Association of Omega-3 Status With Long-Term Risk of Hospitalization for Sepsis
Bibliographic record
Abstract
OBJECTIVES: Sepsis is a life-threatening condition characterized by a dysregulated host response to infection. Despite decades of clinical trials, there are no specific treatments; care of the nearly 50 million annual cases worldwide is limited to antimicrobials and supportive measures. A primary prevention strategy may therefore be of value. We hypothesized that higher premorbid omega-3 fatty acid levels would be associated with a reduced incidence of sepsis. DESIGN: Population-based cohort study. SETTING: Retrospective data from the United Kingdom (U.K. Biobank). PATIENTS: Two hundred seventy-three thousand three hundred twenty-five participants from the U.K. Biobank. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Our exposure was baseline estimated omega-3 index (eO3I), modeled both categorically in quartiles, and continuously with restricted cubic splines. Our outcome measure was hospital admission with an International Classification of Diseases , 10th Edition code consistent with sepsis. The median (interquartile range) baseline eO3I was 6.0% (4.8-7.3%). Over a mean follow-up period of 13 years, 9241 participants experienced hospitalization with sepsis. In our adjusted model, compared with the lowest eO3I quartile, participants had lower risks of sepsis incidence in the second quartile (hazard ratio [HR], 0.88; 95% CI, 0.86-0.91; p < 0.001), third quartile (HR, 0.80; 95% CI, 0.78-0.83; p < 0.001), and fourth quartile (HR, 0.75; 95% CI, 0.73-0.77; p < 0.001). When analyzed as a continuous variable, increasing eO3I was associated with a decreasing risk of sepsis ( p < 0.001). CONCLUSIONS: In this population-based cohort study, baseline eO3I was inversely associated with subsequent sepsis incidence. Given that omega-3 levels can be increased with dietary supplementation, primary prevention should be explored to mitigate the burden of sepsis.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".