Weights for ordinal analyses of the modified Rankin Scale in stroke trials: A population-based cohort study

Ganesh, Aravind; Luengo-Fernández, Ramón; Pendlebury,; Rothwell, Peter M.

doi:10.1016/j.eclinm.2020.100415

Cited by 18 publications

(17 citation statements)

References 42 publications

(63 reference statements)

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“…While at first glance it may seem that these patients were doing better than patients without pre-stroke disability, this likely has to do with the greater difficulty of returning to mRS 0 or 1 after a stroke for someone starting out at such excellent pre-morbid status, further reflecting limitations of dichotomized outcome assessments. Adopting non-dichotomized mRS as a primary outcome, such as ordinal shift, weighted mRS,28 29 or delta-mRS (difference between pre- and post-stroke mRS), sliding dichotomous analysis, or changing the dichotomy to focus on avoidance of mRS 5–6, could facilitate more granular analyses of outcomes in patients with pre-morbid disability in future trials 30. Ideally, adjustment for the smaller demonstrable degree of post-stroke change from a higher pre-morbid disability level versus a lower pre-morbid mRS should be considered in the measurement of disability progression.…”

Section: Discussionmentioning

confidence: 99%

Endovascular treatment of acute ischemic stroke in patients with pre-morbid disability: a meta-analysis

Bala

Beland

Mistry

et al. 2022

J NeuroIntervent Surg

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BackgroundTrials of endovascular thrombectomy (EVT) for acute stroke have excluded patients with pre-morbid disability. Observational studies may help inform consideration of EVT in this population. We aimed to assess the effectiveness and safety of EVT in patients with pre-morbid disability.MethodsAccording to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched MEDLINE and Embase for studies describing outcomes in patients with pre-morbid disability (modified Rankin Scale (mRS) 2–5), treated with EVT or medical management (MM). Random-effects meta-analysis was used to pool outcomes including 90-day return to baseline mRS, symptomatic intracerebral hemorrhage (sICH), and 90-day mortality.ResultsWe analyzed 14 studies of patients with pre-morbid disability (mRS 2–5, 1373 EVT and 253 MM). The rate of return to baseline mRS was 30.0% (95% CI 25.3% to 34.7%) in patients treated with EVT. Compared with medical therapy, EVT was associated with a higher likelihood of return to baseline mRS (OR 2.37, 95% CI 1.39 to 4.04) and a trend towards lower mortality (OR 0.68, 95% CI 0.46 to 1.02), with similar odds of sICH (OR 1.01, 95% CI 0.49 to 2.08). In studies comparing patients with versus without pre-morbid disability treated with EVT, similar results were found except that pre-morbid disability, when defined more strictly as mRS 3–5, was associated with mortality (OR 3.49, p<0.001).ConclusionIn eligible patients with pre-morbid disability, observational studies suggest that EVT carries a higher chance of return to baseline mRS compared with patients treated with MM or without pre-morbid disability, although with higher mortality than patients without pre-morbid disability. These findings argue against the routine exclusion of such patients from EVT and merit validation with randomized trials.

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Section: Discussionmentioning

confidence: 99%

Endovascular treatment of acute ischemic stroke in patients with pre-morbid disability: a meta-analysis

Bala

Beland

Mistry

et al. 2022

J NeuroIntervent Surg

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“…Post-stroke dementia contributes to dependency ( 51 , 52 ), institutionalization, and mortality ( 53 ). In OXVASC, each 3-month mRS increment was associated with higher 5-year risk of dementia ( 54 ).…”

Section: Literature Searchmentioning

confidence: 99%

“…The Erlangen Stroke Project found that urinary incontinence on the Barthel Index at 7 days conferred a four-fold higher risk of 12-month institutionalization ( 64 ). In OXVASC, 1-month/3-month mRS predicted 5-year institutionalization (>35% with mRS of 3–5 vs. <10% with mRS 0–2) ( 36 , 54 ).…”

Section: Literature Searchmentioning

confidence: 99%

“…Indeed, the 3-year Australian POISE (Psychosocial Outcomes In Stroke) study found that functional independence at 28 days was the strongest predictor of return-to-work within 1 year post-stroke ( 65 ). In OXVASC, each 3-month mRS increment was associated with worse quality-of-life ratings and 5-year quality-adjusted life expectancy (QALE) ( 54 , 66 ). The VISTA (Virtual International Stroke Trials Archive) collaborators found that 3-month mRS scores accounted for 65–71% of variation in health utilities generated using EQ-5D data for different countries ( 67 ).…”

Section: Literature Searchmentioning

confidence: 99%

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From Three-Months to Five-Years: Sustaining Long-Term Benefits of Endovascular Therapy for Ischemic Stroke

et al. 2021

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Background and Purpose: During the months and years post-stroke, treatment benefits from endovascular therapy (EVT) may be magnified by disability-related differences in morbidity/mortality or may be eroded by recurrent strokes and non-stroke-related disability/mortality. Understanding the extent to which EVT benefits may be sustained at 5 years, and the factors influencing this outcome, may help us better promote the sustenance of EVT benefits until 5 years post-stroke and beyond.Methods: In this review, undertaken 5 years after EVT became the standard of care, we searched PubMed and EMBASE to examine the current state of the literature on 5-year post-stroke outcomes, with particular attention to modifiable factors that influence outcomes between 3 months and 5 years post-EVT.Results: Prospective cohorts and follow-up data from EVT trials indicate that 3-month EVT benefits will likely translate into lower 5-year disability, mortality, institutionalization, and care costs and higher quality of life. However, these group-level data by no means guarantee maintenance of 3-month benefits for individual patients. We identify factors and associated “action items” for stroke teams/systems at three specific levels (medical care, individual psychosocioeconomic, and larger societal/environmental levels) that influence the long-term EVT outcome of a patient. Medical action items include optimizing stroke rehabilitation, clinical follow-up, secondary stroke prevention, infection prevention/control, and post-stroke depression care. Psychosocioeconomic aspects include addressing access to primary care, specialist clinics, and rehabilitation; affordability of healthy lifestyle choices and preventative therapies; and optimization of family/social support and return-to-work options. High-level societal efforts include improving accessibility of public/private spaces and transportation, empowering/engaging persons with disability in society, and investing in treatments/technologies to mitigate consequences of post-stroke disability.Conclusions: In the longtime horizon from 3 months to 5 years, several factors in the medical and societal spheres could negate EVT benefits. However, many factors can be leveraged to preserve or magnify treatment benefits, with opportunities to share responsibility with widening circles of care around the patient.

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“…For the intended use case (Figure 2), a secondary analysis included prediction of mRS 5-6 at 3 months. This secondary endpoint more closely reflects true futile reperfusion, because quality of life may be substantial for patients with mRS grades 3 and 4 22 , while five-year quality-adjusted-life-expectancy in stroke survivors with mRS 5 is overall low (0.06) [22][23][24] .…”

Section: Functional Outcomementioning

confidence: 99%

Beyond Accuracy: Investigating the Potential Clinical Utility of Predicting Functional Dependency and Severe Disability or Death in Successfully Reperfused Patients using Machine Learning

Meier

Burri

Fischer

et al. 2020

Preprint

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ObjectivesMachine learning (ML) has been demonstrated to improve the prediction of functional outcome in patients with acute ischemic stroke. However, its value in a specific clinical use case has not been investigated. Aim of this study was to assess the clinical utility of ML models with respect to predicting functional impairment and severe disability or death considering its potential value as a decision-support tool in an acute stroke workflow.Materials and MethodsPatients (n=1317) from a retrospective, non-randomized observational registry treated with Mechanical Thrombectomy (MT) were included. The final dataset of patients who underwent successful recanalization (TICI ≥ 2b) (n=932) was split in order to develop ML-based prediction models using data of (n=745, 80%) patients. Subsequently, the models were tested on the remaining patient data (n=187, 20%). For comparison, baseline algorithms using majority class prediction, SPAN-100 score, PRE score, and Stroke-TPI score were implemented. The ML methods included eight different algorithms (e.g. Support Vector Machines and Random forests), stacked ensemble method and tabular neural networks. Prediction of modified Rankin Scale (mRS) 3–6 (primary analysis) and mRS 5–6 (secondary analysis) at 3 months was performed using 25 baseline variables available at patient admission. ML models were assessed with respect to their ability for discrimination, calibration and clinical utility (decision curve analysis).ResultsAnalyzed patients (n=932) showed a median age of 74.7 (IQR 62.7–82.4) years with (n=461, 49.5%) being female. ML methods performed better than clinical scores with stacked ensemble method providing the best overall performance including an F1-score of 0.75 ± 0.01, an ROC-AUC of 0.81 ± 0.00, AP score of 0.81 ± 0.01, MCC of 0.48 ± 0.02, and ECE of 0.06 ± 0.01 for prediction of mRS 3–6, and an F1-score of 0.57 ± 0.02, an ROC-AUC of 0.79 ± 0.01, AP score of 0.54 ± 0.02, MCC of 0.39 ± 0.03, and ECE of 0.19 ± 0.01 for prediction of mRS 5–6. Decision curve analyses suggested highest mean net benefit of 0.09 ± 0.02 at a-priori defined threshold (0.8) for the stacked ensemble method in primary analysis (mRS 3–6). Across all methods, higher mean net benefits were achieved for optimized probability thresholds but with considerably reduced certainty (threshold probabilities 0.24–0.47). For the secondary analysis (mRS 5–6), none of the ML models achieved a positive net benefit for the a-priori threshold probability 0.8.ConclusionsThe clinical utility of ML prediction models in a decision-support scenario aimed at yielding a high certainty for prediction of functional dependency (mRS 3–6) is marginal and not evident for the prediction of severe disability or death (mRS 5–6). Hence, using those models for patient exclusion cannot be recommended and future research should evaluate utility gains after incorporating more advanced imaging parameters.

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Weights for ordinal analyses of the modified Rankin Scale in stroke trials: A population-based cohort study

Cited by 18 publications

References 42 publications

Endovascular treatment of acute ischemic stroke in patients with pre-morbid disability: a meta-analysis

Endovascular treatment of acute ischemic stroke in patients with pre-morbid disability: a meta-analysis

From Three-Months to Five-Years: Sustaining Long-Term Benefits of Endovascular Therapy for Ischemic Stroke

Beyond Accuracy: Investigating the Potential Clinical Utility of Predicting Functional Dependency and Severe Disability or Death in Successfully Reperfused Patients using Machine Learning

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