Consensus document for lipid profile determination and reporting in Spanish clinical laboratories. What parameters should be included in a basic lipid profile?

Cardiovascular diseases (CVD) continue to be the main cause of death in our country. Adequate control of lipid metabolism disorders is a key challenge in cardiovascular prevention that is far from being achieved in real clinical practice. There is a great heterogeneity in the reports of lipid metabolism from Spanish clinical laboratories, which may contribute to its poor control. For this reason, a working group of the main scientific societies involved in the care of patients at vascular risk, has prepared this document with a consensus proposal on the determination of the basic lipid profile in cardiovascular prevention, recommendations for its realization and unification of criteria to incorporate the lipid control goals appropriate to the vascular risk of the patients in the laboratory reports.

Failure Mode and Effects Analysis (FMEA) at the preanalytical phase for POCT blood gas analysis: proposal for a shared proactive risk analysis model.

OBJECTIVES: Proposal of a risk analysis model to diminish negative impact on patient care by preanalytical errors in blood gas analysis (BGA). METHODS: Here we designed a Failure Mode and Effects Analysis (FMEA) risk assessment template for BGA, based on literature references and expertise of an international team of laboratory and clinical health care professionals. RESULTS: The FMEA identifies pre-analytical process steps, errors that may occur whilst performing BGA (potential failure mode), possible consequences (potential failure effect) and preventive/corrective actions (current controls). Probability of failure occurrence (OCC), severity of failure (SEV) and probability of failure detection (DET) are scored per potential failure mode. OCC and DET depend on test setting and patient population e.g., they differ in primary community health centres as compared to secondary community hospitals and third line university or specialized hospitals. OCC and DET also differ between stand-alone and networked instruments, manual and automated patient identification, and whether results are automatically transmitted to the patient's electronic health record. The risk priority number (RPN = SEV × OCC × DET) can be applied to determine the sequence in which risks are addressed. RPN can be recalculated after implementing changes to decrease OCC and/or increase DET. Key performance indicators are also proposed to evaluate changes. CONCLUSIONS: This FMEA model will help health care professionals manage and minimize the risk of preanalytical errors in BGA.

Clinical, Operative, and Economic Outcomes of the Point-of-Care Blood Gases in the Nephrology Department of a Third-Level Hospital.

CONTEXT.­: Point-of-care testing allows rapid analysis and short turnaround times. To the best of our knowledge, the present study assesses, for the first time, clinical, operative, and economic outcomes of point-of-care blood gas analysis in a nephrology department. OBJECTIVE.­: To evaluate the impact after implementing blood gas analysis in the nephrology department, considering clinical (differences in blood gas analysis results, critical results), operative (turnaround time, elapsed time between consecutive blood gas analysis, preanalytical errors), and economic (total cost per process) outcomes. DESIGN.­: A total amount of 3195 venous blood gas analyses from 688 patients of the nephrology department before and after point-of-care blood gas analyzer installation were included. Blood gas analysis results obtained by ABL90 FLEX PLUS were acquired from the laboratory information system. Statistical analyses were performed using SAS 9.3 software. RESULTS.­: During the point-of-care testing period, there was an increase in blood glucose levels and a decrease in pCO2, lactate, and sodium as well as fewer critical values (especially glucose and lactate). The turnaround time and the mean elapsed time were shorter. By the beginning of this period, the number of preanalytical errors increased; however, no statistically significant differences were found during year-long monitoring. Although there was an increase in the total number of blood gas analysis requests, the total cost per process decreased. CONCLUSIONS.­: The implementation of a point-of-care blood gas analysis in a nephrology department has a positive impact on clinical, operative, and economic terms of patient care.

Stability of plasma electrolytes in Barricor and PST II tubes under different storage conditions.

INTRODUCTION: Sample stability can be influenced by many different factors; evaporation and leakage from residual cells are the most relevant factors for electrolytes. During the analytical phase, samples are usually kept uncapped at room temperature. Once samples are processed, they are usually stored sealed and refrigerated. Long turnaround time and the possibility of "add-on test" need consideration for electrolyte stability. The aim of our study is to examine short-term electrolyte stability in this two-common laboratory working conditions in two different lithium heparin plasma tubes (Barricor and PST II, Becton Dickinson). MATERIALS AND METHODS: In 39 plasma samples from voluntary subjects we measured sodium (Na+), potassium (K+) and chloride (Cl-) at 6 time points since centrifugation (0h, 3h, 6h, 9h, 12h and 15h). Maximum allowable bias (clinically significant change) was based in SEQC (Sociedad Espanola de Química Clínica) recommendations; 1% for Cl-, 0.6% for Na+ and 4% for K+. RESULTS: In open room temperature tubes, clinically significant changes appeared in Na+ and Cl- after 3 hours and in K+ after 9 hours in both types of tubes. In refrigerated sealed tubes, all the analytes were clinically stable up to 12 hours in both kinds of plasma tubes. We observed a statistically significant progressive increase in K+ levels, which was less pronounced in Barricor tubes. CONCLUSION: Stability of electrolytes is compromised after 3 hours in open tubes and after 12 hours in sealed tubes.