Culture-Negative Septic Shock Compared With Culture-Positive Septic Shock: A Retrospective Cohort Study
Bibliographic record
Abstract
OBJECTIVES: To determine the clinical characteristics and outcomes of culture-negative septic shock in comparison with culture-positive septic shock. DESIGN: Retrospective nested cohort study. SETTING: ICUs of 28 academic and community hospitals in three countries between 1997 and 2010. SUBJECTS: Patients with culture-negative septic shock and culture-positive septic shock derived from a trinational (n = 8,670) database of patients with septic shock. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patients with culture-negative septic shock (n = 2,651; 30.6%) and culture-positive septic shock (n = 6,019; 69.4%) were identified. Culture-negative septic shock compared with culture-positive septic shock patients experienced similar ICU survival (58.3% vs 59.5%; p = 0.276) and overall hospital survival (47.3% vs 47.1%; p = 0.976). Severity of illness was similar between culture-negative septic shock and culture-positive septic shock groups ([mean and SD Acute Physiology and Chronic Health Evaluation II, 25.7 ± 8.3 vs 25.7 ± 8.1]; p = 0.723) as were serum lactate levels (3.0 [interquartile range, 1.7-6.1] vs 3.2 mmol/L [interquartile range, 1.8-5.9 mmol/L]; p = 0.366). As delays in the administration of appropriate antimicrobial therapy after the onset of hypotension increased, patients in both groups experienced congruent increases in overall hospital mortality: culture-negative septic shock (odds ratio, 1.56; 95% CI [1.47-1.66]; p < 0.0001) and culture-positive septic shock (odds ratio, 1.65; 95% CI [1.59-1.71]; p < 0.0001). CONCLUSIONS: Patients with culture-negative septic shock behave similarly to those with culture-positive septic shock in nearly all respects; early appropriate antimicrobial therapy appears to improve mortality. Early recognition and eradication of infection is the most obvious effective strategy to improve hospital survival.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".