Multivariable Prediction Model for Futile Recanalization Therapies in Patients With Acute Ischemic Stroke

Meinel, Thomas; Lerch, Christine; Fischer, Urs; Beyeler, Morin; Mujanović, Adnan; Kurmann, Christoph; Siepen, Bernhard; Scutelnic, Adrian; Müller, Mira; Goeldlin, Martina; Belachew, Nebiyat Filate; Dobrocky, Tomas; Gralla, Jan; Seiffge, David J; Jung, Simon; Arnold, Marcel; Wiest, Roland; Meier, Raphael; Kaesmacher, Johannes

doi:10.1212/wnl.0000000000200815

Cited by 27 publications

(16 citation statements)

References 49 publications

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“…Several predictors of futile recanalization after MT have been identified [11–18]. However, to the best of our knowledge, the present study is the first investigating the predictors of early clinical and long‐term functional outcomes in the optimal setting for MT.…”

Section: Discussionmentioning

confidence: 93%

Predictors for clinical and functional outcomes in stroke patients with first‐pass complete recanalization after thrombectomy

Cappellari

Saia

Pracucci

et al. 2023

Euro J of Neurology

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Background and purpose The aim was to identify baseline clinical and radiological/procedural predictors and 24‐h radiological predictors for clinical and functional outcomes in stroke patients obtaining complete recanalization in one pass of mechanical thrombectomy (MT) in an optimal baseline and procedural setting. Methods A retrospective analysis was conducted of prospectively collected data from 924 stroke patients with anterior large vessel occlusion, Alberta Stroke Program Early Computed Tomography (ASPECT) score ≥6 and pre‐stroke modified Rankin Scale score 0, who started MT ≤6 h from symptom onset and obtained first‐pass complete recanalization. A first logistic regression model was performed to identify baseline clinical predictors and a second model to identify baseline radiological/procedural predictors. A third model including baseline clinical and radiological/procedural predictors was performed, and a fourth model including independent baseline predictors from the third model plus 24‐h radiological variables (hemorrhagic transformation [HT] and cerebral edema [CED]). Results In the fourth model, higher National Institutes of Health Stroke Scale (NIHSS) score (odds ratio [OR] 1.089) and higher ASPECT score (OR 1.292) were predictors of early neurological improvement (ENI) (NIHSS score ≤4 points from baseline or NIHSS score of 0 at 24 h), whereas older age (OR 0.973), longer procedure time (OR 0.990), HT (OR 0.272) and CED (OR 0.569) were inversely associated with ENI. Older age (OR 0.970), diabetes mellitus (OR 0.456), higher NIHSS score (OR 0.886), general anesthesia (OR 0.454), longer onset‐to‐groin time (OR 0.996), HT (OR 0.340) and CED (OR 0.361) were inversely associated with 3‐month excellent functional outcome (mRS score 0–1), whereas higher ASPECT score (OR 1.294) was a predictor of excellent outcome. Conclusions Higher NIHSS score was a predictor of ENI but inversely associated with 3‐month excellent outcome. Older age, HT and CED were inversely associated with both good outcomes.

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Section: Discussionmentioning

confidence: 93%

Predictors for clinical and functional outcomes in stroke patients with first‐pass complete recanalization after thrombectomy

Cappellari

Saia

Pracucci

et al. 2023

Euro J of Neurology

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“…It has been reported that futile recanalization was less often with intravenous thrombolysis (11%) than for mechanical thrombectomy (34%). with a total percentage of 24% 21 . Thus, the fact that the patients included in the sample I were majority treated with intravenous rtPA could support the reduced percentage observed.…”

Section: Discussionmentioning

confidence: 72%

Systemic biomarker associated with poor outcome after futile reperfusion

Hervella,

Sampedro‐Viana,

Rodríguez‐Yáñez

et al. 2024

Eur J Clin Investigation

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BackgroundSuccessful recanalization does not lead to complete tissue reperfusion in a considerable percentage of ischemic stroke patients. This study aimed to identify biomarkers associated with futile recanalization. Leukoaraiosis predicts poor outcomes of this phenomenon. Soluble tumour necrosis factor‐like weak inducer of apoptosis (sTWEAK), which is associated with leukoaraiosis degrees, could be a potential biomarker.MethodsThis study includes two cohorts of ischemic stroke patients in a multicentre retrospective observational study. Effective reperfusion, defined as a reduction of ≥8 points in the National Institutes of Health Stroke Scale (NIHSS) within the first 24 h, was used as a clinical marker of effective reperfusion.ResultsIn the first cohort study, female sex, age, and high NIHSS at admission (44.7% vs. 81.1%, 71.3 ± 13.7 vs. 81.1 ± 6.7; 16 [13, 21] vs. 23 [17, 28] respectively; p < .0001) were confirmed as predictors of futile recanalization. ROC curve analysis showed that leukocyte levels (sensitivity of 99%, specificity of 55%) and sTWEAK level (sensitivity of 92%, specificity of 88%) can discriminate between poor and good outcomes. Both biomarkers simultaneously are higher associated with outcome after effective reperfusion (OR: 2.17; CI 95% 1.63–4.19; p < .0001) than individually (leukocytes OR: 1.38; CI 95% 1.00–1.64, p = .042; sTWEAK OR: 1.00; C I95% 1.00–1.01, p = .019). These results were validated using a second cohort, where leukocytes and sTWEAK showed a sensitivity of 100% and specificity of 66.7% and 75% respectively.ConclusionsLeukocyte and sTWEAK could be biomarkers of reperfusion failure and subsequent poor outcomes. Further studies will be necessary to explore its role in reperfusion processes.

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“…While the mRS is a validated measure to assess poststroke neurological and functional outcomes, 14 whether it is an appropriate tool to quantify non-neurological disability prior to stroke onset is unclear. Past studies have demonstrated that prestroke mRS is a negative prognostic factor for post-EVT outcomes, [15][16][17] however, no study to date has investigated whether these associations apply to both neurological and non-neurological causes of higher prestroke mRS. There is currently little guidance on how to assess non-neurological disability during acute triage, and using prestroke mRS to quantify disability from osteoarthritis and other musculoskeletal diseases has not been validated.…”

Section: Discussionmentioning

confidence: 99%

“…9 Thrombectomy procedure was identified by procedure codes. Stroke severity was identified using International Classification of Diseases, Tenth Revision (ICD-10) codes for National Institutes of Health Stroke Scale (NIHSS)‚ and categorized into the following categories: mild (NIHSS score 0-4), moderate (NIHSS score [5][6][7][8][9][10][11][12][13][14][15], moderate to severe (16)(17)(18)(19)(20), severe (21 or higher), and unknown. The Elixhauser comorbidity index 10,11 was used to identify stroke risk factors and comorbidities, with slight modifications: (1) Atrial fibrillation and atrial flutter were excluded from the arrhythmia category and listed as a stroke risk factor;…”

Section: Icd-10 Codes Used For Identifying Patients and Variables Of ...mentioning

confidence: 99%

Associations of Osteoarthritis With Thrombectomy Utilization and Outcomes for Large Vessel Acute Ischemic Stroke

Chen

Khunte

Colasurdo

et al. 2023

Stroke

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BACKGROUND: Osteoarthritis and other musculoskeletal disorders are the leading causes of disability in the United States. While osteoarthritis is not a direct risk factor for stroke, osteoarthritis may impact patient selection for endovascular thrombectomy (EVT) due to prestroke disability. This study investigates associations of osteoarthritis with EVT utilization and outcomes. METHODS: This was a large-scale cross-sectional study of the 2016 to 2019 National Inpatient Sample database. Adult patients with anterior large vessel ischemic strokes were identified. Patient demographics, stroke risk factors, stroke etiology, presence of osteoarthritis, medical comorbidities, EVT, intravenous thrombolysis treatments, and discharge destinations were recorded. Primary outcome was the rate of EVT treatment. Secondary outcomes include rates of discharge to home and in-hospital mortality. Propensity score matching and multivariable logistic regression models were used to account for possible confounders. RESULTS: Two hundred fifty-two thousand five hundred five patients were identified, of whom 8.5% (21 500 patients) had osteoarthritis. After propensity score matching for 32 clinical variables, osteoarthritis patients were found to be 17.3% less likely to receive EVT than non-osteoarthritis patients (14.4% versus 17.3%, respectively; P <0.001). In multivariable logistic regression analysis, osteoarthritis was associated with 22.6% lower odds of receiving EVT (OR, 0.77 [95% CI, 0.70–0.86]; P <0.001), an effect size larger than any medical comorbidity captured in this study other than dementia and nonstroke neurological disease. Among those treated with EVT, multivariable logistic regression models showed that osteoarthritis was not associated with different odds of being discharged home (OR, 0.99 [95% CI, 0.81–1.21]; P =0.93); however, osteoarthritis was marginally associated with lower odds of in-hospital mortality (OR, 0.74 [95% CI, 0.54–1.01]; P =0.054). CONCLUSIONS: Large vessel ischemic stroke patients with osteoarthritis were significantly less likely to receive EVT therapy despite similar post-EVT outcomes. These results warrant further investigation and prompt a critical review of current patient selection practices for stroke EVT therapy, specifically for patients with baseline disability due to musculoskeletal conditions such as osteoarthritis.

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Multivariable Prediction Model for Futile Recanalization Therapies in Patients With Acute Ischemic Stroke

Cited by 27 publications

References 49 publications

Predictors for clinical and functional outcomes in stroke patients with first‐pass complete recanalization after thrombectomy

Predictors for clinical and functional outcomes in stroke patients with first‐pass complete recanalization after thrombectomy

Systemic biomarker associated with poor outcome after futile reperfusion

Associations of Osteoarthritis With Thrombectomy Utilization and Outcomes for Large Vessel Acute Ischemic Stroke

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