Terminal withdrawal of mechanical ventilation in adult intensive care units: A systematic review and narrative synthesis of perceptions, experiences and practices
Bibliographic record
Abstract
BACKGROUND: During the terminal withdrawal of life-sustaining measures for intensive care patients, the removal of respiratory support remains an ambiguous practice. Globally, perceptions and experiences of best practice vary due to the limited evidence in this area. AIM: To identify, appraise and synthesise the latest evidence around terminal withdrawal of mechanical ventilation in adult intensive care units specific to perceptions, experiences and practices. DESIGN: Mixed methods systematic review and narrative synthesis. A review protocol was registered on PROSPERO (CRD42018086495). DATA SOURCES: Four electronic databases were systematically searched (Medline, Embase, CENTRAL and CINAHL). Obtained articles published between January 2008 and January 2020 were screened for eligibility. All included papers were appraised using relevant appraisal tools. RESULTS: Twenty-five papers were included in the review. Findings from the included papers were synthesised into four themes: 'clinicians' perceptions and practices'; 'time to death and predictors'; 'analgesia and sedation practices'; 'physiological and psychological impact'. CONCLUSIONS: Perceptions, experiences and practices of terminal withdrawal of mechanical ventilation vary significantly across the globe. Current knowledge highlights that the time to death after withdrawal of mechanical ventilation is very short. Predictors for shorter duration could be considered by clinicians and guide the choice of pharmacological interventions to address distressing symptoms that patients may experience. Clinicians ought to prepare patients, families and relatives for the withdrawal process and the expected progression and provide them with immediate and long-term support following withdrawal. Further research is needed to improve current evidence and better inform practice guidelines.
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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 | 0.033 | 0.126 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".