Bibliographic record
Abstract
PURPOSE OF REVIEW: Hypoxemia during one-lung ventilation (OLV) has become less common; however, it may still occur in about 10% of cases. We review recent developments which may affect the incidence and treatment of hypoxemia during OLV. RECENT FINDINGS: Changes in surgical techniques are affecting oxygenation during OLV. The increased use of the supine position may adversely affect the prevalence of hypoxemia, whereas the increased application of thoracoscopic techniques is limiting the treatment options. Treatment options such as global or selective recruitment maneuvers and drug effects of dexmedetomidine and epoprostenol on arterial oxygenation during OLV are discussed. Capnometry prior to, or early during OLV, may in fact be able to predict the degree of hypoxemia during OLV. Persistent controversies surrounding the effect of epidural anesthesia, ventilatory modalities and gravity are reviewed. SUMMARY: Interesting concepts have emerged from case reports and small studies on the treatment and prediction of hypoxemia during OLV. Definitive studies on the most effective ventilatory mode remain elusive. End-organ effects of OLV are an exciting new concept that may shape clinical practice and research going forward.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".