Clinical evaluation of non-contact infrared thermometers

Non-contact infrared thermometers (NCITs) are being widely used during the COVID-19 pandemic as a temperature-measurement tool for screening and isolating patients in healthcare settings, travelers at ports of entry, and the general public. To understand the accuracy of NCITs, a clinical study was conducted with 1113 adult subjects using six different commercially available NCIT models. A total of 60 NCITs were tested with 10 units for each model. The NCIT-measured temperature was compared with the oral temperature obtained using a reference oral thermometer. The mean difference between the reference thermometer and NCIT measurement (clinical bias) was different for each NCIT model. The clinical bias ranged from just under − 0.9 °C (under-reporting) to just over 0.2 °C (over-reporting). The individual differences ranged from − 3 to + 2 °C in extreme cases, with the majority of the differences between − 2 and + 1 °C. Depending upon the NCIT model, 48% to 88% of the individual temperature measurements were outside the labeled accuracy stated by the manufacturers. The sensitivity of the NCIT models for detecting subject’s temperature above 38 °C ranged from 0 to 0.69. Overall, our results indicate that some NCIT devices may not be consistently accurate enough to determine if subject’s temperature exceeds a specific threshold of 38 °C. Model-to-model variability and individual model accuracy in the displayed temperature were found to be outside of acceptable limits. Accuracy and credibility of the NCITs should be thoroughly evaluated before using them as an effective screening tool.

Clinical Evaluation of Non-Contact Infrared Thermometers

Background:Non-contact infrared thermometers (NCITs) are being widely used during the COVID-19 pandemic as a temperature-measurement tool for screening and isolating patients in healthcare settings, travelers at ports of entry, and the general public. Methods:To understand the accuracy of NCITs, a clinical study was conducted with 1113 adult subjects using six different commercially available NCIT models. A total of 60 NCITs were tested with 10 units for each model. The NCIT-measured temperature was compared with the oral temperature obtained using a reference oral thermometer. Results:The mean difference between the reference thermometer and NCIT measurement (clinical bias) was different for each NCIT model. The clinical bias ranged from just under -0.9 °C (under-reporting) to just over 0.2 °C (over-reporting). The individual differences ranged from -3 °C to +2 °C in extreme cases, with the majority of the differences between -2 °C and +1 °C. Depending upon the NCIT model, 48% to 88% of the individual temperature measurements were outside the labeled accuracy stated by the manufacturers. The sensitivity of the NCIT models for detecting subject’s temperature above 38 °C ranged from 0 to 0.69. Conclusions: Overall, our results indicate that some NCIT devices may not be consistently accurate enough to determine if subject’s temperature exceeds a specific threshold of 38 °C. Model-to-model variability and individual model accuracy in the displayed temperature were found to be outside of acceptable limits. Accuracy and credibility of the NCITs should be thoroughly evaluated before using them as an effective screening tool.

Counselor Competence Gender Identity Scale: Measuring Clinical Bias, Knowledge, and Skills

This study assess the psychometric properties of the Counselor Competence Gender Identity Scale (CCGIS), a competency-based assessment that measures the effectiveness of counselors to provide services to gender minorities. Exploratory factor analysis retained 25 items which formed four subscales. The CCGIS also discriminated between different groups of school counselors.

Pharmacogenomics, CYP2D6, and Tamoxifen: A Survey of the Reasons Sustaining European Clinical Practice Paradigms

Tamoxifen is a drug that is often used in the clinical management of breast cancer. CYP2D6 is a key metabolizing enzyme that is involved in the conversion of tamoxifen to its active drug metabolites. CYP2D6 has several alleles that metabolize tamoxifen and other drugs at different rates that can alter therapeutic impact, a characteristic that renders it one of the most studied enzymes in the field of pharmacogenetics. Background and objectives: Portugal has no implemented measures based on pharmacogenomics analysis prior to therapy that might function as a cultural sample control when analyzing the individual and economic factors present in clinical practice paradigms. Therefore, we aim to investigate the impact of CYP2D6 genotyping of the tamoxifen metabolizing enzymes in the clinical management of breast cancer patients. Materials and Methods: Qualitative/quantitative studies regarding the impact of pharmacogenomics in breast cancer; personal interviews in different Portuguese laboratories within hospital setting using a survey. Analysis of data through interviews to management board and/or decision makers from major oncological centers. Results: Reasons for common adoption of pharmacogenomics practice are contradictory and based both in economic factors and cultural/clinical bias. Conclusions: This research study identifies specific cultural and/or clinical bias that act as obstacles to pharmacogenomic implementation and proposes viable courses of action that might bring about change in cultural/medical habits.

Cardiovascular and Patient Phenotype of Extended Haemodialysis: A Critical Analysis of Studying a Unique Patient Population

Background: Extended haemodialysis (EHD) has been associated with better outcomes compared to conventional (CHD) regimes. The cardiovascular (CV) profile of these patients has not been assessed in detail. Methods: We report baseline demographic and CV phenotype of 36 CHD and 36 EHD participants to a longitudinal multicentre study. We measured pulse wave velocity (PWV), 24-h ambulatory blood pressure, sublingual dark-field capillaroscopy and vascular biomarkers. Results: EHD patients were younger (p < 0.01), with less CV comorbidity (p = 0.04) and higher dialysis vintage (p < 0.01). Higher PWV in CHD (p = 0.02) was not independent of demographic differences in the 2 groups. Biomarker profiles were similar in EHD and CHD but abnormal compared to healthy controls. Conclusion: Although CV profiles in these 2 cohorts were similar, EHD patients were distinct from the CHD population in terms of age and dialysis vintage and appear to comprise a unique group. Direct comparison of outcomes in these groups is challenging due to clinical bias.