Renal blood flow, fractional excretion of sodium and acute kidney injury
Bibliographic record
Abstract
PURPOSE OF REVIEW: Global renal blood flow is considered pivotal to renal function. Decreased global renal blood flow (decreased perfusion) is further considered the major mechanism of reduced glomerular filtration rate responsible for the development of acute kidney injury (AKI) in critically ill patients. Additionally, urinary biochemical tests are widely taught to allow the differential diagnosis of prerenal (functional) AKI and intrinsic [structural AKI (so-called acute tubular necrosis)]. In this review we will examine recent evidence regarding these two key clinical paradigms. RECENT FINDINGS: Recent animal experiments and clinical studies in humans using cine-phase contrast magnetic resonance technology are not consistent with the decreased perfusion paradigm. They suggest instead that changes in the intra-renal circulation including modification in efferent arteriolar function and intra-renal shunting are much more likely to be responsible for AKI, especially in sepsis. Similarly, recent human studies indicate the urinary biochemistry has limited diagnostic or prognostic ability and is dissociated form biomarker and microscopic evidence of tubular injury. SUMMARY: Intra-renal microcirculatory changes are likely more important than changes in global blood flow in the development of AKI. Urinary biochemistry is not a clinically useful diagnostic or prognostic tool in critically ill patients at risk of or with 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".