Preoperative Hyponatremia and Perioperative Complications
Bibliographic record
Abstract
BACKGROUND: Although hyponatremia has been linked to increased morbidity and mortality in a variety of medical conditions, its association with perioperative outcomes remains uncertain. METHODS: To determine whether preoperative hyponatremia is a predictor of 30-day perioperative morbidity and mortality, we conducted a cohort study using the American College of Surgeons National Surgical Quality Improvement Program database to identify 964 263 adults undergoing major surgery from more than 200 hospitals (from January 1, 2005, to December 31, 2010) and observed them for 30-day perioperative outcomes. We used multivariable logistic regression to estimate relative risks for death, major coronary events, wound infections, and pneumonia occurring within 30 days of surgery and quantile regression to estimate differences in average length of hospital stay. RESULTS: A total of 75 423 patients with preoperative hyponatremia (sodium level <135 mEq/L [to convert to millimoles per liter, multiply by 1.0]) were compared with 888 840 patients with normal baseline sodium levels (135-144 mEq/L). Preoperative hyponatremia was associated with a higher risk of 30-day mortality (5.2% vs 1.3%; adjusted odds ratio [aOR], 1.44; 95% CI, 1.38-1.50), and this finding was consistent in all the subgroups. This association was particularly marked in patients undergoing nonemergency surgery (aOR, 1.59; 95% CI, 1.50-1.69; P < .001 for interaction) and American Society of Anesthesiologists class 1 and 2 patients (aOR, 1.93; 95% CI, 1.57-2.36; P < .001 for interaction). Furthermore, hyponatremia was associated with a greater risk of perioperative major coronary events (1.8% vs 0.7%; aOR, 1.21; 95% CI, 1.14-1.29), wound infections (7.4% vs 4.6%; 1.24; 1.20-1.28), and pneumonia (3.7% vs 1.5%; 1.17; 1.12-1.22) and prolonged median lengths of stay by approximately 1 day. CONCLUSION: Preoperative hyponatremia is a prognostic marker for perioperative 30-day morbidity and mortality.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".