Evidence map›Paper›PMID 29163328›Full record

ArticleFrontiers in neurology2017

Parkinson's Disease Severity at 3 Years Can Be Predicted from Non-Motor Symptoms at Baseline.

Alba Ayala, José Matías Triviño-Juárez, Maria João Forjaz, Carmen Rodríguez-Blázquez, José-Manuel Rojo-Abuin, Pablo Martínez-Martín

Abstract read
In one paragraph

Article in Frontiers in neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Alba AyalaCentre for Human and Social Sciences, Spanish Scientific Research Council (CCHS, CSIC) and Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Madrid, Spain.
José Matías Triviño-JuárezWest Health District, Primary Care Center Francia, Madrid Health Service, Madrid, Spain.
Maria João ForjazEpidemiology and Biostatistics Department, National School of Public Health, Institute of Health Carlos III and Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Madrid, Spain.
Carmen Rodríguez-BlázquezNational Center of Epidemiology and Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Institute of Health Carlos III, Madrid, Spain.
José-Manuel Rojo-AbuinInstitute of Economics, Geography and Demography, Centre for Human and Social Sciences, Spanish National Research Council (CSIC), Madrid, Spain.
Pablo Martínez-MartínNational Center of Epidemiology and Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Institute of Health Carlos III, Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe aim of this study is to present a predictive model of Parkinson's disease (PD) global severity, measured with the Clinical Impression of Severity Index for Parkinson's Disease (CISI-PD).

methodsThis is an observational, longitudinal study with annual follow-up assessments over 3 years (four time points). A multilevel analysis and multiple imputation techniques were performed to generate a predictive model that estimates changes in the CISI-PD at 1, 2, and 3 years.

resultsThe clinical state of patients (CISI-PD) significantly worsened in the 3-year follow-up. However, this change was of small magnitude (effect size: 0.44). The following baseline variables were significant predictors of the global severity change: baseline global severity of disease, levodopa equivalent dose, depression and anxiety symptoms, autonomic dysfunction, and cognitive state. The goodness-of-fit of the model was adequate, and the sensitive analysis showed that the data imputation method applied was suitable.

conclusionDisease progression depends more on the individual's baseline characteristics than on the 3-year time period. Results may contribute to a better understanding of the evolution of PD including the non-motor manifestations of the disease.

Indexed as

disease global severitymultilevel analysismultiple imputationParkinson’s diseasepredictive model

Identifiers

PMID29163328
PMCPMC5674937

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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.