Impacts of <scp>COVID</scp>‐19 and elective surgery cancellations on platelet supply and utilization in the Canadian Province of British Columbia
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic raised concerns about the vulnerability of platelet supply and the uncertain impact of the resumption of elective surgery on utilization. We report the impact of COVID-19 on platelet supply and utilization across a large, integrated healthcare system in the Canadian province of British Columbia (BC). MATERIALS AND METHODS: Historical platelet use in BC by indication was compiled for fiscal year 2010/2011-2019/2020. Platelet collections, initial daily inventory and disposition data were assessed pre-COVID-19 (1 April 2018-15 March 2020) and for two COVID-19 time periods in BC: a shutdown phase with elective surgeries halted (16 March-17 May, 2020) and a renewal phase when elective surgeries resumed (18 May-27 September 2020); comparisons were made provincially and for individual health authorities. RESULTS: Historically, elective surgeries accounted for 10% of platelets transfused in BC. Initial daily supplier inventory increased from baseline during both COVID-19 periods (93/90 units vs. 75 units pre-COVID-19). During the shutdown phase, platelet utilization decreased 10.4% (41 units/week; p < 0.0001), and remained significantly decreased during the ensuing renewal period. Decreased platelet utilization was attributed to fewer transfusions during the shutdown phase followed by a decreased discard/expiry rate during the renewal phase compared to pre-COVID-19 (15.2% vs. 18.9% pre-COVID-19; p < 0.0001). Differences in COVID-19 platelet utilization patterns were noted between health authorities. CONCLUSION: Decreased platelet utilization was observed in BC compared to pre-COVID-19, likely due to a transient reduction in elective surgery as well as practice and policy changes triggered by pandemic concerns.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".