Journal of Applied Laboratory Medicine最新文献

{"title":"Assessing the Clinical Significance of the MCM6 c.-14011C/T Polymorphism in Lactose Intolerance: Insights from a Case Series.","authors":"Stine B Bruun, Jonna S Madsen, Pernille M Bøttger","doi":"10.1093/jalm/jfae138","DOIUrl":"https://doi.org/10.1093/jalm/jfae138","url":null,"abstract":"","PeriodicalId":46361,"journal":{"name":"Journal of Applied Laboratory Medicine","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142824681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discordant Point-of-Care and Laboratory Hemoglobin A1c Concentrations in Ambulatory Settings.","authors":"Nichole Korpi-Steiner, Steven W Cotten, Randie R Little, Deepa Kirk","doi":"10.1093/jalm/jfae153","DOIUrl":"https://doi.org/10.1093/jalm/jfae153","url":null,"abstract":"","PeriodicalId":46361,"journal":{"name":"Journal of Applied Laboratory Medicine","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142824687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-HDL Cholesterol May Be Preferred over Apolipoprotein B-100 for Risk Assessment when Evaluated by Receiver Operator Characteristic Curve Analysis.","authors":"Stanley S Levinson","doi":"10.1093/jalm/jfae125","DOIUrl":"https://doi.org/10.1093/jalm/jfae125","url":null,"abstract":"<p><strong>Background: </strong>Most studies found that apolipoprotein B (apo B)-100 is a superior marker for coronary risk to non-high-density lipoprotein (HDL) cholesterol (C). Usually, studies use multivariant analysis with single-point odds/risk ratios. In multivariant analysis, when variables are highly correlated they are difficult to interpret. Effects cannot be well discriminated.</p><p><strong>Methods: </strong>Brief review and examination of diagnostic sensitivity and specificity by receiver operator characteristic (ROC) curves at decision levels so that discrimination can be well compared. Since apo B has additional expense, clinical value should be compared in an appropriate format. Apo B and cholesterols were measured in 382 angiographically defined patients.</p><p><strong>Results: </strong>Non-HDLC and apo B were stronger markers than low-density lipoprotein (LDL)C, when examined by logistic regression, but as a result of strong collinearity, non-HDLC appeared weaker than LDLC in the presence of apo B, based on P values. This was true when analyzed with and without nonlipid risk factors. On ROC analysis, apo B and non-HDLC showed stronger C statistics than LDLC and total C. When analyzed alone apo B showed about 6.1% greater sensitivity than non-HDLC. After adjustment for nonlipid risk factors, the C statistics for apo B and non-HDLC were 0.74 and 0.73, and there was little difference in diagnostic specificity.</p><p><strong>Conclusions: </strong>Risk is calculated from an algorithm that includes nonlipid risk factors similar to those examined here along with cholesterols. When assessed by the 10-year screening algorithm, these data support the view that non-HDLC would be less expensive than apo B with similar clinical efficacy.</p>","PeriodicalId":46361,"journal":{"name":"Journal of Applied Laboratory Medicine","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142822681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical and Analytical Performance Evaluation of an Automated Procalcitonin Assay.","authors":"Godwin Ogbonna, Jodiann R Atienza, David W Singleton, Andrea Ott-Vasconi, Stacey A Alvey","doi":"10.1093/jalm/jfae114","DOIUrl":"https://doi.org/10.1093/jalm/jfae114","url":null,"abstract":"<p><strong>Background: </strong>Procalcitonin (PCT) measurement is useful for guiding antibiotic therapy and risk assessment in lower respiratory infections and/or sepsis. This study evaluated clinical and analytical performance of the Vitros® Immunodiagnostic Products B·R·A·H·M·S PCT assay (Vitros PCT).</p><p><strong>Methods: </strong>Precision, limits of blank (LoB), detection (LoD), and quantitation (LoQ) were determined for Vitros PCT, along with method comparison and clinical concordance with the B·R·A·H·M·S PCT™-sensitive KRYPTOR™ assay (KRYPTOR PCT). All-cause 28-day mortality was evaluated according to the change in PCT values (ΔPCT) from day 0 through day 4 in samples from 598 intensive care unit patients with sepsis.</p><p><strong>Results: </strong>Comparison of Vitros PCT and KRYPTOR PCT results yielded a Deming regression slope of 1.057, intercept of -0.010, and correlation coefficient (r) of 0.994. Precision analysis demonstrated within-laboratory coefficients of variation for Vitros PCT ranging from 3.1% to 6.4%. The LoD and observed LoQ were determined as 0.007 and 0.013 ng/mL, respectively. Overall agreement between assay methods was 98.5%, 98.0%, 97.4%, and 97.8%, at PCT clinical decision cutoffs of 0.100, 0.250, 0.500, and 2.00 ng/mL, respectively, with Cohen's Kappa coefficients (κ) > 0.91. ΔPCT values ≤80% vs >80% were associated with increased 28-day-all-cause mortality (P = 0.006).</p><p><strong>Conclusions: </strong>Vitros PCT compares well with KRYPTOR PCT, showing excellent agreement at relevant clinical decision cutoffs that have been used for antibiotic decision-making and assessment of risk for sepsis progression. ΔPCT values determined with Vitros PCT were useful for evaluation of 28-day mortality risk in patients with severe sepsis.</p>","PeriodicalId":46361,"journal":{"name":"Journal of Applied Laboratory Medicine","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142814540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Back to Basics: Unraveling the Fundamentals of Lateral Flow Assays.","authors":"Valentina Restrepo-Cano, Paola García-Huertas, Arley Caraballo-Guzmán, Miryan M Sánchez-Jiménez, Giovanny Torres-Lindarte","doi":"10.1093/jalm/jfae120","DOIUrl":"https://doi.org/10.1093/jalm/jfae120","url":null,"abstract":"<p><strong>Background: </strong>Lateral flow assay (LFA) is a rapid analytical technique that has been implemented as a point-of-care approach for analyte detection. Given the rapid expansion of the use of LFA as a point-of-care testing strategy, LFA development has been subjected to extensive research, which has resulted in upgraded designs and technologies, improving levels of specificity and costs associated with manufacturing. This has allowed LFA to become an important option in rapid testing while maintaining appropriate limits of detection for accurate diagnoses.</p><p><strong>Content: </strong>This review focuses on the theoretical basis of LFA, its components, formats, multiparametric possibilities, labels, and applications. Also, challenges associated with the technique and possible solutions are explored.</p><p><strong>Summary: </strong>We explore LFA as a detection technique, its benefits, opportunities for improvement, and applications, and how challenges to its design can be approached.</p>","PeriodicalId":46361,"journal":{"name":"Journal of Applied Laboratory Medicine","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142808111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of IFCC/IUPAC Format for Specimen and Test Method Display in the Electronic Health Record Facilitates Increased Accuracy of Information.","authors":"Robert F Moran","doi":"10.1093/jalm/jfae112","DOIUrl":"https://doi.org/10.1093/jalm/jfae112","url":null,"abstract":"","PeriodicalId":46361,"journal":{"name":"Journal of Applied Laboratory Medicine","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142808112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of Integrated Clinical Pharmacogenomics Testing at an Academic Medical Center.","authors":"Claire E Knezevic, James M Stevenson, Jonathan Merran, Isabel Snyder, Grant Restorick, Christopher Waters, Mark A Marzinke","doi":"10.1093/jalm/jfae128","DOIUrl":"https://doi.org/10.1093/jalm/jfae128","url":null,"abstract":"<p><strong>Background: </strong>Pharmacogenomics has demonstrated benefits for clinical care, including a reduction in adverse events and cost savings. However, barriers in expanded implementation of pharmacogenomics testing include prolonged turnaround times and integration of results into the electronic health record with clinical decision support. A clinical workflow was developed and implemented to facilitate in-house result generation and incorporation into the electronic health record at a large academic medical center.</p><p><strong>Methods: </strong>An 11-gene actionable pharmacogenomics panel was developed and validated using a QuantStudio 12K Flex platform. Allelic results were exported to a custom driver and rules engine, and result messages, which included a diplotype and predicted metabolic phenotype, were sent to the electronic health record; an electronic consultation (eConsult) service was integrated into the workflow. Postimplementation monitoring was performed to evaluate the frequency of actionable results and turnaround times.</p><p><strong>Results: </strong>The actionable pharmacogenomics panel covered 39 alleles across 11 genes. Metabolic phenotypes were resulted alongside gene diplotypes, and clinician-facing phenotype summaries (Genomic Indicators) were presented in the electronic health record. Postimplementation, 8 clinical areas have utilized pharmacogenomics testing, with 56% of orders occurring in the outpatient setting; 22.1% of requests included at least one actionable pharmacogene, and 67% of orders were associated with a pre- or postresult electronic consultation. Mean turnaround time from sample collection to result was 4.6 days.</p><p><strong>Conclusions: </strong>A pharmacogenomics pipeline was successfully operationalized at a quaternary academic medical center, with direct integration of results into the electronic health record, clinical decision support, and eConsult services.</p>","PeriodicalId":46361,"journal":{"name":"Journal of Applied Laboratory Medicine","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142830394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Characteristics of a Calculated Index Control Method for the phi Multianalyte Assay with Algorithmic Analysis.","authors":"Radwa Ewaisha, Tifani L Flieth, Karl M Ness, Alicia Algeciras-Schimnich, Joshua A Bornhorst","doi":"10.1093/jalm/jfae110","DOIUrl":"https://doi.org/10.1093/jalm/jfae110","url":null,"abstract":"<p><strong>Background: </strong>Multianalyte assays with algorithmic analysis (MAAAs), such as the Prostate Health Index (phi), are increasingly utilized for generating disease risk scores. Currently, imprecision and bias in phi are not directly monitored by quality control (QC) assessment of the index but rather by QC assessment of individual components. This may not be adequately controlling for imprecision and bias in the calculated multicomponent phi value itself.</p><p><strong>Methods: </strong>Inter- and intra-assay phi precision was compared to precision of the individual component assays. QC measurements from total prostate-specific antigen (PSA), free PSA, and p2PSA were used to calculate a single calculated phi QC metric (PHIc). The frequency of QC failure of PHIc, relative to individual components QC by Westgard rules (13S and 22S), was determined. The effects of varying analyte component assay bias on the resulting PHIc metric were also examined.</p><p><strong>Results: </strong>Average measured phi imprecision (6.7% CV) was higher than individual phi analyte component imprecision (3.9-4.5% CV) across 2 Beckman Coulter Unicel DxI 800 instruments. A retrospective examination of PHIc QC over 84 quality control determinations was concurrently carried out for both PHIc and component assay failure patterns, which were dependent on SDs utilized for Westgard evaluation. Finally, reinforcing nonlinear changes in PHIc were observed in select cases of introduced simulated bias of individual component measurements.</p><p><strong>Conclusions: </strong>An additional calculated phi QC measure can be introduced to monitor MAAA precision/bias, and in principle calculated index controls may represent a complementary supplemental QC method that could be applied to other MAAA indices.</p>","PeriodicalId":46361,"journal":{"name":"Journal of Applied Laboratory Medicine","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142606820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling Uncertainty: The Impact of Biological and Analytical Variation on the Prediction Uncertainty of Categorical Prediction Models.","authors":"Remy J H Martens, William P T M van Doorn, Mathie P G Leers, Steven J R Meex, Floris Helmich","doi":"10.1093/jalm/jfae115","DOIUrl":"https://doi.org/10.1093/jalm/jfae115","url":null,"abstract":"<p><strong>Background: </strong>Interest in prediction models, including machine learning (ML) models, based on laboratory data has increased tremendously. Uncertainty in laboratory measurements and predictions based on such data are inherently intertwined. This study developed a framework for assessing the impact of biological and analytical variation on the prediction uncertainty of categorical prediction models.</p><p><strong>Methods: </strong>Practical application was demonstrated for the prediction of renal function loss (Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI] equation) and 31-day mortality (advanced ML model) in 6360 emergency department patients. Model outcome was calculated in 100 000 simulations of variation in laboratory parameters. Subsequently, the percentage of discordant predictions was calculated with the original prediction as reference. Simulations were repeated assuming increasing levels of analytical variation.</p><p><strong>Results: </strong>For the ML model, area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity were 0.90, 0.44, and 0.96, respectively. At base analytical variation, the median [2.5th-97.5th percentiles] percentage of discordant predictions was 0% [0%-28.8%]. In addition, 7.2% of patients had >5% discordant predictions. At 6× base analytical variation, the median [2.5th-97.5th percentiles] percentage of discordant predictions was 0% [0%-38.8%]. In addition, 11.7% of patients had >5% discordant predictions. However, the impact of analytical variation was limited compared with biological variation. AUROC, sensitivity, and specificity were not affected by variation in laboratory parameters.</p><p><strong>Conclusions: </strong>The impact of biological and analytical variation on the prediction uncertainty of categorical prediction models, including ML models, can be estimated by the occurrence of discordant predictions in a simulation model. Nevertheless, discordant predictions at the individual level do not necessarily affect model performance at the population level.</p>","PeriodicalId":46361,"journal":{"name":"Journal of Applied Laboratory Medicine","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiac Troponin to Adjudicate Subclinical Heart Failure in Diabetic Patients and a Murine Model of Metabolic Syndrome.","authors":"Hannah M Brown, Nicholas C Spies, Wentong Jia, John Moley, Sydney Lawless, Brittany Roemmich, Jonathan R Brestoff, Mark A Zaydman, Christopher W Farnsworth","doi":"10.1093/jalm/jfae091","DOIUrl":"10.1093/jalm/jfae091","url":null,"abstract":"<p><strong>Background: </strong>Cardiovascular disease, kidney health, and metabolic disease (CKM) syndrome is associated with significant morbidity and mortality, particularly from congestive heart failure (CHF). Guidelines recommend measurement of cardiac troponin (cTn) to identify subclinical heart failure (HF) in diabetics/CKM. However, appropriate thresholds and the impact from routine screening have not been elucidated.</p><p><strong>Methods: </strong>cTnI was assessed using the Abbott high sensitivity (hs)-cTnI assay in outpatients with physician-ordered hemoglobin A1c (Hb A1c) and associated with cardiac comorbidities/diagnoses, demographics, and estimated glomerular filtration rate (eGFR). Risk thresholds used in CKM staging guidelines of >10 and >12 ng/L for females and males, respectively, were used. Multivariate logistic regression was applied. hs-cTnI was assessed in a high-fat-diet induced murine model of obesity and diabetes.</p><p><strong>Results: </strong>Of 1304 patients, 8.0% females and 15.7% males had cTnI concentrations above the risk thresholds. Thirty-one (4.2%) females and 23 (4.1%) males had cTnI above the sex-specific 99% upper reference limit. A correlation between hs-cTnI and Hb A1c (R = 0.2) and eGFR (R = -0.5) was observed. hs-cTnI concentrations increased stepwise based on A1C of <5.7% (median = 1.5, IQR:1.3-1.8), 5.7%-6.4% (2.1, 2.0-2.4), 6.5%-8.0% (2.8, 2.5-3.2), and >8% (2.8, 2.2-4.3). Male sex (P < 0.001), eGFR (P < 0.001), and CHF (P = 0.004) predicted elevated hs-cTnI. Obese and diabetic mice had increased hs-cTnI (7.3 ng/L, 4.2-10.4) relative to chow-fed mice (2.6 ng/L, 1.3-3.8).</p><p><strong>Conclusion: </strong>A high proportion of outpatients with diabetes meet criteria for subclinical HF using hs-cTnI measurements. Glucose control is independently associated with elevated cTnI, a finding replicated in a murine model of metabolic syndrome.</p>","PeriodicalId":46361,"journal":{"name":"Journal of Applied Laboratory Medicine","volume":" ","pages":"913-926"},"PeriodicalIF":1.8,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142120857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}