Evidence map›Paper›PMID 34442364›Full record

ArticleJournal of personalized medicine2021

Personalized Medicine Approach in Treating Parkinson's Disease, Using Oral Administration of Levodopa/Carbidopa Microtablets in Clinical Practice.

Helga María Grétarsdóttir, Erik Widman, Anders Johansson, Dag Nyholm

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Optimizing Treatment of Parkinson's Disease.Journal of personalized medicine · 2022
    Article
  10. 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

4 authors.

Helga María GrétarsdóttirDepartment of Neuroscience, Neurology, Uppsala University, 75185 Uppsala, Sweden.
Erik WidmanDepartment of Neuroscience, Neurology, Uppsala University, 75185 Uppsala, Sweden.
Anders JohanssonDepartment of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden.ORCID 0000-0002-3928-5184
Dag NyholmDepartment of Neuroscience, Neurology, Uppsala University, 75185 Uppsala, Sweden.ORCID 0000-0001-9776-7715

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe most effective symptomatic treatment in Parkinson's disease (PD) is levodopa in standard doses. However, as the disease progresses, there may be a need for a more personalized approach and fine tuning, in accordance with the patients' needs. This study aims to evaluate the individual experience of levodopa/carbidopa 5/1.25 mg microtablets (LC-5) in clinical practice with respect to efficacy, tolerability, and usability. The method used was as follows: patients answered a questionnaire concerning the effect and usability of LC-5, and their medical records were reviewed. Regarding results, thirty-five survey responses were obtained, and 29 patients' medical records were reviewed. The LC-5 dose dispenser usability was generally rated positively and facilitated medication adherence. The majority (85%) of patients reported symptom improvement while using LC-5, compared with previous standard treatments. These results suggest that LC-5 therapy is generally well-tolerated, with favorable patient-reported efficacy and user friendliness, as well as the possibility for an individualized, fine-tuned PD treatment. Further studies with a prospective design and larger study population are needed to confirm the results.

Indexed as

carbidopadose dispenserlevodopamicrotabletsParkinson’s disease

Identifiers

PMID34442364
PMCPMC8400411

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.