Identifying Primary Spontaneous Pneumothorax from Administrative Databases: A Validation Study
Bibliographic record
Abstract
Introduction. Primary spontaneous pneumothorax (PSP) is a disorder commonly encountered in healthy young individuals. There is no differentiation between PSP and secondary pneumothorax (SP) in the current version of the International Classification of Diseases (ICD-10). This complicates the conduct of epidemiological studies on the subject. Objective. To validate the accuracy of an algorithm that identifies cases of PSP from administrative databases. Methods. The charts of 150 patients who consulted the emergency room (ER) with a recorded main diagnosis of pneumothorax were reviewed to define the type of pneumothorax that occurred. The corresponding hospital administrative data collected during previous hospitalizations and ER visits were processed through the proposed algorithm. The results were compared over two different age groups. Results. There were 144 cases of pneumothorax correctly coded (96%). The results obtained from the PSP algorithm demonstrated a significantly higher sensitivity (97% versus 81%, p = 0.038) and positive predictive value (87% versus 46%, p < 0.001) in patients under 40 years of age than in older patients. Conclusions. The proposed algorithm is adequate to identify cases of PSP from administrative databases in the age group classically associated with the disease. This makes possible its utilization in large population-based studies.
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.
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 | 0.000 | 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) | 0.002 | 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".