Quality of life and <scp>cost‐effectiveness</scp> of convalescent plasma compared to standard care for hospitalized <scp>COVID</scp>‐19 patients in the <scp>CONCOR</scp>‐1 trial
Bibliographic record
Abstract
BACKGROUND: The CONvalescent Plasma for Hospitalized Adults With COVID-19 Respiratory Illness (CONCOR-1) trial was a multicenter randomized controlled trial assessing convalescent plasma in hospitalized COVID-19 patients. This study evaluates the cost-effectiveness of convalescent plasma and its impact on quality-of-life to provide insight into its potential as an alternative treatment in resource-constrained settings. METHODS: Individual patient data on health outcomes and resource utilization from the CONCOR-1 trial were used to conduct the analysis from the Canadian public payer's perspective with a time horizon of 30 days post-randomization. Baseline and 30-day EQ-5D-5L were measured to calculate quality-adjusted survival. All costs are presented in 2021 Canadian dollars. The base case assessed the EQ-5D-5L scores of hospitalized inpatients reporting at both timepoints, and a utility score of 0 was assigned for patients who died within 30 days. Costs for all patients enrolled were used. The sensitivity analysis utilizes EQ-5D-5L scores from the same population but only uses costs from this population. RESULTS: 940 patients were randomized: 627 received CCP and 313 received standard care. The total costs were $28,716 (standard deviation, $25,380) and $24,258 ($22,939) for the convalescent plasma and standard care arms respectively. EQ-5D-5L scores were 0.61 in both arms (p = .85) at baseline. At 30 days, EQ-5D-5L scores were 0.63 and 0.64 for patients in the convalescent plasma and standard care arms, respectively (p = .46). The incremental cost was $4458 and the incremental quality-adjusted life day was -0.078. DISCUSSION: Convalescent plasma was less effective and more costly than standard care in treating hospitalized COVID-19.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".