Hypernatremia in the critically ill is an independent risk factor for mortality

Am J Kidney Dis. 2007 Dec;50(6):952-7. doi: 10.1053/j.ajkd.2007.08.016.

Abstract

Background: Hypernatremia is common in the intensive care unit (ICU). We assessed the prevalence of hypernatremia and its impact on mortality and ICU length of stay (LOS).

Study design: Retrospective analysis.

Setting & participants: All patients admitted to a medical ICU of a university hospital during a 35-month observation period.

Predictor: Hypernatremia (serum sodium > 149 mmol/L) after admission to the ICU.

Outcomes & measurements: Main outcomes were 28-day hospital mortality and ICU LOS. Demographic factors, main diagnosis, and severity of illness. Cox proportional hazards regression models were used for data analysis.

Results: Of 981 patients, 90 (9%) had hypernatremia, on admission to the ICU in 21 (2%) and developed during the ICU stay in 69 patients (7%). Of these 981 patients, 235 (24%) died; LOS was 8 +/- 9 (SD) days. Mortality rates were 39% and 43% in patients with hypernatremia on admission or that developed after admission compared with 24% in patients without hypernatremia (P < 0.01). LOS was 20 +/- 16 days in patients with hypernatremia compared with 8 +/- 10 days in patients without hypernatremia (P < 0.001). In multivariable analysis, hypernatremia was an independent risk factor for mortality (relative risk, 2.1; 95% confidence interval, 1.4 to 3.3).

Limitations: Retrospective design, absence of data for long-term mortality.

Conclusions: Most cases of hypernatremia in the ICU developed after admission, suggesting an iatrogenic component in its evolution. Hypernatremia is associated with increased mortality. Strategies for preventing hypernatremia in the ICU should be encouraged.

MeSH terms

  • Adult
  • Aged
  • Critical Illness / mortality*
  • Female
  • Hospital Mortality*
  • Humans
  • Hypernatremia / diagnosis*
  • Hypernatremia / etiology*
  • Intensive Care Units
  • Kaplan-Meier Estimate
  • Length of Stay / statistics & numerical data
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Prevalence
  • Prognosis
  • Proportional Hazards Models
  • Retrospective Studies
  • Risk Factors