A comparative study of the use of selective digestive decontamination prophylaxis in living‐donor liver transplant recipients
Bibliographic record
Abstract
INTRODUCTION: Bacterial infections are major causes of early morbidity and mortality after liver transplantation. Selective digestive decontamination (SDD) can be used pre-operatively for living-donor liver transplant (LD-LT), but its role in this setting remains controversial. METHODS: To evaluate this strategy, we retrospectively analyzed a cohort of consecutive LD-LTs performed in our center from March 2007 to February 2011 and compared the incidence and nature of early infectious complications, length of intensive care unit stay and hospitalization, antibiotic use, and emergence of resistant bacteria in patients with or without SDD prophylaxis. RESULTS: Of 148 LD-LTs in the study period, 111 received SDD prophylaxis while 37 did not. In a multivariate model, the independent factors associated with an increased risk of early post-transplant infections were length of postoperative mechanical ventilation (for every additional day odds ratio [OR] = 2.37, 95% confidence interval [CI] 1.4-4.0; P = 0.002), and choledochojejunostomy (OR = 4.5, 95% CI 1.95-10.5; P < 0.001). Use of SDD did not affect the rate or distribution of infectious complications, duration of hospitalization, antibiotic use, or acquisition of resistant bacteria (OR = 3.52, 95% CI 0.43-15.17; P = 0.376). CONCLUSION: In conclusion, the use of SDD prophylaxis in LD-LT was not beneficial and should be avoided, as it offers no advantage and could potentiate the emergence of multidrug-resistant organisms.
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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 | 0.000 |
| 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".