Evidence map›Paper›PMID 39846565›Full record

ArticleNeuroSci2025

Trends and Disparities in Parkinson's Disease Mortality in the United States with Predictions Using Machine Learning.

Henry Weresh, Kallin Hermann, Ali Al-Salahat, Amna Noor, Taylor Billion, Yu-Ting Chen, Abubakar Tauseef, Ali Bin Abdul Jabbar

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PubMed Full text at PMC Publisher
In one paragraph

Article in NeuroSci, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Article
  3. Article
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.

Henry WereshSchool of Medicine, Creighton University, Omaha, NE 68178, USA.
Kallin HermannSchool of Medicine, Creighton University, Omaha, NE 68178, USA.ORCID 0009-0009-4080-9051
Ali Al-SalahatNeurology Department, Creighton University, Omaha, NE 68178, USA.ORCID 0000-0003-4047-0835
Amna NoorServices Hospital, Lahore 40050, Pakistan.ORCID 0009-0006-4446-508X
Taylor BillionSchool of Medicine, Creighton University, Omaha, NE 68178, USA.
Yu-Ting ChenNeurology Department, Creighton University, Omaha, NE 68178, USA.ORCID 0009-0009-9775-627X
Abubakar TauseefDepartment of Medicine, Creighton University, Omaha, NE 68178, USA.
Ali Bin Abdul JabbarDepartment of Medicine, Creighton University, Omaha, NE 68178, USA.ORCID 0000-0001-5145-8626

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundParkinson's disease (PD) is a progressive neurodegenerative condition characterized by the degradation of dopaminergic pathways in the brain. As the population in the United States continues to age, it is essential to understand the trends in mortality related to PD. This analysis of PD's mortality characterizes temporal shifts, examines demographic and regional differences, and provides machine-learning predictions.

methodsPD-related deaths in the United States were gathered from CDC WONDER. Age-adjusted mortality rates (AAMR) were collected, and trends were analyzed based on gender, race, region, age, and place of death. Annual percent change and average annual percent change were calculated using Joinpoint Regression program. Forecasts were obtained using the optimal Autoregressive Integrated Moving Average (ARIMA) model.

resultsOverall mortality rate due to Parkinson's increased from 1999 to 2022. Male gender, White race, Southern region, and older ages were associated with higher mortality compared to other groups. Deaths at home decreased and hospice deaths increased during the study period.

conclusionsThis study highlights the increasing rate of PD AAMR and how it may become even more prevalent with time, emphasizing the value of increasing knowledge surrounding the disease and its trends to better prepare health systems and individual families for the burden of PD.

Indexed as

healthcare disparitiesmachine learningmortalityParkinson diseaseParkinson disease mortality

Identifiers

PMID39846565
PMCPMC11755521

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LicenceCC BY
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Registered trials

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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.