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Enregistrement W3081877184 · doi:10.1001/jama.2020.17022

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19

2020· article· en· W3081877184 sur OpenAlexafffund
Derek C. Angus, Lennie Derde, Farah Al-Beidh, Djillali Annane, Yaseen M. Arabi, Abi Beane, Wilma van Bentum-Puijk, Lindsay R. Berry, Zahra Bhimani, Marc J. M. Bonten, Charlotte Bradbury, Frank Brunkhorst, Meredith Buxton, Adrian Buzgau, Allen Cheng, Menno D. de Jong, Michelle A. Detry, Lise J Estcourt, Mark Fitzgerald, Herman Goossens, Cameron Green, Rashan Haniffa, Alisa M. Higgins, Christopher M. Horvat, Sebastiaan Hullegie, Peter Krüger, François Lamontagne, Patrick R. Lawler, Kelsey Linstrum, Edward Litton, Elizabeth Lorenzi, John Marshall, Daniel F. McAuley, Anna McGlothin, Shay McGuinness, Bryan J. McVerry, Stephanie A. Montgomery, Paul Mouncey, Srinivas Murthy, Alistair Nichol, Rachael Parke, Kathy Rowan, Ashish Sanil, Marlene Santos, Christina Saunders, Christopher Seymour, Anne Turner, Frank L. van de Veerdonk, Balasubramanian Venkatesh, Ryan Zarychanski, Scott Berry, Roger Lewis, Colin McArthur, Steven A. Webb, Anthony Gordon

Notice bibliographique

RevueJAMA · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueAdrenal Hormones and Disorders
Établissements canadiensUniversity of ManitobaUniversity Health NetworkUniversity of TorontoUniversity of British ColumbiaUniversité de SherbrookeSt. Michael's Hospital
Organismes subventionnairesNational Heart, Lung, and Blood InstituteNIHR Imperial Biomedical Research CentreHealth Research Council of New ZealandNational Health and Medical Research CouncilMedical Research CouncilKing Saud bin Abdulaziz University for Health ScienceUniversiteit van AmsterdamUniversité de Versailles Saint-Quentin-en-YvelinesRadboud Universitair Medisch CentrumCenter for Sepsis Control and CareQueen's UniversityRadboud UniversiteitNational Institute of General Medical SciencesMonash UniversityGeorge Institute for Global HealthUniversité de SherbrookeImperial College Healthcare NHS TrustUniversity College DublinUniversity of BristolQueen's University BelfastImperial College LondonKing Abdullah International Medical Research CenterEuropean CommissionUniversity of PittsburghBreast Cancer Research FoundationUniversitätsklinikum JenaFP7 HealthUniversity of TorontoMinderoo FoundationUniversity of OxfordNHS Blood and TransplantNational Institute for Health and Care Research
Mots-clésMedicineRandomized controlled trialIntensive care unitOdds ratioHydrocortisoneCorticosteroidShock (circulatory)Intensive careInternal medicineClinical endpointPsychological interventionIntensive care medicine

Résumé

récupéré en direct d'OpenAlex

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,022

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,280
Écart entre enseignants0,267 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeEssai randomisé
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations884
Publié2020
Routes d'admission2
Résumé présentoui

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