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Background The osmolal gap has been used for decades to screen for exposure to toxic alcohols. However, several issues may affect its reliability. We aimed to develop equations to calculate osmolarity with improved performance when used to screen for intoxication to toxic alcohols. Study Design Retrospective cohort study. Setting & Participants 7,525 patients undergoing simultaneous measurements of osmolality, sodium, potassium, urea, glucose, and ethanol or undergoing similar measurements performed within 30 minutes of a measurement of toxic alcohol levels at a single tertiary-care center from April 2001 to June 2016. Patients with detectable toxic alcohols were excluded. Index Test Equations to calculate osmolarity using multiple linear regression. Outcomes The performance of new equations compared with published equations developed to calculate osmolarity, and to diagnose toxic alcohol intoxications more accurately. Results We obtained 7,525 measurements, including 100 with undetectable toxic alcohols. Among them, 3,875 had undetectable and 3,650 had detectable ethanol levels. In the entire cohort, the best equation to calculate osmolarity was 2.006×Na + 1.228×Urea + 1.387×Glucose + 1.207×Ethanol (values in mmol/L, R2=0.96). A simplified equation, 2.0×Na + 1.2×Urea + 1.4×Glucose + 1.2×Ethanol, had a similar R2 with 95% of osmolal gap values between −10.9 and 13.8. In patients with undetectable ethanol concentrations, the range of 95% of osmolal gap values was narrower than previous published formulas, and in patients with detectable ethanol concentrations, the range was narrower or similar. We performed a subanalysis of 138 cases for which both the toxic alcohol concentration could be measured and the osmolal gap could be calculated. Our simplified equation had superior diagnostic accuracy for toxic alcohol exposure. Limitations Single center, no external validation, limited number of cases with detectable toxic alcohols. Conclusions In a large cohort, coefficients from regression analyses estimating the contribution of glucose, urea, and ethanol were higher than 1.0. Our simplified formula to precisely calculate osmolarity yielded improved diagnostic accuracy for suspected toxic alcohol exposures than previously published formulas.

We congratulate the KDIGO (Kidney Disease: Improving Global Outcomes) work group on their comprehensive work in a broad subject area and agreed with many of the recommendations in their clinical practice guideline on the evaluation and management of chronic kidney disease. We concur with the KDIGO definitions and classification of kidney disease and welcome the addition of albuminuria categories at all levels of glomerular filtration rate (GFR), the terminology of G categories rather than stages to describe level of GFR, the division of former stage 3 into new G categories 3a and 3b, and the addition of the underlying diagnosis. We agree with the use of the heat map to illustrate the relative contributions of low GFR and albuminuria to cardiovascular and renal risk, though we thought that the highest risk category was too broad, including as it does people at disparate levels of risk. We add an albuminuria category A4 for nephrotic-range proteinuria and D and T categories for patients on dialysis or with a functioning renal transplant. We recommend target blood pressure of 140/90mm Hg regardless of diabetes or proteinuria, and against the combination of angiotensin receptor blockers with angiotensin-converting enzyme inhibitors. We recommend against routine protein restriction. We concur on individualization of hemoglobin A1c targets. We do not agree with routine restriction of sodium intake to 3.3g/d). We suggest screening for anemia only when GFR is 60mg/mmol or proteinuria with protein excretion > 1g/d as the referral threshold for proteinuria.

Background: Cardiovascular disease (CVD) is the leading cause of death in patients with end-stage renal disease (ESRD). Disregulation of apoptosis within the vessel wall and upregulation of the Fas/Fas-ligand (Fas-L) system contribute to the development of atherosclerosis. Cross-sectional studies have suggested that elevated plasma levels of the soluble form of Fas (sFas) are associated with CVD. However, the role of sFas and sFas-L in predicting future cardiovascular events has yet to be defined. Methods: We evaluated the role of plasma sFas and sFas-L levels as predictors of CVD in a prospective cohort of 107 chronic hemodialysis patients. Results: During the study period (27 months), 53 patients (49.5%) presented with at least one cardiovascular end point. On univariate analysis, baseline sFas levels were significantly associated with the occurrence of cardiovascular end points, whereas sFas-L levels were not. Using Cox proportional hazards, increased sFas levels were associated with a significantly greater risk for cardiovascular end points ( P = 0.03). This effect was independent of baseline CVD history, classic risk factors for atherosclerosis (diabetes, hypercholesterolemia, hypertension, and smoking), and markers of inflammation (C-reactive protein [CRP], soluble intercellular adhesion molecule-1). Increased CRP levels also were associated with cardiovascular end points ( P = 0.04). In addition, increased cardiovascular mortality was found in patients in the highest sFas tertile compared with those in the lowest tertile (27.8% versus 8.6%; P = 0.04). Conclusion: Increased plasma sFas levels are predictive of future CVD. These results suggest that sFas is a novel and independent predictor of active atherosclerotic disease in patients with ESRD.

Coronary artery disease (CAD) is the leading cause of death in patients with end-stage renal disease (ESRD). Recent evidence suggests that the expression of Fas, a molecule implicated in the initiation of apoptosis in various cell types, is increased at sites of atherosclerotic plaques. However, the significance of plasma levels of the soluble form of Fas (sFas) and its ligand (sFas-L) as markers of atherosclerosis has yet to be defined. The present report is a cross-sectional analysis of baseline data from an ongoing prospective study designed to evaluate the role of sFas and sFas-L as markers of CAD in ESRD. We evaluated the association between plasma levels of sFas and sFas-L and evidence of CAD in a cohort of 107 chronic hemodialysis patients. Plasma levels of sFas were significantly greater ( P = 0.04) among subjects with (n = 64) than without evidence of CAD (n = 43). Plasma levels of sFas-L were similar in both groups. Using multivariate analysis, sFas level was found to be independently associated with CAD ( P = 0.01) after adjustment for classic risk factors for CAD (hyperlipidemia, diabetes, hypertension, and smoking), markers of inflammation (C-reactive protein [CRP], intercellular adhesion molecule 1), and other confounders. An increase of one quintile in plasma concentration of sFas was associated with an odds ratio for CAD of 1.64 (95% confidence interval, 1.11 to 2.41). Models that incorporated sFas were significantly better at identifying patients with CAD than models limited to classic risk factors for atherosclerosis, alone ( P = 0.008) or in combination with CRP levels ( P = 0.006). In summary, increased plasma levels of sFas are associated with CAD in stable patients with ESRD. These results suggest that sFas may represent a novel and independent marker of CAD. © 2001 by the National Kidney Foundation, Inc.