Can billing codes accurately identify rapidly progressing stage 3 and stage 4 chronic kidney disease patients: a diagnostic test study.

BACKGROUND: The International Classification of Diseases (ICD) coding system is the industry standard tool for billing, disease classification, and epidemiology purposes. However, ICD codes are often not assigned or incorrectly given, particularly among Chronic Kidney disease (CKD) patients. Our study evaluated the diagnostic accuracy of CKD-staging ICD codes among CKD patients from a large insurer database in identifying individuals rapidly progressing towards end-stage renal disease (ESRD). PATIENTS AND METHODS: Serial observations including outpatient serum creatinine measurements collected from 2007 through 2014 of 216,529 patients were examined. The progression of CKD using a serum creatinine based longitudinal mixed-model was contrasted with that documented by CKD-staging ICD codes. Rapid progressors, defined as those with yearly estimated glomerular filtration rate (eGFR) loss greater than 4 ml/min/1.73m2) were identified. The diagnosis of CKD using eGFR was also compared to diagnosis using a set of CKD related ICD codes. RESULTS: Of 10,927 clinically identified CKD patients qualifying for inclusion in the progression analysis, 323 were clinically identified as rapid progressors. CKD-staging ICD codes identified 83 of these, for a sensitivity of 25.7% with positive predictive value (PPV) of 13.74%, and specificity 95.09% with negative predictive value (NPV) of 97.68%. Of 28,762 laboratory-confirmed CKD patients, 9249 had a qualifying ICD code, for a sensitivity of 16% with PPV of 63.10%; Of 187,767 patients with laboratory-confirmed absence of CKD, 182,359 also did not have a qualifying ICD code, for a specificity of 97.12% with NPV of 90.33%. CONCLUSION: This study depicts the novel finding that ICD-codes display poor capacity to identify rapidly progressing CKD patients when compared to gold standard eGFR measures, and further demonstrates the limitations of coding in CKD diagnosis. This analysis further defines the limitations of ICD codes in addressing diagnosis of disease severity or disease progression for clinical or epidemiological purposes.

Preoperative serum potassium predicts the clinical outcome after non-cardiac surgery.

BACKGROUND: Potassium disorders have been linked to adverse outcomes in various medical conditions. However, the association of preoperative serum potassium with postoperative outcome is not well established. We aimed to examine the association between preoperative potassium with a 30-day mortality and adverse cardiovascular event (MACE). METHODS: We conducted a cohort study using a prospectively collected database of patients, undergoing surgical procedures from 1998 to 2013 in the VA Western New York Healthcare System, which are reported to the Veterans Affairs Surgical Quality Improvement Program (VASQIP). The patients were categorized into three groups based on their documented preoperative potassium concentrations. Hypokalemia was defined as serum potassium concentration <4 mmol/L and hyperkalemia was defined as serum potassium concentrations >5.5 mmol/L. The values within the range of 4.0-5.5 mmol/L were considered as normokalemia and used as the control group. Statistical analyses included Chi-square test, analysis of variance and multivariate logistic regression to estimate the risk of MACE within 30 days of surgery. RESULTS: Study included 5959 veterans who underwent surgery between 1998 and 2013. The patients in the hyperkalemics group had lower kidney function compared to the other two groups. The frequency of MACE was 13.6% in hypokalemics and 21.9% in hyperkalemics that were both significantly higher than 4.9% in controls. In multivariate logistic regression the hazard risk (HR) ratios of MACE were (2.17, 95% CI 1.75-2.70) for hypokalemics and (3.23, 95% CI 2.10-4.95) for hyperkalemics when compared to normokalemic controls. CONCLUSIONS: Preoperative hypokalemia and hyperkalemia are both independent predictors of MACE within 30 days.