Comparison of Predictors and Mortality Between Bloodstream Infections Caused by ESBL-Producing <i>Escherichia coli</i> and ESBL-Producing <i>Klebsiella pneumoniae</i>
Bibliographic record
Abstract
OBJECTIVETo compare the epidemiology, clinical characteristics, and mortality of patients with bloodstream infections (BSI) caused by extended-spectrum β-lactamase (ESBL)-producing Escherichia coli (ESBL-EC) versus ESBL-producing Klebsiella pneumoniae (ESBL-KP) and to examine the differences in clinical characteristics and outcome between BSIs caused by isolates with CTX-M versus other ESBL genotypesMETHODSAs part of the INCREMENT project, 33 tertiary hospitals in 12 countries retrospectively collected data on adult patients diagnosed with ESBL-EC BSI or ESBL-KP BSI between 2004 and 2013. Risk factors for ESBL-EC versus ESBL-KP BSI and for 30-day mortality were examined by bivariate analysis followed by multivariable logistic regression.RESULTSThe study included 909 patients: 687 with ESBL-EC BSI and 222 with ESBL-KP BSI. ESBL genotype by polymerase chain reaction amplification of 286 isolates was available. ESBL-KP BSI was associated with intensive care unit admission, cardiovascular and neurological comorbidities, length of stay to bacteremia >14 days from admission, and a nonurinary source. Overall, 30-day mortality was significantly higher in patients with ESBL-KP BSI than ESBL-EC BSI (33.7% vs 17.4%; odds ratio, 1.64; P=.016). CTX-M was the most prevalent ESBL subtype identified (218 of 286 polymerase chain reaction-tested isolates, 76%). No differences in clinical characteristics or in mortality between CTX-M and non-CTX-M ESBLs were detected.CONCLUSIONSClinical characteristics and risk of mortality differ significantly between ESBL-EC and ESBL-KP BSI. Therefore, all ESBL-producing Enterobacteriaceae should not be considered a homogeneous group. No differences in outcomes between genotypes were detected.CLINICAL TRIALS IDENTIFIERClinicalTrials.gov. Identifier: NCT01764490.Infect Control Hosp Epidemiol 2018;39:660-667.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".