis rate in patients with metastatic cancer.
Clinical Outcomes
Ultimately, Cancer-AIS patients were likely to have longer hospitalization lengths (6.32 days vs 5.18 days, p < 0 .01) and higher rates of inpatient mortality (OR 1.93, 95% CI 1.91–1.96, p < 0 .01) than patients without cancer. In addition, patients with cancer were less likely to experience routine discharge (OR 0.64, 95% CI 0.64–0.65, p < 0 .01) and more likely to experience nonroutine discharge discharges (OR 1.18, 95% CI 1.17–1.19, p < 0 .001) such as home with care or transfer to a short-term hospital compared with patients without cancer. On unadjusted analysis, Cancer-EVT patients had similar rates of intracranial hemorrhage (13.6%) as EVT patients without cancer but were less likely to be routinely discharged (OR 0.71, 95% CI 0.68–0.75, p < 0 .01) with higher rates of in-hospital mortality (OR 1.38, 95% CI 1.29–1.47, p < 0 .01) than EVT patients without cancer.
Propensity score matching produced comparison groups of patients with and without cancer (844) and comparison groups of patients with and without metastatic disease (221). Baseline characteristics of the matched cohorts are shown in Table 4. There were no differences in Elixhauser, NIHSS, age, sex, or posterior circulation strokes among the propensity score cancer and no cancer groups. There were no differences in Elixhauser, NIHSS, sex, or posterior circulation strokes between patients with and without metastatic disease. Patients without metastasis were older (70.34 ±13.48 years) than patients with metastasis (67.84±10.79 years) (p = 0.01).
On adjusted analysis, Cancer-EVT had no significant differences in the likelihood of intracranial hemorrhage (p = 1.00) or routine discharge (p = 0.54) compared with EVT patients without cancer. However, Cancer-EVT patients had a nonsignificant trend toward higher in-hospital mortality (OR 1.33, 95% CI 0.98–1.81, p = 0.09) and significantly higher likelihood of a prolonged hospitalization course greater than 10 days (OR 1.34 95% CI 1.07–1.68, p < 0.01) than EVT patients without cancer (Table 4). In patients with AIS undergoing EVT, lung cancer (OR 2.38, 95% CI1.50–3.78, p < 0.01), urologic cancer (OR 1.90, 95% CI 1.10–3.2, p = 0.03), and metastatic cancer (OR 2.29, 95% CI1.57–3.33) p < 0.01) were associated with inpatient mortality. Hematopoietic malignancy (OR 1.78, 95% CI 1.32–2.41 p < 0.01) was associated with increased hospital stay of 10 days or longer (eTable 6 of the Supplement, links.lww.com/WNL/C358). In the subgroup of patients with metastatic cancer who underwent EVT, there again were no significant differences in the likelihood of an intracranial hemorrhage or routine discharge when compared with patients without cancer when compared with EVT patients without metastatic disease. However, patients with metastatic cancer had a nonsignificant trend toward lower likelihood of nonroutine discharge (OR 0.67, 95% CI 0.45–1.01, p < 0.07) and a significantly higher likelihood of inpatient mortality (OR 2.72, 95% CI 1.52–4.90, p < 0 .01) than EVT patients without metastatic cancer (Table 5).
Propensity Score–Adjusted Outcomes of Patients Undergoing EVT With vs Without Cancer
Propensity Score–Adjusted Outcomes of Patients Undergoing EVT With Metastatic Cancer vs Without Cancer
Discussion
In this study using a large national inpatient data set from 2016 to 2019, we demonstrated that in the modern thrombectomy era, over 20% of patients with cancer who underwent endovascular thrombectomy had a favorable discharge to home without services. In addition, adjusted analysis revealed that patients with cancer have comparable rates of favorable outcomes such as routine discharge and did not have significant differences in adverse events such as intracerebral hemorrhage, nonroutine discharges, and inpatient mortality. Likewise, patients with metastatic cancer also had similar rates of routine discharge as patients without cancer, although with a higher risk of in-hospital mortality. Finally, although the rates of EVT are continuing to increase, patients with cancer or malignancy were still less likely to receive this treatment as of 2019.
This study provides temporal trends and clinical outcomes for patients with cancer who undergo EVT in the modern thrombectomy era. Prior studies on the subject have been either case series, smaller registry data, or retrospective database reviews before the widespread adoption of endovascular thrombectomy.12,13,15,18 Our findings are in line with the results of prior smaller registry studies, which showed good functional outcome rates between 15% and 36% in patients with cancer who undergo EVT.13,18 A recent analysis of a similar database sample showed that patients with cancer undergoing acute reperfusion strategies (thrombolysis and/or EVT) have survival benefits that offset malignancy-related adverse outcomes, although they did not do a propensity score analysis to adjust for confounding variables.19
Our study highlights the potential benefit of endovascular thrombectomy for patients with cancer in contemporary practice and supports the need to establish national guidelines for providers. Importantly, there was no difference in the NIHSS between patients with cancer and patients without cancer who underwent endovascular thrombectomy. This suggests that similar treatment selection guidelines were applied between the groups. The observed lower rates of reperfusion therapy may be due to reluctance by treating physicians due to concerns about comorbidities or life expectancy. However, given the poor prognosis for patients with large vessel occlusions without acute reperfusion therapy, limiting treatment based on malignancy status may ultimately result in a Self-fulfilling prophecy. Patients with even advanced malignancies are living longer with targeted treatments and immunotherapies.20,21 Given that a significant portion of these patients may return to their baseline functional status after thrombectomy, reperfusion therapy should not be withheld solely on the basis of malignancy and individualized decision-making with families should occur.
Our study has several limitations. Foremost, as a retrospective review of administrative data, we were unable to obtain more granular data such as patients' premorbid functional status, cancer stage or recent treatments (outside of the index hospitalization), life expectancy, and time from stroke onset to presentation. Patient preferences are also not reflected as the database reports more objectively tangible variables. As such, there may be the potential for confounding by indication in treatments and outcomes. Likewise, we were unable to assess the patients' code status, which may partially account for the higher rates of in-hospital mortality seen in the cancer cohort. To mitigate this, we performed propensity score matching to ameliorate differences in comorbidities and clinical severity. Although propensity score matching allows for more suitable comparison groups, it does not address the selection bias inherent to database analysis. Still, the large sample size captured by the NIS reflects distributions of trends seen in the larger population. Second, given our reliance on diagnosis and procedure ICD-10 codes, there may have been misclassification of some patients' information at the time of coding. ICD-10 codes may capture a large population without specific context; therefore, we must select the most relevant contexts to analyze, such as the cohort of patients who specifically received IV tPA. Third, the NIS collects inpatient data, and postdischarge data are therefore not available. With this limitation, we were unable to study the time window of presentation and treatment, which plays a large role in patient selection of tPA or EVT for AIS. We were also unable to characterize longer-term stroke outcomes after hospital discharge. Fourth, the patients with AIS with comorbid cancer who underwent endovascular thrombectomy were presumably selected for treatment using established neurologic clinical criteria. This must be emphasized as it presents the potential for selection bias of patients with cancer with better neurologic status. We do not compare patients with AIS with cancer who did not undergo endovascular thrombectomy, and therefore, the results are not generalizable to all patients with AIS with comorbid cancer. Our study also has multiple strengths. As the largest study of its kind, it is powered to control for multiple variables and minimizes the effects of any individual misclassification. It reflects real-world contemporary stroke management since the proliferation of endovascular thrombectomy. Given the logistical and ethical constraints of conducting a randomized control trial on this topic, it may be the closest approximation of the potential benefits of endovascular thrombectomy in the cancer population.
In conclusion, we report that in contemporary medical practice, patients with acute stroke with comorbid cancer who undergo endovascular thrombectomy have similar rates of intracranial hemorrhage and likelihood for a favorable outcome at discharge as patients without cancer. Although limited to inpatient data, the comparable outcomes between the groups suggest that reperfusion therapy may be considered for AIS in patients with cancer. These findings may inform shared decision-making on an individual basis.
Study Funding
The authors report no targeted funding.
Disclosure
The authors report no relevant disclosures. Go to Neurology.org/N for full disclosures.
Appendix Authors

Footnotes
Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
Submitted and externally peer reviewed. The handling editor was José Merino, MD, MPhil, FAAN.
Editorial, page 1021
CME Course: NPub.org/cmelist
- Received February 15, 2022.
- Accepted in final form July 21, 2022.
- © 2022 American Academy of Neurology
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