Biochemia Medica最新文献

The acquired hemophilia A (AHA) is a life-threatening condition. The incidence of AHA is extremely low, which requires a multidisciplinary approach to diagnosis and treatment. This is case report of 73-year-old man who presented with AHA secondary to severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) pneumonia. The patient had extensive skin bleeding and hematomas. In the coagulation screening tests activated partial thromboplastin time (APTT) was prolonged with normal prothrombin time (PT), which was indication for further investigation. The APTT in a mixing study with normal plasma did not correct so clotting factors inhibitors were suspected. With signs of bleeding, extremely low factor VIII (FVIII) activity (2%) and presence of FVIII inhibitors, AHA was diagnosed and treatment initiated. Patient was treated with factor eight inhibitor bypassing agent (FEIBA) for three days, followed by long-term corticosteroid and cyclophosphamide therapy. Malignant and autoimmune diseases as the most common causes of AHA were ruled out. The patient had a good response to therapy with gradual normalization of APTT and FVIII activity. To the best of our knowledge, the present case is the first reported case of de novo AHA after SARS-CoV-2 pneumonia. The diagnosis of AHA should be suspected in a patient with bleeding into the skin and mucous membranes without a previous personal and family history of bleeding, and with isolated prolonged APTT. It is important to investigate any isolated prolongation of APTT in cooperation with clinical laboratory experts.

Introduction: The aim of the study was to determine the current state of laboratory's extra-analytical phase performance by calculating preanalytical and postanalytical phase quality indicators (QIs) and sigma values and to compare obtained data according to desired quality specifications and sigma values reported by The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Working Group - Laboratory errors and Patient Safety.

Materials and methods: Preanalytical and postanalytical phase data were obtained through laboratory information system. Rejected samples in preanalytical phase were grouped according to reasons for rejection and frequencies were calculated both monthly and for 2019. Sigma values were calculated according to "short term sigma" table.

Results: The number of rejected samples in laboratory was 643 out of 191,831 in 2019. Total preanalytical phase rejection frequency was 0.22%. According to the reasons for rejection, QIs and sigma values were: "Samples with excessive transportation time": 0.0036 and 5.47; "Samples collected in wrong container" 0.02 and 5.11. In December, QIs and sigma values were: "Samples with excessive transportation time": 0.01 and 5.34; "Samples collected in wrong container": 0.03 and 4.98. The postanalytical QIs and sigma values were: "Reports delivered outside the specified time": 0.34 and 4.21; "Turn around time of potassium": 56 minute and 3.84, respectively. There were no errors in "Critical values of inpatients and outpatients notified after a consensually agreed time".

Conclusions: Extra-analytical phase was evaluated by comparing it with the latest quality specifications and sigma values which will contribute to improving the quality of laboratory medicine.

Introduction: Coronavirus disease 2019 (COVID-19) is known to induce robust antibody response in most of the affected individuals. The objective of the study was to determine if we can harvest the test sensitivity and specificity of a commercial serologic immunoassay merely based on the frequency distribution of the SARS-CoV-2 immunoglobulin (Ig) G concentrations measured in a population-based seroprevalence study.

Materials and methods: The current study was conducted on a subset of a previously published dataset from the canton of Geneva. Data were taken from two non-consecutive weeks (774 samples from May 4-9, and 658 from June 1-6, 2020). Assuming that the frequency distribution of the measured SARS-CoV-2 IgG is binormal (an educated guess), using a non-linear regression, we decomposed the distribution into its two Gaussian components. Based on the obtained regression coefficients, we calculated the prevalence of SARS-CoV-2 infection, the sensitivity and specificity, and the most appropriate cut-off value for the test. The obtained results were compared with those obtained from a validity study and a seroprevalence population-based study.

Results: The model could predict more than 90% of the variance observed in the SARS-CoV-2 IgG distribution. The results derived from our model were in good agreement with the results obtained from the seroprevalence and validity studies. Altogether 138 of 1432 people had SARS-CoV-2 IgG ≥ 0.90, the cut-off value which maximized the Youden's index. This translates into a true prevalence of 7.0% (95% confidence interval 5.4% to 8.6%), which is in keeping with the estimated prevalence of 7.7% derived from our model. Our model can provide the true prevalence.

Conclusions: Having an educated guess about the distribution of test results, the test performance indices can be derived with acceptable accuracy merely based on the test results frequency distribution without the need for conducting a validity study and comparing the test results against a gold-standard test.