Handling of lipemic samples in the clinical laboratory.

Interferences in the clinical laboratory may lead physicians misinterpret results for some biological analytes. The most common analytical interferences in the clinical laboratory include hemolysis, icterus and lipemia. Lipemia is defined as turbidity in a sample caused by the accumulation of lipoproteins, mainly very-low density lipoproteins (VLDL) and chylomicrons. Several methods are available for the detection of lipemic samples, including the lipemic index, or triglyceride quantification in serum or plasma samples, or mean corpuscular hemoglobin (MCHC) concentration in blood samples. According to the European Directive 98/79/CE, it is the responsibility of clinical laboratories to monitor the presence of interfering substances that may affect the measurement of an analyte. There is an urgent need to standardize interference studies and the way interferences are reported by manufacturers. Several methods are currently available to remove interference from lipemia and enable accurate measurement of biological quantities. The clinical laboratory should establish a protocol for the handling of lipemic samples according to the biological quantity to be tested.

Dynamic profiles and predictive values of some biochemical and haematological quantities in COVID-19 inpatients.

INTRODUCTION: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in some hospitalized patients has shown some important alterations in laboratory tests. The aim of this study was to establish the most relevant quantities associated with the worst prognosis related to COVID-19. MATERIALS AND METHODS: This was a descriptive, longitudinal, observational and retrospective study, in a cohort of 845 adult inpatients from Bellvitge University Hospital (L'Hospitalet de Llobregat, Barcelona, Spain). A multivariate regression analysis was carried out in demographic, clinical and laboratory data, comparing survivors (SURV) and non-survivors (no-SURV). A receiver operating characteristic analysis was also carried out to establish the cut-off point for poor prognostic with better specificity and sensibility. Dynamic changes in clinical laboratory measurements were tracked from day 1 to day 28 after the onset of symptoms. RESULTS: During their hospital stay, 18% of the patients died. Age, kidney disease, creatinine (CREA), lactate-dehydrogenase (LD), C-reactive-protein (CRP) and lymphocyte (LYM) concentration showed the strongest independent associations with the risk of death in the multivariate regression analysis. Established cut-off values for poor prognosis for CREA, LD, CRP and LYM concentrations were 75.0 µmol /L, 320 U/L, 80.9 mg/L and 0.69 x109/L. Dynamic profile of laboratory findings, were in agreement with the consequences of organ damage and tissue destruction. CONCLUSIONS: Age, kidney disease, CREA, LD, CRP and LYM concentrations in COVID-19 patients from the southern region of Catalonia provide important information for their prognosis. Measurement of LD has demonstrated to be very good indicator of poor prognosis at initial evaluation because of its stability over time.

Estimation of change limits (deltacheck) in clinical laboratory.

Objectives: Change limits, more commonly called delta check, are those in which a change in a patient's measured result in relation to their corresponding preceding measurement is suspected of being erroneous and should be considered as a doubtful result. The aim of this study was to provide change limits for some biochemical and haematological quantities to detect doubtful measured results and to assess its effectiveness to detect erroneous results for their application in and the standardization of the plausibility control. Methods: Change limits have been estimated for 13 biochemical and 6 haematological quantities. For each quantity, relative differences (D), expressed as a percentage between the two consecutive measured results from the same patient (from scheduled laboratory requests), were calculated. From these differences (D), the p5 and p95 percentiles of the data distribution were calculated. To assess the effectiveness of the change limits to detect laboratory errors, 43 erroneous laboratory reports, containing different biochemical and haematological quantities, were obtained from the standard laboratory plausibility control procedure. Results: From the 43 erroneous laboratory reports, 31 (72%) were due to endovenous administration errors and 12 (28%) were due to mislabeling errors. All erroneous laboratory reports were detected when the change limits of the quantities were combined and applied together. Conclusions: The best combination of quantities, which detect all the erroneous reports in the same specimen were: potassium, albumin, creatinine, glucose and haemoglobin.

Biomaker evaluation for major adverse cardiovascular event development in patients undergoing cardiac Surgery.

Objectives: The postoperative period of cardiac surgery (CS) is associated with the development of major adverse cardiovascular events (MACEs). However, the evaluation of MACE after CS by means of biomarkers is poorly developed. We aimed to evaluate postoperative biomarkers that could be associated with MACE. Methods: Two Hundred and ten patients who underwent CS were enrolled during the study period. The diagnosis of MACE was defined as the presence of at least one of the following complications: acute myocardial infarction, heart failure, stroke presented during intensive care unit (ICU) stay, and 30-day mortality after CS. High-sensitive troponin T (hs-TnT), C-reactive protein, procalcitonin, interleukin-6, and immature platelet fraction (IPF) were measured on ICU admission and after 24 h. The difference between both measurements (Δ) was calculated to assess their association with MACE. Early infected patients (n=13) after CS were excluded from final analysis. Results: The most frequent surgery was single-valve surgery (n=83; 38%), followed by coronary artery bypass graft (n=72; 34%). Postoperative MACE was diagnosed in 31 (14.8%) patients. Biomarker dynamics showed elevated values at 24 h compared with those at ICU admission in patients with MACE versus no-MACE. Multivariate analysis showed that ΔIPF (OR: 1.47; 95% CI: 1.110-1.960; p=0.008) and Δhs-TnT (OR: 1.001; 95% CI: 1.0002-1.001; p=0.008) were independently associated with MACE. Conclusions: These findings suggest that postoperative ΔIPF and Δhs-TnT may be useful biomarkers for the identification of patients at risk of MACE development.

Evaluation of the delta of immature platelet fraction as a predictive biomarker of inflammatory response after cardiac surgery.

AIMS: Cardiac surgery (CS) can induce an inflammatory response (IR) that is associated with poorer outcomes. Immature platelets are among the factors that may be associated with IR development. We aimed to evaluate whether immature platelet fraction (IPF) could be a predictive biomarker for IR and whether IPF could improve the prognosis assessment of IR for Acute Physiologic and Chronic Health Evaluation (APACHE II) and Sequential Organ Failure Assessment (SOFA) following CS. METHODS: Three-hundred and twenty-seven (327) patients who underwent CS were enrolled during the study period. IR was defined according to the need for vasopressor support (>48 hours). Perioperative variables and outcomes were registered in our database. IPF was measured immediately following CS and at 24 hours by Sysmex XN analyzer and the difference between both measurements (ΔIPF) was calculated. To assess the relationship between ΔIPF and IR, univariate and multivariate logistic regression were performed. To analyse the additive value of ΔIPF in APACHE II and SOFA scores in predicting IR, an area under the receiver operating characteristic (AUROC) curve was calculated. RESULTS: Among 327 patients included, 60 patients (18.3%) developed IR. Multivariate analysis showed ΔIPF was significantly associated with IR (OR: 1.26; 95% CI: 1.01 to 1.56; p=0.038). The combination of ΔIPF with scores improved the AUROC for IR prediction: 0.629 vs 0.728 (p=0.010) for APACHE II and 0.676 vs 0.715 (p=0.106) for SOFA. CONCLUSION: These findings suggested that ΔIPF may be a useful and low-cost biomarker for the early identification of patients at risk of IR development.

Reference interval for immature platelet fraction on Sysmex XN haematology analyser in adult population.

INTRODUCTION: The Sysmex XN-series haematology analyser has newly adopted a fluorescent channel to measure immature platelet fraction (IPF). To promote the clinical utility of this promising parameter, establishing a reliable reference interval is mandatory. According to previous studies, IPF values may be affected by the employed analyser and the ethnic background of the individual, but no differences seem to be found between individuals' genders. Therefore, this study aimed to define the reference interval for IPF in a Spanish population following Clinical and Laboratory Standard Institute (CLSI) guidelines. MATERIALS AND METHODS: A total of 153 healthy Caucasian adults from Spain met the inclusion criteria. IPF measurement was performed by means of a Sysmex XN-2000 haematology analyser. A non-parametric percentile method was used to calculate the reference intervals in accordance with CLSI guidelines. RESULTS: The obtained reference interval for IPF on the Sysmex XN-2000 was 1.6-9.6% (90% confidence intervals (CIs) were 1.5-1.8 and 9.3-11.5, respectively). No significant gender difference in IPF reference intervals was observed (P = 0.101). CONCLUSIONS: This study provides, for the first time, a reference interval for IPF using a Sysmex XN-2000 in a Spanish population, ranging from 1.6 to 9.6%. These data are needed to evaluate platelet production in several conditions such as thrombocytopenia, inflammatory states and cardiovascular diseases, as well as for future research.

Estimation of Alert and Change Limits of Haematological Quantities and its Application in the Plausibility Control.

INTRODUCTION: In the process of quality assurance of the measured values of the clinical laboratory, one of the purposes is to perform the validation of patients' measured values in the most objective way. This validation process is called plausibility control which may be defined as the set of procedures used to decide if a patient's measured value is valid according to established clinical and biological criteria. The aim of this study is to propose a model to estimate alert and change limits of measured values of the blood cell count, to be applied to detect doubtful patients' measured values. METHODS: Some alert and change limits were estimated from the emergency laboratory database of the year 2010 using different percentiles. A verification of the suitability of the proposed model was also performed. RESULTS: Most of the fractions of the measured values excluded by the alert and change limits were according to the theoretical expected. The overall fraction of the number of doubtful clinical laboratory reports ranged between 0.6 and 47.6 %. CONCLUSIONS: The proposed model helps, improves and standardizes the process of detection of doubtful measured values since they are produced objectively. These limits can also be configured in a laboratory information system letting the clinical laboratory professional staff to save time and efforts.