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Record W2783787964 · doi:10.1002/hep.29773

NACSELD acute‐on‐chronic liver failure (NACSELD‐ACLF) score predicts 30‐day survival in hospitalized patients with cirrhosis

2018· article· en· W2783787964 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHepatology · 2018
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsUniversity of AlbertaUniversity of Toronto
Fundersnot available
KeywordsMedicineCirrhosisInternal medicineLiver failureGastroenterology

Abstract

fetched live from OpenAlex

The North American Consortium for the Study of End-Stage Liver Disease's definition of acute-on-chronic liver failure (NACSELD-ACLF) as two or more extrahepatic organ failures has been proposed as a simple bedside tool to assess the risk of mortality in hospitalized patients with cirrhosis. We validated the NACSELD-ACLF's ability to predict 30-day survival (defined as in-hospital death or hospice discharge) in a separate multicenter prospectively enrolled cohort of both infected and uninfected hospitalized patients with cirrhosis. We used the NACSELD database of 14 tertiary care hepatology centers that prospectively enrolled nonelective hospitalized patients with cirrhosis (n = 2,675). The cohort was randomly split 60%/40% into training (n = 1,605) and testing (n = 1,070) groups. Organ failures assessed were (1) shock, (2) hepatic encephalopathy (grade III/IV), (3) renal (need for dialysis), and (4) respiratory (mechanical ventilation). Patients were most commonly Caucasian (79%) men (62%) with a mean age of 57 years and a diagnosis of alcohol-induced cirrhosis (45%), and 1,079 patients had an infection during hospitalization. The mean Model for End-Stage Liver Disease score was 19, and the median Child score was 10. No demographic differences were present between the two split groups. Multivariable modeling revealed that the NACSELD-ACLF score, as determined by number of organ failures, was the strongest predictor of decreased survival after controlling for admission age, white blood cell count, serum albumin, Model for End-Stage Liver Disease score, and presence of infection. The c-statistics were 0.8073 for the training set and 0.8532 for the validation set. CONCLUSION: Although infection status remains an important predictor of death, NACSELD-ACLF was independently validated in a separate large multinational prospective cohort as a simple, reliable bedside tool to predict 30-day survival in both infected and uninfected patients hospitalized with a diagnosis of cirrhosis. (Hepatology 2018;67:2367-2374).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.229
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it