Evidence map›Paper›PMID 32642327›Full record

ArticleNeurology. Clinical practice2020

Comorbid disease drives short-term hospitalization outcomes in patients with multiple sclerosis.

Adys Mendizabal, Dylan P Thibault, James A Crispo, Adina Paley, Allison W Willis

Open access · greenAbstract read
In one paragraph

Article in Neurology. Clinical practice, 2020. 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
0.4field-weighted citation impact, top 39% 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.

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, 6 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
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 at 1 institution in 1 country.

Adys MendizabalDepartment of Neurology (AM, DPT, JAC, AP, AWW), University of Pennsylvania Perelman School of Medicine; Department of Neurology Translational Center of Excellence for Neuroepidemiology (DPT, JAC, AWW), Neurological Outcomes and Disparities Research, University of Pennsylvania Perelman School of Medicine; Department of Biostatistics (AWW), Epidemiology and Informatics, University of Pennsylvania; Center for Clinical Epidemiology and Biostatistics (AWW), University of Pennsylvania Perelman School of Medicine; and Leonard Davis Institute of Health Economics (AWW), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Dylan P ThibaultDepartment of Neurology (AM, DPT, JAC, AP, AWW), University of Pennsylvania Perelman School of Medicine; Department of Neurology Translational Center of Excellence for Neuroepidemiology (DPT, JAC, AWW), Neurological Outcomes and Disparities Research, University of Pennsylvania Perelman School of Medicine; Department of Biostatistics (AWW), Epidemiology and Informatics, University of Pennsylvania; Center for Clinical Epidemiology and Biostatistics (AWW), University of Pennsylvania Perelman School of Medicine; and Leonard Davis Institute of Health Economics (AWW), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
James A CrispoDepartment of Neurology (AM, DPT, JAC, AP, AWW), University of Pennsylvania Perelman School of Medicine; Department of Neurology Translational Center of Excellence for Neuroepidemiology (DPT, JAC, AWW), Neurological Outcomes and Disparities Research, University of Pennsylvania Perelman School of Medicine; Department of Biostatistics (AWW), Epidemiology and Informatics, University of Pennsylvania; Center for Clinical Epidemiology and Biostatistics (AWW), University of Pennsylvania Perelman School of Medicine; and Leonard Davis Institute of Health Economics (AWW), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Adina PaleyDepartment of Neurology (AM, DPT, JAC, AP, AWW), University of Pennsylvania Perelman School of Medicine; Department of Neurology Translational Center of Excellence for Neuroepidemiology (DPT, JAC, AWW), Neurological Outcomes and Disparities Research, University of Pennsylvania Perelman School of Medicine; Department of Biostatistics (AWW), Epidemiology and Informatics, University of Pennsylvania; Center for Clinical Epidemiology and Biostatistics (AWW), University of Pennsylvania Perelman School of Medicine; and Leonard Davis Institute of Health Economics (AWW), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Allison W WillisDepartment of Neurology (AM, DPT, JAC, AP, AWW), University of Pennsylvania Perelman School of Medicine; Department of Neurology Translational Center of Excellence for Neuroepidemiology (DPT, JAC, AWW), Neurological Outcomes and Disparities Research, University of Pennsylvania Perelman School of Medicine; Department of Biostatistics (AWW), Epidemiology and Informatics, University of Pennsylvania; Center for Clinical Epidemiology and Biostatistics (AWW), University of Pennsylvania Perelman School of Medicine; and Leonard Davis Institute of Health Economics (AWW), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
University of Pennsylvania · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveReadmission is used as a quality indicator and is the primary target outcome for disease-modifying therapy (DMT) for multiple sclerosis (MS). However, data on readmissions for patients with MS are limited.

methodsUsing the US Nationwide Readmissions Database, we performed a retrospective cohort study of adults hospitalized for MS in 2014. Primary study outcomes were within 30- and 90-day readmissions. Descriptive analyses compared patient, clinical, and hospital variables readmission status. Multivariable logistic regression models estimated the associations between these variables and readmission.

resultsOf 16,629 individuals meeting the study criteria, most were women (73.7%), aged 35-54 years (48.0%), and Medicare program participants (36.8%). In total, 49.7% of inpatients with MS had 1-2 comorbid medical conditions and 23.7% had 3 or more. Having 3 or more comorbidity conditions associated with increased adjusted odds of the 30-day readmission (adjusted odds ratio [AOR] 1.92, 1.34-2.74). Anemia (AOR 1.62, 1.22-2.14), rheumatoid arthritis/collagen vascular diseases (AOR 2.20, 1.45-3.33), congestive heart failure (AOR 2.43, 1.39-4.24), chronic pulmonary disease (AOR 1.35, 1.02-1.78), diabetes with complications (AOR 2.27, 1.45-3.56), hypertension (AOR 1.25, 1.03-1.53), obesity (AOR 1.35, 1.05-1.73), and renal failure (AOR 1.68, 1.06-2.67) were associated with the 30-day readmission. Medicare insurance and nonroutine discharge were also associated with readmission, whereas patient characteristics (sex, age, and socioeconomic status) were not. The most frequent (26.7%) reason for readmission was multiple sclerosis. Ninety-day analyses produced similar findings.

conclusionsComorbid diseases were associated with the readmission for persons with multiple sclerosis. Evaluations of the real-world effectiveness for DMTs in reducing hospitalizations in patients with MS may need to consider comorbid disease burden and management.

Identifiers

PMID32642327
PMCPMC7292556
OpenAlexW3022910051

What OpenQuestion holds

Textmetadata
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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.