Physical Therapy Management of Ventilated Patients with Acute Respiratory Distress Syndrome or Severe Acute Lung Injury
Bibliographic record
Abstract
The early use of prone positioning, longer duration in prone lying (i.e., sufficient dosage), and use of prone positioning over a sufficient number of days are important components of the prone-positioning protocol for ventilated patients with ARDS/ALI.47–49,70,72,73 Kinetic therapy or lateral positioning with head of bed >30° and sitting with head of the bed >30° may be used for routine positioning of patients with ventilated ARDS/ALI.28,42,43 Step-wise early mobilization of ICU patients is safe and is associated with favourable outcomes in terms of both hospital length of stay and functional ability of the patient.29,30,32 Early intervention of sufficient frequency and duration and over an adequate period are the key to success for many physiotherapy interventions for ventilated ARDS/ALI patients. This review provides a starting point for physiotherapy guidelines in the management of patients with ARDS/ALI, but more clinical research is needed, and, of course, the patient's best interest is paramount when research findings are incorporated into clinical practice.88,89 Even given the complexity involved in clinical research on ICU care of severely ill patients, there may be some simple but important treatment interventions for physical therapists to use that may save lives when properly administered.90
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 0.001 |
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".