The impact of obesity in cirrhotic patients with septic shock: A retrospective cohort study
Bibliographic record
Abstract
BACKGROUND & AIMS: The prevalence of obesity in cirrhosis is rising. The impact of obesity in critically ill cirrhotic patients with sepsis/septic shock has not been evaluated. This study aimed to examine the relationship between obesity and mortality in cirrhotic patients admitted to the intensive care unit with septic shock. METHODS: A retrospective cohort study of all cirrhotic patients with septic shock (n = 362) and a recorded body mass index (BMI) from an international, multicentre (CATSS) database (1996-2015) was performed. Patients were classified by BMI as per WHO categories. Primary outcome was in-hospital mortality. Multivariate logistic regression analyses were carried out to determine independent associations with outcome. RESULTS: In this analysis, mean age was 56.4 years, and 62% were male. Median BMI was 26.3%, and 57.7% were overweight/obese. In-hospital mortality was 71%. Obese patients were more likely to have comorbidities of cardiac disease, lung disease and diabetes. Compared to survivors (n = 105), non-survivors (n = 257) had significantly higher MELD and APACHEII scores and higher requirements for renal replacement therapy and mechanical ventilation (P < .03 for all). Using multivariable logistic regression, increase in BMI (OR 1.07, P = .034), time delay to appropriate antimicrobials (OR 1.16 per hour, P = .003), APACHEII (OR 1.12 per unit, P = .008) and peak lactate (OR 1.15, P = .028) were independently associated with in-hospital mortality. CONCLUSIONS: Septic shock in cirrhosis carries a high mortality. Increased BMI is common in critically ill cirrhotic patients and independently associated with increased in-hospital mortality.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".