Evidence map›Paper›PMID 41441609›Full record

ArticleToxins2025

Artificial Intelligence in Managing Spasticity with Botulinum Toxin Type A-Insights from an Exploratory Pilot Investigation: The AIMS Study.

Mirko Filippetti, Rita Di Censo, Lyria Arcari, Maria Concetta Schiavariello, Marco Battaglia, Salvatore Facciorusso, Stefania Spina, Laura Antonucci, Andrea Santamato, Alessio Baricich and 2 more

Abstract read
In one paragraph

Article in Toxins, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Mirko FilippettiSection of Physical and Rehabilitation Medicine, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy.ORCID 0000-0001-5930-5974
Rita Di CensoSection of Physical and Rehabilitation Medicine, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy.ORCID 0000-0002-8017-4013
Lyria ArcariSection of Physical and Rehabilitation Medicine, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy.
Maria Concetta SchiavarielloSection of Physical and Rehabilitation Medicine, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy.
Marco BattagliaDepartment of Health Sciences, University of Piemonte Orientale, 28100 Novara, Italy.ORCID 0000-0003-1357-1374
Salvatore FacciorussoSpasticity and Movement Disorders "ReSTaRt", Physical Medicine and Rehabilitation Section, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy.ORCID 0000-0001-6748-9152
Stefania SpinaSpasticity and Movement Disorders "ReSTaRt", Physical Medicine and Rehabilitation Section, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy.ORCID 0000-0002-7220-4016
Laura AntonucciFondazione IRCCS Don Carlo Gnocchi ONLUS, 50143 Florence, Italy.
Andrea SantamatoSpasticity and Movement Disorders "ReSTaRt", Physical Medicine and Rehabilitation Section, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy.ORCID 0000-0002-1452-8485
Alessio BaricichRehabilitation Unit, IRCCS Humanitas Research Hospital, 20089 Rozzano, Italy.ORCID 0000-0001-8440-6283
Nicola SmaniaSection of Physical and Rehabilitation Medicine, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy.ORCID 0000-0001-7630-1887
Alessandro PicelliSection of Physical and Rehabilitation Medicine, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy.ORCID 0000-0002-3558-8276

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to explore the potential role of artificial intelligence in optimizing botulinum toxin type A treatment for spasticity and to evaluate its alignment with expert clinical decisions. A comparative analysis was conducted using thirty hypothetical clinical cases involving individuals with spasticity resulting from various neurological conditions. Five rehabilitation physicians, each with more than five years of experience, participated in the study. An artificial intelligence model trained on scientific literature and clinical guidelines generated treatment recommendations, including target muscles and dosages, which were compared with those proposed independently by the physicians. The primary outcome was the level of agreement in muscle selection and dosage. The model demonstrated consistency and adherence to guidelines but showed limited adaptability in complex presentations, such as an adducted thigh and equinovarus foot. It generally recommended lower dosages and differed significantly from physicians in both muscle selection and treatment strategies. Artificial intelligence shows promise as a clinical support tool in spasticity management, offering standardized and reproducible recommendations. However, its limited capacity to interpret clinical subtleties currently restricts its practical application. Future models should integrate multimodal clinical data and real-time clinician feedback to better emulate expert decision-making processes.

Indexed as

Artificial IntelligenceBotulinum Toxins, Type AMuscle SpasticityNeuromuscular AgentsHumansMalePilot ProjectsBotulinum Toxins, Type ANeuromuscular Agentsbotulinum toxinsmachine learningmuscle spasticity

Identifiers

PMID41441609
PMCPMC12737341

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.