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1.
Acute Med ; 19(1): 15-20, 2020.
Article in English | MEDLINE | ID: mdl-32226952

ABSTRACT

BACKGROUND: counting respiratory rate over 60 seconds can be impractical in a busy clinical setting. METHODS: 870 respiratory rates of 272 acutely ill medical patients estimated from observations over 15 seconds and those calculated by a computer algorithm were compared. RESULTS: The bias of 15 seconds of observations was 1.85 breaths per minute and 0.11 breaths per minute for the algorithm derived rate, which took 16.2 SD 8.1 seconds. The algorithm assigned 88% of respiratory rates their correct National Early Warning Score points, compared with 80% for rates from 15 seconds of observation. CONCLUSION: The respiratory rates of acutely ill patients are measured nearly as quickly and more reliably by a computer algorithm than by observations over 15 seconds.


Subject(s)
Diagnosis, Computer-Assisted , Hospitalization , Mobile Applications , Respiratory Rate , Adult , Algorithms , Humans
2.
QJM ; 112(7): 513-517, 2019 Jul 01.
Article in English | MEDLINE | ID: mdl-30888422

ABSTRACT

BACKGROUND: Respiratory rate is often measured over a period shorter than 1 min and then multiplied to produce a rate per minute. There are few reports of the performance of such estimates compared with rates measured over a full minute. AIM: Compare performance of respiratory rates calculated from 15 and 30 s of observations with measurements over 1 min. DESIGN: A prospective single center observational study. METHODS: The respiratory rates calculated from observations for 15 and 30 s were compared with simultaneous respiratory rates measured for a full minute on acutely ill medical patients during their admission to a resource poor hospital in sub-Saharan Africa using a novel respiratory rate tap counting software app. RESULTS: There were 770 respiratory rates recorded on 321 patients while they were in the hospital. The bias (limits of agreement) between the rate derived from 15 s of observations and the full minute was -1.22 breaths per minute (bpm) (-7.16 to 4.72 bpm), and between the rate derived from 30 s and the full minute was -0.46 bpm (-3.89 to 2.97 bpm). Rates observed over 1 min that scored 3 National Early Warning Score points were not identified by half the rates derived from 15 s and a quarter of the rates derived from 30 s. CONCLUSION: Practice-based evidence shows that abnormal respiratory rates are more reliably detected with measurements made over a full minute, and respiratory rate measurement 'short-cuts' often fail to identify sick patients.


Subject(s)
Acute Disease , Monitoring, Physiologic/methods , Respiratory Rate , Adult , Aged , Female , Hospitalization , Humans , Male , Middle Aged , Prospective Studies , Risk Assessment , Software
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