Early and out‐of‐hospital use of COVID‐19 convalescent plasma: An international assessment of utilization and feasibility
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The use of coronavirus disease 2019 (COVID-19) convalescent plasma (CCP) in the treatment of patients with severe acute respiratory syndrome-2 infection has been controversial. Early administration of CCP before hospital admission offers a potential advantage. This manuscript summarizes current trials of early use of CCP and explores the feasibility of this approach in different countries. MATERIALS AND METHODS: A questionnaire was distributed to the International Society of Blood Transfusion (ISBT) CCP working group. We recorded respondents' input on existing trials on early/outpatient CCP and out-of-hospital (OOH)/home transfusion (HT) practices in their countries and feedback on challenges in initiating home CCP infusion programmes. In addition, details of existing trials registered on clinicaltrials.gov were summarized. RESULTS: A total of 31 country representatives participated. Early/OOH CCP transfusion studies were reported in the United States, the Netherlands, Spain and Brazil. There were a total of six published and five ongoing trials on the prophylactic and therapeutic early use of CCP. HT was practised in Australia, the UK, Belgium, France, Japan, Nigeria, the Netherlands, Spain, Italy, Norway, the United States and some provinces in Canada. Thirty-four representatives indicated a lack of OOH CCP or HT in their institutions and countries. Barriers to implementation of OOH/HT included existing legislation, lack of policies pertaining to outpatient transfusion, and associated logistical challenges, including lack of staffing and resources. CONCLUSION: Early administration of CCP remains a potential option in COVID-19 management in countries with existing OOH/HT programmes. Legislation and regulatory bodies should consider OOH/HT practice for transfusion in future pandemics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".