Mechanistic rationale of drugs, Primary endpoints, Geographical distribution of clinical trials against Severe acute respiratory syndrome-related coronavirus-2: A Systematic review
Notice bibliographique
Résumé
Abstract Objective To do a systematic review and critical appraisal of the ongoing clinical trials that are assessing various therapeutic interventions against SARS-CoV-2 with an aim to provide insight into the various interventions tested, clinical rationale, geographical distribution of the trials as well as the endpoints assessed in the studies. Design Rapid systematic review and critical appraisal of the ongoing clinical trials against SARS-CoV-2. Data sources ClinicalTrials.gov, World health organization (WHO) International Clinical Trials Registry Platform (ICTRP) and Cochrane COVID registry were assessed till May 11 th 2020. Study selection Studies on any intervention based randomized controlled trials (RCTs), prospective clinical studies on SARS-CoV-2 in patients ≥18 years of age. Studies on autopsy series, preclinical studies, diagnostic methods, mathematical modelling, epidemiology and health services research, pediatric populations were excluded. Data extraction The data was extracted by two authors independently into pre-defined forms based on the SPIRIT 2013 checklist. The data was extracted on various domains such as trial number, study title, abstract of the study, interventions assessed, sample size, phase of the study, study sponsor, primary endpoint assessed and country of study. Results The search resulted in 3242 ongoing studies of which 829 studies were included. There are 134 different drug-based interventions being assessed in 463 clinical trials as treatment options. Seventy-two studies assessed preventive options of which 53 are drug-based prophylaxis and 19 assessed vaccines. Herbal medicines are being assessed in 79 studies; convalescent plasma therapy in 56 studies; stem cell-based interventions in 42 studies; anesthesia-based interventions in 31 studies, machine-based interventions in 24 studies, mental health-based interventions in18 studies, rehabilitation-based interventions in 12 studies and miscellaneous interventions in 32 studies. China accounts for 35% of all ongoing clinical studies followed by USA 23%, France 7%, Spain 3.3%,Canada 2%, multi-country studies account only for 1.5% (13) and other countries together account for 28%.Amongst the 463 studies assessing drug-based treatment options, studies that are funded by federal and academic institutions are 79.6%, pharmaceutical company funded studies are 15.11% and no funding information is available in 5.10%. The definitive outcomes like mortality are being assessed as primary outcome in 22.8% of the studies only and need for ventilator in 6.2% of the studies. Rest of the studies has primary outcomes such as clinical recovery (15.9%), viral clearance(17.4%), time to recovery (10.1%), oxygen improvement (5.6%), ICU admission (1.9%), lab and imaging(6.4%), adverse effects (5.3%) and symptom reduction(1.5%),no outcome reported(6.2%) which account for 71% of the studies. Amongst the pharmaceutical company funded drug-based studies, only 20% of the studies had mortality as the primary outcome. Only 5.5% of the ongoing clinical trials are specifically designed to assess the most vulnerable population like elderly, patients with comorbidities and cancer. The most common intervention being tested against COVID-19 are antimalarial medications with 105 clinical studies. Hydroxychloroquine is the most common drug being tested with 83 ongoing studies. Conclusion Multiple intervention based clinical studies against SARS-CoV-2 are being performed throughout the world with a high concentration of clinical trials in the developed world. There is a high concern that most of the studies maybe repetitive; elderly and patients with comorbidities are being underrepresented; definite endpoints like mortality are being assessed in only one-fifth of the studies.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,035 | 0,137 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,017 | 0,015 |
| Bibliométrie | 0,015 | 0,013 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».