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Adherence of Clinical Practice Guidelines for Pharmacologic Treatments of Hospitalized Patients With COVID-19 to Trustworthy Standards

2021· review· en· W4200224094 on OpenAlexaff
Karen E. A. Burns, Matthew Laird, James M. Stevenson, Kimia Honarmand, David Granton, Michelle E. Kho, Jan O. Friedrich, Maureen O. Meade, Mark Duffett, Dipayan Chaudhuri, Kuan Liu, Frédérick D’Aragon, Arnav Agarwal, Neill K. J. Adhikari, Hayle Noh, Bram Rochwerg, David Lightfoot, Karen Choong, Andrea Lucas, Joanna C. Dionne, Colungo Lozano, Erick Duan, Emilie P. Belley‐Côté, Melissa Parker, John Basmaji, Vincent Lau, Samantha Arora

Bibliographic record

VenueJAMA Network Open · 2021
Typereview
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsHealth Sciences CentreSt. Michael's HospitalSunnybrook Health Science CentrePublic Health OntarioSt. Joseph’s Healthcare HamiltonUniversity of TorontoUniversité de SherbrookeWestern UniversityImpactLondon Health Sciences CentreMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsGuidelineMedicineMEDLINEFamily medicineGovernment (linguistics)Evidence-based medicineClinical trialScientific evidencePandemicAlternative medicineCoronavirus disease 2019 (COVID-19)DiseaseInternal medicinePolitical sciencePathology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.165
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.731
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.165
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.611
GPT teacher head0.684
Teacher spread0.073 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations9
Published2021
Admission routes1
Has abstractyes

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