The case for the repeatability intra-class correlation as a metric of precision for salivary bioscience data: Justification, assessment, application, and implications.

Best practice standards for measuring analyte levels in saliva recommend that all biospecimens be tested in replicate with mean concentrations used in statistical analyses. This approach prioritizes minimizing laboratory-based measurement error but, in the process, expends considerable resources. We explore the possibility that, due to advances in salivary assay precision, the contribution of laboratory-based measurement error in salivary analyte data is very small relative to more important and meaningful variability in analyte levels across biological replicates (i.e., between different specimens). To evaluate this possibility, we examine the utility of the repeatability intra-class correlation (rICC) as an additional index of salivary analyte data precision. Using randomly selected subsamples (Ns=200 and 60) of salivary analyte data collected as part of a larger epidemiologic study, we compute the rICCs for seven commonly assayed salivary measures in biobehavioral research - cortisol, alpha-amylase, c-reactive protein, interlekin-6, uric acid, secretory immunoglobulin A, and testosterone. We assess the sensitivity of rICC estimates to assay type and the unique distributions of the underlying analyte data. We also use simulations to examine the bias, precision, and coverage probability of rICC estimates calculated for small to large sample sizes. For each analyte, the rICCs revealed that less than 5% of variation in analyte levels was attributable to laboratory-based measurement error. rICC estimates were similar across all analytes despite differences in analyte levels, average intra-assay coefficients of variation, and in the distributional properties of the data. Guidelines for calculating rICC are provided to enable investigators and laboratory staff to apply this metric and more accurately quantify, and communicate, the magnitude of laboratory-based measurement error in their data. By helping investigators scale measurement error relative to more scientifically meaningful variability between biological replicates, the application of the rICC has the potential to influence research strategies and tactics such that resources (e.g., finances, effort, number/volume of biospecimens) are allocated more efficiently and effectively.

Effect of animal assisted interactions on activity and stress response in children in acute care settings.

Objective: Determine the effects of animal assisted interactions (AAI) on activity and stress response in pediatric acute care settings. Design: Randomized treatment control design. Setting: Inpatient pediatric acute care units (PICU, CVICU and Hematology/Oncology). Patients: Eighty pediatric inpatients (49% male) age 2-19 years. Intervention: The AAI experimental group patients interacted with therapy dog teams for 5-10 min and the comparison group patients continued their current activity without an AAI visit. Measurement and results: Salivary cortisol, activity level, and mood were assessed before and after AAI. AAI was associated with a decrease in cortisol levels and increases in mood and activity. Conclusion: AAI benefits children in pediatric acute care units.

A multi-centre international study of salivary hormone oestradiol and progesterone measurements in ART monitoring.

RESEARCH QUESTION: Ovarian stimulation during IVF cycles involves close monitoring of oestradiol, progesterone and ultrasound measurements of follicle growth. In contrast to blood draws, sampling saliva is less invasive. Here, a blind validation is presented of a novel saliva-based oestradiol and progesterone assay carried out in samples collected in independent IVF clinics. DESIGN: Concurrent serum and saliva samples were collected from 324 patients at six large independent IVF laboratories. Saliva samples were frozen and run blinded. A further 18 patients had samples collected more frequently around the time of HCG trigger. Saliva samples were analysed using an immunoassay developed with Salimetrics LLC. RESULTS: In total, 652 pairs of saliva and serum oestradiol were evaluated, with correlation coefficients ranging from 0.68 to 0.91. In the European clinics, a further 237 of saliva and serum progesterone samples were evaluated; however, the correlations were generally poorer, ranging from -0.02 to 0.22. In the patients collected more frequently, five out of 18 patients (27.8%) showed an immediate decrease in oestradiol after trigger. When progesterone samples were assessed after trigger, eight out of 18 (44.4%) showed a continued rise. CONCLUSIONS: Salivary oestradiol hormone testing correlates well to serum-based assessment, whereas progesterone values, around the time of trigger, are not consistent from patient to patient.