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Mortality Rates Among Hospitalized Patients With COVID-19 Infection Treated With Tocilizumab and Corticosteroids

2022· review· en· W4214709934 on OpenAlexaff
Arthur M. Albuquerque, Lucas Tramujas, Lorenzo R. Sewanan, Donald R. Williams, James M. Brophy

Bibliographic record

VenueJAMA Network Open · 2022
Typereview
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsTocilizumabMedicineInternal medicineOdds ratioRandomized controlled trialConfidence intervalMeta-analysisRheumatoid arthritis

Abstract

fetched live from OpenAlex

Importance: A World Health Organization (WHO) meta-analysis found that tocilizumab was associated with reduced mortality in hospitalized patients with COVID-19. However, uncertainty remains concerning the magnitude of tocilizumab's benefits and whether its association with mortality benefit is similar across respiratory subgroups. Objective: To use bayesian methods to assess the magnitude of mortality benefit associated with tocilizumab and the differences between respiratory support subgroups in hospitalized patients with COVID-19. Design, Setting, and Participants: A bayesian hierarchical reanalysis of the WHO meta-analysis of tocilizumab studies published in 2020 and 2021 was performed. Main results were estimated using weakly informative priors to exert little influence on the observed data. The robustness of these results was evaluated using vague and informative priors. The studies featured in the meta-analysis were randomized clinical tocilizumab trials of hospitalized patients with COVID-19. Only patients receiving corticosteroids were included. Interventions: Usual care plus tocilizumab in comparison with usual care or placebo. Main Outcomes and Measures: All-cause mortality at 28 days after randomization. Results: Among the 5339 patients included in this analysis, most were men, with mean ages between 56 and 66 years. There were 2117 patients receiving simple oxygen only, 2505 receiving noninvasive ventilation (NIV), and 717 receiving invasive mechanical ventilation (IMV) in 15 studies from multiple countries and continents. Assuming weakly informative priors, the overall odds ratios (ORs) for survival were 0.70 (95% credible interval [CrI], 0.50-0.91) for patients receiving simple oxygen only, 0.81 (95% CrI, 0.63-1.03) for patients receiving NIV, and 0.89 (95% CrI, 0.61-1.22) for patients receiving IMV, respectively. The posterior probabilities of any benefit (OR <1) were notably different between patients receiving simple oxygen only (98.9%), NIV (95.5%), and IMV (75.4%). The posterior probabilities of a clinically meaningful association (absolute mortality risk difference >1%) were greater than 95% in patients receiving simple oxygen only and greater than 90% in patients receiving NIV. In contrast, the posterior probability of this clinically meaningful association was only approximately 67% in patients receiving IMV. The probabilities of tocilizumab superiority in the simple oxygen only subgroup compared with the NIV and IMV subgroups were 85% and 90%, respectively. Predictive intervals highlighted that only 72.1% of future tocilizumab IMV studies would show benefit. The conclusions did not change with different prior distributions. Conclusions and Relevance: In this bayesian reanalysis of a previous meta-analysis of 15 studies of hospitalized patients with COVID-19 treated with tocilizumab and corticosteroids, use of simple oxygen only and NIV was associated with a probability of a clinically meaningful mortality benefit from tocilizumab. Future research should clarify whether patients receiving IMV also benefit from tocilizumab.

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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.586
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.002
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 head0.098
GPT teacher head0.450
Teacher spread0.353 · 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 designObservational
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

Citations35
Published2022
Admission routes1
Has abstractyes

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