Evidence map›Paper›PMID 37240599›Full record

ReviewJournal of clinical medicine2023

Application Prospect of the SOFA Score and Related Modification Research Progress in Sepsis.

Xuesong Wang, Zhe Guo, Yan Chai, Ziyi Wang, Haiyan Liao, Ziwen Wang, Zhong Wang

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
6.7field-weighted citation impact, top 2% 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

22 citing papers in PubMed, 31 citations in OpenAlex.

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  18. SOFA in sepsis: with or without GCS.European journal of medical research · 2024
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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

7 authors at 2 institutions in 1 country.

Xuesong WangSchool of Clinical Medicine, Tsinghua University, Beijing 100190, China.ORCID 0000-0001-5346-6902
Zhe GuoSchool of Clinical Medicine, Tsinghua University, Beijing 100190, China.
Yan ChaiSchool of Clinical Medicine, Tsinghua University, Beijing 100190, China.
Ziyi WangSchool of Clinical Medicine, Tsinghua University, Beijing 100190, China.
Haiyan LiaoSchool of Clinical Medicine, Tsinghua University, Beijing 100190, China.
Ziwen WangSchool of Clinical Medicine, Tsinghua University, Beijing 100190, China.
Zhong WangBeijing Tsinghua Changgung Hospital, Tsinghua University, Beijing 100084, China.
Beijing Tsinghua Chang Gung Hospital · CNTsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In 2016, the SOFA score was proposed as the main evaluation system for diagnosis in the definition of sepsis 3.0, and the SOFA score has become a new research focus in sepsis. Some people are skeptical about diagnosing sepsis using the SOFA score. Experts and scholars from different regions have proposed different, modified versions of SOFA score to make up for the related problems with the use of the SOFA score in the diagnosis of sepsis. While synthesizing the different improved versions of SOFA proposed by experts and scholars in various regions, this paper also summarizes the relevant definitions of sepsis put forward in recent years to build a clear, improved application framework of SOFA score. In addition, the comparison between machine learning and SOFA scores related to sepsis is described and discussed in the article. Taken together, by summarizing the application of the improved SOFA score proposed in recent years in the related definition of sepsis, we believe that the SOFA score is still an effective means of diagnosing sepsis, but in the process of the continuous refinement and development of sepsis in the future, the SOFA score needs to be further refined and improved to provide more accurate coping strategies for different patient populations or application directions regarding sepsis. Against the big data background, machine learning has immeasurable value and significance, but its future applications should add more humanistic references and assistance.

Indexed as

machine learningsepsisSOFA score

Identifiers

PMID37240599
PMCPMC10218823
OpenAlexW4377043982

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.