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Current clinical methods of measurement of respiratory rate give imprecise values

ABSTRACT: Background Respiratory rate is a basic clinical measurement used for illness assessment. Errors in measuring respiratory rate are attributed to observer and equipment problems. Previous studies commonly report rate differences ranging from 2 to 6?breaths·min?1 between observers. Methods To study why repeated observations should vary so much, we conducted a virtual experiment, using continuous recordings of breathing from acutely ill patients. These records allowed each breathing cycle to be precisely timed. We made repeated random measures of respiratory rate using different sample durations of 30, 60 and 120?s. We express the variation in these repeated rate measurements for the different sample durations as the interquartile range of the values obtained for each subject. We predicted what values would be found if a single measure, taken from any patient, were repeated and inspected boundary values of 12, 20 or 25?breaths·min?1, used by the UK National Early Warning Score, for possible mis-scoring. Results When the sample duration was nominally 30?s, the mean interquartile range of repeated estimates was 3.4?breaths·min?1. For the 60?s samples, the mean interquartile range was 3?breaths·min?1, and for the 120?s samples it was 2.5?breaths·min?1. Thus, repeat clinical counts of respiratory rate often differ by >3?breaths·min?1. For 30?s samples, up to 40% of National Early Warning Scores could be misclassified. Conclusions Early warning scores will be unreliable when short sample durations are used to measure respiratory rate. Precision improves with longer sample duration, but this may be impractical unless better measurement methods are used. In acutely ill patients, the usual 30?s to count breathing are insufficient to give a reliable measurementhttps://bit.ly/31DNhKU

SUBMITTER: Drummond G

PROVIDER: S-EPMC7520170 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Project description:BackgroundA number of orbital diseases may be evaluated based on the degree of exophthalmos, but there is still no gold standard method for the measurement of this parameter. In this study we compare two exophthalmometry measurement methods (digital photography and clinical) with regard to reproducibility and the level of correlation and agreement with measurements obtained with Computerized Tomography (CT) measurements.MethodsSeventeen patients with bilateral proptosis and 15 patients with normal orbits diseases were enrolled. Patients underwent orbital CT, Hertel exophthalmometry (HE) and standardized frontal and side facial photographs by a single trained photographer. Exophthalmometry measurements with HE, the digital photographs and axial CT scans were obtained twice by the same examiner and once by another examiner. Pearson correlation coefficient (PCC) was used to assess correlations between methods. Validity between methods was assessed by mean differences, interintraclass correlation coefficients (ICC's), and Bland-Altman plots.ResultsMean values were significantly higher in the proptosis group (34 orbits) than in the normal group (30 orbits), regardless of the method. Within each group, mean digital exophthalmometry measurements (24.32 ± 5.17 mm and 18.62 ± 3.87 mm) were significantly greater than HE measurements (20.87 ± 2.53 mm and 17.52 ± 2.67 mm) with broader range of standard deviation. Inter-/intraclass correlation coefficients were 0.95/0.93 for clinical, 0.92/0.74 for digital, and 0.91/0.95 for CT measurements. Correlation coefficients between HE and CT scan measurements in both groups of subjects (r = 0.84 and r = 0.91, p < 0.05) were greater than those between digital and CT scan measurements (r = 0.61 and r = 0.75, p < 0.05). On the Bland-Altman plots, HE showed better agreement to CT measurements compared to the digital photograph method in both groups studied.ConclusionsAlthough photographic digital exophthalmometry showed strong correlation and agreement with CT scan measurements, it still performs worse than and is not as accurate as clinical Hertel exophthalmometry. This trail is registered with NCT01999790.

Project description:Eighteen-month-long randomized, placebo-controlled clinical trials are common for phase II and phase III drug development for Alzheimer's disease (AD). Yet, no 18-month trial has shown statistically significant outcomes favoring the test drug. We examined characteristics and underlying assumptions of these trials by assessing the placebo groups.We searched the clinicaltrials.gov registry for randomized, placebo-controlled clinical trials for AD of at least 18-month duration and extracted demographic, clinical, and trials characteristics, and change in main outcomes from the placebo groups. We obtained additional information from presentations, abstracts, publications, and sponsors.Of 23 trials identified, 11 were completed and had baseline data available; nine had follow-up data available; 17 were phase III. General inclusion criteria were very similar except that minimum Mini-Mental State Examination (MMSE) scores varied from 12 to 20. Sample sizes ranged from 402 to 1,684 for phase III trials and 80 to 400 for phase II. Cholinesterase inhibitor use was from 53% to 100%, and memantine use was from 13.5% to 78%. The AD Assessment Scale-cognitive (ADAS-cog) was the co-primary outcome in all trials; and activities of daily living, global severity, or global change ratings were the other co-primaries. APOE epsilon4 genotype carriers ranged from 58% to 67%; mean baseline ADAS-cog was 17.8 to 24.2. ADAS-cog worsening in the placebo groups during 18 months ranged from 4.34 to 9.10, with standard deviations from 8.17 to 9.39, increasing during 18 months.Inclusion criteria are essentially similar to earlier 6-month and 12-month trials in which cholinesterase inhibitors were not allowed, as were mean ADAS-cog rates of change. Yet increasing variability and relatively little change overall in the ADAS-cog placebo groups, eg, about 25% of patients do not worsen by more than 1 point, might make it more unlikely than previously assumed that a modestly effective drug can be reliably recognized, especially when the drug might work only to attenuate decline in function and not to improve function. These observations would be strengthened by pooling individual trials data, and pharmaceutical sponsors should participate in such efforts.

Project description:Identifying patients with acute respiratory distress syndrome (ARDS) is a recognized challenge. Experts often have only moderate agreement when applying the clinical definition of ARDS to patients. However, no study has fully examined the implications of low reliability measurement of ARDS on clinical studies.To investigate how the degree of variability in ARDS measurement commonly reported in clinical studies affects study power, the accuracy of treatment effect estimates, and the measured strength of risk factor associations.We examined the effect of ARDS measurement error in randomized clinical trials (RCTs) of ARDS-specific treatments and cohort studies using simulations. We varied the reliability of ARDS diagnosis, quantified as the interobserver reliability (?-statistic) between two reviewers. In RCT simulations, patients identified as having ARDS were enrolled, and when measurement error was present, patients without ARDS could be enrolled. In cohort studies, risk factors as potential predictors were analyzed using reviewer-identified ARDS as the outcome variable.Lower reliability measurement of ARDS during patient enrollment in RCTs seriously degraded study power. Holding effect size constant, the sample size necessary to attain adequate statistical power increased by more than 50% as reliability declined, although the result was sensitive to ARDS prevalence. In a 1,400-patient clinical trial, the sample size necessary to maintain similar statistical power increased to over 1,900 when reliability declined from perfect to substantial (??=?0.72). Lower reliability measurement diminished the apparent effectiveness of an ARDS-specific treatment from a 15.2% (95% confidence interval, 9.4-20.9%) absolute risk reduction in mortality to 10.9% (95% confidence interval, 4.7-16.2%) when reliability declined to moderate (??=?0.51). In cohort studies, the effect on risk factor associations was similar.ARDS measurement error can seriously degrade statistical power and effect size estimates of clinical studies. The reliability of ARDS measurement warrants careful attention in future ARDS clinical studies.

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Current clinical methods of measurement of respiratory rate give imprecise values

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