What is the Appropriate Reference Interval for Glucose?
[Editorials]
Nichols, James H.
A reference interval is defined as "(a range) of values obtained by observation or measurement of a particular type of quantity on a reference individual, an individual selected for comparison using defined criteria." Reference intervals are utilized in the interpretation of laboratory data to determine the health or illness of a patient. The concept of a reference interval is sometimes confused with a "normal" range. However, there are multiple definitions of normality. This has led to the recommended use of the term "reference" rather than "normal," because any given test result can be compared against a reference population with defined characteristics and the presence or absence of a disease without necessarily being "normal."
Laboratory accreditation standards of CLIA '88, JCAHO, CAP guidelines require the development of a reference interval or range of results to assist clinicians with interpretation of test results. To be compliant, all test results must be reported with an appropriate reference interval or the laboratory must have interpretive information readily available to clinicians. This makes sense because results on a single sample can vary between laboratories depending on the instrumentation, calibration, standardization, and methodology for sample analysis. Even reanalysis on the same analyzer can generate different results simply due to method imprecision. The reference interval thus incorporates biologic, instrument, and method variability in defining the range of results found in reference healthy individuals versus those with disease.
This requirement for reporting reference intervals is often at odds with the clinician's desire for succinct laboratory reports. The Laboratory Director must balance fulfillment of regulations against the amount and detail of the interpretive comments. Longer reference intervals provide better information but will lengthen laboratory reports and can break panels of linked patient results onto separate pages. Longer reference intervals or interpretive comments will also tend to not be read or utilized by physicians. Some physicians will even complain because they do not want pages of interpretive comments. Just give them the results. The Laboratory Director has the difficult task of trying to meet accreditation requirements while also pleasing the customer, the physician.
Unfortunately, for most tests, there is no single, universal reference interval that is applicable to all patients in every situation. Reference intervals can vary by age, sex, and race, and there are a multitude of metabolic, drug, and physiologic effects that influence the interpretation of any given result. Defining an appropriate reference interval that is required by a physician to properly interpret a test result while minimizing the amount of detail and information provided in the result report is a challenging task.
Take glucose, for instance. There are a variety of factors to consider when interpreting glucose test results. Glucose levels routinely vary throughout the day in response to meals. Increases of 18 to 63 mg/dL are noted after eating. Smaller increases have been seen after ingestion of a mixed meal containing both fat and starch, whereas larger increases were noted with a predominantly starch meal. On the other hand, vegetarians tend to have significantly lower mean concentrations of glucose when compared with individuals who consume meat. Glucose decreases upon fasting and drops of up to 45 mg/dL from mean glucose levels have been noted in individuals after 48 hours of fasting. Glucose also decreases after strenuous exercise, physical training, and weight loss, after drinking alcohol, and during pregnancy. Neonates have lower glucose levels than adults and can experience transient hypoglycemia, particularly in preterm infants. Whole blood levels are 12% to 15% lower than plasma glucose due to the lower water content in erythrocytes compared to plasma. During fasting, venous blood is only approximately 2 to 5 mg/dL lower than capillary glucose due to glucose absorption and cellular metabolism from capillary blood. However, capillary glucose concentrations may be 20 to 70 mg/dL higher than concurrent venous blood samples after a meal due to the postprandial effects of insulin on cellular uptake and metabolism. Preanalytic factors can further affect glucose variability, as delays in processing of blood samples can result in 5% to 7% decreases in glucose over time due to glycolysis. Glycolysis is greater at higher temperatures and in the presence of leukocytosis or bacterial infection. The use of glycolysis inhibitors, fluoride, and oxalate can slow glycolysis rates but can take an hour or 2 to become fully effective. The appropriate glucose reference interval will thus depend on a number of factors, including age of the patient, diet, exercise, and type of sample. Delays in processing and other preanalytic factors that could affect test interpretation should be commented with the test result to ensure notice by the clinician and appropriate action (ie, sample recollection).
Glucose is one of a few analytes (like cholesterol and prostate-specific antigen) where a consensus reference interval has been developed and promoted. The American Diabetes Association (ADA) recommends 1 of 3 criteria for diagnosis of diabetes mellitus:
1. Symptoms of diabetes (polyuria, polydipsia, and unexplained weight loss) plus a casual (random without regard to time since last meal) plasma glucose concentration >=200 mg/dL.
2. Fasting plasma glucose >=126 mg/dL (no energy intake for at least 8 hours).
3. Two-hour postload glucose >=200 mg/dL during an oral glucose tolerance test performed as described by the World Health Organization using a glucose load of 75 g of anhydrous glucose dissolved in water.
The ADA also defines impaired fasting glucose as a plasma glucose level between 100 and 125 mg/dL and the reference nondiabetic interval for glucose as <100 mg/dL after an 8-hour fast. Most hospitals have adopted these guidelines for their glucose reference intervals as a matter of simplicity to meet the accreditation requirements of attaching a reference interval to every test result.
However, there are problems with adopting a consensus recommendation as the glucose reference interval to be applied to all test results regardless of patient diagnosis or conditions for ordering the test. Can this reference interval be equally applied to both inpatients and outpatients? Inpatients are bedridden, are under more stress, and have less exercise than outpatients. What about inpatients on IV (intravenous) fluids and/or parenteral nutrition? Could IV patients be considered truly fasting or does the clinician have to consider the test to be more casual and random when interpreting the result? The ADA only mentions plasma glucose levels in their recommendation, but some laboratories only analyze serum. Is serum the same as plasma on all analyzers? Some devices and instruments, like the HemoCue, only accept whole blood. Given the differences between whole blood and plasma, the reference intervals would be expected to be different. What should be the appropriate reference interval for a whole blood analyzer? Clearly, the whole blood reference interval should be developed from individuals who are well defined, characterized, and donated whole blood samples rather than attempting to apply corrections to a plasma reference interval. Interpretation and application of an appropriate reference interval thus requires consideration of the patient's condition, type of sample, and the analytic methodology.
An important consideration for correct interpretation is also the reason why the test was ordered. Most glucose levels are ordered to manage insulin therapy, not to diagnose diabetes. The ADA does not have comparable recommendations for sliding insulin scales, and every clinician and institution tends to vary their dosage of insulin depending on the patient's condition, the type of insulin, the patient's past insulin response, and physician preference. Recent studies have additionally indicated the benefits of reduced infection rates and shorter hospitalizations by the management of intravenous insulin dosing based on glucose levels in postsurgical patients. The original Portland Protocol targeted maintenance of glucose levels <200 mg/dL in cardiac surgery patients, but this protocol has now been expanded to all surgical patients using lower targets of 150 mg/dL and even 100 to 125 mg/dL. Given the variability of insulin management, there is no single "reference" interval or universally accepted target goal for maintenance of glucose in specific situations like postsurgical, ambulant outpatient type 1 diabetic, hospitalized inpatients, or other clinical populations.
There are multiple layers of detailed interpretation that could be included in a glucose reference interval. However, much of this information would not be applicable to any single result, as there is only one purpose that the clinician had in mind when ordering the test. The level could be to diagnose diabetes and the specimen could have been fasting or 2 hours postprandial as part of a glucose tolerance test, or the level could have been ordered to manage insulin. The patient could be on intensive insulin drip, as part of a protocol, or the patient could be on an intermittent, as needed basis schedule. Each of these situations will have different reference intervals or targets. For diagnosis, the clinician may be considering whether the patient is fasting or not: if fasting, whether the result is <100 mg/dL, and if not fasting, whether the result is >200 mg/dL. For management, the patient may be on an insulin protocol with a specific target of 150 mg/dL, 200 mg/dL, or some other physician preference. Each of these patient situations requires a different reference interval or target.
Unfortunately, current Laboratory Information Systems (LIS) are not very sophisticated and do a very poor job at integrating patient diagnosis and symptoms with test results and interpretive comments. In many cases, we are solely forced into a "one-size, fits all" type of reference interval because the laboratory cannot practically list all possible effects and considerations involved in the interpretation of a glucose level in a succinct, concise manner to fit every patient. In practice, hospitals tend to adopt the consensus ADA recommendations simply to meet regulatory compliance rather than try to match the patient's clinical condition. Laboratories clearly know that a reference interval for glucose of <100 mg/dL works for outpatients who are fasting, but may not applicable to most of their inpatients on IV insulin, total parenteral nutrition, and other medications. Yet, the laboratory has to report some reference interval or interpretation with the glucose level to be compliant. So a single reference interval is applied equally to inpatients and outpatients realizing that it may not be applicable to hospitalized inpatients. The alternative is to adopt the more random glucose level that is diagnostic of diabetes for patients who are not fasting (ie, >=200 mg/dL), with the understanding that this test is probably not being ordered to diagnose patients but to manage their insulin therapy. It is thus difficult to fit one reference interval onto all inpatient glucose levels for insulin management, and it is not yet possible to customize an individual target for single patients in our current LIS.
In the LIS, reference intervals can be created for fasting glucoses that are tied to a test code for fasting glucose. Likewise, a 2-hour glucose reference interval can be attached to a test code for glucose tolerance tests. Different test codes can be created for urine glucose versus CSF glucose versus plasma or whole blood glucose. Pregnancy tolerance ranges can be created with specific test codes for each timed sample interval. Test codes and reference intervals can be created for random glucose levels or even insulin protocols. However, the maintenance and updating of multiple test codes becomes exceedingly complicated as the reference intervals become more individualized and detailed. Requisitions and electronic ordering systems will need to have multiple codes and test names that clearly distinguish one type of glucose test from another. As the laboratory creates more test codes, each with a different name and reference interval for specific purposes, there is a greater probability of clinicians ordering the wrong test and getting an inappropriate reference interval (which is what we were trying to prevent by creating multiple test codes in the first place).
Therefore, is the laboratory really benefiting the patient by forcing an interpretation that may be incorrect or even misleading simply to comply with a "one-size fits all" regulation? Wouldn't the laboratory be better not reporting a reference interval or claiming that the "reference interval depends on patient condition, purpose for test, and individual insulin management goals?" Or, would this comment be too long and lead to further physician complaints?
More detailed reference intervals based on age, sex, clinic, location, or even ordering physician become extremely complex to practically manage in large health systems without current LIS computers. In the future, with total electronic patient medical records, reference intervals may be more easily customized. The physician can order one glucose test, and the computer will be able to sort out what type of specimen was collected, when the last meal was ingested, what type of food was ingested, and report reference intervals applicable not only to the age and sex of a patient but also to their diet, exercise regimen, instrument methodology, type of sample, and even individualized patient therapeutic goals. Until such information systems are available, we may be better off not reporting a reference range for every glucose result. Interpretive information could be available in the ordering computer, on hospital Web sites, in laboratory manuals, or the laboratory can provide more detailed interpretive information individually when the clinician contacts the laboratory. In this manner, the Laboratory Director can guarantee that the clinician is comparing his result to the appropriate reference interval and that treatment fits the patient's needs. Laboratories should question regulations like CAP, JCAHO, and CLIA '88 that mandate a reference range for tests that may be difficult to effectively implement with our current level of technology. More importantly, the laboratory should investigate if it is harming patients by reporting an inappropriate reference interval. Laboratories rarely receive the information necessary for a proper interpretation, namely, why the physician ordered the test. Until the laboratory can routinely acquire why the test was ordered and how the result will be utilized in the continuing care of the patient with each test request, the laboratory will continue to face challenges when deciding how to apply an appropriate glucose reference interval and result interpretation.
Point of Care: The Journal of Near-Patient Testing & Technology, Volume 5(2), 2006, pp 49-51
What's New in Point-of-Care Testing in 2005?
[Literature Review on POCT]
Melanson, Stacy E. F.
Abstract: The field of point-of-care testing has expanded considerably during the past year including both technological advances in instrumentation and utilization of point-of-care testing. Literature published in 2005 on any aspect of point-of-care testing was reviewed. This article summarizes the most important findings in the fields of diabetes, coagulation, cardiac markers, infectious disease, and toxicology, as well as newer areas such as gynecology.
New advances have occurred in both the technology and in the utilization of point-of-care (POC) devices.1-5 Many automated readers have been designed to avoid result misinterpretation. Manufacturers have also focused on more sensitive methods such as immunosensors, which provide reduced assay time, wider measurement ranges, and quantitative results.1 In the areas of toxicology and infectious diseases, matrices other than whole blood or urine can be used for analysis. Saliva testing has been approved for both HIV testing and drugs of abuse. A focus on cost-effectiveness and efficiency, in addition to rapid turnaround time, has also been observed.3 The idea of POC in nonurgent situations has been explored. Point-of-care testing (POCT) at routine outpatient visits allows the physician to interpret and explain the results at the appointment avoiding follow-up phone calls. One study illustrated the benefit of ruling out urinary tract infections using a urine dipstick.3 This approach decreased laboratory workload and allowed decisions about antimicrobial therapy to be made immediately. Although the scope of POCT is evolving rapidly, mistakes are still made by operators,4 and some results may require laboratory confirmation.5
DIABETES
Diabetes is a major worldwide health care concern, and the benefits of monitoring diabetic status at the POC have been examined. Recent programs in rural Australia measure glucose, HbA1C, albumin-creatinine ratio, and lipids in diabetic patients at the POC. This process increases the number of patients achieving glycemic control and reduces HbA1C levels.6,7
Glucose meters are frequently used not only in rural clinics, but also in hospitals of all sizes. Despite the positive impact on patient care, problems with glucose meters, such as sampling error and the effects of hematocrit and oxygen tension, are well known.8,9 A new glucose meter that measures hematocrit and glucose simultaneously and automatically corrects for hematocrit has been reported.10 This device provides improved accuracy for glucose results especially in critically ill patients. In addition to the issue of low and high hematocrit, different glucose results may be obtained, depending on the sample type. Although small but significant differences are seen between capillary- and venous-derived bedside samples,9 a larger controversy exists about how to report discrepancies between whole blood and plasma glucose concentrations. The International Foundation for Clinical Chemistry recently recommended reporting the concentration of glucose in plasma, irrespective of sample type by using a factor of 1.11 to convert whole blood to an equivalent plasma concentration.8
Other devices to monitor diabetes at the POC are increasingly used. Two studies illustrate that HbA1C measurements on a POC analyzer, Bayer DCA2000, are comparable to the central laboratory.11,12 [beta]-Hydroxybutyrate was useful to identify patients at highest risk for diabetic ketoacidosis in an accident and emergency department in the United Kingdom.13 Analytes, such as glycated albumin, are also under investigation for their use as an index of glycemic control.14
COAGULATION
Many patients are prescribed warfarin for various medical conditions to prevent thromboembolism. Convenient methods, either at the POC or in the patient's home, are being used to monitor therapy and prevent over-anticoagulation or under-anticoagulation. The stability and reproducibility of some test devices have been confirmed.15 In addition, several studies have examined POC devices (CoaguCheckS and ProTime microcoagulation system monitor) and compared the results with those in the central laboratory.16-18 With most systems, the international normalized ratio (INR) is accurate, but a positive bias is seen with increasing INR. This bias is accentuated in patients receiving low-molecular-weight heparin in addition to warfarin.19 One study recommended requiring venipuncture for all POC INRs of more than 4.0.17 These results suggest that each laboratory should understand the benefits and limitations of the specific POC device and define guidelines for when testing is required in the central laboratory. Patient self-testing methods for INR (CoaguCheckS 20 and the ProTime 21) can provide results that are comparable to laboratory testing; however, the practice of home testing currently is not widely accepted or performed in the United States.22
In addition to PT-INR, methods for D-dimer at the POC have been developed. Studies in the past year have demonstrated the accuracy of the Dade Stratus CS DDMR 23 and illustrated the ability of D-dimer not only to rule out pulmonary embolism, but also to help exclude aortic dissection in patients with chest and/or back pain.24
CARDIAC MARKERS
Cardiac markers assessing the presence of ischemia, myocardial necrosis, heart failure, and inflammation have been measured at the POC. A recent study confirmed that bedside troponin testing decreases the length of stay in the emergency department.25 Although the accuracy and efficiency of POC troponin testing have been illustrated repeatedly, Hallani et al 26 demonstrated that the Roche assay exhibits poor sensitivity compared with the central laboratory for values less than 0.1 ng/mL. Participation from cardiology and the laboratory is still required to assist in interpretation of results.27
The Triage BNP assay has been available for several years as a tool to identify heart failure in patients presenting with shortness of breath. The Triage method was recently shown to provide similar diagnostic accuracy to the Beckman Access, but the authors noted that the results were method dependent and that a single predefined cutoff for BNP should not be used.28 BNP has also been shown to correlate with the magnitude of patient ductus arteriosus in premature newborns.29
Measurement of CRP at the POC is more recent and less common than the measurement of troponin or BNP. An evaluation of the I-CHROMA high-sensitivity C-reactive protein assay method demonstrated an excellent correlation with the TBA 200FR turbidimeter and the BNII nephelometer and may permit expansion of this test at the POC in the future.30
INFECTIOUS DISEASE
The Centers for Disease Control and Prevention has recently defined goals to prevent HIV transmission. Rapid or POC HIV testing has been recommended for women in labor with unknown HIV status to quicken antiretroviral therapy and prevent neonatal transmission. The POC Oraquick method was shown to be more cost-effective in a low-prevalence population than the enzyme-linked immunosorbent assay method.31 Due to its specificity, the Oraquick produced fewer false positives, therefore decreasing unnecessary treatment with antiretrovirals and the associated economic and social costs. Rapid HIV testing has also been implemented in other settings such as emergency departments and infectious disease clinics. Kendrick et al 32 illustrated the use of POC HIV for the identification of patients who are newly HIV infected.
OTHER
The role of POCT in the areas of diabetes, coagulation, cardiac markers, HIV, and toxicology has been described for several years. Some newer areas include gynecologic infections, bladder cancer, and blood typing. An immunochromatographic capillary flow (dipstick) assay for Trichomonas vaginalis was used in a clinic and was shown to be comparable to microscopy and culture.35 A recent study also examined the ability of nuclear matrix protein NMP22 at the POC to aid in the detection of bladder cancer.36 Assays for thyroid peroxidase and thyroglobulin antibody were found to be useful in patients with suspected cancer or other thyroid conditions.37 Initial studies on testing for Rh (D) phenotype at the POC demonstrated acceptable sensitivity, specificity, and accuracy.38 Performing lipids 39 and lactate 40 at the POC has also been described.
Despite the advances in POCT, several issues still need to be resolved. Data management and entry of results into an information system are particularly challenging with visually read methods that require manual entry into the patient record. Lockout and fault-blocking functions are necessary to prevent operator areas. Finally, POC continues to be more expensive on a unit-cost basis than testing performed in the central laboratory, although some studies over recent years have demonstrated the overall cost-effectiveness of POCT in selected situations.
REFERENCES
1. von Lode P. Point-of-care immunotesting: approaching the analytical performance of central laboratory methods. Clin Biochem. 2005;38:591-606. Full Text Bibliographic Links [Context Link]
2. Cho JH, Pack EH, Cho IH, et al. An enzyme immunoanalytical system based on sequential cross-flow chromatography. Anal Chem. 2005;77:4091-4097. Bibliographic Links [Context Link]
3. Patel HD, Livsey SA, Swann RA, et al. Can urine dipstick testing for urinary tract infection at point of care reduce laboratory workload? J Clin Pathol. 2005;58:951-954. Ovid Full Text Bibliographic Links [Context Link]
4. Meier FA, Jones BA. Point-of-care testing error: sources and amplifiers, taxonomy, prevention strategies, and detection monitors. Arch Pathol Lab Med. 2005;129:1262-1267. Full Text Bibliographic Links [Context Link]
5. Mshelia DS, Buba AA. Point of care testing: a delight or a dilemma in the developing world? An overview. Niger Postgrad Med J. 2005;12:136-139. Bibliographic Links [Context Link]
6. Shephard MD, Mazzachi BC, Shephard AK, et al. The impact of point of care testing on diabetes services along Victoria's Mallee Track: results of a community-based diabetes risk assessment and management program. Rural Remote Health. 2005;5:371. [Context Link]
7. Shephard MD, Gill JP. An innovative Australian point-of-care model for urine albumin:creatinine ratio testing that supports diabetes management in indigenous medical services and has international application. Ann Clin Biochem. 2005;42:208-215. Full Text Bibliographic Links [Context Link]
8. D'Orazio P, Burnett RW, Fogh-Andersen N, et al. Approved IFCC recommendations on reporting results for blood glucose (abbreviated). Clin Chem. 2005;51:1573-1576. Full Text Bibliographic Links [Context Link]
9. Boyd R, Leigh B, Stuart P. Capillary versus venous bedside blood glucose estimations. Emerg Med J. 2005;22:177-179. Bibliographic Links [Context Link]
10. Rao LV, Jakubiak F, Sidwell JS, et al. Accuracy evaluation of a new glucometer with automated hematocrit measurement and correction. Clin Chim Acta. 2005;356:178-183. Bibliographic Links [Context Link]
11. Martin DD, Shephard DD, Freeman H, et al. Point-of-care testing of HbA1C and blood glucose in a remote aboriginal Australian community. Med J Aust. 2005;16:524-527. Full Text Bibliographic Links [Context Link]
12. Greaves RF, Northfield JA, Cameron FJ. Haemoglobin A1c: evaluation of three point of care analysers for use in a pediatric diabetes clinic. Ann Clin Biochem. 2005;42:124-129. Full Text Bibliographic Links [Context Link]
13. Harris S, Ng R, Syed H, et al. Near patient blood ketone measurements and their utility in predicting diabetic ketoacidosis. Diabet Med. 2005;22:221-224. Bibliographic Links [Context Link]
14. Yamaguchi M, Kambe S, Eto T, et al. Point of care testing system via enzymatic method for the rapid, efficient assay of glycated albumin. Biosens Bioelectron. 2005;21:426-432. Full Text Bibliographic Links [Context Link]
15. van den Besselaar AM, Hockstra MM. Long-term stability and reproducibility of CoaguChek test strips. Thromb Haemost. 2005;93:1189-1192. Bibliographic Links [Context Link]
16. Kitchen DP, Kitchen S, Jennings I, et al. Point of care testing by health care professionals: current practice amongst the UK National External Quality Assessment Scheme Participants. Br J Haematol. 2005;130:320-321. Bibliographic Links [Context Link]
17. Dorfman DM, Goonan EM, Boutilier MK, et al. Point-of-care (POC) versus central laboratory instrumentation for monitoring oral anticoagulation. Vasc Med. 2005;10:23-27. Full Text Bibliographic Links [Context Link]
18. McBane RD, Felty CL, Hartgers ML, et al. Importance of device evaluation for point-of-care prothrombin time international normalized ratio testing for programs. Mayo Clin Proc. 2005;80:181-186. Ovid Full Text Full Text Bibliographic Links [Context Link]
19. Phillips EM, Buchan DA, Newman N, et al. Low-molecular-weight heparin may alter point-of-care assay for international normalized ratio. Pharmacotherapy. 2005;25:1341-1347. Bibliographic Links [Context Link]
20. Gardiner C, Williams K, Mackie IJ, et al. Patient self-testing is a reliable and acceptable alternative to laboratory INR monitoring. Br J Haematol. 2005;128:242-247. [Context Link]
21. Sunderji R, Gin K, Shalansky K, et al. Clinical impact of point-of-care laboratory measurement of anticoagulation. Am J Clin Pathol. 2005;123:184-188. Bibliographic Links [Context Link]
22. Wittkowsky AK, Sekreta CM, Nutescu EA, et al. Barriers to patient self-testing of prothrombin time: national survey of anticoagulation practitioners. Pharmacotherapy. 2005;25:265-269. Bibliographic Links [Context Link]
23. Freyburger G, Reboul MP, Labrouche S, et al. Diagnosis accuracy of a new challenger for thrombosis exclusion, the Stratus CS DDMR. Clin Chim Acta. 2005;354:181-189. Full Text Bibliographic Links [Context Link]
24. Akutsu K, Sato N, Yamamoto T, et al. A rapid beside D-dimer assay (cardiac D-dimer) for screening of clinically suspected acute aortic dissection. Circ J. 2005;69:397-403. Bibliographic Links [Context Link]
25. Singer AJ, Ardise J, Gulla J, et al. Point-of-care testing reduces length of stay in emergency chest pain patients. Ann Emerg Med. 2005;45:587-591. Ovid Full Text Full Text Bibliographic Links [Context Link]
26. Hallani H, Leung DY, Newland E, et al. Use of a quantitative point-of-care test for the detection of serum cardiac troponin T in patients with suspected acute coronary syndromes. Intern Med J. 2005;35:560-562. Bibliographic Links [Context Link]
27. DiSerio F, Amodio G, Varraso L, et al. Integration between point-of-care cardiac markers in an emergency/cardiology department and the central laboratory: methodological and preliminary clinical evaluation. Clin Chem Lab Med. 2005;43:202-209. Bibliographic Links [Context Link]
28. Prontera C, Storti S, Emdin M, et al. Comparison of a fully automated immunoassay with a point-of-care testing method for B-type natriuretic peptide. Clin Chem. 2005;51:1274-1276. Full Text Bibliographic Links [Context Link]
29. Flynn PA, da Graca RL, Auld PA, et al. The use of a bedside assay for plasma B-type natriuretic peptide as a biomarker in the management of patent ductus arteriosus in premature neonates. J Pediatr. 2005;147:38-42. Full Text Bibliographic Links [Context Link]
30. Oh SW, Moon JD, Park SY, et al. Evaluation of fluorescence hs-CRP immunoassay for point-of-care testing. Clin Chim Acta. 2005;356:172-177. Bibliographic Links [Context Link]
31. Doyle NM, Levison JE, Gardner MO. Rapid HIV versus enzyme-lined immunosorbent assay screening in a low-risk Mexican American population presenting in labor: a cost-effectiveness analysis. Am J Obstet Gynecol. 2005;193:1280-1285. Ovid Full Text Full Text Bibliographic Links [Context Link]
32. Kendrick SR, Kroc KA, Withum D, et al. Outcomes of offering rapid point-of-care HIV testing in a sexually transmitted disease clinic. J Acquir Immune Defic Syndr. 2005;38:142-146. Ovid Full Text Bibliographic Links [Context Link]
33. Tomaszewski C, Runge J, Gibbs M, et al. Evaluation of a rapid bedside toxicology screen in patients with suspected drug toxicity. J Emerg Med. 2005;28:389-394. Full Text Bibliographic Links [Context Link]
34. Dale C, Aulaqi AA, Baker J, et al. Assessment of a point-of-care test for paracetamol and salicylate in blood. QJM. 2005;98:113-118. Ovid Full Text Bibliographic Links [Context Link]
35. Huppert JS, Batteiger BE, Braslins P, et al. Use of an immunochromatographic assay for rapid detection of Trichomonas vaginalis in vaginal specimens. J Clin Microbiol. 2005;43:684-687. Bibliographic Links [Context Link]
36. Grossman HB, Messing E, Soloway M, et al. Detection of bladder cancer using a point-of-care proteomic assay. JAMA. 2005;293:810-816. Ovid Full Text Bibliographic Links [Context Link]
37. Burne P, Mitchell S, Rees Smith B. Point-of-care assays for autoantibodies to thyroid peroxidase and to thyroglobulin. Thyroid. 2005;15:1005-1010. Bibliographic Links [Context Link]
38. Herold TJ, Whittaker DS, Glynn T. Determining the accuracy of a rapid point-of-care test for determining Rh(D) phenotype. Acad Emerg Med. 2005;12:474-476. Full Text Bibliographic Links [Context Link]
39. Panz VR, Raal FJ, Paiker J, et al. Performance of the CardioChek PA and Cholestech LDX point-of-care analysers compared to clinical diagnostic laboratory methods for the measurement of lipids. Cardiovasc J S Afr. 2005;16:112-117. Bibliographic Links [Context Link]
40. Rossi AF, Khan DM, Hannan R, et al. Goal-directed medical therapy and point-of-care testing improve outcomes after congenital heart surgery. Intensive Care Med. 2005;31:98-104. Full Text Bibliographic Links [Context Link]
Point of Care: The Journal of Near-Patient Testing & Technology, Volume 5(2), June 2006, pp 74-76
ANATOMIC PATHOLOGY
Histopathological Evaluation Of Ocular Microsporidiosis By Different Stains
Joveeta Joseph, Geeta K Vemuganti, Prashant Garg and Savitri Sharma
Background
There is limited data on comparing stains in the detection of microsporidia in corneal biopsies. Hence we wanted to evaluate various stains for their ability to detect microsporidia in corneal tissue sections.
Methods
Four cases diagnosed with microsporidiosis on Hematoxylin and Eosin and Periodic Acid Schiff's stained sections of the corneal button between January 2002 and December 2004, were included. Further sections were prospectively stained with calcofluor white, Gram, Giemsa, Masson's trichrome, acridine orange, Gomori's methenamine silver, Gram's chromotrope and modified acid fast stain. The stained sections were analyzed for the spore characteristics in terms of size, shape, color contrast, cell wall morphology, waist band in cytoplasm and ease of detection.
Results
All sections showed microsporidial spores as 3 – 5 μm, oval bodies. 1% acid fast, Gram's chromotrope and GMS stains provided a reliable diagnosis of microsporidia as diagnostic waist band could be identified and good contrast helped distinguish the spores from inflammatory debris.
Conclusion
Considering the ease of performance, cost effectiveness and rapidity of the technique, 1% acid fast stain and Gram's chromotrope stain are ideal for the detection of microsporidia.
BMC Clinical Pathology 2006, 6:6, 23 , 2006
Primary Histologic Diagnosis Using Automated Whole Slide Imaging: A Validation Study
Only prototypes 5 years ago, high-speed, automated whole slide imaging (WSI) systems (also called digital slide systems, virtual microscopes or wide field imagers) are becoming increasingly capable and robust. Modern devices can capture a slide in 5 minutes at spatial sampling periods of less than 0.5 micron/pixel. The capacity to rapidly digitize large numbers of slides should eventually have a profound, positive impact on pathology. It is important, however, that pathologists validate these systems during development, not only to identify their limitations but to guide their evolution.
Three pathologists fully signed out 25 cases representing 31 parts. The laboratory information system was used to simulate real-world sign-out conditions including entering a full diagnostic field and comment (when appropriate) and ordering special stains and recuts. For each case, discrepancies between diagnoses were documented by committee and a "consensus" report formed that was then compared with the microscope-based, signed out report from the clinical archive.
In 17 of 25 cases there were no discrepancies between the individual study pathologist reports. In 8 of the remaining cases, there were 12 discrepancies, including 3 in which image quality could be at least partially implicated. When the WSI consensus diagnoses were compared with the original sign-out diagnoses, no significant discrepancies were found. Full text of the pathologist reports, the WSI consensus diagnoses, and the original sign-out diagnoses are available as an attachment to this publication.
Conclusions
The results indicated that the image information contained in current whole slide images is sufficient for pathologists to make reliable diagnostic decisions and compose complex diagnostic reports. This is a very positive result; however, this does not mean that WSI is as good as a microscope. Virtually every slide had focal areas in which image quality (focus and dynamic range) was less than perfect. In some cases, there was evidence of over-compression and regions made "soft" by less than perfect focus. We expect systems will continue to get better, image quality and speed will continue to improve, but that further validation studies will be needed to guide development of this promising technology.
BMC Clinical Pathology 2006, 6:4, 27. 2006
Cellular Fibromas of the Ovary: A Study of 75 Cases Including 40 Mitotically Active Tumors Emphasizing Their Distinction From Fibrosarcoma Irving JA, Alkushi A, Young RH et al
Cellular fibroblastic tumors of the ovary are currently classified as either cellular fibroma (CF) or fibrosarcoma. The former are characterized by bland nuclei, 3 or fewer mitotic figures per 10 high-power fields (MFs/10 HPFs), and a low malignant potential, whereas fibrosarcomas usually have severe nuclear atypia, >/=4 MFs/10 HPFs, and an aggressive clinical course. The prognosis of cellular fibromatous tumors with >/=4 MFs/10 HPFs and low-grade cytology is not established and it is the purpose of this study to investigate that aspect. It has been our anecdotal experience that otherwise typical CFs with >/=4 MFs/10 HPFs usually have a benign clinical course, suggesting that such tumors should be regarded as "mitotically active cellular fibroma" (MACF) rather than fibrosarcoma. Seventy-five cellular fibromatous neoplasms were analyzed to determine their clinicopathologic features and the appropriateness of "MACF" as a designation for otherwise typical CFs with >/=4 MFs/10 HPFs. The mean age of patients with CF (n=35, 0 to 3 MFs/10 HPFs) and MACF (n=40, >/=4 MFs/10 HPFs) was 51 and 41 years, respectively. Patients most commonly presented with symptoms related to a pelvic mass. All tumors were unilateral. The mean tumor size of CFs was 8.0 cm and 9.4 cm for MACFs. The majority of the tumors were solid; approximately one-third of them had a cystic component. Ovarian surface adhesions, involvement of the ovarian surface, or both, was present in 6% of CFs and 10% of MACFs. Eleven percent of CFs and 13% of MACFs were associated with extraovarian involvement. All tumors consisted of cellular, intersecting bundles of spindle cells with bland nuclear features. The mean highest mitotic count for MACFs was 6.7 MFs/10 HPFs (range 4 to 19 MFs/10 HPFs). Follow-up of 3 months to 12 years (mean 4.75 y) was available in 18 of the 40 patients with MACFs and was uneventful in all cases. We conclude that cellular fibromatous neoplasms with bland cytology and elevated mitotic counts are associated with favorable patient outcome and should be diagnosed as MACF rather than fibrosarcoma, which usually have moderate to severe atypia and elevated mitotic rates. As prior observations have shown that even typical CFs can occasionally recur locally, particularly if they are associated with rupture or adherence, long-term follow-up for patients with CFs and MACFs is appropriate.
Am J Surg Pathol. 2006 Aug;30(8):929-938.
July 2006
July 2006