Why the study?
Concerns exist regarding linear models like the Proportional Recovery Rule, including methodological dependence of fitter classifications, mathematical coupling, and ceiling effects on clinical scales.
Does Repeated Spectral Clustering of NIHSS scores identify distinct recovery patterns beyond the traditional Proportional Recovery Rule in patients with wake-up stroke?
Population
201 patients from the WAKE-UP trial moderately impaired at onset and still impaired at 22/36 hours
Comparison
Repeated Spectral Clustering recovery patterns vs Proportional Recovery Rule linear fit
Design
Clustering analysis of clinical trial cohort
Follow-up
90 days
Key result
Repeated Spectral Clustering of NIHSS recovery ratios identified six distinct recovery clusters in wake-up stroke patients, revealing that most patients experience non-proportional recovery trajectories.
Authors
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Should not yet alter recovery expectations in wake-up stroke; leaves open whether spectral clustering refines prognostication beyond proportional models.
Observational (n=201)
Double-blind
Randomized
Yes
Does Repeated Spectral Clustering of NIHSS scores identify distinct recovery patterns beyond the traditional Proportional Recovery Rule in patients with wake-up stroke?
Unsupervised clustering of NIHSS recovery ratios identifies six distinct recovery trajectories in wake-up stroke patients, challenging the traditional dichotomous 'fitters vs. non-fitters' proportional recovery rule.
Zanola et al. (2025) conducted an observational in Wake-up stroke (n=201). Intravenous alteplase (rtPA) vs. Placebo was evaluated on Recovery ratio (RR) based on total NIHSS from 22/36 hours to 90 days. Repeated Spectral Clustering of NIHSS recovery ratios identified six distinct recovery clusters in wake-up stroke patients, revealing that most patients experience non-proportional recovery trajectories.