Evidence map›Paper›PMID 41684736›Full record

SynthesisFrontiers in neurology

Can patient-reported outcome measures predict mortality in neurological populations? A systematic review.

Hyunjun Ahn, Yadi Li, Nicolas Thompson, LaDonna Pierce, Irene Katzan, Brittany Lapin

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neurology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Hyunjun AhnLerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States.
Yadi LiDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, United States.
Nicolas ThompsonDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, United States.
LaDonna PierceFloyd D. Loop Alumni Library, Cleveland Clinic, Cleveland, OH, United States.
Irene KatzanCerebrovascular Center Neurological Institute, Cleveland, OH, United States.
Brittany LapinDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patient-reported outcome measures (PROMs) are increasingly used for symptom monitoring and care delivery, yet their prognostic value for identifying patients at higher risk for mortality in neurological populations is unclear. This systematic review evaluated whether PROMs predict mortality and/or survival in adults with neurological conditions. Methods: We systematically searched MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials (January 2002-November 2024) for studies incorporating PROMs into mortality or survival prediction models across 10 neurological conditions: motor neuron disease, diabetic neuropathy, nervous system cancers, Alzheimer's and other dementias, Guillain-Barré syndrome, epilepsy, headache, multiple sclerosis, Parkinson's disease, and stroke. Screening, data extraction, and risk-of-bias assessment followed the CHARMS and PRISMA guidelines. Findings were descriptively summarized. Results: Of 6,218 abstracts reviewed, 49 studies met the inclusion criteria. Most evaluated stroke ( Conclusion: PROMs independently predict mortality in several neurological conditions, though prognostic value varied by condition and instrument type. Future studies should evaluate their additive value and feasibility for integration into prognostic models in routine care.

Indexed as

mortalityneurologypatient reported outcomesprediction modelquality of lifesurvivalsystematic review

Identifiers

PMID41684736
PMCPMC12890656

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.