MétaCan
Menu
← Back to cohort
Record W4396990685 · doi:10.1681/asn.20213210s1366c

Functional Sodium Magnetic Resonance Imaging of Human Kidney

2021· article· en· W4396990685 on OpenAlexaff
Sandrine Lemoine, Alireza Akbari, Fabio R. Salerno, Timothy J. Scholl, Guido Filler, Andrew A. House, Christopher W. McIntyre

Bibliographic record

VenueJournal of the American Society of Nephrology · 2021
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsMagnetic resonance imagingMedicineSodiumKidneyNuclear magnetic resonanceHuman kidneyChemistryRadiologyInternal medicinePhysics

Abstract

fetched live from OpenAlex

Background: Maintenance of a cortico-medullary concentration gradient (CMG) is required for urine concentration. We explored the ability of 23NaMRI in measuring 1) the dynamics of CMG for the first time compared to urinary osmolarity after a water load and 2) the CMG in kidney disease. Methods: We conducted an exploratory pilot study for 10 healthy controls following water load then 5 cardiorenal patients with kidney disease. 1) Fasting healthy controls provided urine samples to measure osmolarity and baseline 23NaMRI scans were performed. They were instructed to ingest water (15 mL/kg) within 15 minutes. Four subsequent sodium images and urine samples were acquired at 15 min intervals starting one hour after water ingestion. 2) Cardiorenal patients underwent an MRI scan, provided a blood and urine sample, but no water loading. Results: Mean age of the 10 healthy controls was 41.8 ± 15.3 years. In the morning fasting, medulla/cortex ratio was 1.55 ± 0.11 with concurrent urinary osmolarity measured at 814 ± 121 mOsm/L. Mean ± SD fasting urinary osmolarity dropped significantly to 73 ± 14 mOsm/L, p=0.001. Mean medulla/cortex ratio dropped significantly to 1.31 ± 0.09 mOsm/L for maximal dilution, p=0.002. Figure 1 displays changes of 23NaMRI pictures before (A) then 1h (B), 1H15 (C), 1h30 (D) and 1h45 (E) after a water load. Urinary osmolarity and medulla/cortex ratio are significantly correlated, r=0.54, p=0.0001. Mean age of the 5 cardiorenal patients was 76.6 ± 12.2 years, eGFR was 54 ± 37 mL/min/1.73m2. Urinary osmolarity was 498 ± 145 mOsm/L and medulla/cortex ratio was 1.35 ± 0.11. We measured corticomedullary gradient in cardiorenal patient with different level of eGFR to show the ability and feasibility to measure this gradient in pathological settings. Conclusions: We explored CMG dynamically every 15 min in healthy controls and demonstrated significant changes after a water load. We were also able to acquire 23NaMRI pictures in cardiorenal patients with kidney disease with plans for future analyses.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.017
GPT teacher head0.303
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Society of Nephrology→Same topicAdvanced MRI Techniques and Applications→French-language works237,207→