Evidence map›Paper›PMID 33988142›Full record

ArticleActa bio-medica : Atenei Parmensis2021

COVID-19 … What are drugs and strategies now?

Valentina Bellini, Andrea Cortegiani, Luigi Vetrugno, Francesco Potì, Francesco Saturno, Michelangelo Craca, Elena Bignami

Abstract readLetter
In one paragraph

Article in Acta bio-medica : Atenei Parmensis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Valentina BelliniAnesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy. bellini.vnt@gmail.com.
Andrea CortegianiDepartment of Surgical, Oncological and Oral Science (Di.Chir.On.S.), University of Palermo. Department of Anesthesia Intensive Care and Emergency, Policlinico Paolo Giaccone, Palermo, Italy. andrea.cortegiani@unipa.it.
Luigi VetrugnoDepartment of Medicine, University of Udine, Italy, Anesthesia and Intensive Care Clinic, Via Colugna n° 50 33100 Udine, Italy; University-Hospital of Udine, Department of Anesthesia and Intensive Care, P.le S. Maria della. Misericordia n° 15 33100 Udine, Italy. luigi.vetrugno@uniud.it.
Francesco PotìDepartment of Medicine and Surgery - Unit of Neurosciences, University of Parma, Parma, Italy. francesco.poti@unipr.it.
Francesco SaturnoAnesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy. francescosat88@gmail.com.
Michelangelo CracaAnesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy. michecraca@gmail.com.
Elena BignamiAnesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy. elenagiovanna.bignami@unipr.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

From February 2019 the World faces the Covid19 pandemic. The data in our possession are still insufficient to effectively combat this pathology. The gold standard for diagnosis remains molecular testing, while clinical and instrumental and serological diagnostics are highly nonspecific leading to a slowdown in the battle against covid19.[3] Can Artificial Intelligence (AI) and Machine Learning (ML) help us? The use of large databases to cross-reference data to stratify the diagnostic scores, to quickly differentiate a critical Covid-19 patient from a non-critical one is the challenge of the future. All to achieve better management of resources in the field and a more effective therapeutic approach.[2].

Indexed as

COVID-19Pharmaceutical PreparationsArtificial IntelligenceHumansPandemicsSARS-CoV-2Pharmaceutical Preparations

Identifiers

PMID33988142
PMCPMC8182577

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

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.