Clostridium ramosum Bacteremia in an Immunocompetent Patient with SARS-CoV-2 Infection: A Case Report
Bibliographic record
Abstract
Danni Bao,1 Xiaohong Xu,1 Yizhang Wang,1 Fengjiao Zhu,1 Yanhong Wu,1 Hongzhang Li2 1Department of Clinical Laboratory, Sanmen Peopleâs Hospital, Taizhou, Zhejiang, Peopleâs Republic of China; 2Department of Gastroenterology, Sanmen Peopleâs Hospital, Taizhou, Zhejiang, Peopleâs Republic of ChinaCorrespondence: Hongzhang Li, Department of Gastroenterology, Sanmen Peopleâs Hospital, Taizhou, Zhejiang, Peopleâs Republic of China, Email lihongzhang@zjsmyy.comAbstract: We report a case of Clostridium ramosum bacteremia in a 73-year-old patient with SARS-CoV-2 infection and right lower abdominal tenderness in China. The microbiological features and genomic epidemiological characteristics of C. ramosum worldwide were investigated to identify the possible sources of infection. Whole-genome sequencing of C. ramosum WD-I2 was performed using an Illumina NovaSeq 6000 platform. Phylogenetic analysis of C. ramosum WD-I2 and other publicly available C. ramosum isolates was performed and visualized using the interactive Tree of Life (iTOL) web server. The resistome of C. ramosum WD-I2 consists of two antimicrobial resistance genes (tetM and ermB), which explains the antimicrobial resistance trait to tetracycline and macrolides. Phylogenetic analysis showed that the strain closest to our isolated strain WD-I2 was SUG1069, recovered from a pig feces sample from Canada, which differed by 589 SNPs. To our knowledge, this is the first report of C. ramosum bacteremia in China. Our findings highlight the potential risk of invasive C. ramosum infections during the COVID-19 pandemic.Keywords: Clostridium ramosum, bacteremia, antimicrobial resistance, SARS-CoV-2, whole genome sequencing
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".