Diuretic Plasma Concentration is not Related to Fall Risk in Older Adults

Abstract

Diuretics are established fall-risk increasing drugs. However, not all diuretics users experience fall incidents. Due to interindividual
heterogeneity in older populations, it is difficult to identify which older adults are at highest risk of medication-related falls. Therefore, we assessed if diuretic plasma concentrations are associated with fall risk in users. We analyzed plasma samples of 307 hydrochlorothiazide and 110 furosemide users from a cohort of older community-dwelling adults. Cox proportional hazard and logistic regression models were used to analyze associations between diuretic concentration at baseline, changes over time and fall risk. There was no significant association between fall risk and plasma concentration of either hydrochlorothiazide or furosemide at baseline. Nor was a change in concentration over time associated with fall risk. Thus, diuretic plasma concentration is not associated with fall risk in older communitydwelling adults.

Abstract

Diuretics are established fall-risk increasing drugs. However, not all diuretics users experience fall incidents. Due to interindividual heterogeneity in older populations, it is difficult to identify which older adults are at highest risk of medication-related falls. Therefore, we assessed if diuretic plasma concentrations are associated with fall risk in users. We analyzed plasma samples of 307 hydrochlorothiazide and 110 furosemide users from a cohort of older community-dwelling adults. Cox proportional hazard and logistic regression models were used to analyze associations between diuretic concentration at baseline, changes over time and fall risk. There was no significant Keywords: Diuretics; Falls; Older adults; Plasma concentration. association between fall risk and plasma concentration of either hydrochlorothiazide or furosemide at baseline. Nor was a change in concentration over time associated with fall risk. Thus, diuretic plasma concentration is not associated with fall risk in older community dwelling adults.

Keywords

Diuretics; Falls; Older adults; Plasma concentration.

Abbreviations

ADR: Adverse Drug Reaction; ATC: Anatomical Therapeutical Chemical; BMI: Body Mass Index; B-PROOF study: B-Vitamins for the Prevention Of Osteoporotic Fractures study; EDTA: Ethylene Diamine Tetraacetic Acid; eGFR: estimated Glomerular Filtration Rate; FRID: Fall-Risk Increasing Drug; GDS: Geriatric Depression Scale; HR: Hazard Ratio; IQR: Inter Quartile Range; LC-MS: Liquid Chromatography - Mass Spectrometry; MMSE: Mini-Mental State Examination; OR: Odds Ratio; SD: Standard Deviation.

Citation

van Poelgeest EP, Ploegmakers KJ, Seppala LJ, van Dijk SC, LCPGM de Groot, et.al, (2025) Diuretic Plasma Concentration is not Re lated to Fall Risk in Older Adults. J Nephrol Kidney Dis (1): 6.

INTRODUCTION

In older persons, falls are a major health problem associated with morbidity, mortality, decreased quality of life and substantial health care costs [1]. Approximately one-third of people 65 years and over fall at least once a year [1,2]. A well-established and potentially modifiable risk factor for falling is the use of fall-risk increasing drugs (FRIDs), such as diuretics [1,3,4]. Diuretic use is associated with potentially serious adverse drug reactions (ADRs), especially in older adults due to age-related pharmacokinetic and pharmacodynamic changes, multimorbidity and drug/drug or drug/disease interactions [5-7]. A systematic review and meta-analysis showed that loop diuretic use was associated with increased  all risk in older adults [4]. Thiazide(like) and loop diuretics increase sodium and potassium excretion, potentially resulting in electrolyte imbalances and hypovolemia, which can contribute to increased fall risk [8]. It is, however, currently unknown which individual factors play a role in diuretic-related falls. Potentially, diuretic blood concentration levels modify fall risk in older people: there are substantial inter-individual differences in response to diuretic treatment due to variation in pharmacokinetic processes between individuals. For instance, furosemide bioavailability ranges from 10 to 100% [9]. There have been reports in observational studies demonstrating an association between increased concentrations of other FRIDs and their active metabolites and fall risk in older adults [10]. Literature on the potential link between diuretic plasma concentration and falls in older adults is currently lacking. Our objective was to evaluate if diuretic plasma concentrations are associated with fall risk in older persons.

MATERIALS AND METHODS

Trial design and participants

This study used a subsample of the B-PROOF (B-Vitamins for the Prevention of Osteoporotic Fractures) study (ClinicalTrials.gov NCT00696514), performed in community-dwelling older adults. B-PROOF is a randomized, placebo-controlled, double-blinded trial that studied the effect of vitamin B12 and folic acid supplementation on osteoporotic fractures in 2,919 participants aged 65 years and over, having mildly elevated (12-50 µmol/L) serum homocysteine levels. The protocol was approved by the Medical Ethical Committee of Wageningen University. All participants gave their written informed consent prior to study participation. Because the intervention did not affect fall outcomes [11], data could be used for the current observational study. The detailed study protocol was published previously [12].

Diuretic use

Diuretic use was determined based on both self-reported questionnaires and pharmacy dispensing record data obtained from the Dutch Foundation for Pharmaceutical Statistics. The Anatomical Therapeutical Chemical (ATC) coding system was used to identify 254 furosemide (C03CA01) and 528 hydrochlorothiazide (C03AA03, C03EA01, C09DX01, C09XA52) users. All furosemide users were selected and approximately three hundred hydrochlorothiazide users were selected based on a random sample. Participants having prescriptions up to 30 days prior blood withdrawal at baseline and/or follow-up visit were selected. To capture more potential users, also participants with a prescription of up to 30 days after the withdrawal date were selected as some participants might not had a refill in the 30 days before. We also included participants that self-reported usage both at baseline and/or follow-up blood sampling.

Diuretic plasma concentrations

At baseline and follow-up, fasted blood samples were collected in the morning. Furosemide and hydrochlorothiazide plasma concentrations were assessed from blood collected in EDTA (Ethylene Diamine Tetraacetic Acid) tubes at both data points, and stored at -80°C until analysis using liquid chromatography-mass spectrometry (LC-MS). If the concentration was undetectable, the respective concentration was set at half of the lower limit of detection: 5.0 ng/ml. Because the population consisted of chronic diuretic users, we also calculated delta concentrations by subtracting the concentration at follow-up minus concentration at baseline.

Outcomes

The primary outcome was time to first fall during follow-up of 2-3 years measured by fall calendars. Participants were followed until their drop-out date or the date of their last calendar, date of death or the end of the study, whichever came first [12]. Secondary outcome was the occurrence of a fall during follow-up in relation to the change in plasma concentration over time.

Covariates

Baseline characteristics were assessed using questionnaires and included age, gender, use of a walking aid, alcohol consumption, smoking status, medical history including cardiovascular diseases, self-reported medication use, cognitive performance and presence of depressive symptoms. Baseline measurements included height, weight, blood pressure, physical performance, and kidney function tests [12].

Statistical analysis

Baseline characteristics were calculated for fallers and non-fallers using Chi-square tests and Mann-Whitney U tests and t-tests for categorical and continuous non-normally distributed and normally distributed data, respectively. Plasma concentrations were analysed continuously and categorically. For the categorical analysis, plasma concentration were divided in concentrations below and above the median and in 4 equal quartiles (lowest-25th, 25th-50th, 50th-75th, 75th- highest). The concentrations below the median and the lowest 25th quartile were set as the reference category. To analyse the association of changing concentration over time (delta concentration) and fall risk, all participants with decreasing (negative delta) or stable concentration over time were given the value 0. All participants with an increasing concentration over time (positive delta) were given value 1. Participants with a value 0 as delta concentration were set as the reference category. We used Cox regression models to calculate hazard ratios (HRs) for time to first fall based on diuretic concentration at baseline. To analyze the association between the delta plasma concentration and fall occurrence during follow-up logistic regression models were used to calculate odds ratios (ORs). In model 1, diuretic concentration was adjusted for age and gender. Potential confounders described above under covariates were added to model 2 if they changed the effect size 10% or more. If there were <10 fall events per covariate in the final model, we chose the most clinically relevant covariates. P-values ≤0.05 were considered statistically significant. All statistical analyses were performed using SPSS for Windows, version 26.0.0.1 (IBM Corp., New York).

RESULTS AND DISCUSSION

Study population

We included 307 hydrochlorothiazide and 110 furosemide users in our analyses. Baseline characteristics of these participants are shown in Tables 1 and 2. We calculated 294 delta concentrations for hydrochlorothiazide users and 79 delta concentrations for furosemide users after exclusion of incomplete cases.

Hydrochlorothiazide and fall risk

During follow-up 51% of the hydrochlorothiazide users experienced a fall. Baseline hydrochlorothiazide plasma concentration was not associated with time to first fall in the continuous or categorical analysis (Table 3). No association was found between the delta concentration of hydrochlorothiazide and fall risk (model 1: OR: 0.80 [0.50-1.27], p=0.347).

Furosemide and fall risk

During follow-up 55% of furosemide users experienced a fall. No association was found between baseline plasma furosemide concentration and fall risk (Table 3). No association between delta concentration and fall risk was found (Model 2: OR: 2.58[0.97-6.89], p=0.058). Our study showed that neither hydrochlorothiazide nor furosemide plasma concentration were associated with fall risk. To the best of our knowledge, this was the first study to assess the role of diuretic plasma concentrations in fall risk in older persons. 

Methodologically, fall-related research is challenging due to e.g. variable follow-up time, changes in exposure during follow-up, recurrent fall incidents in the same individual and recall bias [13]. The strengths of our study were that we prospectively collected fall data with weekly fall calendars, minimizing recall bias. Also, we thoroughly collected medication usage, using both pharmacy prescription data and self-reported medication lists. The limitations of our study were that diuretic plasma concentrations were merely measured at baseline and follow-up visit, and not at the time of the fall. In addition, data regarding presence of postural hypotension and electrolyte disturbances was lacking. Lastly, diuretics have their main site of action on the electrolyte transporters on the tubular membrane rather than the blood membrane. Therefore, measuring diuretic concentrations in urine might have been more insightful than measuring plasma concentrations. Unfortunately, however, urine samples were not available in the B-PROOF trial.

Table 1: Baseline characteristics hydrochlorothiazide users (n=303)

† presented as median (Inter Quartile Range (IQR)), ‡ presented as n (%), § presented as mean (standard deviation (SD)). *represents p-value ≤ 0.05 (comparison of non-fallers to fallers). Abbreviations: BMI: Body Mass Index; MMSE: Mini-Mental State Examination; GDS: Geriatric Depression Scale; eGFR: estimated Glomerular Filtration Rate.

Table 2: Baseline characteristics furosemide users (n=110)

† presented as median (Inter Quartile Range (IQR)), ‡ presented as n (%), § presented as mean (standard deviation (SD)). *represents p-value ≤ 0.05 (comparison of non-fallers to fallers).

Abbreviations: BMI: Body Mass Index; MMSE: Mini-Mental State Examination; GDS: Geriatric Depression Scale; eGFR: estimated Glomerular Filtration Rate.

Table 3: Baseline characteristics furosemide users (n=110)

Data are presented as Hazard ratio with 95% confidence interval. N= number of participants. Model 1: adjusted for age and gender. Number of events hydrochlorothiazide: 159. Number of events furosemide: 60.

a: Median concentration hydrochlorothiazide: 46.6 ng/ml

b: Hydrochlorothiazide concentration range 1st quartile: 5.0-17.2 ng/ml; 2nd quartile: 17.2-46.6 ng/ml; 3rd quartile: 46.6-115.0 ng/ml; 4th quartile:

115.0-647.0 ng/ml.

c: Median concentration furosemide: 34.2 ng/ml

d: Furosemide concentration range 1st quartile: 5.0-14.5 ng/ml; 2nd quartile: 14.5-34.2 ng/ml; 3rd quartile: 34.2-178.0 ng/ml; 4th quartile: 178.0-

1930.0 ng/ml.

e: Number of users: 110; number of events: 60. Model 2 is adjusted for age, gender and cardiovascular medication use minus diuretics. f: Number of users: 110; number of events: 60. Model 2 is adjusted for age, gender and Body Mass Index (BMI).

No model 2 was constructed for the hydrochlorothiazide analysis and the continuous analysis of furosemide because none of the covariates changed

the outcome more than 10%

CONCLUSION

In conclusion, our results do not justify the assessment of diuretic plasma blood concentrations in an effort to reduce fall risk in older adults using diuretics. Future research should focus on identification of other potential markers for prediction of diuretic related fall-risk in older persons. Analysis of diuretic concentration might be helpful, or clinical outcomes such as orthostatic hypotension and electrolyte imbalances. A more detailed insight in risk factors determining medication related fall risk has the potential to facilitate individualized clinical decision-making with the aim of reducing falls risk in older adults [8].

ACKNOWLEDGEMENTS

the authors thank D. van der Laan and M. Pistorius, of the hospital pharmacy department of the Amsterdam Academic Medical Center, for analyzing the included blood samples and providing us the data to investigate our research question. Also, we thank the participants of the B-PROOF study for their enthusiasm and cooperation. Furthermore, we thank the dedicated team that conducted the study. Especially, A.C. Ham, A.W. Enneman, R. Dhonukshe-Rutten, P Lips and J. van Wijngaarden.

FUNDING INFORMATION

This project was funded by the Clementine Brigitta Maria Dalderup fund (numbers 3021 and 3549), the Netherlands Organization for Health Research and Development (ZonMw; number 6130.0031), and NZO (Dutch Dairy Association; number KB-15-004-003).

REFERENCES

2. Campbell AJ, Borrie MJ, Spears GF, Jackson SL, Brown JS, Fitzgerald JL. Circumstances and Consequences of Falls Experienced by a Community Population 70 Years and over during a Prospective- Study. Age Ageing. 1990; 19: 136-141.
3. Seppala LJ, Petrovic M, Ryg J, Bahat G, Topinkova E, Szczerbinska K, et al. STOPPFall(Screening Tool of Older Persons Prescriptions in older adults with high fall risk): a Delphi study by the EuGMS Task and Finish Group on Fall-Risk-Increasing Drugs. Age Ageing. 2021; 50: 1189-1199.
4. de Vries M, Seppala LJ, Daams JG, van de Glind EMM, Masud T, van der Velde N, et al. Fall-Risk-Increasing Drugs: A Systematic Review and Meta-Analysis: I. Cardiovascular Drugs. J Am Med Dir Assoc. 2018; 19: 371.e1-371.e9.
5. Mertens B, Hias J, Hellemans L, Walgraeve K, Spriet I, Tournoy J, et al. Drug-related hospital admissions in older adults: comparison of the Naranjo algorithm and an adjusted version of the Kramer algorithm. Eur Geriatr Med. 2022; 13: 567-577.
6. Aubert CE, Rodondi N, Netzer S, Dalleur O, Spinewine A, Drenth-van Maanen C, et al. Predictors of 1-year drug-related admissions in older multimorbid hospitalized adults. J Am Geriatr Soc. 2022; 70: 1510-1516.
7. Hendriksen LC, van der Linden PD, Lagro-Janssen ALM, van den Bemt PMLA, Siiskonen SJ, Teichert M, et al. Sex differences associated with adverse drug reactions resulting in hospital admissions. Biol Sex Differ. 2021; 12: 34.

8. van Poelgeest EP, Handoko ML, Muller M, van der Velde N, Fall-Risk ETFG. Diuretics, SGLT2 inhibitors and falls in older heart failure patients: to prescribe or to deprescribe? A clinical review. Eur Geriatr Med. 2023; 14: 659-674.
9. Brater DC. Update in Diuretic Therapy: Clinical Pharmacology. Semin Nephrol. 2011; 31: 483-494.
10. Hartholt KA, Becker ML, van der Cammen TJ. Drug-induced falls in older persons: is there a role for therapeutic drug monitoring? Ther Adv Drug Saf. 2016; 7: 39-42.
11. Swart KMA, Ham A, van Wijngaarden JP, Enneman AW, van Dijk SC, Sohl E, et al. A Randomized Controlled Trial to Examine the Effect of 2-Year Vitamin B12 and Folic Acid Supplementation on Physical Performance, Strength, and Falling: Additional Findings from the B-PROOF Study. Calcified Tissue Int. 2016; 98: 18-27.
12. van Wijngaarden JP, Dhonukshe-Rutten RAM, van Schoor NM, van der Velde N, Swart KMA, Enneman AW, et al. Rationale and design of the B-PROOF study, a randomized controlled trial on the effect of supplemental intake of vitamin B12 and folic acid on fracture incidence. BMC Geriatr. 2011; 11: 80 .
13. Leclerc BS, Bégin C, Cadieux É, Goulet L, Leduc N, Kergoat MJ, et al. Risk factors for falling among community-dwelling seniors using home-care services:: An extended hazards model with time- dependent covariates and multiple events. Chronic Dis Can. 2008; 28: 111-120.