RESUMO
Objectives Stringent quality control is an essential requisite of diagnostic laboratories to deliver consistent results. Measures used to assess the performance of a clinical chemistry laboratory are internal quality control and external quality assurance scheme (EQAS). However, the number of errors cannot be measured by the above but can be quantified by sigma metrics. The sigma scale varies from 0 to 6 with "6" being the ideal goal, which is calculated by using total allowable error (TEa), bias, and precision. However, there is no proper consensus for setting a TEa goal, and influence of this limiting factor during routine laboratory practice and sigma calculation has not been adequately determined. The study evaluates the impact of the choice of TEa value on sigma score derivation and also describes a detailed structured approach (followed by the study laboratory) to determine the potential causes of errors causing poor sigma score. Materials and Methods The study was conducted at a clinical biochemistry laboratory of a central government tertiary care hospital. Internal and external quality control data were evaluated for a period of 5 months from October 2019 to February 2020. Three drugs (carbamazepine, phenytoin, and valproate) were evaluated on the sigma scale using two different TEa values to determine significant difference, if any. Statistical Analysis Bias was calculated using the following formula: Bias% = (laboratory EQAS result - peer group mean) × 100 / peer group mean Peer group mean sigma metric was calculated using the standard equation: Sigma value = TEa - bias / coefficient of variation (CV)%. Results Impressive sigma scores (> 3 sigma) for two out of three drugs were obtained with TEa value 25, while with TEa value 15, sigma score was distinctly dissimilar and warranted root cause analysis and corrective action plans to be implemented for both valproate and carbamazepine. Conclusions The current study evidently recognizes that distinctly different sigma values can be obtained, depending on the TEa values selected, and using the same bias and precision values in the sigma equation. The laboratories should thereby choose appropriate TEa goals and make judicious use of sigma metric as a quality improvement tool.
RESUMO
Introduction Studies conducted in the recent past have demonstrated the role of inflammation, obesity and dysfunctional insulin signaling as contributing factors in the pathogenesis of acute coronary syndrome (ACS). However, pharmacological interventions targeting a single pathway have not proven useful in the long run. This indicates that a synergism occurs between the various risk factors and hence calls for a combinatorial approach. This study was planned to study the interplay, if any, between pregnancy associated plasma protein-A (PAPP-A), inflammation and adiposity in patients with ACS. Materials and methods The study was conducted in a tertiary care hospital in Delhi. The study population consisted of 128 subjects, divided into two groups. The control group consisted of 64 healthy subjects without ACS. Cases consisted of 64 subjects with angiographically proven ACS cases. PAPP-A and high sensitivity C-reactive protein (hs-CRP) were estimated by enzyme-linked immunosorbent assay (ELIZA) kits. Results The mean level of PAPP-A and hs-CRP were significantly higher in cases as compared to the controls. A positive correlation of PAPP-A was observed with hs-CRP, insulin, ApoB and Lp(a). The relative risk for ACS was 14.2 with a p value of <0.001 when all the three parameters - hs-CRP, PAPP-A and body mass index (BMI) were considered together. This was significantly higher when each risk factor was assessed standalone. Conclusions Our study results suggest a possible interplay between chronic inflammation, obesity and plaque instability among patients with ACS. This interaction can accelerate the process of plaque rupture in patients with increased BMI as compare to those patients with low/normal BMI.