Evidence map›Paper›PMID 40677684›Full record

ArticleFrontiers in neurology2025

Identifying key covariates of clinical outcomes for critically ill patients with Parkinson's disease: analysis of the MIMIC-IV database.

LiHua Luo, Yang Chen, HangQing Zhao, Rong Dong, Yuzhou Long

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

5 authors.

LiHua Luo *Department of Neurology, The Affiliated Hospital of Yunnan University, Kunming, Yunnan, China.
Yang Chen *The First People's Hospital of Yunnan Province, Kunming, Yunnan, China.
HangQing ZhaoDepartment of Neurology, The Affiliated Hospital of Yunnan University, Kunming, Yunnan, China.
Rong DongDepartment of Neurology, The Affiliated Hospital of Yunnan University, Kunming, Yunnan, China.
Yuzhou LongDepartment of Neurology, The Affiliated Hospital of Yunnan University, Kunming, Yunnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Parkinson's disease (PD) is a common chronic degenerative disease, and its exact pathological mechanism remains unclear. In this study, we identified covariates associated with the clinical outcomes of PD using patient data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, providing new references for the treatment of patients. Methods: The data of patients with PD and relevant covariates were obtained from the MIMIC-IV database. The patients were categorized into the in-hospital death and in-hospital survival groups based on their survival status, and the relationship between their outcomes and covariates was investigated. Key covariates markedly associated with the clinical outcomes of PD were further screened using regression analysis. Finally, a nomogram for predicting the risk of in-hospital mortality in patients with PD was constructed and validated. Results: A total of 143 patients with PD and 37 covariates were included in this study. Of the included patients, 25 were assigned to the in-hospital death group and 118 were assigned to the in-hospital survival group. Covariates such as the respiratory rate, mean arterial pressure (MAP), respiratory failure, anion gap, bicarbonate levels, blood urea nitrogen levels, and sequential organ failure assessment (SOFA) scores were markedly associated with in-hospital mortality in patients with PD. Subsequently, age [hazard ratio (HR) = 1.0565, 95% confidence interval (CI) = 1.0065-1.1090, Conclusion: This study revealed four key covariates associated with the clinical outcomes of PD, providing new references for the treatment of patients.

Indexed as

covariatein-hospital mortalityMIMIC IV databasenomogramParkinson’s diseaseprognostic factors

Identifiers

PMID40677684
PMCPMC12267009

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