Effects of Intraoperative Fluid Management on Postoperative Outcomes
Bibliographic record
Abstract
OBJECTIVE: Evaluate the dose-response relationship between intraoperative fluid administration and postoperative outcomes in a large cohort of surgical patients. BACKGROUND: Healthy humans may live in a state of fluid responsiveness without the need for fluid supplementation. Goal-directed protocols driven by such measures are limited in their ability to define the optimal fluid state during surgery. METHODS: This analysis of data on file included 92,094 adult patients undergoing noncardiac surgery with endotracheal intubation between 2007 and 2014 at an academic tertiary care hospital and two affiliated community hospitals. The primary exposure variable was total intraoperative volume of crystalloid and colloid administered. The primary outcome was 30-day survival. Secondary outcomes were respiratory complications within three postoperative days (pulmonary edema, reintubation, pneumonia, or respiratory failure) and acute kidney injury. Exploratory outcomes were postoperative length of stay and total cost of care. Our models were adjusted for patient-, procedure-, and anesthesia-related factors. RESULTS: A U-shaped association was observed between the volume of fluid administered intraoperatively and 30-day mortality, costs, and postoperative length of stay. Liberal fluid volumes (highest quintile of fluid administration practice) were significantly associated with respiratory complications whereas both liberal and restrictive (lowest quintile) volumes were significantly associated with acute kidney injury. Moderately restrictive volumes (second quintile) were consistently associated with optimal postoperative outcomes and were characterized by volumes approximately 40% less than traditional textbook estimates: infusion rates of approximately 6-7 mL/kg/hr or 1 L of fluid for a 3-hour case. CONCLUSIONS: Intraoperative fluid dosing at the liberal and restrictive margins of observed practice is associated with increased morbidity, mortality, cost, and length of stay.
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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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".