Preanalytical Errors Research Articles

Nursing organization and management in the practice of blood sample collection

Laboratory testing of blood samples is essential for the diagnosis and treatment of patients. This article aims to describe preanalytical errors in the clinical laboratory from a nursing management approach. Diagnostic tests are clinical decision support tools. Their use is said to be adequate or appropriate if the result answers the question that the clinician had asked himself before its request and, at the same time, if it helps him to decide some therapeutic action that benefits the patient. Venous blood collection is one of the most frequent nursing interventions in the ED, as well as a conclusive diagnostic test to establish a clinical judgment. Laboratory results have been estimated to affect up to 70 % of the medical diagnosis, thus impacting the course of treatment and prognosis of patients. Therefore, it is necessary to have excellent quality control throughout the laboratory process to ensure that the results released to the clinician are reliable and truthful. In the pre-analytical process there is a wide variety of errors, these errors cover several areas; those related to the blood test request, i.e., that it is inadequate or incorrectly performed, lost or misidentified

Influence of exogenous and endogenous factors on the quality of the preanalytical stage of laboratory tests (review of literature).

A literature review in the article presents an analysis of the influence of endogenous and exogenous factors on quality of preanalytical phase of laboratory testing. The review shows significance of external and internal factors influencing blood samples at preanalytical phase of laboratory testing. Among the exogenous factors considered: phlebotomy, test tubes for samples, transportation and storage. A number of factors exist at this phase that significantly affect test results. We examined these aspects of phlebotomy process: staff training, disinfectant contamination, needle diameter, needle material contamination. The review considers possible contamination with tube components and the importance of choosing the right anticoagulants and excipients. Transportation and storage of biological samples can be a source of errors at the preanalytical phase of laboratory testing. We analyzed the problem of determining the stability of analytes during storage and aspects of transportation samples by modern means. Among the endogenous factors considered: hemolysis, lipemia, icterricity, cell metabolism.. Hemolysis is one of the most frequent consequences of errors at the preanalytical phase. We analyzed importance of choosing a method for identifying hemolized tubes and the heterogeneity of bias results on different analytical systems. The review shows contribution of various classes of lipoproteins to turbidity of sample, possible preanalytical errors and impact on analytical tests. We examined possible effects of high bilirubin concentrations on analyte measurements. In the review, we also examined metabolism of some cells and its effect on samples.

A Study on Sample Rejection Rates due to Pre-analytical Errors: Associated Factors and Knowledge, Attitudes and Practices of Nurses on Blood Sample Collection for Haematology at a Teaching Hospital in Sri Lanka

Introduction: Clinical diagnosis is mostly dependent on laboratory test results. Studies have shown that 70% of clinical laboratory samples are rejected due to pre-analytical errors. This study was conducted to assess; rejection rates of blood samples, major reasons for rejection of blood samples, and knowledge, attitudes and practice of nurses on blood sample collection. Methods: Details of rejected blood samples were collected using data sheets of rejected blood specimens at the Teaching Hospital Karapitiya, Sri Lanka. Knowledge, attitudes and practices of nursing officers on blood sample collection were assessed using a self-administered questionnaire. Data were analyzed using SPSS version 22. Results: Overall blood sample rejection rate was 3.3%. The major cause of rejection of blood samples was the clotting of specimens. Insufficient volume, hemolysis, unavailability of request form for investigation, discrepancies in bed head tickets, discrepancies of the names, and use of IV line for blood collection were among the other reasons for sample rejection. The highest rejection rate was reported from the samples obtained for Prothrombin time/International Normalized Ratio (PT/INR) test. According to the scores obtained for knowledge of the nurses on blood sample collection, 43% of them scored ‘average’ while 38% scored ‘good’. The nurses’ attitudes on blood sample collection were satisfactory. Conclusions: Overall rejection rate was higher in the Haematology Laboratory of Teaching Hospital Karapitiya compared to the values reported elsewhere. Although the overall knowledge of nurses was satisfactory regarding blood sample collection, aspects such as knowledge on the correct volume of blood needed for specific investigations, choosing a suitable site for blood drawing, and practices such as the provision of duly filled investigation forms need to be improved.Keywords: Rejection rate, Pre-analytical error, Haematology, Blood, Sample collection

Mortality in an Italian nursing home during COVID-19 pandemic: correlation with gender, age, ADL, vitamin D supplementation, and limitations of the diagnostic tests.

Introduction: The COVID-19 pandemic caused an increased mortality in nursing homes due to its quick spread and the age-related high lethality.Results: We observed a two-month mortality of 40%, compared to 6.4% in the previous year. This increase was seen in both COVID-19 positive (43%) and negative (24%) residents, but 8 patients among those testing negative on the swab, tested positive on serological tests. Increased mortality was associated with male gender, older age, no previous vitamin D supplementation and worse “activities of daily living (ADL)” scores, such as Barthel index, Tinetti scale and S.OS.I.A. classification.Conclusion: Our data confirms a higher geriatric mortality due to COVID-19. Negative residents also had higher mortality, which we suspect is secondary to preanalytical error and a low sensitivity of the swab test in poorly compliant subjects. Male gender, older age and low scores on ADL scales (probably due to immobility) are risk factors for COVID-19 related mortality. Finally, mortality was inversely associated with vitamin D supplementation.Design: In this observational study, we described the two-month mortality among the 157 residents (age 60-100) of a nursing home after Sars-CoV-2 spreading, reporting the factors associated with the outcome. We also compared the diagnostic tests for Sars-CoV-2.

Risk assessment of pre-analytical errors and their impact on patient safety in a tertiary care centre in South India

To identify the different preanalytical errors encountered in the central laboratory and to adopt the corrective measures to overcome them. To identify the cause of the preanalytical errors. To evaluate the impact of corrective measures and their role on patients safetyThe study comprised of 500 samples over a period of one year in Central Laboratory, Mahatma Gandhi Medical College and Research Institute, Pondicherry. The study included all the samples collected from the patients that are sent to the Central laboratory, Mahatma Gandhi Medical College and Research Institute, departments like Pathology, Biochemistry and Microbiology. The samples were received along with the patients request form which included the patients details like name, age, sex, treating clinician, place of admission or where from the sample was collected, nature of the sample, the name of the test, clinical diagnosis etc. Amongst 500 samples received, preanalytical errors were detected in 263(52.6%) samples. Majority 83.6% were from inpatient wards, whereas 16.4% samples were from outpatient departments.58.1% of samples were from Hematology, 21.6% of samples were from Biochemistry and 20.1% of samples were from Microbiology. 54.3% of samples were blood samples, 42.9% of were serum samples and 2.6% of were urine samples. The most common pre-analytical error encountered was insufficient volume accounting to 27.7% and least encountered pre-analytical error was Lipemic sample accounting to 7.2%. Failure Mode and Effects Analysis(FMEA) was applied and insufficient volume, diluted sample, mismatch name, clotted sample and lipemic sample were graded as very high with scale of 8. Insufficient information alone was graded as high grade with scale 7. It is the need of the hour to adopt adequate, effective corrective strategies to curb the pre-analytical errors in the laboratory, thereby ensuring safety and satisfaction to the patients and clinicians, which would pave the way for an efficient heath care system.

Preanalytical variables and its impact on total quality management of clinical biochemistry laboratory- A tertiary referral rural hospital study

Introduction: Advances in science and Technology have led to transformation of laboratory diagnostics from manual, cumbersome testing methods to fully automated science, ensuring accuracy and speed. Quality is the core issue for all laboratories and this requires total quality management in the laboratory process in the preanalytical, analytical and post analytical phases. Objectives: To study and evaluate the types, frequency and magnitude of errors in our tertiary health care clinical Biochemistry Laboratory in the preanalytical testing process and its overall impact on Total Quality Management System of our laboratory. Materials and Methods: A prospective observational study, samples received for analysis between Jan 2015 to Dec 2015 in the clinical biochemistry section was evaluated for various preanalytical errors. We evaluated the frequency and types of preanalytical errors found in our laboratory by monitoring specimes requested for laboratory analyses from both inpatient and outpatient divisions and statistically analyzed. Results and Discussion: Of the total 1,38,275 analytical requests, 6446 (4.66%) samples were rejected due to various errors in preanalytical variables. For the inpatient samples, preanalytical error rate was 4.20% (4107 samples), the preanalytical variable with highest frequency of occurrence was specimen hemolysis/ Lipemic sample (1.00%) 980 samples. For the outpatient sample preanalytical error rate was 5.75% (2339). The variable with highest frequency was requisitions with incomplete patient treating physician information 1.37% (559). Preanalytical errors in laboratories are very common and play a very important role in patient care and treatment. Lipemic/hemolytic samples are known to affect the parameter to be analysed and incomplete patient information leads to error in reporting the patient’s results, which means the post analytical error becomes unavoidable and incomplete treating physician information leads to delayed reporting

Effectiveness of computerized ordering of test using unique hospital identification number to reduce pre analytical errors - a cross sectional study in a tertiary care hospital of south India

Introduction: Laboratory test request forms are important communication device between the clinician and lab personnel. Studies have confirmed that most laboratory errors occur in the preanalytical phase clinicians are ordering investigations in paper request forms which are incomplete with regard to patient information and clinical details. Ordering the request through hospital computers using UHID number of the patient can reduce preanalytical errors. Materials and Methods: Our study evaluated 806 Biochemistry lab report forms, by systematic sampling that reached Central Biochemistry lab from August to October 2016 and the same patients report forms retrieved from hospital computer using UHID number are compared for specific variables. Results: Analysis of the study shows that information regarding sample collection time, sample receiving time in lab, reference range of the analyte, and name of the doctor are 100% entered in hospital computer but 0% entry in the paper request forms. General information of the patient 100% entry in hospital computer, in paper report form it is 98%. But clinical notes, drug history and diagnosis not mentioned in both the hospital computer and the paper request forms. Conclusion: Computerized entry and ordering of investigations by health care persons will reduce preanalytical errors. Keywords: Preanalytical errors, Computerised ordering, Biochemistry lab reports, UHID Number.

Comparative evaluation of Rosner’s index (ICA) Vs Chang’s (% correction) as a screening test (mixing study)

Introduction: It is difficult to interpretate mixing study results (both screening & confirmatory) in presence of LAC. The main objective of this study is to define cut off values for ICA & % Correction which will reduce the no. of false positive & negative cases & will help in proper categorization of factor deficiency & inhibitors. This study also briefs about preanalytical errors & their correction Material and Methods: Rosner Index= × Cut offs ? 10 = Correction & ? 15 = Inhibitor Latest Sysmex CS-5100 auto-analyser was used to determine the Cut-offs. DRVVT mixing test ratio (Rosners index/ ICA) 1.15, % correction = 10, DRVVT Normalised ratio (NR) = 1.05. p value < 0>15 is 91.1% sensitive for inhibitor diagnosis & it could not categorise, 8% of total cases into factor deficiency /inhibitor. Discussion: Rosners index (ICA) as a confirmatory test for LA is more sensitive than % correction & DRVVT NR. Chang’s % correction with a cut off value of >70% is 85% sensitive in diagnosing factor deficiency & a cut off value of Conclusion: It can be safely concluded that Rosner index is better than % correction, both as a screening test & confirmatory test, to differentiate factor deficiency from inhibitor. This study results are in agreement with CLSI guidelines & favours the sequential order screen-confirm- & then if required mixing study as in case of screen and confirm analysis is not clear-cut and/or when other causes of prolonged clotting times are known or suspected The draw back with the mixing studies is that weak LAC can be missed. Though in this study Nijmegen is better than Bethesda in terms of sensitivity & specificity as the later gives false positive results, other studies has to be taken into consideration which shows that both the Bethesda & Nijgmegen technique have low specificity at higher inhibitor titre. If actual quantitation of high titre activity is required, then it is more reliable to estimate empirically plasma dilution that gives 50% inhib

Characterization of analytical errors in thromboelastography interpretation

IntroductionInterpretation of Thromboelastography (TEG) curve involves correlating patient’s clinical profile with TEG parameters and the tracing, keeping in mind the potential sources of errors, and hence requires expertise. We aimed to analyse the analytical errors in TEG interpretation due to paucity of literature in this regard. Material and methodsThe retrospective study was conducted in an apex trauma center in North India. Five months of data was reviewed by two laboratory physicians, with differences resolved by consensus. Cases with pre-analytical errors, missing data and TEG runs lasting <10 ​min were excluded. The analytical errors were classified into: preventable, potentially preventable, non-preventable, and non-preventable but care could have been improved. ResultsOut of 440 TEG tracings reviewed, 70 were excluded. An analytical error was present in 60/370 (16.2%) tracings. There were six types analytical errors, of which, tracings of severe hypocoagulable states showing k-time ​= ​0 (33.3%) was the commonest, followed by tracings with spikes at irregular intervals (30%). Of all the analytical errors, 29/60 (48.2%) were preventable and 5/60 (8.3%) were potentially preventable. ConclusionAnalytical variables that lead to errors in TEG interpretation were identified in about one-sixth of the cases and almost half of them were preventable. Awareness about the common errors amongst clinicians and laboratory physicians is critical to prevent treatment delay and safeguard patient safety.

COMPARISON OF INCIDENCE OF PRE-ANALYTICAL PHASE ERRORS IN OPD AND IPD SAMPLES IN A SUPER-SPECIALTY HOSPITAL: A RETROSPECTIVE STUDY

Objective: To evaluate and compare the incidence of errors in pre-analytical phase in OPD and IPD samples. Multitude of human involvement in preanalytical processes makes this phase error prone. Analysis of the same can help in assessing the magnitude and planning the corrective steps. Methodology: Study was conducted retrospectively for the period July 2019 to June 2020. Samples collected from OPD sample collection room and different areas of IPD were scrutinized for pre-defined errors. Number of errors in OPD and IPD were statistically compared. Results: 679 samples out of 50713 (1.3%) OPD samples in the study period had one error or the other. Similarly, 1533 samples out of 87525 (1.7%) IPD samples had errors. When compared statistically, this difference is highly significant. (p &lt; 0.00001). Conclusion: IPD samples are more prone to errors for the fact that these samples are collected by nursing staff or resident doctors in the different areas of the hospital. This staff is involved in patient care and has to look after multiple tasks, hence chances of error are more. OPD samples are collected by the same team, who are trained phlebotomists and are in constant touch with lab. Thus OPD samples have less preanalytical phase errors.

Questionnaire-based Study to Assess Knowledge of Preanalytical Phase of Laboratory Testing Among Trainee Doctors in a Tertiary Care Hospital Medical College.

Objective To determine the knowledge base of common laboratory practices related to preanalytical phase of laboratory testing among medical interns and first-year postgraduate residents in a tertiary care hospital medical college. Materials and methods Questionnaire-based survey on preanalytical phase of laboratory testing was conducted among 208 participants, who volunteered and were MBBS interns and first-year postgraduate residents in a medical college, over the period from June 2018 to December 2019. A total of 15-item, multiple-choice questions (MCQs) were included, of which four were opinion-based and not considered for analysis. Responses were further categorized based on percentages with correct response, so we could identify specific knowledge points which need training. Statistical analysis Results were analyzed using Microsoft Excel functions and a simple calculator. Results A total of 208 participants were included in the study, which consisted of an equal number of interns (104) and first-year postgraduate residents (104). The term “preanalytical error” was known to 62.5% of participants. Only 9.62% participants took formal training in phlebotomy. Topics related to questions like coagulation testing, ideal fasting duration, mixing of blood, and order of draw received less than 40% correct response which meant that it requires more training. Conclusions In this era of evidence-based medicine, central laboratory plays a pivotal role in patient management, and quality of laboratory results are of paramount importance. Over a period of time, automation technology has reduced analytical phase errors to the minimum. Most errors reported are part of the preanalytical phase, and it has been found that a majority of them are committed due to a lack of knowledge and skills. In order to improve the preanalytical phase and make it as error-free as possible, the staff (technicians, nurses, and trainee doctors) should be constantly motivated and trained.

3D-printed simulator for nasopharyngeal swab collection for COVID-19.

IntroductionTesting for COVID-19 is a cornerstone of pandemic control. If conducted inappropriately, nasopharyngeal swab collection can be painful and preanalytical sample collection errors may lead to false negative results. Our objective was to develop a realistic and easily available synthetic simulator for nasopharyngeal swab collection.Materials and methodsThe nasopharyngeal swab collection simulator was designed through different development steps: segmentation, computer-aided design (CAD), and 3D printing. The model was 3D printed using PolyJet technology, which allows multi-material printing using hard and soft materials.ResultsThe simulator splits in the parasagittal plane close to the septum to allow better visualization and understanding of nasal cavity landmarks. The model is able to simulate the softness and texture of different structural elements. The simulator allows the user to conduct realistic nasopharyngeal swab collection. A colored pad on the posterior wall of the nasopharynx provides real-time feedback to the user. The simulator also permits incorrect swab insertion, which is of obvious benefit from a training perspective. Comprehensive 3D files for printing and full instructions for manufacturing the simulator is freely available online via an open access link.Conclusion In the context of the COVID-19 pandemic, we developed a nasopharyngeal swab collection simulator which can be produced by 3D printing via an open access link, which offers complete operating instructions.

Diagnostic performance of the ClearLLab 10C B cell tube.

Pre-analytical and analytical errors can threaten the reliability of flow cytometry (FC) results. A potential solution to some of these is the use of dry, pre-mixed antibodies, such as the ClearLLab 10C system. The purpose of the present study was to compare the diagnostic performance of the ClearLLab 10C B cell tube with that of our standard laboratory practice. We compared the diagnoses made with the ClearLLab 10C B cell tube (experimental strategy) with those made with standard laboratory practice (standard strategy). Samples were selected aiming for representation of the full spectrum of B cell disorders, with an emphasis on mature B cell malignancies, as well as healthy controls. We included 116 samples (34 normal controls, 4 acute lymphoblastic leukemias, 54 mature lymphoproliferative disorders in peripheral blood and bone marrow, 3 myelomas, 6 bone marrow samples with involvement by lymphoma and 1 with elevated hematogone count, 14 lymph node samples, 1 cerebrospinal fluid, and 1 pleural effusion). There were two diagnostic errors (1.7%). The agreement between the two strategies in the percentage of CD19 cells and fluorescence intensity of CD5, CD19, CD20, CD200, and CD10 was very good. In this study, the ClearLLab 10C B cell tube performed similarly to our standard laboratory practice to diagnose and classify mature B cell malignancies.

Evaluation of quality indicators in pre-analytical phase of testing in clinical biochemistry laboratory of a tertiary care hospital in India

Preanalytical errors account for nearly 70% of the total number of laboratory errors. Hence, controlling them is a big challenge. Quality Indicators expressed as sigma metrics provide a convenient way to objectively quantify errors. Aim: To quantify performance in the preanalytical phase of the testing process in Clinical Biochemistry laboratory of a tertiary care hospital in India using quality indicators. Study period: January to September 2016. Quality Indicators (QIs) used: samples lost–not received (QI-8); samples collected in an inappropriate blood collection tube (QI-9); haemolyzed samples (QI-10); clotted samples (QI-11); samples with insufficient sample volume (QI-12); improperly labelled (QI-15); damaged in transport (QI-14). Sigma metric was calculated for the above mentioned QIs. The total number of samples received during the study period was 5,73,694 and the total number of preanalytical errors was 1,782. Among the preanalytical errors, 43.9% were samples with insufficient volume (sigma: 4.5), 33.2 % were haemolyzed samples (sigma: 4.6), 11.3% were samples collected in an inappropriate blood collection tube (sigma: 4.9), 6.7% were samples not received in the laboratory (sigma: 5.1), 4.2% were clotted samples (sigma: 5.2), 0.7% were improperly labelled (sigma: 5.6), only one sample (0.06%) was lost over 9 months period due to spill in pneumatic chute. QIs serve as a tool to monitor process performance in the laboratory. In this study, insufficient sample volume and haemolysis were the major causes of preanalytical errors. All QIs had acceptable sigma value. Regular training of phlebotomists regarding the preanalytical errors needs to be conducted to achieve six sigma performance.

Comparison of knowledge, attitude and practices in routine blood and urine collection among final year laboratory technician students, nursing students and house surgeons

Background: Laboratory services are the backbone of the modern health care sector. In spite of rapid advances in laboratory science, it is still susceptible to various manual and systemic errors. Pre-analytical phase includes specimen collection, storage, separation and transport. Errors in this phase are majorly due to human mistakes and the majority of these errors are preventable. Laboratory technicians and nursing staff from in-patient care are most commonly and directly involved in sample collection. There are many studies done using them as study population. However, the role of physician in sample collection techniques is often ignored. Ideally a doctor should also be aware of the sample collection techniques and anticipate possible lab errors due to pre-analytical error.Methods: A quantitative cross sectional comparative study with 60 participants comprising 20 each from house surgeons, final year lab technicians and nursing students in a tertiary care hospital. A pre-tested, self-administered and validated questionnaire was used to assess knowledge, attitude and practices in routine blood and urine collection with total 27 questions. Statistical analysis: ANOVA, student’s t- test and qualitative analysis was done.Results: In the area of sample collection techniques house surgeons lacked the required knowledge compared to nursing and lab technician students and it was also reflected in sample collection practices.Conclusions: Based on the study, we strongly opine to train MBBS students in routine blood collection techniques and sensitize them to pre analytical errors which will help in reducing lab reporting errors.

Swabbing Thoroughly People for COVID-19 Positivity. Insights on the Main Bio-analytical and Microbiology Bias and Concerns.

Thorough swabbing is becoming an increasing approach to fight COVID-19 transmission, particularly among asymptomatic subjects, who are thought to represent the majority of potentially-contacting people. Particularly in the current management of COVID-19 emergency, the 3T approach, i.e., testing, tracing and treating, is felt as particularly crucial to fight COVID-19 pandemic. Aside from the time-consuming, cost expensive and the many burdensome issues associated with a thorough swabbing, adopting easy-to-make criteria such as “drive-thru-swab” may exacerbate the burden of critical biases and pre-analytical errors, which may impair the analytical reliability of these tests. This manuscript addresses some major points about.

Validation of phlebotomy performance metrics developed as part of a proficiency-based progression initiative to mitigate wrong blood in tube

AimsThe purpose of this study was to (1) characterise the procedure of phlebotomy, deconstruct it into its constituent parts and develop a performance metric for the purpose of training healthcare...

Study of pre analytical errors in clinical biochemistry laboratory in rural area of Punjab

Introduction: The pre analytical phase is an important component of laboratory medicine. It includes the time from the order of test by the clinician until the sample is ready for analysis – it can account up to 70% of errors during the total diagnostic process. The major 5 key components for the establishment of quality and reliability in the laboratory diagnostics include (a) Quality laboratory process (QLPs), (b) Quality control(QC), (c) Quality Assurance/Assessment (QA), (d) Quality Improvement (QI) and (e) Quality policy(QP). Objectives: 1. To stratify the pre-analytical errors documented during pre analytical testing process; 2. To formulate the possible corrective measures to be taken to minimise such errors. Materials and Methods: A prospective study was done for a period of 6 months from 1st august 2019 to 31st Jan 2020 in Clinical Biochemistry laboratory of PGIMER satellite centre, Sangrur. All types of pre-analytical errors were Recorded. In our study, total blood specimens received during Aug 2019 to Jan 2020 were 2980. Out of which 284 specimens were sorted with pre analytical errors. Results: These 284 specimens were categorised as follows: Improper request form (n= 24); improper labelling (n=39); improper tube collection (n=51); insufficient sample n=48); in-vitro haemolysis (n=66), sample not received(SNR) (n=56). Conclusion: Pre-analytical errors are not inevitable and can be avoided with a diligent application of proper quality control, proper education of phlebotomist about the errors and effective collection systems to improve the total quality management of laboratory so as to ensure total quality patient care.

Haemovigilance: Role and importance of blood request forms in routine hospital practice.

Objectives: To assess the extent of Blood Request Forms (BRFs) usage in routine blood banking, at a major Hospital in Lahore. Study Design: Cross-sectional Descriptive study. Setting: Shaikh Zayed Medical Complex Blood Bank, Lahore. Period: 6 months (Sept 2016 to March 2017). Material &amp; Methods: A total of 1052 BRFs dispatched from in-patient of Shaikh Zayed Medical Complex, Lahore were selected. Patient’s MR number, date, demographic information, diagnosis, ward, history of transfusions, type of blood transfused, phlebotomist’s name etc., were analyzed. They were assessed and the results were produced in tabulated form as well as in graph. Results: Among the 1052 BRFs, “MR number” was filled in 99.4% (n=1046) forms, while 0.6% (n=6) were not filled. The column of “Date” was filled in 97% (n=1020) forms, while it was left blank in 3% (n=32) forms. Similarly, the column of “Age” was filled in 97.7% (n=1028) forms, whereas it was left empty in 2.3% (n=24) forms. Demographic information like “Patient’s Name” and “Gender” were filled in 100% forms. “Ward” was filled in 97.1% (n=1022) forms, while 2.9% (n=30) were unfilled. As far as “H/O previous transfusion(s)” column is concerned, 40.9% (n=430) forms were filled and 59.1% (n=622) were left unfilled. “H/O previous transfusion reaction(s)” column had almost the similar number with 37.6% (n=396) filled and 62.4% (n=656) left empty. The column of “Diagnosis” was filled in 22.4% (n=236) and was found unfilled in 77.6% (n=816). Moreover, the column of “Which type of component transfused” was filled in 96% (n=1010), while 4% (n=42) were unfilled. The column of “Amount of blood needed” was filled in 96.4% (n=1014) forms, while 3.6% (n=38) forms were unfilled. “When is the blood needed” column had only 29.3% (n=308) filled forms, whereas 70.7% (n=744) forms did not mention when the blood was needed. One of the most important columns is “Patient’s blood group”, which was filled in only 53.4% (n=562) forms, while 46.6% (n=490) forms were left empty. The column of “Name of phlebotomist” was filled in only 13.9% (n=146), while 86.1% (n=906) of the forms were found unfilled in this column. In total, our study revealed that among 1052 BRFs, only 6.8% (n=72) werecompletely filled, while 93.2% (n=980) were incompletely filled. Conclusion: Lack of awareness in BRF filling should be properly addressed to enhance efficiency and to reduce pre-analytical errors in healthcare setups. It is of utmost need that the clinicians and nurses should be made aware that BRFs play a pivotal role in smooth and error-free functioning of the healthcare setups.

Diurnal variations in canine hematological parameters after commercial feed feeding

Complete blood count (CBC) is the evaluation of blood cells, which provides resourceful information. Considering that inadequate fasting time is the most common pre-analytical error in laboratory diagnosis and is associated with lipemia in blood samples, which has not yet been adequately investigated in dogs, this study aimed to assess diurnal postprandial changes in the CBC of healthy dogs fed with industrialized feed. Eighteen clinically healthy dogs aged 2-6 years and weighing over 6 kg were enrolled in the study. All dogs received “Premium” industrialized feed every 12 hours. Blood was collected after a 12-hour fasting period at 6:00 am (baseline), followed by feeding and new blood samples collected hourly for the next 11 consecutive hours. Red blood cell (RBC) counts, red cell distribution width (RDW), white blood cell (WBC) counts, platelets, mean platelet volume (MPV) and hemoglobin were obtained using an automated veterinary cell counter. Hematocrit (HTC) was determined by Strumia's microcapillary method, differential leukocyte count was performed on hematological dye-stained blood smears and total plasma protein (TPP) was determined using refractometry. Variables were tested for normality and differences were considered significant when p &lt; 0.05. A statistically significant decrease was observed in the erythrogram from 2 h for RBC and hemoglobin, from 3 h for HTC and from 4 h for MCV, persisting until the end of 11 hours. There was no change in MCHC and RDW. Regarding the leukogram, a significant increase in WBC was observed from 2 to 7 h, due to the increase in segmented neutrophils 2 to 8 h following feeding. Lymphocyte counts decreased significantly at 2 and 6 h following feeding. No alteration was observed in eosinophil, basophil, monocyte and platelet counts, as well as in MPV. From 5 h to 11 h after feeding, a significant decrease was seen on TPP. However, changes in hematological parameters did not exceed reference ranges for the canine species. Feeding dogs with industrialized feed caused statistically significant changes in erythrogram, leukogram and plasma protein content. While these changes do not seem to exceed reference values for the species in healthy animals, caution is warranted for sick animals with borderline values, in which these changes might be clinically important depending on the pathologic process.