Evidence map›Paper›PMID 39327306›Full record

ArticleAnalytical and bioanalytical chemistry2024

Cortisol and cortisone determination by disposable pipette extraction (DPX) and ultra-efficient liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) in urine and saliva samples from patients with Parkinson's disease.

Priscila Kakuda, Israel Donizeti de Souza, Larissa Fritz Covari, Vitor Tumas, Maria Eugênia Costa Queiroz

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Article in Analytical and bioanalytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Interpol review of forensic toxicology, 2023-2025.Forensic science international. Synergy · 2026
    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.

Priscila KakudaDepartment of Pharmaceutical Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil.
Israel Donizeti de SouzaDepartamento de Química, Faculdade de Filosofia Ciências E Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil.
Larissa Fritz CovariDepartamento de Química, Faculdade de Filosofia Ciências E Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil.
Vitor TumasDepartment of Neuroscience and Behavior, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil.
Maria Eugênia Costa QueirozDepartment of Pharmaceutical Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil. mariaeqn@ffclrp.usp.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Higher serum cortisol levels appear to be associated with stress that can overlap or manifest anxiety, fatigue, depression, and sleep dysfunction. These are common and intrusive non-motor symptoms of Parkinson's disease (PD). Thus, stress has been proposed to mediate Parkinson's disease development, and cortisol has been suggested as a biomarker for the generation of stress-related symptoms in Parkinson's disease. This study describes sensitive and robust disposable pipette extraction (DPX) and ultra-efficient liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method to determine cortisol and cortisone (as potential endocrine biomarkers for Parkinson's disease) in 24-h urine and saliva samples obtained from Parkinson's disease patients. Important parameters on DPX extraction were optimized to achieve the best extraction recovery and cleanup efficiency. The proposed method was linear from 0.5 (lower limit of quantification) to 500 ng mL

Indexed as

CortisoneHydrocortisoneParkinson DiseaseSalivaTandem Mass SpectrometryAgedBiomarkersChromatography, High Pressure LiquidFemaleHumansLimit of DetectionMaleMiddle AgedBiomarkersCortisoneHydrocortisoneAnxietyCortisolCortisoneSample preparationUrine

Identifiers

PMID39327306

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.