Evidence map›Paper›PMID 33081722›Full record

ArticleBMC microbiology2020

Evaluation of the Autof MS1000 mass spectrometer in the identification of clinical isolates.

Qiong Ma, Qi Zhang, Youhua Yuan, Wenjuan Yan, Shanmei Wang, Junhong Xu, Jiangfeng Zhang, Yuming Wang, Yi Li

Open access · goldAbstract read
In one paragraph

Article in BMC microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 18 citations in OpenAlex.

  1. Comparative analytical performance of Autof MS2600 and Biotyper Sirius for rapid MALDI-TOF MS identification of microorganisms from positive blood cultures.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
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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

9 authors at 2 institutions in 1 country.

Qiong MaDepartment of Clinical Laboratory, Henan Provincial People's Hospital, Henan University People's Hospital, Zhengzhou, 450003, Henan, China.
Qi ZhangDepartment of Clinical Laboratory, Henan Provincial People's Hospital, Henan University People's Hospital, Zhengzhou, 450003, Henan, China.
Youhua YuanDepartment of Clinical Laboratory, Henan Provincial People's Hospital, Henan University People's Hospital, Zhengzhou, 450003, Henan, China.
Wenjuan YanDepartment of Clinical Laboratory, Henan Provincial People's Hospital, Henan University People's Hospital, Zhengzhou, 450003, Henan, China.
Shanmei WangDepartment of Clinical Laboratory, Henan Provincial People's Hospital, Henan University People's Hospital, Zhengzhou, 450003, Henan, China.
Junhong XuDepartment of Clinical Laboratory, Henan Provincial People's Hospital, Henan University People's Hospital, Zhengzhou, 450003, Henan, China.
Jiangfeng ZhangDepartment of Clinical Laboratory, Henan Provincial People's Hospital, Henan University People's Hospital, Zhengzhou, 450003, Henan, China.
Yuming WangHenan Provincial People's Hospital, Henan University People's Hospital, and People's Hospital of Henan University, Weiwu Road 5, 450003, Zhengzhou, Henan, People's Republic of China. henanyuming@sina.com.
Yi LiDepartment of Clinical Laboratory, Henan Provincial People's Hospital, Henan University People's Hospital, Zhengzhou, 450003, Henan, China. liyilabmed@henu.edu.cn.
Henan Provincial People's Hospital · CNHenan University · CN

Funding

Henan Provincial Key Programs in Science and Technology 181200211900Joint Programs of Henan Provincial Government and Healthy Ministry SB2018084 SB20190318 LHGJ20190611
6 · The paper itself

Abstract

backgroundTo evaluate the accuracy and performance of the Autof MS1000 mass spectrometer in bacteria and yeast identification, 2342 isolates were obtained from microbial cultures of clinical specimens (e.g. blood, cerebrospinal fluid, respiratory tract samples, lumbar puncture fluid, wound samples, stool, and urine) collected in 2019 in Henan Provincial People's Hospital. Repetitive strains from the same patient were excluded. We tested the Autof MS1000 and Bruker Biotyper mass spectrometry systems and the classical biochemical identification system VITEK 2/API 20C AUX. Inconsistencies in strain identification among the three systems were identified by 16S rDNA and gene sequencing.

resultsAt the species level, the Autof MS1000 and Bruker Biotyper systems had isolate identification accuracies of 98.9 and 98.5%, respectively. At the genus level, the Autof MS1000 and Bruker Biotyper systems were 99.7 and 99.4% accurate, respectively. The instruments did not significantly differ in identification accuracy at either taxonomic level. The frequencies of unreliable identification were 1.1% (26/2342) for the Autof MS1000 and 1.5% (34/2342) for the Bruker Biotyper. In vitro experiments demonstrated that the coincidence rate of the Autof MS1000 mass spectrometer in the identification of five types of bacteria was > 93%, the identification error rate was < 3%, and the no identification rate was 0. This indicates that the Autof MS1000 system is acceptable for identification.

conclusionsThe Autof MS1000 mass spectrometer can be utilised to identify clinical isolates. However, an upgradation of the database is recommended to correctly identify rare strains.

Indexed as

Spectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationBacteriaBacterial Typing TechniquesHumansRNA, BacterialRNA, Ribosomal, 16SRNA, BacterialRNA, Ribosomal, 16SAutof MS1000Bacterial identificationBruker BiotyperClinical samplesMass spectrometryPerformance verification

Identifiers

PMID33081722
PMCPMC7576717
OpenAlexW3094265123

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.