Effect of pharmacological interventions for the treatment of people with post‐COVID‐19 condition: A rapid review
Bibliographic record
Abstract
Abstract Objective Little is known about the treatment of post‐coronavirus disease 2019 (COVID‐19) condition (PCC). This article examines the effectiveness of pharmacological interventions for treating people with PCC. Methods We searched Medline, EMBASE, ClinicalTrials. gov, and the International Clinical Trials Registry Platform. Two independent review authors screened citations, extracted data, and assessed the quality of the included studies. Due to heterogeneity in participants, interventions, and outcomes, we synthesized data narratively. We assessed the certainty of evidence using GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). Participants People with PCC. Interventions Pharmacological interventions include corticosteroids, ivabradine, and inhaled hydrogen. Outcome Measures Olfactory function, sinus tachycardia, respiratory function. Results We identified 5 completed studies and 41 ongoing studies. Oral corticosteroids and olfactory training had higher olfactory scores after 10 weeks (MD: 5.60, 95% confidence interval [CI]: 1.41 to 9.79). Patients allocated oral corticosteroid, and nasal irrigation demonstrated improved recovery of olfactory function compared with the control group at 40 days (median 60, interquartile range [IQR]: 40 vs. median 30, IQR: 25, p = 0.024). Patients allocated to topical corticosteroid nasal spray and olfactory training had improved recovery of olfactory function after 2 weeks (median 7, IQR: 5−10 vs. median 5, IQR: 2−8, p = 0.08). Participants allocated to ivabradine had a greater mean reduction in heart rate compared with participants randomized to carvedilol (MD: −4.24, 95% CI: −10.09 to 1.61). Participants allocated to inhaled hydrogen therapy had an improved vital capacity (MD: 0.20, 95% CI: 0.07 to 0.33), forced expiratory volume (MD: 0.19, 95% CI: 0.04 to 0.34), 6‐minute walk test (MD: 55.0, 95% CI: 36.04 to 73.96). Conclusions The evidence is of low to very low certainty about the effect of all pharmacological interventions investigated for the treatment of people with PCC. There is currently a significant body of research underway that could expand the evidence to inform treatment decisions on pharmacological interventions for PCC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".