Evidence map›Paper›PMID 36225889›Full record

ArticleFrontiers in aging neuroscience2022

The hotspots and publication trends in postoperative delirium: A bibliometric analysis from 2000 to 2020.

Xiaowan Lin, Ying Cao, Xiao Liu, Kang Yu, Huihui Miao, Tianzuo Li

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

6 authors.

Xiaowan LinDepartment of Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Ying CaoDepartment of Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Xiao LiuDepartment of Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Kang YuDepartment of Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Huihui MiaoDepartment of Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Tianzuo LiDepartment of Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Postoperative delirium (POD) is a common aging-associated postoperative complication that has received increasing attention in the context of the aging global population and the number of articles published on POD is gradually increasing. This study aimed to quantify the basic information of scholarly publications on POD and identify the most impactful literature, trends, and hotspots in POD research. Materials and methods: We searched articles on POD through the Science Citation Index Expanded databases published from 2000 to 2020. Bibliographic information, including year, country, authorship, type, journal, funding, affiliations, subject areas, and hotspots, was collected for further analysis. Results: A total of 2,114 articles on POD from 2000 to 2020 were identified. The highest number of studies ( Conclusion: This study provides an overview of developments in the field of POD over the past 20 years using bibliometric analysis. Overall, research on POD has flourished worldwide. The United States (US) has a relatively high academic impact owing to its productive expertise and institutions in this field. Despite much research illustrating the diagnosis and management of POD in clinical practice, more basic research is needed.

Indexed as

bibliometricelderlyhotspotsPODpublication trends

Identifiers

PMID36225889
PMCPMC9549321

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.