bluuebunny/crossref_metadata_2025_split huggingface dataset:
B-125 Laboratory Profiles for Diagnostic Workup of Acute Abdominal Pain in the Emergency Department: A Comparative Study of University and Non-University Acute Care Hospitals in Germany and Switzerland
Authors: Bauer I , Grossmann K , Risch L , Renz H , Risch M 
Published: October 2024

Abstract

Background
Laboratory medicine plays a fundamental role in patient care, especially in emergency departments where rapid diagnosis is critical to the efficient management of high patient volumes. With the aim of simplifying and standardizing laboratory requests, laboratory profiles have widely been established. This study uses the laboratory profile for “acute abdominal pain” as an example to illustrate the extent to which the laboratory profiles used in hospitals differ from each other and whether they are in line with current scientific recommendations.

Methods
Hospital data and laboratory profiles for “acute abdominal pain” from 18 hospitals, 9 from Germany and 9 from Switzerland, were analyzed and compared. The hospitals were distinguished by bed size, inpatient and outpatient case numbers, country affiliation and university level. In addition, an 'evidence-based laboratory profile' for acute abdominal pain was created based on current guidelines for the five most important causes of acute abdominal pain and compared with hospital laboratory profiles.

Results
German hospitals include significantly more laboratory parameters into acute abdominal pain profiles than Swiss hospitals (p = 0,0052). No significant differences in the number of laboratory parameters were found between university and non-university hospitals (p = 0,0507). There is a significant positive correlation between the hospital bed size and the number of laboratory parameters in the profiles (r = 0,5521). The number of inpatient cases in a hospital are also positively correlated with the number of laboratory parameters in the profiles (r = 0,4751). The number of outpatient cases ist not associated with the number of laboratory in the profiles parameters (r = 0,0599). The evidence-based laboratory profile for acute abdominal pain includes 21 laboratory parameters, but only two of them are collected by all investigated hospitals (bilirubin and ALAT).There were no significant differences in the fulfillment of the evidence-based laboratory profile between Germany and Switzerland, or between university or non-university status.

Conclusions
The study shows that there are quantitative and qualitative differences between the laboratory profiles for investigation of acute abdominal pain within the participating hospitals. In Germany and Switzerland there is no consensus on which analyses to include into a profile investigating acute abdominal pain. For increasing efficiency and accuracy of laboratory testing in in the diagnostic workup of acute abdominal pain it seems advisable to obtain consensus on what to reasonably include into a profile on a national or international level.
B-128 Delivering Predictable Operational efficiency gains at our core central reference laboratory with strategic deployment of navify® Lab Operation informatics automation solution
Authors: Christy A L , Gohil S , Lad A , Alangadan K , Shah N , Bhakta S , Manjure A , Shaikh S 
Published: October 2024

Abstract

Background
Metropolis Healthcare Limited (‘MHL’) operates a network of 200 clinical labs in India, our Global Reference Lab (GRL) in Mumbai processes over 25000 tests in a 17 hour daily operation. We are an ISO15189 and CAP accredited laboratory. Our strategic goals have been to bring operational standardization across the network & Improve speed of service with a predictable 90 percentile production TAT. To achieve this goal, we chose digitalization of our laboratory operation with the deployment of navify ® Lab Operations informatics automation solution in. This poster explains our journey of planning, implementing, and delivering on our goal of predictable operational efficiency. The digital solution is at the forefront of all digitalization IQC processes, auto validation and auto approval of patient results passing through a framework of autoverification rules and complete traceability of processes.

Methods
The poster will explain the scope, planning and implementation approach of this digital automation project at Global reference Lab in 5 stepsHL7 order structure for communication between LIS and navify ® Lab Operations22 analyzers from 11 different manufacturers being connected to the Informatics solution. the corresponding testingTest & IQC (Internal Quality Control) Master with specific ranges and rules10 steps AV (Auto verification) Rules decision framework of concentric sieves across lab disciplines (155 AV Algorithms have been configured at GRL)Structured user acceptance testing framework before Go Live.

Results
This poster discusses the outcomes that we have seen on deployment of this digital solution.Over 25,000 test results are subject AV engine daily with AV rate of 75 % of all results in Biochemistry, Immunoassays.66 % of all Complete Blood Count (CBC) reports 95 % of all HbA1c results 93 % of all ESR resultsOver 1750 QC results are subject to QC rules dailyThere is an improvement of 4 hours observed in production TAT

Conclusions
Laboratory Informatics solution has enhanced lab performance in terms of TAT & efficiency of review. The staff satisfaction (both technical and medical) has increased and we see an impact on production outcome. The poster will also show an incremental effectiveness analysis by comparing key performance areas such as predictability in production, staff time saved, before and after technology deployment.
B-130 Time-of-day dependence of running averages for some components of metabolic panels at our hospital: relation to strategy for patient-based quality control
Authors: Stickle D , Karaseva A O 
Published: October 2024

Abstract

Background
Our hospital system recently reorganized its lab services so as to restrict in-house testing almost exclusively to inpatient testing. This disruption in patient mix caused us to reassess properties of running averages for our most common analytes, for potential use of such data in real-time patient-based quality control (PBQC). In particular, we examined whether there were analytes for which there was significant dependence of running averages on 24-h clock time (time-of-day, TOD).

Methods
We performed a retrospective analysis of 3-months' data (FY24, Q2) for patient results of 13 components of the Basic Metabolic Panel (BMP) and Comprehensive Metabolic Panel: Albumin*, Alkaline phosphatase, Alanine amino transferase, Aspartate aminotransferase*, Calcium*, Chloride*, CO2*, Creatinine, Potassium*, Total Protein*, Sodium, Total Bilirubin, and Urea. Running averages for 20 consecutive results (20-mers) were computed for data restricted to results within reference intervals. This produced an overall mean (X) and standard-deviation (SD) of 20-mers for each analyte. We then computed the average 20-mer result (Y) reported within 1-h bins across 24-hour clock time (t). Y(t) was regarded as having TOD-dependence if: (a) there was an 8-h interval of contiguous results for Y that were strictly either below or above X; and (b) either nadir or apex values for |Y-X| exceeded 0.5 SD.

Results
Seven analytes (*, above) demonstrated TOD-dependence of running means for 20-mers according to criteria given above. An example of TOD-dependent Y(t) is shown in Figure (Albumin).

Conclusions
For our hospital, TOD-dependence of running means was identified for 7 of 13 metabolic panel analytes. TOD-dependence of running means is a circumstance in which use of only a fixed target for running means in PBQC would lead to inherent TOD-dependent variation in capability for systematic error detection. Use of TOD-dependent targets for PBQC would be appropriate in these cases.
B-131 The fallacy of average sigma levels from mixed sample levels
Authors: BROOKS Z 
Published: October 2024

Abstract

Background
Sigma measures the number of SDs (z-value) from the existing sample mean to the nearest analytical performance standard or allowable error limit. Authors and software programs often measure sigma metrics for each QC sample but use an average sigma to compare methods and select QC strategies. That practice leads to dramatic over or under-estimation of the number of errors reported and the selection of inappropriate QC strategies.

Methods
Data samples were created to produce sigma values of 3.0, 4.5, and 6.0. Microsoft Excel function NORMSDIST was used to convert sigma to percent to number of errors per million patients. NORMSINV was used to convert the number of errors per million patients to sigma.

Results
A. Six sigma represents a method with a failure rate of 0.000001% or 0.001 failures of ASP/TEa per million patients. B. Three sigma represents a method with a failure rate of 0.135 percent or 1,350 failures of ASP/TEa per million patients. C. While the average sigma value of samples A and B was 4.5s, the average error rate was 0.0675 percent or 675 failures of ASP/TEa per million patients. D. An error rate was 0.0675 percent converts with the NORMSINV function to a sigma of 3.21. E. A true 4.5 sigma method would have a failure rate of 0.00034 percent or 3.4 failures of ASP/TEa per million patients.

Conclusions
Sigma studies that present an average sigma value underestimate the true number of errors reported. It would be more scientifically correct to either report the number of errors reported or to report the average sigma value based on the average number of errors. Laboratory professionals should interpret sigma studies and publications cautiously if a single sigma is used to represent two or more data sets.
B-141 Analysis of risk factors and construction of prediction model for pneumonia in patients with pneumoconiosis based on the clinical laboratory indexes
Authors: Xu Y , Cui X , Guo Y 
Published: October 2024

Abstract

Background
Pneumoconiosis has been the leading industrial disease in China. Pneumonia is one of the common comorbidities for patients with pneumoconiosis, which may lead to the worse condition and poor prognosis. Timely and accurate diagnosis is necessary to retard the pneumonia progression in pneumoconiosis patients. Due to the similarity of clinical features between pneumoconiosis and pneumonia, clinical laboratory tests are needed for assessing the hazard of pneumonia occurrence in patients with pneumoconiosis. Therefore, we aim to explore the risk factors of pneumonia from laboratory test indexes for patients with pneumoconiosis, construct prediction model, and evaluate its feasibility.

Methods
A total of 243 patients with pneumoconiosis from the General Hospital of Xuzhou Mining Group from September 2021 to August 2023 were selected as the modeling set, which was further separated as the non-pneumonia group and the pneumonia group. Nineteen laboratory test indexes related to inflammation, tumor markers, renal function, and blood routine examination were compared between the two groups. The univariate and multivariate Logistic analysis was used to screen out risk factors and construct the prediction model. Two hundred and twenty-eight patients with pneumoconiosis from General Hospital of Xuzhou Mining Group (Yi'an Branch) were enrolled as the validation set. The predictive efficiency of the model on pneumonia for patients with pneumoconiosis was evaluated through Hosmer-Lemeshow(H-L)test and receiver operating characteristic (ROC) curve.

Results
C-reactive protein (CRP), interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-10 (IL-10), β2 microglobulin, creatinine, urea, neutrophil percentage, lymphocyte percentage, and lymphocyte count in pneumonia group were significant different from those in non-pneumonia group (&lt;0.05). Logistic regression analysis suggested that CRP (OR=3.883, &lt;0.001), IL-6 (OR=1.217, =0.003), IL-8 (OR=1.215, =0.002) and β2-microglobulin (OR=2.838, =0.002) were independent risk factors for pneumonia in patients with pneumoconiosis. The prediction model was constructed as Logit (P) =1.357×CRP+0.196×IL-6+0.195×IL-8+1.043×β2-microglobulin-9.772. The H-L test demonstrated that there was no significantly difference between predicted values and the true values. The areas under ROC curves of the model in the modeling set and the validation set were 0.909 and 0.848. The sensitivity was 86.8% and 75.6%, and accuracy 82.1% and 79.7%, respectively.

Conclusions
CRP, IL-6, IL-8, and β2-microglobulin were independent risk factors of pneumonia for pneumoconiosis patients. The risk model constructed by laboratory test indexes showed a good predictive performance, which might provide laboratory evidence for the pneumonia diagnosis in patients with pneumoconiosis.
B-147 Enhancing the Detection of Vitamin D Metabolites by LC-MS/MS Using a Novel Derivatization Kit
Authors: Muramatsu S , Nakagawa T , Yokota H , Wakui M , Matsushita H 
Published: October 2024

Abstract

Background
Vitamin D is crucial for various biological functions and exists in various tissues, including bones, intestines, and kidneys. 25-hydroxyvitamin D serves as a key marker for assessing vitamin D status in the body. Currently, LC-MS/MS is the gold standard for measuring vitamin D levels. The JeoQuant Kit for LC/MS Analysis of Vitamin D Metabolites (JEOL, Tokyo, Japan), which is used for the determination of vitamin D metabolites in serum based on the DAP-PA (Seki et al, 2019), enhances the ionization efficiency in the LC-MS/MS system for four vitamin D metabolites (25(OH)D3, 25(OH)D2, 24,25(OH)2D3 and 3-epi-25(OH)D3), enabling accurate fractionation and quantification. DAP-PA was developed as a caged Cookson-type reagent, demonstrating significantly enhanced stability compared to previous non-caged Cookson-type reagents. Our research aimed to assess whether the kit works practically.

Methods
The JeoQuant Kit contains internal standards of stable isotope-labelled compounds at appropriate concentrations, derivatization reagents, quality control materials derived from human serum and calibration materials. An Acquity H-Class UPLC coupled with an Acquity TQD mass spectrometer (Waters, MA, US) was used for analysis. CAPCELL CORE C18 2.1mm*100mm (Osaka-soda, Tokyo, Japan) was used as the analytical column. For the pretreatment, an Isolute SLE+ column (Biotage, Tokyo, Japan) was used. Eluent of LC-MS/MS was used 0.1% formic acid aqueous solution and 0.1% formic acid acetonitrile, with binary gradient.

Results
Using attached control L/H, reproducibility was shown by intra- and inter-assay CVs which were below 10% and 15%, respectively. Storage tests of derivatization agents at -20°C, 4°C, and room temperature for one week showed no significant difference on peak areas (one-way ANOVA). Through this derivatization, it was possible to achieve more than a 20-fold increase in sensitivity compared to measurements without derivatization. Notably, low concentrations of 3-epi-25(OH)D3 were distinctly separated and detected.

Conclusions
This study showed that the JeoQuant Kit effectively increases the sensitivity of vitamin D metabolites through derivatization. It also emphasized the reagent's notable stability. Furthermore, it enabled the detection of 3-epi-25(OH)D3 with less sensitive LC-MS/MS models, offering clear separation from 25(OH)D3. The kit, which is complete with calibrants, internal standards, and quality control samples, simplifies analytical procedures for vitamin D metabolite quantification, potentially aiding in developing Vitamin D- related biomarkers. Efforts to compare analytical performance of this kit with that of other methods are underway to establish its benefits.
B-152 Analysis of carbonyl compounds in exhaled breath for detection of COVID-19
Authors: Fu X , Xie Z , Morris J D , Alksas A D , El-Baz A D , Huang J D , Nantz M H 
Published: October 2024

Abstract

Background
COVID-19 pandemic has caused enormous loss of lives and economic disruption. The global crisis has resulted in more than 700 million infections and 7 million deaths worldwide. Rapid screening and detection of highly infectious respiratory diseases is a key for preventing and curbing future epidemic and pandemic. The objective of this work is to develop a novel breath analysis technique for detection of COVID-19 using chemoselective capture of carbonyl compounds in exhaled breath for analysis by gas chromatography-mass spectrometry (GC-MS). Respiratory viral infection causes oxidative stress and inflammation in its host body which leads to production of higher levels of some carbonyl compounds through oxidation of lipids and could be detected in exhaled breath. This breath analysis technique can be rapidly adapted for screening infectious respiratory diseases for future epidemic and potential pandemic.

Methods
A total of 237 subjects were enrolled in this study. Of these, 142 were COVID-19 positive and 95 were negative. One liter exhaled breath in Tedlar bags from both COVID-19 positive and negative subjects confirmed by reverse transcriptase polymerase chain reaction between April 2022 and September 2023. The collected one liter breath samples were completely evacuated through a cartridge packed with silica particles in 2-3 minutes. Silica particles were coated with a reactive aminooxy agent for capture of carbonyl compounds in the breath samples through oximation reactions. The captured carbonyl compounds were eluted by methanol and the eluted solutions were analyzed by GC-MS for calculation of each compound concentration in the exhaled breath samples. Biostatistics was used to identify significant carbonyl compounds (defined as p value &lt; 0.05) as markers of CPOVID-19 infection. A machine learning algorithm was implemented with the captured carbonyl compounds as input features for differentiation of COVID-19 positive from negative subjects.

Results
A total of more than 30 carbonyl compounds were detected in exhaled breath samples of all subjects. 10 features including 3 individual carbonyl compounds and 7 compound ratios show significant differences (p value &lt;0.05) between COVID-19 positive and negative groups. The developed machine learning and artificial intelligence (AI) algorithms successfully separated COVOD-19 positive from negative with an accuracy of 95.4%, sensitivity of 96.5%, specificity of 93.7%, and AUROC=0.974.

Conclusions
The analysis of carbonyl compounds in exhaled breath by GC-MS has great potential for non-invasive detection of COVID-19. The method could be rapidly adapted for detection of other respiratory infectious diseases with a small sample size and data set for training of the machine learning and AI algorithms.
B-154 Development and Evaluation of an Automated High-Throughput Magnetic Bead-Based pre-treatment Platform for Lipid-Soluble Vitamins in Clinical Mass Spectrometry
Authors: Ma T , Liu H , Yao H , Yang Y , Dong L 
Published: October 2024

Abstract

Background
Mass spectrometry has become a critical tool in clinical diagnostics due to its unparalleled sensitivity, specificity, and ability for multiplex analysis, redefining standards in small molecule detection. However, its efficacy is limited by complex sample preparation requirements, such as purification and enrichment. Traditional pre-treatment methods often involve labor-intensive, error-prone procedures that can dilute samples, thereby necessitating enhanced sensitivity in mass spectrometry. Addressing these challenges, we developed an automated, high-throughput pre-treatment platform using magnetic bead technology to streamline the preparation of small molecules for analysis via liquid chromatography-tandem mass spectrometry (LC-MS/MS). This study assesses the platform's effectiveness and reliability using lipid-soluble vitamins as a test case.

Methods
We developed a magnetic bead-based extraction process for lipid-soluble vitamins (Vitamins A, 25-hydroxyvitamin D2, 25-hydroxyvitamin D3, E, and K1) from clinical serum samples, utilizing Zybio's EXM3000 for automation. Protein-bound vitamins were dissociated using methanol and isopropanol, followed by magnetic bead extraction. The extracted vitamins underwent LC-MS/MS analysis. Comparative analysis with traditional liquid-liquid extraction methods, using 20 clinical samples and commercially available kits, evaluated this novel approach's analytical efficacy.

Results
The method showed excellent linearity (r &gt; 0.99) for the target compounds. The imprecision ranged from 1.5% to 9.3%, and the accuracy (recovery rate) was between 91.5% and 113.4%. The limit of quantification, repeated six times, had a deviation of -8.5% to 13% and a CV of 1.5%-6.4%, meeting industry standards and EP document requirements. Comparisons with commercial kits in 20 clinical samples showed deviations within ±15%, and the 95% confidence interval for expected bias met the testing requirements. The method also demonstrated high correlation with the commercial kits, as evidenced by regression equations for Vitamin A: y = 0.9732x - 1.7985, 25-hydroxyvitamin D2: y = 1.0163x - 0.0055, 25-hydroxyvitamin D3: y = 1.0597x - 0.7968, Vitamin E: y = 1.0569x - 0.2917, and Vitamin K1: y = 1.0055x - 0.0039.

Conclusions
This study showed excellent performance of a novel automated high-throughput magnetic bead sample preparation platform for small molecules in clinical mass spectrometry. This technology overcomes the complexities associated with sample pre-treatment in clinical mass spectrometry and holds broad clinical application prospects in mass spectrometric analysis.