Estimating excess glucose, sodium and water deficits in non-ketotic hyperglycaemia

Bartoli, Ettore; Guidetti, Francesca; Bergamasco, Luca

doi:10.1093/ndt/gfm427

Cited by 12 publications

(35 citation statements)

References 8 publications

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“…Therefore, in the majority of cases the physicians resort to estimates, more easily done in the presence of hypo- and hypernatremia, provided that there are changes either in solute or water stores [1]. Calculations in mixed water-electrolyte disturbances were not available till recently, when we described methods capable of yielding exact or accurate estimates under certain conditions [2,3,5,6,7]. However, the problem per se is mathematically unsolvable, as the number of equations exceeds that of variables involved.…”

Section: Discussionmentioning

confidence: 99%

“…The true TBW during the derangement was obtained from patient BW with the following formula: TBW (true) = 0.6 · BW when BMI = 24 ± 2, with the empirical anthropometric formulas in the other circumstances [4,5]. If BW could not be measured, we collected the water balance from the time of admission to the ward to the end of treatment, and back-calculated the TBW from the normal patient weight according to established anthropometric formulas or from height [4,5], subtracting the water balance. The true ΔNa, ΔV, ΔOAN, ΔCl and ΔECV were consequently calculated as previously reported [2].…”

Section: Methodsmentioning

confidence: 99%

“…The true ΔNa, ΔV, ΔOAN, ΔCl and ΔECV were consequently calculated as previously reported [2]. When height is known, TBW = 24 · h 2 · 0.6, where the BMI is 24, h 2 the square of height in meters and 0.6 the fraction of water over weight when BMI is normal [4,5]. As fat is anhydrous, the formula states that TBW does not change when BW rises by fat accumulation above a BMI of 24: thus, TBW can be computed correctly even by knowing only the height.…”

Section: Methodsmentioning

confidence: 99%

“…The patients were evaluated clinically. Special care was taken to examine clinical and laboratory parameters of dehydration calculating a dehydration score as previously described [5]. The following parameters were considered to calculate the cumulative score by adding the individual ones reported within brackets: blood pressure mm Hg: ≤115/70 (1), <100/60 (2), diastolic unmeasurable (3); heart rate per minute: ≥84 (1); ≥92 (2), ≥100 (3); appearance of skin and mucosae: dry (3); plasma creatinine mg/dl: ≥1.5 (1), ≥2.0 (2), ≥2.5 (3); creatinine clearance ml/min: ≤60 (1), <20 (3); hematocrit %: ≥40 (1), >54 (3); jugular veins and bedside estimate of CVP: low (1); extremities: cold (1); extremities and forehead: sweaty (1); mental state: clouded (3); peripheral veins: flat (1); urine volume/24 h: <400 (1), <200 ml (3).…”

Section: Methodsmentioning

confidence: 99%

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Computation of Na and Water Deficit of Iso-Osmolar Dehydration

Sainaghi¹,

Bergamasco²,

Castello³

et al. 2010

Nephron Physiol

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Background and Aims: The presence of altered plasma Na concentration (PNa) allows calculations of changes in water and electrolyte contents, which are not feasible during normonatremic derangements. We have developed a computational algorithm whereby the changes in solute (ΔNa and ΔCl) and solvent (ΔV) contents can be computed exactly when Na is lost entirely as NaCl (or NaHCO₃) and nearly exactly in all other circumstances, except when the losses of Na and Cl occur in the same proportions as those of the normal plasma concentration of these ions. Methods: In computer experiments, we simulated different fluid depletions containing 140 mEq/l of Na (which is to say, ΔNa/ΔV ≈ 140), coupled with variable ratios in Na to Cl losses (variable ΔNa/ΔCl). The data were back-calculated with our algorithms from the ensuing plasma ion concentrations (PNa₁, PCl₁ and POAN₁, where subscript ₀ and ₁ indicate normal and deranged plasma concentration values, respectively, and OAN indicates anions other than Cl), as if they had been measured on patients, and from known normal values (TBW₀, ECV₀, Na₀). These were compared to the true values used to build the simulations. This procedure was reproduced in 17 patients suffering from iso-osmolar dehydration, where true data were obtained by balance studies. Results: True and calculated data were compared with linear regression analysis. We obtained significant correlations both in computer-simulated and real patients (R² = 0.83, p < 0.005 and R² = 0.63, p < 0.05, respectively). Conclusion: This new math model and its related computational method are useful in the correct evaluation and treatment of iso-osmolar dehydration.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Computation of Na and Water Deficit of Iso-Osmolar Dehydration

Sainaghi¹,

Bergamasco²,

Castello³

et al. 2010

Nephron Physiol

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“…We suggest that simplicity without loss of accuracy is an advantage of this method. Rigorous, but more complex, methods calculating the replacement solutions have been reported [7][8]. Table 1 shows the abbreviations used in this report.…”

Section: Introductionmentioning

confidence: 99%

Principles of Quantitative Fluid and Cation Replacement in Extreme Hyperglycemia

Tzamaloukas¹,

Sun

Konstantinov³

et al. 2013

Cureus

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An improved method to compute the solute and water derangements of hyperglycaemia

et al. 2007

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Evaluation and treatment of hyperglycaemic hyponatremia, being quantitatively inaccurate, is open to new advancements. We herein describe the improvement of previous calculations of glucose appearance (G(A)), solute and solvent changes. From G(A) we derive the predicted plasma sodium concentration (PNa(G)), assuming no change in total body water (TBW), but only water shift from cells to the extracellular space (ECV). This assumption is validated by the respective solute ratios (PCl/PNa) unchanged from normal values, as well as the ratios between actual and normal solute concentrations (PNa(1)/PNa(0), PCl(1)/PCl(0)), identical for all solutes. When the assumption is met, G(A) can be exactly calculated. When the ratios are different from normal, they indicate the presence of a mixed abnormality due to a loss either of sodium, or sodium and water. These are estimated by computing the difference between PNa(G) and the actual PNa measured (PNa(1)). PNa(1) approximately equal PNa(G) if TBW and Na are unchanged, PNa(1) < PNa(G) in the presence of prevalent Na depletion, PNa(1) > PNa(G )when volume depletion prevails. In the first circumstance the ECV expansion is exactly established by appropriate mathematical formulas, in the latter conditions either Na or volume depletion are empirically estimated with algebric expressions. These equations were validated on computer-simulated models, and applied to 49 subjects with plasma glucose concentration >15 mM/L. G(A) and PNa(G) were computed, and, with the same formulas used in computer-simulated experiments, we calculated water and Na deficits. The PNa measured after correction of hyperglycaemia was correctly predicted (R(2) = 0.63, P < 0.0001). This method provides a firm ground to select the correct equation to accurately estimate the initial conditions of hyperosmolar hyperglycaemia, significantly improving its quantitative correction.

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Estimating excess glucose, sodium and water deficits in non-ketotic hyperglycaemia

Abstract: This new method more accurately computes the initial conditions, resulting in a useful stratification of patients which improves the quantitative evaluation and treatment of hyperosmolar coma.

Cited by 12 publications

References 8 publications

Computation of Na and Water Deficit of Iso-Osmolar Dehydration

Computation of Na and Water Deficit of Iso-Osmolar Dehydration

Principles of Quantitative Fluid and Cation Replacement in Extreme Hyperglycemia

An improved method to compute the solute and water derangements of hyperglycaemia

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