Journal of Laboratory Medicine最新文献

{"title":"Assessing the stability of uncentrifuged serum and plasma analytes at various post-collection intervals","authors":"Atiqah Mokhsin, Poonaresi Subramaniam, Sivasooriar Sivaneson, Nelson Nheu, Gobhy Ramaloo, Azana S. Hanifah, Sumitha B. Mahathevan, Mohanaraja Nadarajah, Gayathiri Sampasivam, Aletza Mohd Ismail, Thuhairah Abdul Rahman","doi":"10.1515/labmed-2024-0062","DOIUrl":"https://doi.org/10.1515/labmed-2024-0062","url":null,"abstract":"Objectives Our study aimed to assess the stability of 26 biochemistry analytes in serum or plasma samples separated from blood samples centrifuged at different time intervals after collection, simulating sample transport via despatch delivery systems. Methods Blood from forty-one volunteers were collected using five serum separator tubes (SST) and five fluoride oxalate tubes (FOT) for each volunteer following written informed consent. Each of the five tubes in both groups of SST and FOT was centrifuged at one of the time intervals: 0.5 h, 4 h, 8 h, 12 and 24 h after collection. These samples were left standing prior to centrifugation at room temperature. We calculated the percentage difference for each analyte between the 0.5 h and other time intervals to assess analyte stability. The percentage difference was compared to the desirable specification for bias and reference change value (RCV). Results Mean concentration of serum potassium showed a significant increase in the percentage RCV after 8 h, while CKMB showed an increase after 12 h of delayed centrifugation compared to the baseline (0.5 h). There were no significant percentage RCV for the other analytes at all timelines. Conclusions Serum potassium and CKMB were stable up to 8 and 12 h of delayed centrifugation respectively whilst all other analytes appear stable up to 24 h, suggesting that sample transport delay of up to 8 h, with the condition that room temperature is maintained, may not have a significant impact on accuracy of the biochemistry/immunochemistry test results.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":"5 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Gaussian mixture modelling can help to verify reference intervals from laboratory data with a high proportion of pathological values","authors":"Georg Hoffmann, Nina Allmeier, Modupe Kuti, Stefan Holdenrieder, Inga Trulson","doi":"10.1515/labmed-2024-0118","DOIUrl":"https://doi.org/10.1515/labmed-2024-0118","url":null,"abstract":"Objectives Although there are several indirect methods that can be used to verify reference limits, they have a common weakness in that they assume a low proportion of pathological values. This paper investigates whether a Gaussian decomposition algorithm can identify the non-pathological fraction even if it is not the main subset of mixed data. Methods All investigations are carried out in the R programming environment. The mclust package is used for Gaussian mixture modelling via the expectation maximization (EM) algorithm. For right-skewed distributions, logarithms of the original values are taken to approximate the Gaussian model. We use the Bayesian information criterion (BIC) for evaluation of the results. The reflimR and refineR packages serve as comparison procedures. Results We generate synthetic data mixtures with known normal distributions to demonstrate the feasibility and reliability of our approach. Application of the algorithm to real data from a Nigerian and a German population produces results, which help to interpret reference intervals of reflimR and refineR that are obviously too wide. In the first example, the mclust analysis of hemoglobin in Nigerian women supports the medical hypothesis that an anemia rate of more than 50 % leads to falsely low reference limits. Our algorithm proposes various scenarios based on the BIC values, one of which suggests reference limits that are close to published data for Nigeria but significantly lower than those established for the Caucasian population. In the second example, the standard statistical analysis of creatine kinase in German patients with predominantly cardiac diseases yields a reference interval that is clearly too wide. With mclust we identify overlapping fractions that explain this false result. Conclusions Gaussian mixture modelling does not replace standard methods for reference interval estimation but is a valuable adjunct when these methods produce discrepant or implausible results.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":"60 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using machine learning techniques for exploration and classification of laboratory data","authors":"Inga Trulson, Stefan Holdenrieder, Georg Hoffmann","doi":"10.1515/labmed-2024-0100","DOIUrl":"https://doi.org/10.1515/labmed-2024-0100","url":null,"abstract":"Objectives The study aims to acquaint readers with six widely used machine learning (ML) techniques (Principal Component Analysis (PCA), Uniform Manifold Approximation and Projection (UMAP), k-means, hierarchical clustering and the decision tree models (rpart and random forest)) that might be useful for the analysis of laboratory data. Methods Utilizing a recently validated data set from lung cancer diagnostics, we investigate how ML can support the search for a suitable tumor marker panel for the differentiation of small cell (SCLC) and non-small cell lung cancer (NSCLC). Results The ML techniques used here effectively helped to gain a quick overview of the data structures and provide initial answers to the clinical questions. Dimensionality reduction techniques such as PCA and UMAP offered insightful visualization and impression of the data structure, suggesting the existence of two tumor groups with a large overlap of largely inconspicuous values. This impression was confirmed by a cluster analysis with the k-means algorithm, indicative of unsupervised learning. For supervised learning, decision tree models like rpart or random forest demonstrated their utility in differential diagnosis of the two tumor types. The rpart model, which constructs binary decision trees based on the recursive partitioning algorithm, suggests a tree involving four serum tumor markers (STMs), which were confirmed by the random forest approach. Both highlighted pro-gastrin-releasing peptide (ProGRP), neuron specific enolase (NSE), cytokeratin-19 fragment (CYFRA 21-1) and cancer antigen (CA) 72-4 as key tumor markers, aligning with the outcomes of the initial statistical analysis. Cross-validation of the two proposals showed a higher area under the receiver operating characteristic (AUROC) curve of 0.95 with a 95 % confidence interval (CI) of 0.92–0.97 for the random forest model compared to an AUROC curve of 0.88 (95 % CI: 0.83–0.93). Conclusions ML can provide a useful overview of inherent medical data structures and distinguish significant from less pertinent features. While by no means replacing human medical and statistical expertise, ML can significantly accelerate the evaluation of medical data, supporting a more informed diagnostic dialogue between physicians and statisticians.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":"27 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Serum LDH and its isoenzymes (LDH2 and LDH5) associated with predictive value for refractory mycoplasma pneumoniae pneumonia in children","authors":"Jun Lv, Yu Wan, Fei Jiang, Fei Fan","doi":"10.1515/labmed-2024-0067","DOIUrl":"https://doi.org/10.1515/labmed-2024-0067","url":null,"abstract":"Objectives To contrast the level of lactate dehydrogenase (LDH) and its isoenzymes between general mycoplasma pneumoniae pneumonia (GMPP) and refractory mycoplasma pneumoniae pneumonia (RMPP) groups and to investigate their predictive value for RMPP in children. Methods A total of 160 children with GMPP and 100 children with RMPP were enrolled from August 2022 to April 2023 in our hospital. Serum LDH and its isoenzymes levels were assessed between the two groups. LDH and its isoenzymes were entered into multivariate logistic regression analysis to identify risk factors for RMPP, and variables with significance were used to analyze their diagnostic values for RMPP. ROC curves were drawn, and the AUC was calculated, with sensitivity and specificity obtained. Results Children with RMPP displayed more blatant inflammatory responses as well as more alarming imaging findings compared to those with GMPP. The levels of serum LDH and its isoenzymes in children with RMPP were significantly higher than those in children with GMPP. In the multivariate logistic regression analysis, LDH (OR=1.02, p<0.001), LDH2 (OR=1.05, p=0.010) and LDH5 (OR=1.04, p˂0.001) showed statistically significant differences. When the cut-off values were 372.5, 97.46, and 49.29 U/L respectively, the AUCs of LDH (sensitivity=0.80, specificity=0.89), LDH2 (sensitivity=0.83, specificity=0.71), and LDH5 (sensitivity=0.82, specificity=0.72) predicting RMPP were 0.91, 0.81, and 0.82, respectively. The AUC of [LDH + LDH5] (0.92) was the highest. Conclusions Serum LDH, LDH2, and LDH5 have good diagnostic values for RMPP and possess the potential to be biological markers in children with RMPP. And the predictive value is higher when used in combination.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":"22 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of two different technologies measuring the same analytes in view of the In Vitro Diagnostica Regulation (IVDR)","authors":"Noel Stierlin, Andreas Hemmerle, Karin Jung, Jörg Thumfart, Martin Risch, Lorenz Risch","doi":"10.1515/labmed-2024-0052","DOIUrl":"https://doi.org/10.1515/labmed-2024-0052","url":null,"abstract":"Objectives This study systematically compared the performance and comparability of two medical laboratory analytical instruments, the conventional wet chemistry analyzer (cobas) and the dry slide technology (Vitros), across various clinical chemistry assays. Methods The evaluation focused on assessing imprecision, inaccuracy, recovery, and method comparison using leftover patient serum samples. Results The results indicated good to very good agreement for most clinical chemistry analytes, with larger differences observed for comparison of serum patient samples on albumin and protein. Conclusions Understanding and acknowledging method-specific variations, are crucial for accurate result interpretation in clinical laboratories. This study contributes valuable insights to ongoing discussions on method standardization.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":"187 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Direct, age- and gender-specific reference intervals: applying a modified M-estimator of the Yeo-Johnson transformation to clinical real-world data","authors":"Tobias Ueli Blatter, Christos Theodoros Nakas, Alexander Benedikt Leichtle","doi":"10.1515/labmed-2024-0076","DOIUrl":"https://doi.org/10.1515/labmed-2024-0076","url":null,"abstract":"Objectives Reference intervals for the general clinical practice are expected to cover non-pathological values, but also reflect the underlying biological variation present in age- and gender-specific patient populations. Reference intervals can be inferred from routine patient data measured in high capacity using parametric approaches. Stratified reference distributions are obtained which may be transformed to normality via e.g. a Yeo-Johnson transformation. The estimation of the optimal transformation parameter for Yeo-Johnson through maximum likelihood can be highly influenced by the presence of outlying observations, resulting in biased reference interval estimates. Methods To reduce the influence of outlying observations on parametric reference interval estimation, a reweighted M-estimator approach for the Yeo-Johnson (YJ) transformation was utilised to achieve central normality in stratified reference populations for a variety of laboratory test results. The reweighted M-estimator for the YJ transformation offers a robust parametric approach to infer relevant reference intervals. Results The proposed method showcases robustness up to 15 % of outliers present in routine patient data, highlighting the applicability of the reweighted M-estimator in laboratory medicine. Furthermore, reference intervals are personalised based on the patients’ age and gender for a variety of analytes from routine patient data collected in a tertiary hospital, robustly reducing the dimensionality of the data for more data-driven approaches. Conclusions The method shows the advantages for estimating reference intervals directly and parametrically from routine patient data in order to provide expected reference ranges. This approach to locally inferred reference intervals allows a more nuanced comparison of patients’ test results.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":"43 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Standardization with zlog values improves exploratory data analysis and machine learning for laboratory data","authors":"Amani Al-Mekhlafi, Sandra Klawitter, Frank Klawonn","doi":"10.1515/labmed-2024-0051","DOIUrl":"https://doi.org/10.1515/labmed-2024-0051","url":null,"abstract":"Objectives In the context of exploratory data analysis and machine learning, standardization of laboratory results is an important pre-processing step. Variable proportions of pathological results in routine datasets lead to changes of the mean (<jats:italic>µ</jats:italic>) and standard deviation (<jats:italic>σ</jats:italic>), and thus cause problems in the classical z-score transformation. Therefore, this study investigates whether the zlog transformation compensates these disadvantages and makes the results more meaningful from a medical perspective. Methods The results presented here were obtained with the statistical software environment R, and the underlying data set was obtained from the UC Irvine Machine Learning Repository. We compare the differences of the zlog and z-score transformation for five different dimension reduction methods, hierarchical clustering and four supervised classification methods. Results With the zlog transformation, we obtain better results in this study than with the z-score transformation for dimension reduction, clustering and classification methods. By compensating the disadvantages of the z-score transformation, the zlog transformation allows more meaningful medical conclusions. Conclusions We recommend using the zlog transformation of laboratory results for pre-processing when exploratory data analysis and machine learning techniques are applied.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":"39 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic value of anti-hexokinase 1 and anti-kelch-like 12 antibodies in primary biliary cholangitis patients","authors":"Min Yang, Chao Hu, Jun Huang, Ying Fu, Qi Zhang, Yulan Cheng, Jie Lu, Guiling Li, Jun Zhang","doi":"10.1515/labmed-2023-0127","DOIUrl":"https://doi.org/10.1515/labmed-2023-0127","url":null,"abstract":"Objectives Anti-mitochondrial antibody (AMA) is not always present in patients with primary biliary cholangitis (PBC). We aimed to determine the additional value of anti-hexokinase 1 (anti-HK1) and anti-kelch-like 12 (anti-KLHL12) antibody in PBC and analyzed the biochemical and immunological parameters of 212 subjects, including PBC patients and healthy controls. Methods Serum anti-gp210 and sp100 antibodies were determined by an immunoblotting test (IBT). Enzyme-linked immunosorbent assay (ELISA) was employed to evaluate anti-HK1 and anti-KLHL12. The diagnostic value of anti-HK1 and anti-KLHL12 to PBC was analyzed by constructing a receiver operating characteristic (ROC) curve. Results ROC analyses didn’t show a very good performance of serum anti-HK1 for PBC diagnosis; the AUC was 0.664 with a sensitivity of 53.3 % and a specificity of 79.2 %. Regarding anti-KLHL12, ROC analysis yielded an AUC of 0.626, with a sensitivity of 45.7 % and a specificity of 93.8 %. For AMA-negative PBC patients, the AUC increased to 0.790 for KLHL12, and 0.708 for HK1. AMA combined with anti-HK1 or anti-KLHL12 antibody significantly improved the diagnostic sensitivity of PBC from 82 to about 95 %, respectively. In AMA-negative PBC patients, the sensitivities for anti-HK1 (62.50 %) and anti-KLHL12 (75 %) antibodies were higher than for anti-gp210 (37.5 %) and anti-sp100 antibody (43.75 %). When these four antibodies were combined, the overall sensitivity increased to 87.5 %. Conclusions The determination of anti-HK1 and anti-KLHL12 facilitates the diagnosis of PBC, particularly in AMA-negative patients. Adding anti-HK1 and anti-KLHL12 antibodies to clinical detection enables early diagnosis and timely treatment, potentially improving patient prognosis.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":"21 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140938301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attention should be paid to false-positive results due to heterophilic antibodies interfering with Abbott high-sensitivity cardiac troponin I assay","authors":"Weiping Liu, Xia Long, Lulu Chen, Kailan Yang","doi":"10.1515/labmed-2023-0131","DOIUrl":"https://doi.org/10.1515/labmed-2023-0131","url":null,"abstract":"Objectives In recent years, chemiluminescent microparticle immunoassay (CMIA) has been widely used for determination of high-sensitivity troponin I (hs-cTnI). However, a CMIA analysis is usually affected by the presence of some endogenous or exogenous substances. This case-report aims to unveil the essence of the reoccurrence of false-positive results due to heterophilic antibodies interference with Abbott high-sensitivity cardiac troponin I assay, although the assay method applied a chimeric antibody. Case presentation A 28-year-old female misdiagnosed with myocarditis due to falsely elevated hs-cTnI with an initial test result of 595.0 ng/L considered as critical value was reported. And the false critical value of hs-cTnI reoccurred five times after admission. The heterophilic blocking tube (HBT) procedure caused a decrease in troponin concentrations within the reference values, which suggests the presence of interference from heterophilic antibodies. Conclusions It requires a close and strong collaboration between clinicians and laboratorians to manage the similar case on the interference from heterophilic antibodies. To prevent false-positive results caused by interferences from being used in clinical practice, the clinicians are suggested to contact the laboratorians whenever the clinical picture, historical data and laboratory values are not conclusive.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":"68 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epidemiology of Mycoplasma pneumoniae in children with acute respiratory infections in Hangzhou during January 2021 to June 2023","authors":"Lin Chen, Shuangshuang Huang, Hao Wang, Fengqing Cai, Zhaoyang Peng, Shanshan Wang","doi":"10.1515/labmed-2024-0014","DOIUrl":"https://doi.org/10.1515/labmed-2024-0014","url":null,"abstract":"Objectives <jats:italic>Mycoplasma pneumoniae</jats:italic> (MP) is known to be a common pathogen causing human respiratory infections. On December 7, 2022, the Chinese government announced 10 new measures of Prevention and Control of COVID-19, marking the onset of the post-COVID-19 era. This study aimed to investigate the epidemiological characteristics of Mycoplasma pneumoniae (MP) infections among children from January 2021 to June 2023. Methods Children with respiratory tract infection were enrolled in the study with fever and one or more respiratory symptoms. A serological diagnosis was confirmed with MP IgM antibodies. Results A total of 18,763 patients were enrolled, of whom 4,867 cases were MP-positive, resulting in a positivity rate of 25.9 %. The MP positivity rate increased annually, with 18.6 , 26.7, and 33.2 % in 2021, 2022, and 2023, respectively. The main disease type of MP infection was Mycoplasma pneumoniae pneumonia (MPP), with 74.0 , 87.8, and 86.4 % in 2021, 2022, and 2023, respectively. Higher positivity rates were concentrated in children aged 6 years and older, and the positivity rate in children under 1 year of age in 2023 is the largest increase among all age groups. Conclusions The positivity rate of MP increased significantly after the adjustment of COVID-19 prevention and control in China, and the most significant increase was seen in the infant group. Effective prevention and control measures should be implemented to reduce the prevalence of MP infection among children aged 6 years older and the infant group (&lt;1 year).","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":"48 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140562012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}