Bacterial culture of platelets with large volume delayed sampling

We read with interest the article by Delage and Bernier entitled, “Bacterial culture of platelets with the large volume delayed sampling approach: a narrative review” (1). The final paragraph of the review discusses a study that compared the bacterial risk control strategies that employ testing using a simulation approach (2). The simulation study started with the conditional probability that all platelet components were contaminated with bacteria. Delage and Bernier were correct that a range of plausible lag and doubling times were included in the study, and these were weighted equally because we felt there was no synthesized information available at the time to demonstrate otherwise. We wish to clarify, however, their statement about the bacterial inoculum sizes used in our simulation study. It was stated that a single starting inoculum size of 10 colony forming units (CFUs) was used for our study. While we presented summary results for the 10 CFU inoculum size simulation scenarios for simplicity due to the large amounts of data generated by our analysis, we actually evaluated a range of inoculum sizes (1–60 CFU) as stated in the methods section of the paper. These bacterial contamination scenarios and probabilities of exposure can be viewed in the supplemental materials. We made the results of all scenarios available in the supplemental materials so that other authors could evaluate scenarios of interest. When using 60 CFU inoculum sizes, our results did not change.

Recently, we were able to update the practical range of doubling times for the simulation because we performed a meta-analysis of bacterial growth characteristics reported in the literature (3). This allowed us to narrow the doubling time range. We did not revise the lag time range because lag times in published studies generally used inoculum sizes that are likely much larger than what occurs in the real world. These larger inoculum sizes would be expected to artificially shorten lag times. The overall findings and conclusions of the simulation with revised inputs did not change. Additionally, we have also rerun the analysis using the 77 CFU inoculum size noted by the authors (Table 1) (4). Again, the overall findings did not change.

The authors also cited a publication that reported growth characteristics of Staphylococcus epidermidis where the inoculum size was 10–20 CFU, which was included in the aforementioned meta-analysis (5). This single study involving a single bacterial species had a sample size of 20 and found 75% of lag times were 1–2 days, while 25% were 2–3 days. The authors suggest that perhaps our simulation analysis should not have weighted lag times equally based on these data. However, we also published a meta-analysis quantifying residual bacterial detection rates after initial cultures of platelet components (6). We found the sensitivity of initial culture was just 31%. While many of the included studies performed culture before 48 hours, three studies performed culture on day two (day zero = day of collection) (7-9). The reported sensitivities of day two culture were 21%, 50%, and 100%, respectively. Removing Cutibacterium acnes, which is of debated clinical significance, these sensitivities become 41%, 50%, and 100%, respectively. Of note, the study with 100% sensitivity had the smallest sample size at 2,397 platelet components tested. Based on these studies assessing bacterial contamination detected at issue/outdate, we have not elected to revise the contamination scenarios in the simulation analysis at this time.

We appreciate that 48-hour large-volume delayed sampling (LVDS) enhances the detection rate and ability to interdict contaminated platelet components relative to 24-hour primary culture. For bacteria that do not have shorter lag times, risk of false negative culture results along with longer storage periods of 7 days may confer a higher risk versus other strategies outlined in the updated Food and Drug Administration (FDA) guidance. Passive surveillance can miss septic transfusion reaction events and active surveillance approaches could help clarify this question if sample sizes are sufficient to obtain estimates given low overall event rates (10). Alternatively, spiking studies with practical inoculum sizes and adequate sample sizes with a diversity of bacterial species could be used to compare different testing strategies.

Acknowledgments

Funding: None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Annals of Blood. The article did not undergo external peer review.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://aob.amegroups.com/article/view/10.21037/aob-23-53/coif). R.A.M. serves as an unpaid editorial board member of Annals of Blood from September 2023 to August 2025. R.A.M. reports having received speaker’s honoraria from Cerus Corporation (manufacturer of pathogen reduction technology) for about three lectures covering his research on risks associated with bacterial contamination of platelet components. Most recent honorarium was about two years ago. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

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