Predictors of Respiratory Failure Development in a Multicenter Cohort of Inpatients With Cirrhosis
Bibliographic record
Abstract
INTRODUCTION: Hospitalized patients with cirrhosis can develop respiratory failure (RF), which is associated with a poor prognosis, but predisposing factors are unclear. METHODS: We prospectively enrolled a multicenter North American cirrhosis inpatient cohort and collected admission and in-hospital data (grading per European Association for the Study of Liver-Chronic Liver Failure scoring system, acute kidney injury [AKI], infections [admission/nosocomial], and albumin use) in an era when terlipressin was not available in North America. Multivariable regression to predict RF was performed using only admission day and in-hospital events occurring before RF. RESULTS: A total of 511 patients from 14 sites (median age 57 years, admission model for end-stage liver disease [MELD]-Na 23) were enrolled: RF developed in 15%; AKI occurred in 24%; and 11% developed nosocomial infections (NI). At admission, patients who developed RF had higher MELD-Na, gastrointestinal (GI) bleeding/AKI-related admission, and prior infections/ascites. During hospitalization, RF developers had higher NI (especially respiratory), albumin use, and other organ failures. RF was higher in patients receiving albumin (83% vs 59%, P < 0.0001) with increasing doses (269.5 ± 210.5 vs 208.6 ± 186.1 g, P = 0.01) regardless of indication. Admission for AKI, GI bleeding, and high MELD-Na predicted RF. Using all variables, NI (odds ratio [OR] = 4.02, P = 0.0004), GI bleeding (OR = 3.1, P = 0.002), albumin use (OR = 2.93, P = 0.01), AKI (OR = 3.26, P = 0.008), and circulatory failure (OR = 3.73, P = 0.002) were associated with RF risk. DISCUSSION: In a multicenter inpatient cirrhosis study of patients not exposed to terlipressin, 15% of patients developed RF. RF risk was highest in those admitted with AKI, those who had GI bleeding on admission, and those who developed NI and other organ failures or received albumin during their hospital course. Careful volume monitoring and preventing nosocomial respiratory infections and renal or circulatory failures could reduce this risk.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".