Clinical validation of loop-mediated isothermal amplification for the detection of <i>Escherichia coli</i> sequence type complex 131
Bibliographic record
Abstract
ABSTRACT The dissemination of Escherichia coli multidrug-resistant (MDR) STc131 is related to its persistence in the human gastrointestinal tract as efficient gut colonizers. Infection and prevention measures are the cornerstones for preventing STc131 spread. Oral decolonization therapies that target ST131 are being developed. There are no rapid methods available to identify STc131 in human specimens. A loop-mediated isothermal amplification (LAMP) assay (named LAMP-ST131) was developed for the detection of STc131 on well-characterized E. coli isolates and then compared to culture and PCR for urines and stool swabs. With E. coli isolates ( n = 720), LAMP-ST131 had a sensitivity (sens) of 100% [95% confidence interval (C.I.) = 98.1–100%)] and a specificity (spec) of 98.9% (95% C.I. = 97.5–99.5%). On urines ( n = 550), LAMP-ST131 had a sens of 97.6% (95% C.I. = 89.68–94.33%) and a spec of 92.3% (95% C.I. = 87.68–99.88%), while on stool swabs ( n = 278), LAMP-ST131 had a sens of 100% (95% C.I. = 88.7–100%) and a spec of 83.9% (95% C.I. = 78.8–87.9%). LAMP-ST131 detected 10 (urines) and 100 (stool swabs) gene copies/μL. LAMP-ST131 accurately identified STc131 within E. coli isolates and human specimens. The implementation of LAMP-ST131 will aid genomic surveys, enable the rapid implementation of effective infection prevention measures, and identify patients suitable for ST131 decolonization therapies. Such approaches will curb the spread of STc131 and decrease incidence rates of global MDR E. coli infections. IMPORTANCE We developed an accurate non-culture-based loop-mediated isothermal amplification (LAMP) methodology for the detection of (sequence type) STc131 among Escherichia coli isolates and human specimens. The use of LAMP-ST131 for global genomic surveillance studies and to identify patients that are suitable for ST131 decolonization therapies will be important for decreasing multidrug-resistant E. coli infections across the globe.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".