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Record W1499459667 · doi:10.25011/cim.v30i3.1755

BNP after Cardiac Surgery in Patients with Normal Ventricular Function

2007· article· en· W1499459667 on OpenAlexvenueno aff
Elio Venturini, Antonella Leoni, C Marabotti, Alessandro Scalzini, Roberto Testa

Bibliographic record

VenueClinical and investigative medicine · 2007
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineCardiologyVentricleHeart failureAtrial fibrillationBrain natriuretic peptideCardiac surgeryNatriuretic peptideDiastoleBlood pressure

Abstract

fetched live from OpenAlex

Background: Brain natriuretic peptide (BNP) is proven marker for diagnosis and stratification of patients (P) with heart failure; furthermore it can be useful for differential diagnosis of dyspnea, for detection of diastolic dysfunction and as guide and monitoring of therapy. Acute coronary syndrome, atrial fibrillation (AF), aortic stenosis and hypertrophic cardiomyopathy are other conditions in which the BNP can be raised. Little is know about the level of BNP in P undergone cardiac surgery. Aim of the study was to detect the concentration of BNP immediately after CABG and to follow the course during cardiac rehabilitation (CR). Methods: we studied 18 P (mean age 67.8±11.2 yrs) 9.1±3.6 days after surgery and we repeated the evaluation after our program of CR, in average 56 days of distance from CABG. In each P was performed an echocardiogram (inclusive study of right ventricle, diastolic function and DTI), a determination of BNP (NT-proBNP) and also the six-minute walking test (SMWT). Every effort was made for not varying the therapy during the period of observation. Exclusion criteria were: MI in the last 3 months, heart and renal failure, use of inotropics drugs and AF after cardiac surgery. Results: the concentration of BNP was high in both determinations even if it lowered in the second (BNP1 vsBNP2: pg/ml 1225.1±873.2 vs 708.7±741 P < 0.001); also the left atrial volume decreased ( ml 50.7±11.6 vs 46.4±8.8 P < 0.01) while the ejection fraction didn't vary, (EF1 vs EF2: 57.2±6.7 vs 59.8±9.1 ns). There was an increase of the distance crossed to the SMWT ( mt 254.7±65.4 vs 435.3±69.6 P < 0.001); glycaemia and creatinine values were normal in both determinations while the hemoglobin increased (11.5±1.2 vs 13.2±1.3 P < 0.01). Other echo parameters(E/A, E/Em, TAPSE, PAPs ) were not meaningfully varied with the exception of DT (221.6±66.3 vs 253.8±72.3 P < 0.05). We have not found correlations between Ä BNP and: Ä LAV, Ä SMWT, Ä E/A or Ä E/Em. Instead, the relationship was statistically significant with the DT (r: 0.78 P < 0.01). Also the second determination of the BNP had the followings relationships: *** Table in Full Text PDF. *** Conclusion: after CABG, the level of BNP is elevated also in P with normal ventricular function; the most elevated values were in the immediate proximity of surgery for then being reduced during CR program. The improvement of the diastolic function, pointed out by the increase of the DT, it seems to correlate with the reduction of natriuretic peptides; the relationship of the other indexes of diastolic function, of the EF and of the PAPs with the BNP is detectable only at the second collecting. Is possible to infer that conditions in narrow relationship with the surgery (extracorporeal circulation, quick variations of circulating volume, direct stimulation of the myocardium and impaired lung function due to sternotomy) can induce the liberation of the BNP; this can conceal the association between the incretion of BNP and the indexes of ventricular function.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.291
Teacher spread0.234 · 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 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

Citations0
Published2007
Admission routes1
Has abstractyes

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