Literature DB >> 34006120

EXPRESS: Routine use of natriuretic peptides: lessons from a Big Data analysis.

Francois-Xavier Goudot1, Sonia Msadek1, Tanissia Boukertouta1, Pierre-Olivier Schischmanoff2, Christophe Meune3.   

Abstract

BACKGROUND: Natriuretic peptides (NPs) have broad indications during heart failure (HF) 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 km2 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 NP 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 9,188 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 â¥75y 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 NPs 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.

Entities:  

Keywords:  Cardiology; Peptide hormones

Year:  2021        PMID: 34006120     DOI: 10.1177/00045632211020779

Source DB:  PubMed          Journal:  Ann Clin Biochem        ISSN: 0004-5632            Impact factor:   2.057


  1 in total

1.  Big Data Analysis and Application of Liver Cancer Gene Sequence Based on Second-Generation Sequencing Technology.

Authors:  Chaohui Xiao; Fuchuan Wang; Tianye Jia; Liru Pan; Zhaohai Wang
Journal:  Comput Math Methods Med       Date:  2022-08-16       Impact factor: 2.809

  1 in total

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