Real-world Time to Positivity of 2 Widely Used Commercial Blood Culture Systems in Patients With Severe Manifestations of Sepsis: An Analysis of the FABLED Study
Bibliographic record
Abstract
Abstract Background Of all microbiological tests performed, blood cultures have the most impact on patient care. Timely results are essential, especially in the management of sepsis. While there are multiple available blood culture systems on the market, they have never been compared in a prospective study in a critically ill population. Methods We performed an analysis of the FABLED study cohort to compare culture results and time to positivity (TTP) of 2 widely used blood culture systems: BacT/Alert and BACTEC. In this multisite prospective study, patients with severe manifestations of sepsis had cultures drawn before antibiotics using systematic enrollment criteria and blood drawing methodology allowing for minimization of pre-analytical biases. Results We enrolled 315 patients; 144 had blood cultures (47 positive) with BacT/Alert and 171 with BACTEC (53 positive). Patients whose blood cultures were processed using the BacT/Alert system were younger (median, 64 vs 70 years; P = .003), had a higher proportion of HIV (9.03% vs 1.75%; P = .008) and a lower qSOFA (P = .003). There were no statistically significant differences in the most commonly identified bacterial species. TTP was shorter for BACTEC (median [interquartile range {IQR}], 12.5 [10–14] hours) compared with BacT/Alert (median [IQR], 17 [14–21] hours; P < .0001). Conclusions In this large prospective multi-centre study comparing the two blood culture systems among patients with severe manifestations of sepsis, and using a rigorous pre-analytical methodology, the BACTEC system yielded positive culture results 4.5 hours earlier than BacT/Alert. These results apply to commonly isolated bacteria. However, our study design did not allow direct comparison of TTP for unusual pathogens nor of clinical sensitivity between systems. More research is needed to determine the clinical implications of this finding.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".