Evidence map›Paper›PMID 33192460›Full record

ArticleFrontiers in aging neuroscience2020

Metabolomic and Lipidomic Profiling of Preoperative CSF in Elderly Hip Fracture Patients With Postoperative Delirium.

Yongzheng Han, Wenchao Zhang, Jiao Liu, Yanan Song, Taotao Liu, Zhengqian Li, Xiaoxiao Wang, Ning Yang, Yue Li, Dengyang Han and 7 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 9% 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

30 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Observational
  15. Article
  16. Review
  17. Article
  18. Review
  19. Review
  20. Metabolites · 2022
    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

17 authors at 3 institutions in 1 country.

Yongzheng HanDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Wenchao ZhangDepartment of Anesthesiology, Beijing Jishuitan Hospital, Beijing, China.
Jiao LiuCenter of Medical and Health Analysis, Peking University Health Science Center, Beijing, China.
Yanan SongDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Taotao LiuDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Zhengqian LiDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Xiaoxiao WangResearch Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, China.
Ning YangDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Yue LiDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Dengyang HanDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Xinning MiDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Yang ZhouDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Min LiDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Xiangyang GuoDepartment of Anesthesiology, Peking University Third Hospital, Beijing, China.
Lijun ZhongCenter of Medical and Health Analysis, Peking University Health Science Center, Beijing, China.
Geng WangDepartment of Anesthesiology, Beijing Jishuitan Hospital, Beijing, China.
Yi YuanDepartment of Anesthesiology, Beijing Jishuitan Hospital, Beijing, China.
Peking University · CNPeking University Third Hospital · CNBeijing Jishuitan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate dysregulated molecules in preoperative cerebrospinal fluid (CSF) of elderly hip fracture patients with postoperative delirium (POD), in order to identify potential pathological mechanisms and biomarkers for pre-stage POD. MATERIALS AND

methodsThis nested case control study used untargeted metabolomic and lipidomic analysis to profile the preoperative CSF of patients (

resultsDemographic characteristics of the groups were matched. Eighteen metabolites and thirty-three lipids were dysregulated in the preoperative CSF of POD patients. Pathway enrichment analysis revealed perturbations in D-glutamine and D-glutamate metabolism; glycerophospholipid metabolism; alanine, aspartate and glutamate metabolism; sphingolipid metabolism; histidine metabolism; and arginine biosynthesis at the pre-delirium stage. Receiver operating characteristic curve analysis indicated that phosphatidylethanolamine (PE, 40:7e), with an area under the curve value of 0.92, is a potential biomarker for POD.

conclusionMultiple pathological mechanisms in the POD group were involved before surgery, including neuroinflammation, oxidative stress, and energy metabolism disorders induced by hypoxia, as well as neurotransmitter imbalances such as increased dopamine and glutamate, and decreased glutamine. These metabolic abnormalities potentially increase the fragility of the brain, thus contributing to POD. PE (40:7e) might be a potential biomarker for POD. Not only do our results provide potential biomarkers for POD, but also provide information for deep pathological research. CLINICAL

trial registrationwww.ClinicalTrials.gov, identifier ChiCTR1900021533.

Indexed as

cerebrospinal fluidhip fracturelipidomicsmetabolomicspostoperative delirium

Identifiers

PMID33192460
PMCPMC7642614
OpenAlexW3093819740

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.