Systematic review: the natural history of alpha‐1 antitrypsin deficiency, and associated liver disease
Bibliographic record
Abstract
BACKGROUND: Alpha-1 antitrypsin deficiency (AATD) is estimated to affect three million people worldwide. It causes liver disease in a proportion of carriers of the PiS and PiZ allele due to the formation and retention of polymers within the endoplasmic reticulum of hepatocytes. The reason for this selective penetrance is not known. Although clinical trials are underway, liver transplantation is the only effective treatment for liver disease due to AATD. AIMS: To report the prevalence and natural history of liver disease among individuals with AATD, and assess the outcomes of liver transplantation through systematic review. METHODS: A comprehensive search was conducted across multiple databases. Two independent authors selected the articles and assessed bias using the Newcastle-Ottawa Scale. Data were pooled for analysis, where comparable outcomes were reported. RESULTS: Thirty-five studies were identified related to disease progression and 12 for the treatment of AATD. Seven per cent of children were reported to develop liver cirrhosis, with 16.5% of individuals presenting in childhood requiring liver transplantation. Of those surviving to adulthood, 10.5% had liver cirrhosis and 14.7% required transplantation. Liver transplantation was the only effective treatment reported and outcomes compare favourably to other indications, with 5-year survival reported as over 90% in children and over 80% in adults. DISCUSSION: The clinical course of liver disease in individuals with AATD remains poorly understood, but affects about 10% of those with AATD. More research is required to identify those patients at risk of developing liver disease at an early stage, and to provide alternative treatments to liver transplantation.
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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 | 0.007 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".