What defines success following reperfusion after mechanical thrombectomy for older patients in the real world?

Ruiz, Amber; Longstreth, W. T.; Tirschwell, David; Creutzfeldt, Claire J.

doi:10.1007/s00415-021-10859-1

Cited by 2 publications

(6 citation statements)

References 9 publications

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“…The model output can be used to inform and discuss with patients and/or next of kin the high risk of poor outcome and help to set realistic expectations. 41 However, in high-resource healthcare systems, the algorithm will probably not be used because no patients will be excluded from acute recanalization treatments despite high chances for FRT. In addition, false positives (classifying patients as FRT, despite the fact that they might gain functional independence) should be weighted more than false-negative classifications.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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Background and Objectives:Very poor outcome despite intravenous thrombolysis (IVT) and mechanical thrombectomy (MT) occurs in about 1 of 4 patients with ischemic stroke and is associated with a high logistic and economic burden. We aimed to develop and validate a multivariable prognostic model to identify futile recanalization therapies (FRT) in patients undergoing those therapies.Materials and Methods:Patients from a prospectively collected observational registry of a single academic stroke center treated with MT and/or IVT were included. The dataset was split into a training (N=1808, 80%) and internal validation (N=453, 20%) cohort. We used gradient boosted decision tree machine-learning models after k-NN imputation of 32 variables available at admission to predict FRT defined as modified Rankin-Scale (mRS) 5-6 at 3 months. We report feature importance, ability for discrimination, calibration and decision curve analysis.Results:2261 patients with a median (IQR) age 75 years (64-83), 46% female, median NIHSS 9 (4-17), 34% IVT alone, 41% MT alone, 25% bridging were included. Overall 539 (24%) had FRT, more often in MT alone (34%) as compared to IVT alone (11%). Feature importance identified clinical variables (stroke severity, age, active cancer, prestroke disability), laboratory values (glucose, CRP, creatinine), imaging biomarkers (white matter hyperintensities) and onset-to-admission time as the most important predictors. The final model was discriminatory for predicting 3-month FRT (AUC 0.87, 95% CI 0.87-0.88) and had good calibration (Brier 0.12, 0.11-0.12). Overall performance was moderate (F1-score 0.63 ± 0.004) and decision curve analyses suggested higher mean net benefit at lower thresholds of treatment (up to 0.8).Conclusions:This FRT prediction model can help inform shared decision making and identify the most relevant features in the emergency setting. While it might be particularly useful in low resource healthcare settings, incorporation of further multifaceted variables is necessary to further increase the predictive performance.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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“…A few recent real-world observational studies paint a less optimistic picture for thrombectomy of patients ≥85 years, [8][9][10] likely because the cohort of elderly patients in the thrombectomy trials was not representative of realworld patients. After all, the ASPECTS in the thrombectomy trials was higher in the elderly compared with the younger group, 7 suggesting that elderly patients were preselected based on their likelihood of succeeding (selection bias).…”

Section: See Related Article P 2220mentioning

confidence: 99%

“…In addition, patients with prestroke disability (modified Rankin Scale score >1) were excluded from all of the HERMES trials, although this subgroup represents 25% to 50% of elderly patients in real-world studies. 8,10,11 The focus on independence as the primary outcome is limiting, especially for people who might have been dependent before the stroke, and for whom the return to prior function should be considered a good outcome. Stroke.…”

Section: See Related Article P 2220mentioning

confidence: 99%

“…They are also more likely to have advance directives documenting a preference towards less aggressive medical care than younger patients, and possibly a lower tolerance for new disability. 8…”

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confidence: 99%

“…Study the effect of a communication intervention for elderly patients that includes more detailed advance care planning and provides a preamble to potential future emergent care conversations. 8…”

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confidence: 99%

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