Preventive interventions for post Covid-19 condition: systematic review update
Bibliographic record
Abstract
ABSTRACT Background Post COVID-19 condition (PCC) can affect individuals regardless of the severity of their initial illness, and its impact on daily life can be significant. There are uncertainties about whether treatments in the acute or post-acute phase of infection can prevent PCC. We report an update to a previous systematic review on the effects of interventions to prevent PCC. Methods We updated our previous peer-reviewed searches on February 9, 2024. We searched bibliographic databases and grey literature resources to identify trials and comparative observational studies reporting on any intervention provided during the acute (symptom onset to 4 weeks) or post-acute phase (4-8 weeks) of COVID-19 and our primary outcome of incidence of PCC, ascertained at 3 months or longer following infection and capturing, at a minimum, symptoms of fatigue, dyspnea and one or more aspects of cognitive function. Non-recovery from COVID-19 was included if necessary. Secondary outcomes included fatigue, breathlessness/dyspnea, post-exertional malaise, health-related quality of life, psychopathology, cognitive impairment, hospitalization, return to work/education, and adverse effects of the intervention. For screening we employed artificial intelligence to prioritize records and modified our methods to rely on single-reviewer screening after 50% of citations were screened in duplicate. Study selection and risk of bias assessments were conducted independently by two reviewers and data extraction relied on verification of another reviewer’s work. We grouped studies by intervention type and timing, and by acute-care setting, and performed meta-analysis where appropriate. Sensitivity analyses were conducted for the primary outcome, excluding studies with high risk of bias, using non-recovery as a proxy outcome, and evaluating the outcome at more than 12 months of follow-up. We assessed the certainty of evidence using GRADE. Results Twenty-four studies (5 randomized and 19 non-randomized), all among adults, were included. The acute care setting in nine studies was outpatient and in 15 studies was in-patient; all but one intervention was administered during the acute-phase of illness. The use of convalescent plasma in outpatient acute COVID-19 care probably does not reduce the risk of PCC (relative risk [RR]: 0.93, 95% CI: 0.77-1.12; 1 RCT; moderate certainty). There was low-certainty evidence suggesting that probiotics (RR [95% CI]: 0.32 [0.13-0.78]; 1 RCT) and metformin (0.50 [0.25-0.99]; 1 RCT among individuals with a BMI ≥25 kg/m 2 ) reduce PCC to a small-to-moderate extent in outpatients, while ivermectin (outpatients), antivirals (outpatients), steroids (in-patients), and therapeutic-dose heparin (vs. prophylactic dose; in-patients) may not be effective. Evidence was very low certainty for several other acute-phase pharmacologic intervention and post-acute outpatient assessment and referrals. For outpatient antiviral treatment, while overall PCC risk may not decrease, there might be a slight reduction in psychopathology. Similarly, inpatient antiviral use may not prevent PCC but may offer a small reduction in prolonged general malaise after light exertion. Therapeutic-dose heparin may slightly reduce the risk of cognitive impairment compared to prophylactic-dose heparin among in-patients. The findings remained consistent across all these sensitivity analyses. Conclusions Evidence suggests that PCC can be prevented to some extent among outpatients with the use of probiotics and metformin during the acute phase of COVID-19. Effects from interventions used among in-patients and within the post-acute phase are uncertain at this time. Evidence on commonly recommended interventions including rehabilitation or multidisciplinary care was lacking. Protocol registration CRD42024513247
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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 | 0.012 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".