ReviewFrontiers in medicine2026
Candidate treatments for long COVID: a narrative review of expert and patient-driven priorities.
Review in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- The Post-COVID syndrome caused by excessive inflammation: pathogenesis, potential targets and therapeutic agents.Frontiers in pharmacology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To map the existing evidence for candidate treatments for long COVID that were prioritised by clinicians and people with lived experience, and to characterise their feasibility, acceptability and safety. Study design: The study was conducted as a narrative review using pragmatic methods including iterative stakeholder-informed decision-making a monthly-updated evidence search, rapid lay evidence summaries and a structured research prioritisation process. Data sources: Potential candidate treatments were identified via a combination of database and trial registry searches. These were then ranked by clinicians and people with lived experience using surveys. Evidence summaries for the top 14 interventions (low-dose naltrexone, antivirals, metformin, nicotine, vagus nerve stimulation, antihistamines, guanfacine, colchicine, nattokinase, intravenous immunoglobulins, monoclonal antibodies, coenzyme Q10, multicomponent rehabilitation packages, and exercise training) were created. Prioritised treatments were collated first by searching a collaborative living evidence database (updated monthly) of relevant systematic reviews and randomised controlled trials and then by conducting supplementary searches of other study designs. Data synthesis: Six of 14 interventions had long-COVID-specific randomised controlled trial (RCT) evidence (exercise [16 RCTs], multicomponent packages [5 RCTs], coenzyme Q10 [2 RCTs], antivirals [1 RCT], vagus nerve stimulation [1 pilot RCT], monoclonal antibodies [1 small RCT]); the remainder relied on indirect or very low-certainty data (e.g., uncontrolled studies or mechanistic rationale). Across interventions, evidence certainty was mostly low to very low, and safety/feasibility varied. Conclusion: This review prioritises and maps candidate treatments for long COVID. There was insufficient direct evidence to inform clinical recommendations. Rather, the treatments presented in this review represent those that could be rigorously tested in clinical trials as they show biological plausibility and/or are feasible and acceptable to people with lived experience and clinicians. Registration: A review protocol was not prospectively registered because the review adopted an iterative approach to support priority setting rather than clinical guidance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.