A prospective, observational registry of patients with severe sepsis: The Canadian Sepsis Treatment and Response Registry*
Bibliographic record
Abstract
OBJECTIVE: To determine the location of acquisition, timing, and outcomes associated with severe sepsis in community and teaching hospital critical care units. DESIGN: Prospective, observational study. SETTING: Twelve Canadian community and teaching hospital critical care units. PATIENTS: All patients admitted between March 17, 2003, and November 30, 2004 to the study critical care units with at least a 24-hr length of stay or severe sepsis identified during the first 24 hrs. INTERVENTIONS: Daily monitoring for severe sepsis. MEASUREMENTS AND MAIN RESULTS: We recorded data describing characteristics of patients, infections, systemic responses, and organ dysfunction. Severe sepsis occurred in 1238 patients (overall rate, 19.0%; range, 8.2%-35.3%). Hospital mortality was 38.1% (95% confidence interval [CI]: 35.4-40.8). Median intensive care unit length of stay was 10.3 days (interquartile range: 5.5, 17.9). Variables associated with mortality in multivariable analysis included age (odds ratio [OR] by decade 1.50; 95% CI: 1.36-1.65), acquisition location of severe sepsis (with community as the reference-hospital [OR: 1.69; CI: 1.16-2.46], early intensive care unit [OR: 2.15; CI: 1.42-3.25], late intensive care unit [OR: 2.65; CI: 1.82-3.87]), late intensive care unit (OR: 2.65; CI: 1.82-3.87), any comorbidity (OR: 1.42; CI: 1.04-1.93), chronic renal failure (OR: 2.03; CI: 1.10-3.76), oliguria (OR: 1.34; CI: 1.02-1.76), thrombocytopenia (OR: 2.12; CI: 1.43-3.13), metabolic acidosis (OR: 1.54; CI: 1.13-2.10), Multiple Organ Dysfunction Score (OR: 1.15; CI: 1.09-1.21) and Acute Physiology and Chronic Health Evaluation II predicted risk (OR: 3.75; CI: 2.08-6.76). CONCLUSION: These data confirm that sepsis is common and has high mortality in general intensive care unit populations. Our results can inform healthcare system planning and clinical study designs. Modifiable variables associated with worse outcomes, such as nosocomial infection (hospital acquisition), and metabolic acidosis indicate potential targets for quality improvement initiatives that could decrease mortality and morbidity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".