Is Perioperative Fluid and Salt Balance a Contributing Factor in Postoperative Worsening of Obstructive Sleep Apnea?
Bibliographic record
Abstract
An understanding of the potential mechanisms underlying recurrent upper airway collapse may help anesthesiologists better manage patients in the postoperative period. There is convincing evidence in the sleep medicine literature to suggest that a positive fluid and salt balance can worsen upper airway collapse in patients with obstructive sleep apnea through the redistribution of fluid from the legs into the neck and upper airway while supine, in a process known as "rostral fluid shift." According to this theory, during the day the volume from a fluid bolus or from fluid overload states (i.e., heart failure and chronic kidney disease) accumulates in the legs due to gravity, and when a person lies supine at night, the fluid shifts rostrally to the neck, also owing to gravity. The fluid in the neck can increase the extraluminal pressure around the upper airways, causing the upper airways to narrow and predisposing to upper airway collapse. Similarly, surgical patients also incur large fluid and salt balance shifts, and when recovered supine, this may promote fluid redistribution to the neck and upper airways. In this commentary, we summarize the sleep medicine literature on the impact of fluid and salt balance on obstructive sleep apnea severity and discuss the potential anesthetic implications of excessive fluid and salt volume on worsening sleep apnea.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".