Temporal Artery versus Bladder Thermometry during Adult Medical-Surgical Intensive Care Monitoring: An Observational Study

Abstract Background We sought to evaluate agreement between a new and widely implemented method of temperature measurement in critical care, temporal artery thermometry and an established method of core temperature measurement, bladder thermometry as performed in clinical practice. Methods Temperatures were simultaneously recorded hourly (n = 736 observations) using both devices as part of routine clinical monitoring in 14 critically ill adult patients with temperatures ranging ≥1°C prior to consent. Results The mean difference between temporal artery and bladder temperatures measured was -0.44°C (95% confidence interval, -0.47°C to -0.41°C), with temporal artery readings lower than bladder temperatures. Agreement between the two devices was greatest for normothermia (36.0°C to < 38.3°C) (mean difference -0.35°C [95% confidence interval, -0.37°C to -0.33°C]). The temporal artery thermometer recorded higher temperatures during hypothermia (< 36°C) (mean difference 0.66°C [95% confidence interval, 0.53°C to 0.79°C]) and lower temperatures during hyperthermia (≥38.3°C) (mean difference -0.90°C [95% confidence interval, -0.99°C to -0.81°C]). The sensitivity for detecting fever (core temperature ≥38.3°C) using the temporal artery thermometer was 0.26 (95% confidence interval, 0.20 to 0.33), and the specificity was 0.99 (95% confidence interval, 0.98 to 0.99). The positive likelihood ratio for fever was 24.6 (95% confidence interval, 10.7 to 56.8); the negative likelihood ratio was 0.75 (95% confidence interval, 0.68 to 0.82). Conclusions Temporal artery thermometry produces somewhat surprising disagreement with an established method of core temperature measurement and should not to be used in situations where body temperature needs to be measured with accuracy

Matched case-control studies: a review of reported statistical methodology

Daniel J Niven1, Luc R Berthiaume2, Gordon H Fick1, Kevin B Laupland11Department of Critical Care Medicine, Peter Lougheed Centre, Calgary, 2Department of Community Health Sciences, University of Calgary, Calgary, Alberta, CanadaBackground: Case-control studies are a common and efficient means of studying rare diseases or illnesses with long latency periods. Matching of cases and controls is frequently employed to control the effects of known potential confounding variables. The analysis of matched data requires specific statistical methods.Methods: The objective of this study was to determine the proportion of published, peer reviewed matched case-control studies that used statistical methods appropriate for matched data. Using a comprehensive set of search criteria we identified 37 matched case-control studies for detailed analysis.Results: Among these 37 articles, only 16 studies were analyzed with proper statistical techniques (43%). Studies that were properly analyzed were more likely to have included case patients with cancer and cardiovascular disease compared to those that did not use proper statistics (10/16 or 63%, versus 5/21 or 24%, P&amp;nbsp;= 0.02). They were also more likely to have matched multiple controls for each case (14/16 or 88%, versus 13/21 or 62%, P&amp;nbsp;= 0.08). In addition, studies with properly analyzed data were more likely to have been published in a journal with an impact factor listed in the top 100 according to the Journal Citation Reports index (12/16 or 69%, versus 1/21 or 5%, P &amp;le; 0.0001).Conclusion: The findings of this study raise concern that the majority of matched case-control studies report results that are derived from improper statistical analyses. This may lead to errors in estimating the relationship between a disease and exposure, as well as the incorrect adaptation of emerging medical literature.Keywords: case-control, matched, dependent data, statistic