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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".