Are the Dysnatremias a Permanent Threat to the Critically Ill Patients?

Catabolism highly influences ICU-acquired hypernatremia in a mainly trauma and surgical cohort

PURPOSE

To further analyse causes and effects of ICU-acquired hypernatremia.

METHODS

This retrospective, single-centre study, analysed 994 patients regarding ICU-acquired hypernatremia. Non-hypernatremic patients (n = 617) were compared to early-hypernatremic (only before ICU-day 4; n = 87), prolonged-hypernatremic (before and after ICU-day 4; n = 169) and late-hypernatremic patients (only after ICU-day 4; n = 121). Trends in glomerular filtration rate (eGFR), urea-to-creatinine ratio (UCR), fraction of urea in total urine osmolality and urine sodium were compared. Risk factors for i) the development of hypernatremia and ii) mortality were determined.

RESULTS

Thirty-eight percent (n = 377) developed ICU-acquired hypernatremia. Specifically in the prolonged- and late-group, decreased eGFRs and urine sodium but increased UCR and fractions of urea in urine osmolality were present. Decreased eGFR was a risk factor for the development of hypernatremia in all groups; disease severity and increased catabolism particularly in the prolonged- and late-hypernatremic group. Increased age, SAPS-III and signs of catabolism but not the development of hypernatremia itself was identified as significant risk factor for mortality.

CONCLUSIONS

Late- and prolonged-hypernatremia is highly related to an increased protein metabolism. Besides excessive catabolism, initial disease severity and a decrease in renal function must be considered when confronted with ICU-acquired hypernatremia.

Early ICU-acquired hypernatraemia is associated with injury severity and preceded by reduced renal sodium and chloride excretion in polytrauma patients

PURPOSE

To further elucidate the origin of early ICU-acquired hypernatraemia.

MATERIAL AND METHODS

In this retrospective single-centre study, polytrauma patients requiring ICU treatment were analysed.

RESULTS

Forty-eight (47.5%) of 101 included polytrauma patients developed hypernatraemia within the first 7 days on ICU. They were more severely ill as described by higher SAPS III, ISS, daily SOFA scores and initial norepinephrine requirements as well as longer requirements of mechanical ventilation and ICU treatment in general. The development of hypernatraemia was neither attributable to fluid- or sodium-balances nor renal impairment. Although lower in the hypernatraemic group from day 4 onwards, median creatinine clearances were sufficiently high throughout the observation period. However, in the hypernatraemic group, urine sodium and chloride concentrations prior to the evolvement of hypernatraemia (56 (27-87) mmol/l and 39 (23-77) mmol/l) were significantly decreased when compared to i) the time after developing hypernatraemia (94 (58-134) mmol/l and 78 (36-115) mmol/l; p < 0.001) and ii) the non-hypernatraemic group in general (101 (66-143) mmol/l and 75 (47-109) mmol/l; p < 0.001).

CONCLUSIONS

Early ICU-acquired hypernatraemia is associated with injury severity and preceded by reduced renal sodium and chloride excretion in polytrauma patients.

Electrolyte Analysis and Replacement: Challenging a Paradigm in Surgical Patients

Postoperative patients are susceptible to alterations in electrolyte homeostasis. Although electrolytes are replaced in critically ill patients, stable asymptomatic non-intensive care unit (ICU) patients often receive treatment of abnormal electrolytes. We hypothesize there is no proven benefit in asymptomatic patients. In 2016, using the electronic medical records and pharmacy database at a university academic medical center, we conducted a retrospective cost analysis of the frequency and cost of electrolyte analysis (basic metabolic panel [BMP], ionized calcium [Ca], magnesium [Mg], and phosphorus [P]) and replacement (potassium chloride [KCl], Mg, oral/iv Ca, oral/iv P) in perioperative patients. Patients without an oral diet order, with creatinine more than 1.4, age less than 16 years, admitted to the ICU, or with length of stay of more than 1 week were excluded. Nursing costs were calculated as a fraction of hourly wages per laboratory order or electrolyte replacement. One hundred thirteen patients met our criteria over 11 months. Mean length of stay was 4 days; mean age was 54 years; and creatinine was 0.67 ± 0.3. Electrolyte analysis laboratory orders (n = 1,045) totaled $6,978, and BMP was most frequently ordered accounting for 36% of laboratory costs. In total, 683 doses of electrolytes cost the pharmacy $1,780. Magnesium was most frequently replaced, followed by KCl, P, and Ca. Nursing cost associated with electrolyte analysis/replacement was $7,782. There is little evidence to support electrolyte analysis and replacement in stable asymptomatic noncritically ill patients, but their prevalence and cost ($146/case) in this study were substantial. Basic metabolic panels, pharmacy charges for potassium, and nursing staff costs accounted for the most significant portion of the total cost. Considering these data, further research should determine whether these practices are warranted.

A deep learning backcasting approach to the electrolyte, metabolite, and acid-base parameters that predict risk in ICU patients

BACKGROUND

A powerful risk model allows clinicians, at the bedside, to ensure the early identification of and decision-making for patients showing signs of developing physiological instability during treatment. The aim of this study was to enhance the identification of patients at risk for deterioration through an accurate model using electrolyte, metabolite, and acid-base parameters near the end of patients' intensive care unit (ICU) stays.

METHODS

This retrospective study included 5157 adult patients during the last 72 hours of their ICU stays. The patients from the MIMIC-III database who had serum lactate, pH, bicarbonate, potassium, calcium, glucose, chloride, and sodium values available, along with the times at which those data were recorded, were selected. Survivor data from the last 24 hours before discharge and four sets of nonsurvivor data from 48-72, 24-48, 8-24, and 0-8 hours before death were analyzed. Deep learning (DL), random forest (RF) and generalized linear model (GLM) analyses were applied for model construction and compared in terms of performance according to the area under the receiver operating characteristic curve (AUC). A DL backcasting approach was used to assess predictors of death vs. discharge up to 72 hours in advance.

RESULTS

The DL, RF and GLM models achieved the highest performance for nonsurvivors 0-8 hours before death versus survivors compared with nonsurvivors 8-24, 24-48 and 48-72 hours before death versus survivors. The DL assessment outperformed the RF and GLM assessments and achieved discrimination, with an AUC of 0.982, specificity of 0.947, and sensitivity of 0.935. The DL backcasting approach achieved discrimination with an AUC of 0.898 compared with the DL native model of nonsurvivors from 8-24 hours before death versus survivors with an AUC of 0.894. The DL backcasting approach achieved discrimination with an AUC of 0.871 compared with the DL native model of nonsurvivors from 48-72 hours before death versus survivors with an AUC of 0.846.

CONCLUSIONS

The DL backcasting approach could be used to simultaneously monitor changes in the electrolyte, metabolite, and acid-base parameters of patients who develop physiological instability during ICU treatment and predict the risk of death over a period of hours to days.

ICU-Acquired Hypernatremia Is Associated with Persistent Inflammation, Immunosuppression and Catabolism Syndrome

Developing hypernatremia while on intensive care unit (ICU) is a common problem with various undesirable effects. A link to persistent inflammation, immunosuppression and catabolism syndrome (PICS) can be established in two ways. On the one hand, hypernatremia can lead to inflammation and catabolism via hyperosmolar cell stress, and on the other, profound catabolism can lead to hypernatremia via urea-induced osmotic diuresis. In this retrospective single-center study, we examined 115 patients with prolonged ICU stays (≥14 days) and sufficient renal function. Depending on their serum sodium concentrations between ICU day 7 and 21, allocation to a hypernatremic (high) and a nonhypernatremic group (low) took place. Distinct signs of PICS were detectable within the complete cohort. Thirty-three of them (28.7%) suffered from ICU-acquired hypernatremia, which was associated with explicitly higher signs of inflammation and ongoing catabolism as well as a prolonged ICU length of stay. Catabolism was discriminated better by the urea generation rate and the urea-to-creatinine ratio than by serum albumin concentration. An assignable cause for hypernatremia was the urea-induced osmotic diuresis. When dealing with ICU patients requiring prolonged treatment, hypernatremia should at least trigger thoughts on PICS as a contributing factor. In this regard, the urea-to-creatinine ratio is an easily accessible biomarker for catabolism.

Intensive care unit-acquired hyponatremia in critically ill medical patients

Background

Previous research has focused on intensive care unit (ICU)-acquired hypernatremia; however, ICU-acquired hyponatremia has frequently been overlooked and has rarely been studied in surgical or mixed ICUs. The aim of this study is to investigate the incidence of ICU-acquired hyponatremia, the risk factors associated with its development, and its impact on outcomes in critically ill medical patients.

Methods

We conducted a retrospective cohort study based on the prospective registry of all critically ill patients admitted to the medical ICU from January 2015 to December 2018. Baseline characteristics and management variables were compared between ICU-acquired hyponatremia and normonatremia patients.

Results

Of 1342 patients with initial normonatremia, ICU-acquired hyponatremia developed in 217 (16.2%) patients and ICU-acquired hypernatremia developed in 117 (8.7%) patients. The Sequential Organ Failure Assessment (8.0 vs 7.0, P = 0.009) and Simplified Acute Physiology Score 3 scores (55.0 vs 51.0, P = 0.005) were higher in ICU-acquired hyponatremia patients compared with normonatremia patients. Baseline sodium (137.0 mmol/L vs 139.0 mmol/L, P < 0.001), potassium (4.2 mmol/L vs 4.0 mmol/L, P = 0.001), and creatinine (0.98 mg/dL vs 0.88 mg/dL, P = 0.034) levels were different between the two groups. Net volume balance over first 3 days was higher in ICU-acquired hyponatremia patients (19.4 mL/kg vs 11.5 mL/kg, P = 0.004) and was associated with the development of ICU-acquired hyponatremia (adjusted odds ratio, 1.004; 95% confidence interval, 1.002–1.007; P = 0.001). ICU mortality was similar in both groups (15.2% vs. 14.4%, P = 0.751), but renal replacement therapy was more commonly required in ICU-acquired hyponatremia patients (13.4% vs 7.4%, P = 0.007).

Conclusions

ICU-acquired hyponatremia is not uncommon in critically ill medical patients. Increased volume balance is associated with its development. ICU-acquired hyponatremia is related to increased use of renal replacement therapy but not to mortality.

Excess sodium is deleterious on endothelial and glycocalyx barrier function: A microfluidic study

BACKGROUND

Hypernatremia is a common problem affecting critically ill patients, whether due to underlying pathology or the subsequent result of hypertonic fluid resuscitation. Numerous studies have been published, suggesting that hypernatremia may adversely affect the vascular endothelial glycocalyx. Our study aimed to evaluate if high sodium concentration would impair the endothelial and glycocalyx barrier function and if stress conditions that simulate the shock microenvironment would exacerbate any observed adverse effects of hypernatremia.

METHODS

Human umbilical vein endothelial cells (HUVEC) were cultured in microfluidic channels subjected to flow conditions overnight to stimulate glycocalyx growth. Cells were then subjected to sodium (Na) concentrations of either 150 mEq/L or 160 mEq/L, with Hepes solution applied to media to maintain physiologic pH. Subsets of HUVEC were also exposed to hypoxia/reoxygenation and epinephrine (HR + Epi) to simulate shock insult, then followed by Na treatment. Perfusate was then collected 60 minutes and 120 minutes following treatments. Relevant biomarkers were then evaluated and HUVEC underwent fluorescent staining followed by microscopy.

RESULTS

Glycocalyx degradation as indexed by hyaluronic acid and syndecan-1 was elevated in all subgroups, particularly those subjected to HR + Epi with Na 160 mEq/L. Thickness of the glycocalyx as evaluated by fluorescent microscopy was reduced to half of baseline with Na 160 mEq/L and to one third of baseline with additional insult of HR + Epi. Endothelial activation/injury as indexed by soluble thrombomodulin was elevated in all subgroups. A profibrinolytic coagulopathy phenotype was demonstrated in all subgroups with increased tissue plasminogen activator levels and decreased plasminogen activator inhibitor-1 levels.

CONCLUSION

Our data suggest that hypernatremia results in degradation of the endothelial glycocalyx with further exacerbation by shock conditions. A clinical study using clinical measurements of the endothelial glycocalyx in critically ill or injured patients with acquired hypernatremia would be warranted.

Could dysnatremias play a role as independent factors to predict mortality in surgical critically ill patients?

Several studies have demonstrated the impact of dysnatremias on mortality of intensive care unit (ICU) patients. The objective of this study was to assess whether dysnatremia is an independent factor to predict mortality in surgical critically ill patients admitted to ICU in postoperative phase.One thousand five hundred and ninety-nine surgical patients (58.8% males; mean age of 60.6 ± 14.4 years) admitted to the ICU in the postoperative period were retrospectively studied. The patients were classified according to their serum sodium levels (mmol/L) at admission as normonatremia (135-145), hyponatremia (<135), and hypernatremia (>145). APACHE II, SAPS III, and SOFA were recorded. The capability of each index to predict mortality of ICU and hospital mortality of patients was analyzed by multiple logistic regression.Hyponatremia did not have an influence on mortality in the ICU with a relative risk (RR) = 0.95 (0.43-2.05) and hospital mortality of RR = 1.40 (0.75-2.59). However, this association was greater in patients with hypernatremia mortality in the ICU (RR = 3.33 [95% confidence interval, CI 1.58-7.0]) and also in hospital mortality (RR = 2.9 [ 95% CI = 1.51-5.55). The pairwise comparison of ROC curves among the different prognostic indexes (APACHE II, SAPS III, SOFA) did not show statistical significance. The comparison of these indexes with serum sodium levels for general population, hyponatremia, and normonatremia was statistically significant (P < .001). For hypernatremia, the AUC and 95% CI for APACHE II, SAPS III, SOFA, and serum sodium level were 0.815 (0.713-0.892), 0.805 (0.702-0.885), 0.885 (0.794-0.945), and 0.663 (0.549-0.764), respectively. The comparison among the prognostic indexes was not statistically significant. Only SOFA score had a statistic difference compared with hypernatremia (P < .02).The serum sodium levels at admission, especially hypernatremia, may be used as an independent predictor of outcome in the surgical critically ill patients.