A63 TRENDS AND OUTCOMES OF LIVER DISEASE HOSPITALIZATIONS DURING THE CORONAVIRUS PANDEMIC IN THE UNITED STATES: A NATIONWIDE POPULATION-LEVEL ANALYSIS
Bibliographic record
Abstract
Abstract Background The impact of the Coronavirus disease-2019 (COVID-19) pandemic on patients with liver disease is not well described at the population level in the United States. Purpose We used the largest, nationwide inpatient dataset to describe inpatient liver disease outcomes in the United States during the first year of the pandemic (2020) using 2018 and 2019 as comparator years. Method Using the National Inpatient Sample (2018-2020), we explored year-to-year and 2020 month-to-month trends in hospitalizations, length of stay, and inpatient mortality for liver-related indications including compensated cirrhosis, decompensated cirrhosis, alcohol-associated liver disease (ALD), alcohol-associated hepatitis (AH), hepatocellular carcinoma (HCC), and variceal upper gastrointestinal bleeding (VUGIB) using regression modeling. We also looked at the impact of the COVID-19 pandemic on liver transplantation rates. A p-value <0.05 was considered statistically significant. Result(s) Hospitalizations for both compensated and decompensated cirrhosis decreased in 2020 compared to 2019 (relative change [RC] of 1.5%, p <0.001, Table 1). Interestingly, hospitalizations for ALD and AH increased in 2020 compared to pre-pandemic years (ALD RC=15.5% and AH RC 17.0%; p<0.001). Despite the decrease in cirrhosis hospitalizations in 2020, all-cause inpatient mortality among patients with compensated cirrhosis increased from 30,135 in 2019 to 35,220 in 2020 (p<0.001) and from 22,850 in 2019 to 26,390 in 2020 among patients with decompensated cirrhosis (p<0.001). This was accompanied by a 27.8% increase in mortality for ALD (p=0.004) in comparison to pre-pandemic years. Corresponding to the peaks of the pandemic, we observed the fewest cirrhosis hospitalizations in April and December 2020 (Table 2), however, these months had the highest observed mortality rates (p-trend ≤ 0.004). Reassuringly, liver transplantation rates were not significantly impacted by the COVID-19 pandemic (p=0.51). Image Conclusion(s) Cirrhosis hospitalizations, in general, decreased in 2020 compared to pre-pandemic years but were associated with higher all-cause mortality rates particularly in the peak months of the COVID-19 pandemic (April and December 2020) possibly reflecting COVID-19 specific mortality. Alcoholic liver disease admissions also increased during the pandemic while liver transplantation rates were not significant impacted. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".