Trends and Outcomes of Alcoholic Liver Cirrhosis Hospitalizations in the Last Two Decades: Analysis of the Nationwide Inpatient Sample
Bibliographic record
Abstract
Background: Liver cirrhosis is a major burden on the health care system. Alcohol is one of the most common etiologies of cirrhosis. The aim of our article is to examine the trends of alcoholic liver cirrhosis (ALC) hospitalizations over the past two decades. Methods: This was a retrospective longitudinal study. Using the International Classification of Diseases, Ninth Revision, Clinical Modification/Procedure Coding System (ICD-9-CM/PCS) and the ICD-10-CM/PCS, the Nationwide Inpatient Sample (NIS) database was analyzed. We included 1998, 2003, 2008, 2013, and 2018 NIS databases. Using multivariate regression analysis, we examined trends of ALC hospitalizations including inpatient mortality, mean length of stay (LOS), and mean total hospital charges (THCs). Results: We included 261,420 hospitalizations with ALC as the primary diagnosis for admission. There was a trend toward increasing hospitalizations over that period; they increased from 46,186 in 1998 to 69,970 in 2018 (P < 0.001). Moreover, there was a 2.1-fold increase in the mean THC in 2018 compared to 1998 (P < 0.001). On the other hand, inpatient mortality decreased from 12.8% in 1998 to 4.7% in 2018 (P < 0.001), and a trend of decreasing mean LOS was observed. The mean LOS decreased from 7.0 days in 1998 to 5.9 days in 2018 (P < 0.001). Conclusions: Over the last two decades, there was a trend of increasing hospitalizations and THC. However, we noticed a trend toward decreasing inpatient mortality and LOS over that period, which might reflect in part an improvement in the medical care provided for these patients.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".