Introduction: The analytical phase of the total testing process is the one in which the clinical biochemist can directly intervene to improve the quality of tests reporting. The sigma metrics and Operational Process Specification (OPSpec) chart can specify to which category the laboratory belongs. Aim: To apply sigma metrics to analytical process of testing, do the root cause analysis and apply the corrective measures according to Westgard Rules to improve laboratory performance towards the quality assurances. Materials and Methods: This was a retrospective-prospective study carried out in a clinical laboratory of MKCG Medical College and Hospital, Berhampur, Odisha, India, from July 2020 to March 2021. A retrospective secondary data analysis of six months duration was carried out in a clinical chemistry laboratory with a follow-up prospective study for three months. During this period, 16 analytes were tabulated to analyse the Internal Quality Control (IQC). External Quality Control (EQC) for the same analytes were obtained on monthly basis and the sigma metrics was calculated for each analytes. For analytes with sigma value <3, appropriate measures were taken according to Westgard rules to improvise the quality of laboratory investigations. The statistical analysis of sigma metrics was performed in “R” v-3.6.3. Results: Out of total 16 analytes, three analytes at level 1 and two analytes at level 2 Quality control (QC) showed a world class performance whereas four analytes showed a poor performance at both the QC levels with sigma metrics value <3. From Quality Goal Index (QGI) and root cause analysis, the source of error was detected and corrected. Conclusion: The inaccuracy and imprecision of different parameters in the analytical phase of the testing process can be addressed by calculating the sigma metrics and do the root cause analysis. Application of corrective measures according to Westgard rule can improve the laboratory performance towards the quality assurance.
Introduction: Metabolic Syndrome (MetS) is an important public health burden associated with five-fold risk of developing Type 2 Diabetes Mellitus (T2DM) and two fold risk of Cardio Vascular Disease (CVD). Recent studies described that osteoblasts produce osteocalcin which increases insulin secretion and adiponectin production resulting in insulin sensitivity. Aim: To determine the association of serum osteocalcin with MetS and to assess the correlation of insulin resistance Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) with osteocalcin. Materials and Methods: This case-control study was carried out in the Department of Biochemistry at MKCG Medical College, Brahmapur, Odisha, India. By observing the mean and standard deviation from previous studies, with 95% Confidence Interval (CI) and 80% power of study, the sample size was calculated to be 45. Forty eight cases between 20-45 years of age meeting the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria of MetS and 50 age and sex matched healthy individuals were taken as controls. Individuals with any systemic illness or on any kind of medications were excluded from the study. Fasting blood sugar, lipid profile were measured by standard procedures. Serum osteocalcin and serum insulin was estimated by Enzyme-linked Immunosorbent Assay (ELISA) LISA SCAN READER and ROCHE e COBAS 411 electrochemiluminiscence, respectively. Statistical analysis was done in Statistical Package for the Social Sciences (SPSS) 22.0 version software. Results: Serum osteocalcin was found to be lower in cases as compared to controls (7.74±4.62 ng/mL and 23.24±9.74 ng/mL) respectively. Osteocalcin was also found to be significantly negatively correlated with HOMA-IR, Waist Circumference (WC), triglyceride and fasting blood sugar in cases with (r=-0.322, p=0.025), (r=-0.519, p<0.001), (r=-0.401, p=0.005), (r=-0.539, p<0.001), respectively and also in controls with (r=-0.494, p<0.001), (r=-0.176, p=0.245), (r=-0.398, p<0.05), (r=-0.141, p<0.05), respectively. Conclusion: Serum osteocalcin being negatively correlated with insulin resistance may have therapeutic role in prevention of MetS which may be substantiated with further study.
Introduction: During summer 2015, we had observed a significant rise in incidence of hypokalemia in comparison to winter 2014-2015. We speculated these findings might have occurred as a result of delay in centrifugation during which the samples were exposed to the high ambient temperature. So we took up the study to find out whether reducing the time period between venipuncture and centrifugation can be of any help to reduce the magnitude of incidence of pseudohypokalemia during summer months. Materials and Methods: We reduced the time between venipuncture and serum separation to less than thirty minutes for all the samples received at the laboratory in the year 2015-2016. Estimation of serum potassium was done within thirty minutes of serum separation. Result: In the year 2014-2015 the difference between proportion of hypokalemia in summer and winter was statistically significant (p<0.0001) whereas the difference in proportion of hypokalemia in 2015-2016 between summer and winter was not statistically significant (p<0.897). Conclusion:The laboratory people should be aware of the fact that delays in sample centrifugation and estimation of serum potassium results in spuriously low serum potassium value at high ambient temperature. Reducing the time of serum separation and estimation of serum potassium to within one hour can solve the problem of pseudohypokalemia and thereby improve the patient management.
Errors in laboratory are heterogeneous in nature as it involves various complex procedures and a variety of persons preforming all the processes, starting from ordering of tests to reporting of result to its influence on ultimate patient care. The core job of a laboratory is to produce the correct test result. If we can't get the test results right, then we aren't doing our core job. It's our profession to know all the details of testing and instrumentation and quality control. It's our profession to assure that test results are correct. Improvements need not be only at "pre" or "post" or "analytical" -it should be at all three stages, as the consequence of error in any of the stage is the same: poor patient care. No error is worse than the other. We must make efforts on all fronts. Even if this means making small improvements in each area, a unified improvement effort will achieve better test results and better patient care than narrow efforts in either the pre-, post-or analytical area. To have a uniform consensus, the laboratories should have certain quality indicators to have control over the procedures that tend to generate errors.
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