Mechanistic rationale of drugs, Primary endpoints, Geographical distribution of clinical trials against Severe acute respiratory syndrome-related coronavirus-2: A Systematic review
Bibliographic record
Abstract
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.
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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 | 0.035 | 0.137 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.015 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".