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1.
Clin Chem Lab Med ; 2024 Jul 12.
Artigo em Inglês | MEDLINE | ID: mdl-38987249

RESUMO

OBJECTIVES: This study investigates the application of 15 Quality Indicators (QIs) in clinical laboratories in Fujian Province, China, from 2018 to 2023. It identifies the main causes of laboratory errors and explores issues in the application of QIs, providing a reference for establishing provincial state-of-the-art and operational quality specifications (QSs). METHODS: All clinical laboratories in Fujian Province were organized to submit general information and original QIs data through the online External Quality Assessment (EQA) system of the National Clinical Laboratory Center (NCCL) for a survey of 15 QIs. Data from 2018 to 2023 were downloaded for statistical analysis, and the current QSs for the 15 QIs in Fujian Province were compared and analyzed with those published by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Working Group on Laboratory Errors and Patient Safety (WG-LEPS). RESULTS: QIs data from 542 clinical laboratories were collected. The survey on data sources showed that the number of laboratories recording QIs data using Laboratory Information Systems (LIS) increased annually, but the growth was modest and the proportion was less than 50 %. Among the laboratories using LIS to record QIs data, 133 continuously participated in this survey for six years, reporting different QIs. Over the six years, all reported QIs showed significant improvement or at least remained stable. The best median Sigma (σ) metrics were for the percentage of critical values notification and timely critical values notification, reaching 6σ, followed by the percentage of incorrect laboratory reports, with σ metrics ranging from 4.9σ to 5.1σ. In contrast, the percentage of tests covered by internal quality control (IQC) (1.5σ-1.7σ) and inter-laboratory comparison (0.1σ) remained consistently low. Compared to the QSs published by IFCC WG-LEPS, the QSs for the 15 QIs in Fujian Province in 2023 were stricter or roughly equivalent, except for the percentage of incorrect laboratory reports (Fujian Province: 0-0.221, IFCC WG-LEPS: 0-0.03). CONCLUSIONS: 1. The application of QIs has significantly improved the quality of testing in clinical laboratories in Fujian Province, but the percentage of tests covered by IQC and inter-laboratory comparison remain low; 2. Effective application of QIs requires the establishment of comprehensive LIS, unified calculation standards, and other supporting measures.

2.
Access Microbiol ; 6(2)2024.
Artigo em Inglês | MEDLINE | ID: mdl-38482363

RESUMO

Background: Rhodococcus equi is one of the most important causes of zoonotic infections from grazing animals. It poses a particular risk to immunocompromised individuals, including those who are undergoing long-term immunosuppressive therapy. Case presentation: We report a case of Rhodococcus equi infection in a 65-year-old man with a medical history of diabetes, hypertension, and Adult Still's Disease, currently taking long-term hormone therapy. The non-human immunodeficiency virus (HIV)-infected patient had blood, lung tissue, and sputum samples infected with Rhodococcus equi. His condition initially failed to improve despite multiple therapies, including vancomycin and meropenem. Although his symptoms improved after shifting his antibiotics to cover for the causative agent, he did not completely recover upon hospital discharge. Conclusions: In recent years, the number of Rhodococcus equi cases has increased. This report describes a lethal case of Rhodococcus equi infection in a patient without HIV.

3.
Heliyon ; 10(1): e23583, 2024 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-38173531

RESUMO

Coronavirus disease 2019 (COVID-19) is associated with immune dysregulation and cytokine storm. It is essential to explore the immune response characteristics of peripheral circulation in COVID-19 patients to reveal pathogenesis and predict disease progression. In this study, the levels of total immunoglobulins (IgG, IgM, IgA), complement (C3, C4),lymphocyte subsets (CD3+ cell,CD4+ cell,CD8+ cell, NK cell, CD19+ cell and CD45+ cell) and cytokines (IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-17, IL-12p, IL-1ß, TNF-α, IFN-α and IFN-γ) were retrospectively analyzed in COVID-19 patients. A total of 513 patients were enrolled in this study, cases were distributed according to clinical status as mild or moderate (n = 212), severe survivors (n = 197) and severe non-survivors (n = 104). IL-6, IL-8, IL-10 and IFN-γ were increased in severe patients compared with non-severe patients, despite decreased CD45+ cell, CD3+ cell, CD4+ cell, CD8+ cell, CD19+ cell, and NK cell. Compared with severe survivors, the levels of L-6, IL-8 and IL-10 in non-survivors increased significantly, and levels of C3, CD45+ cell, CD3+ cell,CD4+ cell,CD8+ cell, and NK cell decreased. Moreover, age, IL-8, IL-10, CD8+cells and NK cell were independent risk factors for the severity of COVID-19. Multivariable regression showed increasing odds ratio of in-hospital death associated with tumor, older age, higher IL-8 level, and decreasing odds ratio of in-hospital death associated with increased levels of CD8+cell and NK cell. Finally, patients with tumor, or high IL-6 or high IL-10 expression and lower CD8+ or lower NK levels exhibited a significantly shorter survival time. In conclusion, our study provides findings of the immunological characteristics associated with disease severity to predict the progression of COVID-19. The immune inflammation factors, such as IL-6, IL-8, IL-10, CD8+ cell and NK cell, could serve as excellent biomarkers for monitoring or predicting COVID-19 progression therapeutic to COVID-19 patients.

4.
Front Immunol ; 15: 1394429, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38799467

RESUMO

Background: The severity, symptoms, and outcome of COVID-19 is thought to be closely linked to how the virus enters host cells. This process involves the key roles of angiotensin-converting enzyme 2 (ACE2) and the Tyrosine protein kinase receptor UFO (AXL) receptors. However, there is limited research on the circulating levels of ACE2 and AXL and their implications in COVID-19. Methods: A control group of 71 uninfected individuals was also included in the study. According to the Guidance for Corona Virus Disease 2019 (10th edition), a cohort of 358 COVID-19 patients were categorized into non-severe and severe cases. Serum ACE2/AXL levels in COVID-19 patients were detected by enzyme-linked immunosorbent assay (ELISA) at different time points post-COVID-19 infection, including days 0-7, 8-15, 31-179 and >180 days. Serum SARS-CoV-2 IgG/IgM antibodies in COVID-19 patients at the same intervals were assessed by using an iFlash 3000 Chemiluminescence Immunoassay Analyzer. The receiver operating characteristic (ROC) curves were used to assess the diagnostic value of the biological markers, and the association between laboratory parameters and illness progression were explored. Results: Compared with the uninfected group, the levels of ACE2 and AXL in the COVID-19 group were decreased, and the SARS-COV-2 IgG level was increased. AXL (AUC = 0.774) demonstrated a stronger predictive ability for COVID-19 than ACE2. In the first week after infection, only the level of AXL was statistically different between severe group and non-severe group. After first week, the levels of ACE2 and AXL were different in two groups. Moreover, in severe COVID-19 cases, the serum ACE2, AXL, and SARS-COV-2 IgM levels reached a peak during days 8-15 before declining, whereas serum SARS-COV-2 IgG levels continued to rise, reaching a peak at day 31-180 days before decreasing. In addition, the AXL level continued to decrease and the SARS-COV-2 IgG level continued to increase in the infected group after 180 days compared to the uninfected group. Conclusions: The levels of serum ACE2 and AXL correlate with COVID-19 severity. However, AXL can also provide early warning of clinical deterioration in the first week after infection. AXL appears to be a superior potential molecular marker for predicting COVID-19 progression.


Assuntos
Enzima de Conversão de Angiotensina 2 , Receptor Tirosina Quinase Axl , Biomarcadores , COVID-19 , Progressão da Doença , Proteínas Proto-Oncogênicas , Receptores Proteína Tirosina Quinases , SARS-CoV-2 , Humanos , COVID-19/sangue , COVID-19/imunologia , COVID-19/diagnóstico , Receptores Proteína Tirosina Quinases/sangue , Receptores Proteína Tirosina Quinases/imunologia , Masculino , Proteínas Proto-Oncogênicas/sangue , Feminino , Enzima de Conversão de Angiotensina 2/sangue , Biomarcadores/sangue , Pessoa de Meia-Idade , SARS-CoV-2/imunologia , Adulto , Idoso , Anticorpos Antivirais/sangue , Imunoglobulina G/sangue , Índice de Gravidade de Doença , Imunoglobulina M/sangue , Curva ROC
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