Rates of Significant Preventable Adverse Events in Hospitalized Patients With Respiratory Disease
Bibliographic record
Abstract
OBJECTIVE: Patients admitted to the hospital with an acute illness secondary to respiratory disease are at increased risk of adverse events, many of which may be preventable. This study examined the incidence and nature of preventable adverse events (PAEs) leading to significant morbidity or mortality in a cohort of patients admitted with a primary respiratory presentation at an acute care hospital. METHODS: A review was conducted of patients admitted to a pulmonary ward at our center who were either transferred to the ICU or died on the ward between January 1, 2020 and April 19, 2021. Electronic medical records were reviewed for any indication of an event that led to clinical decompensation or death. Logistic regression was conducted to assess the association between select patient clinical factors and the occurrence of a PAE. RESULTS: Out of 874 patients admitted to the hospital's pulmonary wards, 27 patients were transferred to the ICU because of worsening medical status, while another 55 patients died on the ward. Eight patients (30%) experienced a PAE consisting of either inadvertent oxygen removal (n = 4) or aspiration (n = 4) just before requiring transfer to the ICU. Thirteen of the deceased individuals (24%) experienced PAEs just before death, including inadvertent oxygen removals (n = 7), aspiration (n = 4), or oximetry malfunction (n = 2). No specific clinical factors that could be used to predict the occurrence of PAEs were identified. CONCLUSION: Preventable adverse events were identified in over a quarter of admitted patients with respiratory disease who required an ICU transfer or died in-hospital. Enhanced surveillance of hospitalized patients with acute respiratory disease is warranted.
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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 | 0.000 | 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) | 0.000 | 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".