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Biomedical subjects

G J Kost

Publications and source records attributed to G J Kost.

At least 19 recordsLinked to original sources
PubMed2001

Oxygen effects on glucose meter measurements with glucose dehydrogenase- and oxidase-based test strips for point-of-care testing.

OBJECTIVES: To determine the effects of different oxygen tensions (Po2) on glucose measurements with glucose dehydrogenase (GD)-based and glucose oxidase (GO)-based test strips, to quantitate changes in glucose measurements observed with different Po2 levels, and to discuss the potential risks of oxygen-derived glucose errors in critical care. DESIGN: Venous blood from healthy volunteers was tonometered to create different oxygen tensions simulating patient arterial Po2 levels. Venous blood from diabetic patients was exposed to air to alter oxygen tensions simulating changes in Po2 during sample handling. Whole-blood glucose measurements obtained from these samples with six glucose meters were compared with reference analyzer plasma glucose measurements. Glucose differences were plotted vs. different Po2 levels to identify error trends. Error tolerances were as follows: a) within +/-15 mg/dL of the reference measurement for glucose levels 100 mg/dL. SETTING AND SUBJECTS: Five healthy volunteers in the bench study and 11 diabetic patients in the clinical study. RESULTS: In the bench study, increases in Po2 levels decreased glucose measured with GO-based amperometric test strips, mainly at Po2 levels >100 torr. At nearly constant glucose concentrations, glucose meter systems showed large variations at low (39 torr) vs. high (396 torr) Po2 levels. Glucose measured with GD-based amperometric and GO-based photometric test strips generally were within error tolerances. In the clinical study, 31.6% (Precision PCx), 20.2% (Precision QID), and 23.0% (Glucometer Elite) of glucose measurements with GO-based amperometric test strips, 14.3% (SureStep) of glucose measurements with GO-based photometric test strips, and 4.6% (Accu-Chek Advantage H) and 5.9% (Accu-Chek Comfort Curve) of glucose measurements with GD-based amperometric test strips were out of the error tolerances. CONCLUSIONS: Different oxygen tensions do not significantly affect glucose measured with the GD-based amperometric test strips, and have minimal effect on GO-based photometric test strips. Increases in oxygen tension lowered glucose measured with GO-based amperometric test strips. We recommend that the effects of different oxygen tensions in blood samples on glucose measurements be minimized by using oxygen-independent test strips for point-of-care glucose testing in critically ill and other patients with high or unpredictable blood Po2 levels.

Blood Gas Analysis↗
PubMed2001

Preventing medical errors in point-of-care testing: security, validation, safeguards, and connectivity..

OBJECTIVES: o prevent medical errors, improve user performance, and enhance the quality, safety, and connectivity (bidirectional communication) of point-of-care testing. PARTICIPANTS: Group A included 37 multidisciplinary experts in point-of-care testing programs in critical care and other hospital disciplines. Group B included 175 professional point-of-care managers, specialists, clinicians, and researchers. The total number of participants equaled 212. EVIDENCE: This study followed a systems approach. Expert specifications for prevention of medical errors were incorporated into the designs of security, validation, performance, and emergency systems. Additional safeguards need to be implemented through instrument software options and point-of-care coordinators. Connectivity will be facilitated by standards that eliminate deficiencies in instrument communication and device compatibility. Assessment of control features on handheld, portable, and transportable point-of-care instruments shows that current error reduction features lag behind needs. CONCENSUS PROCESS: Step 1: United States national survey and collation of group A expert requirements for security, validation, and performance. Step 2: Design of parallel systems for these functions. Step 3: Written critique and improvement of the error-prevention systems during 4 successive presentations to group B participants over 9 months until system designs stabilized into final consensus form. CONCLUSIONS: The consensus process produced 6 conclusions for preventing medical errors in point-of-care testing: (1) adopt operator certification and validation in point-of-care testing programs; (2) implement security, validation, performance, and emergency systems on existing and new devices; (3) require flexible, user-defined error-prevention system options on instruments as a prerequisite to federal licensing of new diagnostic tests and devices; (4) integrate connectivity standards for bidirectional information exchange; (5) preserve fast therapeutic turnaround time of point-of-care test results; and (6) monitor invalid use, operator competence, quality compliance, and other performance improvement indices to reduce errors, thereby focusing on patient outcomes.(Arch Pathol Lab Med. 2001;1307-1315)

Consensus Statements as Topic↗
PubMed2000

Oxygen effects on glucose measurements with a reference analyzer and three handheld meters.

Oxygen may affect glucose meter and reference analyzer measurements. We evaluated the effects of changes in blood oxygen tension (Po2) on Accu-Chek Comfort Curve (Roche Diagnostics, Indianapolis, IN), Precision G, (Abbott Laboratories, Bedford, MA) and One Touch II (Lifescan, Milpitas, CA) glucose meter measurements, and on Yellow Springs Instruments (YSI) (Yellow Springs, OH) reference analyzer measurements. Venous blood drawn from healthy volunteers was adjusted to three glucose levels of 80, 200, and 400 mg/dL, each tonometered with six different Po2 levels (40, 80, 160, 240, 320, and 400 torr). To quantitate oxygen effects on reference analyzer measurements, glucose differences between test sample (Po2 changed) and control (Po2 80 torr) were calculated (YSItest-YSIcontrol). The threshold for determination of oxygen effects was +/-2 SD, where 2 SD was fro

Blood Chemical Analysis↗
PubMed2000

Multicenter study of whole-blood creatinine, total carbon dioxide content, and chemistry profiling for laboratory and point-of-care testing in critical care in the United States.

OBJECTIVES: To introduce a creatinine biosensor and a total carbon dioxide content (TCO2) method for whole-blood measurements, to evaluate the clinical performance of a new transportable analyzer that simultaneously performs these two and six other tests (Na+, K+, Cl-, glucose, urea nitrogen, and hematocrit), and to assess the potential of the new analyzer for point-of-care testing in critical care by comparing results obtained by nonlaboratory personnel and by medical technologists. DESIGN: Multicenter sites compared whole-blood measurements with the transportable analyzer to plasma measurements from the same specimens with local reference instruments. One site compared whole-blood results produced by nonlaboratory personnel vs. medical technologists and evaluated day-to-day and within-day precision at the point of care. SETTINGS AND PATIENTS: Four medical centers in the United States. Venous and arterial specimens from 710 critically ill patients with a variety of diagnoses. Point-of-care testing in the emergency room and operating room. RESULTS: The linear regression analyses at the four medical centers showed the following: creatinine (a) slope, 0.91 to 1.22, (b) y intercept, -0.07 to 0.15 mg/dL, and (c) r2, 0.77 to 1.00; and TCO2: (a) slope, 0.64 to 1.00, (b) y intercept, 1.36 to 9.6 mmol/L, and (c) r2, 0.52 to 0.72 (yi, whole-blood analyses; xi, plasma reference measurements). Bland-Altman plots also were used to assess multicenter creatinine and TCO2 results. Of the other analytes, K+, glucose, and urea nitrogen had the highest r2-values. For the eight chemistry profile tests performed at the point of care (yi, nonlaboratory personnel results; xi, medical technologist results), the average value of r2 was 0.96 (SD 0.08) in the operating room and 0.96 (SD 0.06) in the emergency room, and mean paired differences (yi - xi) were not statistically or clinically significant. Precision was acceptable. CONCLUSIONS: The performance of the creatinine biosensor and the TCO2 method was acceptable for whole-blood samples. Comparisons of whole-blood results from the transportable analyzer and plasma results from the local reference instruments revealed analyte biases that may be attributed to differences between direct whole-blood analyses and indirect-diluted plasma measurements and other factors. Performance of nonlaboratory personnel and medical technologists was equivalent for point-of-care testing in critical care settings. The whole-blood analyzer should be useful when patient care demands immediate results.

Biosensing Techniques↗
PubMed2000

Effects of drugs on glucose measurements with handheld glucose meters and a portable glucose analyzer.

Thirty drugs used primarily in critical care and hospital settings were tested in vitro to observe interference on glucose measurements with 6 hand-held glucose meters and a portable glucose analyzer. Paired differences of glucose measurements between drug-spiked samples and unspiked control samples were calculated to determine bias. A criterion of +/- 6 mg/dL was used as the cutoff for interference. Ascorbic acid interfered with the measurements on all glucose devices evaluated. Acetaminophen, dopamine, and mannitol interfered with glucose measurements on some devices. Dose-response relationships help assessment of drug interference in clinical use. High dosages of these drugs may be given to critically ill patients or self-administered by patients without medical supervision. Package inserts for the glucose devices may not provide adequate warning information. Hence, we recommend that clinicians choose glucose devices carefully and interpret results cautiously when glucose measurements are performed during or after drug interventions.

Blood Glucose↗
PubMed2000

Point-of-care glucose testing: effects of critical care variables, influence of reference instruments, and a modular glucose meter design.

OBJECTIVE: To assess the clinical performance of glucose meter systems when used with critically ill patients. DESIGN: Two glucose meter systems (SureStepPro and Precision G) and a modular adaptation (Immediate Response Mobile Analysis-SureStepPro) were assessed clinically using arterial samples from critically ill patients. A biosensor-based analyzer (YSI 2700) and a hospital chemistry analyzer (Synchron CX-7) were the primary and secondary reference instruments, respectively. PATIENTS AND SETTING: Two hundred forty-seven critical care patients at the University of California, Davis, Medical Center participated in this study. OUTCOME MEASURES: Error tolerances of +/-15 mg/dL for glucose levels </=100 mg/dL and +/-15% for glucose levels >100 mg/dL were used to evaluate glucose meter performance; 95% of glucose meter measurements should fall within these tolerances. RESULTS: Compared to the primary reference method, 98% to 100% of SureStepPro and 91% to 95% of Precision G measurements fell within the error tolerances. Paired differences of glucose measurements versus critical care variables (Po(2), pH, Pco(2), and hematocrit) were analyzed to determine the effects of these variables on meter measurements. Po(2) and Pco(2) decreased Precision G and SureStepPro measurements, respectively, but not enough to be clinically significant based on the error tolerance criteria. Hematocrit levels affected glucose measurements on both meter systems. Modular adaptation did not affect test strip performance. CONCLUSIONS: Glucose meter measurements correlated best with primary reference instrument measurements. Overall, both glucose meter systems showed acceptable performance for point-of-care testing. However, the effects of some critical care variables, especially low and high hematocrit values, could cause overestimated or underestimated glucose measurements.

Blood Glucose↗
PubMed2000

Effects of pH on glucose measurements with handheld glucose meters and a portable glucose analyzer for point-of-care testing.

OBJECTIVES: To determine pH effects on glucose measurements obtained with the latest generation of glucose devices, to quantitate changes in glucose measurements obtained over a wide pH range, and to assess the potential clinical risks of pH effects with use of point-of-care glucose testing. DESIGN: Paired differences of glucose measurements between pH-altered and parallel control samples with target pH 7.40 were calculated. SETTING: A pH range of 6.94 to 7.84 was used to evaluate pH effects on glucose measurements in vitro with 6 handheld glucose meters and a portable glucose analyzer at both normal, 4.81 mmol/L (86.6 mg/dL), and high, 11.16 mmol/L (201 mg/dL), glucose levels. MAIN OUTCOME MEASURES: Glucose measurements obtained from test samples and control samples were compared by calculating paired differences, which were plotted against pH to show pH effects on glucose meter measurements. RESULTS: At the normal glucose level, different pH levels did not interfere significantly with glucose measurements. At the high glucose level, a trend whereby low pH decreased and high pH increased glucose measurements was observed on the Precision G and the Precision QID glucose meters. CONCLUSION: Because of potential risk in diabetic patients with ketoacidosis and in other patients with acid-base disorders, we recommend that clinicians choose glucose devices carefully and interpret the measurements cautiously when point-of-care glucose testing is performed in critically ill patients with acidemia, alkalemia, or changing acid-base status.

Blood Chemical Analysis↗
PubMed2000

Whole-blood glucose and lactate. Trilayer biosensors, drug interference, metabolism, and practice guidelines.

OBJECTIVE: To assess the effects of 30 of the most commonly used critical care drugs on measurements obtained with trilayer electrochemical biosensors on a reference analyzer (ABL625-GL), to determine metabolic changes in glucose and lactate in vitro, and to formulate guidelines for whole-blood analysis of these 2 analytes. DESIGN: Serial measurements were taken of changes in glucose and lactate levels caused by metabolism in whole blood in vitro over time. A parallel control study of drug interference with measurements of glucose and lactate in whole blood and of dose-response relationships in whole-blood samples and in plasma samples also was conducted. RESULTS: At room temperature, whole-blood metabolism decreased glucose levels -2.3% at 15 minutes, -4.6% at 30 minutes, and -6.4% at 45 minutes. Metabolism increased lactate levels 11.4% at 15 minutes, 20.6% at 30 minutes, and 26.7% at 45 minutes in vitro. Paired differences between drug-spiked and control samples were calculated to determine interference (corrected for metabolism). The threshold for determination of interference was +/-2 SD from within-day precision, equal to +/-0.18 and +/-0.10 mmol/L for glucose and lactate, respectively. Only mannitol (C(6)H(14)O(6)) interfered with glucose and lactate measurements. At a concentration of 24 mg/mL, mannitol decreased whole-blood glucose levels by an average of 0.711 mmol/L (12.8 mg/dL) and whole-blood lactate levels by 0.16 mmol/L (1.4 mg/dL). Mannitol interference with measurements may have resulted from suppression of hydrogen peroxide formation in the enzymatic reactions in the biosensors, repartitioning of water between erythrocytes and plasma, or from other mechanisms. CONCLUSIONS: Most critical care drugs had no significant effects on the trilayer electrochemical biosensors. Whole-blood analysis should be performed within 15 minutes for lactate and within 30 minutes for glucose because of metabolism in vitro. Mannitol effects on glucose measurements may be clinically significant in mannitol-induced acute renal failure and therefore should be considered for appropriate diagnosis and treatment of critically ill patients.

Biosensing Techniques↗
PubMed2000

Effects of different hematocrit levels on glucose measurements with handheld meters for point-of-care testing.

OBJECTIVES: To determine the effects of low, normal, and high hematocrit levels on glucose meter measurements and to assess the clinical risks of hematocrit errors. DESIGN: Changes in glucose measurements between low and high hematocrit levels were calculated to determine hematocrit effects. The differences between glucose measured with meters and with a plasma glucose method (YSI 2300) also were compared. SETTING: Six hand-held glucose meters were assessed in vitro at low (19.1%), normal (38.5%), and high (58.3%) hematocrit levels, and at 6 glucose concentrations ranging from 2.06 mmol/L (37.1 mg/dL) to 30.24 mmol/L (544.7 mg/dL). RESULTS: Most systems, regardless of the reference to which they were calibrated, demonstrated positive bias at lower hematocrit levels and negative bias at higher hematocrit levels. Low, normal, and high hematocrit levels progressively lowered Precision G and Precision QID glucose measurements. Hematocrit effects on the other systems were more dependent on the glucose concentration. Overall, Accu-Chek Comfort Curve showed the least sensitivity to hematocrit changes, except at the lowest glucose concentration. CONCLUSIONS: We strongly recommend that clinical professionals choose glucose systems carefully and interpret glucose measurements with extreme caution when the patient's hematocrit value changes, particularly if there is a simultaneous change in glucose level.

Biosensing Techniques↗
PubMed1999

The laboratory-clinical interface: point-of-care testing.

POC testing provides an opportunity for clinicians and laboratorians to work together to consider how best to serve the patients within an individual institution. Each health system has unique characteristics relative to patient population, as well as a unique laboratory structure. If physicians, nurses, laboratorians, and pathologists work collaboratively, the best interests of patients will be served. In some institutions that cater to specific patient groups, POC testing may offer clear and distinct advantages. In other institutions with sophisticated transport systems and established rapid response capabilities, the quality resulting from central laboratory testing may outweigh any advantages of bedside testing. Clearly, attention to regulatory issues, QC issues, the importance of proper documentation, proficiency testing, performance enhancement, and cost-effectiveness is requisite. As the technology for diagnostic testing advances through more microcomputerization, microchemistry, and enhanced test menus, the concept of POC testing will need perpetual revisiting. We hope that the information provided here will aid clinicians, laboratorians, and administrators in their quest to best serve their patients.

Costs and Cost Analysis↗
PubMed1999

Knowledge optimization theory and application to point-of-care testing.

Point-of-care testing is defined as testing at or near the site of patient care wherever that medical care is needed. The number and types of tests available at the point of care are increasing dramatically. Point-of-care testing provides test results to the clinical team immediately, usually within a therapeutic turnaround time of five minutes. Immediacy of data is a primary benefit, but we must evaluate when, why, and where point-of-care testing should be used because in most cases this new modality is more expensive than conventional testing in clinical laboratories. Knowledge optimization integrates key components of testing, patient focusing, performance, and test clusters, in concert with synthesis of temporal and diagnostic-therapeutic process information that the physician can assimilate quickly and act on to improve patient outcomes. We identify through literature searches, meta-analysis, and documented outcomes results, the optimal applications of point-of-care testing in critical care and other medical settings. The basis for optimality is improved medical and/or economic outcomes. Results show that point-of-care testing is strongly justified for emergency resuscitations under any circumstances, in critical care, such as the operating room and intensive care unit, and in disease management. Long-range implications are: (1) the point-of-care testing trend will accelerate; (2) viable optimization tools include integrative strategies, clinical algorithms, care paths, and performance maps; (3) attention should be focused on rapid communication and understanding of critical results; and (4) enhanced human interfaces are crucial for efficient medical decision making and efficacious patient therapy.

Artificial Intelligence↗
PubMed1998

Multicenter study of oxygen-insensitive handheld glucose point-of-care testing in critical care/hospital/ambulatory patients in the United States and Canada.

OBJECTIVES: Existing handheld glucose meters are glucose oxidase (GO)-based. Oxygen side reactions can introduce oxygen dependency, increase potential error, and limit clinical use. Our primary objectives were to: a) introduce a new glucose dehydrogenase (GD)-based electrochemical biosensor for point-of-care testing; b) determine the oxygen-sensitivity of GO- and GD-based electrochemical biosensor test strips; and c) evaluate the clinical performance of the new GD-based glucose meter system in critical care/hospital/ambulatory patients. DESIGN: Multicenter study sites compared glucose levels determined with GD-based biosensors to glucose levels determined in whole blood with a perchloric acid deproteinization hexokinase reference method. One site also studied GO-based biosensors and venous plasma glucose measured with a chemistry analyzer. Biosensor test strips were used with a handheld glucose monitoring system. Bench and clinical oxygen sensitivity, hematocrit effect, and precision were evaluated. SETTING: The study was performed at eight U.S. medical centers and one Canadian medical center. PATIENTS: There were 1,248 patients. RESULTS: The GO-based biosensor was oxygen-sensitive. The new GD-based biosensor was oxygen-insensitive. GD-based biosensor performance was acceptable: 2,104 (96.1%) of 2,189 glucose meter measurements were within +/-15 mg/dL (+/-0.83 mmol/L) for glucose levels of < or = 100 mg/dL (< or = 5.55 mmol/L) or within +/-15% for glucose levels of > 100 mg/dL, compared with the whole-blood reference method results. With the GD-based biosensor, the percentages of glucose measurements that were not within the error tolerance were comparable for different specimen types and clinical groups. Bracket predictive values were acceptable for glucose levels used in therapeutic management. CONCLUSIONS: The performance of GD-based, oxygen-insensitive, handheld glucose testing was technically suitable for arterial specimens in critical care patients, cord blood and heelstick specimens in neonates, and capillary and venous specimens in other patients. Multicenter findings benchmark the performance of bedside glucose testing devices. With the new +/-15 mg/dL --> 100 mg/dL --> +/-15% accuracy criterion, point-of-care systems for handheld glucose testing should score 95% (or better), as compared with the recommended reference method. Physiologic changes, preanalytical factors, confounding variables, and treatment goals must be taken into consideration when interpreting glucose results, especially in critically ill patients, for whom arterial blood glucose measurements will reflect systemic glucose levels.

Adult↗
PubMed1998

A strategy for the use of cardiac injury markers (troponin I and T, creatine kinase-MB mass and isoforms, and myoglobin) in the diagnosis of acute myocardial infarction.

OBJECTIVE: To design a strategy for cardiac injury marker testing in the diagnosis of acute myocardial infarction. DESIGN: Prospective study. Group I (n=54 patients): evaluation of clinical performance. Specimens collected at 0, 3, 6, and 12 (+/-1.5) hours after presentation. World Health Organization criteria were used for diagnosis of acute myocardial infarction. Group II (n=57 patients): evaluation of temporal evolution. Time intervals 0 to 1.5, 1.5 to 4.5, 4.5 to 7.5, and 7.5 to 13.5 hours. Patients identified by positive creatine kinase-MB (CK-MB) mass or myoglobin. Fourteen patients in Group I qualified for Group II. Hence, the total number of patients was 97. SETTING: A team of laboratorians and clinicians at the University of California, Davis, hospital assessed the clinical performance and temporal evolution of serial CK-MB isoform, troponin I, and troponin T results in comparison to parallel CK-MB mass and myoglobin results. MAIN OUTCOME MEASURES: Group I: sensitivity, specificity, and positive and negative predictive values. Group II: the time interval of the first positive result for each cardiac injury marker. Strategy and conclusions were based on study results and a literature review. PARTICIPANTS: Emergency department patients with acute onset of chest pain and other complaints, possibly indicative of myocardial ischemia, who were under evaluation for admission. RESULTS: Twenty-seven cases of acute myocardial infarction were documented. Group I: troponin I had the highest specificity (100%) and the highest positive predictive value (100%); troponin I, troponin T, and CK-MB mass had the highest sensitivity (90.0%); and the negative predictive values of troponin I, troponin T, and CK-MB mass were comparable (97.8%, 97.6%, and 97.6%, respectively). Group II: early diagnosis (within 1.5 hours) was provided by both CK-MB isoforms and CK-MB mass, and then by myoglobin and troponins, in order of decreasing frequency. CONCLUSIONS: Creatine kinase-MB mass, myoglobin, and troponin I were selected as the cardiac injury markers of choice at our institution. The strategy calls for serial testing of myoglobin and CK-MB mass initially-and serially if warranted by heightened clinical suspicion--with troponin I added if indicated for (1) specific confirmation, (2) late presentation, or (3) risk stratification.

Biomarkers↗