Neither Blood Culture Positivity nor Time to Positivity Is Associated With Mortality Among Patients Presenting With Severe Manifestations of Sepsis: The FABLED Cohort Study
Bibliographic record
Abstract
Abstract Background Sepsis is a leading cause of morbidity, mortality, and health care costs worldwide. Methods We conducted a multicenter, prospective cohort study evaluating the yield of blood cultures drawn before and after empiric antimicrobial administration among adults presenting to the emergency department with severe manifestations of sepsis. Enrolled patients who had the requisite blood cultures drawn were followed for 90 days. We explored the independent association between blood culture positivity and its time to positivity in relation to 90-day mortality. Results Three hundred twenty-five participants were enrolled; 90-day mortality among the 315 subjects followed up was 25.4% (80/315). Mortality was associated with age (mean age [standard deviation] in those who died was 72.5 [15.8] compared with 62.9 [17.7] years among survivors; P < .0001), greater Charlson Comorbidity Index (2 [interquartile range {IQR}, 1–3] vs 1 [IQR, 0–3]; P = .008), dementia (13/80 [16.2%] vs 18/235 [7.7%]; P = .03), cancer (27/80 [33.8%] vs 47/235 [20.0%]; P = .015), positive quick Sequential Organ Failure Assessment score (57/80 [71.2%] vs 129/235 [54.9%]; P = .009), and normal white blood cell count (25/80 [31.2%] vs 42/235 [17.9%]; P = .02). The presence of bacteremia, persistent bacteremia after antimicrobial infusion, and shorter time to blood culture positivity were not associated with mortality. Neither the source of infection nor pathogen affected mortality. Conclusions Although severe sepsis is an inflammatory condition triggered by infection, its 90-day survival is not influenced by blood culture positivity nor its time to positivity. Clinical Trials Registration NCT01867905.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".