Evidence map›Paper›PMID 32922015›Full record

ArticleNeuropsychiatric disease and treatment2020

Identification of Potential Metabolite Markers for Middle-Aged Patients with Post-Stroke Depression Using Urine Metabolomics.

Jing Xie, Yu Han, Yueling Hong, Wen-Wen Li, Qilin Pei, Xueyi Zhou, Bingbing Zhang, Ying Wang

Open access · goldAbstract read
In one paragraph

Article in Neuropsychiatric disease and treatment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 28% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
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

8 authors at 4 institutions in 1 country.

Jing Xie *Chongqing Emergency Medical Center, Department of Endocrinology and Nephrology, The Fourth People's Hospital of Chongqing, Central Hospital of Chongqing University, Chongqing 400014, People's Republic of China.
Yu Han *Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, People's Republic of China.
Yueling Hong *Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, People's Republic of China.
Wen-Wen LiDepartment of Pathology, Faculty of Basic Medicine, Chongqing Medical University, Chongqing 400016, People's Republic of China.
Qilin PeiInstitute of Life Sciences, Chongqing Medical University, Chongqing 400016, People's Republic of China.
Xueyi ZhouDepartment of Pathology, Faculty of Basic Medicine, Chongqing Medical University, Chongqing 400016, People's Republic of China.
Bingbing ZhangKey Laboratory of Biorheological Science and Technology, Ministry of Education, Bioengineering College, Chongqing University, Chongqing 400044, People's Republic of China.
Ying WangDepartment of Rehabilitation, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400000, People's Republic of China.
Chongqing Medical University · CNChongqing Emergency Medical Center · CNChongqing University · CNFirst Affiliated Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPost-stroke depression (PSD) is one of the most common complications in stroke survivors. But, there are still no objective methods to diagnose PSD. This study aims to identify potential biomarkers for diagnosing PSD in middle-aged stroke survivors.

methodsMiddle-aged subjects aged 30 to 59 years (92 PSD patients and 89 stroke survivors without depression) were included in this study. Urinary metabolites were detected by gas chromatography-mass spectrometry (GC-MS). Differential urinary metabolites and potential biomarkers were screened by applying statistical analysis.

resultsThe different urinary metabolic phenotypes between PSD patients and stroke survivors without depression were identified. A total of 12 differential urinary metabolites were accurately identified by using orthogonal partial least-squares-discriminant analysis. After analyzing those 12 differential urinary metabolites by step-wise logistic regression analysis, only seven metabolites (palmitic acid, hydroxylamine, myristic acid, glyceric acid, lactic acid, tyrosine and azelaic acid) were finally selected as potential biomarkers for diagnosing PSD in middle-aged stroke survivors. A panel consisting of these potential biomarkers could effectively diagnose middle-aged PSD patients.

conclusionUrinary metabolic profiles were different between middle-aged PSD patients and stroke survivors without depression. Our results would be helpful in future for developing an objective method to diagnose PSD in middle-aged stroke survivors.

Indexed as

biomarkersmetabolitespost-stroke depression

Identifiers

PMID32922015
PMCPMC7457842
OpenAlexW3081317868

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.