Evidence mapPaperPMID 40622467Full record

ReviewInflammopharmacology2025

Long COVID syndrome: exploring therapies for managing and overcoming persistent symptoms.

Dhrita Chatterjee, Kousik Maparu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Inflammopharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. VSL#3British journal of biomedical science · 2026
    Trial
  2. Review
  3. Review
  4. Article
  5. Therapeutic Potential ofPharmaceuticals (Basel, Switzerland) · 2025
    Article
  6. Article
  7. 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

2 authors.

Dhrita ChatterjeePharmacology Division, Sanaka Education Trusts Group of Institutions, Durgapur, Malandighi, 713212, India.
Kousik MaparuPharmacology Division, Sanaka Education Trusts Group of Institutions, Durgapur, Malandighi, 713212, India. maparukousik@gmail.com.ORCID http://orcid.org/0000-0001-7033-7790

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), is a growing global health concern, affecting 10-35% of COVID-19 survivors. Characterized by persistent multisystem symptoms lasting beyond 12 weeks, common manifestations include fatigue, dyspnea, chest pain, cognitive impairment, depression, and anxiety. The underlying pathophysiology remains unclear but is likely to involve immune dysregulation, persistent inflammation, endothelial dysfunction, gut dysbiosis, and viral persistence. This review examines the epidemiology, risk factors, and clinical manifestations of long COVID, with a focus on its impact on cardiopulmonary, neurological, and mental health. Therapeutic approaches include pharmacological interventions such as anti-inflammatory agents, antioxidants, neuroprotective drugs, and repurposed medications. Non-pharmacological strategies, such as physical rehabilitation, cognitive therapy, dietary modification, and emerging therapies like stem cell therapy, as well as immunomodulatory approaches, offer promising avenues for recovery. We also highlight ongoing clinical trials evaluating targeted therapies for long-term COVID syndrome. Future research should focus on elucidating the pathophysiological mechanisms, identifying biomarkers, and optimizing personalized treatment strategies for long-term COVID-19 management.

Indexed as

COVID-19COVID-19 Drug TreatmentHumansPost-Acute COVID-19 SyndromeRisk FactorsSARS-CoV-2Anti-oxidantsDyspneaGUT dysbiosisImmune dysregulationLong-COVID syndromeSARS-CoV-2Viral persistence

Identifiers

What Socratic 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 Socratic graph.