Evidence map›Paper›PMID 34349362›Full record

ReviewJournal of anaesthesiology, clinical pharmacology

Common anti-COVID-19 drugs and their anticipated interaction with anesthetic agents.

Shagun B Shah, Uma Hariharan, Rajiv Chawla

Abstract readReview
In one paragraph

Review in Journal of anaesthesiology, clinical pharmacology. 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. Combinatorial chemistry & high throughput screening · 2023
    Review
  2. Article
  3. Review
  4. Anti-COVID-19 drugs, COVID-19 and anesthetics - The challenge for anesthesiologists.Journal of anaesthesiology, clinical pharmacology · 2022
    Article
  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

3 authors.

Shagun B ShahRajiv Gandhi Cancer Institute and Research Centre, Sector-5, Rohini, India.
Uma HariharanDr. Ram Manohar Lohia Hospital and PGIMER, CHS, New Delhi, India.
Rajiv ChawlaRajiv Gandhi Cancer Institute and Research Centre, Sector-5, Rohini, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The corona virus disease 2019 (COVID-19) pandemic has till date (26/7/20) affected 1crore 62 lac 73 thousand 638 people globally with almost 6.5 lakh mortalities. COVID-19 has invaded the operation theatre and intensive care unit (ICU) in a short span of 6 months. It appears inevitable that all of us, as anesthesiologists, have to treat COVID-positive patients, either in the ICU or the operation theatre. Many asymptomatic, presumably noninfected people including frontline health care workers are also consuming potential anticorona viral drugs (such as hydroxychloroquine) prophylactically and may present for surgery. Detailed knowledge of which anesthetic and perioperative care drugs can interact with anti-COVID drugs would be very valuable for pre, intra-, and postoperative management of such patients and COVID-19 positive patients requiring intubation, mechanical ventilation, and ICU-sedation. Powered with this knowledge, anesthesiologists and intensivists can minimize the adverse effects of drug interactions. An extensive literature search using different search engines including Cochrane, Embase, Google Scholar, Scopus, and PubMed for all indexed review articles, original articles, case reports, and referenced webpages was performed to extract the most current and relevant literature on drug-drug interactions for clinicians.

Indexed as

Anesthetic drugsazithromycinCOVID-19dexamethasonefavipiravirhydroxychloroquineivermectinnitazoxanideremdesivirritonavirtocilizumab

Identifiers

PMID34349362
PMCPMC8289657

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.