Hyponatremia and mortality risk: a Danish cohort study of 279 508 acutely hospitalized patients

in European Journal of Endocrinology
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  • 1 Department of Clinical Epidemiology, Department of Nephrology, Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Olof Palmes Allé 43–45, DK-8200 Aarhus N, Denmark

Objective

We aimed to investigate the impact of hyponatremia severity on mortality risk and assess any evidence of a dose–response relation, utilizing prospectively collected data from population-based registries.

Design

Cohort study of 279 508 first-time acute admissions to Departments of Internal Medicine in the North and Central Denmark Regions from 2006 to 2011.

Methods

We used the Kaplan–Meier method (1 – survival function) to compute 30-day and 1-year mortality in patients with normonatremia and categories of increasing hyponatremia severity. Relative risks (RRs) with 95% CIs, adjusted for age, gender and previous morbidities, and stratified by clinical subgroups were estimated by the pseudo-value approach. The probability of death was estimated treating serum sodium as a continuous variable.

Results

The prevalence of admission hyponatremia was 15% (41 803 patients). Thirty-day mortality was 3.6% in normonatremic patients compared to 7.3, 10.0, 10.4 and 9.6% in patients with serum sodium levels of 130–134.9, 125–129.9, 120–124.9 and <120 mmol/l, resulting in adjusted RRs of 1.4 (95% CI: 1.3–1.4), 1.7 (95% CI: 1.6–1.8), 1.7 (95% CI: 1.4–1.9) and 1.3 (95% CI: 1.1–1.5) respectively. Mortality risk was increased across virtually all clinical subgroups, and remained increased by 30–40% 1 year after admission. The probability of death increased when serum sodium decreased from 139 to 132 mmol/l. No clear increase in mortality was observed for lower concentrations.

Conclusions

Hyponatremia is highly prevalent among patients admitted to Departments of Internal Medicine and is associated with increased 30-day and 1-year mortality risk, regardless of underlying disease. This risk seems independent of hyponatremia severity.

Abstract

Objective

We aimed to investigate the impact of hyponatremia severity on mortality risk and assess any evidence of a dose–response relation, utilizing prospectively collected data from population-based registries.

Design

Cohort study of 279 508 first-time acute admissions to Departments of Internal Medicine in the North and Central Denmark Regions from 2006 to 2011.

Methods

We used the Kaplan–Meier method (1 – survival function) to compute 30-day and 1-year mortality in patients with normonatremia and categories of increasing hyponatremia severity. Relative risks (RRs) with 95% CIs, adjusted for age, gender and previous morbidities, and stratified by clinical subgroups were estimated by the pseudo-value approach. The probability of death was estimated treating serum sodium as a continuous variable.

Results

The prevalence of admission hyponatremia was 15% (41 803 patients). Thirty-day mortality was 3.6% in normonatremic patients compared to 7.3, 10.0, 10.4 and 9.6% in patients with serum sodium levels of 130–134.9, 125–129.9, 120–124.9 and <120 mmol/l, resulting in adjusted RRs of 1.4 (95% CI: 1.3–1.4), 1.7 (95% CI: 1.6–1.8), 1.7 (95% CI: 1.4–1.9) and 1.3 (95% CI: 1.1–1.5) respectively. Mortality risk was increased across virtually all clinical subgroups, and remained increased by 30–40% 1 year after admission. The probability of death increased when serum sodium decreased from 139 to 132 mmol/l. No clear increase in mortality was observed for lower concentrations.

Conclusions

Hyponatremia is highly prevalent among patients admitted to Departments of Internal Medicine and is associated with increased 30-day and 1-year mortality risk, regardless of underlying disease. This risk seems independent of hyponatremia severity.

Introduction

Serum sodium concentration is one of the most frequently performed laboratory measurements in clinical medicine (1). Changes in serum sodium concentrations are closely linked to extracellular volume regulation and cellular homeostasis, and are associated with several common conditions encountered in Departments of Internal Medicine (2). The reported prevalence of hyponatremia (serum sodium concentration <135 mmol/l) at hospital admission ranges from 5% to almost 35%, depending on the study population and the timing requirements specified for the serum measurement (3, 4, 5, 6). Hyponatremia has been associated with increased morbidity and mortality in patients with preexisting heart disease, kidney failure, cirrhosis and cancer (7, 8, 9, 10, 11). Still, few data exist on the prevalence and prognostic impact of hyponatremia in broader populations of patients admitted acutely to Departments of Internal Medicine.

In 2009, Whelan et al. (12) showed a positive association between degree of hyponatremia and in-hospital mortality risk compared to patients with normonatremia. While this finding was supported by two subsequent studies by Kovesdy et al. (9) and Wald et al. (13), others have not been able to confirm such a dose–response relation (4, 14). Varying effects of hyponatremia in different patient populations or in the setting of different underlying diseases offer one possible explanation for these diverse results. In a cohort study of 98 411 patients admitted to two teaching hospitals in Boston, Massachusetts and hospitalized for >2 days, Waikar et al. (4) found a twofold increased risk for in-hospital death associated with hyponatremia compared to normonatremia for patients with several, but not all, acute medical and surgical conditions.

To investigate these issues in further detail, we conducted a large population-based study on the prevalence and prognostic impact of mild to severe hyponatremia in patients acutely admitted to Departments of Internal Medicine across diagnostic groups defined by the primary diagnosis associated with the current hospitalization and by previous morbidities included in the Charlson comorbidity index (CCI).

Methods

Setting

We conducted this cohort study using Danish population-based medical registries. The Danish National Health Service guarantees free and unfettered access to tax-supported health care for all Danish citizens. The unique ten-digit identification number (CPR number) assigned by the Civil Registration System (CRS) to each person born in or immigrating to Denmark is used in all public records and allows for unambiguous individual-level linkage between Danish registries. This ensures virtually complete follow-up of patients receiving care from the Danish National Health Service (15).

Study cohort

We used the Danish National Patient Registry (DNPR) to identify all hospital admissions in the North and Central Denmark Regions from 1st January 2006 to 31st December 2011 (cumulative population ≈two million inhabitants). The study period was selected based on the availability of complete data in the clinical laboratory information system database (LABKA) for the entire study area (1). The DNPR is a population-based nationwide registry primarily established to monitor hospital activities. The registry contains records for all admissions to Danish non-psychiatric hospitals since 1977 and for all emergency department and outpatient specialist clinic visits since 1995. Reporting to the DNPR is mandatory (16).

For each patient identified, we included in the study only the first acute admission to a Department of Internal Medicine during the study period (in patients ≥15 years of age). Study criteria were: i) admission to a Department of Internal Medicine; ii) an ‘acute’ admission type, assigned by a secretary upon hospital entry and iii) no surgical, oncologic, gynecologic or obstetric hospitalizations recorded within 30 days prior to the current admission. Admissions on the same day as discharge or transfers between departments were considered as a single hospitalization.

Admission serum sodium value

The LABKA database contains results of all analyses of blood samples drawn from hospitalized patients or outpatients and submitted to hospital laboratories in the Northern and Central Denmark regions (1). Analyses are recorded according to the Nomenclature, Properties, and Units (NPU) coding system and/or local nomenclature. Each record contains information on time and date of the analysis and its results. From the LABKA database, we retrieved information on the first serum sodium measurement performed during hospitalization.

To reduce the probability that serum sodium levels were affected by hospital treatment, we focused on measurements performed within 24 h following admission. We defined normonatremia as serum sodium values between 135 and 145 mmol/l and hyponatremia as serum sodium values <135 mmol/l. Hyponatremia upon admission was divided into four further categories (<120, 120–124.9, 125–129.9 and 130–134.9 mmol/l), in accordance with previous studies (4). If no sodium measurement was performed within 24 h of admission, patients were categorized as having normonatremia and a serum sodium value of 140 mmol/l was imputed.

Mortality

Residence, migration and vital status of all Danish residents can be tracked through the CRS, which is updated daily (15). We obtained information from the CRS on gender, age, migration and vital status, date of migration and date of death of deceased patients.

Diagnostic groups

For each hospitalization, one primary diagnosis and one or more secondary diagnoses are assigned by the discharging physician and recorded in the DNPR. Diagnoses were coded according to the International Classification of Diseases (ICD), 8th revision (ICD8) until the end of 1993 and according to the 10th revision (ICD10) thereafter (16).

We used the primary diagnosis recorded in the DNPR to determine the main indication for treatment during the current hospitalization. On this basis, we categorized patients into 11 major disease groups: infectious disease, cardiovascular disease, respiratory disease (excluding pneumonia diagnoses, which were included in the infectious disease group) gastrointestinal disease, urogenital disease, endocrine disease, neurologic disease, muscle and connective tissue disease, cancer, observation for suspected disease, and ‘other’. Some major primary discharge diagnosis categories were subdivided for further examination.

We used inpatient and outpatient specialist clinic diagnoses recorded in the DNPR prior to the current hospitalization to identify previous morbidities included in the CCI. We used these diagnoses to compute CCI scores as a proxy for the preexisting morbidity burden of each patient. The CCI, a validated comorbidity scoring system, includes 19 specific conditions, each given a weighted score from 1 to 6 depending on its correlation with 1-year mortality (17, 18). We defined three CCI levels: low (CCI score=0), medium (CCI score=1–2) and high (CCI score >2).

Statistical analysis

Baseline characteristics of patients with hyponatremia and normonatremia were described in contingency tables.

We computed the prevalence of hyponatremia overall and for each hyponatremia category. The denominator contained the total number of first-time admissions to a Department of Internal Medicine, including patients with hypernatremia or a missing admission sodium measurement. We further computed the prevalence of hyponatremia according to age and diagnostic groups (i.e. groups based on CCI level, specific preexisting morbidities, and primary discharge diagnosis).

Patients with hyponatremia and normonatremia were followed from the date of the first acute Internal Medicine admission until death, migration or up to 1 year. We used the Kaplan–Meier method (1 – the survival function) to compute 30-day and 1-year mortality with 95% CIs, and plotted cumulative mortality for categories of serum sodium values. Since the majority of previous studies only had access to in-hospital mortality data, we also computed in-hospital mortality rates for comparison. We computed relative risk (RR) of death with corresponding 95% CIs, comparing mortality risk at 30 days and 1 year in patients with hyponatremia with that in patients with normonatremia using the pseudo-value approach. This approach allows for direct regression modelling of right-censored data comparing survival (or failure) functions for non-proportional hazard rates at a fixed point in time (19). We repeated the analyses adjusting for gender, age group and the specific preexisting morbidities included in the CCI.

We fitted the regression using a restricted cubic spline function (five knots) and plotted the resulting curve against serum sodium concentration (20), in order to identify threshold values for the association between hyponatremia and increased mortality. Furthermore, we examined the impact of hyponatremia on mortality in different diagnostic groups, by computing 30-day adjusted RRs stratified by CCI level, specific preexisting morbidities and primary discharge diagnoses. In these analyses, we adjusted for CCI level rather than specific preexisting CCI morbidities to better comply with the rule of thumb for minimum outcome events per predictor variable in each cell. Finally, we performed a sensitivity analysis excluding all patients with no admission serum sodium measurement. This allowed us to evaluate the impact of classifying these patients as normonatremic (21).

The study was approved by the Danish Data Protection Agency (2013-41-1924). Data analyses were conducted using STATA Software V.12.1 (STATA, College Station, TX, USA).

Results

Prevalence

From the DNPR, we identified 279 508 patients with an acute admission to a Department of Internal Medicine during the study period. Among these, 254 284 (91.0%) patients had a serum sodium measurement within 24 h of admission. In total, 232 911 (83.3%) patients were categorized as normonatremic. The overall prevalence of hyponatremia at admission was 15.0% (41 803 patients). The proportion of patients in the four hyponatremia categories (130–134.9, 125–129.9, 120–124.9 and <120 mmol/l) was 10.5, 2.9, 0.9 and 0.6% respectively. Characteristics of patients with hyponatremia and normonatremia are shown in Table 1.

Table 1

Characteristics of acute medical inpatients with and without hyponatremiaa. Values are expressed as numbers (percentage) unless otherwise indicated.

Serum sodium level (mmol/l)
HyponatremiaNormonatremia
<120 (n=1773)120–124.9 (n=2573)125–129.9 (n=8170)130–134.9 (n=29 287)135–145 (n=232 921)
Median age (IQR)72 (61–82)70 (60–80)70 (59–81)69 (55–80)61 (43–75)
Gender (female)1136 (64.1)1420 (55.2)4406 (53.9)15 115 (51.6)115 896 (49.8)
CCI level
 Low (CCI score 0)876 (49.4) 1134 (44.1)3593 (44.0)13 735 (46.9)139 106 (59.7)
 Medium (CCI score 1–2)670 (37.8)992 (38.6)3051 (37.4)10 485 (35.8)68 543 (29.4)
 High (CCI score >2)227 (12.8)447 (17.4)1526 (18.7)5067 (17.3)25 263 (10.9)
Specific pre-existing morbidity
 Myocardial infarction76 (4.3)160 (6.2)468 (5.7)1908 (6.5)13 153 (5.7)
 Congestive heart failure75 (4.2)143 (5.6)569 (7.0)1787 (6.1)10 030 (4.3)
 Peripheral vascular disease120 (6.8)207 (8.1)657 (8.0)2170 (7.4)11 523 (5.0)
 Cerebrovascular disease169 (9.5)306 (11.9)927 (11.4)3140 (10.7)19 514 (8.4)
 Dementia21 (1.2)234 (1.3)84 (1.0)305 (1.0)2208 (1.0)
 Chronic pulmonary disease224 (12.6)345 (13.4)1101 (13.5)3768 (12.9)24 006 (10.3)
 Connective tissue disease57 (3.2)116 (4.5)353 (4.3)1301 (4.4)8270 (3.6)
 Ulcer disease150 (8.5)262 (10.2)685 (8.4)2050 (7.0)11 575 (5.0)
 Mild liver disease78 (4.4)112 (4.4)319 (3.9)729 (2.5)3083 (1.3)
 Moderate/severe liver disease16 (0.9)47 (1.8)104 (1.3)221 (0.8)793 (0.3)
 Diabetes 1 and 2129 (7.3)241 (9.4)822 (10.1)2917 (10.0)13 882 (6.0)
 Diabetes with complications59 (3.3)136 (5.3)448 (5.5)1538 (5.3)6954 (3.0)
 Hemiplegia16 (0.9)20 (0.8)52 (0.6)165 (0.6)992 (0.4)
 Moderate/severe renal disease29 (1.6)57 (2.2)251 (3.1)873 (3.0)5292 (2.3)
 Malignant tumor213 (12.0)321 (12.5)1173 (14.4)3962 (13.5)20 879 (9.0)
 Leukaemia4 (0.2)10 (0.4)33 (0.4)122 (0.4)817 (0.4)
 Lymphoma7 (0.4)16 (0.6)87 (1.1)354 (1.2)1693 (0.7)
 Metastatic cancer21 (1.2)51 (2.0)217 (2.7)737 (2.5)2850 (1.2)
 AIDS1 (0.1)2 (0.1)10 (0.1)45 (0.2)218 (0.1)

AIDS, acquired immunodeficiency syndrome; CCI, Charlson comorbidity index; IQR, interquartile range.

Data for patients with serum sodium >145 mmol/l are not displayed.

Table 2 presents prevalence estimates according to age, CCI level and diagnostic groups. The prevalence of hyponatremia increased with age and CCI level. We found hyponatremia to be particularly prevalent in patients with previous liver disease or metastatic cancer, and in patients in whom diabetes, pneumonia, sepsis, kidney disease and liver disease were indicated as the primary reason for hospitalization based on the primary discharge diagnosis. A total of 4794 (1.7%) patients were hypernatremic (serum sodium >145 mmol/l) and therefore excluded from the mortality analyses.

Table 2

Prevalence of hyponatremia overall and by hyponatremia severity according to comorbidity level specific preexisting morbidity and primary discharge diagnosis of acute medical inpatientsa. Values are expressed as numbers (percentage) unless otherwise indicated.

Serum sodium concentration (mmol/l)
Hyponatremia n(%)Normonatremia n(%)
<120120–124.9125–129.9130–134.9Overall135–145
Overall1773 (0.6)2573 (0.9)8170 (2.9)29 287 (10.5)41 803 (15.0)232 911 (83.3)
Age groups (years)
 15–191 (0.0)13 (0.1)70 (0.6)631 (5.5)715 (6.2)10 468 (91.2)
 20–295 (0.0)19 (0.1)114 (0.6)1011 (5.5)1149 (6.2)16 855 (91.5)
 30–3921 (0.1)53 (0.2)240 (1.0)1476 (6.4)1790 (7.7)21 040 (90.8)
 40–49117 (0.4)179 (0.6)572 (1.8)2391 (7.3)3259 (10.0)28 981 (88.5)
 50–59285 (0.7)406 (1.0)1228 (2.9)3979 (9.5)5898 (14.1)35 240 (84.4)
 60–69407 (0.8)629 (1.2)1859 (3.6)5890 (11.4)8785 (17.0)42 443 (81.8)
 70–79420 (0.8)621 (1.2)1930 (3.8)6743 (13.4)9714 (19.3)40 018 (79.3)
 >80517 (1.0)653 (1.3)2157 (4.4)7166 (14.5)10 493 (21.2)37 866 (76.4)
CCI level
 Low (CCI score 0)876 (0.5)1134 (0.7)3593 (2.2)13 735 (8.5)22 026 (12.5)139 106 (86.3)
 Medium (CCI score 1–2)670 (0.8)992 (1.2)3051 (3.6)10 485 (12.3)13 025 (18.5)68 543 (80.4)
 High (CCI score >2)227 (0.7)447 (1.4)1526 (4.6)5067 (15.3)5262 (23.0)25 263 (76.3)
Specific pre-existing morbidity
 Myocardial infarction76 (0.5) 160 (1.0) 468 (2.9)1908 (12.0)2612 (16.3)13 153 (82.2)
 Congestive heart failure75 (0.6)143 (1.1) 569 (4.4)1787 (13.9)2574 (20.0)10 030 (77.9)
 Peripheral vascular disease120 (0.8) 207 (1.4) 657 (4.4)2170 (14.6)3154 (21.2)11 523 (77.3)
 Cerebrovascular disease169 (0.7)306 (1.2)927 (3.8)3140 (12.7)4542 (18.4)19 514 (79.2)
 Dementia21 (0.7)34 (1.2) 84 (2.9)305 (10.7)444 (15.5)2208 (77.3)
 Chronic pulmonary disease224 (0.8)345 (1.2)1101 (3.7) 3768 (12.6) 5438 (18.2)24 006 (80.2)
 Connective tissue disease57 (0.6) 116 (1.1) 353 (3.5) 1301 (12.7)1827 (17.8)8270 (80.8)
 Ulcer disease150 (1.0)262 (1.7) 685 (4.6)2050 (13.6)3147 (20.9)11 575 (77.0)
 Mild liver disease78 (1.8)112 (2.5)319 (7.2)729 (16.5)1238 (28.0)3083 (69.7)
 Moderate/severe liver disease16 (1.3) 47 (3.9)104 (8.6)221 (18.2)388 (32.0)793 (65.4)
 Diabetes 1 and 2129 (0.7)241 (1.3)822 (4.5)2917 (16.0)4109 (22.5)13 882 (76.0)
 Diabetes with complications59 (0.6) 136 (1.5) 448 (4.8)1538 (16.6)2181 (23.6)6954 (75.1)
 Hemiplegia16 (1.2) 20 (1.6) 52 (4.0)165 (12.8)253 (19.6)992 (76.8)
 Moderate/severe renal disease29 (0.4) 57 (0.9)251 (3.8)873 (13.2)1210 (18.2)5292 (79.8)
 Malignant tumor213 (0.8)321 (1.2) 1173 (4.6)3962 (14.7) 5669 (21.0)20 879 (77.5)
 Leukaemia4 (0.4) 10 (1.0)33 (3.3)122 (12.3)169 (17.0)1693 (77.8)
 Lymphoma7 (0.3) 16 (0.7)87 (4.0)354 (16.3)464 (21.3)1203 (75.6)
 Metastatic cancer21 (0.5) 51 (1.3)217 (5.5)737 (18.8)1026 (26.2)2850 (72.9)
 AIDS1 (0.4) 2 (0.7)10 (3.6) 45 (16.3)58 (20.9)218 (78.7)
Primary discharge diagnosis
 Infections295 (0.7)530 (1.2)2132 (4.8)8604 (19.4)11 561 (26.1)32 082 (72.3)
 Pneumonia90 (0.7)183 (1.3)321 (5.4)2809 (20.6)3814 (27.9)9515 (69.7)
 Sepsis38 (1.5)43 (1.7)179 (7.0)631 (24.6)891 (34.7)1582 (61.6)
 Other infections167 (0.6)304 (1.1)1221 (4.3)5164 (18.3)6856 (24.3)20 985 (74.5)
 Cardiovascular disease198 (0.4)390 (0.7)1292 (2.3)4729 (8.4)6609 (11.7)49 173 (87.0)
 Stroke28 (0.3)36 (0.4)170 (2.0)671 (7.9)905 (10.7)7457 (88.1)
 Acute ischemic heart disease48 (0.4)114 (0.8)383 (2.8)1484 (10.8)2029 (14.7)11 636 (84.5)
 Congestive heart failure27 (0.8)56 (1.6)133 (3.8)401 (11.5)617 (17.6)2632 (80.2)
 Other cardiovascular disease95 (0.3)184 (0.6)606 (2.0)2173 (7.1)3058 (9.9)27 266 (88.6)
 Respiratory disease (excl. pneumonia)87 (0.8)140 (1.3)390 (3.6)1267 (11.6)1884 (17.3)8849 (81.0)
 Gastrointestinal disease95 (1.0)157 (1.7)503 (5.4)1321 (14.1)2076 (22.1)7216 (76.8)
 Liver disease41 (3.0)61 (4.5)160 (11.8)311 (22.9)573 (42.1)773 (56.8)
 Other gastrointestinal disease54 (0.7)96 (1.2)343 (4.3)1010 (12.6)1503 (18.7)6443 (80.2)
 Urogenital disease20 (0.7)44 (1.6)147 (5.3)448 (16.2)559 (26.4)2057 (74.2)
 Kidney disease18 (0.9)38 (1.8)124 (5.9)379 (17.9)659 (23.8)1512 (71.3)
 Other urogenital disease2 (0.3)6 (0.9)23 (3.5)69 (10.6)100 (15.4)545 (83.7)
 Endocrine disease637 (5.4)407 (3.5)737 (6.2)2105 (17.8)3886 (32.9)7593 (64.3)
 Diabetes46 (1.0)85 (1.9) 318 (7.1)1173 (26.0)1622 (36.0)2833 (62.9)
 Hypothyroidism3 (2.0)2 (1.4)3 (2.0)11 (7.5)19 (12.9)128 (87.1)
 Hyperthyroidism4 (0.6)1 (0.2)4 (0.6)24 (3.9)36 (5.7)592 (93.2)
 Hyponatremia and hypoosmolality424 (55.1)169 (22.0)101 (13.1)35 (4.6)729 (94.8)38 (4.9)
 Other endocrine disease160 (2.8)160 (2.8)311 (5.4)859 (14.9)1480 (25.8)4002 (69.6)
 Neurologic disease 22 (0.2)78 (0.6)246 (1.9)737 (5.8)1083 (8.5)11 442 (90.2)
 Muscle and connective tissue disease32 (0.3)68 (0.7)202 (2.1)789 (8.2)1091 (11.4)8400 (87.7)
 Cancer46 (0.9)73 (1.4)304 (5.7)948 (17.6)1371 (25.5)3995 (73.5)
 Observation for suspected disease65 (0.2)130 (0.4)504 (1.4)2164 (5.8)2863 (7.7)33 776 (91.2)
 Other276 (0.4)556 (0.7)1713 (2.2)6175 (7.8)8720 (11.0)68 369 (86.5)

AIDS, acquired immunodeficiency syndrome; CCI, Charlson comorbidity index.

Data for patients with serum sodium >145 mmol/l are not displayed.

Mortality

A total of 46 (0.02%) and 464 (0.17%) patients migrated before they could be followed for 30 days or 1 year respectively. In-hospital, 30-day and 1-year mortality were 6.8, 8.1 and 21.5% in patients with hyponatremia, compared to 2.9, 3.6 and 10.6% among patients with normonatremia (Table 3 and Fig. 1). Absolute mortality was increased in all categories of hyponatremia. The higher mortality risk in patients with hyponatremia of any severity compared to normonatremic patients persisted after controlling for age, gender and previous morbidities, yielding adjusted RRs at 30 days of 1.4 (95% CI: 1.3–1.4), 1.7 (95% CI: 1.6–1.8), 1.7 (95% CI: 1.4–1.9) and 1.3 (95% CI: 1.1–1.5) for sodium levels of 130–134.9, 125–129.9, 120–124.9 and <120 mmol/l respectively. At 1 year, the corresponding RRs were 1.3 (95% CI: 1.3–1.3), 1.4 (95% CI: 1.4–1.5), 1.4 (95% CI: 1.3–1.5) and 1.3 (95% CI: 1.1–1.4) respectively (Table 3). A secondary analysis of patients with serum sodium <120 mmol/l showed a further decrease in 30-day RR with decreasing serum sodium levels (RRs of 1.4 (95% CI: 1.1–1.8), 1.1 (95% CI: 0.8–1.6) and 1.1 (95% CI: 0.7–1.8) for sodium levels of 115–119.9, 110–114.9 and <110 mmol/l respectively). Similar results were observed for in-hospital mortality and at 1 year (Supplementary Table 1, see section on supplementary data given at the end of this article).

Table 3

Thirty-day and 1-year cumulative mortality and crude and adjusted RRs stratified by serum sodium concentration at hospital admission.

Serum sodium level (mmol/l)Total (n)30-day mortality1-year mortality
Deaths (n)Cumulative mortality (95% CI)Crude RR (95% CI)Adjusted RRa (95% CI)Deaths (n)Cumulative mortality (95% CI)Crude RR (95% CI)Adjusted RRa (95% CI)
Normonatremia 232 91182753.6 (3.5–3.6)1 (ref.)1 (ref.)23 56110.6 (10.4–10.7)1 (ref.)1 (ref.)
Hyponatremia overall 41 803 3387 8.1 (7.9–8.4) 2.3 (2.2–2.4) 1.5 (1.4–1.5) 871121.5 (21.2–22.0) 2.0 (2.0–2.1) 1.3 (1.3–1.4)
Hyponatremia category
 130–134.929 28721337.3 (7.0–7.6)2.1 (2.0–2.1)1.4 (1.3–1.4)571520.2 (19.8–20.7)1.9 (1.9–2.0)1.3 (1.3–1.3)
 125–129.9 817081810.0 (9.4–10.7)2.8 (2.6–3.0)1.7 (1.6–1.8)196724.8 (23.8–25.7)2.4 (2.3–2.4)1.4 (1.4–1.5)
 120–124.9 2573 26610.4 (9.2–11.6)2.9 (2.6–3.3)1.7 (1.4–1.9)61724.7 (23.0–26.4)2.3 (2.2–2.5)1.4 (1.3–1.5)
 <12017731709.6 (8.3–11.1)2.7 (2.3–3.1)1.3 (1.1–1.5)41223.9 (22.0–26.0) 2.3 (2.1–2.5)1.3 (1.1–1.4)

RR, relative risk.

Adjusted for age group, gender and history of specific morbidities included in the CCI.

Figure 1
Figure 1

(A) Thirty-day and (B) 1-year cumulative mortality according to categories of serum sodium concentration at hospital admission.

Citation: European Journal of Endocrinology 173, 1; 10.1530/EJE-15-0111

Serum sodium concentrations of 139 to 141 mmol/l were associated with the lowest risk of death, based on the restricted cubic spline models (Fig. 2). A steep increase in predicted 30-day and 1-year mortality was observed with decreasing sodium levels, until the level dropped below 132 mmol/l. After this point, only minor increases were observed. Controlling for the confounding effects of age, gender and previous morbidities resulted in the curve further plateauing below this point.

Figure 2
Figure 2

Crude and adjusted* predicted probability of (A) 30-day and (B) 1-year mortality as a function of admission serum sodium concentration. *Adjusted for age group, gender and history of specific morbidities included in the Charlson comorbidity index. The gray area represents the 95% CI.

Citation: European Journal of Endocrinology 173, 1; 10.1530/EJE-15-0111

Serum sodium was not measured within 24 h of admission in 25 224 patients. These patients were younger and had slightly lower CCI scores than patients with normonatremia (Supplementary Table 2, see section on supplementary data given at the end of this article). Excluding patients without admission serum sodium measurement had only a limited effect on absolute mortality and risk estimates (Supplementary Table 3).

Mortality risk according to diagnostic groups

Patients with hyponatremia had increased 30-day mortality across virtually all major categories of primary discharge diagnoses compared to patients with normonatremia (Fig. 3A and see Supplementary Table 4, see section on supplementary data given at the end of this article for RR estimates by hyponatremia category stratified by diagnostic group). One exception was the category of endocrine disease; patients given a primary discharge diagnosis of ‘hyponatremia and hypoosmolality’ had an RR of 0.2 (95% CI: 0.1–1.1). Notably, hyponatremic patients with an unspecific diagnosis of ‘observation for suspected disease’ had more than a twofold increased risk of death within 30 days of admission. In contrast to the overall findings, mortality risk increased with increasing hyponatremia severity in patients with a primary discharge diagnosis of sepsis (from 0.9 (95% CI: 0.7–1.1) for sodium levels of 130–134.9 mmol/l to 1.9 (95% CI: 1.2–3.0) for sodium levels <120 mmol/l), respiratory disease (from 1.2 (95% CI: 1.0–1.4) for sodium levels of 130–134.9 mmol/l to 2.9 (95% CI: 1.9–4.3) for sodium levels <120 mmol/l), liver disease (from 1.1 (95% CI: 0.8–1.6) for sodium levels of 130–134.9 mmol/l to 2.6 (95% CI: 1.5–4.6) for sodium levels <120 mmol/l) and cancer (from 1.4 (95% CI: 1.3–1.6) for sodium levels of 130–134.9 mmol/l to 1.9 (95% CI: 1.2–3.0) for sodium levels <120 mmol/l) (see Supplementary Table 4 for further details).

Figure 3
Figure 3

Adjusted 30-day relative risk (RR) of death among patients with hyponatremia compared to patients with normonatremia, stratified by diagnostic groups. Adjusted for (A) age group, gender and Charlson comorbidity index (CCI) level, (B) age group, gender and CCI level (excl. the specific morbidity) and (C) age group and gender. Subgroups with too few events to yield meaningful estimates were left out.

Citation: European Journal of Endocrinology 173, 1; 10.1530/EJE-15-0111

Hyponatremia was associated with increased risk of death among patients in most groups of previous morbidity (Fig. 3B and C). Overall, the RR increased with increasing CCI level. However, when we computed RRs for each hyponatremia category separately within each stratum of CCI level, we found that RRs decreased with increasing CCI level for patients with serum sodium <120 mmol/l (Supplementary Table 4).

Discussion

In this large population-based cohort study in a hospital setting with complete follow-up, hyponatremia was present at admission in nearly one of seven patients. Any degree of hyponatremia was associated with increased short- and long-term mortality compared to normonatremia. For hyponatremic serum sodium values, a biphasic dose–response relation was observed. The probability of death increased with decreasing serum sodium until a threshold of 132 mmol/l, below which there was no further increase in mortality. Mortality risk was increased across virtually all major primary discharge diagnosis groups and categories of previous morbidity.

As indicated by the divergent results of previous studies, the prevalence of hyponatremia is highly influenced by study population composition (4, 12), criteria applied to define hyponatremia at hospital admission (3, 4), and composition of the denominator (i.e. whether only patients for whom serum sodium was measured were included) (3, 4, 6, 12). The 15% overall prevalence of hyponatremia observed in our study is comparable with that observed among 2171 internal medicine patients in a recent single-center study (5). Furthermore, the prevalence among patients hospitalized with chronic heart failure (7), acute myocardial infarction (22), ischemic stroke (23) and pneumonia (24) concurs with previous reports. The in-hospital mortality in our study was equivalent to previous reports applying the same definition for hyponatremia (4, 12, 13).

Our study challenges the hypothesis that mortality risk attributed to hyponatremia continues to increase when serum sodium decreases, as found by Wald et al. (13) among hospitalized patients in general and by Kovesdy et al. (9) among patients with chronic kidney disease. Notably, these studies were based on very few (∼10 or less) deaths among patients with serum sodium <120 mmol/l. In contrast, we found that decrease in serum sodium below a threshold of 132 mmol/l, did not contribute to further increase in overall mortality risk. However, in the stratified analysis, we did find that mortality risk increased by hyponatremia severity in patients with a primary diagnosis of cancer, liver disease, respiratory disease and sepsis. Still, <25 deaths were observed in the two lower hyponatremia categories for each of the patient subgroups, and cautious interpretation about the pattern of the dose–response relation in these patients is needed.

We utilized prospective, independently collected data without restrictions on patients' sodium measurements at admission (4, 12, 13, 14) or on length of hospitalizations (4), thereby essentially eliminating the risk of selection bias. The study also benefitted from the long-term and virtually complete follow-up provided by registry data (15, 16, 25). Importantly, our large study population allowed us to examine the mortality risk associated with different levels of hyponatremia and across numerous diagnostic groups, while controlling for important confounders. Hyperglycemia causes osmotic shift of water out of cells, which can potentially result in hyponatremia. Some previous studies have applied a correction factor to the measured serum sodium concentration in the presence of hyperglycemia. In the present study, we aimed to examine the prognostic impact of low serum sodium concentration regardless of cause, and therefore refrained from such correction. Adjusting for the ICD10 discharge diagnosis for hyperglycemia and ketoacidosis associated with the current admission (n=559) had no influence on RR estimates (data not shown), consistent with findings of studies in which a correction factor was used (4, 14).

Some limitations should be considered when interpreting our results. By assigning patients with no admission sodium measurement to the normonatremic group, we may have misclassified some patients with hyponatremia. However, we believe the effect of this potential bias is small. Generally, serum sodium is measured for a wide range of indications and the mortality rate in patients lacking admission laboratory measurements has been found to resemble that of patients with laboratory test results within reference values (26). Furthermore, the misclassification of some patients with undetected hyponatremia as normonatremic would likely be non-differential with regard to outcome and would bias our results towards the null, as supported by the results of our sensitivity analyses. Another limitation was our inability to measure the severity of illness during hospitalization. Finally, we cannot rule out residual confounding through our use of ICD10 discharge diagnoses recorded in the DNPR to categorize patients into diagnostic groups (27, 28, 29). Thirty-eight patients categorized as normonatremic had received a primary diagnosis of ‘hyponatremia and hypoosmolality’. Among these, only nine patients developed hyponatremia during hospitalization. For the remaining patients, it is possible that a hyponatremic serum sodium value, measured at the request of the general practitioner, had triggered hospitalization. However, we cannot dismiss coding error as an alternative explanation.

A possible mechanism for the increased mortality associated with hyponatremia independent of underlying disease, and for the overall absence of further increase in mortality risk when serum sodium decreased below 132 mmol/l, may be hyponatremia-induced oxidative stress (30). It is possible that even small decreases in serum sodium below 139 mmol/l may be sufficient to induce accumulation of free oxygen radicals and thereby induce damage to proteins, lipids and DNA. A growing body of evidence indicates that inflammatory mediators, such as interleukins 1 and 6, can induce hyponatremia through excessive vasopressin release (31, 32). This could explain the potential lower mortality observed in patients with serum sodium <120 mmol/l, among who a large proportion is believed to have hyponatremia caused by medication rather than severe underlying disease, and consequently a lower level of inflammation (14). In support of this hypothesis, one-quarter (n=424) of patients with serum sodium <120 mmol/l had a primary discharge diagnosis of ‘hyponatremia and hypoosmolality’. Given the very low sensitivity of this ICD10 discharge diagnosis even in severe hyponatremia (34% for serum sodium values ≤115 mmol/l), this could indicate absence of other critical morbidities (33). Alternatively, assignment of the ‘hyponatremia and hypoosmolality’ diagnosis could indicate that active steps to correct hyponatremia were taken. However, it was beyond the scope of this study to examine whether the lower mortality observed in patients with serum sodium <120 mmol/l could be attributed to treatment of hyponatremia.

Discussion of possible underlying mechanisms should not divert attention from the finding that hyponatremia at admission, regardless of severity, is associated with a poor prognosis in patients acutely admitted with medical disorders. Our study clarifies the clinical course of hyponatremia and underscores the pronounced negative impact of even mild hyponatremia at hospital admission on mortality risk. Sodium measurement should be considered in future risk stratification models for acute medical patients.

Supplementary data

This is linked to the online version of the paper at http://dx.doi.org/10.1530/EJE-15-0111.

Declaration of interest

Prof. J O L Jørgensen received an unrestricted research grant from Otsuka Pharma Scandinavia AB for the submitted work. L Holland-Bill and J O L Jørgensen have received lecture fees from Otsuka Pharma Scandinavia AB. L Holland-Bill, C F Christiansen, U Heide-Jørgensen and S P Ulrichsen are employees at the Department of Clinical Epidemiology, Aarhus University Hospital. The Department of Clinical Epidemiology, Aarhus University Hospital receives funding from companies in the form of research grants to (and administered by) Aarhus University. There are no other relationships or activities that could appear to have influenced the submitted work.

Funding

The study was supported by the Program for Clinical Research Infrastructure (PROCRIN) established by the Lundbeck Foundation and the Novo Nordisk Foundation, by a grant from the Aarhus University Research Foundation, and by an unrestricted research grant from Otsuka Pharma Scandinavia AB to Prof. J O L Jørgensen. The funding sources had no role in the design and conduct of the study; the collection, management, analysis and interpretation of the data; the preparation, review or approval of the manuscript; or the decision to submit the manuscript for publication.

Author contribution statement

L Holland-Bill, C F Christiansen, T Ring, J O L Jørgensen and H T Sørensen contributed to conception and design of the study. U Heide-Jørgensen and S P Ulrichsen acquired the data. L Holland-Bill conducted the statistical analyses. All authors contributed to the interpretation of data and in drafting the manuscript. All authors critically revised and approved the final version for submission. All authors had full access to the data in the study, and can take responsibility for the integrity of the data and accuracy of data analysis. L Holland-Bill is the guarantor for the study.

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  • View in gallery

    (A) Thirty-day and (B) 1-year cumulative mortality according to categories of serum sodium concentration at hospital admission.

  • View in gallery

    Crude and adjusted* predicted probability of (A) 30-day and (B) 1-year mortality as a function of admission serum sodium concentration. *Adjusted for age group, gender and history of specific morbidities included in the Charlson comorbidity index. The gray area represents the 95% CI.

  • View in gallery

    Adjusted 30-day relative risk (RR) of death among patients with hyponatremia compared to patients with normonatremia, stratified by diagnostic groups. Adjusted for (A) age group, gender and Charlson comorbidity index (CCI) level, (B) age group, gender and CCI level (excl. the specific morbidity) and (C) age group and gender. Subgroups with too few events to yield meaningful estimates were left out.

  • 1

    Grann AF, Erichsen R, Nielsen AG, Froslev T, Thomsen RW. Existing data sources for clinical epidemiology: the clinical laboratory information system (LABKA) research database at Aarhus University, Denmark. Clinical Epidemiology 2011 3 133138. (doi:10.2147/CLEP.S17901).

    • Search Google Scholar
    • Export Citation
  • 2

    Rose BD, Post TW. Clinical physiology of acid-base and electrolyte disorders. 5th ed. New York, NY: McGraw-Hill 2001 241–298, 696–745

  • 3

    Zilberberg MD, Exuzides A, Spalding J, Foreman A, Jones AG, Colby C, Shorr AF. Epidemiology, clinical and economic outcomes of admission hyponatremia among hospitalized patients. Current Medical Research and Opinion 2008 24 16011608. (doi:10.1185/03007990802081675).

    • Search Google Scholar
    • Export Citation
  • 4

    Waikar SS, Mount DB, Curhan GC. Mortality after hospitalization with mild, moderate, and severe hyponatremia. American Journal of Medicine 2009 122 857865. (doi:10.1016/j.amjmed.2009.01.027).

    • Search Google Scholar
    • Export Citation
  • 5

    Sturdik I, Adamcova M, Kollerova J, Koller T, Zelinkova Z, Payer J. Hyponatraemia is an independent predictor of in-hospital mortality. European Journal of Internal Medicine 2014 25 379382. (doi:10.1016/j.ejim.2014.02.002).

    • Search Google Scholar
    • Export Citation
  • 6

    Frenkel WN, van den Born BJ, van Munster BC, Korevaar JC, Levi M, de Rooij SE. The association between serum sodium levels at time of admission and mortality and morbidity in acutely admitted elderly patients: a prospective cohort study. Journal of the American Geriatrics Society 2010 58 22272228. (doi:10.1111/j.1532-5415.2010.03104.x).

    • Search Google Scholar
    • Export Citation
  • 7

    Gheorghiade M, Abraham WT, Albert NM, Gattis Stough W, Greenberg BH, O'Connor CM, She L, Yancy CW, Young J, Fonarow GC. Relationship between admission serum sodium concentration and clinical outcomes in patients hospitalized for heart failure: an analysis from the OPTIMIZE-HF registry. European Heart Journal 2007 28 980988. (doi:10.1093/eurheartj/ehl542).

    • Search Google Scholar
    • Export Citation
  • 8

    Doshi SM, Shah P, Lei X, Lahoti A, Salahudeen AK. Hyponatremia in hospitalized cancer patients and its impact on clinical outcomes. American Journal of Kidney Diseases 2012 59 222228. (doi:10.1053/j.ajkd.2011.08.029).

    • Search Google Scholar
    • Export Citation
  • 9

    Kovesdy CP, Lott EH, Lu JL, Malakauskas SM, Ma JZ, Molnar MZ, Kalantar-Zadeh K. Hyponatremia, hypernatremia and mortality in patients with chronic kidney disease with and without congestive heart failure. Circulation 2012 125 677684. (doi:10.1161/CIRCULATIONAHA.111.065391).

    • Search Google Scholar
    • Export Citation
  • 10

    Waikar SS, Curhan GC, Brunelli SM. Mortality associated with low serum sodium concentration in maintenance hemodialysis. American Journal of Medicine 2011 124 7784. (doi:10.1016/j.amjmed.2010.07.029).

    • Search Google Scholar
    • Export Citation
  • 11

    Jenq CC, Tsai MH, Tian YC, Chang MY, Lin CY, Lien JM, Chen YC, Fang JT, Chen PC, Yang CW. Serum sodium predicts prognosis in critically ill cirrhotic patients. Journal of Clinical Gastroenterology 2010 44 220226. (doi:10.1097/MCG.0b013e3181aabbcd).

    • Search Google Scholar
    • Export Citation
  • 12

    Whelan B, Bennett K, O'Riordan D, Silke B. Serum sodium as a risk factor for in-hospital mortality in acute unselected general medical patients. QJM: Monthly Journal of the Association of Physicians 2009 102 175182. (doi:10.1093/qjmed/hcn165).

    • Search Google Scholar
    • Export Citation
  • 13

    Wald R, Jaber BL, Price LL, Upadhyay A, Madias NE. Impact of hospital-associated hyponatremia on selected outcomes. Archives of Internal Medicine 2010 170 294302. (doi:10.1001/archinternmed.2009.513).

    • Search Google Scholar
    • Export Citation
  • 14

    Chawla A, Sterns RH, Nigwekar SU, Cappuccio JD. Mortality and serum sodium: do patients die from or with hyponatremia? Clinical Journal of the American Society of Nephrology 2011 6 960965. (doi:10.2215/CJN.10101110).

    • Search Google Scholar
    • Export Citation
  • 15

    Schmidt M, Pedersen L, Sorensen HT. The Danish Civil Registration System as a tool in epidemiology. European Journal of Epidemiology 2014 29 541549. (doi:10.1007/s10654-014-9930-3).

    • Search Google Scholar
    • Export Citation
  • 16

    Lynge E, Sandegaard JL, Rebolj M. The Danish National Patient Register. Scandinavian Journal of Public Health 2011 39 3033. (doi:10.1177/1403494811401482).

    • Search Google Scholar
    • Export Citation
  • 17

    Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of Chronic Diseases 1987 40 373383. (doi:10.1016/0021-9681(87)90171-8).

    • Search Google Scholar
    • Export Citation
  • 18

    Frenkel WJ, Jongerius EJ, Mandjes-van Uitert MJ, van Munster BC, de Rooij SE. Validation of the Charlson comorbidity index in acutely hospitalized elderly adults: a prospective cohort study. Journal of the American Geriatrics Society 2014 62 342346. (doi:10.1111/jgs.12635).

    • Search Google Scholar
    • Export Citation
  • 19

    Parner E, Andersen P. Regression analysis of censored data using pseudo-observations. Stata Journal 2010 10 408422.

  • 20

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