Evidence map›Paper›PMID 36721795›Full record

ReviewNeuropsychiatric disease and treatment2023

Effective Management of "OFF" Episodes in Parkinson's Disease: Emerging Treatment Strategies and Unmet Clinical Needs.

Nbaa Masood, Joohi Jimenez-Shahed

Open access · goldAbstract readReview
In one paragraph

Review in Neuropsychiatric disease and treatment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
5.1field-weighted citation impact, top 4% 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

16 citing papers in PubMed, 25 citations in OpenAlex.

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  12. Parkinson's disease · 2025
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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

2 authors at 1 institution in 1 country.

Nbaa MasoodDepartment of Neurology, Icahn School of Medicine at Mount Sinai, Mount Sinai West, New York, NY, USA.
Joohi Jimenez-ShahedDepartment of Neurology, Icahn School of Medicine at Mount Sinai, Mount Sinai West, New York, NY, USA.ORCID 0000-0002-9772-7569
Icahn School of Medicine at Mount Sinai · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motor complications related to the chronic administration of levodopa and failure to prevent the neurodegenerative disease process counterbalance the pivotal discovery of levodopa as the cornerstone of PD treatment. Excellent motor control is offered early during the course of treatment, but this diminishes as pathological changes in the striatum lead to synaptic dopamine levels becoming completely dependent on exogenous dopamine. This non-physiologic stimulation of dopamine receptors eventually manifests as OFF episodes. As no disease modifying therapy exists for PD that can disrupt these pathological changes, most research and treatment focuses on optimization of dopaminergic stimulation of striatal receptors so that they mimic tonic, physiologic stimulation as closely as possible. Strategies focusing on these challenges have included non-pharmacologic approaches, optimizing levodopa pharmacokinetics, using adjunctive treatments including those with non-dopaminergic mechanisms, and implementing rescue therapies. Device aided therapies, including surgery, are also available. In this review, we will focus on effective management of motor symptoms related to OFF periods, including emerging strategies. Unmet clinical needs will be discussed, including non-motor symptoms, targeted molecular therapies and disease modifying therapy.

Indexed as

advanced Parkinson’s Diseasechronic levodopa complicationscontinuous dopaminergic stimulationdyskinesiasmotor complicationsnonmotor symptoms

Identifiers

PMID36721795
PMCPMC9884436
OpenAlexW4318753984

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.