Evidence map›Paper›PMID 24829234›Full record

SynthesisJournal of clinical microbiology2014

Accuracy of matrix-assisted laser desorption ionization-time of flight mass spectrometry for identification of clinical pathogenic fungi: a meta-analysis.

Huazhi Ling, Zhijie Yuan, Jilu Shen, Zhongxin Wang, Yuanhong Xu

Abstract readEvaluation StudyMeta-Analysis
In one paragraph

Synthesis in Journal of clinical microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 4 pooled it
–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

26 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  9. Identification of Microbial Strains via 2D Cross-Correlation of LC-MS Data.Journal of the American Society for Mass Spectrometry · 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

5 authors.

Huazhi LingDepartment of Clinical Laboratory, First Affiliated Hospital, Anhui Medical University, Hefei, People's Republic of China.ORCID http://orcid.org/0000-0003-2768-1128
Zhijie YuanSchool of Mathematics, Hefei University of Technology, Hefei, People's Republic of China School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, People's Republic of China.
Jilu ShenDepartment of Clinical Laboratory, First Affiliated Hospital, Anhui Medical University, Hefei, People's Republic of China.
Zhongxin WangDepartment of Clinical Laboratory, First Affiliated Hospital, Anhui Medical University, Hefei, People's Republic of China.
Yuanhong XuDepartment of Clinical Laboratory, First Affiliated Hospital, Anhui Medical University, Hefei, People's Republic of China xyhong1964@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fungal infections in the clinic have become increasingly serious. In many cases, the identification of clinically relevant fungi remains time-consuming and may also be unreliable. Matrix-assisted laser desorption ionization-time of flight mass spectroscopy (MALDI-TOF MS) is a newly developed diagnostic tool that is increasingly being employed to rapidly and accurately identify clinical pathogenic microorganisms. The present meta-analysis aimed to systematically evaluate the accuracy of MALDI-TOF MS for the identification of clinical pathogenic fungi. After a rigorous selection process, 33 articles, involving 38 trials and a total of 9,977 fungal isolates, were included in the meta-analysis. The random-effects pooled identification accuracy of MALDI-TOF MS increased from 0.955 (95% confidence interval [CI], 0.939 to 0.969) at the species level to 0.977 (95% CI, 0.955 to 0.993) at the genus level (P < 0.001; χ(2) = 15.452). Subgroup analyses were performed at the species level for several categories, including strain, source of strain, system, system database, and modified outcomes, to calculate the accuracy and to investigate heterogeneity. These analyses revealed significant differences between the overall meta-analysis and some of the subanalyses. In parallel, significant differences in heterogeneity among different systems and among different methods for calculating the identification ratios were found by multivariate metaregression, but none of the factors, except for the moderator of outcome, was significantly associated with heterogeneity by univariate metaregression. In summary, the MALDI-TOF MS method is highly accurate for the identification of clinically pathogenic fungi; future studies should analyze the comprehensive capability of this technology for clinical diagnostic microbiology.

Indexed as

FungiHumansMicrobiological TechniquesMycologyMycosesSpectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization

Identifiers

PMID24829234
PMCPMC4097711

What OpenQuestion holds

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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.