Fasciculation analysis reveals a novel parameter that correlates with predicted survival in ALS

Kate Wannop, James Bashford, Aidan Wickham, Raquel Iniesta, Emmanuel Drakakis, Martyn Boutelle, Kerry Mills, Christopher Shaw

Research output: Contribution to journalArticlepeer-review

28 Downloads (Pure)


Introduction: Prognostic uncertainty in ALS confounds clinical management planning, patient counseling and trial stratification. Fasciculations are an early clinical hallmark of disease and can be quantified non-invasively. Using an innovative analytical method, we correlated novel fasciculation parameters with a predictive survival model.

Methods: Using high-density surface EMG, we collected biceps recordings from ALS patients on their first research visit. Accessing an online survival prediction tool, we provided eight clinical and genetic parameters to estimate individual patient survival. Fasciculation analysis was performed using an automated algorithm (SPiQE), with a Cox proportional hazards model to calculate hazard ratios.

Results: The median predicted survival for 31 patients was 41 months (IQR = 31.5-57). Univariate hazard ratios were 1.09 (95% CI = 1.03-1.16) for the Rate of Change of Fasciculation Frequency (RoCoFF) and 1.10 (95% CI = 1.01-1.19) for the Amplitude Dispersion Rate. Only the RoCoFF remained significant (p=0.04) in a multivariate model.

Discussion: Non-invasive measurement of fasciculations at a single time-point could enhance prognostic models in ALS, where higher RoCoFF values indicate shorter survival.
Original languageEnglish
JournalMuscle and Nerve
Publication statusAccepted/In press - 7 Nov 2020


Dive into the research topics of 'Fasciculation analysis reveals a novel parameter that correlates with predicted survival in ALS'. Together they form a unique fingerprint.

Cite this