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Article Dans Une Revue Annals of Clinical Biochemistry Année : 2021

Routine use of natriuretic peptides: Lessons from a big data analysis

Fx Goudot
S Msadek
  • Fonction : Auteur
T Boukertouta
  • Fonction : Auteur
C Meune

Résumé

Background Natriuretic peptides have broad indications during heart failure and the detection of left ventricular dysfunction in high-risk patients. They can also be used for the diagnosis/management of other cardiac diseases. However, very little is known regarding their use in routine practice. Methods We examined all biological tests performed from February 2010 to August 2015 in two districts from the French Brittany, covering 13,653 km 2 and including 22,265 physicians. We report the settings and conditions of N-terminal pro-B-type natriuretic peptide (NT-proBNP) measurements (the only locally natriuretic peptide available). Results From a total of 3,606,432 tests requested in 557,650 adult (older than 20 years) patients, only 56,653 (1.6%) included at least one NT-proBNP measurement. NT-proBNP measurements gradually increased, from 9188 in 2011 to 12,938 in 2014 ( P < 0.001). Most NT-proBNP tests were measured in urban laboratories (72.7%) and in private (62.9%) non-hospital/clinics laboratories; they were mostly ordered by general practitioners (66% compared with 11% by cardiologists). The number of NT-proBNP measurements increased with age up to 80–90 years, and 70.3% of tests were measured in ≥75 years patients. Creatinine and electrolytes were not associated with NT-proBNP in 15.8% and 19.7% of tests, respectively. Conclusion Among a very large cohort, we observed that natriuretic peptides remain largely undermeasured. NT-proBNP is mostly measured in elderly patients, and its interpretation may be hazardous in up to 16% of all individuals because no measurement of creatinine was associated to NT-proBNP.
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Dates et versions

hal-03946271 , version 1 (19-01-2023)

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Fx Goudot, S Msadek, T Boukertouta, Po Schischmanoff, C Meune. Routine use of natriuretic peptides: Lessons from a big data analysis. Annals of Clinical Biochemistry, 2021, 58 (5), pp.481-486. ⟨10.1177/00045632211020779⟩. ⟨hal-03946271⟩
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