Comorbidities and Readmissions in Survivors of Acute Hypercapnic Respiratory Failure
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is defined by chronic airflow obstruction, but is presently considered as a complex, heterogeneous, and multicomponent disease in which comorbidities and extrapulmonary manifestations make important contributions to disease expression. COPD-related hospital readmission. In particular frequent intensive care unit (ICU) readmissions for exacerbations represent a major challenge and place a high burden on patient outcomes and health-related quality of life, as well as on the healthcare system.In this narrative review, we first address major and often undiagnosed comorbidities associated with COPD that could have an impact on hospital readmission after an index ICU admission for acute hypercapnic respiratory failure. Some guidance for treatment is discussed. Second, we present predictors of hospital and ICU readmission and discuss various strategies to reduce such events.There is a strong rationale to detect and treat major comorbidities early after index ICU admission for acute hypercapnic respiratory failure. It still remains unclear, however, if a comprehensive and holistic approach to comorbidities in frail patients surviving hypercapnic respiratory failure can efficiently reduce the readmission rate.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".