Development and validation of a nomogram for freezing of gait in patients with Parkinson's Disease

Li, Kelu; Zhu, Yongyun; Ning, Pingping; Bao, Jianjian; Liu, Bin; Yang, Hongju; Yin, Weifang; Xu, Yanming; Ren, Hui; Yang, Xinglong

doi:10.1111/ane.13583

Cited by 2 publications

(3 citation statements)

References 48 publications

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“…Previous studies already suggested these clinical features as potential predictors of FoG 37,38 . Other studies suggested that also non-motor symptoms including REM sleep disorders, cognitive and mood alterations might contribute to FoG development 27,28,30 , however we did not observe any difference between PD-FoG-converters and PD-non-converters at baseline in our sample. Our study has the main strength to combine clinical and MRI data showing that the highest accuracy of the prediction model (AUC = 0.95) metric could be obtained combining clinical and functional topological MRI data.…”

Section: Discussioncontrasting

confidence: 88%

“…To date, several studies suggested the presence of clinical motor and non-motor predictors of FoG development, including for instance gait and balance deficits, cognitive changes, mood alterations, hyposmia and REM sleep behavior disorders [27][28][29][30] . On the other hand, very few studies provided longitudinal MRI data to explore the progression of PD-FoG patients and even fewer MRI studies monitored over time PD patients developing FoG in order to identify predictive brain signs of FoG onset 31,32 .…”

Section: Introductionmentioning

confidence: 99%

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MRI biomarkers of freezing of gait development in Parkinson’s disease

Sarasso

Basaia

Cividini

et al. 2022

npj Parkinsons Dis.

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This study investigated longitudinal clinical, structural and functional brain alterations in Parkinson’s disease patients with freezing of gait (PD-FoG) and in those developing (PD-FoG-converters) and not developing FoG (PD-non-converters) over two years. Moreover, this study explored if any clinical and/or MRI metric predicts FoG development. Thirty PD-FoG, 11 PD-FoG-converters and 11 PD-non-converters were followed for two years. Thirty healthy controls were included at baseline. Participants underwent clinical and MRI visits. Cortical thickness, basal ganglia volumes and functional network graph metrics were evaluated at baseline and over time. In PD groups, correlations between baseline MRI and clinical worsening were tested. A ROC curve analysis investigated if baseline clinical and MRI measures, selected using a stepwise model procedure, could differentiate PD-FoG-converters from PD-non-converters. At baseline, PD-FoG patients had widespread cortical/subcortical atrophy, while PD-FoG-converters and non-converters showed atrophy in sensorimotor areas and basal ganglia relative to controls. Over time, PD-non-converters accumulated cortical thinning of left temporal pole and pallidum without significant clinical changes. PD-FoG-converters showed worsening of disease severity, executive functions, and mood together with an accumulation of occipital atrophy, similarly to PD-FoG. At baseline, PD-FoG-converters relative to controls and PD-FoG showed higher global and parietal clustering coefficient and global local efficiency. Over time, PD-FoG-converters showed reduced parietal clustering coefficient and sensorimotor local efficiency, PD-non-converters showed increased sensorimotor path length, while PD-FoG patients showed stable graph metrics. Stepwise prediction model including dyskinesia, postural instability and gait disorders scores and parietal clustering coefficient was the best predictor of FoG conversion. Combining clinical and MRI data, ROC curves provided the highest classification power to predict the conversion (AUC = 0.95, 95%CI: 0.86–1). Structural MRI is a useful tool to monitor PD progression, while functional MRI together with clinical features may be helpful to identify FoG conversion early.

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Section: Discussioncontrasting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

MRI biomarkers of freezing of gait development in Parkinson’s disease

Sarasso

Basaia

Cividini

et al. 2022

npj Parkinsons Dis.

View full text Add to dashboard Cite

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“…This index could provide a comprehensive assessment and help to stratify patients based on their individual risk levels. Initial attempts at developing such composite scores have shown promise, particularly when combining imaging with other measures 36 , 53 . Considering the low ability to differentiate posterior putamen, ventral putamen and caudate uptake, it would be interesting in the future to explore DAT uptake levels at the different regions of the striatum and how they might correlate with FOG.…”

Section: Discussionmentioning

confidence: 99%

A meta-analysis identifies factors predicting the future development of freezing of gait in Parkinson’s disease

Herman,

Barer,

Bitan

et al. 2023

npj Parkinsons Dis.

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Freezing of gait (FOG) is a debilitating problem that is common among many, but not all, people with Parkinson’s disease (PD). Numerous attempts have been made at treating FOG to reduce its negative impact on fall risk, functional independence, and health-related quality of life. However, optimal treatment remains elusive. Observational studies have recently investigated factors that differ among patients with PD who later develop FOG, compared to those who do not. With prediction and prevention in mind, we conducted a systematic review and meta-analysis of publications through 31.12.2022 to identify risk factors. Studies were included if they used a cohort design, included patients with PD without FOG at baseline, data on possible FOG predictors were measured at baseline, and incident FOG was assessed at follow-up. 1068 original papers were identified, 38 met a-priori criteria, and 35 studies were included in the meta-analysis (n = 8973; mean follow-up: 4.1 ± 2.7 years). Factors significantly associated with a risk of incident FOG included: higher age at onset of PD, greater severity of motor symptoms, depression, anxiety, poorer cognitive status, and use of levodopa and COMT inhibitors. Most results were robust in four subgroup analyses. These findings indicate that changes associated with FOG incidence can be detected in a subset of patients with PD, sometimes as long as 12 years before FOG manifests, supporting the possibility of predicting FOG incidence. Intriguingly, some of these factors may be modifiable, suggesting that steps can be taken to lower the risk and possibly even prevent the future development of FOG.

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Development and validation of a nomogram for freezing of gait in patients with Parkinson's Disease

Cited by 2 publications

References 48 publications

MRI biomarkers of freezing of gait development in Parkinson’s disease

MRI biomarkers of freezing of gait development in Parkinson’s disease

A meta-analysis identifies factors predicting the future development of freezing of gait in Parkinson’s disease

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