Clinicians often need to know whether a new method of measurement is equivalent to an established one already in clinical use. This article reviews the methodology of a method-comparison study to assist the clinician with the conduct and evaluation of such studies. Temperature data from 1 subject are used to illustrate the procedures. Although one would not make decisions on the basis of the findings from 1 subject, the large number of paired measurements in the data set permits its use for illustrative purposes. Currently available software eliminates the need for tedious statistical computation but does not reduce the burden of understanding the concepts underlying a method-comparison study and accurate interpretation of the findings.

Clinicians often need to know if a new method of measurement is equivalent to an established one already in clinical use. This paper reviews the methodology of a method-comparison study to assist the clinician with the conduct and evaluation of such studies. Temperature data from one subject are used to illustrate the procedures. Although one would not make decisions based on the findings from one subject, the large number of paired measurements in the data set permits its use for illustrative purposes. Currently available software eliminates the need for tedious statistical computation, but does not reduce the burden of understanding the concepts underlying a method-comparison study and accurate interpretation of the findings. KeywordsBias; Clinical Measurement; Method-comparison; Precision; Temperature With the rapid development and adoption of critical care technology, clinicians increasingly need to know if the newest technique is equivalent to that in current use. Such a question can be answered with a method-comparison study. For example, when noninvasive infrared thermometers were introduced, a plethora of studies was published reporting comparisons of body temperature values when measured simultaneously with the infrared thermometer and such established thermal sensors as the pulmonary artery catheter. [1][2][3][4][5] Other examples of method-comparisons include arterial pulse contour versus pulmonary artery thermodilution cardiac output and point-of-care versus laboratory testing of blood glucose levels. [6][7][8] The basic indication for a method-comparison study is the need to determine if two methods for measuring the same thing (e.g., body temperature, cardiac output) do so in an equivalent manner. The clinical question is one of substitution: Can one measure X with either Method A or Method B and get the same results?In this paper the author discusses, and illustrates with two examples, the design, analysis and interpretation of a method-comparison study. The examples use partial data from a published report of in vitro and in vivo testing of multiple methods of measuring core body temperature in a pre-clinical critical care laboratory setting. 9 Clinicians may wish to conduct a method-comparison study before adopting new technology in practice. This paper provides information on how to do so. At the very least, the information should help clinicians interpret the findings of method-comparison studies encountered in the literature. NIH Public Access Method-Comparison MethodologyA review of terminology precedes discussion of methodology as statistical reporting terms are used inconsistently in the literature. 10 "Accuracy" and "precision" are used often when "bias" and "repeatability" are the properties being assessed. Accuracy is the degree to which an instrument measures the real value of a variable and is assessed by comparing the measurement method with a gold standard that has been calibrated to be highly accurate. In a methodcomparison study, however, the investigator is comparing a l...

• Background Oral care and head-of-bed elevation are interventions to decrease risk of aspiration pneumonia in hospitalized patients. In a previous study, nurses’ self-reports of how often they performed oral care did not match documented provision of such care. • Objectives To replicate the original study and estimate instrument reliability. • Methods A cross-sectional design was used, and survey data from nursing personnel and bedside observational data from 9 intensive care units were collected. • Results A total of 181 surveys (47%) were returned, and data were collected from 436 bedsides. Reported frequencies of oral care and use of oral care products differed between nonintubated and intubated patients (P<.001). The mean documented frequency of oral care for nonintubated patients was 1.8 (SD 1.5); self-reported frequency was 3 (SD 2.4). The mean documented frequency of oral care for intubated patients was 3.3 (SD 1.8); self-reported frequency was 4.2 (SD 2.1). Documented oral care frequency differed by unit (P = .006) and intubation status (P < .001). Mean observed head-of-bed position was 38° (SD 24°) for nonintubated patients and 23° (SD 12°) for intubated patients (P < .001). Intubation status, but not unit, affected observed head-of-bed position (P < .001). Three survey items had adequate reliability evidence (r=0.70). Interrater reliability for bedside data collection was 96% or greater. • Conclusions Despite inadequate estimates of survey reliability, findings generally were comparable to results of the original study; nurses report more frequent oral care than is documented. Intensive care nurses elevate the head of patients’ beds in accordance with self-reports.

Investigators commonly assess intra- and inter-assay coefficients of variation (CVs) to estimate the precision of salivary cortisol enzyme immunoassay (EIA). However, little guidance is available as to which samples to use for CV assessment. The purposes of this methodological study were to compare differences in intra- and inter-assay CVs (a) among controls, standards, and/or unknown samples; and (b) between fresh and previously frozen saliva. A total of 174 duplicates (controls = 58, standards = 48, and unknowns = 68) were tested. The unknowns were from 34 students; all student saliva was assayed as both fresh and frozen samples. All samples were assayed in duplicate, using a commercial salivary cortisol EIA kit, by the same technician with the same equipment. A priori criteria for intra- and inter-assay CV, respectively, were ≤ 4% and ≤ 7%, and a was .05 for CV differences. Mean intra-assay CVs for controls, standards, unknowns, and combined samples were ≤ 2.5%, and mean inter-assay CVs were ≤ 2.8%. Mean intra-assay CVs were 2.2% for fresh saliva and 1.5% for frozen samples. Comparisons showed no significant differences in intra- or inter-assay CV among controls, standards, and/or unknown samples. Inter-assay CV was significantly different between fresh and previously frozen saliva (p = .043), with fresh saliva CV higher than frozen; the difference was not meaningful because all evaluations showed minimal measurement error. In conclusion, results indicate that estimation of precision can be achieved by testing of controls, standards, or unknowns and with either fresh or frozen saliva in this population.

A unit-based expert nurse can increase patient-focused care.

Accurate measurement of core body temperature is important in monitoring the thermal state of the body. It is one technique for assessing how the animal adapts to changing internal and external environments. Temperature monitoring is ubiquitous in research protocols, but is often used without assessing the assumptions of the performance of the temperature measurement systems that are used. Furthermore, little attention may be given to equivalence of various sites of measurement. Protocols with swine that undergo anaesthesia are particularly at risk because swine have a genetic susceptibility to the myopathic condition of malignant hyperthermia (Gronert 1980). Vigilant monitoring, assessment, and treatment of rapid core body temperature changes are essential, and measurement needs to re ect real-time thermal state reliably over time.Although the literature on comparisons of methods of body temperature measurement is extensive, very few studies have measured nearly continuous temperature with a time series design. The time series design permits

Experimental control and mathematical techniques increase confidence that results of circadian temperature rhythm studies reflect true changes in the circadian timing system versus coupling with exogenous synchronizers. Masking effects represent confounding influences in studies that are concerned with the endogenous temperature rhythm. Because it is technically difficult to measure directly the behavior of the endogenous timing system, marker rhythms are used as proxy measures. However in addition to entraining, the external environment exerts a direct masking effect on the monitored rhythm. Methods for measuring circadian temperature rhythm are reviewed in this article. Constant routine, forced desynchrony, and purification methods represent attempts, at an experimental or mathematical level, to remove masking effects and more accurately capture the endogenous circadian temperature rhythm. Exogenous factors have not been subjected to the same scrutiny as the endogenous features of circadian temperature rhythm. But it is the environmental context, the extent to which the endogenous features are adaptively modified by the field environment, that will ultimately determine the biological value of circadian temperature rhythm to the organism. Thus, nurse investigators are encouraged to use rigorous methods to study both endogenous circadian temperature rhythm and exogenous rhythms.

The purposes of this pilot study are to describe the 24-hr patterns of dyspnea, fatigue, and peak expiratory flow rate (PEFR) in patients with chronic obstructive pulmonary disease (COPD) and examine their interrelationships. The repeated-measures design protocol involved 10 patients with moderate to severe COPD who self-assessed dyspnea, fatigue, and PEFR five times a day for 8 days. Circadian rhythms were documented by single cosinor analysis in 40% of the participants for dyspnea, 60% for fatigue, and 60% for PEFR. The 8-day, 24-hr means of dyspnea and fatigue were moderately correlated; 70% of the sample displayed significant correlations. The means of PEFR and both dyspnea and fatigue were weakly negatively correlated. The findings suggest that circadian rhythm in lung function may not be temporally coupled with the circadian rhythm in dyspnea and fatigue in all patients and that the mean self-perceived levels of dyspnea and fatigue are moderately related.