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%. Results: At least one episode of dysglycemia occurred in 103 (51.5%) of the patients, including 6 (3.0%) with hypoglycemia, 83 (41.5%) with hyperglycemia, 18 (9.0%) with severe hyperglycemia, and 40 (20.0%) with increased GV. Unblinded use of the OS with appropriate alarms would likely have averted 97.1% of the episodes of dysglycemia: hypoglycemia (100.0%), hyperglycemia (96.4%), severe hyperglycemia (100.0%), and increased GV (97.5%). Point accuracy of the OS was very similar to that of the point of care BG monitoring devices used in the trial. Conclusion: Unblinded use of the OS would have eliminated nearly every episode of dysglycemia in this cohort of critically ill patients, thereby markedly improving the quality and safety of glucose control.

Gestational diabetes mellitus (GDM) is defined by glucose intolerance that is first documented during pregnancy (1). Maternal hyperglycemia that is less severe than that in diabetes mellitus is strongly associated with increased birth weight, risk of Caesarean delivery, and other adverse outcomes (2). Diagnosis of GDM is important because the risk of adverse events is reduced by treatment (3, 4). Diagnosis of GDM depends exclusively on measurements of plasma glucose. Glucose is typically measured before and at fixed time points after an oral glucose load (5). However, a diagnosis of GDM often is made or excluded based on a single measured glucose concentration above or below a defined threshold (6). By contrast, outside of pregnancy, diagnosis of diabetes requires, in the absence of typical symptoms, documentation of hyperglycemia (by either glucose or hemoglobin A1c) on more than one occasion (7). The requirement for accurate glucose measurements for diagnosis of GDM is heightened by the fact that hemoglobin A1c is not an alternative to glucose measurements for diagnosis of GDM. A major source of preanalytical error in measuring glucose is loss of glucose from blood specimens through glycolysis occurring primarily in red and white blood cells (8). Glucose is lost from whole blood samples at a rate of 5%–7% per hour at room temperature (8). Thus, loss of glucose at 1 h exceeds the desirable limit of total analytical error for glucose based on biological variation. This preanalytical loss of glucose poses a threat to the diagnostic sensitivity of testing for GDM. Moreover, variation in time to centrifugation of blood samples introduces variability in glucose results with resultant variability in likelihood of diagnosis of GDM. Sodium fluoride (NaF) is widely used to inhibit glycolysis, but it is inadequate. NaF does not stop glycolysis for the first 2 h or more after sample collection, and during the first 60–90 min the loss of glucose proceeds at the same rate with or without NaF (8, 9). Glucose tolerance testing presents a special problem when the fasting and other samples are held at the point of care (POC) for 2 h until completion of the procedure (10). The AACC and American Diabetes Association (ADA) guideline on laboratory testing in diabetes (8) addresses the handling of samples collected for measurement of glucose in the diagnosis of diabetes. The guideline recommends that samples be immediately immersed in an ice slurry and analyzed within 30 min of collection (8). This is difficult to achieve in routine patient care, and evidence suggests that this recommendation is not always followed in testing for GDM (10, 11). A study in this issue of Clinical Chemistry addresses the problem that glycolysis presents in the diagnosis of GDM (12). In a previous study (10), some of the same authors compared results of GDM testing in which samples were handled either with their institution’s usual procedures, including use of NaF-containing blood tubes, or according to the ADA/AACC-recommended procedures (8). The recommended sample-handling approach produced a 2.7-fold increase in the rate of diagnosis of GDM (10). The increase was entirely attributable to control of glycolysis. Now these authors have evaluated the potential of glucose meters, used at the point of care, to improve the diagnostic accuracy of testing for GDM by minimizing the loss of glucose before analysis (12). Thus, they measured glucose in skin-puncture blood at the POC, with samples collected from patients in the fasting state and at 1 and 2 h after a 75-gram oral glucose load. Venous blood samples were collected at the same times, and handled strictly according the ADA/AACC guidelines; glucose in the venous plasma was measured in a laboratory nationally accredited according to ISO 15189. Linear regression analysis of the POC glucose results vs. the laboratory plasma glucose results was conducted using a randomly selected derivation cohort (n1⁄4 102). The resulting equations were used to calculate the predicted laboratory plasma glucose result corresponding to each POC capillary result in the remainder of the cohort (n1⁄4 100). For estimation of diagnostic accuracy of the glucose meters in the latter cohort, the predicted venous values were used rather than the actual meter results. For the reference standard for diagnosis of a Department of Pathology, University of Virginia School of Medicine, Charlottesville, VA; b Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL; c Department of Laboratory Medicine, NIH Clinical Center, Bethesda, MD. *Address correspondence to the author at: Department of Pathology, University of Virginia School of Medicine, PO Box 800168, Charlottesville, VA 22908. Fax 301-4021885; e-mail davidbruns@gmail.com. Received November 26, 2019; accepted November 27, 2019. DOI: 10.1093/clinchem/hvz027

BACKGROUNDAnalytical characteristics of methods to measure biomarkers determine how well the methods measure what they claim to measure. Transparent reporting of analytical characteristics allows readers to assess the validity and generalizability of clinical studies in which biomarkers are used. Our aims were to assess the reporting of analytical characteristics of biomarkers used in clinical research and to evaluate the extent of reported characterization procedures for assay precision.METHODSWe searched 5 medical journals (Annals of Internal Medicine, JAMA: The Journal of the American Medical Association, The Lancet, The New England Journal of Medicine, and PLOS Medicine) over a 10-year period for the term "biomarker" in the full-text field. We included studies in which biomarkers were used for inclusion/exclusion of study participants, for patient classification, or as a study outcome. We tabulated the frequencies of reporting of 11 key analytical characteristics (such as analytical accuracy of test results) in the included studies.RESULTSA total of 544 studies and 1299 biomarker uses met the inclusion criteria. No information on analytical characteristics was reported for 67% of the biomarkers. For 65 biomarkers (3%), ≥4 characteristics were reported (range, 4-8). The manufacturer of the measurement procedure could not be determined for 688 (53%) of the 1299 biomarkers. The extent of assessments of assay imprecision, when reported, did not meet expectations for clinical use of biomarkers.CONCLUSIONSReporting of the analytical performance of biomarker measurements is variable and often absent from published clinical studies. We suggest that readers need fuller reporting of analytical characteristics to interpret study results, assess generalizability of conclusions, and compare results among clinical studies.

CONTEXT.—Turnaround time and productivity of clinical mass spectrometric (MS) testing are hampered by time-consuming manual review of the analytical quality of MS data before release of patient results.OBJECTIVE.—To determine whether a classification model created by using standard machine learning algorithms can verify analytically acceptable MS results and thereby reduce manual review requirements.DESIGN.—We obtained retrospective data from gas chromatography-MS analyses of 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH) in 1267 urine samples. The data for each sample had been labeled previously as either analytically unacceptable or acceptable by manual review. The dataset was randomly split into training and test sets (848 and 419 samples, respectively), maintaining equal proportions of acceptable (90%) and unacceptable (10%) results in each set. We used stratified 10-fold cross-validation in assessing the abilities of 6 supervised machine learning algorithms to distinguish unacceptable from acceptable assay results in the training dataset. The classifier with the highest recall was used to build a final model, and its performance was evaluated against the test dataset.RESULTS.—In comparison testing of the 6 classifiers, a model based on the Support Vector Machines algorithm yielded the highest recall and acceptable precision. After optimization, this model correctly identified all unacceptable results in the test dataset (100% recall) with a precision of 81%.CONCLUSIONS.—Automated data review identified all analytically unacceptable assays in the test dataset, while reducing the manual review requirement by about 87%. This automation strategy can focus manual review only on assays likely to be problematic, allowing improved throughput and turnaround time without reducing quality.

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.RESULTS:Two of 3 immunochemical procedures, 5 of 9 BCG, and 10 of 12 BCP methods recovered the RM value within its uncertainty. One immunochemical and 3 BCG methods were biased vs the RM value. Random error components were small for all measurement procedures. The Tina-quant immunochemical method was chosen as the reference measurement procedure based on recovery and results of error analyses. Mean biases for BCG vs Tina-quant were 1.5% to 13.9% and were larger at lower albumin concentrations. BCP methods' mean biases were -5.4% to 1.2% irrespective of albumin concentration. Biases for plasma samples were generally higher than for serum samples for all method types. For most measurement procedures, biases were lower for serum from patients on hemodialysis vs patients without kidney disease.CONCLUSIONS:Significant differences among immunochemical, BCG, and BCP methods compromise interpretation of serum albumin results. Guidelines and calculations for clinical management of kidney and other diseases must consider the method used for albumin measurement until harmonization can be achieved.

BACKGROUND:Transport of blood samples through pneumatic tube systems (PTSs) generates air bubbles in transported blood samples and, with increasing duration of transport, the appearance of hemolysis. We investigated the role of air-bubble formation in PTS-induced hemolysis.METHODS:Air was introduced into blood samples for 0, 1, 3 or 5min to form air bubbles. Hemolysis in the blood was assessed by (H)-index, lactate dehydrogenase (LD) and potassium in plasma. In an effort to prevent PTS-induced hemolysis, blood sample tubes were completely filled, to prevent air bubble formation, and compared with partially filled samples after PTS transport. We also compared hemolysis in anticoagulated vs clotted blood subjected to PTS transport.RESULTS:As with transport through PTSs, the duration of air bubble formation in blood by a gentle stream of air predicted the extent of hemolysis as measured by H-index (p<0.01), LD (p<0.01), and potassium (p<0.02) in plasma. Removing air space in a blood sample prevented bubble formation and fully protected the blood from PTS-induced hemolysis (p<0.02 vs conventionally filled collection tube). Clotted blood developed less foaming during PTS transport and was partially protected from hemolysis vs anticoagulated blood as indicated by lower LD (p<0.03) in serum than in plasma after PTS sample transport.CONCLUSIONS:Prevention of air bubble formation in blood samples during PTS transport protects samples from hemolysis.

BACKGROUND:Unrecognized hemoglobinopathies can lead to measured hemoglobin A1c (Hb A1c) concentrations that are erroneous or misleading. We determined the effects of rare hemoglobin variants on capillary electrophoresis (CE) and HPLC methods for measurement of Hb A1c. METHODS:We prospectively investigated samples in which Hb A1c was measured by CE during a 14-month period. For samples in which the electropherograms suggested the presence of rare hemoglobinopathies, hemoglobin variants were identified by molecular analysis or by comparison with electropherograms of known variants. When sample volume permitted, Hb A1c was measured by 2 HPLC measurement procedures and by boronate affinity HPLC. RESULTS:Hb A1c was measured by CE in 33,859 samples from 26,850 patients. 15 patients (0.06%) were identified as having rare hemoglobinopathies: Hbs A2 prime, Agenogi, Fannin-Lubbock I, G Philadelphia, G San Jose, J Baltimore, La Desirade, N Baltimore, Nouakchott, and Roanne. Among 6 of these samples tested by 2 ion-exchange HPLC methods, the rare Hb was detected by both HPLC methods in only one sample, and none were detected by boronate affinity HPLC. The mean of the Hb A1c results of 2 HPLC methods differed from the result of the CE method by 0.7-2.2% Hb A1c in samples with variant hemoglobins versus <0.2% Hb A1c in samples without variants. CONCLUSION:Measurement procedures differ in the ability to detect the presence of rare Hb variants and to quantify Hb A1c in patients who harbor such variants.

To the Editor: Hemoglobin (Hb)1 variants represent a challenge to the validity of measurements of Hb A1c. Hb variants can falsely increase or decrease reported Hb A1c results, depending on the measurement procedure used (1, 2). Moreover, Hb A1c results in patients who harbor an Hb variant can be clinically misleading if the variant alters the lifespan of erythrocytes. The effects of common hemoglobin variants (Hbs C, D, E, F, and S) on some measurement procedures for Hb A1c have been documented (2, 3), including a recent study in Clinical Chemistry (4). More than 1000 other, rarer hemoglobin variants have been identified, however, and little is known about the effects of most of these variants on measurement procedures …

BACKGROUND:In the immediate postoperative period following resection of growth hormone (GH)-secreting pituitary tumors, serum concentrations of GH have limited ability to predict remission of acromegaly. Since many actions of GH actions are mediated by insulin-like growth factor-1 (IGF-I), we aimed to determine the rates of fall of IGF-I during 72 h after surgical resection of pituitary tumors.METHODS:We studied patients who were undergoing pituitary surgery for acromegaly. IGF-I was measured by LC-MS and GH by immunoassay. Remission was defined by the combination of serum GH <0.4 ng/mL during oral glucose tolerance testing performed 8 weeks after the surgical procedure and normal IGF-I at ≥8 weeks.RESULTS:During the first 72 h after surgery, the mean (SD) rate of decline of IGF-I was 185 (61) ng/mL per 24 h in those who achieved remission (n = 23), with a mean (SD) apparent half-life of 55 (19) h. IGF-I had decreased to <65% of the preoperative IGF-I on postoperative day 2 in 20 of 23 remission patients (87%) vs none of 5 patients who did not achieve remission. GH was <2.7 ng/mL on day 2 in 21 of 23 remission patients (91%), but in none of the nonremission patients. The combination of IGF-I and GH on day 2 separated the remission and nonremission groups of patients.CONCLUSIONS:Rapid decline of serum IGF-I during the immediate postoperative period warrants further study as an analytically independent adjunct to GH measurement for early prediction of biochemical remission of acromegaly.

Diagnostic accuracy studies are, like other clinical studies, at risk of bias due to shortcomings in design and conduct, and the results of a diagnostic accuracy study may not apply to other patient groups and settings. Readers of study reports need to be informed about study design and conduct, in sufficient detail to judge the trustworthiness and applicability of the study findings. The STARD statement (Standards for Reporting of Diagnostic Accuracy Studies) was developed to improve the completeness and transparency of reports of diagnostic accuracy studies. STARD contains a list of essential items that can be used as a checklist, by authors, reviewers and other readers, to ensure that a report of a diagnostic accuracy study contains the necessary information. STARD was recently updated. All updated STARD materials, including the checklist, are available at http://www.equator-network.org/reporting-guidelines/stard. Here, we present the STARD 2015 explanation and elaboration document. Through commented examples of appropriate reporting, we clarify the rationale for each of the 30 items on the STARD 2015 checklist, and describe what is expected from authors in developing sufficiently informative study reports.

To the Editor: The pneumatic tube system (PTS) has become a common means of transportation of specimens in medical centers. Although the PTS provides convenience and speed of transport, hemolysis of blood specimens and preanalytical variation have been related to excessive acceleration forces and prolonged time/distance traveled in the PTS (1–5). As a result, regular assessment of 3-axis acceleration (i.e., forces) in PTSs has been recommended in an article in this journal (5). An editorial related to that article suggested that products designed for PTS assessment may become commercially available and capable of recording g -forces in PTSs (2). To date, however, we have found no products that are available in the US designed to record forces in the PTS used in our health system (Swisslog). Many modern smartphones are equipped with an accelerometer that measures acceleration forces. The devices also contain a chronometer, and they are nearly ubiquitous and are portable, …

Background: Pneumatic tube systems (PTSs) are convenient methods of patient sample transport in medical centers, but excessive acceleration force and time/distance traveled in the PTS have been correlated with increased blood-sample hemolysis. We investigated the utility of smartphones for monitoring of PTS-related variables.Methods: Smartphones were sent through the PTS from several hospital locations. Each smartphone used 2 apps as data-loggers to record force of acceleration vs time. To relate the smartphone data to sample integrity, blood samples were collected from 5 volunteers, and hemolysis of the samples was analyzed after they were transported by hand or via I of 2 PTS routes. Increased sample hemolysis as measured by plasma lactate dehydrogenase (ID) was also related to the amount of transport in the PTS.Results: The smartphones showed higher duration of forceful acceleration during transport through 1 of the 2 PTS routes, and the increased duration correlated with significant increases in hemolysis (H)-index and plasma LD. In addition, plasma LD showed a positive linear relationship with number of shock forces experienced during transport through the PTS.Conclusions: Smartphones can monitor PTS variables that cause sample hemolysis. This provides an accessible method for investigating specific PTS routes in medical centers. (C) 2016 Elsevier B.V. All rights reserved.

A 58-year-old man with chronic systolic heart failure and type 2 diabetes mellitus presented with bacteremia, acute exacerbation of chronic heart failure, and acute renal failure.He described poor appetite and drinking beer for several days.Alanine aminotransferase (ALT) 2 was 16 U/L initially but decreased until it became undetectable (Ͻ6 U/L) on the Architect 16200 (Table 1).ALT was readily measurable on the Vitros 350, with a result of 11 U/L, when tested on hospital day 22.QUESTIONS 1.What is ALT? 2. What coenzymes are required for its activity?3. What is the reason for the difference in results of Architect and Vitros assays?The answers are on the next page.

A 62-year-old woman with osteoporosis was noted to have undetectable urine calcium (Table 1). The patient had undergone Roux-en-Y surgery for weight loss 10 years earlier. Her medications included zoledronic acid, calcitriol, and calcium supplements to treat the osteoporosis. Urine calcium concentrations were repeatedly <2 mg/dL (Table 1), corresponding to <45 to <52 mg …

Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.

A 55-year-old man with ankylosing spondylitis presented with increasing symptoms despite treatment with adalimumab. The decreased therapeutic response raised concern that he had produced antibodies against the drug or that he had cross-reacting antibodies made against a similar drug, infliximab, with which he was treated 7 years earlier. Tests for antibodies against the drugs were negative, but the serum adalimumab and infliximab concentrations, reported automatically with results for antidrug antibodies, …

The metalloproteinase SAS1B [ovastacin, ASTL, astacin-like] was immunolocalized on the oolemma of ovulated human oocytes and in normal ovaries within the pool of growing oocytes where SAS1B protein was restricted to follicular stages spanning the primary-secondary follicle transition through ovulation.Gene-specific PCR and immunohistochemical studies revealed ASTL messages and SAS1B protein in both endometrioid [74%] and malignant mixed Mullerian tumors (MMMT) [87%] of the uterus.A MMMT-derived cell line, SNU539, expressed cell surface SAS1B that, after binding polyclonal antibodies, internalized into EEA1/LAMP1-positive early and late endosomes.Treatment of SNU539 cells with anti-SAS1B polyclonal antibodies caused growth arrest in the presence of active complement.A saporin-immunotoxin directed to SAS1B induced growth arrest and cell death.The oocyte restricted expression pattern of SAS1B among adult organs, cell-surface accessibility, internalization into the endocytic pathway, and tumor cell growth arrest induced by antibody-toxin conjugates suggest therapeutic approaches that would selectively target tumors while limiting adverse drug effects in healthy cells.The SAS1B metalloproteinase is proposed as a prototype cancer-oocyte tumor surface neoantigen for development of targeted immunotherapeutics with limited on-target/off tumor effects predicted to be restricted to the population of growing oocytes.

Background: The role of blood glucose (BG) measurement frequency on the domains of glycemic control is not well defined. Methods: 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. The primary outcomes included rates of hyperglycemia (BG > 180 mg/dL), hypoglycemia (BG < 70 and 40 mg/dL), proportion of patients with elevated glucose variability (within-patient coefficient of variation [CV] > 20%), and time in range (BG ranges 80-150 mg/dL and 80-180 mg/dL). Results: Percentages of hyperglycemia, hypoglycemia at both thresholds, and patients with elevated glucose variability as well as time outside glycemic targets were substantially higher in simulations with measurement interval Q2h compared to those with measurement interval Q1h and moderately higher in simulations with Q1h than in those with Q15’. Higher measurement frequency mitigated the deleterious effect of high measurement imprecision, defined as CV ≥ 15%. Conclusions: This Monte Carlo simulation suggests that glycemic control in critically ill patients is more optimal with a BG measurement interval no longer than 1h, with further benefit obtained with use of measurement interval of 15’. These findings have important implications for the development of glycemic control standards.

Background: Ethical considerations are increasingly important in medicine. We aimed to determine the mode and extent of teaching of ethics in training programs in clinical chemistry and laboratory medicine.Methods: We developed an on-line survey of teaching in areas of ethics relevant to laboratory medicine. Reponses were invited from directors of training programs who were recruited via email to leaders of national organizations.Results: The survey was completed by 80 directors from 24 countries who directed 113 programs. The largest numbers of respondents directed postdoctoral training of scientists (42%) or physicians (33%), post-masters degree programs (33%), and PhD programs (29%). Most programs (82%) were 2 years or longer in duration. Formal training was offered in research ethics by 39%, medical ethics by 31%, professional ethics by 24% and business ethics by 9%. The number of reported hours of formal training varied widely, e.g., from 0 to >15 h/year for research ethics and from 0 to >15 h for medical ethics. Ethics training was required and/or tested in 75% of programs that offered training. A majority (54%) of respondents reported plans to add or enhance training in ethics; many indicated a desire for online resources related to ethics, especially resources with self-assessment tools.Conclusion: Formal teaching of ethics is absent from many training programs in clinical chemistry and laboratory medicine, with heterogeneity in the extent and methods of ethics training among the programs that provide the training. A perceived need exists for online training tools, especially tools with self-assessment components. (C) 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).