Literature DB >> 28134672

Effects of room environment and nursing experience on clinical blood pressure measurement: an observational study.

Meng Zhang1, Xuemei Zhang, Fei Chen, Birong Dong, Aiqing Chen, Dingchang Zheng.   

Abstract

OBJECTIVE: This study aimed to examine the effects of measurement room environment and nursing experience on the accuracy of manual auscultatory blood pressure (BP) measurement.
MATERIALS AND METHODS: A training database with 32 Korotkoff sounds recordings from the British Hypertension Society was played randomly to 20 observers who were divided into four groups according to the years of their nursing experience (i.e. ≥10 years, 1-9 years, nursing students with frequent training, and those without any medical background; five observers in each group). All the observers were asked to determine manual auscultatory systolic blood pressure (SBP) and diastolic blood pressure (DBP) both in a quiet clinical assessment room and in a noisy nurse station area. This procedure was repeated on another day, yielding a total of four measurements from each observer (i.e. two room environments and two repeated determinations on 2 separate days) for each Korotkoff sound. The measurement error was then calculated against the reference answer, with the effects of room environment and nursing experience of the observer investigated.
RESULTS: Our results showed that there was no statistically significant difference for BPs measured under both quiet and noisy environments (P>0.80 for both SBP and DBP). However, there was a significant effect on the measurement accuracy between the observer groups (P<0.001 for both SBP and DBP). The nursing students performed best with overall SBP and DBP errors of -0.8±2.4 and 0.1±1.8 mmHg, respectively. The SBP measurement error from the nursing students was significantly smaller than that for each of the other three groups (all P<0.001).
CONCLUSION: Our results indicate that frequent nursing trainings are important for nurses to achieve accurate manual auscultatory BP measurement.

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Year:  2017        PMID: 28134672     DOI: 10.1097/MBP.0000000000000240

Source DB:  PubMed          Journal:  Blood Press Monit        ISSN: 1359-5237            Impact factor:   1.444


  2 in total

1.  Deep learning-based automatic blood pressure measurement: evaluation of the effect of deep breathing, talking and arm movement.

Authors:  Fan Pan; Peiyu He; Fei Chen; Xiaobo Pu; Qijun Zhao; Dingchang Zheng
Journal:  Ann Med       Date:  2019 Nov - Dec       Impact factor: 4.709

2.  Quantitative Assessment of Blood Pressure Measurement Accuracy and Variability from Visual Auscultation Method by Observers without Receiving Medical Training.

Authors:  Wenai Chen; Fei Chen; Yong Feng; Aiqing Chen; Dingchang Zheng
Journal:  Biomed Res Int       Date:  2017-12-20       Impact factor: 3.411

  2 in total

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