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Defined as red blood cell break down and the release of hemoglobin and intracellular contents into the plasma, hemolysis can seriously impact patient care as well as the laboratory's reputation through its affect on test results. Therefore, the European Preanalytical Scientific Committee, in collaboration with the International Federation of Clinical Chemistry Working Group on Patient Safety, have designed a questionnaire to collect data on prevalence and management of hemolytic specimens referred to the clinical laboratories for clinical chemistry testing. This book will help identify the areas where hemolysis occurs most frequently, which can, in turn, guide further analysis about why it is occurring. Once these elements are known, practices and procedures can be implemented to dramatically reduce hemolysis and avoid erroneous laboratory results affecting patient care and increasing laboratory costs.

Abstract Objectives: To describe the proportion of patients attending an accident and emergency department for whom blood analysis at the point of care brought about a change in management; to measure the extent to which point of care testing resulted in differences in clinical outcome for these patients when compared with patients whose samples were tested by the hospital laboratory. Design: Open, single centre, randomised controlled trial. Blood samples were randomly allocated to point of care testing or testing by the hospital's central laboratory. Setting: The accident and emergency department of the Bristol Royal Infirmary, a large teaching hospital which cares for an inner city population. Subjects: Representative sample of patients who attended the department between April 1996 and April 1997 and who required blood tests. Data collection was structured in 8 hour blocks so that all hours of the day and all days of the week were equally represented. Main outcome measures: The proportion of patients for whom point of care testing brought about a change in treatment in which timing was considered to be critical to clinical outcome. Mortality, the length of stay in hospital, admission rate, the amount of time spent waiting for results of blood tests, the amount of time taken to decide on management plans, and the amount of time patients spent in the department were compared between patients whose samples were tested at the point of care and those whose samples were sent to the laboratory. Results: Samples were obtained from 1728 patients. Changes in management in which timing was considered to be critical occurred in 59 out of 859 (6.9%, 95% confidence interval 5.3% to 8.8%) patients in the point of care arm of the trial. Decisions were made 74 minutes earlier (68 min to 80 min, P<0.0001) when point of care testing was used for haematological tests as compared to central laboratory testing, 86 minutes earlier (80 min to 92 min, P<0.0001) for biochemical tests, and 21 minutes earlier (−3 min to 44 min, P=0.09) for analyses of arterial blood gases. There were no differences between the groups in the amount of time spent in the department, length of stay in hospital, admission rates, or mortality. Conclusion: Point of care testing reduced the time taken to make decisions on patient management that were dependent on the results of blood tests. It also brought about faster changes in treatment for which timing was considered to be critical in about 7% of patients. These changes did not affect clinical outcome or the amount of time patients spent in the department. Key messages Point of care testing reduced the amount of time doctors spent waiting for results of blood tests when compared to the time spent waiting for results from the hospital laboratory in an accident and emergency department The time taken to decide on a management plan was also reduced as a result of the shorter time spent waiting for results of point of care tests About 7% of patients who needed urgent blood testing had changes in treatment in which timing was considered to be critical when point of care testing was used Patients did not spend less time in the accident and emergency department even when test results were available more quickly and patient management decisions were made more quickly. This suggests that the availability of test results is not the factor which slows down the arrangement of further care Improvements in process, such as a reduction in the time doctors wait for test results and the ability to make clinical decisions more quickly, do not seem to improve clinical outcome in this sample of patients

To provide a comprehensive overview of the complexities associated with cardiac troponin (cTn) testing. An emphasis is placed on the sources of error, organized into the preanalytical, analytical, and postanalytical phases of the testing pathway. Controversial areas are also explored. A case scenario and review of the relevant literature describing laboratory considerations involving cTn testing are described. Advanced comprehension of the specific assay used in a given laboratory is necessary for optimal reporting, utilization, and quality monitoring of cTn. cTn assays are reliable diagnostic tests for acute myocardial infarction, but understanding their limitations is required for appropriate result interpretation.

Blood obtained via fingerprick is commonly used in point-of-care assays, but few studies have assessed variability in parameters obtained from successive drops of fingerprick blood, which may cause problems for clinical decision making and for assessing accuracy of point-of-care tests. We used a hematology analyzer to analyze the hemoglobin concentration, total WBC count, three-part WBC differential, and platelet count in six successive drops of blood collected from one fingerprick from each of 11 donors, and we used a hemoglobinometer to measure the hemoglobin concentration of 10 drops of fingerprick blood from each of 7 donors. The average percent coefficient of variation (CV) for successive drops of fingerprick blood was higher by up to 3.4 times for hemoglobin, 5.7 times for WBC count, 3 times for lymphocyte count, 7.7 times for granulocyte count, and 4 times for platelets than in venous controls measured using a hematology analyzer. The average percent CV for fingerprick blood was up to 5 times higher for hemoglobin than venous blood measured using a point-of-care hemoglobinometer. Fluctuations in blood parameters with increasing volume of fingerprick blood are within instrument variability for volumes equal to or greater than 60 to 100 μL. These data suggest caution when using measurements from a single drop of fingerprick blood.

This scoping review protocol describes the strategy for a scoping review that aims to provide a comprehensive overview of published guidelines for the prescription of standard laboratory tests performed in intensive care unit (ICU) patients. The use of clinical laboratories is constantly increasing. However, there is evidence of inappropriate use. Inappropriate laboratory testing has the potential to harm patients, increase costs, burden staff, and has an environmental impact. Effective management can be achieved through demand managing strategies, such as providing guidelines on performing the appropriate test, for the right patient, at the right time. Although national and international guidelines exist for individual tests, a comprehensive summary of available recommendations for laboratory testing in the ICU is currently unavailable. This scoping review will incorporate documents that provide explicit advice on which test to perform in ICU patients. We selected 34 tests routinely ordered in the ICU. This review will consider any document type that matches our concept and context. We will consider gray literature with appropriate adherence to guidelines methodology. We will not limit the review by geographical location, but will only include articles published in English. Our scoping review will follow the Joanna Brigg Institute (JBI) methodology. We will search Medline (PubMed), Embase, Scopus, Google Scholar, and Google. Our search strategy adheres to the JBI 3-step construction approach for systematic reviews. We will search for keywords related to guidelines, laboratory testing, and the 34 selected tests. We will report our study using the S1 Checklist. Review registration number: osf.io/yfs9z.

Within-subject biological variation data (CV ) are used to establish quality requirements for assays and allow calculation of the reference change value (RCV) for quantitative clinical laboratory tests. The CV is generally determined using a large number of samples from a small number of individuals under controlled conditions. The approach presented here is to use a small number of samples (n = 2) that have been collected for routine clinical purposes from a large number of individuals. Pairs of sequential results from adult patients were extracted from a routine pathology database for 29 common chemical and hematological tests. Using a statistical process to identify a central gaussian distribution in the ratios of the result pairs, the total result variation for individual results was determined for 26 tests. The CV was then calculated by removing the effect of analytical variation. This approach produced estimates of CV that, for most of the analytes in this study, show good agreement with published values. The data demonstrated minimal effect of sex, age, or time between samples. Analyte concentration was shown to affect the distributions with first results more distant from the population mean more likely to be followed by a result closer to the mean. The process described here has allowed rapid and simple production of CV data. The technique requires no patient intervention and replicates the clinical environment, although it may not be universally applicable. Additionally, the effect of regression to the mean described here may allow better interpretation of sequential patient results.

Due to the influence of gender, race/genetics, age, lifestyle habits and geography on the references intervals (RIs), the Clinical and Laboratory Standards Institute (CLSI) recommends the determination of population-specific RIs. Ghana continues to depend on pre-established RIs from other countries which poses the risk of misdiagnoses and wrong treatment. This study presents the haemato-biochemical RIs from four eco-geographical zones in Ghana. In this population-based cross-sectional study, a total of 1227 randomly selected healthy voluntary blood donors from the four eco-geographic zones (Coastal Savannah, Rain Forest, Savannah and Transitional) were enrolled and screened. Based on the CLSI Guidance Document C28A2992, the data of eligible participants were used to non-parametrically determine the RIs for the haemato-biochemical parameters at the 2.5th and 97.5th percentiles. Comparison of analytes by gender was done by Wilcoxon rank sum test and eco-geographic differences were assessed using the Kruskal-Wallis with the Dunn post hoc multiple comparison tests. There were statistically significant differences in most of the haematological parameters (RBC, Hb, HCT, MCV, PLT, WBC; p-values <0.0001 and MCH; p-value = 0.007), and biochemical analytes (Urea, Cr, Trig, HDL-C, AST, ALT, ALP, GGT, BID, BIT, Prot-T and Albumin; p-values <0.0001) based on gender. Significant inter eco-geographic (intra-population) variations and substantial differences between the established RI and the RIs accompanying the analyzers used were also observed. This study reports significant inter-sex and inter-geographical differences in haemato-biochemical RIs in Ghana as well as differences in RIs with both the RIs accompanying the analyzers and those of other countries. Determining RIs representative of populations and including them in the report systems of laboratories to ensure effective and efficient healthcare service delivery is thus recommended.

BackgroundThe testing and result communication process in primary care is complex. Its successful completion relies on the coordinated efforts of a range of staff in primary care and external settings working together with patients. Despite the importance of diagnostic testing in provision of care, this complexity renders the process vulnerable in the face of increasing demand, stretched resources and a lack of supporting guidance.MethodsWe conducted a series of focus groups with patients and staff across four primary care practices using process-improvement strategies to identify and understand areas where either unnecessary delay is introduced, or the process may fail entirely. We then worked with both patients and staff to arrive at practical strategies to improve the current system.ResultsA total of six areas across the process were identified where improvements could be introduced. These were: (1) delay in phlebotomy, (2) lack of a fail-safe to ensure blood tests are returned to practices and patients, (3) difficulties in accessing results by telephone, (4) role of non-clinical staff in communicating results, (5) routine communication of normal results and (6) lack of a protocol for result communication.ConclusionsA number of potential failures in testing and communicating results to patients were identified, and some specific ideas for improving existing systems emerged. These included same-day phlebotomy sessions, use of modern technology methods to proactively communicate routine results and targeted training for receptionists handling sensitive data. There remains an urgent need for further work to test these and other potential solutions.

Background Quality control (QC) is critical for ensuring the accuracy and reliability of hematology testing. Traditional QC strategies, however, are often limited in their ability to provide timely detection of analytical errors and to adapt to complex, real‐world laboratory conditions. Methods In this multicenter study, we applied the Six Sigma quality management framework to systematically evaluate the performance of five hematology parameters (Hb, WBC, RBC, HCT, and PLT). To enhance QC monitoring, we established a dynamic quality control strategy that integrates moving average (MA) monitoring with a long short‐term memory (LSTM) predictive model. Patient sample data were incorporated alongside routine QC data to validate clinical adaptability. Results Sigma metrics revealed marked performance differences among the parameters, with Hb and WBC achieving world‐class or excellent performance (σ ≥ 6), while PLT showed relatively lower stability. The combined MA–LSTM approach significantly improved sensitivity for error detection while reducing false positives compared with conventional rule‐based QC. The dynamic model demonstrated robust predictive ability, enabling real‐time QC monitoring across multiple laboratory sites. Conclusion By combining Six Sigma evaluation, MA monitoring, and LSTM modeling, we propose a dynamic QC strategy that overcomes key limitations of conventional quality control methods. This approach provides laboratories with an intelligent, proactive, and clinically adaptable solution for improving the reliability of hematology testing and ensuring higher quality patient care. This study employed the Six Sigma quality management framework to evaluate the performance of hematology parameters across multiple centers and established a dynamic quality control strategy by integrating moving average (MA) and long short‐term memory (LSTM) methods. The proposed approach enhanced error detection sensitivity, reduced false positives, and enabled more intelligent, real‐time laboratory quality management.

Background and Objectives: Laparoscopic cholecystectomy is one of the most performed surgical procedures worldwide. In low-risk patients, routine postoperative blood tests are frequently ordered despite limited evidence supporting their necessity. The aim of the study was to evaluate the predictability of complications that may occur with routine postoperative blood tests. Materials and Methods: This retrospective study examined 538 patients who underwent surgery in Cam and Sakura City Hospital between May 2020 and May 2021. Patients were divided into two groups: no postoperative complications (Group NC, n = 521) and postoperative complications (Group C, n = 17). Demographic characteristics, including age and gender, duration of surgery, cystic duct closure method, drain use, complications, preoperative and postoperative blood tests, and the mean time of hospital stay, were the collected data throughout the study. Results: The analysis of the post-operative blood test values revealed that the total bilirubin (p = 0.005), ALT (p = 0.002), AST (p = 0.002), GGT (p = 0.02) and amylase (p = 0.034) values were statistically significantly higher in Group C than in Group NC, but these values did not exceed the normal range except for ALT, AST and GGT, which were slightly higher than the normal parameters. Seventeen patients (3.15%) developed postoperative complications, including biliary leakage (n = 1); choledocholithiasis (n = 2); cardiac (n = 2), pulmonary (n = 9), and hemorrhagic (n = 2) complications; and a superficial wound infection (n = 1). Most complications were identified by symptoms and clinical observation. Conclusions: Routine postoperative blood tests in low-risk laparoscopic cholecystectomy patients do not significantly contribute to the early detection of complications. Clinical observation and targeted use of laboratory or imaging tests in selected high-risk cases might be more efficient. This approach can help reduce unnecessary workload, hospital costs, and healthcare expenditures without compromising patient safety.