Development of a sensitive prognostic scoring system for the evaluation of severity of acute-on-chronic hepatitis B liver failure: A retrospective cohort study
Bibliographic record
Abstract
PURPOSE: The purpose of the current study was to establish an objective, simple, and sensitive prognostic scoring system for estimating the severity of acute-on-chronic liver failure in hepatitis B (ACLFB). METHODS: A novel prognostic scoring system was calculated from six clinical indices including total bilirubin (TB), prothrombin activity (PTA), creatinine (Cr), hepatic encephalopathy (HE), infections, and the depth of ascites from 726 patients with ACLFB. Indices were scored from 1 to 4 according to their severity. Groups of the same patients were scored with three-indices (TB, PTA and Cr), four-indices (TB, PTA, Cr and HE), five-indices (TB, PTA, Cr, HE and the depth of ascites) or six-indices (TB, PTA, Cr, HE, the depth of ascites, and infections). The differences in the sensitivity and specificity of four scoring systems were analyzed. RESULTS: The demarcation points of the three-, four-, five- and six-indices scoring systems were 4.62, 6.12, 7.88 and 9.57, respectively. The analysis of the areas under the receiver operating characteristic (ROC) curve indicated that the four-, five- and six-indices scoring systems were more exact, and objective than the three-indices prognostic scoring system. In the six-indices scoring system, the survival rates of patients with scores from 2 to 6 was 98.31% (233/237), and the mortality rate of patients with scores of 16 and above was 100.00% (140/140), while the mortality rates were 8.33% (3/36) and 96.43% (27/28) for those with scores from 7 to 15, respectively. CONCLUSION: A six-indices scoring system is an objective, pertinent, and sensitive system, and may be useful for the prognostic evaluation of ACLFB.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".