The clinical value of England, Canada and Japanese liver transplantation criteria to predict the prognosis of the patients with chronic severe hepatitis in China
Bibliographic record
Abstract
目的 探讨英国、加拿大和日本的肝移植标准评估我国慢性重型肝炎患者预后的临床价值.方法 慢性重型肝炎患者55例,分别按英国标准(KCH)、加拿大标准(CanWAIT)和日本标准(JLT)进行分组,符合标准者为达标组,不符合标准者为未达标组.比较各标准的达标组与未达标组在观察期内(入院后90 d)的存活时间、存活率及病死率,评估各标准的预测能力及其与慢性重型肝炎临床分期的相关性.结果 符合KCH标准者17例,平均存活时间(MST)为17.5 d,病死率达100.0%,与未达标的38例(MST为69.2 d,病死率为34.2%)比较,差异有统计学意义(P＜0.01).符合CanWAIT标准者17例,MST为17.5 d,病死率达100.0%,与未达标的38例(MST为69.2 d,病死率为34.2%)比较,差异有统计学意义(P＜0.01).符合JLT标准者21例,MST为17.7 d,病死率为95.2%,与未达标的34例(MST为75.2 d,病死率为29.4%)比较,差异有统计学意义(P＜0.01).KCH标准和CanWAIT标准的敏感度、特异度、准确度、阳性预测值和阴性预测值分别是56.7%、100.0%、76.4%、100.0%和65.7%,JLT标准分别是66.7%、96.0%、80.0%、95.2%和70.6%.KCH标准、CanWAIT标准和JLT标准与慢性重型肝炎临床分期的相关系数分别是0.371、0.395和0.490.结论 以KCH标准、CanWAIT标准和JLT标准评估我国慢性重型肝炎患者的预后,其敏感度低,特异度高,对未达标者的生存预测值不高,而对达标者的死亡预测值高。
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".