Preoperative renal parenchymal volumetrics and prediction of renal insufficiency following radical nephrectomy.
Bibliographic record
Abstract
471 Background: To identify predictors of post-operative renal insufficiency by analyzing pre-operative imaging volumetrics among patients undergoing radical nephrectomy (RN) for renal cell carcinoma (RCC). Methods: A retrospective review of all patients undergoing RN for RCC between January 2011 and August 2013 was performed. Estimated glomerular filtration rate (eGFR) was calculated employing the modified diet in renal disease (MDRD) formula using the pre-operative and one-year serum creatinine values. Pre-operative and 1-year post-operative CT/MRI scans were reviewed. AW Volume Share 5 workstations were utilized to calculate volumes. Statistical analysis using Chi-square and Fisher exact test were employed. Results: Of the 147 patients undergoing RN 65 patients met the inclusion criteria. Patients with smaller tumor volumes (<375 cm3) were more likely to have a greater decline in their post-operative eGFRs (>35%) when compared to patients with larger tumors (58 vs. 21%; p=0.0165). Patients with a pre-operative eGFR >60 ml/min/1.73m2 had a greater (>25%) drop in their 1-year eGFR (81 vs. 47%; p=0.0084). A smaller volume (<150 cm3) of parenchyma of the ipsilateral kidney was associated less compensatory (<25%) hypertrophy (100 vs. 69, p=0.0348). Smaller tumors (<300 cm3) were more likely to have a greater degree (>10%) of compensatory hypertrophy (78 vs. 43% p=0.0234) and less blood loss (<300 cc, 82 vs. 44%, p=0.0082). Older patients and patients with a combined history of diabetes (DM) and hypertension (HTN) were more likely to have compensatory (>25%) hypertrophy (age >65, 100% vs. 31%, p<0.001; DM+HTN, 100% vs. 75%, p=0.0084). The degree of compensatory hypertrophy (>25%) however, did not predict 1-year eGFR (35%) change (p=0.2203). New kidney disease (eGFR<60 ml/min/1.73m2) occurred in 71% patients. Conclusions: Volumetric imaging shows promising potential and may become a valuable tool in predicting post-operative renal insufficiency for patients undergoing nephrectomy and should be investigated further both in RN and partial nephrectomy cohorts.
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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 | 0.000 | 0.002 |
| 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".