ArticleBMC neurology2025
Characteristics of brain glucose metabolism in Parkinson's disease patients with freezing of gait: a study based on
Article in BMC neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- A review of FDG-PET biomarker analysis methods in Parkinson's disease.Journal of Parkinson's disease · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
objectiveFreezing of gait (FOG) is a common gait disorder in the advanced stages of Parkinson's disease (PD), closely associated with impaired balance and executive function. This study aimed to investigate specific changes in brain glucose metabolism in FOG patients using
methodsEighteen PD patients with FOG(PD-FOG), 11 patients without FOG (PD-NFOG) and 17 healthy controls (HC) were recruited. All participants underwent
resultsPET imaging analysis showed that the differences between the PD-FOG group and the PD-NFOG group were mainly located in the frontal lobe, parietal lobe and cingulate gyrus. The 3D CNN achieved diagnostic accuracies of 90.09% for distinguishing PD and 95.40% for FOG, surpassing other machine learning models. The 3D CNN achieved the smallest mean squared error (MSE), amounting to 48.01, in the prediction of Freezing of Gait Questionnaire (FOG-Q) scores.
conclusionSpecific glucose metabolism patterns in PD-FOG mainly covered the frontoparietal network (FPN). The integration of
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.