Profile of the Risk of Death After Septic Shock in the Present Era
Bibliographic record
Abstract
OBJECTIVES: To investigate mortality of ICU patients over a 3-month period after an initial episode of septic shock and to identify factors associated with mortality. DESIGN: Prospective multicenter observational cohort study. SETTING: Fourteen ICUs from 10 French nonacademic and university teaching hospitals. PATIENTS: All consecutive adult patients with septic shock admitted between October 2009 and September 2011 were eligible. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: Multivariable analyses were performed using a Cox proportional hazard model and a flexible extension of the Cox model. In total, 1,495 of 10,941 patients (13.7%) had septic shock and 1,488 patients (99.5%) were included. Median age was 68 years (range, 58-78 yr). The majority of admissions (84%) were medical. Median (interquartile range) Simplified Acute Physiological Score II and Sequential Organ Failure Assessment were, respectively, 56 (45-70) and 11 (9-14). ICU and hospital mortality were, respectively, 39.4% and 48.6%. At 3 months, 776 patients (52.2%) had died. Factors significantly associated with increased risk of death in the multivariable Cox model were older age, male sex, comorbidities (immune deficiency, cirrhosis), Knaus C/D score, and high Sequential Organ Failure Assessment score. Flexible analyses indicated that the impact of Sequential Organ Failure Assessment score was greatest early after septic shock, while the onset of the effect of age, nosocomial infection, and cirrhosis was later. CONCLUSIONS: This is the most recent large-scale epidemiological study to investigate medium-term mortality in nonselected patients hospitalized in the ICU for septic shock. Advances in early management have improved survival at the initial phase, but risk of death persists in the medium term. Flexible modeling techniques yield insights into the profile of the risk of death in the first 3 months.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".