Evidence map›Paper›PMID 39503271›Full record

ArticleMovement disorders clinical practice2025

Identifying and Predicting Risk for Hospital Admission among Patients with Parkinsonism.

Emma Tenison, Anita McGrogan, Yoav Ben-Shlomo, Emily J Henderson

Abstract read
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Article in Movement disorders clinical practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Emma TenisonDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.ORCID 0000-0003-2330-8844
Anita McGroganDepartment of Life Sciences, University of Bath, Claverton Down, Bath, United Kingdom.ORCID 0000-0003-3855-9400
Yoav Ben-ShlomoDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.ORCID 0000-0001-6648-3007
Emily J HendersonDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.ORCID 0000-0002-0016-1870

Funding

Gatsby Charitable Foundation GAT3676
6 · The paper itself

Abstract

backgroundPatients with parkinsonism are more likely than age-matched controls to be admitted to hospital. It may be possible to reduce the cost and negative impact by identifying patients at highest risk and intervening to reduce hospital-related costs. Predictive models have been developed in nonparkinsonism populations.

objectivesThe aims were to (1) describe the reasons for admission, (2) describe the rates of hospital admission/emergency department attendance over time, and (3) use routine data to risk stratify unplanned hospital attendance in people with parkinsonism.

methodsThis retrospective cohort study used Clinical Practice Research Datalink GOLD, a large UK primary care database, linked to hospital admission and emergency department attendance data. The primary diagnoses for nonelective admissions were categorized, and the frequencies were compared between parkinsonism cases and matched controls. Multilevel logistic and negative binomial regression models were used to estimate the risk of any and multiple admissions, respectively, for patients with parkinsonism.

resultsThere were 9189 patients with parkinsonism and 45,390 controls. The odds of emergency admission more than doubled from 2010 to 2019 (odds ratio [OR] 2.33; 95% confidence interval [CI] 1.96, 2.76; P-value for trend <0.001). Pneumonia was the most common reason for admission among cases, followed by urinary tract infection. Increasing age, multimorbidity, parkinsonism duration, deprivation, and care home residence increased the odds of admission. Rural location was associated with reduced OR for admission (OR 0.79; 95% CI 0.70, 0.89).

conclusionsOur risk stratification tool may enable empirical targeting of interventions to reduce admission risk for parkinsonism patients.

Indexed as

HospitalizationParkinsonian DisordersPatient AdmissionAdultAgedAged, 80 and overEmergency Service, HospitalFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsUnited Kingdomemergency departmenthospital admissionparkinsonismParkinson's diseaseprimary care database

Identifiers

PMID39503271
PMCPMC11736886

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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.