Evidence map›Paper›PMID 38562474›Full record

ArticleFrontiers in microbiology2024

Benefit analysis of the auto-verification system of intelligent inspection for microorganisms.

Yu-Hsiang Ou, Yung-Ta Chang, Ding-Ping Chen, Chun-Wei Chuang, Kuo-Chien Tsao, Chiu-Hsiang Wu, An-Jing Kuo, Huey-Ling You, Chung-Guei Huang

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Yu-Hsiang Ou *Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Yung-Ta Chang *Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Ding-Ping Chen *Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Chun-Wei ChuangDepartment of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Kuo-Chien TsaoDepartment of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Chiu-Hsiang WuDepartment of Laboratory Medicine, Chang Gung Memorial Hospital, Keelung, Taiwan.
An-Jing KuoDepartment of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Huey-Ling YouDepartments of Laboratory Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan.
Chung-Guei HuangDepartment of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, the automatic machine for microbial identification and antibiotic susceptibility tests has been introduced into the microbiology laboratory of our hospital, but there are still many steps that need manual operation. The purpose of this study was to establish an auto-verification system for bacterial naming to improve the turnaround time (TAT) and reduce the burden on clinical laboratory technologists. After the basic interpretation of the gram staining results of microorganisms, the appearance of strain growth, etc., the 9 rules were formulated by the laboratory technologists specialized in microbiology for auto-verification of bacterial naming. The results showed that among 70,044 reports, the average pass rate of auto-verification was 68.2%, and the reason for the failure of auto-verification was further evaluated. It was found that the main causes reason the inconsistency between identification results and strain appearance rationality, the normal flora in the respiratory tract and urine that was identified, the identification limitation of the mass spectrometer, and so on. The average TAT for the preliminary report of bacterial naming was 35.2 h before, which was reduced to 31.9 h after auto-verification. In summary, after auto-verification, the laboratory could replace nearly 2/3 of manual verification and issuance of reports, reducing the daily workload of medical laboratory technologists by about 2 h. Moreover, the TAT on the preliminary identification report was reduced by 3.3 h on average, which could provide treatment evidence for clinicians in advance.

Indexed as

auto-verificationmatrix-assisted laser desorption/ionization-time of flight mass spectrometermicrobiologymicroorganismsturnaround time

Identifiers

PMID38562474
PMCPMC10982382

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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.