Evidence map›Paper›PMID 33087496›Full record

ArticleNeurology2021

Predictors of Mortality in Older Adults With Epilepsy: Implications for Learning Health Systems.

Leah J Blank, Emily K Acton, Allison W Willis

Abstract read
In one paragraph

Article in Neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

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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

3 authors.

Leah J BlankFrom the Department of Neurology, Division of Health Outcomes and Knowledge Translational Research (L.J.B.), and Department of Population Health Science and Policy (L.J.B.), Icahn School of Medicine at Mount Sinai, New York, NY; Center for Clinical Epidemiology and Biostatistics (E.K.A., A.W.W.), Department of Neurology Translational Center of Excellence for Neuroepidemiology and Neurological Outcomes Research (E.K.A., A.W.W.), Department of Neurology (A.W.W.), Department of Biostatistics, Epidemiology and Informatics (A.W.W.), and Leonard Davis Institute of Health Economics (A.W.W.), University of Pennsylvania Perelman School of Medicine, Philadelphia. Leah.Blank@mssm.edu.
Emily K ActonFrom the Department of Neurology, Division of Health Outcomes and Knowledge Translational Research (L.J.B.), and Department of Population Health Science and Policy (L.J.B.), Icahn School of Medicine at Mount Sinai, New York, NY; Center for Clinical Epidemiology and Biostatistics (E.K.A., A.W.W.), Department of Neurology Translational Center of Excellence for Neuroepidemiology and Neurological Outcomes Research (E.K.A., A.W.W.), Department of Neurology (A.W.W.), Department of Biostatistics, Epidemiology and Informatics (A.W.W.), and Leonard Davis Institute of Health Economics (A.W.W.), University of Pennsylvania Perelman School of Medicine, Philadelphia.
Allison W WillisFrom the Department of Neurology, Division of Health Outcomes and Knowledge Translational Research (L.J.B.), and Department of Population Health Science and Policy (L.J.B.), Icahn School of Medicine at Mount Sinai, New York, NY; Center for Clinical Epidemiology and Biostatistics (E.K.A., A.W.W.), Department of Neurology Translational Center of Excellence for Neuroepidemiology and Neurological Outcomes Research (E.K.A., A.W.W.), Department of Neurology (A.W.W.), Department of Biostatistics, Epidemiology and Informatics (A.W.W.), and Leonard Davis Institute of Health Economics (A.W.W.), University of Pennsylvania Perelman School of Medicine, Philadelphia.

Funding

Clinical Pharmacoepidemiology Training ProgramT32GM075766 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI Sean Hennessy, Charles Edward Leonard · 2006 to 2026
$8.4M
Neurologic Clinical Epidemiology Training ProgramT32NS061779 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Andrea Lauren Christman Schneider, Allison Willis · 2008 to 2026
$4.6M
NIGMS NIH HHS T32 GM075766NINDS NIH HHS T32 NS061779
6 · The paper itself

Abstract

objectiveTo determine the incidence of epilepsy and subsequent 5-year mortality among older adults, as well as characteristics associated with mortality.

methodsThis was a retrospective cohort study of Medicare beneficiaries age 65 or above with at least 2 years enrollment before January 2009. Incident epilepsy cases were identified in 2009 using ICD-9-CM code-based algorithms; death was assessed through 2014. Cox regression models examined the association between 5-year mortality and incident epilepsy, and whether mortality differed by sociodemographic characteristics or comorbid disorders.

resultsAmong the 99,990 of 33,615,037 beneficiaries who developed epilepsy, most were White (79.7%), female (57.3%), urban (80.5%), and without Medicaid (71.3%). The 5-year mortality rate for incident epilepsy was 62.8% (62,838 deaths). In multivariable models, lower mortality was associated with female sex (adjusted hazards ratio [AHR] 0.85, 95% confidence interval [CI] 0.84-0.87), Asian race (AHR 0.82, 95% CI 0.76-0.88), and Hispanic ethnicity (AHR 0.81, 95% CI 0.76-0.84). Hazard of death increased with comorbid disease burden (per 1-point increase: AHR 1.27, 95% CI 1.26-1.27) and Medicaid coinsurance (AHR 1.17, 95% CI 1.14-1.19). Incident epilepsy was particularly associated with higher mortality when diagnosed after another neurologic condition: Parkinson disease (AHR 1.29, 95% CI 1.21-1.38), multiple sclerosis (AHR 2.13, 95% CI 1.79-2.59), dementia (AHR 1.33, 95% CI 1.31-1.36), traumatic brain injury (AHR 1.55, 95% CI 1.45-1.66), and stroke/TIA (AHR 1.20, 95% CI 1.18-1.21).

conclusionsNewly diagnosed epilepsy is associated with high 5-year mortality among Medicare beneficiaries. Future studies that parse the interplay of effects from underlying disease, race, sex, and poverty on mortality will be critical in the design of learning health care systems to reduce premature deaths.

Indexed as

AgedAged, 80 and overComorbidityEpilepsyFemaleHumansLearning Health SystemMaleMedicareRetrospective StudiesRisk FactorsUnited States

Identifiers

PMID33087496
PMCPMC7884975

What OpenQuestion holds

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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.