Individual Intraclass Correlation Coefficients Research Articles

Multiple Laser Doppler Flowmetry Probes Increase the Reproducibility of Skin Blood Flow Measurements.

Cutaneous microcirculatory perfusion is commonly measured using laser Doppler flowmetry (LDF) probes, which provide a continuous, non-invasive quantification of skin blood flow (SkBF). However, inhomogeneities in the skin’s microvasculature density contribute to a decrease in reproducibility whenever an LDF probe is removed and replaced, as is the case during pre- and post-intervention or between-day measurements. Therefore, this study aimed to determine whether increasing the total number of individual LDF probes in a localized area improves the reproducibility of the measurement. Seven laser Doppler probes were secured in a custom-made acrylic holder designed to attach to the skin’s surface easily. SkBF, local skin temperature (Tsk), and blood pressure (BP) were assessed in 11 participants (6 M, 5 F, 42 ± 15 years). SkBF and Tsk were measured from the dorsal forearm (arm trial) for 5 min. Next, the multi-laser device was moved to the lateral side of the calf (leg trial), and measurements were obtained for 5 min. Each arm and leg trial was cyclically repeated three times, and all trials were separated by intermissions lasting 10–15 min. The average SkBF and the cutaneous vascular conductance (CVC) from all possible LDF probe combinations were not statistically different across the three arm and leg trials. Two-way mixed-effects models with absolute agreement were used to compute the intraclass correlation coefficient (ICC) for CVC, and the minimum ICC increased with the addition of LDF probes. The ICC of the average CVC from seven LDF probes was 0.96 between the arm trials and 0.91 between the leg trials, which suggests that there is excellent reliability and little difference between trials following the removal and replacement of the device. Moreover, all individual ICC values from ≥3 LDF probe combinations were greater than 0.70 (i.e., good reliability). These data suggest that SkBF measurements with multiple laser Doppler probes in a custom-made holder have excellent reproducibility after replacing the probes within the same participant. Therefore, this application could provide more reproducible assessments between repeated measurements (e.g., before and after exercise or clinical procedures) where the LDF probes must be removed and replaced within the same location.

Concordance between Laboratory and Field Methods for the Assessment of Body Fat in Olympic Combat Athletes: Analysis of the Influence of Adiposity.

Combat sports athletes competing in the same discipline exhibit notable and substantial differences in body weight, body composition (BC) and adiposity. No studies have considered the influence of adiposity levels in the agreement between different BC assessment methods. The aim of this study was to analyze the influence of adiposity in the agreement between different methods used to estimate relative body fat (%BF) in Olympic combat sport athletes. A total of 38 male athletes were evaluated using air displacement plethysmography and dual-energy X-ray absorptiometry (DXA) as laboratory methods, and bioelectrical impedance analysis (BIA), near-infrared interactance (NIR) and anthropometry as field methods. All methods were compared to DXA. Agreement analyses were performed by means of individual intraclass correlation coefficients (ICCs) for each method compared to DXA, Bland–Altman plots and paired Student t-tests. The ICCs for the different methods compared to DXA were analyzed, considering tertiles of %BF, tertiles of body weight and type of sport. For the whole group, individual ICCs oscillated between 0.806 for BIA and 0.942 for anthropometry. BIA showed a statistically significant underestimation of %BF when compared to DXA. The agreement between every method and DXA was not affected by %BF, but it was highest in athletes at the highest %BF tertile (>13%). The ICC between NIR and DXA was poor in 72–82 kg athletes. Our results indicate that field methods are useful for routine %BF analysis, and that anthropometry is particularly appropriate, as it showed the highest accuracy irrespective of the athletes’ adiposity.

Validation of a Semiautomatic Image Analysis Software for the Quantification of Musculoskeletal Tissues.

Accurate quantification of bone, muscle, and their components is still an unmet need in the musculoskeletal field. Current methods to quantify tissue volumes in 3D images are expensive, labor-intensive, and time-consuming; thus, a reliable, valid, and quick application is highly needed. Tissue Compass is a standalone software for semiautomatic segmentation and automatic quantification of musculoskeletal organs. To validate the software, cross-sectional micro-CT scans images of rat femur (n = 19), and CT images of hip and abdomen (n = 100) from the Osteoporotic Fractures in Men (MrOS) Study were used to quantify bone, hematopoietic marrow (HBM), and marrow adipose tissue (MAT) using commercial manual software as a comparator. Also, abdominal CT scans (n = 100) were used to quantify psoas muscle volumes and intermuscular adipose tissue (IMAT) using the same software. We calculated Pearson's correlation coefficients, individual intra-class correlation coefficients (ICC), and Bland-Altman limits of agreement together with Bland-Altman plots to show the inter- and intra-observer agreement between Tissue Compass and commercially available software. In the animal study, the agreement between Tissue Compass and commercial software was r > 0.93 and ICC > 0.93 for rat femur measurements. Bland-Altman limits of agreement was -720.89 (-1.5e+04, 13,074.00) for MAT, 4421.11 (-1.8e+04, 27,149.73) for HBM and -6073.32 (-2.9e+04, 16,388.37) for bone. The inter-observer agreement for QCT human study between two observers was r > 0.99 and ICC > 0.99. Bland-Altman limits of agreement was 0.01 (-0.07, 0.10) for MAT in hip, 0.02 (-0.08, 0.12) for HBM in hip, 0.05 (-0.15, 0.25) for bone in hip, 0.02 (-0.18, 0.22) for MAT in L1, 0.00 (-0.16, 0.16) for HBM in L1, and0.02 (-0.23, 0.27) for bone in L1. The intra-observer agreement for QCT human study between thetwo applications was r > 0.997 and ICC > 0.99. Bland-Altman limits of agreement was 0.03 (-0.13, 0.20) for MAT in hip, 0.05 (-0.08, 0.18) for HBM in hip, 0.05 (-0.24, 0.34) for bone in hip, -0.02 (-0.34, 0.31) for MAT in L1, -0.14 (-0.44, 0.17) for HBM in L1, -0.29 (-0.62, 0.05) for bone in L1, 0.03 (-0.08, 0.15) for IMAT in psoas, and 0.02 (-0.35, 0.38) for muscle in psoas. Compared to a conventional application, Tissue Compass demonstrated high accuracy and non-inferiority while also facilitating easier analyses. Tissue Compass could become the tool of choice to diagnose tissue loss/gain syndromes in the future by requiring a small number of CT sections to detect tissue volumes and fat infiltration.

Identifying Crucial Equipment and Skills Needed to Evacuate Critically Ill Infants During Disasters: Using Nursing Expertise to Guide Training Targets.

Unexpected disasters, such as earthquakes or fires, require preparation to address knowledge gaps that may negatively affect vulnerable patients. Training programs can promote natural disaster readiness to respond and evacuate patients safely, but also require evidence-based information to guide learning objectives. There is limited evidence on what skills and bedside equipment are most important to include in disaster training and evacuation programs for critically ill infants. An expert panel was used to create a 13-item mastery checklist of skills for bedside registered nurses (RNs) required to successfully evacuate a critically ill infant. Expert nurses were surveyed, and the Angoff method was used to determine which of the mastery checklist skills a newly graduated nurse (ie, the "minimally competent" nurse) should be able to do. Participants then rated the importance of 26 commonly available pieces of bedside equipment for use in evacuating a hemodynamically unstable, intubated infant during a disaster. Twenty-three emergency department (ED) and neonatal intensive care unit (NICU) charge RNs responded to the survey with a mean of 19 (SD = 9) years of experience and 30% reporting personal experience with evacuating patients. The skills list scores showed an emphasis on the newly graduated nurse having more complete mastery of skills surrounding thermoregulation, documentation, infection control, respiratory support, and monitoring. Skills for communication, decision making, and anticipating future needs were assessed as less likely for a new nurse to have mastered. On a scale of one (not important) to seven (critically important), the perceived necessity of equipment ranged from a low of 1.6 (breast pump) to a high of 6.9 (face mask). The individual intraclass correlation coefficient (ICC) of 0.55 showed moderate reliability between raters and the average team ICC of 0.97 showed excellent agreement as a group. Experts rated the ability to manage physiological issues, such as thermoregulation and respiratory support, as skills that every nurse should master. Disaster preparedness activities for nurses in training may benefit from checklists of essential equipment and skills to ensure all nurses can independently manage patients' physiologic needs when they enter the workforce. Advanced nursing training should include education on decision making, communication during emergencies, and anticipation of future issues to ensure that charge and resource nurses can support bedside nurses during evacuation events.

Head-to-head comparison of health-state values derived by a probabilistic choice model and scores on a visual analogue scale

BackgroundHealth states were quantified based on discrete choice (DC) modeling and visual analogue scale (VAS) values using the five-level version of the EQ-5D (EQ-5D-5L). The aim of this study was to determine the extent of the relationship between DC derived values (indirect method) and VAS values (direct method).MethodsData were collected in Canada, the United Kingdom, the Netherlands, and the United States. Respondents were asked to perform paired comparisons between two EQ-5D-5L health states for DC. In total, 400 different EQ-5D-5L states were included. After each DC task, respondents were prompted to score the two states one after another on a VAS. Intraclass correlation coefficients were calculated between DC and VAS values and illuminating graphs were designed.ResultsApproximately 400 respondents participated from each country. High similarity [individual intraclass correlation coefficients (ICC) >0.85] of DC and moderate correspondence of VAS values were observed for the four countries. Cross-country comparison of DC values shows a nonlinear relationship to the VAS values.ConclusionEQ-5D-5L derived DC and VAS values show a close but nonlinear relationship. Given the obvious biases associated with the VAS, DC methods based on ordinal responses may be a better alternative.