Clinical characteristics associated with adverse events in patients with exacerbation of chronic obstructive pulmonary disease: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: To assist physicians with difficult decisions about hospital admission for patients with acute exacerbation of chronic obstructive pulmonary disease (COPD) presenting in the emergency department, we sought to identify clinical characteristics associated with serious adverse events. METHODS: We conducted this prospective cohort study in 6 large Canadian academic emergency departments. Patients were assessed for standardized clinical variables and then followed for serious adverse events, defined as death, intubation, admission to a monitored unit or new visit to the emergency department requiring admission. RESULTS: We enrolled 945 patients, of whom 354 (37.5%) were admitted to hospital. Of 74 (7.8%) patients with a subsequent serious adverse event, 36 (49%) had not been admitted after the initial emergency visit. Multivariable modelling identified 5 variables that were independently associated with adverse events: prior intubation, initial heart rate ≥ 110/minute, being too ill to do a walk test, hemoglobin < 100 g/L and urea ≥ 12 mmol/L. A preliminary risk scale incorporating these and 5 other clinical variables produced risk categories ranging from 2.2% for a score of 0 to 91.4% for a score of 10. Using a risk score of 2 or higher as a threshold for admission would capture all patients with a predicted risk of adverse events of 7.2% or higher, while only slightly increasing admission rates, from 37.5% to 43.2%. INTERPRETATION: In Canada, many patients with COPD suffer a serious adverse event or death after being discharged home from the emergency department. We identified high-risk characteristics and developed a preliminary risk scale that, once validated, could be used to stratify the likelihood of poor outcomes and to enable rational and safe admission decisions.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".