Estimations of isoprenoid emission capacity from enclosure studies: measurements, data processing, quality and standardized measurement protocols

Computerized clinical decision support systems (CDSS) for intensive insulin therapy (IIT) generate recommendations using blood glucose (BG) values manually transcribed from testing devices to computers, a potential source of error. We quantified the frequency and effect of blood glucose transcription mismatches on IIT protocol performance.We examined 38 months of retrospective data for patients treated with CDSS IIT in two intensive care units at one teaching hospital. A manually transcribed BG value not equal to a corresponding device value was deemed mismatched. For mismatches we recalculated CDSS recommendations using device BG values. We compared matched and mismatched data in terms of CDSS alerts, blood glucose variability, and dosing.Of 189,499 CDSS IIT instances, 5.3% contained mismatched BG values. Mismatched data triggered 93 false alerts and failed to issue 170 alerts for nurses to notify physicians. Four of six BG variability measures differed between matched and mismatched data. Overall insulin dose was greater for matched than mismatched [matched 3.8 (1.6-6.0), median (interquartile range, IQR), versus 3.6 (1.6-5.7); p < 0.001], but recalculated and actual dose were similar. In mismatches preceding hypoglycemia, recalculated insulin dose was significantly lower than actual dose [recalculated 2.7 (0.4-5.0), median (IQR), versus 3.5 (1.4-5.6)]. In mismatches preceding hyperglycemia, recalculated insulin dose was significantly greater than actual dose [recalculated 4.7 (3.3-6.2), median (IQR), versus 3.3 (2.4-4.3); p < 0.001]. Administration of recalculated doses might have prevented blood glucose excursions.Mismatched blood glucose values can influence CDSS IIT protocol performance

Estimation of isoprenoid emission factors from enclosure studies: measurements, data processing, quality and standardized measurement protocols

The capacity for volatile isoprenoid production under standardized environmental conditions (&lt;i&gt;E&lt;/i&gt;&lt;sub&gt;S&lt;/sub&gt;), the emission factor) is a key characteristic in constructing isoprenoid emission inventories. However, there is large variation in published &lt;i&gt;E&lt;/i&gt;&lt;sub&gt;S&lt;/sub&gt; estimates for any given species, and this variation leads to significant uncertainties in emission predictions. We review the sources of variation in &lt;i&gt;E&lt;/i&gt;&lt;sub&gt;S&lt;/sub&gt; that are due to measurement and analytical techniques and calculation and averaging procedures. This review demonstrates that estimations of &lt;i&gt;E&lt;/i&gt;&lt;sub&gt;S&lt;/sub&gt; critically depend on applied experimental protocols and on data processing and reporting. A great variety of experimental setups has been used in the past, contributing to study-to-study variations in &lt;i&gt;E&lt;/i&gt;&lt;sub&gt;S&lt;/sub&gt; estimates. We suggest that past experimental data should be distributed into broad quality classes depending on whether the data can or cannot be considered quantitative based on rigorous experimental standards. Apart from analytical issues, the accuracy of &lt;i&gt;E&lt;/i&gt;&lt;sub&gt;S&lt;/sub&gt; values is strongly driven by extrapolation and integration errors introduced during data processing. Additional sources of error, especially in meta-database construction, can further arise from inconsistent use of units and expression bases of &lt;i&gt;E&lt;/i&gt;&lt;sub&gt;S&lt;/sub&gt;. We propose a standardized experimental protocol for BVOC estimations and highlight basic meta-information that we strongly recommend to report with any &lt;i&gt;E&lt;/i&gt;&lt;sub&gt;S&lt;/sub&gt; measurement. We conclude that standardization of experimental and calculation protocols and critical examination of past reports is essential for development of accurate emission factor databases