Infectious Diseases Society of America Guidelines on the Treatment and Management of Patients With COVID-19 (September 2022)
Bibliographic record
Abstract
There are many pharmacologic therapies that are being used or considered for treatment of coronavirus disease 2019 (COVID-19), with rapidly changing efficacy and safety evidence from trials. The objective was to develop evidence-based, rapid, living guidelines intended to support patients, clinicians, and other healthcare professionals in their decisions about treatment and management of patients with COVID-19. In March 2020, the Infectious Diseases Society of America (IDSA) formed a multidisciplinary guideline panel of infectious disease clinicians, pharmacists, and methodologists with varied areas of expertise to regularly review the evidence and make recommendations about the treatment and management of persons with COVID-19. The process used a living guideline approach and followed a rapid recommendation development checklist. The panel prioritized questions and outcomes. A systematic review of the peer-reviewed and grey literature was conducted at regular intervals. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was used to assess the certainty of evidence and make recommendations. Based on the most recent search conducted on 31 May 2022, the IDSA guideline panel has made 32 recommendations for the treatment and management of the following groups/populations: pre- and postexposure prophylaxis, ambulatory with mild-to-moderate disease, and hospitalized with mild-to-moderate, severe but not critical, and critical disease. As these are living guidelines, the most recent recommendations can be found online at: https://idsociety.org/COVID19guidelines. At the inception of its work, the panel has expressed the overarching goal that patients be recruited into ongoing trials. Since then, many trials were conducted that provided much-needed evidence for COVID-19 therapies. There still remain many unanswered questions as the pandemic evolved, which we hope future trials can answer.
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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 | 0.011 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 0.017 |
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".