Adherence of Clinical Practice Guidelines for Pharmacologic Treatments of Hospitalized Patients With COVID-19 to Trustworthy Standards
Bibliographic record
Abstract
Importance: The COVID-19 pandemic created the need for rapid and urgent guidance for clinicians to manage COVID-19 among patients and prevent transmission. Objective: To appraise the quality of clinical practice guidelines (CPGs) using the National Academy of Medicine (NAM) criteria. Evidence Review: A search of MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials to December 14, 2020, and a search of related articles to February 28, 2021, that included CPGs developed by societies or by government or nongovernment organizations that reported pharmacologic treatments of hospitalized patients with COVID-19. Teams of 2 reviewers independently abstracted data and assessed CPG quality using the 15-item National Guideline Clearinghouse Extent of Adherence to Trustworthy Standards (NEATS) instrument. Findings: Thirty-two CPGs were included in the review. Of these, 25 (78.1%) were developed by professional societies and emanated from a single World Health Organization (WHO) region. Overall, the CPGs were of low quality. Only 7 CPGs (21.9%) reported funding sources, and 12 (37.5%) reported conflicts of interest. Only 5 CPGs (15.6%) included a methodologist, described a search strategy or study selection process, or synthesized the evidence. Although 14 CPGs (43.8%) made recommendations or suggestions for or against treatments, they infrequently rated confidence in the quality of the evidence (6 of 32 [18.8%]), described potential benefits and harms (6 of 32 [18.8%]), or graded the strength of the recommendations (5 of 32 [15.6%]). External review, patient or public perspectives, or a process for updating were rare. High-quality CPGs included a methodologist and multidisciplinary collaborations involving investigators from 2 or more WHO regions. Conclusions and Relevance: In this review, few COVID-19 CPGs met NAM standards for trustworthy guidelines. Approaches that prioritize engagement of a methodologist and multidisciplinary collaborators from at least 2 WHO regions may lead to the production of fewer, high-quality CPGs that are poised for updates as new evidence emerges. Trial Registration: PROSPERO Identifier: CRD42021245239.
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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 | 0.329 | 0.803 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".