Evidence map›Paper›PMID 35164701›Full record

ArticleBMC infectious diseases2022

Characterizing patients with rare mucormycosis infections using real-world data.

Yayue Zhang, Anita H Sung, Emily Rubinstein, Michael Benigno, Richard Chambers, Nataly Patino, Jalal A Aram

Abstract read
In one paragraph

Article in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Review
  5. Review
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.

Yayue ZhangHematology and Oncology Department, Dongzhimen Hospital, Beijing University of Chinese Medicine, Hai Yun Cang on the 5th Zip, Dongcheng District, Beijing, China. zhangyayue@gmx.com.ORCID http://orcid.org/0000-0003-2711-8909
Anita H SungPfizer Inc, Hospital BU, 23 East 42nd Street, New York, NY, 10017, USA.
Emily RubinsteinPfizer Inc, Hospital BU, 23 East 42nd Street, New York, NY, 10017, USA.
Michael BenignoPfizer Inc, Hospital BU, 23 East 42nd Street, New York, NY, 10017, USA.
Richard ChambersPfizer Inc, Hospital BU, 23 East 42nd Street, New York, NY, 10017, USA.
Nataly PatinoPfizer Inc, Hospital BU, 23 East 42nd Street, New York, NY, 10017, USA.
Jalal A AramPfizer Inc, Hospital BU, 23 East 42nd Street, New York, NY, 10017, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInvasive mucormycosis (IM) is a rare and often life-threatening fungal infection, for which clinical and epidemiological understanding is lacking. Electronic health record (EHR) data can be utilized to elucidate large populations of patients with IM to address this unmet need. This study aimed to descriptively assess data on patients with IM using the Optum® EHR dataset.

methodsUS patient data from the Optum® deidentified EHR dataset (2007-2019) were analyzed to identify patients with IM. Patients with hematologic malignancies (HM), at high risk of IM, were selected and sorted by IM diagnosis (ICD9 117.7; ICD10 B46). Demographics, comorbidities/other diagnoses, and treatments were analyzed in patients with IM.

resultsIn total, 1133 patients with HM and IM were identified. Most were between 40 and 64 years of age, Caucasian, and from the Midwest. Essential primary hypertension (50.31%) was the most common comorbidity. Of the 1133 patients, only 33.72% were prescribed an antifungal treatment. The most common antifungal treatments were fluconazole (24.27%) and posaconazole (16.33%), which may have been prophylactic, and any AmB (15.62%).

conclusionsA large population of patients with IM were identified, highlighting the potential of analyzing EHR data to investigate epidemiology, diagnosis, and the treatment of apparently rare diseases.

Indexed as

Hematologic NeoplasmsMucormycosisMycosesAntifungal AgentsComorbidityHumansAntifungal AgentsElectronic health recordsEpidemiologyHematologic malignanciesInvasive mucormycosisReal-world dataZygomycosis

Identifiers

PMID35164701
PMCPMC8845356

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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.