1 Introduction
Serum sodium concentrations (NaC) <135 mmol/l (hyponatremia) are observed in up to 50% of older patients admitted to hospital [
1,
2]. The high prevalence of this electrolyte abnormality in older hospitalized patients might be secondary to the presence of one, or more, disease states characterized by alterations in sodium and water balance, impaired homeostasis, and polypharmacy, as well as in-hospital iatrogenic interventions [
3]. There is increasing evidence that lower NaC values are independently associated with adverse clinical outcomes in old age [
3]. More specifically, they predict loss of independence, increased length of stay, and mortality in older hospitalized patients [
4‐
6].
Several drugs and drug classes, e.g., diuretics, antidepressants, and antiepileptics, are known to reduce NaC. Proposed mechanisms for these reductions include alterations in sodium and water homeostasis, potentiation of the physiological effects of the antidiuretic hormone, and resetting of control mechanisms located in the hypothalamus [
7]. However, it is possible that associations between NaC and the use of diuretics, antidepressants, antiepileptics, and other drug classes are at least partly explained by the disease state for which these drugs are prescribed in the first instance [
8].
The increased risk of hyponatremia, an independent predictor of adverse outcomes in the older population, with several commonly prescribed drugs warrants regular medication reviews to prevent and rectify this electrolyte abnormality, potentially improving outcomes in this group [
3]. However, investigating associations between drugs and NaC in patients with concomitant prescribed medications and multiple disease states presents significant challenges. In particular, it is extremely difficult to disentangle the independent effects on NaC of individual drugs and other clinical and demographic parameters [
7]. One methodological approach that might be useful in simplifying the problem of trying to identify likely associations between drugs and NaC is to group individuals by their most distinctive patterns of medication use, typically using two to four groups to make interpretation easier. If examination of the resulting classes reveals a very high probability of either using or avoiding a particular medication, this raises the possibility that any observed differences in clinical characteristics (such as NaC) between the classes may partly be due to use of that medication. Such an approach also helps increase the external validity and clinical relevance of the study since, in the real world, older patients generally take a multitude of medications, which is captured in the resulting groups.
To investigate the independent associations between drug use and NaC in older hospitalized patients, we applied a clustering technique known as latent class analysis (LCA) to identify specific patterns of drug use. We then determined whether these patterns were associated with lower NaC.
4 Discussion
We used LCA to characterize patterns of drug use in a consecutive series of older patients admitted to general medicine wards and subsequently discharged to an aged care facility. We observed significant differences in NaC according to the pattern of medication use. Patterns that reflected a high probability of antiplatelet or anticoagulant medication use had lower NaC values than patterns of lower overall medication anticoagulant use. Although patients who used anticoagulants generally had a slightly higher overall pattern of use and reduced likelihood of antiplatelet or medication use, our findings remained consistent after adjusting for DBI and CCI score, age, eGFR, and digoxin use. In addition, age, CCI score, and eGFR were also independently associated with NaC, which strengthens the validity of the study given that these factors are all known confounders. The similar results obtained when assessing NaC on admission rather than the mean concentrations during hospitalization further supports the presence of independent associations between lower NaC and antiplatelet drugs and anticoagulants. Our approach enabled us to take account for the general background of multiple medication use and comorbidities that typically exists among older patients. It also revealed significant associations that could not be identified when these medications were assessed for association in isolation.
A number of reviews have elegantly discussed the available evidence of the causative role of several drugs on the risk of hyponatremia, particularly in older patients [
3,
7,
12]. However, a substantial number of studies (1) comprised small population groups and case reports, (2) included patients only receiving the investigated drug, and (3) did not ascertain the potential contributing role of other clinical and demographic characteristics on the incidence of hyponatremia [
3,
7,
12]. These issues are particularly relevant in older patients with multiple disease states and polypharmacy.
We observed significant independent associations between lower NaC and the patterns of drug use characterized by the concomitant use of antiplatelet and anticoagulant drugs. By contrast, no associations were observed with drugs previously reported as causing hyponatremia, such as proton pump inhibitors, oral hypoglycemics, diuretics, inhibitors of the renin-angiotensin system, antipsychotics, and antidepressants [
13‐
18]. To the best of our knowledge, this is the first report to describe an independent association between patterns of drug use dominated by the use of antiplatelet drugs and anticoagulants and lower NaC. Both classes of drugs are routinely prescribed in primary and secondary cardiovascular prevention as well as in other pro-thrombotic states. The high prevalence of disease states associated
per se with lower NaC in patients prescribed either antiplatelet drugs or anticoagulants, e.g., heart failure, renal failure, and fluid overload, might potentially explain our findings. In other words, the association between NaC and antiplatelet drugs and anticoagulants might represent confounding by indication. However, this hypothesis is not supported by the lack of associations observed in our study between lower NaC and other drugs often co-prescribed with antiplatelet drugs and/or anticoagulants, e.g., statins, oral hypoglycemics, diuretics, inhibitors of the renin-angiotensin system, and beta-blockers. Confirmation is required in larger studies in different populations, and further research is also required to identify the mechanisms responsible for a possible effect of antiplatelet drugs and anticoagulants on sodium homeostasis.
Increasing age and higher eGFR were also associated with lower NaC. A negative association between age and NaC has been previously reported in older patients presenting to hospital. In multivariate regression analysis, Lindner et al. [
19] observed that both age >60 years (OR 2.5, 95% CI 1.9–3.0,
p < 0.001) and use of diuretics (OR 1.9, 95% CI 1.7–2.2,
p < 0.001) were independently associated with hyponatremia in 20,667 patients attending the emergency department. In this study, the strong negative association between age and NaC was also observed in patients not treated with diuretics [
19]. It is therefore possible that ageing
per se causes alterations of sodium and water homeostasis either peripherally, e.g., kidney, or centrally, e.g., osmotic receptors in the hypothalamus [
20]. Chronic kidney disease, hence a reduced eGFR, is associated with an increased incidence of either hypo- or hypernatremia [
21]. A large population study by Kovesdy et al. [
22] investigated the prevalence of hyponatremia and hypernatremia in 655,493 US veterans according to the different stages of chronic kidney disease. Overall, the prevalence of hyponatremia was higher than that of hypernatremia (13.5 vs. 2.0%). Interestingly, the relative prevalence of hyponatremia was higher in the early stages of chronic kidney disease, whereas the prevalence of hypernatremia was higher in the more advanced stages [
22]. Unlike our study, Kovesdy et al. [
22] included both inpatient and outpatient populations. Moreover, no multivariate analysis was performed to assess independent associations between eGFR and NaC. Further studies in larger patient populations are required to confirm the presence of an independent association between higher eGFR and hyponatremia in older hospitalized patients.
Our conclusions rely partly on being able to accurately characterize the three latent classes that were first determined based on statistical analysis alone. Although there was some overlap in medication use across classes, almost all subjects in class 2 used anticoagulants, almost all subjects in class 3 used antiplatelets, no subjects in class 1 used anticoagulants, and only three in class 1 used antiplatelets. Therefore, identifying the main distinguishing feature of each class was straightforward, increasing the likelihood that the observed differences in NaC between classes may have been due to differences in the use of these two medications.
The study has a number of limitations. Only a fairly limited number of clinical variables were assessed. Therefore, the possibility of unobserved residual confounding remains. In addition, we did not have information on the primary diagnosis at presentation. Although the latter might have affected NaC per se during hospitalization, this would only cause biased estimates for the associations if there was an imbalance in conditions associated with lower NaC across the three classes. In addition, although all subjects in class 2 used anticoagulants, they also had a slightly higher medication use overall. However, adjusting for either the number of medications used or the DBI score did not alter our findings. Our sample size was fairly small, and information on eGFR was missing for some subjects. This means that a larger sample size may have enabled us to observe a significant difference in NaC between individuals in classes 2 and 3. However, the mean marginal difference of approximately 1.1 mmol/l is unlikely to be clinically significant. We have no data on how and when medications were changed after admission or how prescribing changes affected NaC and vice versa. Similarly, we were unable to discriminate between short-term and chronic use medications upon admission. However, our sensitivity analyses on NaC on admission confirm the presence of independent associations between lower NaC and antiplatelet drugs and anticoagulants. A further limitation was that we conducted our study in a single hospital using admissions between November and April, inclusively. Therefore, our results need to be replicated in larger multicentre studies, using admissions from a non-summer period, before they can be made more generalizable. Finally, since our study was cross-sectional in nature, we cannot be sure of whether or not the observed associations were causal. However, it is unlikely that low NaC or a disease state associated with hyponatremia would be an indicator for the use of antiplatelet drugs or anticoagulants.
The study also has a number of strengths. Attempting to assess the impact of individual medications on NaC is often problematic because of the observational nature of studies as well as the presence of polypharmacy and multiple disease states in older patients. Using LCA allows a ‘subject-focused’ as opposed to a ‘variable-based’ approach, which tries to assess the impact of individual variables. We were also able to use multiple measures of NaC for each individual patient, thereby increasing the accuracy of the true underlying NaC for each individual. Finally, we were able to adjust for several important clinical and demographic variables that may influence the association between medication use and NaC, including age and eGFR, which were also associated with NaC.