The “Renocentric Theory” of Renal Resistive Index: Is It Time for a Copernican Revolution?
Bibliographic record
Abstract
Ultrasound (US) with duplex Doppler scanning has spread to the capillary level, becoming an irreplaceable tool in daily clinical practice thanks to its characteristics: low cost, repeatability, and noninvasiveness. Moreover, US has become over time more sensitive and accurate; it can be considered an extension of the clinician’s hand. For this reason, it currently represents the ideal tool for first-level diagnostic use in several fields, and is the simplest and most flexible instrument for obtaining morphological and functional information on different organs, including the kidneys. In this issue of The Journal , Gigante, et al 1 propose to assess renal involvement in patients with systemic sclerosis (SSc) through the evaluation of both structural and hemodynamic US measurements, paying particular attention to the Doppler-measured renal resistive index (RRI) and its clinical significance. This index has a relatively recent history and an unfortunate name: resistance index (or resistive index ). It was initially proposed by Gosling and King2 and Pourcelot3 in 1974 to identify the renal vascular diseases through the noninvasive measurement of intrarenal hemodynamics indirectly related to changes in arteriolar resistance. For a long time, the role of RRI has remained confined to renal damage, and it has been used as an important marker to predict the progression of renal function in patients with chronic kidney disease (CKD), diabetes mellitus, or hypertension (HTN). Its prognostic value has been studied only in the context of purely kidney diseases, with inconsistent results4. Over the years many authors have tried to find a correct interpretation of the RRI, and several studies have shown that it was minimally affected by intrarenal resistance: unexpectedly, the correlation between RRI values and changes in renal vascular impedance proved to be weak. Through in vitro studies, Tublin, et al observed that the RRI was dependent on … Address correspondence to Dr. G. Geraci, University of Palermo, Via del Vespro 141, 90127 Palermo, Italy. E-mail: giulio.geraci{at}unipa.it
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".