Physiological and clinical effects of trunk inclination adjustment in patients with respiratory failure: a scoping review and narrative synthesis
Bibliographic record
Abstract
BACKGROUND: Adjusting trunk inclination from a semi-recumbent position to a supine-flat position or vice versa in patients with respiratory failure significantly affects numerous aspects of respiratory physiology including respiratory mechanics, oxygenation, end-expiratory lung volume, and ventilatory efficiency. Despite these observed effects, the current clinical evidence regarding this positioning manoeuvre is limited. This study undertakes a scoping review of patients with respiratory failure undergoing mechanical ventilation to assess the effect of trunk inclination on physiological lung parameters. METHODS: The PubMed, Cochrane, and Scopus databases were systematically searched from 2003 to 2023. INTERVENTIONS: Changes in trunk inclination. MEASUREMENTS: Four domains were evaluated in this study: 1) respiratory mechanics, 2) ventilation distribution, 3) oxygenation, and 4) ventilatory efficiency. RESULTS: After searching the three databases and removing duplicates, 220 studies were screened. Of these, 37 were assessed in detail, and 13 were included in the final analysis, comprising 274 patients. All selected studies were experimental, and assessed respiratory mechanics, ventilation distribution, oxygenation, and ventilatory efficiency, primarily within 60 min post postural change. CONCLUSION: levels. Improvements in oxygenation were observed in a few patients and only in those who exhibited an increase in EELV upon moving to a semi-recumbent position. Therefore, the trunk inclination angle must be accurately reported in patients with respiratory failure under mechanical ventilation.
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 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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".