Prospective observational pilot study of the T2Resistance panel in the T2Dx system for detection of resistance genes in bacterial bloodstream infections
Bibliographic record
Abstract
ABSTRACT Early initiation of antimicrobial therapy targeting resistant bacterial pathogens causing sepsis and bloodstream infections (BSIs) is critical for a successful outcome. The T2Resistance Panel (T2R) detects the following resistance genes within organisms that commonly cause BSIs directly from patient blood samples: bla KPC , bla CTXM-14/15 , bla NDM /bla /IMP /bla VIM , bla AmpC , bla OXA , vanA , vanB , and mec A/ mec C. We conducted a prospective study in two major medical centers for the detection of circulating resistance genes by T2R in patients with BSIs. T2R reports were compared to antimicrobial susceptibility testing (AST), phenotypic identification, and standard molecular detection assays. Among 59 enrolled patients, 25 resistance genes were identified: bla KPC ( n = 10), bla NDM /bla /IMP /bla VIM ( n = 5), bla CTXM-14/15 ( n = 4), bla AmpC ( n = 2), and mec A/ mec C ( n = 4). Median time-to-positive-T2R in both hospitals was 4.4 hours [interquartile range (IQR): 3.65–4.97 hours] in comparison to that for positive blood cultures with final reporting of AST of 58.34 h (IQR: 45.51–111.2 hours; P < 0.0001). The sensitivity of T2R to detect the following genes in comparison to AST was 100% for bla CTXM-14/15 , bla NDM /bla / IMP /bla VIM , bla AmpC , mec A/ mec C and 87.5% for bla KPC . When monitored for the impact of significant antimicrobial changes, there were 32 events of discontinuation of unnecessary antibiotics and 17 events of escalation of antibiotics, including initiation of ceftazidime/avibactam in six patients in response to positive T2R results for bla KPC . In summary, T2R markers were highly sensitive for the detection of drug resistance genes in patients with bacterial BSIs, when compared with standard molecular resistance detection systems and phenotypic identification assays while significantly reducing by approximately 90% the time to detection of resistance compared to standard methodology and impacting clinical decisions for antimicrobial therapy. IMPORTANCE This is the first reported study to our knowledge to identify key bacterial resistance genes directly from the bloodstream within 3 to 5 hours in patients with bloodstream infections and sepsis. The study further demonstrated a direct effect in modifying initial empirical antibacterial therapy in response to T2R signal to treat resistant bacteria causing bloodstream infections and sepsis.
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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 | 0.002 | 0.001 |
| 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 | 0.000 | 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".