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Impaired Baroreceptor Control of Renal Sympathetic Activity in Human Chronic Heart Failure

2004· article· en· W2138933836 on OpenAlexaff
Abdul Al‐Hesayen, John D. Parker

Bibliographic record

VenueCirculation · 2004
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsMedicineBaroreceptorHeart failureCardiologyInternal medicineChronic renal failureSympathetic nervous systemBaroreflexSympathetic activityHeart rateBlood pressure

Abstract

fetched live from OpenAlex

BACKGROUND: The regulation of renal sympathetic activity in the setting of heart failure is largely unexplored. We used the norepinephrine spillover method to address the hypothesis that baroreflex control of renal sympathetic activity is blunted in heart failure. METHODS AND RESULTS: Twenty-two patients were studied, 11 in a group with heart failure and 11 in a group with normal ventricular function. In both groups, renal norepinephrine spillover was assessed in response to sodium nitroprusside infused to steady-state conditions. Sodium nitroprusside resulted in significant reductions in mean systemic arterial pressure (normal group, -13+/-1% [mean+/-SEM]; heart failure group, -12+/-1%). In response to nitroprusside, there was an 85+/-34% increase in renal norepinephrine spillover in the normal group (from 537+/-84 to 840+/-140 pmol/min, P<0.05). Despite similar hemodynamic responses to nitroprusside in the heart failure group, renal norepinephrine spillover was unchanged (from 1420+/-153 to 1387+/-161 pmol/min, P=NS), a response that was significantly different from that seen in the normal group. CONCLUSIONS: In patients with heart failure, compared with those with normal ventricular function, renal sympathetic activity did not change in response to a steady-state infusion of sodium nitroprusside. This result provides evidence for reduced baroreflex control of renal sympathetic activity in heart failure.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.377

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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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 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

Citations25
Published2004
Admission routes1
Has abstractyes

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