Mortality and quality of life in the five years after severe sepsis
Bibliographic record
Abstract
INTRODUCTION: Severe sepsis is associated with high levels of morbidity and mortality, placing a high burden on healthcare resources. We aimed to study outcomes in the five years after severe sepsis. METHODS: This was a cohort study using data from a prospective audit in 26 adult ICUs in Scotland. Mortality was measured using clinical databases and quality of life using Short Form 36 (SF-36) at 3.5 and 5 years after severe sepsis. RESULTS: A total of 439 patients were recruited with a 58% mortality at 3.5 years and 61% mortality at 5 years. A total of 85 and 67 patients responded at 3.5 and 5 years follow-up, respectively. SF-36 physical component score (PCS) was low compared to population controls at 3.5 years (mean 41.8 (SD 11.8)) and at 5 years (mean 44.8 (SD 12.7)). SF-36 mental component score (MCS) was slightly lower than population controls at 3.5 years (mean 47.7 (SD 14.6)) and at 5 years after severe sepsis (mean 48.8 (SD 12.6)). The majority of patients were satisfied with their current quality of life (QOL) (80%) and all patients would be willing to be treated in an ICU again if they become critically ill despite many having unpleasant memories (19%) and recall (29%) of ICU events. CONCLUSIONS: Patients with severe sepsis have a high ongoing mortality after severe sepsis. They also have a significantly lower physical QOL compared to population norms but mental QOL scores were only slightly below population norms up to five years after severe sepsis. All survivors would be willing to be treated in an ICU again if critically ill. Mortality and QOL outcomes were broadly similar to other critically ill cohorts throughout the five years of follow-up.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".