{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:19:09Z","timestamp":1787026749440,"version":"build-2736575974"},"reference-count":83,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T00:00:00Z","timestamp":1772150400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study design<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data sources<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data synthesis<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Registration<\/jats:title>\n                    <jats:p>A review protocol was not prospectively registered because the review adopted an iterative approach to support priority setting rather than clinical guidance.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2026.1734600","type":"journal-article","created":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T05:24:49Z","timestamp":1772169889000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Candidate treatments for long COVID: a narrative review of expert and patient-driven priorities"],"prefix":"10.3389","volume":"13","author":[{"given":"Shaira Nicole","family":"Baptista","sequence":"first","affiliation":[{"name":"Australian Living Evidence Collaboration, Monash University School of Public Health and Preventive Medicine","place":["Melbourne, VIC, Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tiffany","family":"Atkins","sequence":"additional","affiliation":[{"name":"Bond University Institute for Evidence-Based Healthcare","place":["Robina, QLD, Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samantha","family":"Chakraborty","sequence":"additional","affiliation":[{"name":"Australian Living Evidence Collaboration, Monash University School of Public Health and Preventive Medicine","place":["Melbourne, VIC, Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mina","family":"Bakhit","sequence":"additional","affiliation":[{"name":"Bond University Institute for Evidence-Based 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