Evidence map›Paper›PMID 25343038›Full record

ReviewF1000prime reports2014

Epidemiology of invasive fungal diseases on the basis of autopsy reports.

María Cecilia Dignani

Abstract readReview
In one paragraph

Review in F1000prime reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Focusing COVID-19-associated mucormycosis: a major threat to immunocompromised COVID-19.Environmental science and pollution research international · 2023
    Review
  10. Review
  11. Review
  12. Economic Burden of Fungal Diseases in the United States.Open forum infectious diseases · 2022
    Article
  13. Article
  14. Review
  15. Article
  16. Characteristics of Invasive Pulmonary Fungal Diseases Diagnosed by Pathological Examination.The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2021
    Article
  17. Article
  18. Article
  19. Article
  20. 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

1 author.

María Cecilia DignaniRegistro de Micosis Invasoras REMIIN (Invasive Mycoses' Registry) Yerbal 315 App 2B, 1405, Buenos Aires Argentina ; Argentinean Society of Infectious Diseases Av. De Mayo 1370, Floor 11th, Of. 300, 1085, Buenos Aires Argentina ; Italian Hospital of Mendoza East Access 1070, San José, 5519, Mendoza Argentina.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invasive fungal diseases (IFDs) are a major cause of morbidity and mortality among immunocompromised patients and cost to health services. They are difficult to prevent, diagnose, and treat. This difficulty in diagnosis leads us to treat them empirically by using several tools, including epidemiological data, non-culture methods and images. Most of the available epidemiological information may not be accurate because we are dealing with a disease that only has an estimated 50% chance of being diagnosed before death. Therefore, autopsy reports become a valuable tool, not only to define the real epidemiology, but also to address the trend in pre-mortem diagnosis, which is the best marker available to prove the efficiency of the research in IFD. This article reviews and analyzes the data on IFD obtained from 11 single-center, multi-center and nationwide autopsy reports published between 2008 and 2013, and also discusses the issues we need to address in order to improve the quality of the epidemiological data on invasive fungal disease obtained from autopsy reports.

Identifiers

PMID25343038
PMCPMC4166943

What OpenQuestion holds

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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.