Clinical Outcomes and Predictors of Thirty-Day Readmissions of Hypertriglyceridemia-Induced Acute Pancreatitis
Bibliographic record
Abstract
Background: Hypertriglyceridemia (HTG) is a well-established cause of acute pancreatitis often leading to significant morbidity, mortality, and healthcare burden. This study aimed to describe the rate, reasons, and predictors of HTG-induced acute pancreatitis (HTG-AP) in the USA. Methods: This retrospective study analyzed the Nationwide Readmissions Database (NRD) for 2018 to determine all adults (≥ 18 years) readmitted within 30 days of an index hospitalization of HTG-AP. Hospitalization characteristics and adverse outcomes for 30-day readmissions were highlighted and compared with index admissions of HTG-AP. Furthermore, independent predictors for 30-day readmissions of HTG-AP were also identified. P values ≤ 0.05 were considered statistically significant. Results: In 2018, the rate of 30-day readmission of HTG-AP was noted to be 13.5%. At the time of readmission, AP (45.2%) was identified as the most common principal diagnosis, followed by chronic pancreatitis (6.3%) and unspecified sepsis (4.8%). Compared to index admissions, 30-day readmissions of HTG-AP had a higher proportion of patients with Charlson Comorbidity Index (CCI) scores ≥ 3 (48.5% vs. 33.8%, P < 0.001). Furthermore, we noted higher rates of inpatient mortality (1.7% vs. 0.7%, odds ratio (OR): 2.55, 95% confidence interval (CI): 1.83 - 3.57, P < 0.001), mean length of stay (LOS) (5.6 vs. 4.1 days, OR: 1.5, 95% CI: 1.2 - 1.7, P < 0.001), and mean total healthcare charge (THC) ($56,799 vs. $36,078, OR: 18,702, 95% CI: 15,136 - 22,267, P < 0.001) for 30-day readmissions of HTG-AP compared to index admissions. Independent predictors for 30-day all-cause readmissions of HTG-AP included hypertension, protein energy malnutrition (PEM), CCI scores ≥ 3, chronic kidney disease and discharge against medical advice. Conclusions: AP was the principal diagnosis on presentation in only 45.2% patients for 30-day readmissions of HTG-AP. Compared to index admissions, 30-day readmissions of HTG-AP had a higher comorbidity burden, inpatient mortality, mean LOS and mean THC.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".