Evidence map›Paper›PMID 31616388›Full record

ArticleFrontiers in microbiology2019

Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS.

Anna F Lau, Robert C Walchak, Heather B Miller, E Susan Slechta, Kamal Kamboj, Katherine Riebe, Amy E Robertson, Jeremy J Gilbreath, Kaitlin F Mitchell, Meghan A Wallace and 20 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
4.0field-weighted citation impact, top 6% 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

29 citing papers in PubMed, 55 citations in OpenAlex.

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  18. Studies in mycology · 2021
    Review
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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

30 authors at 11 institutions in 1 country.

Anna F LauDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United States.
Robert C WalchakDivision of Clinical Microbiology, Mayo Clinic, Rochester, MN, United States.
Heather B MillerDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
E Susan SlechtaARUP Institute for Clinical and Experimental Pathology, Salt Lake City, UT, United States.
Kamal KambojDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, United States.
Katherine RiebeDepartment of Pathology, Medical College of Wisconsin, Milwaukee, WI, United States.
Amy E RobertsonClinical Microbiology Laboratory, Weill Cornell Medical Center/New York Presbyterian Hospital, New York, NY, United States.
Jeremy J GilbreathDepartment of Laboratory Medicine, University of Washington, Seattle, WA, United States.
Kaitlin F MitchellDepartment of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States.
Meghan A WallaceDepartment of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States.
Alexandra L BrysonDepartment of Pathology, Virginia Commonwealth University School of Medicine, Richmond, VA, United States.
Joan-Miquel Balada-LlasatDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, United States.
Amanda BulmanBruker Daltonics, Inc., Billerica, MA, United States.
Blake W BuchanDepartment of Pathology, Medical College of Wisconsin, Milwaukee, WI, United States.
Carey-Ann D BurnhamDepartment of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States.
Susan Butler-WuDepartment of Laboratory Medicine, University of Washington, Seattle, WA, United States.
Uma DesaiDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United States.
Christopher D DoernDepartment of Pathology, Virginia Commonwealth University School of Medicine, Richmond, VA, United States.
Kimberly E HansonARUP Institute for Clinical and Experimental Pathology, Salt Lake City, UT, United States.
Christina M HendersonDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United States.
Markus KostrzewaBruker Daltonics, Inc., Billerica, MA, United States.
Nathan A LedeboerDepartment of Pathology, Medical College of Wisconsin, Milwaukee, WI, United States.
Thomas MaierBruker Daltonics, Inc., Billerica, MA, United States.
Preeti PancholiDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, United States.
Audrey N SchuetzClinical Microbiology Laboratory, Weill Cornell Medical Center/New York Presbyterian Hospital, New York, NY, United States.
Gongyi ShiBruker Daltonics, Inc., Billerica, MA, United States.
Nancy L WengenackDivision of Clinical Microbiology, Mayo Clinic, Rochester, MN, United States.
Sean X ZhangDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Adrian M ZelaznyDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United States.
Karen M FrankDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United States.
National Institutes of Health Clinical Center · USBruker (United States) · USMedical College of Wisconsin · USThe Ohio State University Wexner Medical Center · USWashington University in St. Louis · USARUP Laboratories (United States) · USCornell University · USJohns Hopkins University · USUniversity of Washington · USVirginia Commonwealth University · USWinnMed · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesRapid and accurate mold identification is critical for guiding therapy for mold infections. MALDI-TOF MS has been widely adopted for bacterial and yeast identification; however, few clinical laboratories have applied this technology for routine mold identification due to limited database availability and lack of standardized processes. Here, we evaluated the versatility of the NIH Mold Database in a multicenter evaluation.

methodsThe NIH Mold Database was evaluated by eight US academic centers using a solid media extraction method and a challenge set of 80 clinical mold isolates. Multiple instrument parameters important for spectra optimization were evaluated, leading to the development of two specialized acquisition programs (NIH method and the Alternate-B method).

resultsA wide range in performance (33-77%) was initially observed across the eight centers when routine spectral acquisition parameters were applied. Use of the NIH or the Alternate-B specialized acquisition programs, which are different than those used routinely for bacterial and yeast spectral acquisition (MBT_AutoX), in combination with optimized instrument maintenance, improved performance, illustrating that acquisition parameters may be one of the key limiting variable in achieving successful performance.

conclusionSuccessful mold identification using the NIH Database for MALDI-TOF MS on Biotyper systems was demonstrated across multiple institutions for the first time following identification of critical program parameters combined with instrument optimization. This significantly advances our potential to implement MALDI-TOF MS for mold identification across many institutions. Because instrument variability is inevitable, development of an instrument performance standard specific for mold spectral acquisition is suggested to improve reproducibility across instruments.

Indexed as

filamentous fungiidentificationMALDI-TOF MSmoldrapid

Identifiers

PMID31616388
PMCPMC6764242
OpenAlexW2970560761

What OpenQuestion holds

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LicenceCC BY
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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.