Prediction of Acute Kidney Injury After Cardiac Surgery With Combined Arterial and Venous Intrarenal Doppler
Bibliographic record
Abstract
Background: Acute kidney injury (AKI) occurs in up to 50% of cardiac surgical patients and is often hemodynamically mediated. Point-of-care ultrasound is a non-invasive tool that has the potential to characterize intrarenal hemodynamics and predict the risk of AKI. Objectives: We aimed to determine the predictive characteristics of intrarenal arterial and venous Doppler markers for postoperative AKI in cardiac surgical patients. Design: This study is the secondary analysis of a prospective cohort study. Setting: This study is carried out in a care academic cardiac surgical center in Montreal, Quebec, Canada. Patients: Adult patients undergoing cardiac surgery with the use of cardiopulmonary bypass. Measurements: Point-of-care ultrasound assessments were performed preoperatively and at intensive care unit admission. Arterial measurements included the renal resistive index (RRI) and intrarenal artery velocity-time integral normalized to peak systolic velocity (VTI/PSV). Venous measurements included intrarenal venous flow (IRVF) pattern and renal venous stasis index (RVSI). Methods: We used area under the receiving operating characteristic curves (AUCs) with net reclassification index (NRI) and multivariable logistic regression to determine predictive characteristics for postoperative AKI. Furthermore, we used hierarchical clustering to identify potential groups with similar Doppler parameters and performed comparisons of patients' characteristics and outcomes between groups. Results: We included 136 patients with 47 (34.6%) developing postoperative AKI. At intensive care unit admission, arterial indices showed similar discrimination for the prediction of AKI (RRI: AUC = 0.64; 95% confidence interval (CI) = 0.55 to 0.74; and VTI/PSV: AUC = 0.67; 95% CI = 0.57 to 0.77). Venous Doppler indices including IRVF patterns (AUC = 0.64; 95% CI = 0.53 to 0.74) and RVSI (AUC = 0.60; 95% CI = 0.50 to 0.71) also showed similar performance. The combined model of RRI and IRVF pattern (AUC = 0.69; 95% CI = 0.59 to 0.78) improved the prediction of AKI compared to either RRI (NRI = 0.50; 95% CI = 0.17 to 0.84) or IRVF pattern (NRI = 0.38; 95% CI = 0.04 to 0.70) alone. Through hierarchical clustering, we identified 3 groups (1: low RRI, 2: high RRI/low RVSI, and 3: high RRI/high RVSI) with different patient characteristics and outcomes. The patient in group 3 had a higher risk of AKI and worse clinical outcomes compared with other groups. Limitations: Single-center design in cardiac surgical patients limits generalizability. Conclusions: Although more complex indices of intrarenal Doppler indices including the VTI/PSV and RVSI did not improve prediction of postoperative AKI, combining RRI and IRVF pattern improved risk prediction for AKI. Intrarenal arteriovenous Doppler subphenotypes identified patient groups at high risk of postoperative AKI.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".