Review3 Biotech2022
COVID-19 associated mucormycosis: evolving technologies for early and rapid diagnosis.
Review in 3 Biotech, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed, 25 citations in OpenAlex.
- Co-Infection of Mucormycosis and COVID-19: A Retrospective Cross-Sectional Study of Patients Admitted to Imam Khomeini Hospital in Ahvaz, Iran.Health science reports · 2025Article
- Nanotechnology-based fungal detection and treatment: current status and future perspective.Naunyn-Schmiedeberg's archives of pharmacology · 2024Review
- Article
- Mucormycosis diagnosis revisited: Current and emerging diagnostic methodologies for the invasive fungal infection (Review).Experimental and therapeutic medicine · 2023Review
- Clinical Phenotypes of COVID-19 Associated Mucormycosis (CAM): A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2022Review
- A case control investigation of COVID-19 associated mucormycosis in India.BMC infectious diseases · 2022Article
- COVID-19-associated disseminated mucormycosis: An autopsy case report.World journal of clinical cases · 2022Article
- COVID-19-Associated Pulmonary Mucormycosis.Journal of fungi (Basel, Switzerland) · 2022Review
- Mucormycosis and COVID-19-Associated Mucormycosis: Insights of a Deadly but Neglected Mycosis.Journal of fungi (Basel, Switzerland) · 2022Review
- Mucormycosis and COVID-19 pandemic: Clinical and diagnostic approach.Journal of infection and public health · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The post-coronavirus disease (COVID-19) mucormycosis is a deadly addition to the pandemic spectrum. Although it's a rare, aggressive, and opportunistic disease, the associated morbidity and mortality are significant. The complex interplay of factors aggravating CAM is uncontrolled diabetes, irrational and excessive use of antibiotics, steroids, and an impaired immune system. Recently, India has been witnessing a rapid surge in the cases of coronavirus disease-associated mucormycosis (CAM), since the second wave of COVID-19. The devastating and lethal implications of CAM had now become a matter of global attention. A delayed diagnosis is often associated with a poor prognosis. Therefore, the rapid and early diagnosis of infection would be life-saving. Prevention and effective management of mucormycosis depend upon its early and accurate diagnosis followed by a multimodal therapeutic approach. The current review summarizes an array of detection methods and highlights certain evolving technologies for early and rapid diagnosis of CAM. Furthermore, several potential management strategies have also been discussed, which would aid in tackling the neglected yet fatal crisis of mucormycosis associated with COVID-19.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.