Patient survival, predictive factors and disease course of severe sepsis in Czech intensive care units: A multicentre, retrospective, observational study
Bibliographic record
Abstract
BACKGROUND: Severe sepsis/septic shock is associated with high mortality. In Central Europe, there is a dearth of information on the prevalence and treatment of severe sepsis. The EPOSS (Data-based Evaluation and Prediction of Outcome in Severe Sepsis) project launched in 2011 was aimed at collecting data on patients with severe sepsis/septic shock. METHODS: The EPOSS study processes data from the EPOSS project database, and is a retrospective, multicentre, observational study. This included all consecutive patients aged 18 and over who were admitted to participating ICUs from 1 January 2011 to 5 November 2013 and met the inclusion criteria of severe sepsis/septic shock. The primary endpoint was to analyse the relationship between in-hospital mortality (either in ICU or after discharge from ICU) and the type and number of fulfilled diagnostic and treatment interventions during the first 6 h after the diagnosis of severe sepsis/septic shock. RESULTS: The collected dataset involved 1082 patients meeting the criteria of severe sepsis/septic shock. Following data validation, a final dataset of 897 patients was obtained. The average age of the patient group was 64.7 years; mortality at discharge from EPOSS ICUs was 35.5% and from hospital 40.7%. Of the 10 evaluated diagnostic and treatment interventions within the initial 6 hours of identifying severe sepsis/septic shock (i.e. fulfilment of SSC bundles), four or five diagnostic and treatment interventions were administered to 58.4% patients. Combined diagnostic and treatment interventions associated with the lowest in-hospital mortality were: CVP of ≥8-12 mm Hg & MAP of ≥65 mm Hg & Urine output at ≥0.5 mL/kg/h & Lactate of ≤4.0 mmol/L & Initial lactate measured & Antibiotics in the first hour. Lactate at <4 mmol/L and MAP of ≥65 mm Hg remained statistically significant even after adjustment for patient age and APACHE II score. Statistically significantly increased in-hospital mortality was found in patients admitted from general departments (45.7%) or from other ICUs (41.6%), compared to a lower in-hospital mortality of patients transferred from outpatient clinics (26.5%) or Emergency (38.0%). Severe sepsis/septic shock patients transferred from the department of internal medicine were associated with a higher in-hospital mortality (45.1%) than surgical patients (35.5%). CONCLUSIONS: The most effective measures associated with the lowest in-hospital mortality in septic shock patients were CVP of ≥8-12 mm Hg, MAP of ≥65 mm Hg, urine output at ≥0.5 mL/kg/h, initial lactate level of ≤4.0 mmol/L and administration of antibiotics within the first hour.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".