Evidence map›Paper›PMID 33254502›Full record

ArticleMedical hypotheses2020

The AI-discovered aetiology of COVID-19 and rationale of the irinotecan+ etoposide combination therapy for critically ill COVID-19 patients.

Bragi Lovetrue

Open access · hybridAbstract read
In one paragraph

Article in Medical hypotheses, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
0.6field-weighted citation impact, top 20% 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

18 citing papers in PubMed, 31 citations in OpenAlex.

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  17. Repurposing FDA-approved drugs to fight COVID-19 usingInformatics in medicine unlocked · 2021
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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

1 author at 1 institution in 1 country.

Bragi LovetrueDemiurge Technologies AG, Baarerstrasse 14, ZUG, 6300 Zug, Switzerland. Electronic address: bragi@demiurge.ch.
Biogen (Switzerland) · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present the AI-discovered aetiology of COVID-19, based on a precise disease model of COVID-19 built under five weeks that best matches the epidemiological characteristics, transmission dynamics, clinical features, and biological properties of COVID-19 and consistently explains the rapidly expanding COVID-19 literature. We present that SARS-CoV-2 implements a unique unbiased survival strategy of balancing viral replication with viral spread by increasing its dependence on (i) ACE2-expressing cells for viral entry and spread, (ii) PI3K signaling in ACE2-expressing cells for viral replication and egress, and (iii) viral- non-structural-and-accessory-protein-dependent immunomodulation to balance viral spread and viral replication. We further propose the combination of irinotecan (an in-market topoisomerase I inhibitor) and etoposide (an in-market topoisomerase II inhibitor) could potentially be an exceptionally effective treatment to protect critically ill patients from death caused by COVID-19-specific cytokine storms triggered by sepsis, ARDS, and other fatal comorbidities.

Indexed as

COVID-19 Drug TreatmentComorbidityCOVID-19Critical IllnessDisease OutbreaksDisease ProgressionDrug DiscoveryDrug Therapy, CombinationEtoposideHumansIrinotecanSARS-CoV-2SepsisSignal TransductionTopoisomerase II InhibitorsTopoisomerase I InhibitorsEtoposideIrinotecanTopoisomerase II InhibitorsTopoisomerase I InhibitorsACE2AetiologyCOVID-19Cytokine stormEtoposideICUIrinotecanSARS-CoV-2Treatment

Identifiers

PMID33254502
PMCPMC7428675
OpenAlexW3012767430

What OpenQuestion holds

Textmetadata
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.