Biomedical subjects

Martin H Kroll

Publications and source records attributed to Martin H Kroll.

6 recordsLinked to original sources

PubMed2004

Performance of four sources of cholesterol oxidase for serum cholesterol determination by the enzymatic endpoint method.

BACKGROUND: Cholesterol oxidase is used for the determination of serum cholesterol. It can be derived from Streptomyces, Pseudomonas fluorescens, Cellulomonas, and Brevibacterium. This study compared the performance characteristics of four enzymes in the endpoint cholesterol determination. METHODS: Using the Mega analyzer, we studied assay optimization, linearity, precision, recovery, interference, stability, and compared 110 patient samples. RESULTS: The linearity for the four enzymes was up to 13.0 mmol/l at the optimal enzyme activity. The average within-run CVs ranged from 1.6% to 1.9% and between-day ranged from 2.8% to 3.0%, within the NCEP analytical criteria. The analytical recoveries obtained from four reagents ( approximately 96.5%) were excellent. The assays using these enzyme sources compared favorably with the commercial method and appeared accurate near the clinical decision cut-points. Hemoglobin concentration at 1.9 g/l interfered with the P. fluorescens cholesterol oxidase. Bilirubin caused a negative interference while lipemia generated a positive interference with all enzyme sources. Reagents were stable up to 6 weeks. CONCLUSIONS: Streptomyces, Cellulomonas, and Brevibacterium were essentially analytically equivalent. Streptomyces and Cellulomonas cholesterol oxidase are one-quarter as expensive Brevibacterium. Cellulomonas is a new source of cholesterol oxidase for determining serum cholesterol by the endpoint method.

Bilirubin↗

PubMed2004

Evaluation of linearity in the clinical laboratory.

CONTEXT: Clinical laboratory assessment of test linearity is often limited to satisfying regulatory requirements rather than integrating this tool into the laboratory quality assurance program. Although an important part of quality control and method validation for clinical laboratories, linearity of clinical tests does not get the attention it deserves. OBJECTIVE: This article evaluates the concepts and importance of linearity evaluations for clinical tests. DESIGN: We describe the theory and procedural steps of each linearity evaluation. We then evaluate the statistical methods for each procedure. RESULTS: Visual assessment, although simple, is subjective. The lack-of-fit error and the 1986 NCCLS EP6-P G test are sensitive to imprecision and assume that the data are first order. Regression analysis, as developed as the polynomial method, is partly based on the experiences of the College of American Pathologists Instrumentation Resource Committee and has proved to be a robust statistical method. CONCLUSIONS: We provide general guidelines for handling non-linear results from a linearity evaluation. Handling linearity data in an objective manner will aid clinical laboratorians whose goal is to improve the quality of the tests they perform.

Clinical Laboratory Techniques↗

PubMed2003

Multicenter evaluation of the Roche NT-proBNP assay and comparison to the Biosite Triage BNP assay.

BACKGROUND: Brain natriuretic peptides (BNPs) are useful in the assessment of heart failure, left ventricular dysfunction, and acute coronary syndromes. METHODS: We performed a multicenter evaluation of the automated Roche NT-proBNP assay and compared its performance to the Biosite Triage BNP assay. RESULTS: The N-terminal (1-76) pro brain natriuretic peptide (NT-proBNP) method is precise (CV 2-fold higher CV, and plasma samples are more labile when stored at room temperature and 4 degrees C. Comparison studies showed a reasonable correlation between NT-proBNP and BNP assays, with a substantially higher slope bias of 6-20 for the NT-proBNP assay. CONCLUSIONS: The automated Roche NT-proBNP assay has good analytical performance and better precision than the Biosite BNP assay. Unlike BNP, NT-proBNP is stable in EDTA plasma for 3 days at room temperature or longer at 4 degrees C. The Roche NT-proBNP is fully automated and will accommodate the testing of large numbers of clinical samples for assessing cardiac dysfunction.

Anticoagulants↗

PubMed2002

Bioeffects of myocardial contrast microbubble destruction by echocardiography.

BACKGROUND: Microbubble destruction during contrast echocardiography is known to cause capillary leaks and red blood cell extravasation in skeletal muscle. This study evaluated the biological effects of microbubble destruction on cardiac muscle. METHODS: Contrast echocardiography was performed in 36 rats randomized to receive either Definity or Optison at a mechanical index (MI) of 1.6, 1.2, or 0.8. Myocardial bioeffects were assessed by measuring left ventricular (LV) size and fractional area shortening and histopathology. In addition, blood samples for troponin T were drawn at baseline, postinfusion (30 minutes), day 1, day 4, and day 7. LV size and function were measured at baseline and immediately prior to euthanasia on day 7, after which the heart was removed and sectioned for histopathology. RESULTS: There was no statistical difference in LV size or function regardless of the contrast agent or MI, nor was there any histopathological evidence of myocardial damage. However, troponin T increased over time (F = 3.77, P = 0.012), peaking at 30 minutes and returning to normal by day 4. The difference between Definity and Optison was not statistically significant. However, troponin T values were higher at a higher MI (F = 5.01, P = 0.012). Of 12 rats imaged at a MI of 1.6, 9 (75%) had elevated troponin T as compared to 4 (33%) of 12 at a MI of 1.2. None of the 12 rats imaged at a MI of 0.8 had an elevated troponin T at any time point. CONCLUSIONS: Microbubble destruction at high acoustic power (MI 1.6) can cause mild troponin T elevations that are not associated with LV dysfunction or histopathological evidence of myocardial damage.

Albumins↗

PubMed2002

Point-of-care testing for prothrombin time, but not activated partial thromboplastin time, correlates with laboratory methods in patients receiving aprotinin or epsilon-aminocaproic acid while undergoing cardiac surgery.

Point-of-care testing (POCT) of coagulation parameters can help optimize transfusion practice in cardiac surgery. Antifibrinolytic agents may interfere with the laboratory and/or POCT coagulation assays. This randomized controlled study compared coagulation parameters obtained from a whole blood POCT coagulation device with a typical laboratory instrument in cardiac surgery patients receiving aprotinin, epsilon-aminocaproic acid, or normal saline before undergoing cardiopulmonary bypass. Aliquots of arterial blood samples from 42 patients were collected perioperatively, and their prothrombin times (PTs) and activated partial thromboplastin times (aPTTs) were measured by POCT and laboratory instrumentation. Linear regression and error analyses were used for the method comparison. For PT, the POCT device compared favorably with the laboratory method. For aPTT, the POCT device did not compare well with the laboratory method. Treatment with antifibrinolytic agents does not interfere with determination of PT.

Aminocaproic Acid↗

PubMed2002

Evaluating sequential values using time-adjusted biological variation.

One can compare the difference between two sequential values with the biological variation. Biological variation is a measure of the random disturbances of an analyte's value, measured at different times. When the difference > Z square root 2 SD(BV) then the difference is due to an underlying disease process or physiologic change. A Z value of 1.96 yields a 95% confidence limit. When using multiple sequential values or time periods exceeding that for the empirically derived biological variance, a random walk model allows one to estimate the spread of the variance. For a difference, (delta) to be significant, delta > Z square root 2n SD(BV), where n is the ratio of time reflecting the longer time period divided by the shorter time period. Not all variances grow to this degree over time, because restoring forces diminish the extent of random disturbances. The relationship between a biological variance measured over a longer time period to the one measured over a shorter period can be expressed in terms of this restoring force as SD2 BV,n = SD2 BV,1 sigma(n) j=1 e(-2)(j-1)phi, where n is the ratio of time periods. One can calculate phi using this formula and a spreadsheet. From phi one can calculate the biological variance for any time period, within experimental limits, and compare the difference in sequential values with it. Test intervals can be calculated based on these biological variances.

Analysis of Variance↗