Administrative coding for alpha-1 antitrypsin deficiency including the pi*ZZ phenotype is accurate in Sweden
Bibliographic record
Abstract
Background We aimed to validate the International Classification of Diseases (ICD)-10 codes for alpha-1 antitrypsin deficiency (AATD) (E880A = asymptomatic AATD; E880B = symptomatic AATD) in a large hospital reporting to the Swedish National Patient Register and to ascertain their relation to the protease inhibitor (Pi)*ZZ-phenotype.Methods We randomly selected 150 adults and 50 children who visited Karolinska University Hospital (Stockholm, Sweden) between 2014 and 2024 with coding for E880A or E880B (1:1). Positive predictive values (PPVs) of AATD ICD-10 codes were calculated for correctly assigned codes and the Pi*ZZ-phenotype using medical charts as gold standard. Information on smoking status, lung disease, liver disease, and living area, were also retrieved.Results The PPV of AATD ICD-10 codes (E880A + E880B) in adults was 99% (95%CI = 95–100%; n = 148/150). The PPV for the Pi*ZZ-phenotype was only 59% (95%CI = 50–67; n = 83/141) but increased to 79% (95%CI = 67–88%; n = 50/63) when only considering outpatients with E880B coding. Of adult participants, 13% had liver disease, 51% had lung disease, and 50% were ever-smokers. In children, the PPV of E880A + E880B was 100% (95%CI = 91–100%; n = 50/50) for any AATD diagnosis and was 88% for the Pi*ZZ-phenotype (95%CI = 75–95%; n = 43/49). Liver or lung disease occurred in 6% of children. Results were consistent across several sensitivity analyses.Conclusion In a tertiary care setting, the validity of ICD-10 codes for AATD is excellent. The PPV of these codes for delineating the Pi*ZZ-phenotype is high in children but requires an algorithm in adults with coding for E880B in outpatients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".