Fifteen-minute Frequency of Glucose Measurements and the Use of Threshold Alarms: Impact on Mitigating Dysglycemia in Critically Ill Patients.

Background: The use of near-continuous blood glucose (BG) monitoring has the potential to improve glycemic control in critically ill patients. The MANAGE IDE trial evaluated the performance of the OptiScanner (OS) 5000 in a multicenter cohort of 200 critically ill patients.

Methods: An Independent Group reviewed the BG run charts of all 200 patients and voted whether unblinded use of the OS, with alarms set at 90 and 130 to 150 mg/dL to alert the clinical team to impending hypoglycemia and hyperglycemia, respectively, would have eliminated episodes of dysglycemia: hypoglycemia, defined as a single BG <70 mg/dL; hyperglycemia, defined as >4 hours of BG >150 mg/dL; severe hyperglycemia, defined as >4 hours of BG >200 mg/dL and increased glucose variability (GV), defined as coefficient of variation (CV) >20%.

State of Harmonization of 24 Serum Albumin Measurement Procedures and Implications for Medical Decisions.

Background: Measurements of serum and plasma albumin are widely used in medicine, including as indicators of quality of patient care in renal dialysis centers.

Methods: Pools were prepared from residual patient serum (n = 50) and heparin plasma (n = 48) from patients without renal disease, and serum from patients with kidney failure before hemodialysis (n = 53). Albumin was measured in all samples and in ERM-DA470k/IFCC reference material (RM) by 3 immunochemical, 9 bromcresol green (BCG), and 12 bromcresol purple (BCP) methods.

The impact of measurement frequency on the domains of glycemic control in the critically ill--a Monte Carlo simulation.

The role of blood glucose (BG) measurement frequency on the domains of glycemic control is not well defined. This Monte Carlo mathematical simulation of glycemic control in a cohort of critically ill patients modeled sets of 100 patients with simulated BG-measuring devices having 5 levels of measurement imprecision, using 2 published insulin infusion protocols, for 200 hours, with 3 different BG-measurement intervals-15 minutes (Q15'), 1 hour (Q1h), and 2 hours (Q2h)-resulting in 1,100,000 BG measurements for 3000 simulated patients. The model varied insulin sensitivity, initial BG value and rate of gluconeogenesis.

Falsely increased chloride and missed anion gap elevation during treatment with sodium thiosulfate.

Background: Sodium thiosulfate (STS) is used to treat calciphylaxis and cyanide poisoning, but can lead to a serious anion-gap acidosis. We suspected that the calculated anion gap in a patient treated with STS for calciphylaxis was decreased to normal by a falsely increased chloride, and we hypothesized that STS directly interfered with chloride measurements.

Methods: Plasma pools were prepared with 12 concentrations of STS from 0 to 20 mmol/l.

Effects of measurement frequency on analytical quality required for glucose measurements in intensive care units: assessments by simulation models.

Background: Total error allowances have been proposed for glucose meters used in tight-glucose-control (TGC) protocols. It is unclear whether these proposed quality specifications are appropriate for continuous glucose monitoring (CGM).

Methods: We performed Monte Carlo simulations of patients on TGC protocols.

From slide sets to sound bites: teaching and learning pathology in the digital age.

Educational evolution is particularly important in pathology, particularly cytopathology, due to the vast amounts of independent learning required to master this field. In this study, learning challenges faced by pathology residents were addressed through a variety of educational modalities including 24 short (∼10 minute) online tutorials (dubbed "Sound Bites") covering selected topics in cytopathology as well as other areas of anatomic and clinical pathology. Additionally, residents were provided with an annotated glass slide set covering pediatric pathology with an associated multiple choice self-assessment as well as multiheaded microscope slide review sessions.

Empiric validation of simulation models for estimating glucose meter performance criteria for moderate levels of glycemic control.

Background: We used simulation modeling to relate glucose meter performance criteria to insulin dosing errors for patients on a moderate glycemic control protocol (glucose target, 110-150 mg/dL) and empirically validated assumptions from simulation models using observed glucose meter and laboratory glucose values obtained nearly simultaneously.

Subjects And Methods: The 25,948 glucose values from 1,513 patients on a moderate glycemic control protocol were used to represent the expected distribution of glucose values in this patient population. Simulation models were used to relate glucose meter analytical performance to insulin dosing errors assuming 10%, 15%, or 20% total allowable error (TEa).

Failure of current laboratory protocols to detect lot-to-lot reagent differences: findings and possible solutions.

Background: Maintaining consistency of results over time is a challenge in laboratory medicine. Lot-to-lot reagent changes are a major threat to consistency of results.

Methods: For the period October 2007 through July 2012, we reviewed lot validation data for each new lot of insulin-like growth factor 1 (IGF-1) reagents (Siemens Healthcare Diagnostics) at Mayo Clinic, Rochester, MN, and the University of Virginia, Charlottesville, VA.

Hepatocyte cytokeratin 7 expression in chronic allograft rejection.

We examined hepatocyte cytokeratin 7 (CK7) expression in chronic allograft rejection (CR), a ductopenic condition in which this has not been systematically evaluated, in 20 patients with the clinicopathologic diagnosis of CR and age-, sex-, and native-disease-matched control subjects. We also studied baseline biopsy specimens from both groups. Three pathologists independently reviewed H&E- and CK7-stained sections, counting interlobular bile ducts (BDs) and portal tracts (PTs), noting the morphologic pattern of injury and scoring hepatocyte CK7 expression (0, none; 1+, rare; 2+, multifocal, predominantly periportal; 3+, extension into the lobule; 4+, diffuse).

An appraisal of statistical procedures used in derivation of reference intervals.

When conducting studies to derive reference intervals (RIs), various statistical procedures are commonly applied at each step, from the planning stages to final computation of RIs. Determination of the necessary sample size is an important consideration, and evaluation of at least 400 individuals in each subgroup has been recommended to establish reliable common RIs in multicenter studies. Multiple regression analysis allows identification of the most important factors contributing to variation in test results, while accounting for possible confounding relationships among these factors.

Common reference intervals for aspartate aminotransferase (AST), alanine aminotransferase (ALT) and γ-glutamyl transferase (GGT) in serum: results from an IFCC multicenter study.

Background: Aspartate aminotransferase (AST), alanine aminotransferase (ALT) and γ-glutamyl transferase (GGT) measurements are important for the assessment of liver damage. The aim of this study was to define the reference intervals (RIs) for these enzymes in adults, paying attention to standardization of the methods used and careful selection of the reference population.

Methods: AST, ALT and GGT were measured with commercial analytical systems standardized to the IFCC-recommended reference measurement systems.

Assessing the impact of biomarkers on patient outcome: an obligatory step.

Payers for healthcare increasingly require evidence about health outcomes of medical interventions. Outcomes research uses various study designs to provide such evidence, with the highest level of evidence provided by randomized controlled trials (RCTs). Among published studies of biomarkers, however, relatively few determine the relationship of biomarker testing to outcomes, and only a small fraction of those studies are RCTs, and fewer still follow the CONSORT standards for reporting of trials.

Glucose meter performance criteria for tight glycemic control estimated by simulation modeling.

Background: Glucose meter analytical performance criteria required for safe and effective management of patients on tight glycemic control (TGC) are not currently defined. We used simulation modeling to relate glucose meter performance characteristics to insulin dosing errors during TGC.

Methods: We used 29,920 glucose values from patients on TGC at 1 institution to represent the expected distribution of glucose values during TGC, and we used 2 different simulation models to relate glucose meter analytical performance to insulin dosing error using these 29,920 initial glucose values and assuming 10%, 15%, or 20% total allowable error (TEa) criteria.

Defining laboratory reference values and decision limits: populations, intervals, and interpretations.

This article provides a brief overview of various approaches that may be utilized for the analysis of human semen test results. Reference intervals are the most widely used tool for the interpretation of clinical laboratory results. Reference interval development has classically relied on concepts elaborated by the International Federation of Clinical Chemistry Expert Panel on Reference Values during the 1980s.

Monte Carlo simulation in establishing analytical quality requirements for clinical laboratory tests meeting clinical needs.

Introduction: Patient outcomes, such as morbidity and mortality, depend on accurate laboratory test results. Computer simulation of the effects of test performance parameters on outcome measures may represent a valuable approach to defining the quality of assay performance that is needed to provide optimal outcomes.

Methods: We carried out computer simulations of patients on intensive insulin treatment to determine the effects of glucose meter imprecision and bias on (1) the frequencies of glucose concentrations >160 mg/dL; (2) the frequencies of hypoglycemia (<60 mg/dL); (3) the mean glucose; and (4) glucose variability.