Impact of frailty and older age on weaning from invasive ventilation: a secondary analysis of the WEAN SAFE study
Bibliographic record
Abstract
OBJECTIVE: To understand the impact of both frailty and chronologic age on outcomes of weaning from invasive mechanical ventilation (MV). METHODS: The study population consisted of patients enrolled in the 'WorldwidE. AssessmeNt of Separation of pAtients From ventilatory assistancE (WEAN SAFE) study. We defined 4 non-overlapping groups, namely: 'frail' (clinical frailty scale [CFS] score > 4; age < 80 years); 'elderly' (CFS ≤ 4; age ≥ 80y), 'frail \elderly' (CFS > 4; age ≥ 80 years), and a 'not frail or elderly' population. The primary outcome was the impact of frailty and older age on delayed weaning and failed weaning from invasive MV. Secondary outcomes included the impact of frailty and age on ICU and hospital survival. RESULTS: In the study population, 760 (17%) were frail, while 360 (8%) were elderly, 197 (4%) were frail and elderly, while 3,176 (70%) were not frail or elderly. The frail and elderly cohorts were more likely to be female, had hypoxemic/hypercapnic respiratory failure or sepsis, and had more comorbidities. The proportion of delayed weaning and of failed weaning from invasive MV was significantly higher in the frail (28 and 23%), the elderly (25 and 19%), and the frail and elderly groups (22% and 25%), compared to the not frail or elderly population (12% and 13%, P < 0.01). ICU and hospital mortality was higher in the frail (21 and 33%), the elderly (19 and 31%), and the frail and elderly groups (26 and 46%), compared to the not frail or elderly population (12% and 18%, P < 0.001). In multivariate analyses, there was an independent association between frailty and delayed weaning initiation and weaning failure. Old age was independently associated with risk of weaning failure. CONCLUSIONS: Frailty status had a more consistent impact than older age on weaning outcomes. However, overall outcomes in these cohorts are encouraging once separation attempts have been initiated.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".