Effect of post-extubation high-flow nasal cannula on reintubation in elderly patients: a retrospective propensity score-matched cohort study
Bibliographic record
Abstract
Background: Studies of mechanically ventilated patients with a low risk of reintubation have suggested that the use of high-flow nasal cannula (HFNC) oxygen therapy reduces the risk of reintubation compared with conventional oxygen therapy (COT). However, the effect of HFNC following extubation in elderly patients with a high risk of reintubation remains unclear. Methods: All consecutive medical intensive care unit (ICU) patients aged >65 years who were mechanically ventilated for >24 h were prospectively registered between July 2017 and June 2018. Control was obtained from a historical database of patients attending the same ICU from January 2012 to December 2013. A total of 152 patients who underwent HFNC after planned extubation according to institutional protocols (HFNC group) were compared with a propensity-matched historical control group who underwent COT ( n = 175, COT group). The primary outcome was the proportion of reintubated patients within 48 h after planned extubation. Results: One hundred patients from the HFNC group and 129 patients from the COT group were matched by a propensity score that reflected the probability of receiving HFNC, and all variables were well matched. Post-extubation respiratory failure (41.0% versus 33.3%, p = 0.291) and reintubation rate within 48 h (16.0% versus 11.6%, p = 0.436) did not differ between the HFNC and COT groups. However, decreased levels of consciousness as a sign of post-extubation respiratory failure (27.0% versus 11.7%, p = 0.007) were significantly increased in the HFNC group compared with the COT group. Conclusion: Among elderly patients who underwent planned extubation, HFNC was not associated with a decrease in the risk of reintubation. Further prospective study evaluating the clinical benefits of post-extubation HFNC in elderly patients is needed. The reviews of this paper are available via the supplemental material section.
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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 | 0.001 | 0.000 |
| 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".