Risk Factors for Incident Hyponatremia in Skilled Nursing Facility Residents: A Retrospective Cohort Study

Risk Factors for Incident Hyponatremia in Skilled Nursing Facility Residents: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Risk Factors for Incident Hyponatremia in Skilled Nursing Facility Residents: A Retrospective Cohort Study Daniel Mead, Timothy Mallers, Ian Rios, Emily Ho This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9200734/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 14 You are reading this latest preprint version Abstract Background Hyponatremia has long been recognized as a common electrolyte abnormality among skilled nursing facility (SNF) residents. In the literature, hyponatremia is associated with increases in falls, cognitive impairment, hospitalization, and increased mortality. Although many medical conditions and medications contribute to hyponatremia risk, the role of enteral feeding tubes in this population has not been well defined in clinical practice. This study examined the association between enteral feeding tube use and incident hyponatremia and evaluated selected chronic conditions and medication exposures in SNF patients. Methods We conducted a retrospective cohort study using secondary data from a suburban skilled nursing facility. Adults aged ≥ 18 years residing in the SNF with available laboratory data were included (n = 1,256). Exposures included presence of an enteral feeding tube at admission, selected chronic conditions, and high-risk medication exposures. The primary outcome was incident hyponatremia, defined as any corrected serum sodium value < 135 mEq/L occurring after admission. Relative risks were estimated using modified Poisson regression. Results Incident hyponatremia occurred in 34.6% of residents. In adjusted models, enteral feeding tubes (aRR 2.42; 95% CI 1.84–3.19), chronic kidney disease (aRR 1.87; 95% CI 1.43–2.44), and Liver Disease (aRR 1.58; 95% CI 1.20–2.07) remained the significant independent predictors. Congestive Heart Failure, ethnicity, sex, age, and high-risk medication exposure were not significantly associated with risk at the predetermined alpha = 0.01, and no significant interactions were observed between CKD, CHF, and liver disease and enteral feeding tubes on incident hyponatremia. Conclusions Hyponatremia remains a common electrolyte abnormality among SNF residents. Enteral feeding tube use was strongly associated with increased cumulative risk of incident hyponatremia. Both CKD and liver disease also pose risk of incident hyponatremia. SNF residents with enteral feeding tubes may benefit from targeted monitoring and risk stratification in long-term care settings. Clinicians should be aware of these risks while ordering water flushing of enteral tubes and assess these patients regularly for hyponatremia. 1. Introduction and Background Hyponatremia is often encountered in clinical practice and has a higher prevalence in geriatric clinical practice. A particularly high-risk subgroup for hyponatremia are those living in skilled nursing facilities (SNF) with estimates between 15–30% of patients in these settings having an existing diagnosis of hyponatremia [ 1 – 5 ]. Prior cross-sectional and longitudinal studies have shown a higher prevalence of hyponatremia in SNF residents relative to community-dwelling older adults, which indicate a prevalence of hyponatremia at 7–11% [ 6 , 7 ]. Clinical and epidemiological studies consistently link hyponatremia to adverse clinical outcomes, including generalized weakness, falls, fractures, cognitive impairment, hospitalization, and increased mortality [ 8 – 13 ]. Mortality is increased both in-hospital (17.4%) and at 1 year (28.3–41%) compared to eunatremic patients [ 12 , 14 ]. In patients with the diagnosis of Heart Failure with preserved Ejection Fraction (HFpEF), hyponatremia predicts all-cause mortality, rehospitalization, and stroke [ 15 ]. The risk of hyponatremia in this population reflects the intersection of aging, multimorbidity, and care-related exposures, including chronic disease burden and institutional management of fluids and nutrition. Despite its frequency and clinical impact, hyponatremia in SNFs remains under-characterized, particularly with respect to modifiable risk factors and care practices. No large-scale studies yet quantify this risk in skilled nursing populations, creating a gap in clinical knowledge. Accordingly, this study aimed to characterize the burden of hyponatremia in skilled nursing facilities and to examine whether enteral feeding tube use and selected chronic diseases are associated with increased risk of hyponatremia in this population. Review of Literature A search of available literature was done on November 3rd, 2024 within the PubMed and CINAHL databases. Filters were set at 5 years and academic journals only. The keyword items were hyponatremia, geriatric, older adult, elderly, enteral feeding, tube feeding, enteral nutrition, gastric feeding, and skilled nursing. With the specified search terms and filters applied, PubMed yielded 96 records related to geriatrics and an additional 40 records related to enteral feeding terms, while 17 records were identified in CINAHL. 15 studies were selected to review. An additional search used a larger timeframe of 30 years, which found another 7 studies. The final selection included 22 articles. Major themes found in the literature were hyponatremia incidence and prevalence in SNFs, hyponatremia risk factors for the elderly, potential association of hyponatremia and enteral feeding, and clinical tools and monitoring of hyponatremia. Incidence and Prevalence in SNFs As previously mentioned, the general estimation of hyponatremia varies by study, but is generally found to be between 15–30% with malnourished patients potentially having higher risk [ 1 – 5 , 12 , 13 ]. In two older studies from Miller [ 4 ] (1995) and Kugler & Hustead [ 2 ] (2000), up to half of the samples had at least one incident lab value showing hyponatremia in the year before data collection occurred. Risk factors in the Elderly Several main risk factors were identified in the literature for incident hyponatremia. These factors can be subcategorized into 1) Medication-related factors (e.g., thiazide diuretics, antidepressants, antipsychotics, anticonvulsants, and prolonged proton pump inhibitor use) [ 1 , 2 , 16 – 19 ], 2) cardiac, renal, and hepatic disease comorbidities [ 1 , 14 – 16 , 19 , 20 ], 3) low solute intake or malnutrition [ 1 , 5 , 10 , 11 , 19 ], 4) acute illness [ 1 , 8 , 19 , 21 , 22 ], 5) age-related renal and hormonal changes [ 1 , 2 , 16 ], 6) SIADH and non-osmotic ADH release [ 1 , 4 , 19 , 22 ], and 7) institutional care factors [ 5 , 19 ]. Potential Association of Hyponatremia and Enteral Feeding Some data suggests patients with enteral feeding tubes are at high risk of hyponatremia due to poor solute intake and high free water administration [ 1 , 2 , 5 , 16 , 19 ]. One study by Rajarajewwari et al. [ 23 ] (2023) reported a negative correlation between the Identification of Seniors at Risk (ISAR) Scoring tool and hyponatremia severity. This may suggest clinical utility of ISAR for risk stratification screening for hyponatremia. Main Takeaway Despite the common occurrence of and extensive literature describing hyponatremia in older adults, few studies have examined enteral feeding as a major risk factor for incident hyponatremia within skilled nursing facilities. 2. Methods Study Design and Setting Data was collected and analyzed as a quantitative secondary analysis using a retrospective cohort design. All data collection was done by the principal investigator at a single suburban skilled nursing facility (SNF) between May and July 2025. The facility serves a predominantly White population and receives nationwide referrals for in-house dialysis, ventilator care, and subacute rehabilitation services. All data were deidentified at the time of collection. Study Population and Eligibility Criteria Inclusion criteria consisted of current or prior residence at the facility, age ≥ 18 years, and availability of at least annual laboratory data. Exclusion criteria included history of hyponatremia (documented serum sodium < 135 mEq/L prior to or at the time of index admission), pituitary tumors, total parenteral nutrition, diagnosed syndrome of inappropriate antidiuretic hormone secretion (SIADH), hypothyroidism, adrenal insufficiency, or chronic scheduled intravenous fluid administration. Exposure and Covariates Enteral feeding tube presence was defined as present or not present on admission and was considered a baseline exposure. Chronic kidney disease (CKD), congestive heart failure (CHF), liver cirrhosis, and high-risk medication use were examined as exposure variables. Demographic variables, including age, sex, race, and ethnicity, were included as covariates. High-risk medications were handled using an attempt-to-treat approach. Participants were classified as exposed if they were prescribed any agent within the following medication classes on admission: antidepressants, antiepileptics, thiazide diuretics, haloperidol, or proton pump inhibitors. For analytic simplicity, these medication classes were compiled into a single composite variable. Demographic characteristics and diagnoses were obtained from admission facesheets and ICD-10–coded diagnoses. Outcome Definition The primary endpoint was cumulative incident hyponatremia, defined as at least one corrected serum sodium concentration < 135 mEq/L occurring after the index admission date. The index admission served as time zero for cohort entry, at which point exposure status was determined. Only sodium measurements obtained after cohort entry were eligible for outcome classification. Sodium values were corrected for hyperproteinemia, hyperlipidemia, and hyperglycemia using established methods [ 24 , 25 ]. Follow-up duration varied across participants and was determined by the available electronic health record observation period. If any single corrected sodium measurement met the specified threshold during follow-up, the participant was classified as having experienced incident hyponatremia. Because duration of follow-up and laboratory monitoring frequency were not standardized across residents, the outcome was analyzed as cumulative incidence during the available observation period rather than as a time-to-event measure. Statistical Analysis Baseline group differences between participants with and without enteral feeding tubes and those with and without incident hyponatremia were analyzed using chi-square testing for categorical variables. Age was compared using independent t-tests. Given the retrospective cohort design and binary outcome definition, relative risks (RRs) were selected as the primary measure of association. Because follow-up duration varied across residents and time-to-event modeling was not feasible due to data limitations, the outcome was analyzed as a binary cumulative incidence measure. Associations between exposures and incident hyponatremia were first evaluated using crude RRs and 95% confidence intervals. Multivariable associations were subsequently assessed using modified Poisson regression with a log link and robust variance estimation (generalized estimating equations) to directly estimate adjusted relative risks. Covariates included demographic and clinical predictors identified a priori. Interaction terms between enteral feeding tube status and selected chronic conditions (CKD, CHF, and liver disease) were included to evaluate potential effect modification. Participants with missing data for the required outcome or baseline predictor data were excluded from the analysis. Sample Size and Power Calculation Sample size estimation was conducted for the primary outcome and exposure testing. This was completed using G*Power software based on a 2 × 2 contingency table with one degree of freedom. Given the objectives of multiple comparisons, a conservative two-sided significance threshold of α = 0.01 was applied to primary hypothesis testing to reduce the likelihood of type I error. Statistical power was set at 0.95. Small-to-moderate effect sizes (0.1–0.2) were assumed, the estimated required sample size ranged from approximately 325 to 1,300 participants, depending on the assumed effect size. Given this data, the researchers targeted a sample size of 1300. 3. Results Study Population and Baseline Characteristics A total of 1,349 patient records were available for evaluation. 93 of these records were excluded due to missing data on key exposure or outcome variables, including sodium levels, demographic information, or unclear enteral feeding tube status. The final analytic sample consisted of 1,256 individuals with enteral feeding tubes present in 34.7% of patients, and incident hyponatremia occurred in 34.6% of the cohort. The sample was mainly White (64.3%) and non-Hispanic (85.1%) with a mean age of 66.9 years (SD 14.9; range 24–104). To test for any baseline differences in groups, demographics and clinical risk factors were compared by enteral feeding tube status (Table 1 ) and by incident hyponatremia status (Table 2 ). This was done for clinical context rather than investigation of baseline differences. Using a conservative α = 0.01 to maintain consistency in analysis. Both stratification by enteral feeding tube status and incident hyponatremia showed statistically significant baseline differences with race, antidepressant use, haloperidol use, PPI use, CKD status, and CHF status. No statistically significant differences were found between age, ethnicity, sex, composite high-risk drugs, antiepileptics, or thiazides for either stratification by enteral feeding tube status or incident hyponatremia. Additionally, liver disease status differed by enteral feeding tube status but not incident hyponatremia. Table 1 Descriptive Statistics Between Groups Separated by Enteral Feeding Tube Status Variable Enteral Feeding Tube (n = 436) No Enteral Feeding Tube (n = 820) p-value Age, mean (SD) 65.9 (14.9) 67.4 (14.8) 0.08 Race, n (%) < 0.001** Asian 10 (2.3) 33 (4.0) Black 191 (43.8) 181 (22.1) Caucasian 219 (50.2) 588 (71.7) Indian 2 (0.5) 4 (0.5) Middle Eastern 12 (2.8) 14 (1.7) Native American 2 (0.5) 0 (0.0) Hispanic ethnicity, n (%) 62 (14.2) 125 (15.2) 0.63 Male sex, n (%) 240 (55.0) 452 (55.1) 0.98 Drugs frequently associated with hyponatremia, n (%) 336 (77.1) 627 (76.5) 0.81 Antidepressants 135 (31.0) 347 (42.3) < 0.001** Antiepileptics 61 (14.0) 154 (18.8) 0.03 Thiazides 16 (3.7) 54 (6.6) 0.03 Haloperidol 27 (6.2) 168 (20.5) < 0.001** Proton pump inhibitor 257 (59.0) 319 (38.9) < 0.001** Chronic kidney disease 205 (47.0) 240 (29.3) < 0.001** Liver disease 40 (9.2) 130 (15.9) 0.001** Congestive heart failure 171 (39.2) 249 (30.4) 0.002** Table 2 Descriptive Statistics Between Groups Separated by Incident Hyponatremia Variable Hyponatremia (n = 435) No Hyponatremia (n = 821) p-value Age, mean (SD) 66.9 (14.2) 66.8 (15.2) 0.89 Race, n (%) 0.0004** Asian 14 (3.2) 29 (3.5) Black 160 (36.8) 212 (25.8) Caucasian 247 (56.8) 560 (68.2) Indian 1 (0.2) 5 (0.6) Middle Eastern 11 (2.5) 15 (1.8) Native American 2 (0.5) 0 (0.0) Hispanic ethnicity, n (%) 76 (17.5) 111 (13.5) 0.06 Male sex, n (%) 248 (57.0) 444 (54.1) 0.32 Drugs frequently associated with hyponatremia, n (%) 335 (77.0) 628 (76.5) 0.84 Antidepressants 146 (33.6) 336 (40.9) 0.01** Antiepileptics 67 (15.4) 148 (18.0) 0.24 Thiazides 21 (4.8) 49 (6.0) 0.40 Haloperidol 48 (11.0) 147 (17.9) 0.001** Proton pump inhibitor 232 (53.3) 344 (41.9) < 0.001** Chronic kidney disease 245 (56.3) 200 (24.4) < 0.001** Liver disease 66 (15.2) 104 (12.7) 0.22 Congestive heart failure 194 (44.6) 226 (27.5) < 0.001** Multivariable Analysis A multivariate modified Poisson regression model with robust variance estimation was constructed to evaluate independent associations between clinical predictors and incident hyponatremia. After adjustment for demographic and clinical covariates, enteral feeding tube use was strongly associated with incident hyponatremia (adjusted RR 2.42; 95% CI 1.84–3.19; p < 0.0001). Chronic kidney disease (CKD) was independently associated with increased risk of hyponatremia (adjusted RR 1.87; 95% CI 1.43–2.44; p < 0.0001). Liver disease was also significantly associated with increased risk (adjusted RR 1.58; 95% CI 1.20–2.07; p = 0.001). Both congestive heart failure (adjusted RR 1.30; 95% CI 1.00–1.69; p = 0.052) and Hispanic ethnicity (adjusted RR 1.25; 95% CI 1.04–1.51; p = 0.019) approached statistical significance but did not achieve the predetermined statistical significance (α = 0.01). These results are summarized in Table 3 . Age, sex, and each of the high-risk medications were not significantly associated with incident hyponatremia in the adjusted model. Table 3 Stratified Associations Between Clinical Predictors and Incident Hyponatremia by Enteral Feeding Tube Status Predictor Adjusted RR 95% CI p-value Enteral feeding tube (Yes; ref No) 2.42 1.84–3.19 < 0.0001** Chronic kidney disease (Yes; ref No) 1.87 1.43–2.44 < 0.0001** Liver disease (Yes; ref No) 1.58 1.20–2.07 0.001** Congestive heart failure (Yes; ref No) 1.30 1.00–1.69 0.052 Hispanic ethnicity 1.25 1.04–1.51 0.019 Male sex 1.06 0.92–1.22 0.403 Age (per year) 0.999 0.994–1.004 0.710 Antidepressant use (Yes; ref No) 0.92 0.79–1.07 0.291 Antiepileptic use (Yes; ref No) 1.11 0.90–1.36 0.322 Thiazide use (Yes; ref No) 0.95 0.68–1.34 0.786 Haldol use (Yes; ref No) 1.02 0.80–1.30 0.892 PPI use (Yes; ref No) 0.99 0.86–1.15 0.923 Interaction Terms Enteral feeding tube × CKD 1.06 0.77–1.47 0.704 Enteral feeding tube × CHF 0.85 0.62–1.15 0.295 Enteral feeding tube × Liver disease 0.72 0.50–1.04 0.083 Interaction terms between enteral feeding tube status and CKD (adjusted RR 1.06; 95% CI 0.77–1.47; p = 0.704), CHF (adjusted RR 0.85; 95% CI 0.62–1.15; p = 0.295), and liver disease (adjusted RR 0.72; 95% CI 0.50–1.04; p = 0.083) were not statistically significant, indicating no evidence of multiplicative effect modification in the adjusted model. The absence of significant interaction terms suggests that the association between enteral feeding tube use and cumulative incident hyponatremia was relatively consistent across comorbidity strata. 4. Discussion Principal Findings In this retrospective cohort of SNF residents, incident hyponatremia was common, affecting approximately one-third of participants. The mean age of the cohort was somewhat younger than in many geriatric SNF studies; however, the population studied reflects the increasingly diverse case mix of modern skilled nursing facilities, which frequently include younger adults with complex medical needs. The data did identify enteral feeding tubes as a strong risk factor for cumulative incident hyponatremia. Enteral feeding tube patients faced greater than double the risk of incident hyponatremia compared with those without enteral feeding tubes. CKD and liver disease were also independently associated with increased risk. Interestingly, CHF, age, sex, ethnicity, and high-risk medication exposure was not independently associated with incident hyponatremia. The cumulative incidence of hyponatremia observed in this cohort is consistent with these prior observations and reinforces the clinical importance of electrolyte monitoring in long-term care settings. The absence of a medication effect may reflect exposure misclassification, residual confounding, or the high baseline medical complexity of this population. The absence of significance from age, sex, and ethnicity show these demographics did not have any major statistical impact on incident hyponatremia on adjusted analysis. Interestingly, CHF failed to demonstrate a statistically significant association with incident hyponatremia at the pre-determined conservative alpha. A type 2 error could be to blame by random chance, so further study should focus on this comorbidity to determine if there is indeed a causal relationship. The theoretical link between CHF and incident hyponatremia is similar to CKD and liver mechanisms with pathophysiologic links between neurohormonal activation and dilutional hyponatremia. Enteral feeding tube use and CKD represented the strongest independent predictors of incident hyponatremia with liver disease representing a mostest risk in this cohort. The underlying clinical mechanism of CKD is likely impaired renal free water clearance. Liver disease demonstrated a more modest association, aligning with known alterations in fluid regulation among patients with hepatic dysfunction. The lack of statistical significance with the interaction terms leads one to speculate that enteral feeding tubes do not modify the relationship of comorbid disease (CKD, CHF, liver disease) on incident hyponatremia. Comparison with Prior Literature The findings of this study are consistent with prior literature outlining hyponatremia as a common electrolyte disorder among older adults in SNFs. Previous studies have estimated hyponatremia prevalence in skilled nursing facilities between 15% and 30%, typically higher than estimates reported among community-dwelling older adults. Several chronic conditions previously associated with hyponatremia were also identified in this analysis. Chronic kidney disease and liver disease were both found to increase risk after adjustment, which is consistent with established basic science and clinical literature physiologic mechanisms involving impaired water excretion, altered renal handling of sodium, and neurohormonal activation. These findings align with prior epidemiologic studies demonstrating increased hyponatremia risk among patients with renal dysfunction, advanced liver disease, and other conditions associated with volume dysregulation. In contrast to themes in the literature, CHF and high-risk medication exposure were not independently associated with incident hyponatremia. Although these factors are frequently cited as contributors to hyponatremia in hospitalized populations, their effects in long-term care residents may be more heterogeneous and influenced by underlying disease severity, medication dosing, or clinical monitoring patterns. It is also possible that the high baseline medical complexity of the cohort reduced the relative contribution of individual medication classes or conditions. Relatively few studies have evaluated the relationship between enteral feeding and hyponatremia in long-term care settings. Case reports and smaller clinical studies have suggested that enteral nutrition through enteral tube feeding may influence electrolyte balance through mechanisms such as free-water administration, dilutional effects of feeding regimens, or underlying comorbid illness. The strong association observed between enteral feeding tube use and incident hyponatremia in this cohort extends these observations and suggests that residents receiving enteral nutrition may represent a subgroup at elevated risk. These findings support prior evidence linking chronic disease burden to hyponatremia while highlighting enteral feeding tube use as a potentially important and understudied risk factor in skilled nursing facility residents. These findings also suggest that care-related exposures, including enteral feeding practices, may warrant consideration when evaluating electrolyte abnormalities in institutionalized populations. Clinical Implications Although enteral feeding tube use in SNF settings is associated with substantially higher risk of incident hyponatremia, comorbid conditions such as CKD, and liver disease further increase this risk. Patients with enteral feeding tubes and coexisting CKD or liver disease demonstrated higher cumulative risk. These findings highlight the importance of routine monitoring to facilitate earlier detection, treatment, or prevention of hyponatremia. Healthcare and public health professionals caring for older adults in SNF settings should consider developing or refining risk management strategies to identify individuals at highest risk. In the absence of a validated hyponatremia-specific screening tool, existing instruments such as the Identification of Seniors at Risk tool may be considered. Additionally, emerging risk stratification approaches from the STRATIFY study may offer a hyponatremia-specific screening framework once publicly available. Implementation of such tools could potentially reduce incident hyponatremia, associated adverse events, hospitalizations, and mortality. As aging populations increasingly rely on institutional long-term care globally, identifying modifiable risk factors for electrolyte disturbances carries broader clinical and public health implications. Strengths This study has several strengths. The cohort included more than 1,200 skilled nursing facility residents with available laboratory data, providing a relatively large sample for examining electrolyte abnormalities in a long-term care setting. Incident hyponatremia was identified using objective serum sodium measurements obtained during routine clinical care rather than administrative coding, which reduces the potential for outcome misclassification. Importantly, the study evaluates enteral feeding tube use as a potential risk factor for hyponatremia, an exposure that has received limited attention in studies of skilled nursing facility residents. Because laboratory testing reflected routine clinical practice rather than protocol-driven monitoring, the findings may better represent real-world detection patterns in skilled nursing facilities. The study also evaluated multiple clinically relevant comorbid conditions and medication exposures within the same analytic framework, allowing comparison of several commonly cited risk factors in this population. Finally, the use of modified Poisson regression allowed direct estimation of relative risks for a common outcome, providing effect estimates that are more interpretable for clinical and epidemiologic research in skilled nursing facility populations. Limitations Several limitations should be considered when interpreting these findings. This was a single-site study, which may limit generalizability. The study facility receives specialized referrals including ventilator-dependent patients and in-house dialysis, which may reflect a population with higher medical complexity than typical community SNFs. The retrospective cohort design introduces potential for selection bias, misclassification bias, surveillance bias, and unmeasured confounding. Residents receiving enteral feeding often require more intensive clinical monitoring and may undergo more frequent laboratory testing, which could increase the likelihood of detecting hyponatremia relative to residents without feeding tubes. Reliance on existing electronic health record data may have increased the likelihood of exposure or outcome misclassification, potentially biasing estimates toward the null. Follow-up duration and laboratory monitoring frequency were not standardized and may have varied according to clinical complexity. Residents with enteral feeding tubes may have experienced longer facility stays and more frequent serum sodium testing, increasing the likelihood of detecting hyponatremia. Because time-to-event modeling was not feasible, the outcome was analyzed as cumulative incidence during the available observation period. Differential surveillance and variable follow-up may therefore have inflated risk estimates associated with enteral feeding tube use. Residual confounding remains possible, and medication adherence could not be assessed due to the data that was available. Medication exposures were treated as cumulative, which can obscure true casual associations and these variables were mainly used to determine any true baseline differences between main exposure and outcomes. The definition of incident hyponatremia included mild cases that may be clinically insignificant; future studies may consider a lower sodium threshold (e.g., < 130 mEq/L) or focus on symptomatic and clinically significant hyponatremia cases. Some subgroup analyses were limited by small sample sizes, reducing precision. Demographic subgroup analyses were not performed, as they were beyond the scope of the study objectives. Duration of follow-up and frequency of sodium testing were not available for quantification and therefore could not be incorporated into the analytic model. As a result, differences in length of stay or monitoring intensity between exposure groups may have influenced the observed cumulative risk estimates. These findings should therefore be interpreted as associations within an available observation window rather than precise time-dependent risk estimates. 5. Conclusion Hyponatremia remains a prevalent issue in older adults in SNF settings. Prompt recognition and correction of risk factors can improve motor and cognitive function, reducing morbidity and enhancing quality of life [ 10 , 11 ]. Residents with enteral feeding tubes are at greater risk than those without enteral feeding tubes. Additionally, CKD, CHF, and liver disease independently contribute to heightened risk of developing incident hyponatremia. High-risk medications did not demonstrate an independent association in this cohort. No significant multiplicative interactions were observed between enteral feeding tube status and major chronic comorbidities. Findings of this study support the need for healthcare and public health practitioners to consider enhanced monitoring protocols for high-risk patients, particularly those with enteral feeding tubes and significant chronic comorbidities. Understanding and recognizing those at risk is essential to prevent adverse outcomes associated with hyponatremia. Declarations Ethics approval and consent to participate Ethics approval for this study was obtained from the Rosalind Franklin University of Medicine and Science Institutional Review Board. The requirement for informed consent was waived due to the retrospective design and use of de-identified data. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Clinical trial number Not applicable. Authors’ contributions (CRediT) Conceptualization: D.M., T.M., and I.R. Data curation: D.M. Methodology: D.M., T.M., and I.R. Formal analysis: D.M. and E.H. Investigation: D.M., T.M., and I.R. Writing—original draft: D.M. and E.H. Writing—review and editing: D.M., T.M., I.R., and E.H. Supervision: D.M. All authors read and approved the final manuscript. Funding This research received no external funding. Author Contribution Conceptualization: D.M., T.M., and I.R.Data curation: D.M.Methodology: D.M., T.M., and I.R.Formal analysis: D.M. and E.H.Investigation: D.M., T.M., and I.R.Writing—original draft: D.M. and E.H.Writing—review and editing: D.M., T.M., I.R., and E.H.Supervision: D.M.All authors read and approved the final manuscript. Acknowledgement The authors declare no conflicts of interest and no source of funding for this project. The authors used ChatGPT (OpenAI) to assist with language editing and readability. The tool was not used for data analysis, study design, or interpretation of results. All analytic decisions and conclusions are those of the authors. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article. The authors would like to thank the IRB of the hosting organization as well as the skilled nursing facility that hosted data collection. Data Availability The datasets generated and/or analyzed during the current study are not publicly available due to data use agreements and privacy restrictions but may be available from the corresponding author on reasonable request and with permission of the data-holding institution. References Filippatos TD, Makri A, Elisaf MS, Liamis G. Hyponatremia in the elderly: challenges and solutions. Clin Interv Aging. 2017;12:1957–65. 10.2147/CIA.S138535 . Kugler JP, Hustead T. Hyponatremia and hypernatremia in the elderly. Am Fam Physician. 2000;61:3623–30. Mannesse CK, Vondeling AM, van Marum RJ, van Solinge WW, Egberts TCG, Jansen PAFJ. Prevalence of hyponatremia on geriatric wards compared to other settings over four decades: a systematic review. Ageing Res Rev. 2013;12:165–73. 10.1016/j.arr.2012.04.006 . Miller M, Morley JE, Rubenstein LZ. Hyponatremia in a nursing home population. J Am Geriatr Soc. 1995;43:1410–3. 10.1111/j.1532-5415.1995.tb06623.x . Serrano Valles C, Gómez Hoyos E, Ortolá Buigues A, Primo Martín D, Jiménez Sahagún R, García Calvo S, et al. Prevalencia y factores asociados a la hiponatremia en pacientes con nutrición enteral [Hyponatremia among patients with total enteral tube feeding: prevalence and associated clinical factors]. Nutr Hosp. 2022;39:723–7. 10.20960/nh.03964 . Fratangelo L, Nguyen S, D’Amelio P. Hyponatremia and aging-related diseases: key player or innocent bystander? A systematic review. Syst Rev. 2023;12:84. 10.1186/s13643-023-02246-w . Aydin AE, Ates Bulut E, Kocyigit SE, Dost FS, Mutlay F, Altunkalem Seydi K, et al. An instant relationship between hyponatremia, geriatric syndromes, and drugs in older adults: a cross-sectional analysis from a single geriatric clinic. Diagnostics (Basel). 2025;15:744. 10.3390/diagnostics15060744 . Ande SP, Kanitkar S, Borle A, Ahlawat M. Hyponatremia among elderly hospitalized patients: an observational study. Cureus. 2024;16:e67632. 10.7759/cureus.67632 . Shi LT, Feng Z, Zhu CM. A retrospective study: exploring preoperative hyponatremia in elderly patients with hip fractures. J Orthop Surg Res. 2024;19:186. 10.1186/s13018-024-04643-w . Kapoor M, Dhar M, Pathania M. The assessment of baseline comprehensive geriatric assessment parameters in geriatric patients with varying severity of hyponatremia at a tertiary care center. Cureus. 2022;14:e21516. 10.7759/cureus.21516 . Kapoor M, Pathania M, Dhar M. Serum sodium improvement: change in comprehensive geriatric assessment parameters in geriatric patients with hyponatremia. BMC Geriatr. 2023;23:666. 10.1186/s12877-023-04299-x . Netzer S, Gastens V, Boland B, et al. Association between hyponatremia and mortality and readmission in multimorbid older adults: a cohort study. J Clin Med. 2023;14:7146. 10.3390/jcm14207146 . Boyer S, Gayot C, Bimou C, et al. Prevalence of mild hyponatremia and its association with falls in older adults admitted to an emergency geriatric medicine unit (the MUPA Unit). BMC Geriatr. 2019;19:265. 10.1186/s12877-019-1282-0 . Ioannou P, Panagiotakis S, Tsagkaraki E, Tsioutis C, Fragkiadakis K, Gikas A, et al. Increased mortality in elderly patients admitted with hyponatremia: a prospective cohort study. J Clin Med. 2021;10:3059. 10.3390/jcm10143059 . Su Y, Ma M, Zhang H, Pan X, Zhang X, Zhang F, et al. Prognostic value of serum hyponatremia for outcomes in patients with heart failure with preserved ejection fraction: an observational cohort study. Exp Ther Med. 2020;20:101. 10.3892/etm.2020.9231 . Djukic M, Grewe J, Kunz O, Gross O, Nau R. Hyponatremia in geriatric patients. Z Gerontol Geriatr. 2024. 10.1007/s00391-024-02342-z . Goto M, Sakai M. Proton-pump inhibitor use and hyponatremia. Nihon Ronen Igakkai Zasshi. 2023;60:153–7. 10.3143/geriatrics.60.153 . Jun K, Kim Y, Ah YM, Lee JY. Awareness of the use of hyponatraemia-inducing medications in older adults with hyponatraemia: a study of their prevalent use and association with recurrent symptomatic or severe hyponatraemia. Age Ageing. 2021;50:1137–43. 10.1093/ageing/afaa195 . Schrier RW, Abraham WT, Koomans HA, et al. Hyponatremia in the elderly: epidemiology, diagnosis, and management in nursing home patients. J Am Geriatr Soc. 1995;43:547–52. 10.1111/j.1532-5415.1995.tb07891.x . Baser S, Yılmaz CN, Gemcioglu E. Do the etiology of hyponatremia and serum sodium levels affect the length of hospital stay in geriatric patients with hyponatremia? J Med Biochem. 2022;41:40–6. 10.5937/jomb0-29914 . Simakoloyi N, Erasmus E, van Hoving DJ. The characteristics of geriatric patients managed within the resuscitation unit of a district-level emergency centre in Cape Town. Afr J Emerg Med. 2022;12:39–43. 10.1016/j.afjem.2021.11.005 . Thorpe O, Cuesta M, Fitzgerald C, Feely O, Tormey WP, Sherlock M, et al. Active management of hyponatraemia and mortality in older hospitalised patients compared with younger patients: results of a prospective cohort study. Age Ageing. 2021;50:1144–50. 10.1093/ageing/afaa248 . Rajarajeswari TB, Arul Senghor KA, Vinodhini VM, Kumar JS, Prasath N. Hyponatremia and Identification of Seniors at Risk (ISAR) score in geriatric patients: an analytical cross-sectional study. Cureus. 2023;15:e49493. 10.7759/cureus.49493 . Hillier TA, Abbott RD, Barrett EJ. Hyponatremia: evaluating the correction factor for hyperglycemia. Am J Med. 1999;106:399–403. 10.1016/S0002-9343(99)00055-8 . Wang A, Koshiaris C, Archer L, et al. Developing prediction models for electrolyte abnormalities in patients indicated for antihypertensive therapy: evidence-based treatment and monitoring recommendations. J Hypertens. 2025;43:1348–59. 10.1097/HJH.0000000000004032 . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9200734","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626471059,"identity":"a9204d87-7260-42fe-bf3e-b6f8630c4f27","order_by":0,"name":"Daniel Mead","email":"data:image/png;base64,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","orcid":"","institution":"Rosalind Franklin University of Medicine and Science","correspondingAuthor":true,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Mead","suffix":""},{"id":626471060,"identity":"c24f0d2b-ae06-4629-a15e-c5daa9148675","order_by":1,"name":"Timothy Mallers","email":"","orcid":"","institution":"Rosalind Franklin University of Medicine and Science","correspondingAuthor":false,"prefix":"","firstName":"Timothy","middleName":"","lastName":"Mallers","suffix":""},{"id":626471061,"identity":"c7545e39-7cb9-494f-bb74-06f815a01b18","order_by":2,"name":"Ian Rios","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Ian","middleName":"","lastName":"Rios","suffix":""},{"id":626471062,"identity":"792806b8-8c99-4bac-9abc-3786674d136c","order_by":3,"name":"Emily Ho","email":"","orcid":"","institution":"Kent State University","correspondingAuthor":false,"prefix":"","firstName":"Emily","middleName":"","lastName":"Ho","suffix":""}],"badges":[],"createdAt":"2026-03-23 12:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9200734/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9200734/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107707610,"identity":"33d25058-cd4d-4837-a3c9-4deae5754341","added_by":"auto","created_at":"2026-04-24 09:20:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":341510,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9200734/v1/2b4b253a-ac96-492d-bda5-45000d12c93a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk Factors for Incident Hyponatremia in Skilled Nursing Facility Residents: A Retrospective Cohort Study","fulltext":[{"header":"1. Introduction and Background","content":"\u003cp\u003eHyponatremia is often encountered in clinical practice and has a higher prevalence in geriatric clinical practice. A particularly high-risk subgroup for hyponatremia are those living in skilled nursing facilities (SNF) with estimates between 15\u0026ndash;30% of patients in these settings having an existing diagnosis of hyponatremia [\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Prior cross-sectional and longitudinal studies have shown a higher prevalence of hyponatremia in SNF residents relative to community-dwelling older adults, which indicate a prevalence of hyponatremia at 7\u0026ndash;11% [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Clinical and epidemiological studies consistently link hyponatremia to adverse clinical outcomes, including generalized weakness, falls, fractures, cognitive impairment, hospitalization, and increased mortality [\u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Mortality is increased both in-hospital (17.4%) and at 1 year (28.3\u0026ndash;41%) compared to eunatremic patients [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In patients with the diagnosis of Heart Failure with preserved Ejection Fraction (HFpEF), hyponatremia predicts all-cause mortality, rehospitalization, and stroke [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The risk of hyponatremia in this population reflects the intersection of aging, multimorbidity, and care-related exposures, including chronic disease burden and institutional management of fluids and nutrition. Despite its frequency and clinical impact, hyponatremia in SNFs remains under-characterized, particularly with respect to modifiable risk factors and care practices. No large-scale studies yet quantify this risk in skilled nursing populations, creating a gap in clinical knowledge. Accordingly, this study aimed to characterize the burden of hyponatremia in skilled nursing facilities and to examine whether enteral feeding tube use and selected chronic diseases are associated with increased risk of hyponatremia in this population.\u003c/p\u003e \u003cp\u003e \u003cb\u003eReview of Literature\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA search of available literature was done on November 3rd, 2024 within the PubMed and CINAHL databases. Filters were set at 5 years and academic journals only. The keyword items were hyponatremia, geriatric, older adult, elderly, enteral feeding, tube feeding, enteral nutrition, gastric feeding, and skilled nursing. With the specified search terms and filters applied, PubMed yielded 96 records related to geriatrics and an additional 40 records related to enteral feeding terms, while 17 records were identified in CINAHL. 15 studies were selected to review. An additional search used a larger timeframe of 30 years, which found another 7 studies. The final selection included 22 articles. Major themes found in the literature were hyponatremia incidence and prevalence in SNFs, hyponatremia risk factors for the elderly, potential association of hyponatremia and enteral feeding, and clinical tools and monitoring of hyponatremia.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIncidence and Prevalence in SNFs\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs previously mentioned, the general estimation of hyponatremia varies by study, but is generally found to be between 15\u0026ndash;30% with malnourished patients potentially having higher risk [\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In two older studies from Miller [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] (1995) and Kugler \u0026amp; Hustead [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] (2000), up to half of the samples had at least one incident lab value showing hyponatremia in the year before data collection occurred.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRisk factors in the Elderly\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSeveral main risk factors were identified in the literature for incident hyponatremia. These factors can be subcategorized into 1) Medication-related factors (e.g., thiazide diuretics, antidepressants, antipsychotics, anticonvulsants, and prolonged proton pump inhibitor use) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], 2) cardiac, renal, and hepatic disease comorbidities [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], 3) low solute intake or malnutrition [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], 4) acute illness [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], 5) age-related renal and hormonal changes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], 6) SIADH and non-osmotic ADH release [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and 7) institutional care factors [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003ePotential Association of Hyponatremia and Enteral Feeding\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSome data suggests patients with enteral feeding tubes are at high risk of hyponatremia due to poor solute intake and high free water administration [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. One study by Rajarajewwari et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] (2023) reported a negative correlation between the Identification of Seniors at Risk (ISAR) Scoring tool and hyponatremia severity. This may suggest clinical utility of ISAR for risk stratification screening for hyponatremia.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMain Takeaway\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDespite the common occurrence of and extensive literature describing hyponatremia in older adults, few studies have examined enteral feeding as a major risk factor for incident hyponatremia within skilled nursing facilities.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e \u003cb\u003eStudy Design and Setting\u003c/b\u003e \u003c/p\u003e \u003cp\u003eData was collected and analyzed as a quantitative secondary analysis using a retrospective cohort design. All data collection was done by the principal investigator at a single suburban skilled nursing facility (SNF) between May and July 2025. The facility serves a predominantly White population and receives nationwide referrals for in-house dialysis, ventilator care, and subacute rehabilitation services. All data were deidentified at the time of collection.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy Population and Eligibility Criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003eInclusion criteria consisted of current or prior residence at the facility, age\u0026thinsp;\u0026ge;\u0026thinsp;18 years, and availability of at least annual laboratory data. Exclusion criteria included history of hyponatremia (documented serum sodium\u0026thinsp;\u0026lt;\u0026thinsp;135 mEq/L prior to or at the time of index admission), pituitary tumors, total parenteral nutrition, diagnosed syndrome of inappropriate antidiuretic hormone secretion (SIADH), hypothyroidism, adrenal insufficiency, or chronic scheduled intravenous fluid administration.\u003c/p\u003e \u003cp\u003e \u003cb\u003eExposure and Covariates\u003c/b\u003e \u003c/p\u003e \u003cp\u003eEnteral feeding tube presence was defined as present or not present on admission and was considered a baseline exposure. Chronic kidney disease (CKD), congestive heart failure (CHF), liver cirrhosis, and high-risk medication use were examined as exposure variables. Demographic variables, including age, sex, race, and ethnicity, were included as covariates.\u003c/p\u003e \u003cp\u003eHigh-risk medications were handled using an attempt-to-treat approach. Participants were classified as exposed if they were prescribed any agent within the following medication classes on admission: antidepressants, antiepileptics, thiazide diuretics, haloperidol, or proton pump inhibitors. For analytic simplicity, these medication classes were compiled into a single composite variable. Demographic characteristics and diagnoses were obtained from admission facesheets and ICD-10\u0026ndash;coded diagnoses.\u003c/p\u003e \u003cp\u003e \u003cb\u003eOutcome Definition\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe primary endpoint was cumulative incident hyponatremia, defined as at least one corrected serum sodium concentration\u0026thinsp;\u0026lt;\u0026thinsp;135 mEq/L occurring after the index admission date. The index admission served as time zero for cohort entry, at which point exposure status was determined. Only sodium measurements obtained after cohort entry were eligible for outcome classification. Sodium values were corrected for hyperproteinemia, hyperlipidemia, and hyperglycemia using established methods [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Follow-up duration varied across participants and was determined by the available electronic health record observation period. If any single corrected sodium measurement met the specified threshold during follow-up, the participant was classified as having experienced incident hyponatremia. Because duration of follow-up and laboratory monitoring frequency were not standardized across residents, the outcome was analyzed as cumulative incidence during the available observation period rather than as a time-to-event measure.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBaseline group differences between participants with and without enteral feeding tubes and those with and without incident hyponatremia were analyzed using chi-square testing for categorical variables. Age was compared using independent t-tests. Given the retrospective cohort design and binary outcome definition, relative risks (RRs) were selected as the primary measure of association. Because follow-up duration varied across residents and time-to-event modeling was not feasible due to data limitations, the outcome was analyzed as a binary cumulative incidence measure.\u003c/p\u003e \u003cp\u003eAssociations between exposures and incident hyponatremia were first evaluated using crude RRs and 95% confidence intervals. Multivariable associations were subsequently assessed using modified Poisson regression with a log link and robust variance estimation (generalized estimating equations) to directly estimate adjusted relative risks. Covariates included demographic and clinical predictors identified a priori. Interaction terms between enteral feeding tube status and selected chronic conditions (CKD, CHF, and liver disease) were included to evaluate potential effect modification. Participants with missing data for the required outcome or baseline predictor data were excluded from the analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSample Size and Power Calculation\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSample size estimation was conducted for the primary outcome and exposure testing. This was completed using G*Power software based on a 2 \u0026times; 2 contingency table with one degree of freedom. Given the objectives of multiple comparisons, a conservative two-sided significance threshold of α\u0026thinsp;=\u0026thinsp;0.01 was applied to primary hypothesis testing to reduce the likelihood of type I error. Statistical power was set at 0.95. Small-to-moderate effect sizes (0.1\u0026ndash;0.2) were assumed, the estimated required sample size ranged from approximately 325 to 1,300 participants, depending on the assumed effect size. Given this data, the researchers targeted a sample size of 1300.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cb\u003eStudy Population and Baseline Characteristics\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA total of 1,349 patient records were available for evaluation. 93 of these records were excluded due to missing data on key exposure or outcome variables, including sodium levels, demographic information, or unclear enteral feeding tube status. The final analytic sample consisted of 1,256 individuals with enteral feeding tubes present in 34.7% of patients, and incident hyponatremia occurred in 34.6% of the cohort. The sample was mainly White (64.3%) and non-Hispanic (85.1%) with a mean age of 66.9 years (SD 14.9; range 24\u0026ndash;104).\u003c/p\u003e \u003cp\u003eTo test for any baseline differences in groups, demographics and clinical risk factors were compared by enteral feeding tube status (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and by incident hyponatremia status (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This was done for clinical context rather than investigation of baseline differences. Using a conservative α\u0026thinsp;=\u0026thinsp;0.01 to maintain consistency in analysis. Both stratification by enteral feeding tube status and incident hyponatremia showed statistically significant baseline differences with race, antidepressant use, haloperidol use, PPI use, CKD status, and CHF status. No statistically significant differences were found between age, ethnicity, sex, composite high-risk drugs, antiepileptics, or thiazides for either stratification by enteral feeding tube status or incident hyponatremia. Additionally, liver disease status differed by enteral feeding tube status but not incident hyponatremia.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics Between Groups Separated by Enteral Feeding Tube Status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnteral Feeding Tube (n\u0026thinsp;=\u0026thinsp;436)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo Enteral Feeding Tube (n\u0026thinsp;=\u0026thinsp;820)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65.9 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.4 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e191 (43.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e181 (22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e219 (50.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e588 (71.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle Eastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNative American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic ethnicity, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62 (14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125 (15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e240 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e452 (55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrugs frequently associated with hyponatremia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e336 (77.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e627 (76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntidepressants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e135 (31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e347 (42.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiepileptics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61 (14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e154 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiazides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54 (6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaloperidol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e168 (20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProton pump inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e257 (59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e319 (38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e205 (47.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e240 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e130 (15.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongestive heart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e171 (39.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e249 (30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics Between Groups Separated by Incident Hyponatremia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHyponatremia (n\u0026thinsp;=\u0026thinsp;435)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo Hyponatremia (n\u0026thinsp;=\u0026thinsp;821)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.9 (14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.8 (15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0004**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e160 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e212 (25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e247 (56.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e560 (68.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle Eastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNative American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic ethnicity, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76 (17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e111 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e248 (57.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e444 (54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrugs frequently associated with hyponatremia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e335 (77.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e628 (76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntidepressants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e146 (33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e336 (40.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiepileptics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e148 (18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiazides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaloperidol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProton pump inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e232 (53.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e344 (41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e245 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e200 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66 (15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104 (12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongestive heart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e194 (44.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e226 (27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eMultivariable Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA multivariate modified Poisson regression model with robust variance estimation was constructed to evaluate independent associations between clinical predictors and incident hyponatremia. After adjustment for demographic and clinical covariates, enteral feeding tube use was strongly associated with incident hyponatremia (adjusted RR 2.42; 95% CI 1.84\u0026ndash;3.19; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Chronic kidney disease (CKD) was independently associated with increased risk of hyponatremia (adjusted RR 1.87; 95% CI 1.43\u0026ndash;2.44; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Liver disease was also significantly associated with increased risk (adjusted RR 1.58; 95% CI 1.20\u0026ndash;2.07; p\u0026thinsp;=\u0026thinsp;0.001). Both congestive heart failure (adjusted RR 1.30; 95% CI 1.00\u0026ndash;1.69; p\u0026thinsp;=\u0026thinsp;0.052) and Hispanic ethnicity (adjusted RR 1.25; 95% CI 1.04\u0026ndash;1.51; p\u0026thinsp;=\u0026thinsp;0.019) approached statistical significance but did not achieve the predetermined statistical significance (α\u0026thinsp;=\u0026thinsp;0.01). These results are summarized in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Age, sex, and each of the high-risk medications were not significantly associated with incident hyponatremia in the adjusted model.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStratified Associations Between Clinical Predictors and Incident Hyponatremia by Enteral Feeding Tube Status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted RR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnteral feeding tube (Yes; ref No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.84\u0026ndash;3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease (Yes; ref No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.43\u0026ndash;2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver disease (Yes; ref No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.20\u0026ndash;2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongestive heart failure (Yes; ref No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u0026ndash;1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04\u0026ndash;1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92\u0026ndash;1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.403\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (per year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.994\u0026ndash;1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntidepressant use (Yes; ref No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u0026ndash;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiepileptic use (Yes; ref No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u0026ndash;1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiazide use (Yes; ref No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68\u0026ndash;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.786\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaldol use (Yes; ref No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80\u0026ndash;1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPI use (Yes; ref No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86\u0026ndash;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInteraction Terms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnteral feeding tube \u0026times; CKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u0026ndash;1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnteral feeding tube \u0026times; CHF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u0026ndash;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnteral feeding tube \u0026times; Liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50\u0026ndash;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInteraction terms between enteral feeding tube status and CKD (adjusted RR 1.06; 95% CI 0.77\u0026ndash;1.47; p\u0026thinsp;=\u0026thinsp;0.704), CHF (adjusted RR 0.85; 95% CI 0.62\u0026ndash;1.15; p\u0026thinsp;=\u0026thinsp;0.295), and liver disease (adjusted RR 0.72; 95% CI 0.50\u0026ndash;1.04; p\u0026thinsp;=\u0026thinsp;0.083) were not statistically significant, indicating no evidence of multiplicative effect modification in the adjusted model. The absence of significant interaction terms suggests that the association between enteral feeding tube use and cumulative incident hyponatremia was relatively consistent across comorbidity strata.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e \u003cb\u003ePrincipal Findings\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn this retrospective cohort of SNF residents, incident hyponatremia was common, affecting approximately one-third of participants. The mean age of the cohort was somewhat younger than in many geriatric SNF studies; however, the population studied reflects the increasingly diverse case mix of modern skilled nursing facilities, which frequently include younger adults with complex medical needs. The data did identify enteral feeding tubes as a strong risk factor for cumulative incident hyponatremia. Enteral feeding tube patients faced greater than double the risk of incident hyponatremia compared with those without enteral feeding tubes. CKD and liver disease were also independently associated with increased risk. Interestingly, CHF, age, sex, ethnicity, and high-risk medication exposure was not independently associated with incident hyponatremia. The cumulative incidence of hyponatremia observed in this cohort is consistent with these prior observations and reinforces the clinical importance of electrolyte monitoring in long-term care settings.\u003c/p\u003e \u003cp\u003eThe absence of a medication effect may reflect exposure misclassification, residual confounding, or the high baseline medical complexity of this population. The absence of significance from age, sex, and ethnicity show these demographics did not have any major statistical impact on incident hyponatremia on adjusted analysis. Interestingly, CHF failed to demonstrate a statistically significant association with incident hyponatremia at the pre-determined conservative alpha. A type 2 error could be to blame by random chance, so further study should focus on this comorbidity to determine if there is indeed a causal relationship. The theoretical link between CHF and incident hyponatremia is similar to CKD and liver mechanisms with pathophysiologic links between neurohormonal activation and dilutional hyponatremia.\u003c/p\u003e \u003cp\u003eEnteral feeding tube use and CKD represented the strongest independent predictors of incident hyponatremia with liver disease representing a mostest risk in this cohort. The underlying clinical mechanism of CKD is likely impaired renal free water clearance. Liver disease demonstrated a more modest association, aligning with known alterations in fluid regulation among patients with hepatic dysfunction. The lack of statistical significance with the interaction terms leads one to speculate that enteral feeding tubes do not modify the relationship of comorbid disease (CKD, CHF, liver disease) on incident hyponatremia.\u003c/p\u003e \u003cp\u003e \u003cb\u003eComparison with Prior Literature\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe findings of this study are consistent with prior literature outlining hyponatremia as a common electrolyte disorder among older adults in SNFs. Previous studies have estimated hyponatremia prevalence in skilled nursing facilities between 15% and 30%, typically higher than estimates reported among community-dwelling older adults. Several chronic conditions previously associated with hyponatremia were also identified in this analysis. Chronic kidney disease and liver disease were both found to increase risk after adjustment, which is consistent with established basic science and clinical literature physiologic mechanisms involving impaired water excretion, altered renal handling of sodium, and neurohormonal activation. These findings align with prior epidemiologic studies demonstrating increased hyponatremia risk among patients with renal dysfunction, advanced liver disease, and other conditions associated with volume dysregulation.\u003c/p\u003e \u003cp\u003eIn contrast to themes in the literature, CHF and high-risk medication exposure were not independently associated with incident hyponatremia. Although these factors are frequently cited as contributors to hyponatremia in hospitalized populations, their effects in long-term care residents may be more heterogeneous and influenced by underlying disease severity, medication dosing, or clinical monitoring patterns. It is also possible that the high baseline medical complexity of the cohort reduced the relative contribution of individual medication classes or conditions.\u003c/p\u003e \u003cp\u003eRelatively few studies have evaluated the relationship between enteral feeding and hyponatremia in long-term care settings. Case reports and smaller clinical studies have suggested that enteral nutrition through enteral tube feeding may influence electrolyte balance through mechanisms such as free-water administration, dilutional effects of feeding regimens, or underlying comorbid illness. The strong association observed between enteral feeding tube use and incident hyponatremia in this cohort extends these observations and suggests that residents receiving enteral nutrition may represent a subgroup at elevated risk.\u003c/p\u003e \u003cp\u003eThese findings support prior evidence linking chronic disease burden to hyponatremia while highlighting enteral feeding tube use as a potentially important and understudied risk factor in skilled nursing facility residents. These findings also suggest that care-related exposures, including enteral feeding practices, may warrant consideration when evaluating electrolyte abnormalities in institutionalized populations.\u003c/p\u003e \u003cp\u003e \u003cb\u003eClinical Implications\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAlthough enteral feeding tube use in SNF settings is associated with substantially higher risk of incident hyponatremia, comorbid conditions such as CKD, and liver disease further increase this risk. Patients with enteral feeding tubes and coexisting CKD or liver disease demonstrated higher cumulative risk. These findings highlight the importance of routine monitoring to facilitate earlier detection, treatment, or prevention of hyponatremia.\u003c/p\u003e \u003cp\u003eHealthcare and public health professionals caring for older adults in SNF settings should consider developing or refining risk management strategies to identify individuals at highest risk. In the absence of a validated hyponatremia-specific screening tool, existing instruments such as the Identification of Seniors at Risk tool may be considered. Additionally, emerging risk stratification approaches from the STRATIFY study may offer a hyponatremia-specific screening framework once publicly available. Implementation of such tools could potentially reduce incident hyponatremia, associated adverse events, hospitalizations, and mortality. As aging populations increasingly rely on institutional long-term care globally, identifying modifiable risk factors for electrolyte disturbances carries broader clinical and public health implications.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStrengths\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study has several strengths. The cohort included more than 1,200 skilled nursing facility residents with available laboratory data, providing a relatively large sample for examining electrolyte abnormalities in a long-term care setting. Incident hyponatremia was identified using objective serum sodium measurements obtained during routine clinical care rather than administrative coding, which reduces the potential for outcome misclassification. Importantly, the study evaluates enteral feeding tube use as a potential risk factor for hyponatremia, an exposure that has received limited attention in studies of skilled nursing facility residents.\u003c/p\u003e \u003cp\u003eBecause laboratory testing reflected routine clinical practice rather than protocol-driven monitoring, the findings may better represent real-world detection patterns in skilled nursing facilities. The study also evaluated multiple clinically relevant comorbid conditions and medication exposures within the same analytic framework, allowing comparison of several commonly cited risk factors in this population. Finally, the use of modified Poisson regression allowed direct estimation of relative risks for a common outcome, providing effect estimates that are more interpretable for clinical and epidemiologic research in skilled nursing facility populations.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSeveral limitations should be considered when interpreting these findings. This was a single-site study, which may limit generalizability. The study facility receives specialized referrals including ventilator-dependent patients and in-house dialysis, which may reflect a population with higher medical complexity than typical community SNFs. The retrospective cohort design introduces potential for selection bias, misclassification bias, surveillance bias, and unmeasured confounding. Residents receiving enteral feeding often require more intensive clinical monitoring and may undergo more frequent laboratory testing, which could increase the likelihood of detecting hyponatremia relative to residents without feeding tubes. Reliance on existing electronic health record data may have increased the likelihood of exposure or outcome misclassification, potentially biasing estimates toward the null. Follow-up duration and laboratory monitoring frequency were not standardized and may have varied according to clinical complexity. Residents with enteral feeding tubes may have experienced longer facility stays and more frequent serum sodium testing, increasing the likelihood of detecting hyponatremia. Because time-to-event modeling was not feasible, the outcome was analyzed as cumulative incidence during the available observation period. Differential surveillance and variable follow-up may therefore have inflated risk estimates associated with enteral feeding tube use.\u003c/p\u003e \u003cp\u003eResidual confounding remains possible, and medication adherence could not be assessed due to the data that was available. Medication exposures were treated as cumulative, which can obscure true casual associations and these variables were mainly used to determine any true baseline differences between main exposure and outcomes. The definition of incident hyponatremia included mild cases that may be clinically insignificant; future studies may consider a lower sodium threshold (e.g., \u0026lt;\u0026thinsp;130 mEq/L) or focus on symptomatic and clinically significant hyponatremia cases. Some subgroup analyses were limited by small sample sizes, reducing precision. Demographic subgroup analyses were not performed, as they were beyond the scope of the study objectives. Duration of follow-up and frequency of sodium testing were not available for quantification and therefore could not be incorporated into the analytic model. As a result, differences in length of stay or monitoring intensity between exposure groups may have influenced the observed cumulative risk estimates. These findings should therefore be interpreted as associations within an available observation window rather than precise time-dependent risk estimates.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eHyponatremia remains a prevalent issue in older adults in SNF settings. Prompt recognition and correction of risk factors can improve motor and cognitive function, reducing morbidity and enhancing quality of life [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Residents with enteral feeding tubes are at greater risk than those without enteral feeding tubes. Additionally, CKD, CHF, and liver disease independently contribute to heightened risk of developing incident hyponatremia. High-risk medications did not demonstrate an independent association in this cohort. No significant multiplicative interactions were observed between enteral feeding tube status and major chronic comorbidities. Findings of this study support the need for healthcare and public health practitioners to consider enhanced monitoring protocols for high-risk patients, particularly those with enteral feeding tubes and significant chronic comorbidities. Understanding and recognizing those at risk is essential to prevent adverse outcomes associated with hyponatremia.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e Ethics approval for this study was obtained from the Rosalind Franklin University of Medicine and Science Institutional Review Board. The requirement for informed consent was waived due to the retrospective design and use of de-identified data.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical trial number\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eAuthors\u0026rsquo; contributions (CRediT)\u003c/h2\u003e \u003cp\u003eConceptualization: D.M., T.M., and I.R.\u003c/p\u003e \u003cp\u003eData curation: D.M.\u003c/p\u003e \u003cp\u003eMethodology: D.M., T.M., and I.R.\u003c/p\u003e \u003cp\u003eFormal analysis: D.M. and E.H.\u003c/p\u003e \u003cp\u003eInvestigation: D.M., T.M., and I.R.\u003c/p\u003e \u003cp\u003eWriting\u0026mdash;original draft: D.M. and E.H.\u003c/p\u003e \u003cp\u003eWriting\u0026mdash;review and editing: D.M., T.M., I.R., and E.H.\u003c/p\u003e \u003cp\u003eSupervision: D.M.\u003c/p\u003e \u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: D.M., T.M., and I.R.Data curation: D.M.Methodology: D.M., T.M., and I.R.Formal analysis: D.M. and E.H.Investigation: D.M., T.M., and I.R.Writing\u0026mdash;original draft: D.M. and E.H.Writing\u0026mdash;review and editing: D.M., T.M., I.R., and E.H.Supervision: D.M.All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors declare no conflicts of interest and no source of funding for this project. The authors used ChatGPT (OpenAI) to assist with language editing and readability. The tool was not used for data analysis, study design, or interpretation of results. All analytic decisions and conclusions are those of the authors. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article. The authors would like to thank the IRB of the hosting organization as well as the skilled nursing facility that hosted data collection.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to data use agreements and privacy restrictions but may be available from the corresponding author on reasonable request and with permission of the data-holding institution.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFilippatos TD, Makri A, Elisaf MS, Liamis G. Hyponatremia in the elderly: challenges and solutions. 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Cureus. 2023;15:e49493. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7759/cureus.49493\u003c/span\u003e\u003cspan address=\"10.7759/cureus.49493\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHillier TA, Abbott RD, Barrett EJ. Hyponatremia: evaluating the correction factor for hyperglycemia. Am J Med. 1999;106:399\u0026ndash;403. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0002-9343(99)00055-8\u003c/span\u003e\u003cspan address=\"10.1016/S0002-9343(99)00055-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang A, Koshiaris C, Archer L, et al. Developing prediction models for electrolyte abnormalities in patients indicated for antihypertensive therapy: evidence-based treatment and monitoring recommendations. J Hypertens. 2025;43:1348\u0026ndash;59. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/HJH.0000000000004032\u003c/span\u003e\u003cspan address=\"10.1097/HJH.0000000000004032\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9200734/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9200734/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHyponatremia has long been recognized as a common electrolyte abnormality among skilled nursing facility (SNF) residents. In the literature, hyponatremia is associated with increases in falls, cognitive impairment, hospitalization, and increased mortality. Although many medical conditions and medications contribute to hyponatremia risk, the role of enteral feeding tubes in this population has not been well defined in clinical practice. This study examined the association between enteral feeding tube use and incident hyponatremia and evaluated selected chronic conditions and medication exposures in SNF patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective cohort study using secondary data from a suburban skilled nursing facility. Adults aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years residing in the SNF with available laboratory data were included (n\u0026thinsp;=\u0026thinsp;1,256). Exposures included presence of an enteral feeding tube at admission, selected chronic conditions, and high-risk medication exposures. The primary outcome was incident hyponatremia, defined as any corrected serum sodium value\u0026thinsp;\u0026lt;\u0026thinsp;135 mEq/L occurring after admission. Relative risks were estimated using modified Poisson regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIncident hyponatremia occurred in 34.6% of residents. In adjusted models, enteral feeding tubes (aRR 2.42; 95% CI 1.84\u0026ndash;3.19), chronic kidney disease (aRR 1.87; 95% CI 1.43\u0026ndash;2.44), and Liver Disease (aRR 1.58; 95% CI 1.20\u0026ndash;2.07) remained the significant independent predictors. Congestive Heart Failure, ethnicity, sex, age, and high-risk medication exposure were not significantly associated with risk at the predetermined alpha\u0026thinsp;=\u0026thinsp;0.01, and no significant interactions were observed between CKD, CHF, and liver disease and enteral feeding tubes on incident hyponatremia.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHyponatremia remains a common electrolyte abnormality among SNF residents. Enteral feeding tube use was strongly associated with increased cumulative risk of incident hyponatremia. Both CKD and liver disease also pose risk of incident hyponatremia. SNF residents with enteral feeding tubes may benefit from targeted monitoring and risk stratification in long-term care settings. Clinicians should be aware of these risks while ordering water flushing of enteral tubes and assess these patients regularly for hyponatremia.\u003c/p\u003e","manuscriptTitle":"Risk Factors for Incident Hyponatremia in Skilled Nursing Facility Residents: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 18:52:32","doi":"10.21203/rs.3.rs-9200734/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-15T04:50:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T17:34:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T10:13:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"185663419882920626884757013674506998401","date":"2026-04-25T18:42:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-25T12:12:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"192216347211306015923662119730225731503","date":"2026-04-23T09:44:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T16:06:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"299360043499646900103304208088255590109","date":"2026-04-15T13:57:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25889702692327330590599278028383817129","date":"2026-04-15T12:13:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-15T09:43:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-25T16:45:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-25T10:13:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-25T10:12:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2026-03-23T12:31:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b0b56781-2e99-4917-a5bb-40144cc04b0c","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-15T04:50:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T17:34:09+00:00","index":66,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T10:13:36+00:00","index":65,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T04:54:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 18:52:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9200734","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9200734","identity":"rs-9200734","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}