Glomerular hyperfiltration is an independent predictor of postoperative outcomes: A <scp>NSQIP</scp><scp>multi‐specialty</scp> surgical cohort analysis
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Bibliographic record
Abstract
AIM: While high estimated glomerular filtration rate (eGFR) has been associated with increased overall mortality, its effect on postoperative outcomes is relatively understudied. We sought to investigate the association between high eGFR and 30-day postoperative outcomes using a multi-specialty surgical cohort. METHODS: Using the National Surgical Quality Improvement Program database, we selected adult for whom eGFR could be calculated using the 2021 Chronic Kidney Disease Epidemiology Collaboration equation. Based on sex-specific distributions of eGFR stratified by age quintiles, we classified patients into low (<5th percentile), normal (5-95th percentile) and high eGFR (>95th percentile). The primary outcome was a composite of any 30-day major adverse outcomes, including: death, reoperation, cardiac arrest, myocardial infarction and stroke. Secondary outcomes included 30-day infectious complications, venous thromboembolism (VTE), bleeding requiring transfusion, prolonged length of stay and unplanned readmission. After matching for demographic differences, comorbidity burden and operative characteristics, logistic regression models were used to evaluate the association between extremes of eGFR and the outcomes of interest. RESULTS: Of 1 668 447 patients, 84 115 (5.07%) had a high eGFR. High eGFR was not associated with major adverse outcomes (odds ratio [OR] 1.00 [95% confidence interval (CI): 0.97, 1.03]); however, it was associated with reoperation (OR 1.04 [95% CI: 1.00,1.08]), infectious complications (OR 1.14 [95% CI: 1.11, 1.16]), VTE (OR 1.15 [95% CI: 1.09, 1.22]) and prolonged length of stay (OR 1.19 [95% CI: 1.16, 1.21]). CONCLUSION: Our findings support an association between high eGFR and adverse 30-day postoperative outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it