Analytical Phase Research Articles

Operational Feasibility of Point-of-Care Testing for Sickle Cell Disease in Resource-Limited Settings of Tribal Sub-Plan Region of India

Background: Sickle cell disease (SCD) individuals in India are mostly identified when they become symptomatic. To provide a timely diagnosis of SCD to participants, healthcare workers should be competent in using the point-of-care test (POCT). In this study, we aimed to evaluate the competence of healthcare workers to screen infants and adult populations through POCT. Methodology: This study was conducted in pilot mode over 8 months from April to November 2023. A random sampling method was used to select ten auxiliary nursing midwives (ANMs), ten lab technicians (LTs), and five medical officers (MOs). Each selected ANM and LT was supposed to conduct ten tests and MOs to conduct five tests. The POCT used to diagnose sickle cell disease was HemoTypeSC. Results: Among the healthcare workers who participated in the study, 67% belonged to the scheduled tribes. When the ANM and LT competencies were compared for the pre-analytical phase (phase I), ANMs were more competent than the LTs. ANMs were more adept at handling people, whereas the LTs were more competent in conducting the test procedures. When the comparison was made for the analytical phase (phase II), both the ANMs and LTs were found to be equally competent. ANMs followed the standard operating procedure (SOP) more precisely than MOs and LTs. In the post-analytical phase, LTs were found to be more competent than ANMs. The approach used in this study with sub-centers and primary health centers (PHCs) appears to have encouraged the feasibility of the screening program. Conclusions: The results of this study conclude that the healthcare workers in the region are competent to perform the POCT for the diagnosis of sickle cell disease. The POCT may be introduced in the program for the diagnosis of SCD.

Trust: an essential component in nursing crisis leadership; a hybrid concept analysis

BackgroundGiven the increasing trend of disasters, terrorist attacks, pandemics and other crises, crisis leadership is crucial for nurses who lead others and for those working in such situations. There is a need to define and explore the concept of trust as a component of crisis leadership in nursing.This concept analysis aimed to explore the concept of trust in crisis leadership from a nursing perspective.MethodsA hybrid concept analysis was conducted. The method consisted of three phases: (I) a theoretical phase relying on a structured literature search, including 11 scientific publications; (II) a field-work phase, in which qualitative thematic analysis of interviews with 30 nurses who had been deployed and/or had led others during crises, was conducted and (III) a final analytic phase, where the results from these data collections were merged.ResultsThe analysis suggested that the fundamentals of trust included a perceived intention to do good, the capabilities of both the leader and the team and the perceived predictability of the leader’s behaviour. Trust was found to be built on a perceived forward-looking direction, self-trust and the personal attributes of the leader, such as ethical conduct, the ability to predict the development of crises and an intention to take responsibility and be honest. The social attributes of the relationship between the leader and the team included the intention not to leave anyone behind, loyalty and fostering a sense of belonging among team members. The organisational attributes included a clear organisational structure and clarity of mandate.ConclusionsTrust is an essential component of crisis leadership that depends on a leader’s perceived intention to do good, predictability of the leader’s behaviour and the capabilities of both the leader and the team. The development of trust relies on the personal attributes of the leader, the social relationship between the leader and the team and organisational attributes. Nurses appointed to lead others during a crisis need to understand the fundamentals of trust as part of leadership in highly demanding situations. Thus, it can be argued that being a leader in a crisis situation requires distinct personal and professional attributes and skills compared to those used to meet routine demands.

Working Toward Advanced Architectural Education: Developing an AI-Based Model to Improve Emotional Intelligence in Education

This study explored the integration of emotional intelligence (EI) with artificial intelligence (AI) to address emerging challenges in architectural education. An AI-supported teaching model was developed, utilizing AI tools to assess students’ emotional responses and enabling educators to adapt teaching strategies based on emotional data. This study employed a three-phase methodology: theoretical, analytical, and experimental phases. The theoretical phase involved a comprehensive literature review focusing on the role of EI in architectural education. In the analytical phase, a survey was conducted to evaluate students’ ability to overcome learning challenges using a case study from an Egyptian university. The experimental phase implemented an EI-driven teaching approach with a pilot group of students, incorporating instructor feedback and ChatGPT-4O for assessments in order to minimize potential bias. The results demonstrate that integrating EI into education significantly enhances students’ performance compared to traditional teaching methods. Furthermore, the findings contribute to the development of an AI-based model that provides personalized feedback and fosters a dynamic learning environment, aiming to achieve higher academic and behavioral standards among architecture students. This research offers theoretical and practical insights into advancing the integration of AI and EI in architectural education.

Patient's sexual dignity discomfort in healthcare setting: A concept development.

Background: Body touch and close physical proximity are inevitable in some healthcare procedures and can evoke feelings of shame, humiliation, and anger in patients. Given the increasing recognition of human dignity, exploring the occurrence of these negative emotional experiences and identifying mechanisms for their prevention are crucial.Aim: To develop and define the concept of "patient's sexual dignity discomfort." Design: A hybrid model of concept development was utilized.Methods: In the theoretical phase, a scoping review was conducted to establish a working definition of patient's sexual dignity discomfort. This definition was refined and validated using qualitative data collected during the fieldwork phase. In the analytical phase, a final conceptual model of patient's sexual dignity discomfort was proposed by integrating findings from both the theoretical and fieldwork phases.Ethical considerations: All participants completed an informed consent process, and interviews were conducted via Zoom or phone by a certified psychiatric nurse to ensure confidentiality, anonymity, and comfort.Results: Four themes describing attributes of patient's sexual dignity discomfort were explored: experiencing shame and embarrassment, vulnerability-induced loss of control, dehumanization and objectification, and uncertain sexual autonomy. Patient's sexual dignity discomfort occurs when patients perceive care procedures as sexually inappropriate or as involving unnecessary sexual activity, particularly when healthcare providers display unprofessional attitudes or when patients lack consent or are not mentally prepared for the procedure because of insufficient information. This discomfort leads patients to refuse or avoid healthcare treatments and prioritize finding better healthcare services over their health. It can also prompt providers to avoid patients, resulting in a compromised quality of care and poor health outcomes.Conclusions: Patient's sexual dignity discomfort poses a significant threat to the quality of patient care and preservation of dignity. Nurses can trigger this intentionally or unintentionally, highlighting the need for comprehensive education and training to prevent it.

Economic evaluation: Impact on costs, time, and productivity of the incorporation of integrative digital pathology (IDP) in the anatomopathological analysis of breast cancer in a national reference public provider in Chile.

The incidence of breast cancer has risen in Chile, along with the complexity of diagnosis. For accurate diagnosis, it is necessary to complement the morphology assessed with hematoxylin and eosin with additional techniques to evaluate specific tumor markers. Evaluating the impact on costs, time, and productivity of automated techniques integrated with digital pathology solutions is crucial. To estimate the impact on costs, time, and productivity of incorporating the automation of the HER2 in situ hybridization technique combined with integrative digital pathology (IDP) in breast cancer diagnosis in a Chilean public provider versus a manual technique. This economic evaluation adopted a health economics multi-method approach. A decision model was developed to represent the current manual fluorescence in situ hybridization (FISH) scenario versus an automated dual in situ hybridization (DISH) plus IDP in breast cancer diagnosis. Business process management (BPM) methodology was applied for capturing working time and latencies, in combination with a time-driven activity-based costing (TDABC) methodology for estimating direct, total, and average cost (2023 USD) for both scenarios for the following vectors: Human resources, supplies, and equipment, sorted by pre-analytical, analytical, and post-analytical phases. Indirect costs (2023 USD) were also retrieved. Both BPM and TDABC served to estimate labor productivity. In the baseline scenario based on manual FISH, the turnaround time (TAT) was estimated at 1259 min, at an average total cost of $265.67, considering direct and indirect costs for all phases. An average of 20.5 FISH reports were submitted per pathologist monthly during the baseline. The automated DISH plus IDP scenario consumed 203 min per biopsy, at an average total cost of $231.08, considering direct and indirect costs for all phases; it also showed an average of 22.8 submitted reports per pathologist monthly. This represents a decrease of 13.02% in average total costs, an 83.86% decrease in TAT, and an average labor productivity increase of 11.29%. The incorporation of automated DISH plus IDP in the pathology department of this public provider has resulted in reductions in the time required to perform the in situ hybridization technique, a decrease in total costs, and increased productivity. Particular attention should be given to adopting new technologies to accelerate processing times and workflow.

Therapeutic Drug Monitoring of Low Methotrexate Doses for Drug Exposure and Adherence Assessment-Pre-Analytical Variables, Bioanalytical Issues, and Current Clinical Applications.

Methotrexate (MTX) is an antifolic agent used in the first line of anti-inflammatory disease treatment and some oncologic issues. The metabolism of MTX is rapid, and the MTX concentration in the blood is not significant 24 h after administration. Unlike this, methotrexate polyglutamates (MTXPGs) can be informative biomarkers of drug exposure. It is widely concluded that MTXPG retention in red blood cells (RBCs) is related to appropriate efficacy, drug exposure, and toxicity during treatment. Therefore, the mentioned biomarker may be appropriately used for the PK/PD monitoring of low-dose MTX (LDMTX) treatment. The presented review study aimed to review published studies about MTX determination in clinical practice, including pre-analytical variability, bioanalytical considerations, and clinical applications of the methods for pharmacotherapy supporting target populations. In total, 14 papers from the field of bioanalytics have been included in the main review. For each phase of an analytical process, the best practises and main findings were defined as guidelines for proper analytical method optimisation, validation, and standard operation procedure implementation in clinical practice. The presented study is the first comprehensive review of MTX and its methods of metabolite determination to account for pre-analytical, analytical, and post-analytical phases concerning the TDM process.

Assessing the psychometric properties of the Biphasic Sleep Scale (BiSS): A novel 16‐item self‐report measure

SummaryBiphasic sleep, characterized by nighttime sleep plus daytime napping, has demonstrated some cognitive, health and performance impacts when compared with consolidated monophasic sleep. This motivated the development and validation of the Biphasic Sleep Scale, reported in this paper. Scale development involved a literature review, expert input and individual interviews. The 16‐item Biphasic Sleep Scale was then administered to an international online sample (n = 6965) alongside well‐established validated sleep scales. To ensure a robust evaluation of the Biphasic Sleep Scale, the sample was divided into two parts: with 15% (n = 1000) of the participants allocated to the exploratory analytic phase; and the remaining 85% (n = 5965) reserved for confirmatory analyses. Psychometric evaluation included both exploratory and confirmatory factor analysis, reliability analysis, correlations, network analysis, and item response theory. Exploratory factor analysis indicated a three‐factor structure assessing daytime napping as to likelihood, consequences and effect on nighttime sleep. Confirmatory factor analysis largely confirmed this model with no sex invariance. The three‐factor structure showed adequate fit. The Biphasic Sleep Scale demonstrated good internal consistency (α = 0.88, Ω = 0.89). Network analysis revealed varying centrality and connectivity of items. Item response theory found items covering a range of biphasic sleep levels. Significant positive correlations with sleep criteria provided evidence for convergent validity. Further testing is warranted to confirm the factor structure, refine model parsimony, and establish clinical utility. With additional validation, it is hoped that the Biphasic Sleep Scale will become a widely utilized tool.

Six sigma matrix and Quality Goal Index ratio in improving the quality of analytical phase in a clinical laboratory

Objectives: The objective of the study is to assess the performance of individual biochemical parameters on a sigma scale and also to do root cause analysis and take corrective actions for the parameters with poor performance to improve the quality of our clinical laboratory. Materials and Methods: This is a retrospective and prospective study done in the central laboratory of a tertiary care hospital from January 2023 to September 2023. The daily internal quality control (IQC) data and monthly external quality assessment service data for 10 biochemical parameters from January 2022 to December 2022 were collected retrospectively and from April 2023 to September 2023 prospectively. Parameters with poor sigma performance and root cause analysis were done, and corrective actions were taken. Data were collected prospectively for the next 4 months (April 2023–September 2023), and sigma was calculated. Statistical analysis: Data were input into Microsoft Excel and analyzed using Stata version 14. Results: Out of the ten, 7 parameters at level 1 and five at level 2 IQC showed sigma values between 3 and 6, whereas 2 parameters showed poor performance at both the quality control (QC) levels with sigma metrics values <3. With quality goal index and root cause analysis, the source of error was detected and corrected. Conclusions: Sigma metric analysis is a tool to determine the performance of QC design. This gives the laboratory a select the right QC strategy. This will help to save time, effort, unnecessary runs, calibration, and reagent waste, which affect the outcome of turnaround time.

Solar Energy Applications in Protected Agriculture: A Technical and Bibliometric Review of Greenhouse Systems and Solar Technologies

This study addresses solar energy applications in protected agriculture, focusing on greenhouses and related technologies. A bibliometric and technical analysis is developed, covering research published between 1976 and 2024, to identify the main trends and challenges in the use of solar energy in controlled environments. The methodology was based on the PRISMA approach, using the Scopus database to retrieve relevant documents. From an initial total of 221 documents, 216 were selected after a filtering and debugging process, ensuring the relevance of the final set. In the analytical phase, the results showed a moderate growth of 3.68% in the annual publication rate, highlighting the impact of research on solar energy’s application to air conditioning and energy efficiency in greenhouses. Most of the studies reviewed feature hybrid systems that combine solar energy with other resources, and we highlight both advances in climate control through artificial intelligence and the implementation of photovoltaic and thermal technologies to improve the energy efficiency of agricultural systems. The results also underline the importance of tomato cultivation in the selected studies, reflecting its global economic impact. The conclusions highlight the need for the further integration of energy storage and desalination technologies, especially in arid regions with high solar irradiation, to ensure the sustainability of greenhouses. It is proposed that future research should address the wider implementation of hybrid systems and advanced climate control technologies, optimizing both the use of energy resources and the performance of crops under cover. In addition, it is recommended that international collaboration be strengthened to address technical and climatic challenges in protected agriculture and to expand the adoption of innovative solutions in different geographical contexts.

Uncovering disease-related multicellular pathway modules on large-scale single-cell transcriptomes with scPAFA.

Pathway analysis is a crucial analytical phase in disease research on single-cell RNA sequencing (scRNA-seq) data, offering biological interpretations based on prior knowledge. However, currently available tools for generating cell-level pathway activity scores (PAS) exhibit computational inefficacy in large-scale scRNA-seq datasets. Additionally, disease-related pathways are often identified through cross-condition comparisons within specific cell types, overlooking potential patterns that involve multiple cell types. Here, we present single-cell pathway activity factor analysis (scPAFA), a Python library designed for large-scale single-cell datasets allowing rapid PAS computation and uncovering biologically interpretable disease-related multicellular pathway modules, which are low-dimensional representations of disease-related PAS alterations in multiple cell types. Application on colorectal cancer (CRC) datasets and large-scale lupus atlas over 1.2 million cells demonstrated that scPAFA can achieve over 40-fold reductions in the runtime of PAS computation and further identified reliable and interpretable multicellular pathway modules that capture the heterogeneity of CRC and transcriptional abnormalities in lupus patients, respectively. Overall, scPAFA presents a valuable addition to existing research tools in disease research, with the potential to reveal complex disease mechanisms and support biomarker discovery at the pathway level.

Haematological and Biochemical Reference Intervals Towards a Proactive Health Monitoring Approach in Norwegian Atlantic Salmon Farming.

Haematological and plasma parameters are used in veterinary medicine as a diagnostic tool, allowing for the early detection of potential health and welfare issues. For the implementation of monitoring strategies, reference intervals (RIs) are needed to know when deviations in those parameters become clinically relevant. Here, haematological and plasma biochemical RIs of Norwegian Atlantic salmon (Salmo salar Linnaeus) are presented for 29 biomarkers. Two subgroups were defined from the reference population based on water type, referred to as pre-adult (freshwater, 166.8 ± 118.4 g, N = 979) and adult (seawater, 2655 ± 2883 g, N = 4941), collected at 93 fish farms along the Norwegian coast. While the influence of various pre-analytical variables on RIs is well documented, aquaculture practitioners cannot always control those variables in the field. Here, RIs were calculated from blood samples collected based on local pre-analytical practices and then further processed under standardised conditions (analytical phase). RIs are therefore considered highly relevant for the application in the field. Finally, when taking blood samples in the field, it is advised to centrifuge whole blood as soon as possible, while plasma parameters investigated were stable for 168 h at 4°C or 72 h at room temperature.

Analytical leapfrogging? A conference presentation about ‘caring on the move’

AbstractThis paper discusses the idea of ‘analytical leapfrogging’ by considering how and why we can sometimes be tempted to jump over or ignore a more formal analytical phase in our research. It does this by discussing a vignette presented in a conference session relating to preliminary research on everyday mobilities, care and children with special educational needs and disabilities (SEND). The paper offers some critical reflections on the implications of refracting early project ideas through our own lived experiences and the significance of our analytical histories in shaping the work that we do.

PCR GeneScan Analysis of Rearranged Immunoglobulin or T-Cell Receptor Genes for Clonality Diagnostics in Suspect Lymphoproliferations.

Assessment of the presence of clonal lymphoproliferations via polymerase chain reaction (PCR)-based analysis of rearranged immunoglobulin (IG) or T-cell receptor (TR) genes is a valuable method in the diagnosis of suspect lymphoproliferative disorders. Additionally, this methodology can be used for evaluating dissemination of lymphoma cells and for studying the clonal relationship between multiple (different locations) and consecutive (over time) lymphomas. Here we describe an integrated approach to assess clonality via analysis of Ig heavy chain (IGH), Ig kappa (IGK), TCR beta (TRB), and TCR gamma (TRG) gene rearrangements, based on the standardized multiplex PCRs as originally developed by the European BIOMED-2 consortium (currently named EuroClonality). The described protocol covers the pre-analytical phase of DNA isolation (from formalin-fixed paraffin-embedded and fresh tissues, body fluids, peripheral blood, and bone marrow), the analytical phase of PCR GeneScan analysis, and the post-analytical interpretation of the obtained profiles, following established guidelines.

Diagnostic role of urine human epididymis protein 4 in ovarian cancer.

Ovarian cancer is the 8th most common malignancy in women and the deadliest gynecological cancer. Due to the non-specific symptoms and the lack of effective diagnostic methods, late diagnosis remains the main barrier for improving the poor prognosis. Human epididymis protein 4 (HE4) is a protein overexpressed in ovarian cancer, but not in healthy individuals or benign conditions. The aim of this review article is to evaluate the laboratory aspect and potential clinical application of urine HE4. The methodology is presented, together with discussion on preanalytical, analytical and postanalytical phase of HE4 detection using urine. Moreover, we present the diagnostic role of urine HE4 in differential diagnosis, chemotherapy response, detection of recurrence and detection of low-malignant potential tumors. It has been found that urine HE4 presents as a promising, non-invasive tumor marker for detection and monitoring of ovarian cancer. However, standardization of the HE4 detection process is needed prior to implementation in clinical diagnostics.

Connection between weak measurement in quantum physics and analytic phase retrieval in classical wave optics

Connection between weak measurement in quantum physics and analytic phase retrieval in classical wave optics

Adrenal insufficiency - causes and laboratory diagnosis.

Adrenal insufficiency (AI) manifests as a clinical syndrome arising from either the direct impairment of adrenal glands, leading to primary AI characterized by deficiencies in glucocorticoids and mineralocorticoids, or adrenal cortex atrophy due to diminished adrenocorticotropic hormone (ACTH) stimulation, a consequence of hypothalamic and/or pituitary damage, resulting in secondary AI. The diagnosis of AI is based on clinical assessment and biochemical tests, including basal hormone level measurements and stimulation tests. In evaluating the results of laboratory tests, it is necessary to consider factors that may influence both pre-analytical and analytical phases, as well as the chosen methodology. Correct diagnosis of adrenal insufficiency and timely initiation of suitable replacement therapy are paramount. These steps are crucial not only for managing the condition but also to avert potentially life-threatening adrenal crises.

A-188 Modal Failure and Effects Analysis, FMEA methodology, as a strategy to increase patient safety

Abstract Background Patient safety during the clinical care process is considered a priority in healthcare. Failure Mode and Effects Analysis (FMEA) is a proactive and systematic method of process evaluation and is used to identifying where and how each phase of the analytical process could fail allowing the detection of the causes and the effects they produce on the quality of the results that are issued. A regular use of this tool makes possible to identify the most critical steps, propose improvement strategies and evaluate their impact. The aim of the study is to evaluate applicability of the FMEA tool to identify errors in the pre analytical, analytical, and post analytical phase of a clinical laboratory as well as the main causes and effects, to reduce them by proposing improvement strategies Methods For each phase into which the laboratory activity is divided, the frequency and type of errors that are made and their final consequences on the patient are evaluated. A risk index (NPR=OxDxS) is calculated for each error considering the frequency with which it occurs (O), the ease with which it is detected (D) and the severity of the consequences on the patient (S). Values goes from 1 (rarely) to 10 (often). Improvement actions are proposed for all errors with a risk index greater than 100 and this index is re-evaluated after the implementation of that improvement measures. This same analysis is performed for three times over the last 10 years (in 2014, 2019 and 2023). Results In FMEA analysis carried out in 2014, a total of 40 errors were identified in the pre-analytical phase (63.5% of the total), 12 in the analytical phase and 11 in the post-analytical phase. 50% of the total errors detected required improvement strategies because they had an NPR≥100 value. In the 2023 evaluation, a total of 27 errors were identified in the pre-analytical phase, 10 in the analytical phase, and 5 in the post-analytical phase but only 6 required improvement strategies, which represents an 80% reduction in the most critical errors for patient safety. However, the pre-analytical phase continues to be the most critical, as it continues to account for 64% of the total errors identified, including the lack of identification of the patient or sample and the inadequate prior preparation of the patient. In analytical and post-analytical phases, the NPR values obtained in 2023 decrease significantly over analysis carried out in 2014 and its not needed to apply improvement strategies. Automation and the IT tools significantly reduce the number of errors with high NPR values, but it is undoubtedly the involvement of service professionals that makes the difference over the years. Conclusions The use of the FMEA methodological tool allows the design of appropriate indicators to detect and reduce errors in the clinical laboratory. Its application as part of a good quality control allows a continuous improvement in the laboratory process and consequently a guarantee of quality for the patient

A-209 Preanalytical Phase Errors Constitute the Vast Majority of Errors in Clinical Laboratory Testing

Abstract Background Laboratory errors can occur during the preanalytical, analytic, or post-analytic phase of testing and may pose a considerable threat to patient safety. Studies have estimated that pre-analytical error encapsulates ∼45-68% of laboratory errors and occurs in up to 1.52% of specimens. However, limitations of previously published studies include the use of manual error detection, reliance on manual transcription, small study sizes, and exclusion of common errors. Herein, we aim to identify the types and frequency of errors occurring in each phase of clinical laboratory testing using a large retrospective dataset across a broad range of errors detected in clinical laboratories. Methods This study was performed in the Barnes-Jewish Hospital core laboratory which provides testing for a 1,400-bed tertiary care hospital and included all tests performed for clinical chemistry, special chemistry, toxicology, automated hematology, blood gas testing, coagulation, non-infectious serology, infectious disease serology, urinalysis, and send out testing between January 2022 and May 2023. Errors were compiled from two separate sources. The first source of errors was captured from the laboratory information system (LIS, Cerner). These errors were flagged manually by laboratory staff in real time. The second source of error was a daily report manually curated by a trained medial laboratory scientist as part of routine, laboratory operating procedures and standard workflow. Results There were ∼40,000,000 individual results from ∼11,000,000 specimens during the study period and 87,317 errors observed (∼0.8% of specimens). Of these errors, specimens that were hemolyzed sufficiently to impact result but still reportable were the majority (41,047, 47.2%). When excluding minimal hemolysis, there were 46,270 errors documented. Among these, 44,847 (97.0%) were in the preanalytical phase, 451 (1.0%) were in the analytical phase, and 972 (2.0%) occurred in the postanalytical phase. Subcategorization of preanalytical errors revealed that most of the errors were related to hemolyzed samples requiring results to be suppressed (n=19,701), quantity not sufficient samples (n=8,068), clotted specimens (n=5,840), collection errors (e.g., wrong tube type, n=5,780), not on ice (n=1,369) and IV fluid contamination (n=1,122). In the analytical phase, the causes of error were interfering substances (n=279), QC out of range (n=65), instrument problems (n=58) and reagent issues (n=49). Among the postanalytical errors, 581 were comment errors, 216 were results entry errors, 131 were comments errors with potential impact on patient care, and 44 were dilution errors. Conclusions This study demonstrates that the vast majority of lab errors (∼97.0%) occurring during the preanalytical phase. The high incidence of preanalytical errors, especially errors related to sample integrity implies a need for enhanced tools and training to minimizing errors from specimen collections, maintenance of sample stability, transportation, and processing.

A-193 Optimizing Emergency Laboratory Operations Through Six-Sigma Strategies for Enhanced Efficiency and Effectiveness: A Pilot Study

Abstract Background Quality assurance is vital in laboratory diagnostics to ensure patient safety and accurate results. Laboratories employ internal and external quality control measures, particularly focusing on the analytical phase. Sigma metrics, representing process variation, play a crucial role in assessing accuracy, with Six Sigma setting high standards for operational excellence. This study aims to enhance laboratory testing procedures by analyzing the analytical phase. In 2022, the Emergency laboratory at KFAFH, Jeddah, achieved optimal sigma performance, marking a significant improvement in analytical testing. http://www.westgard.com/sigma-vp-kfafh.htm. In 2023, The study also demonstrated a 30% productivity increase, driven by sustained efforts and Sigma metrics implementation, leading to cost reductions and improved quality. Real-time patient moving averages enhance quality assurance, extending coverage to the total testing process. The primary objectives include redesigning IQC procedures and optimizing resource utilization. This will be accomplished by reducing the frequency of controls, minimizing unnecessary reruns, optimizing resource allocation, and managing total costs, all while ensuring compliance and averting violations. Methods A retrospective-prospective study was conducted at the Emergency Laboratory of King Fahad Armed Forces Hospital in Jeddah, Saudi Arabia, from May 2021 to October 2023. The study assessed 841,558 tests for 131,785 emergency patients. Forty-seven analytes were evaluated for Internal Quality Control and External Quality Control (CAP), with monthly data collection. Chemistry and Hematology parameters were analyzed using Unity Real-Time software on Alinity-ci and Alinity-hq analyzers. Data was collected in three stages: baseline, pre-Sigma verification, post-Sigma implementation, and a sustainability phase. The methodology involved DMAIC model tools like flowcharts, cause & effect analysis, and sigma metric scales. Six Sigma process tools, including DPM and process capability analysis, were used. Interventions included Six Sigma metrics for QC performance, DPM for TAT process improvement, and patient moving average Real-time for proactive risk management in reducing analytical testing variation. Results Excellent performance (> 6 sigma) was achieved for 70% of chemistry test parameters for three control levels.: This indicates a high level of process capability and reliability in laboratory operations, ensuring accuracy and consistency in test results. The study successfully reduced process variation in Emergency Room (ER) laboratory Turnaround times (TATs), leading to an increase in process capability as measured on the Sigma scale, which improved from 1.35 to 3.1, indicating a more robust and efficient laboratory operation. Reducing the cost and efficiency of internal failure controls by 29% and at the same time saving in labor cost/workload marked a decrease in QC frequency from 7.0% to 0.18%, reaching the target goal of TATs and satisfaction. Conclusions The adoption of Six Sigma methodologies resulted in a notable decrease in QC runs, signaling cost savings. These high-quality methods streamline laboratory operations, improve cost-effectiveness for the healthcare system, and ultimately benefit patients and clinicians. Six Sigma methodologies play a crucial role in selecting appropriate QC designs for each parameter, ensuring efficient control while maximizing cost-effectiveness. Emphasizing the importance of suitable QC strategies and continuous technologist training is vital for mitigating analytical errors and enhancing turnaround time through comprehensive automation of the analytical phase.

B-310 Freezing and thawing serum without mixing prior to analysis causes false low Thyroglobulin results

Abstract Background Thyroglobulin (Tg), a glycoprotein that is synthesized in follicular cells of the thyroid gland, is the precursor of Thyroxin (T4) and Triiodothyronine (T3). Tg is a biomarker used for many clinical conditions, including monitoring for recurrence in patients with differentiated thyroid carcinoma. Typically, Tg levels drop to very low or undetectable levels after surgical excision and/or radioiodine ablation of the thyroid, with post-operative levels greater than 1-2 ng/ml indicating potential disease recurrence. Discordant Tg results in a patient sample were identified during a quality check of Tg results. This study investigates the root of cause of the discrepant Tg results. Given that: 1) Tg analyses were performed twice a week at our laboratory due to low daily test volume and patients’ samples received on an unanalytical day were stored at -20°C until analysis; 2) Tg analyses were performed by various medical technologists; 3) sample mixation prior to analysis was not routine practice for our automated laboratory, we hypothesized that the discrepancy was due to inconsistent sample handling, e.g., mixation vs unmixation prior to analysis. Methods Analysis of the daily QC and PT results in the period of the incident occurence ruled out causes in analytical phase. We split 52 de-identified patient serum samples into two equal aliquots and subsequently stored both aliquots at -20°C for 48 hours. Both aliquots of each sample were thawed at room temperature for 1 hour. One of the aliquots was analyzed for Tg without mixing, and the other was analyzed after mixing using a Vortexer for 4 seconds at 250 xg. To investigate if Tg concentrations form a gradient from the top to the bottom of a red-top vacutainer tube, five patient samples with Tg at 2.59, 2.79, 2.92, 52.37 and 144.12 ng/mL were thawed without mixing following storage at -20°C for 48 hours. Five layer (600 μl/layer) aliquots were carefully and sequentially taken from top to bottom for each specimen, and the Tg concentration in the aliquot of each layer was determined using the Beckman Coulter Access-2 Immunoassay. Results Of the 52 patients samples, 14 Tg results were excluded from statistical analysis due to exceeding the assay dynamic range (2 above and 12 below the upper and low limits, respectively). Analysis of the remaining 38 patient samples showed the mean of Tg concentrations was 22.8% (SD 18%) higher in mixed samples than the un-mixed samples. Regression analysis showed an R2 = 0.9976 (Mixed Tg = 1.1523 x Un-mixed + 0.4174, range 0.1 - 275.7 ng/mL, intercept 95%CI -0.721 to 1.556, slop 95%CI 1.1331 to 1.1715, p-value <0.001). Results of Tg gradient analysis showed significant higher Tg values in the 2nd, 3rd, 4th and 5th than the 1st layer by 26% (SD 11%), 63% (26%), 112% (57%), and 160% (76%), respectively. Conclusions False Tg values were found in samples without mixing before analysis after thawing from frozen state, due to formation of Tg concentration gradient in test tube. For obtaining reliable results, samples must be mixed before analysis when thawed from frozen storage.