Bibliographic record
Abstract
Lung transplantation has evolved to become an acceptable therapy for individuals with end-stage lung disease. Readmissions rates after lung transplantation remain high as compared to other medical surgical populations. The purpose of this review is to synthesize the current body of knowledge about patterns, risk factors, and outcomes of readmissions after lung transplantation. The literature revealed that the most common admission diagnoses linked to lung transplant readmissions are infections followed by tachyarrhythmias, airway complications, surgical complications, rejection, thromboembolic events, gastrointestinal complications, and renal dysfunction. Risk factors for these readmissions include male gender, longer intensive care unit stay, reintubation, prolonged chest tube air leak, frailty, and discharge to a long-term care facility. Outcomes of multiple readmissions after lung transplantation are associated with decreased survival and increased risk of mortality. Further research is needed to better understand which readmission diagnoses are preventable and whether multidisciplinary interventions can reduce readmission rates among patients after lung transplantation.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".