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Body Mass Index and Angiotensin-Dependent Control of the Renal Circulation in Healthy Humans

2005· article· en· W2170919561 on OpenAlexfundno aff
Sofia B. Ahmed, Naomi D.L. Fisher, Radomir Stevanovic, Norman K. Hollenberg

Bibliographic record

VenueHypertension · 2005
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsnot available
FundersU.S. Public Health ServiceNational Institutes of HealthNational Heart, Lung, and Blood InstituteKidney Foundation of Canada
KeywordsCaptoprilInternal medicineMedicineEndocrinologyBody mass indexPlasma renin activityRenin–angiotensin systemAngiotensin IIRenal circulationRenal blood flowOverweightKidneyBlood pressure

Abstract

fetched live from OpenAlex

Obesity is increasingly recognized as a risk factor for renal disease, but the mechanism is unclear. Renal plasma flow response to captopril, as an index of renin-angiotensin system activity, was measured by para-aminohippurate clearance technique in 100 healthy, normotensive subjects in balance on a high-salt diet. Of the 100 subjects, body mass index exceeded 25 in 56 and exceeded 30 in 22. The average vasodilator response to captopril was 27+/-7 mL/min per 1.73 m2 (P<0.0001). After adjustment for other predictors of the renal plasma flow response to captopril using a multivariate linear regression model, there was a highly significant relationship between age- and plasma renin activity-adjusted body mass index and the renal plasma flow response to captopril; however, a quadratic model provided a substantially better fit (r=0.55; P<0.0001; P=0.03 versus linear correlation). The strong association between increasing body mass index and angiotensin-dependent control of the renal circulation suggests that this may be a mechanism by which obesity contributes to renal disease. Weight loss should be considered in the overweight or obese patient for renal protection.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.014
GPT teacher head0.242
Teacher spread0.228 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations95
Published2005
Admission routes1
Has abstractyes

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