Evidence map›Paper›PMID 37070056›Full record

ArticleMovement disorders clinical practice2023

Assessment of Axial Postural Abnormalities in Parkinsonism: Automatic Picture Analysis Software.

Carlo Alberto Artusi, Christian Geroin, Gabriele Imbalzano, Serena Camozzi, Stefano Aldegheri, Leonardo Lopiano, Michele Tinazzi, Nicola Bombieri

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in Movement disorders clinical practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06963918 (Effect of Expiratory Muscle Strength Training on Forward Trunk Flexion in Parkinson's Disease), which is not on this map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 9% of its field
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.

NCT06963918 nanot yet recruitingnot on this mapstarted 2025, after this paper: background citation

Effect of Expiratory Muscle Strength Training on Forward Trunk Flexion in Parkinson's Disease

TypeinterventionalSponsorGeneral University Hospital, PragueRan2025 to 2026Enrolled30ConditionsParkinson DiseaseArmsExpiratory muscle strength training
3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Carlo Alberto ArtusiDepartment of Neuroscience "Rita Levi Montalcini" University of Turin Turin Italy.ORCID https://orcid.org/0000-0001-8579-3772
Christian GeroinNeurology Unit, Movement Disorders Division, Department of Neurosciences Biomedicine and Movement Sciences University of Verona Verona Italy.ORCID https://orcid.org/0000-0001-6095-1930
Gabriele ImbalzanoDepartment of Neuroscience "Rita Levi Montalcini" University of Turin Turin Italy.
Serena CamozziNeurology Unit, Movement Disorders Division, Department of Neurosciences Biomedicine and Movement Sciences University of Verona Verona Italy.
Stefano AldegheriDepartment of Computer Science University of Verona Verona Italy.ORCID https://orcid.org/0000-0002-3193-6798
Leonardo LopianoDepartment of Neuroscience "Rita Levi Montalcini" University of Turin Turin Italy.
Michele TinazziNeurology Unit, Movement Disorders Division, Department of Neurosciences Biomedicine and Movement Sciences University of Verona Verona Italy.
Nicola BombieriDepartment of Computer Science University of Verona Verona Italy.
University of Verona · ITAzienda Ospedaliera Citta' della Salute e della Scienza di Torino · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Software-based measurements of axial postural abnormalities in Parkinson's disease (PD) are the gold standard but may be time-consuming and not always feasible in clinical practice. An automatic and reliable software to accurately obtain real-time spine flexion angles according to the recently proposed consensus-based criteria would be a useful tool for both research and clinical practice. Objective: We aimed to develop and validate a new software based on Deep Neural Networks to perform automatic measures of PD axial postural abnormalities. Methods: A total of 76 pictures from 55 PD patients with different degrees of anterior and lateral trunk flexion were used for the development and pilot validation of a new software called AutoPosturePD (APP); postural abnormalities were measured in lateral and posterior view using the freeware NeuroPostureApp (gold standard) and compared with the automatic measurement provided by the APP. Sensitivity and specificity for the diagnosis of camptocormia and Pisa syndrome were assessed. Results: We found an excellent agreement between the new APP and the gold standard for lateral trunk flexion (intraclass correlation coefficient [ICC] 0.960, IC95% 0.913-0.982, Conclusions: AutoPosturePD is a valid tool for spine flexion measurement in PD, accurately supporting the diagnosis of Pisa syndrome and camptocormia.

Indexed as

camptocormiaParkinson's diseasePisa syndromepostural abnormalitiesposture

Identifiers

PMID37070056
PMCPMC10105105
OpenAlexW4319349965

What OpenQuestion holds

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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 OpenQuestion graph.