Pre-analytical Data Research Articles

An emergency department intervention to improve earlier detection of community-onset bloodstream infection among hospitalized patients

Blood cultures (BCs) are essential microbiologic tests, but blood culturing diagnostic stewardship is frequently poor. We aimed to study the process-related failures and to evaluate the effect of an emergency department (ED) intervention on BCs collection practices and yield. We implemented an ED-quality improvement intervention including educational sessions, phlebotomists addition, promoting single-site strategy for BC-collection and preanalytical data feedback. BC-bottles collected, positive BCs, blood volumes and documentation of collection times were measured, before (December 2021-August 2022) and after (September 2022-July 2023) intervention. Results were corrected to hospitalizations admissions or days. We used interrupted-time series analyses for comparisons. A total of 64,295 BC bottles were evaluated, 26,261 before and 38,034 postintervention. The median ED-BCs collected per week increased from 88 to 105 BCs (P<.0001), resulting from increased early sampling (P=.0001). Solitary BCs decreased (95%-28%), documented times increased (2.8%-25%), and average blood volume increased (3mL to 4.5mL) postintervention. Community-onset Bloodstream infections (BSIs) increased (39.6-52 bottles/1,000 admissions, P=.0001), while Health care-associated BSIs decreased (39-27 bottles/10,000 days, P=.0042). Contamination rates did not change. An ED-focused intervention based on the education sessions and single-site strategy improved culturing stewardship and facilitated the early identification of BSI without an increase in contamination.

Are we ready for translational research based on material and data from the Danish CancerBiobank and can we gain new knowledge from biobank registration?

Bio-and GenomeBank, Denmark (RBGB) is a nationwide infra-structure. Danish CancerBiobank (DCB) is a biobank in RBGB. The aim is to describe the degree of biological material collected and stored in DCB for patients diagnosed with primary ovarian cancer registered in The Danish Gynecologic Cancer Database (DGCD). Furthermore, to investigate the concordance between predicted organ of disease registered in RBGB at time of sampling (presumed diagnosis) with final diagnosis for patient. Data extraction from DGCD and DCB. Biological materials are present for 1.347 (62%) of 2.172 patients with primary ovarian cancer (OC). The median age of OC patients were 68 years (range: 18-90 years). Median age of patients with biological material in DCB was 67 years and for patients without biological material in DCB 69 years (p ≤ 0.0001). The histological subtypes for the 1347 OC patients with biological material were 911 (68%) serous adenocarcinoma, 97 (7%) endometrioid adenocarcinoma, 80 (6%) mucinous adenocarcinoma, 58 (4%) clear cell carcinoma, and for 201 (15%) no information were registered. For 327 patients (24%), the presumed diagnosis was hematological with a final diagnosis of OC. Using clinical data and biological material including pre-analytical data regarding the biological material the possibility for translational research is optimal. Furthermore, information registered through daily working procedures may propose the need for additional biomarkers to aid clinicians to stratify patients to treatment in correct fast-track packages.

External Quality Assurance programs for processing methods provide evidence on impact of preanalytical variables

An annual External Quality Assurance (EQA) program has been provided to processing laboratories over the last ten years, allowing them to assess the performance of their processing methods, such as nucleic acid extractions or peripheral blood mononuclear cell (PBMC) isolation and cryopreservation. The objective of this study was to perform a global analysis on almost 1000 EQA scheme/participant data in order to assess (i) the impact of critical preanalytical factors on quantitative or qualitative attributes of different types of specimens and (ii) laboratory performance pattern over time. Statistical analysis was performed within each EQA scheme based on categorized preanalytical data provided by the participants and on centralized measurements of relevant quality attributes of the produced specimens (z-scores): DNA, cell-free (cf)DNA or RNA extraction from blood, DNA or RNA extraction from formalin fixed tissue, DNA or RNA extraction from frozen tissue, DNA extraction from saliva or stool, viable PBMC isolation and cryopreservation. The most critical preanalytical factors in nucleic acid extraction schemes were the nucleic acid extraction method and kit, the elution buffer, the enzymes used during extraction, the input material quantity and the storage temperature. Several indications of laboratory performance improvement over time could be seen. The conclusions are that EQA for processing methods provides unique evidence-based insights into the impact of preanalytical factors and the comparative performance of different processing methods and kits, while supporting laboratories in validating their processing methods.

Metaboprep: an R package for preanalysis data description and processing.

MotivationMetabolomics is an increasingly common part of health research and there is need for preanalytical data processing. Researchers typically need to characterize the data and to exclude errors within the context of the intended analysis. Whilst some preprocessing steps are common, there is currently a lack of standardization and reporting transparency for these procedures.ResultsHere, we introduce metaboprep, a standardized data processing workflow to extract and characterize high quality metabolomics datasets. The package extracts data from preformed worksheets, provides summary statistics and enables the user to select samples and metabolites for their analysis based on a set of quality metrics. A report summarizing quality metrics and the influence of available batch variables on the data are generated for the purpose of open disclosure. Where possible, we provide users flexibility in defining their own selection thresholds.Availability and implementation metaboprep is an open-source R package available at https://github.com/MRCIEU/metaboprep.Supplementary information Supplementary data are available at Bioinformatics online.

Purpose, Partnership, and Possibilities: The Implementation of the Dog Aging Project Biobank.

Biobanks have been supporting longitudinal prospective and retrospective studies by providing standardized services for the acquisition, transport, processing, storage, and distribution of high-quality biological material and associated data. Here, we describe how the Dog Aging Project (DAP), a large-scale longitudinal study of the domestic dog (Canis familiaris) with translational applications for humans, developed a biobank of canine biospecimens and associated data. This was accomplished by working with the Cornell Veterinary Biobank, the first biobank in the world to receive accreditation to ISO 20387:2018-General Requirements for Biobanking. The biobank research team was involved in the early collection stages of the DAP, contributing to the development of appropriate workflows and processing fit-for-purpose biospecimens. In support of a dynamic strategy for real-time adjustment of processes, a pilot phase was implemented to develop, test, and optimize the biospecimen workflows, followed by an early phase of collection, processing, and banking of specimens from DAP participants. During the pilot and early phases of collection, the DAP Biobank stored 164 aliquots of whole blood, 273 aliquots of peripheral blood mononuclear cells, 130 aliquots of plasma, and 70 aliquots of serum, and extracted high molecular weight genomic DNA suitable for whole-genome sequencing from 109 whole blood specimens. These specimens, along with their associated preanalytical data, have been made available for distribution to researchers. We discuss the challenges and opportunities encountered during the implementation of the DAP Biobank, along with novel strategies for promoting biobanking sustainability such as partnering with a DAP quality assurance manager and a DAP marketing and communication specialist and developing a pilot grant structure to fund small innovative research projects.

UriSed 3 PRO automated microscope in screening bacteriuria at region-wide laboratory organization

Background and aimsWe assessed the possibility to rule out negative urine cultures by counting with UriSed 3 PRO (77 Elektronika, Hungary) at Helsinki and Uusimaa Hospital District. Materials and methodsBacteria counting of the UriSed 3 PRO automated microscope was verified with reference phase contrast microscopy against growth in culture. After acceptance into routine, results of bacteria and leukocyte counting from 56 426 specimens with eight UriSed 3 PRO instruments were compared against results from parallel samples cultured on chromogenic agar. Laboratory data including preanalytical details were accessed through the regional database of the Helsinki and Uusimaa Hospital District. ResultsA combined sensitivity of 87–92% and a negative predictive value of 90–96% with a specificity of 54–50% was reached, depending on criteria. Preanalytical data (incubation time in bladder) combined with the way of urine collection would improve these figures if reliable. ConclusionsComplex patient populations, regional logistics and data interfases, and economics related to increased costs of additional particle counts against costs of screening cultures of all samples, did not support adaptation of a screening process of urine cultures. This conclusion was made locally, and may not be valid elsewhere.

Clinically and temporally specific diagnostic thresholds for plasma ACTH in the horse.

Pituitary pars intermedia dysfunction (PPID) is commonly investigated using plasma ACTH concentrations but problems exist with currently available diagnostic thresholds. To derive temporally specific diagnostic thresholds for equine plasma ACTH concentration to be used alongside clinical judgement in each individual week of the year and appropriate for the degree of clinical suspicion in any given case. Furthermore, to apply these thresholds to compare the prevalence of high and low ACTH in two subgroups of animals with high and low clinical suspicion of PPID. A retrospective population study examining a large laboratory database of equine plasma ACTH concentrations using an indirect approach to calculate diagnostic thresholds. Logs of plasma ACTH concentrations from 75892 individual horses were examined using robust L2 estimation of mixtures of two normal distributions in categories of each week and month of the year. Thresholds dividing the two populations of high-ACTH and low-ACTH horses were then established at different levels of sensitivity and specificity and compared with clinical subgroups of horses divided based on reported clinical signs, as having high (n=4036) or low (n=3022) clinical suspicion of PPID. For most of the year there were small interweek differences in diagnostic thresholds. However, from mid-June to early-December diagnostic thresholds showed greater interweek variability, reaching a maximum in late September and early October. Grouping of high- and low-ACTH compared favourably with grouping based on clinical signs. Given the multiple sources of diagnostic samples, pre-analytical data could not be fully verified. Diagnostic thresholds for equine plasma ACTH vary through the year. It is especially important to consider the temporally specific threshold between June and December. Different clinical thresholds can be used depending on the case circumstances and whether a false-positive or false-negative diagnosis is deemed least desirable.

Laboratory Information Systems and Instrument Software Lack Basic Functionality for Molecular Laboratories

Laboratory information systems (LISs) have some basic functionality necessary for molecular workflow that is glaringly absent. This study determined functionality gaps of LISs in molecular laboratories and the associated impact to workflow, efficiency, and security by collecting anonymous survey data from clinical laboratory professionals. A 34-question survey (30 required+4 optional) was compiled using an online survey tool. Participants were recruited through several professional molecular society listservs and given 4 weeks to complete the survey. Data collected included participant demographics, scope of testing, software capabilities for the LIS and molecular instruments, and comments. Eighty respondents completed the entire survey. Many desired versus actual functionality gaps were identified. Prominent among these were bar coding, LIS interfacing, storage of preanalytical data, Health Insurance Portability and Accountability Act compliance/information security, and reporting. Much basic functionality is lacking in molecular LISs and molecular instrument software. Some of these results indicate that instruments and LISs are not compliant with the Health Insurance Portability and Accountability Act. Collaboration between molecular professionals and manufacturers of instruments and software is necessary to correct these deficits and is critically important to ensure the continued high quality and safety of molecular practice as the volume of testing skyrockets.

Why are Events, Facts, and States of Affairs Different?

Abstract This article claims that events, facts and states of affairs need to be differentiated. It takes as a starting point Chisholm’s (1976) claim that only his ontology of states of affairs explains effectively thirteen sentences related to propositions and events. He does this by reducing propositions and events to states of affairs. We argue that our ontology also solves those problems. We defend a hierarchized Platonist ontology that has concrete entities (objects and events) and abstract entities (properties, facts and states of affairs). The distinctions we propose allow us to explain the pre-analytic data analyzed by Chisholm without reducing entities. We claim that our ontology provides a different way of explaining that data, and is, thus, promissory.

Monitoring and reporting of preanalytical errors in laboratory medicine: the UK situation.

Most errors in the clinical laboratory occur in the preanalytical phase. This study aimed to comprehensively describe the prevalence and nature of preanalytical quality monitoring practices in UK clinical laboratories. A survey was sent on behalf of the Association for Clinical Biochemistry and Laboratory Medicine Preanalytical Working Group (ACB-WG-PA) to all heads of department of clinical laboratories in the UK. The survey captured data on the analytical platform and Laboratory Information Management System in use; which preanalytical errors were recorded and how they were classified and gauged interest in an external quality assurance scheme for preanalytical errors. Of the 157 laboratories asked to participate, responses were received from 104 (66.2%). Laboratory error rates were recorded per number of specimens, rather than per number of requests in 51% of respondents. Aside from serum indices for haemolysis, icterus and lipaemia, which were measured in 80% of laboratories, the most common errors recorded were booking-in errors (70.1%) and sample mislabelling (56.9%) in laboratories who record preanalytical errors. Of the laboratories surveyed, 95.9% expressed an interest in guidance on recording preanalytical error and 91.8% expressed interest in an external quality assurance scheme. This survey observes a wide variation in the definition, repertoire and collection methods for preanalytical errors in the UK. Data indicate there is a lot of interest in improving preanalytical data collection. The ACB-WG-PA aims to produce guidance and support for laboratories to standardize preanalytical data collection and to help establish and validate an external quality assurance scheme for interlaboratory comparison.

A Call to Standardize Preanalytic Data Elements for Biospecimens, Part II.

Biospecimens must have appropriate clinical annotation (data) to ensure optimal quality for both patient care and research. Additional clinical preanalytic variables are the focus of this continuing study. To complete the identification of the essential preanalytic variables (data fields) that can, and in some instances should, be attached to every collected biospecimen by adding the additional specific variables for clinical chemistry and microbiology to our original 170 variables. The College of American Pathologists Diagnostic Intelligence and Health Information Technology Committee sponsored a second Biorepository Working Group to complete the list of preanalytic variables for annotating biospecimens. Members of the second Biorepository Working Group are experts in clinical pathology and microbiology. Additional preanalytic area-specific variables were identified and ranked along with definitions and potential negative impacts if the variable is not attached to the biospecimen. The draft manuscript was reviewed by additional national and international stakeholders. Four additional required preanalytic variables were identified specifically for clinical chemistry and microbiology biospecimens that can be used as a guide for site-specific implementation into patient care and research biorepository processes. In our collective experience, selecting which of the many preanalytic variables to attach to any specific set of biospecimens used for patient care and/or research is often difficult. The additional ranked list should be of practical benefit when selecting preanalytic variables for a given biospecimen collection.

A Call to Standardize Preanalytic Data Elements for Biospecimens

Biospecimens must have appropriate clinical annotation (data) to ensure optimal quality for both patient care and research. Clinical preanalytic variables are the focus of this study. To define the essential preanalytic variables (data fields) that should be attached to every collected biospecimen and to provide a complete list of such variables, along with their relative importance, which can vary, depending on downstream use, institutional needs, and information technology capabilities. The College of American Pathologists Diagnostic Intelligence and Health Information Technology Committee sponsored a Biorepository Working Group to develop a ranked list of the preanalytic variables for annotating biospecimens. Members of the working group were experts in anatomic, clinical, and molecular pathology; biobanking; medical informatics; and accreditation. Several members had experience with federal government programs, such as the National Cancer Institute's Biospecimens and Biorepository Branch and the National Cancer Institute's Community Cancer Center Program. Potential preanalytic variables were identified and ranked along with available supporting evidence, definitions, and potential negative effects if the variable was not attached to the biospecimen. Additional national and international stakeholders reviewed the draft manuscript. The ranked listing of 170 preanalytic variables produced can be used as a guide for site-specific implementation into patient care and/or research biorepository processes. Conclusions.-In our collective experience, it is often difficult to choose which of the many preanalytic variables to attach to any specific set of biospecimens used for patient care and/or research. The provided ranked list should aid in the selection of preanalytic variables for a given biospecimen collection.

Pre-analytical issues in the measurement of circulating microparticles: current recommendations and pending questions

Pre-analytical issues in the measurement of circulating microparticles: current recommendations and pending questions

Investigating the quality control of laboratory information

Clinical laboratory results play an important role in helping physicians in diagnosis and treatment. In view of the direct effect of the working methods on the quality of data in the laboratory, quality control of data and results in the Biochemistry Ward of Laboratory includes taking into account all the factors and variables relating to all the pre-analytical, analytical and post-analytical steps at this ward. The objective of this study was to examine the quality control of data and results in the biochemistry departments of hospital laboratories in universities of medical sciences in Tehran.Current study was a descriptive research, and 40 biochemistry laboratories in universities of medical sciences in Tehran constituted the settings of the study. Data were collected by a checklist and a questionnaire using observation and interview. Using the checklist, 33 effective factors in the pre-analytical step; 18 effective factors in the analytical step and 8 effective factors in post-analytical step were examined. The questionnaire included questions relating to biochemical factors in the laboratories, while the factors affecting the quality of the results were examined by using checklist. Data from questions and observations were analyzed by using descriptive statistics and by determining the absolute and relative frequencies.Results showed that in all settings of the study, 58%, 68% and 87% of the factors affecting the pre-analytical, analytical and post-analytical data and results were taken into consideration respectively. However, the biochemistry directors remarked that they considered 77% and 89% of the first two groups of factors respectively, and the third groups of factors were considered only by observation.according to the findings by the checklists, sufficient attention was paid to 58% of the factors effective on pre-analytical data quality (Identifying the patient; Labeling the sample while collecting the sample; etc.), 68% of the factors effective on analytical data quality (Analyzing the samples during the 1 to 4 hours following the collection of the samples; Using control samples for evaluating the operation of instruments once in every 8 hours; etc.) and 87% of the factors effective on the post-analytical data quality (Legibility of the hand-written reports; Similarity of the hand-written reports to the typewritten report, in terms of patient ID data record; etc.) while there is no enough attention paid to other factors in pre-analytical step (Preparing the patient; Paying attention to the physiological changes of the patient’s body; etc.), analytical step (availability of written guidelines for performing certain work where the samples are analyzed; Calibrating the instruments according to the standard program; etc.) and post-analytical step (precision in recording distinguishing features in real values). Also, by comparing the findings obtained using the two tools, it can be found out that the findings do not match each other in certain factors and that the amount of findings obtained from the questionnaire is more than the findings obtained from the checklists.

Incompleteness and fictionality in Meinong's object theory

objects only, but a theory of all objects, existing and non-existing, real, possible and impossible objects. Only the important class of incomplete objects, which as a subclass contains the objects of fiction has been associated by him with a theory of universals as abstract objects. It seems to me that one of Meinong's most fruitful conceptions is his theory of incomplete objects which may be completed. This conception allows for the fact that we can elaborate on our concepts and ideas and that we do widen our knowledge of objects even if they are incomplete. The propositional attitude with which most of this work is done is not knowing or believing, which are directed towards the universe of actual objects, but assuming. That is why Meinong thinks that in all our intellectual efforts we have to go through assumptions. With the capacity of assuming any kind of object, according to the principle of the freedom of assumptions, we cannot only create objects but complete them, even if we cannot turn them into complete ones. How the completing is done depends on the field of work within our intellectual fabric, be it everyday work of imagination, phantasy, or plain thinking in the scientific enterprise, or work in the arts. In none of these and many other fields can we dispense with fictional objects, that is to say, with incomplete objects that serve as those objects which we try to use as starting points for further work. Clearly, the ontology of Meinong does provide us with what we may need when we do not want to reduce different kinds of objects to one another or when we are unable to reduce them: it is a rich ontology. But is it too rich? I do not think so, if we read it bona fide. It proceeds from experience or -if you like -preanalytic data to the explanation by theory, but it does not propound a theory which answers all the questions that can be raised. Surely, there remain many questions and quite a lot of them are difficult to answer. I mention only a few of them. The first question is how incomplete objects are related to the complete ones, like the object "Something Blue" (etwas Blaues) to the blue object which we see on our desk. The second is more general. How are we to view the relation between an incomplete object and its complete counterpart, if we use the incomplete and even fictional object to grasp the complete one? In other words, how is the incomplete object embedded or engraved in the real one, if the latter is the target of our acts of assuming, believing, or judging?

Współzależność analizy etycznej i etyki

This paper is concerned with the interrelationship between ethical analysis (metaethics) and normative ethics. It is argued that the two cannot be divorced logically and that their separation explains in large part why analytical ethical theory has so little of relevance to say to live moral issues. Two of the bases of the prevailing logical separation of the inquiries are examined critically: first, a de jure basis in which the separation is defended on theoretical grounds, e.g. by intuitionists, emotivists and prescriptivists, and second, a de facto basis in which we find a separation in practice that results from using analytical techniques borrowed from other areas in philosophy (viz. epistemology) that are inappropriate for ethics, e.g. by ordinary language philosophers. The prevailing conception of ethical analysis is criticized on the grounds that both the pre-analytical data and the aims of ethical analysis are sui generis and not to be compared to the data and aims of the other kinds of logical analysis. Problems like ethical relativism, moral dilemmas and akrasia cannot be analysed separately, but are part of the given logical and conceptual analysis of ethics.