Objective:To assess the validity of the International Classification of Disease (ICD) codes for identifying patients with dyslipidemia in electronic medical record (EMR) dataMethods:The EMRs of patients receiving primary care in St. John’s, Newfoundland and Labrador (NL), Canada, were retrieved from the Canadian Primary Care Sentinel Surveillance Network database. International Classification of Disease codes were first compared with laboratory lipid data as an independent criterion standard, and next with a “comprehensive criterion standard,” defined as any existence of abnormal lipid test, lipid-lowering medication record, or dyslipidemia ICD codes. The ability of ICD coding alone or combined with other components was evaluated against the two criterion standards using receiver operating characteristic (ROC) analysis, sensitivity, specificity, negative predictive value (NPV) and Kappa agreement. (No specificity was reported for the comparison of ICD codes against the comprehensive criterion standard as this naturally leads to 100% specificity.)Results:The ICD codes led to a poor outcome when compared with the serum lipid levels (sensitivity, 27%; specificity, 76%; PPV, 71%; NPV, 33%; Kappa, 0.02; area under the receiver operating characteristic curve (AUC), 0.51) or with the comprehensive criterion standard (sensitivity, 32%; NPV, 25%; Kappa, 0.15; AUC, 66%). International Classification of Disease codes combined with lipid-lowering medication data also resulted in low sensitivity (51.2%), NPV (32%), Kappa (0.28), and AUC (75%). The addition of laboratory lipid levels to ICD coding marginally improved the algorithm (sensitivity, 94%; NPV, 79%; Kappa, 0.85; AUC, 97%).Conclusions:The use of ICD coding, either alone or in combination with laboratory data or lipid-lowering medication records, was not an accurate indicator in identifying dyslipidemia.

No abstract

The objective of this study was to define the optimal algorithm to identify patients with dyslipidemia using electronic medical records (EMRs). EMRs of patients attending primary care clinics in St. John's, Newfoundland and Labrador (NL), Canada during 2009-2010, were studied to determine the best algorithm for identification of dyslipidemia. Six algorithms containing three components, dyslipidemia ICD coding, lipid lowering medication use, and abnormal laboratory lipid levels, were tested against a gold standard, defined as the existence of any of the three criteria. Linear discriminate analysis, and bootstrapping were performed following sensitivity/specificity testing and receiver's operating curve analysis. Two validating datasets, NL records of 2011-2014, and Canada-wide records of 2010-2012, were used to replicate the results. Relative to the gold standard, combining laboratory data together with lipid lowering medication consumption yielded the highest sensitivity (99.6%), NPV (98.1%), Kappa agreement (0.98), and area under the curve (AUC, 0.998). The linear discriminant analysis for this combination resulted in an error rate of 0.15 and an Eigenvalue of 1.99, and the bootstrapping led to AUC: 0.998, 95% confidence interval: 0.997-0.999, Kappa: 0.99. This algorithm in the first validating dataset yielded a sensitivity of 97%, Negative Predictive Value (NPV) = 83%, Kappa = 0.88, and AUC = 0.98. These figures for the second validating data set were 98%, 93%, 0.95, and 0.99, respectively. Combining laboratory data with lipid lowering medication consumption within the EMR is the best algorithm for detecting dyslipidemia. These results can generate standardized information systems for dyslipidemia and other chronic disease investigations using EMRs.

Situs inversus, an uncommon mirror-image reversal of the major visceral and thoracic organs, is seldom of medical significance. However, the recognition of their unique anatomy is extremely important for those requiring surgical intervention. There are very few reported cases of renal cell carcinoma (RCC) developing in people with situs inversus. To our knowledge, this is the first reported case in Canada. A review of the literature only identified nine published cases worldwide. Here, we review and summarize pertinent information, including patient age and sex, size and location of tumour, method of surgery, and pathology. Our case, a 65-yearold male, presented with left flank pain and gross hematuria. He was diagnosed with left renal cancer as well as tumour thrombus extending into the left renal veins and inferior vena cava (IVC), clinical T3aN0M0. An abdomen and pelvis computed tomography (CT) scan showed a left-to-right reversal of his organs, a mirrorimage, and situs inversus was diagnosed. A left radical nephrectomy with left renal vein and IVC tumour thrombectomy through a left open midline incision was performed.