Effect of ursodeoxycholic acid on preventing SARS-CoV-2 infection in patients with liver transplantation: a multicenter retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Immunosuppressed recipients of liver transplantation (LT) are more likely to develop coronavirus disease 2019 (COVID-19) and may have an increased risk of developing worse outcomes. AIM: To assess the effect of ursodeoxycholic acid (UDCA) on preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in LT recipients. DESIGN: Adult patients (aged ≥ 18 years) who underwent LT between 1 January 2015 and 31 December 2022 were included and categorized into two groups according to their use of UDCA. METHODS: The prevalence and severity of COVID-19 among transplantation patients between the UDCA and non-UDCA groups were estimated and compared. RESULTS: Among the 897 LT patients who met the inclusion criteria, infection rate of SARS-CoV-2 was 78.4%, and the rate of severe illness was 5.1% from January 2022 to January 2023 in China. In the multivariate analysis, only UDCA treatment (P = 0.006) was found to be a protective factor against SARS-CoV-2 infection. After propensity score matching, the SARS-CoV-2 infection rate in the UDCA group was lower than that in the non-UDCA group (74.1% vs. 84.6%, P = 0.002). This rate was further reduced to 62.1% (P = 0.002) when the oral administration dose was >15 mg/kg/day. There was no difference in the rates of severe COVID-19 illness, ICU admission, or ventilation rate or length of hospital stay with or without UDCA treatment (all P > 0.05). CONCLUSIONS: The use of UDCA in LT patients significantly reduced the SARS-CoV-2 infection rate and showed a dose-dependent protective effect.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".