Evidence map›Paper›PMID 39897928›Full record

ReviewHeliyon2025

SARS-CoV-2 drug resistance and therapeutic approaches.

Sania Batool, Santosh Chokkakula, Ju Hwan Jeong, Yun Hee Baek, Min-Suk Song

Abstract readReview
In one paragraph

Review in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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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

5 authors.

Sania BatoolDepartment of Microbiology, Chungbuk National University, College of Medicine and Medical Research Institute, Cheongju 28644, Chungbuk, Republic of Korea.
Santosh ChokkakulaDepartment of Microbiology, Chungbuk National University, College of Medicine and Medical Research Institute, Cheongju 28644, Chungbuk, Republic of Korea.
Ju Hwan JeongDepartment of Microbiology, Chungbuk National University, College of Medicine and Medical Research Institute, Cheongju 28644, Chungbuk, Republic of Korea.
Yun Hee BaekDepartment of Microbiology, Chungbuk National University, College of Medicine and Medical Research Institute, Cheongju 28644, Chungbuk, Republic of Korea.
Min-Suk SongDepartment of Microbiology, Chungbuk National University, College of Medicine and Medical Research Institute, Cheongju 28644, Chungbuk, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In light of the transition of COVID-19 from a pandemic to an endemic phase, there is still a dire need to address challenges associated with drug resistance, particularly among immunocompromised and high-risk populations. This review explores the current state of research on SARS-CoV-2 drug resistance and underscores the ongoing need for effective therapeutic strategies. It critically evaluates existing knowledge on resistance mechanisms and therapeutic options, aiming to consolidate information and highlight areas for future research. By examining the complex interactions between the virus and its host, the review advocates for a multifaceted approach, including combination therapies, targeted drug development, and continuous surveillance of viral mutations. It also emphasizes the impact of evolving viral variants on antiviral efficacy and suggests adaptive treatment protocols. This review aims to enhance our understanding of SARS-CoV-2 drug resistance and contribute to more effective management of COVID-19 through a discussion of promising strategies such as drug repurposing and combination therapies.

Indexed as

Antiviral drugsDrug resistanceResistance mechanismSARS-CoV-2Therapeutic strategies

Identifiers

PMID39897928
PMCPMC11786845

What OpenQuestion holds

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LicenceCC BY
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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.