Is first-pass effect a meaningful metric to evaluate thrombectomy technologies?

Abstract

Background

Good clinical outcomes following stroke thrombectomy have been associated with successful reperfusion following a single pass, often referred to as the first pass effect (FPE). Inherent in FPE is a potential association with rapid recanalization. It remains unclear if the benefit associated with FPE is an epiphenomenon rather than a meaningful metric to evaluate thrombectomy. We retrospectively analyzed a high-volume single-practice database to evaluate the association of FPE with good clinical outcome.

Methods

A database of 1047 consecutive thrombectomies from 2011 to 2020 was retrospectively queried. Demographics and presentation/procedural metrics were correlated with clinical outcome (3-month modified Rankin Scale (mRS)); patients aged 18 years and older with 3-month clinical follow-ups were included. Univariate analysis was performed to evaluate for an association with good clinical outcome (mRS 0-2) at 90 days. Variables meeting a univariate analysis P-value of 0.05 were included in multivariate analyses. Variables included time of onset to recanalization (OTR), onset to puncture (OTP), and puncture to recanalization (PTR), as well as the number of passes.

Results

A total of 685 patients met the criteria for inclusion. Univariate analysis identified nine variables associated with good clinical outcome at 90 days. Multivariate analysis found OTP, patient age, and successful reperfusion (mTICI ≥ 2B) were associated with good clinical outcome. We built a multivariate model across a range of ratios of PTR to OTR. PTR became significantly associated with good clinical outcome (P = 0.044) when PTR/OTR ≥ 3%. Further subset analyses were performed using a conventional definition of FPE. All multivariate analyses revealed time metrics were significantly associated with good clinical outcome while one versus multiple passes was not.

Conclusions

This study demonstrates that time, age, and degree of recanalization are highly associated with good clinical outcome following thrombectomy, whereas the number of passes is not.

Introduction

Mechanical thrombectomy is the standard of care for patients with acute ischemic stroke in the setting of large vessel occlusion within 24 h of the last known well.^1–7 Clinical outcome following thrombectomy is likely dependent on multiple variables, though is clearly impacted by time and procedural efficacy.^8,9

A variable shown to be highly associated with good clinical outcome is the “First Pass Effect” (FPE), whereby complete or near-complete recanalization is achieved with a single thrombectomy pass.^10–12 However, the reason behind this association remains unclear—does FPE truly confer benefit via its inherent association with decreased time to recanalization or do number of “passes” impact thrombectomy outcome for a different reason? On some level, FPE is by definition a surrogate because the brain is unaware of the number of thrombectomy passes, instead responding to a well-described cascade of events following ischemia, including vasogenic edema, ¹³ excitotoxicity, ¹³ peri-infarct depolarization, ¹³ inflammation,^13–15 and apoptosis.^13–15

There are many reasons why FPE might be associated with good clinical outcome. These include reduced clot maceration resulting in lower risk of distal embolization,^16,17 and reduced risk of arterial wall injury including wall thickening or inflammation. ¹⁸ Another possibility is that the number of thrombectomy passes simply reflects a longer procedure (puncture to recanalization time (PTR))—and that reduced procedure time is the cause of improved outcomes. ¹⁹ Accordingly, we hypothesized that FPE may be an epiphenomenon of rapid reperfusion rather than a robust predictor of good clinical outcome in and of itself.

It is crucial to understand whether FPE independently predicts reduced stroke morbidity. If FPE truly predicts good clinical outcome as a stand-alone variable, then a thrombectomy tool that takes longer to deploy but which results in higher rates of FPE should result in better recovery. However, if the true cause of improved clinical outcome from FPE is shorter PTR, then trading increased time for improved likelihood of FPE may lead to worse stroke results.

Our practice maintains a retrospective database with over 1000 consecutive thrombectomy cases. We analyzed this retrospective database from a high-volume, single neuroendovascular practice to explore whether FPE itself is a meaningful metric to predict good clinical outcome or merely a surrogate for more rapid revascularization. These variables were analyzed in both univariate and multivariate models. In addition, the size of our database enabled us to test the impact of PTR on clinical outcome over a series of ratios of the procedural time (PTR) versus the total ischemic time (onset to recanalization (OTR)) from 1% to 10% to better understand the respective impact of each of these time variables versus FPE.

Methods

Patients aged over 18 years were eligible for this retrospective, IRB-approved, grant-supported study if they had a mechanical thrombectomy between 2011 and the first half of 2020. Patients with incomplete 90-day modified Rankin Scale (mRS) scores were excluded. A small subset of patients exhibited presenting symptoms that were mild or fluctuating. These patients were often admitted for observation by the emergency department, only to experience a significant worsening of symptoms after several hours or sometimes days. These cases, with times from arrival to the fluoroscopy suite exceeding 5 h, were thought to represent a different cohort from the standard workup and treatment and were therefore excluded (N = 36). As our practice style evolved, these patients were increasingly taken emergently for thrombectomy, resulting in fewer delayed thrombectomy cases based on symptom fluctuation. Additionally, patients missing time from symptom onset to reperfusion (OTR) and PTR were excluded (N = 19).

During this 10-year interval, 1047 patients underwent mechanical thrombectomy, with 685 meeting the criteria and being included in the analysis. A total of six neurointerventionalists participated. Following the publication of the 2015 randomized controlled thrombectomy trials,^1–5 our practice saw a significant increase in volume. Between 2015 and late 2017, thrombectomy was performed from 0–6 h of last known well, and from 2017 to 2020, the practice evolved to include delayed window thrombectomy up to 24 h.^6,7

For the purpose of this study, we defined FPE as good recanalization achieved with a single thrombectomy pass that was satisfactory to the treating physician given the clinical context. While we recognize that this definition varies from those provided by prior papers on this subject, we nevertheless include this analysis because it is the most generalizable to clinical practice. To enable a more direct comparison with the prior FPE literature, we repeated our analysis using a definition of both modified thrombolysis in cerebral infarction (mTICI) 3, ¹² and mTICI 2c or better. ¹⁰

All patient characteristics, procedural documentation, time metrics, and clinical and technical outcome were reviewed for this study. Detailed data on each mechanical thrombectomy was recorded. Patient characteristics included age and gender. Procedural details such as the number of passes were recorded. Time metrics in this study included time from symptom onset (or last known well) to puncture (OTP) and PTR. The final clinical and technical outcomes were based on 90-day mRS and mTICI, respectively. This review was inclusive of procedures prior to 2013 before mTICI 2C became a standard technical outcome measure. Therefore, all mTICI 2 and above were reviewed for the sake of this trial to categorize as 2B, 2C, or 3.

All statistical analyses were performed using GraphPad Prism (version 10.2.3), assuming a significance of P = 0.05. Means and standard deviations were used to summarize continuous variables, while frequencies and percentages were used for categorical variables. For the univariate analysis, continuous variables were compared by T-test or ANOVA where appropriate. Categorical variables were compared using chi-square or Fisher's exact tests. Variables chosen for the multivariate analysis included modifiable features of the workup and treatment (OTP and PTR), technical success (mTICI ≥ 2B), multiple passes (multiple passes versus one pass), and patient age. The dependent variable for the model was “good clinical outcome” (90-day mRS ≤ 2).

This multivariate analysis initially resulted in the seemingly contradictory finding of a statistically significant association of OTP with clinical outcome but with PTR demonstrating only a trend towards significance. We hypothesized that this discrepancy was due to the relatively short average PTRs in the context of a longer overall ischemic time (OTR). To test this hypothesis, we conducted ten separate multivariate analyses, each including patients with a PTR/OTR ratio above thresholds ranging from 1% to 10% in 1% increments.

• Multivariate analyses were, therefore, conducted for the cohort of patients with: > 0% PTR/OTR (the entire cohort), ≥ 1% PTR/OTR, ≥ 2% PTR/OTR, ≥ 3% PTR/OTR, ≥ 4% PTR/OTR, ≥ 5% PTR/OTR, ≥ 6% PTR/OTR, ≥ 7% PTR/OTR, ≥ 8% PTR/OTR, ≥ 9% PTR/OTR, and ≥ 10% PTR/OTR.

• For each of these ratios, the multivariate logistic regression analysis was performed with OTP, PTR, age, mTICI 2b or greater, and single versus multiple passes.

• To visualize the impact of the procedure time as a proportion of the total ischemic time, the P-values for PTR for each analysis were graphed (y-axis) versus the minimum PTR/OTR ratio (x-axis) (Figure 1(a)).

Figure 1.

(A) Relationship between groin puncture to recanalization (PTR) significance and PTR/onset to reperfusion (OTR) ratios. This figure illustrates the change in P-values for PTR across various minimum PTR/OTR ratio cohorts in multivariate regression models. The x-axis represents different PTR/OTR ratio thresholds, ranging from > 0% (the entire cohort) as well as 1%–10%, in increments of 1%. The y-axis displays the P-values for the association of PTR with good clinical outcome in each cohort. As the minimum PTR/OTR ratio increases, the P-value for PTR becomes increasingly statistically significant and crosses the 0.05 threshold at a ratio threshold of 0.03. PTR, therefore, plays a more critical role in determining good clinical outcomes when it constitutes a larger proportion of the total ischemic time (OTR). (B) Distribution of patients by minimum PTR/OTR ratio thresholds. This figure shows the distribution of patients across increasing PTR/OTR ratio minimum thresholds. 86.3% of the cohort had a PTR/OTR ratio of ≥ 3%, the threshold for significance.

Two more subset analyses of the patient cohort were performed: repeating the multivariate analysis using a more conventional definition of FPE (mTICI 3 or ≥ mTICI 2c).

An additional multivariate analysis was done on patients who only had multi-pass thrombectomy. Similar variables were chosen for this model based on modifiable features of the workup and treatment (OTP and PTR), technical success (mTICI ≥ 2B), number of passes, and age. The dependent variable was good clinical outcome.

Results

A total of 685 patients were included in the analysis. The mean age was 66.4 years, with 53% being female. Patient demographic and presentation data are summarized in Table 1. There were 685 thrombectomies, 625 (91%) anterior distribution occlusions, and 60 (9%) posterior distribution occlusions. Of the anterior distribution occlusions, there were 281 (45%) right-sided occlusions. These included 80 (28%) carotid terminus, 159 (57%) M1 segment MCA occlusions, 41 (15%) M2, 0 (0%) M3, 0 (0%) A1 segment ACA occlusions, and 1 (0.4%) A2. There were 344 (55%) left-sided occlusions. These included 109 (32%) carotid terminus, 162 (47%) M1 segment MCA occlusions, 68 (20%) M2, 3 (0.9%) M3, 1 (0.3%) A1 segment ACA occlusions, and 1 (0.3%) A2. The posterior occlusions included 42 (70%) basilar artery occlusions, 6 (10%) vertebral artery occlusions, 9 (15%) P1 segment posterior cerebral artery occlusions, and 3 (5%) P2. There were a total of 81 (12%) tandem occlusions. With respect to the thrombectomy technique, there were 534 (78%) cases with first-line combination therapy, 141 (21%) cases with first-line aspiration therapy, and 10 (1%) cases with stentriever only. In 65 (9%) of the aspiration first cases, a stentriever was used on subsequent passes. The median number of passes was two. There was one pass in 292 cases (42%), two passes in 173 (25%), three passes in 129 (19%), four passes in 58 (8%), and greater than or equal to five passes in 33 patients (5%).

Table 1.

Univariate analysis for the entire patient cohort.

	Good outcome	Bad outcome	P value
N	233	453
Time metrics
Symptom onset to puncture (OTP), min	366.1 ± 303.4	418.5 ± 311.2	0.0314
Groin puncture to recanalization (PTR), min	35.12 ± 24.47	43.38 ± 33.76	0.0012
Technical metrics
Number of passes	1.918 ± 1.07	2.194 ± 1.313	0.0061
Multiple passes	123 (52.79%)	271 (59.82%)	0.0819
mTICI ≥ 2C	166 (72.17%)	272 (60.31%)	0.0022
mTICI ≥ 2B	217 (94.35%)	384 (85.14%)	0.0004
Patient characteristics
Age, years	60.36 ± 13.85	69.51 ± 15.03	<0.0001
Female sex	111 (49.12%)	240 (54.79%)	0.1653
Subarachnoid hemorrhage	41 (17.6%)	140 (31.25%)	0.0001
tPA	119 (51.07%)	166 (36.64%)	0.0003
Aspect score	8.865 ± 1.509	8.1 ± 1.95	0.0002

The univariate analysis in Table 1 revealed several variables significantly associated with good clinical outcome at 90 days (mRS ≤ 2). These variables included younger age (P < 0.0001) as well as time metrics including shorter OTP (P = 0.0314), shorter PTR (P = 0.0012), and fewer thrombectomy passes (P = 0.0061). There was a trend towards significance for one versus multiple passes as a binary outcome (P = 0.0819). Achieving mTICI score ≥ 2C (P = 0.0022) or ≥ 2B (P < 0.0004) was significantly associated with a good outcome.

Table 2 presents the results of the multivariate logistic regression analysis. OTP (odds ratio (OR) = 0.9991, P = 0.0027), age (OR = 0.9557, P < 0.0001), and mTICI score ≥ 2B (OR = 2.911, P = 0.0017) were significantly associated with patient outcome. Single-pass versus multi-pass thrombectomy (OR = 0.9419, P = 0.7738) was not significantly associated with patient outcome. Somewhat surprisingly, PTR (P = 0.0803) showed only a trend towards significance.

Table 2.

Multivariate analysis for the entire patient cohort.

Variable	P value	Odds ratio estimate	Odds ratio 95% CI
Symptom onset to puncture (OTP)	0.0027	0.9991	0.9985–0.9997
Groin puncture to recanalization (PTR)	0.0803	0.9933	0.9856–1.001
Age	<0.0001	0.9557	0.9441–0.9669
mTICI ≥ 2B	0.0017	2.911	1.537–5.884
Multiple passes	0.7738	0.9419	0.6262–1.418
Area under the ROC curve
Area		0.7195
Std. error		0.01973
95% confidence interval		0.6808–0.7582
P value		<0.0001

As noted in the “Methods” section, we tested the hypothesis that PTR showed only a trend towards significance because the procedure time was a small percentage of the total ischemic time for a subset of the cohort. We then performed multivariate analyses for PTR/OTR ratios for the entire cohort (PTR/OTR > 0%) as well from 1% to 10% with each percent in between (i.e. 1%, 2%, 3%, etc.), including the same variables (FPE, age, OTP, and PTR) (Figure 1(a)). When the PTR was at least 3% of the OTR, the PTR became statistically significantly associated with clinical outcome. This comprised 86.3% (N = 591) of the total cohort (Figure 1(b)). Above the 3% threshold, the PTR in multivariate analyses became increasingly significant thereby validating our hypothesis (Tables 3–5). Age (OR = 0.9563, P < 0.0001) and mTICI ≥ 2B (OR = 3.541, P = 0.0008) were significantly associated with good clinical outcome for all PTR/OTR ratios in this analysis. Single versus multipass thrombectomy (multiple passes) remained statistically insignificant for all PTR/OTR ratios.

Table 3.

Multivariate analysis of patients with a PTR/OTR ratio above 3%.

Variable	P value	Odds ratio estimate	Odds ratio 95% CI
Symptom onset to puncture (OTP)	0.1607	0.9994	0.9986–1.000
Groin puncture to recanalization (PTR)	0.0439	0.9919	0.9838–0.9996
Age	<0.0001	0.9563	0.9437–0.9685
mTICI ≥ 2B	0.0008	3.541	1.760–7.801
Multiple passes	0.8643	0.9626	0.6216–1.494
Area under the ROC curve
Area		0.7219
Std. error		0.02121
95% confidence interval		0.6804–0.7635
P value		<0.0001

Table 4.

Multivariate analysis for patients with modified thrombolysis in cerebral infarction (mTICI 3) only.

Variable	P value	Odds ratio estimate	Odds ratio 95% CI
Symptom onset to puncture (OTP)	0.0199	0.9989	0.9980–0.9998
Groin puncture to recanalization (PTR)	0.1974	0.9899	0.9743–1.005
Age	<0.0001	0.9532	0.9363–0.9692
Multiple passes	0.6046	1.18	0.6301–2.216
Area under the ROC curve
Area		0.7069
Std. error		0.02893
95% confidence interval		0.6502–0.7636
P value		<0.0001

Table 5.

Multivariate analysis for patients with modified thrombolysis in cerebral infarction (mTICI 2C) and above.

Variable	P value	Odds ratio estimate	Odds ratio 95% CI
Symptom onset to puncture (OTP)	0.0177	0.9991	0.9983–0.9998
Groin puncture to recanalization (PTR)	0.4843	0.9962	0.9852–1.007
Age	<0.0001	0.9562	0.9422–0.9696
Multiple passes	0.4443	0.8217	0.4956–1.359
Area under the ROC curve
Area		0.7073
Std. error		0.02467
95% confidence interval		0.6590–0.7557
P value		<0.0001

To further understand FPE as it is conventionally defined, a multivariate analysis was performed using mTICI 3 (Table 4) and mTICI ≥ 2c (Table 5) patients only. In each case, OTP and age were statistically significantly associated with good clinician outcome. Likewise, in the PTR/OTR ratio analyses using these defintions of FPE, PTR demonstrated significance as the PTR/OTR ratio increased, while multiple passes remained insignificant (data not shown).

To further explore the impact of the number of passes, we repeated both univariate (Supplemental Table 1) and multivariate (Supplemental Table 2) analyses for the subset of patients with multiple passes only. If procedural effects other than time truly impact clinical outcome and explain the FPE, then patients with three or four passes would be expected to have worse outcomes than, for example, those with two passes.

In the multi-pass-only cohort univariate analysis (Supplemental Table 1), variables associated with good clinical outcome included PTR (P = 0.00125), and fewer thrombectomy passes (P = 0.0231). Achieving mTICI score ≥ 2B (P = 0.0018) was associated with good clinical outcome.

In the multivariate logistic regression analysis for the multi-pass cohort (Supplemental Table 2), age (OR = 0.9627, P < 0.0001) and mTICI score ≥ 2B (OR = 2.968 P = 0.0076) were significantly associated with good clinical outcome. Number of passes (P = 0.4515) remained insignificant.

Discussion

In a high-volume single-practice thrombectomy cohort, time from onset to puncture was statistically significantly associated with clinical outcome while our multivariate analysis demonstrated that single versus multipass thrombectomy was not. Interestingly, PTR for the entire cohort showed a trend towards significance in association with good clinical outcome. These findings would appear to contradict the literature. However, a closer look suggests that both findings are plausible, and our analysis is both internally consistent and validated.

FPE was first demonstrated by Zaidat et al. ¹¹ and subsequently supported by Nikoubashman et al., ¹² with sample sizes of 354 patients and 164 patients respectively. Single-pass thrombectomy was associated with significantly better clinical outcomes when compared with multiple passes (Zaidat: 61% vs. 35%, Nikoubashman: 62% vs. 40%, P = 0.013 for both studies).^11,12 Zaidat et al. has been critiqued for comparing good single-pass recanalization with all multi-pass cases (which include both good and bad recanalization). While Zaidat et al. did include time from symptom onset to puncture and puncture to recanalization in the univariate analysis, time was completely excluded from the multivariate analysis, thereby eliminating the possibility of exploring the potentially confounding relationship between time and number of passes. ¹¹ Our study would suggest that the number of passes is confounded by time. In a cohort of the size used in this analysis, we were able to demonstrate that time has the true association with clinical outcome, and therefore single versus multipass recanalization becomes insignificant in the multivariate analysis for the entire cohort and all subset analyses (every ratio of PTR/OTR and for multipass thrombectomy only). We further validated the potential impact of time by demonstrating that PTR becomes increasingly statistically significant as it makes up a larger percentage of the total ischemic time.

Nikoubashman used a matched case-control design (including two matched subset analyses) to compare patients with complete recanalization with single-pass or multi-pass thrombectomy. FPE was statistically significantly associated with good clinical outcome for all patients. FPE was also associated with good clinical outcome in two matched subset analyses, one designed to compensate for statistically significant differences in PTR between the one-pass and multi-pass arms (using a matching tolerance of 30 min), and one in which only M1 occlusion and patients not receiving intra-arterial thrombolysis were added as matching variables. In both cases, FPE was significantly associated with outcome. This study only included patients with a known time of symptom onset and therefore the average time from OTR was relatively low (185 minutes for single pass and 251 minutes for multi-pass). While matching the cohorts for time is likely to reduce the impact of this variable, the relatively large 30-min tolerance between the two cohorts still allowed for a 15%–20% difference in the total ischemic time leaving open the question as to whether the matching achieved its aim. In a multivariate analysis, FPE was associated with favorable outcomes while OTR and tPA administration were not. However, the study does not present the complete multivariate analysis so the entire list of variables included cannot be assessed. The authors note that it is possible that the results of the nonmatched cohort are “systematically biased and that the clinical impact of first-pass and multiple-pass reperfusion is an epiphenomenon that is in fact attributable to prolonged time spans between symptom onset and reperfusion.” ¹³

Our results would support this contention. In a much larger, more heterogeneous, but real-world experience, time was the most significant modifiable variable associated with outcome. The results of the complete cohort analysis and the validation of the model by looking at various PTR/OTR ratios suggest that ischemic time and not the number of passes impact clinical outcome. Understandably, as PTR becomes a smaller proportion of the total ischemic time, it has a less significant impact on clincial outcome. Additionally, our series began in 2011 when mechanical thrombectomy was still a developing technique, so it includes cases with longer procedural times, even for single pass thrombectomy. As a result, our cohort exhibits a broad range of PTR times for thrombectomy procedures of all numbers of passes. This heterogeneity allowed us to reliably statistically disentangle the effects of FPE from procedural time in ways previous, more homogeneous studies have not.

For the 14% of our cohort where PTR represented < 3% of the total ischemic time, PTR did not statistically significantly impact clinical outcome. This result is best understood in the context of the total ischemic time. For example, the average PTR was ∼32 min in 2019. A procedure lasting 38 min would represent a substantial 19% relative difference in PTR. However, when the average OTR was ∼530 min (in 2019), a 6-min difference in PTR only accounts for a 1.1% change in the total ischemic event. Not surprisingly, when analyzing patients with a PTR/OTR ratio > 3%, PTR became significantly associated with good clinical outcome in the multivariate analysis. As the ratio grew larger, the statistical significance of the relationship between PTR and good clinical outcome became stronger. This finding validates our model and underscores the impact of time on stroke outcomes.

It should be noted that FPE was not statistically significantly associated with clinical outcome for any of the PTR/OTR cohorts in our multivariate analysis. Importantly, this cohort (PTR/OTR ratio above 3%) still represents the overwhelming majority of our patient population, reinforcing the significance of rapid recanalization during mechanical thrombectomy.

Even when including only patients who had mTICI ≥ 2c or mTICI 3 recanalization, the conventionally defined FPE, time metrics continued to be a statistically significant predictor of good clinical outcome, while having multiple passes were not. For analyses using these conventional definitions of FPE PTR became statistically significant for the cohort in which it represented a larger percentage of the total ischemic time.

Our analysis strongly supports the contention that on some level the ischemic stroke story is as it has always been; healthier, younger patients who are treated earlier with technically successful thrombectomy have better outcome. The size of this cohort and the consecutive nature of the data make an important point about the relative impact of thrombectomy metrics assuming the rapid and successful treatment demonstrated in our practice.

Following the initial FPE publications there has been an effort to study why multi-pass thrombectomy might result in worse outcome. Hypotheses include the possibility of endothelial injury, ¹⁸ dissection, thrombus fragmentation, ¹⁶ device-specific endothelial cell injury,^18,20 endothelial denudation, ²¹ disruption of the internal elastic lamina, ²² edema in the intimal and medial layers of the arterial wall, ²² and arterial wall inflammation ²⁰ as possible explanations for poor clinical outcome. While these observations may be correct, in our cohort they were completely overwhelmed by the impact of time in conjunction with patient age and degree of recanalization. Even in a multi-pass-only multivariate analysis, there was no difference in outcome associated with the number of passes.

This study has several limitations. Firstly, the data spans nearly a decade, during which advances in thrombectomy techniques and tools improved technical outcome and treatment times. Hospital efficiency improved over this decade as well. A detailed review of stroke technique and treatment times in our practice has been analyzed but is outside of the scope of this study. Secondly, this is a real-world consecutive stroke series which on the one hand likely makes it more generalizable, but on another opens the possibility that unmeasured confounding factors, such as physician experience and patient-specific characteristics, may impact the results. Additionally, our single-practice data, while robust, has limitations compared to prospective, multicenter registries such as HERMES, ²³ or the SNIS/NVQI-QOD registry though homogeneity in patient selection, workup, and treatment styles has advantages as well.

Conclusion

This study demonstrates that time, patient age, and technical efficacy are associated with outcome in thrombectomy, whereas FPE is not when controlling for time. These findings challenge the importance of FPE independent of time, suggesting that time to treat and technical outcome should be prioritized. Future large prospective trials should focus on validating these findings, with an emphasis on optimizing procedural times and evaluating the impact of newer thrombectomy devices and techniques.