404. Surveillance of <i>Clostridioides difficile</i> Burden in Hospitals Through Wastewater Analysis
Bibliographic record
Abstract
Abstract Background New tools capable of dynamic assessment of the varying burden of Clostridioides difficile infections are required to mitigate increased patient morbidity, mortality, and health costs. Wastewater (WW)-based epidemiology (WBE) is an emerging science, enabling comprehensive, inclusive, and unbiased assessment of populations, spatially and temporally. We sought to detect, quantify and track C. difficile across a range of scales using WBE. Methods WW collected from two hospitals; the Rockyview General Hospital (RGH; 600 beds) and Peter Lougheed Centre (PLC; 550 beds) both based in Calgary, were compared to that from a municipal WW Treatment Plant (WWTP) in Calgary, Canada. DNA was extracted from pellets collected after WW centrifugation. A multiplexed quantitative PCR assay was used to quantify the abundance of C. difficile 16S rRNA and toxin A (tcdA) genes. These were then assessed as raw values or as normalized ratios to three fecal biomarker genes: total bacterial 16S rRNA, human 18S rRNA, and Bacteroides HF183 16S rRNA. Kruskal-Wallis and Mann-Whitney tests were performed using RStudio and GraphPad Prism (version 9.3.1). Results Eight weekly samples collected from the RGH demonstrated significant changes in the levels of total C. difficile 16S rRNA gene and tcdA over time (P=0.0004 and P=0.0005, respectively, Kruskal-Wallis). Similar trends in total C. difficile and tcdA burden over time were observed when gene copies were normalized with the three fecal biomarker genes. Over a separate 13-week comparison, C. difficile and tcdA gene target abundance was greater in hospital WW (RGH and PLC) than in community-based samples from the WWTP (P=0.048 and P=0.012, respectively, Mann-Whitney). There was no significant difference in C. difficile and tcdA gene target abundance between RGH and PLC (P=0.896 and P=0.343, respectively, Mann-Whitney). Clostridioides difficile genes in wastewater measured by quantitative PCR. C. difficile 16S rRNA and tcdA gene abundance normalized as a ratio against total bacterial load (16S rRNA) varies over time and is markedly increased in hospitals relative to a municipal wastewater treatment plant in Calgary, Canada. Conclusion WW surveillance is a powerful tool that can monitor the burden the C. difficile across a range of scales in real-time. This tool could augment infection prevention and control and antimicrobial stewardship programs to better understand factors that contribute to colonization and infection. Disclosures Thomas J. Louie, MD, Artugen: Advisor/Consultant|Artugen: Grant/Research Support|Crestone: Advisor/Consultant|Crestone: Grant/Research Support|Finch Therapeutics: Advisor/Consultant|Finch Therapeutics: Grant/Research Support|Rebiotix: Advisor/Consultant|Rebiotix: Grant/Research Support|Seres Therapeutics: Advisor/Consultant|Seres Therapeutics: Grant/Research Support|summit plc: Advisor/Consultant|summit plc: Grant/Research Support|Vedanta Biosciences: Advisor/Consultant|Vedanta Biosciences: Grant/Research Support.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".