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\begin{document}

\title{Are higher antidepressant plasma concentrations associated with fall
risk in older antidepressant users?}



\author[1]{anouschka Pronk}%
\author[2]{Eveline van Poelgeest}%
\author[2]{Lotta Seppala}%
\author[2]{Kim Ploegmakers}%
\author[3]{B H Stricker}%
\author[4]{Karin Swart-Polinder}%
\author[5]{Suzanne van Dijk}%
\author[5]{Sadaf Oliai}%
\author[6]{Lisette de Groot}%
\author[7]{Natasja M. van Schoor}%
\author[8]{Ron Mathot}%
\author[2]{Nathalie van der Velde}%
\affil[1]{Amsterdam UMC Locatie AMC}%
\affil[2]{Amsterdam UMC Locatie Meibergdreef}%
\affil[3]{Affiliation not available}%
\affil[4]{Amsterdam UMC Locatie VUmc}%
\affil[5]{Erasmus University Rotterdam}%
\affil[6]{Wageningen Universiteit en Researchcentrum}%
\affil[7]{Amsterdam Public Health Research Institute}%
\affil[8]{Amsterdam UMC - Locatie AMC}%


\vspace{-1em}



  
  \date{March 14, 2025}


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\selectlanguage{english}
\begin{abstract}
Aim Antidepressants are well-established fall-risk increasing
drugs(FRIDs) and therefore falls should be considered an important
adverse drug event(ADE) of antidepressants. However, not all
antidepressant users experience fall incidents and factors associated
with increased fall risk among antidepressant users are incompletely
understood. Our objective was to explore whether antidepressant plasma
concentrations are associated with falls in older antidepressant users.
Methods For this study, we included antidepressant users of the
multicenter B-PROOF study. Fall incidents were recorded prospectively
using fall calendars. Antidepressant plasma concentrations were analyzed
by Liquid chromatography-mass spectrometry(LC-MS) at baseline and at 2
years follow-up. The associations between the observed antidepressant
concentration, or concentration change over time (delta) and fall risk
were assessed using Cox proportional hazard and logistic regression
models and adjusted for potential confounders. Results In total 93
selective serotonin reuptake inhibitor(SSRI) and 41 antidepressant(TCA)
users were identified. There was a significant association between
baseline TCA plasma concentration and fall risk within users (HR 2.50,
95\% CI 1.07-5.87, crude model). Adjusted there were no significant
associations between concentrations of SSRIs and fall risk. Also, for
delta concentrations there was no association with fall risk in users.
Conclusion There might be an association between plasma concentrations
of TCAs and the risk of falling in older users. However, these results
needs to be interpreted with caution considering the small sample size
and accompanying limitation of confinement to crude analyses. Therefore,
replication in a larger cohort, preferably including adjustment for
potential confounders and more frequent measures of plasma
concentrations is needed.%
\end{abstract}%



\sloppy


\textbf{Are higher antidepressant plasma concentrations associated with
fall risk in older antidepressant users?}

A.C.Pronk\textsuperscript{1,2}, E.P.van Poelgeest\textsuperscript{1,2},
L.J.Seppala\textsuperscript{1,2} K.J. Ploegmakers\textsuperscript{1,2},
B.H. Stricker\textsuperscript{3},
K.Swart-Polinder\textsuperscript{4,}S.C. van Dijk\textsuperscript{3}, S.
Oliai Araghi\textsuperscript{3,5}, L.C.P.G.M. de
Groot\textsuperscript{7}, N.M. van Schoor\textsuperscript{2,6,} R.A.A.
Math\selectlanguage{ngerman}ôt\textsuperscript{8}, N. van der Velde\textsuperscript{1,2}.

\textbf{Affiliations}

\textsuperscript{1} Amsterdam UMC location University of Amsterdam,
Internal Medicine, Section of Geriatric Medicine, Meibergdreef 9,
Amsterdam, The Netherlands;

\textsuperscript{2.}Amsterdam Public Health, Aging and Later Life,
Amsterdam, The Netherlands

\textsuperscript{3} Department of Epidemiology, Erasmus University
Medical Center, Rotterdam, the Netherlands.

\textsuperscript{4}Amsterdam UMC, location Vrije Universiteit Amsterdam,
General Practice, Boelelaan 1117, Amsterdam, The Netherlands

\textsuperscript{5} Department of Internal Medicine, Erasmus University
Medical Center, Rotterdam, the Netherlands.

\textsuperscript{6} Amsterdam UMC location Vrije Universiteit Amsterdam,
Epidemiology and Data Science, De Boelelaan 1117, Amsterdam, Netherlands

\textsuperscript{7} Division of Human Nutrition and Health, Wageningen
University, Wageningen, the Netherlands.

\textsuperscript{8} Amsterdam UMC location University of Amsterdam,
Hospital Pharmacy - Clinical Pharmacology, Meibergdreef 9, Amsterdam,
The Netherlands



\textbf{Keywords}

Accidental falls, Antidepressants, Older adults, Pharmacokinetics,
Adverse drug events, Plasma concentration

\textbf{What is already known about this subject}

\begin{itemize}
\tightlist
\item
  Antidepressants have been consistently associated with increased fall
  risk and different adverse effects of antidepressants can influence
  fall risk.
\item
  In older adults, there is substantial inter-individual variation in
  drug pharmacokinetics and -- dynamics.
\item
  Whether antidepressant plasma concentrations can predict falls, is
  unknown.
\end{itemize}

\textbf{What this study adds}

\begin{itemize}
\tightlist
\item
  Our study shows an association between TCA plasma concentration and
  fall risk.
\item
  Due to small sample size and only having plasma concentrations
  available only at certain time points, these analyses should be
  considered exploratory.
\item
  Replication in a larger cohort is needed, with more frequent
  measurements of plasma concentrations.
\end{itemize}

\textbf{Data availability}

Because of restrictions based on privacy regulations and informed
consent of the participants, data cannot be made freely available in a
public repository. B-PROOF data can be obtained upon request. Requests
should be directed towards the principal investigators of the study, who
have a protocol for approving data requests.

\textbf{Funding}

This work was supported by the Clementine Brigitta Maria Dalderup fund
(project numbers 3021 and 3549, receiver N. van der Velde), which is an
Amsterdam University fund
(https://www.auf.nl/en/about-the-fund/about.html). The funder had no
role in study design, data collection and analysis, decision to publish,
or preparation of the manuscript.

The initial B-PROOF was funded by the Netherlands Organization for
Health Research and Development (ZonMw, Grant 6130.0031), the Hague;
unrestricted grant from NZO (Dutch Dairy Association), Zoetermeer;
Orthica, Almere; NCHA (Netherlands Consortium Healthy Ageing),
Leiden/Rotterdam; Ministry of Economic Affairs, Agriculture and
Innovation (project KB-15-004-003), the Hague; Wageningen University,
Wageningen; VUmc, Amsterdam; Erasmus Medical Center, Rotterdam;
Unilever, Colworth, UK. The sponsors and patients had no role in the
design or implementation of the study, data collection, data management,
data analysis, data interpretation, or in the preparation, review, or
approval of the manuscript.

\textbf{Author contribution}

A.C.Pronk, L.J.Seppala, K.J.Ploegmakers, E.P.van Poelgeest, R,Mathot,
B.Stricker and N.van der Velde were responsible for the
conceptualization and methodology of the study. K.Swart, S.C.van Dijk,
S.Oliai Araghi, L.C.P.G.M.de Groot and N.M.van Schoor were responsible
for data curation.

A.C.Pronk analyzed the data. A.C.Pronk, L.J.Seppala, E.P.van Poelgeest
and N.van der Velde were responsible for interpreting the data and wrote
the original draft of the manuscript. All authors reviewed the final
version and gave approval of the version to be published.

\textbf{Competing interest}

KS is an employee of the PHARMO Institute for Drug Outcomes Research.
This independent research institute performs financially supported
studies for government and related healthcare authorities and several
pharmaceutical companies. The other authors have declared that no
competing interest exist.

\textbf{Orcid ID}

Orcid ID: 0000-0001-5154-2369

\textbf{Acknowledgments}

We 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.



\textbf{Aim}

Antidepressants are well-established fall-risk increasing drugs(FRIDs)
and therefore falls should be considered an important adverse drug
event(ADE) of antidepressants. However, not all antidepressant users
experience fall incidents and factors associated with increased fall
risk among antidepressant users are incompletely understood. Our
objective was to explore whether antidepressant plasma concentrations
are associated with falls in older antidepressant users.

\textbf{Methods}

For this study, we included antidepressant users of the multicenter
B-PROOF study. Fall incidents were recorded prospectively using fall
calendars. Antidepressant plasma concentrations were analyzed by Liquid
chromatography-mass spectrometry(LC-MS) at baseline and at 2 years
follow-up. The associations between the observed antidepressant
concentration, or concentration change over time (delta) and fall risk
were assessed using Cox proportional hazard and logistic regression
models and adjusted for potential confounders.

\textbf{Results}

In total 93 selective serotonin reuptake inhibitor(SSRI) and 41
antidepressant(TCA) users were identified. There was a significant
association between baseline TCA plasma concentration and fall risk
within users (HR 2.50, 95\% CI 1.07-5.87, crude model). Adjusted there
were no significant associations between concentrations of SSRIs and
fall risk. Also, for delta concentrations there was no association with
fall risk in users.

\textbf{Conclusion}

There might be an association between plasma concentrations of TCAs and
the risk of falling in older users. However, these results needs to be
interpreted with caution considering the small sample size and
accompanying limitation of confinement to crude analyses. Therefore,
replication in a larger cohort, preferably including adjustment for
potential confounders and more frequent measures of plasma
concentrations is needed.

\textbf{Introduction}

Falls in older adults are a major public health problem and associated
with substantial health care costs and decreased quality of
life\textsuperscript{1}. Annually, one-third of individuals over the age
of 65 falls at least once and 20\% of these falls lead to severe
injuries\textsuperscript{2}. Well established fall risk factors are
fall-risk-increasing drugs (FRIDs) \textsuperscript{3} and
antidepressants use has consistently been associated with increased fall
risk \textsuperscript{4}. Therefore, falls should be considered a common
adverse drug event (ADE) of antidepressants \textsuperscript{5}.
However, not all antidepressant users fall and un(der)treated depression
also increases fall risk \textsuperscript{6, 7}. It is therefore
important to identify for whom the risk-benefit ratio of antidepressant
use is detrimental. Which individual factors in antidepressant users
contribute to fall risk, however, is not completely understood. A
dose-response relationship between antidepressants and the incidence of
falls has been demonstrated in older adults \textsuperscript{8, 9}.
However, in older adults there is substantial inter-individual variation
in drug pharmacokinetics and --dynamics \textsuperscript{10, 11}. Also,
often polypharmacy and multimorbidity are present, predisposing to high
prevalence of drug-drug and drug-disease
interactions\textsuperscript{12}. This makes predicting (adverse) drug
effects based on given dosage difficult. Therefore, the availability of
antidepressant plasma concentrations could be of value in predicting
fall risk in antidepressant users.

Measuring drug concentrations to guide dosing of medicines, optimize
treatment response and minimizing ADE, is called therapeutic drug
monitoring (TDM). Especially within psychiatry this is a widely used
approach \textsuperscript{13}. Whether antidepressant plasma
concentrations is associated with fall risk, however, has not been
studied before. Potentially antidepressant plasma concentration
measurements could guide clinical decision making in falls prevention.
For instance, with regard to decisions on deprescribing or exchanging
the antidepressant to a safer alternative. Therefore, our objective was
to explore whether fall risk in older adults is related to the
antidepressant concentration in plasma. We hypothesized that
antidepressant users with higher exposure in plasma would have a higher
risk of falling compared to those with lower concentrations.

\textbf{Methods}

Trial design and participants

For this explorative study, antidepressant users from the multicenter
B-PROOF (B-Vitamins for the Prevention of Osteoporotic Fractures;
ClinicalTrials.gov NCT00696514) study were included. A detailed
description of the trial was published previously \textsuperscript{14}.
In short, B-PROOF was a large multicenter, double-blind,
placebo-controlled trial for which persons 65 years and older with
mildly elevated homocysteine levels were recruited to participate
between 2008 and 2011, for a follow-up period of 2-3 years. A total of
2,919 participants were included. The primary aim was to assess whether
the addition of vitamin B12 and folic acid to vitamin D therapy
prevented osteoporotic fractures. Because the intervention did not
affect fall-related outcomes, data could be used for the current
observational study \textsuperscript{15}. The Medical Ethics Committee
of Wageningen University approved the study protocol of the B-PROOF
study \textsuperscript{14}. Before entering the study, all participants
gave their written informed consent. All experiments were conducted in
accordance with the principles of the Declaration of Helsinki.

2.2 Antidepressant usage

Participants were considered antidepressant user based on pharmacy
prescription and self-reported usage data. Based on the number of users,
participants using TCAs: amitriptyline (N06AA09), nortriptyline
(N06AA10), and the SSRIs: citalopram (N06AB04), escitalopram (N06AB10),
fluoxetine (N06AB03), fluvoxamine (N06AB08), paroxetine (N06AB05),
sertraline (N06AB06) and the serotonin-norepinephrine reuptake inhibitor
(SNRI) venlafaxine (N06AX16) \textsuperscript{16} were selected.

Usage was defined as having a prescription (based on pharmacy dispensing
record data, obtained from the Dutch Foundation for Pharmaceutical
Statistics (SFK)). 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 have not had a refill in the 30 days before. In case
of missing pharmacy data, usage was defined in case of self-reported
usage based on questionnaires at baseline and follow-up.

To determine used dosage, defined daily dose (DDD) was used. DDD is a
statistical measure of drug consumption and is the assumed average
maintenance dose per day for a drug used for its main indication in
adults \textsuperscript{16}. The average prescribed daily dose was based
on the prescription (or self-reported data) in closest proximity to the
date of baseline blood sampling.

\emph{}

2.3 Exposure: assessment of antidepressant concentration in plasma

Blood samples were obtained from participants in the morning.
Participants were in a fasted state, or had had a light breakfast.
Venous blood was drawn in an EDTA tube at both baseline and follow up
study visits, and stored at -80°C until analysis.

The plasma concentrations of the following antidepressants and their
corresponding (active) metabolites were analyzed using LC-MS with
electrospray ionization (Thermo Finnigan TSQ Access, Waltham, MA, USA):
amitriptyline, nortriptyline, citalopram and metabolite
des(methyl)-citalopram, fluoxetine and metabolite norfluoxetine,
fluvoxamine, paroxetine, venlafaxine and metabolite desmethylvenlafaxine
and sertraline and metabolite norsertraline. A detailed description of
the analysis method can be found in the supporting
information\textbf{(Supporting information appendix S1} ). With regard
to the assessment of total drug exposure metabolite concentrations of
the parent drug and metabolite were summed as in line with clinical
practice. Some amitriptyline and nortriptyline users had plasma
concentration below the lower limit of quantification (LLQ) of the LC-MS
method. In these samples, it was possible to determine semi-quantitative
concentration values \textbf{(Supporting information appendix S1)} .

2.4 Outcome

The primary outcome was time to first fall during follow-up. Falls were
defined as ``an unintentional change in position resulting in coming to
rest at a lower level or on the ground'' as recommended by the
Prevention of Falls Network Europe \textsuperscript{17}. Falls were
reported prospectively by using fall calendars, which the participants
filled in weekly and returned to the research team every three months.
Participants were contacted via telephone in case of missing or unclear
data. Participants were followed until their first fall incident until
their drop-out date or the date of their last calendar, date of death or
end of the study, which ever came first \textsuperscript{14}. We used
the data from fall calendars as a binary variable (yes/no) for the
analyses of plasma concentrations at follow-up and delta concentration.

Covariates

Participant data were collected at baseline and follow-up using a
questionnaire that included data on age, gender, smoking, alcohol
consumption, comorbidities and history of falls. During study visits,
data was collected on (self-reported) medication use, body mass index
(BMI), blood pressure, serum creatinine, physical performance, handgrip
strength, cognitive status, depressive symptoms and presence of pain.
For screening of depressive symptoms, the 15-item version of the
Geriatric Depression Scale (GDS-15) was used. Cognitive performance was
assessed by the mini-mental state examination (MMSE). For pain, the
EURoQoL-item 4 was used (pain or other complaints). Baseline use of
concomitant medication was grouped based on the ATC coding system, and
polypharmacy was defined as usage of five or more
medications\textsuperscript{18}. Serum creatinine levels were used to
calculate kidney function according to the Cockcroft and Gault formula.

2.6 Statistical analyses

If antidepressant use was reported, and plasma concentration was
undetectable, the respective concentration was set at half of the LLQ.
For amitriptyline and nortriptyline, where also semi-quantitative
concentrations below LLQ were available, half of the lowest detectable
concentration was taken. Because the number of participants in the
various individual antidepressant groups were too low for the analyses,
the individual antidepressants subclasses needed to be pooled into two
groups: SSRIs and TCAs. Although venlafaxine is a selective
serotonin-norepinephrine reuptake inhibitor (SNRI), we analyzed
venlafaxine combined with the SSRIs. Since the dose of venlafaxine in
our cohort did not exceed 150 milligram (mg), SNRIs mainly inhibit
reuptake of serotonin and thus closely resemble
SSRIs\textsuperscript{19}.

Relationship between drug exposure and fall risk were analyzed with
plasma concentrations expressed on both a continuous and categorical
scale. If a participant used two or more antidepressants concomitantly,
only the antidepressant with the highest concentration was included in
the analyses. First, the continuous plasma concentration levels of the
individual antidepressants were analyzed. After that, we standardized
the concentrations of the different antidepressants by creating z-scores
to be able to combine the continuous concentrations. Second, for each
antidepressant the median of the plasma concentration was calculated and
the concentrations were reclassified into a binary category (below
(which was set as reference) or above the median). Third, to explore the
influence of the highest plasma concentrations, the antidepressant
plasma concentrations were divided into four categories. The reference
category contained the concentrations below the LLQ. After that, the
concentrations above LLQ were equally divided into tertiles. For the
TCAs, the remaining number of participants per category was too low.
Thus the reference category contained the lowest tertile and the
concentrations below LLQ and the middle and highest tertile were
combined. The same was applied for the SSRI follow-up concentrations.
Also, delta concentrations (concentration at follow-up minus
concentration at baseline) were calculated, reflecting concentration
changes over time. These were reclassified into a binary category,
negative (decrease or equal concentration over time) or positive
(concentration increase over time)

Baseline characteristics were compared between fallers and non-fallers
in antidepressant users. Differences between groups were tested using
chi-square test, t-test or a Mann-Whitney U test (categorical and
continuous non-normally and normally distributed data, respectively). To
study the association between the antidepressant plasma concentration at
baseline and falls during follow-up, Cox proportional hazard models were
used to calculate hazard ratios (HRs). First, we built a model adjusted
for age and gender (model 1). Second, the following covariates were
selected as potential confounders based on a Directed Acyclic Graph
(DAG) and included in the models if they changed the HR of the
association by \selectlanguage{english}[?]10\% (model 2): region, BMI, smoking, alcohol, pain,
depressive symptoms, MMSE, number of medication and estimated glomerular
filtration rate (eGFR). If covariates could not be added, due to the
lack of 10 fall events per covariate \textsuperscript{20}, only the
unadjusted model is presented. For follow-up visit and delta
concentrations, logistic regression models were used to calculate odds
ratios (ORs) for the association between concentration and fall risk
prior to follow-up visit. The same models as described for the Cox
proportional hazard models were applied.

To assess whether antidepressant plasma concentrations were correlated
with dosage, we calculated Pearson correlation coefficients. Since there
were no signs of multicollinearity (correlation coefficient
\textless{}0.5) between plasma concentration and dosage, as a possible
marker for example for disease severity, was added to model 2 to test
whether dosage could be a confounder.

P-values \textless{}0.05 were considered statistically significant.
Statistical analyses were performed in SPSS (version 28.0, IBM, Armonk,
NY, USA).



\textbf{3. Results}

3.1 Study population

A total of 132 antidepressant users were identified from the B-PROOF
cohort. Of those, 59.8\% reported a fall during follow up.
In\textbf{Table 1,} the baseline characteristics of fallers and
non-fallers in antidepressant users are shown. Fallers were more often
female, experienced more falls in the 12 months prior to study
enrollment and more frequently used benzodiazepines concomitantly. The
antidepressants most often used were paroxetine (34.6\%) and
amitriptyline (23.5\%). The range of plasma concentrations were
fluoxetine: \textless{}20 \selectlanguage{greek}µ\selectlanguage{english}g/L -- 366 \selectlanguage{greek}µ\selectlanguage{english}g/L (fluoxetine + norfluoxetine),
fluvoxamine: 126-330 \selectlanguage{greek}µ\selectlanguage{english}g/L, sertraline: \textless{}5 \selectlanguage{greek}µ\selectlanguage{english}g/L -91 \selectlanguage{greek}µ\selectlanguage{english}g/L,
paroxetine: \textless{}5 \selectlanguage{greek}µ\selectlanguage{english}g/L -370 \selectlanguage{greek}µ\selectlanguage{english}g/L, (es)citalopram: \textless{}5
\selectlanguage{greek}µ\selectlanguage{english}g/L -174 \selectlanguage{greek}µ\selectlanguage{english}g/L, amitriptyline: \textless{}22 \selectlanguage{greek}µ\selectlanguage{english}g/L -77.7 ug/L
(amitriptyline + nortriptyline), nortriptyline: \textless{}22 \selectlanguage{greek}µ\selectlanguage{english}g/L -329
\selectlanguage{greek}µ\selectlanguage{english}g/L. Median concentrations of the individual antidepressants did not
differ significantly between fallers and non-fallers, both at baseline
and follow-\textbf{up (Supporting information Table S1).}
In\textbf{supporting information Table S2} present an overview of the
reference values for therapeutic and (potential) toxic concentrations.
Paroxetine, (es)citalopram plasma concentrations were in therapeutic
range, but relatively low. Sertraline and amitriptyline plasma
concentration were below therapeutic range. Nortriptyline plasma
concentrations were higher in fallers compared to non-fallers
(non-significant) and at follow-up above therapeutic range.



\textbf{Table 1 - Baseline characteristics of antidepressant users}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
Non-fallers n= 53\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
Fallers n= 79\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
P-value *\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Age (years) \textsuperscript{a}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
73.4 (5.7)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
74.4 (5.9)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.33\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Gender \textsuperscript{b} male female\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
22 (41.5) 31 (58.5)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
18 (22.8) 61 (77.2)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
\textbf{0.02}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Body Mass Index (kg/m\textsuperscript{2}) \textsuperscript{a}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
27.3 (4.0)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
27.0 (3.6)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.69\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Alcohol use (yes) \textsuperscript{b}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
42 (79.2)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
55 (69.6)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.22\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Smoking (current) \textsuperscript{b}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
12 (22.6)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
13 (16.5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.67\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Depressive symptoms (GDS) \textsuperscript{c}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
2 (1-3)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
2 (1-5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.60\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
MMSE score \textsuperscript{c}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
28 (27-29)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
28 (26-29.5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.71\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Pain (yes) \textsuperscript{b} No pain Some pain Severe pain\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
20 (37.7) 29 (54.7) 4 (7.5)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
25 (31.6) 47 (59.5) 7 (8.9)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
0.77\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Physical performance \textsuperscript{c \#}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
8 (4-10)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
7 (4-9)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.27\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Handgrip strength maximum (kg) \textsuperscript{a}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
29.6 (9.7)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
26.6 (9.1)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.08\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Walking aid use (yes) \textsuperscript{b}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
15 (28.3)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
22 (27.8)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.96\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Number of falls in 12 months prior to study enrolment
\textsuperscript{b} No falls One fall Two or more falls\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
31 (75.6) 7 (17.1) 3 (7.3)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
26 (41.9) 19 (30.6) 17 (27.4)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
\textbf{0.002}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
eGFR ( ml min\textsuperscript{-1} 1.73m\selectlanguage{ngerman}²) \textsuperscript{c}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
70.0 (60.1-80.7)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
65.3 (54.7-76.8)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.19\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Number of medications \textsuperscript{a}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
4.1 (2.4)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
4.7 (2.3)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.12\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Polypharmacy (yes) \textsuperscript{b}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
12 (30)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
28 (70)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.12\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Benzodiazepine use (yes) \textsuperscript{b}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
4 (7.5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
20 (25.3)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{0.01}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
SSRI use\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
37 (69.8)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
56 (70.9)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.89\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
TCA use\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
17 (32.1)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
24 (30.4)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.84\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Opioid use (yes) \textsuperscript{b}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
2 (3.8)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
10 (12.7)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.08\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Antipsychotic use (yes) \textsuperscript{b}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
4 (7.5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
5 (6.3)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.79\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textsuperscript{a} Mean (SD), \textsuperscript{b} presented as n (\%),
\textsuperscript{c} Median (IQR; 25\%-75\%) GDS= Geriatric Depression
Scale; MMSE=Mini-Mental State Examination; eGFR=Estimated glomerular
filtration rate according to Cockcroft and Gault formula; Polypharmacy:
use of five or more medications \# physical performance: combined score
of the walking test, chair stand test and tandem stand test
(maximum=12). * statistically significant at p-value
\textless{}0.05\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textsuperscript{a} Mean (SD), \textsuperscript{b} presented as n (\%),
\textsuperscript{c} Median (IQR; 25\%-75\%) GDS= Geriatric Depression
Scale; MMSE=Mini-Mental State Examination; eGFR=Estimated glomerular
filtration rate according to Cockcroft and Gault formula; Polypharmacy:
use of five or more medications \# physical performance: combined score
of the walking test, chair stand test and tandem stand test
(maximum=12). * statistically significant at p-value
\textless{}0.05\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textsuperscript{a} Mean (SD), \textsuperscript{b} presented as n (\%),
\textsuperscript{c} Median (IQR; 25\%-75\%) GDS= Geriatric Depression
Scale; MMSE=Mini-Mental State Examination; eGFR=Estimated glomerular
filtration rate according to Cockcroft and Gault formula; Polypharmacy:
use of five or more medications \# physical performance: combined score
of the walking test, chair stand test and tandem stand test
(maximum=12). * statistically significant at p-value
\textless{}0.05\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textsuperscript{a} Mean (SD), \textsuperscript{b} presented as n (\%),
\textsuperscript{c} Median (IQR; 25\%-75\%) GDS= Geriatric Depression
Scale; MMSE=Mini-Mental State Examination; eGFR=Estimated glomerular
filtration rate according to Cockcroft and Gault formula; Polypharmacy:
use of five or more medications \# physical performance: combined score
of the walking test, chair stand test and tandem stand test
(maximum=12). * statistically significant at p-value
\textless{}0.05\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

3.2 SSRI concentration at baseline \& time to first fall

The results of the association between plasma concentrations of SSRIs at
baseline and time to first fall are presented in \textbf{Table 2} .
There were no significant associations between baseline plasma
concentration and time to first fall in SSRI users.



\textbf{Table 2. Association between baseline SSRI plasma concentration
and time to first fall}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\textbf{Category} & \textbf{N} & \textbf{Model 1 \textsuperscript{a}} &
\textbf{P-value*} & \textbf{Model 2 \textsuperscript{b}} &
\textbf{P-value*}\tabularnewline
\midrule
\endhead
Concentration divided on median & 93 & 0.91 (0.54-1.55) & 0.74 & 1.10
(0.63-1.94) & 0.73\tabularnewline
Concentrations below LLQ & 10 & Ref. & 0.61 & &\tabularnewline
Lowest tertile & 26 & 1.59 (0.62-4.07) & 0.33 & - &\tabularnewline
Middle tertile & 29 & 1.16 (0.44-3.01) & 0.77 & - &\tabularnewline
Highest tertile & 28 & 1.05 (0.41-2.69) & 0.92 & - &\tabularnewline
Z-score & 93 & 0.96 (0.72-1.27) & 0.76 & 1.09 (0.79-1.52) &
0.59\tabularnewline
Data is presented in Hazard Ratio with 95\% confidence interval. N =
number of plasma concentration. Number of events=57 \textsuperscript{a}
Model 1: adjusted for age and gender. \textsuperscript{b} Model 2 of
median concentration and z-score adjusted for DDD, other covariates did
not influence the model. Model 2 of category percentiles was not applied
considering the limited amount of events. *statistically significant at
p\textless{}0.05 & Data is presented in Hazard Ratio with 95\%
confidence interval. N = number of plasma concentration. Number of
events=57 \textsuperscript{a} Model 1: adjusted for age and gender.
\textsuperscript{b} Model 2 of median concentration and z-score adjusted
for DDD, other covariates did not influence the model. Model 2 of
category percentiles was not applied considering the limited amount of
events. *statistically significant at p\textless{}0.05 & Data is
presented in Hazard Ratio with 95\% confidence interval. N = number of
plasma concentration. Number of events=57 \textsuperscript{a} Model 1:
adjusted for age and gender. \textsuperscript{b} Model 2 of median
concentration and z-score adjusted for DDD, other covariates did not
influence the model. Model 2 of category percentiles was not applied
considering the limited amount of events. *statistically significant at
p\textless{}0.05 & Data is presented in Hazard Ratio with 95\%
confidence interval. N = number of plasma concentration. Number of
events=57 \textsuperscript{a} Model 1: adjusted for age and gender.
\textsuperscript{b} Model 2 of median concentration and z-score adjusted
for DDD, other covariates did not influence the model. Model 2 of
category percentiles was not applied considering the limited amount of
events. *statistically significant at p\textless{}0.05 & Data is
presented in Hazard Ratio with 95\% confidence interval. N = number of
plasma concentration. Number of events=57 \textsuperscript{a} Model 1:
adjusted for age and gender. \textsuperscript{b} Model 2 of median
concentration and z-score adjusted for DDD, other covariates did not
influence the model. Model 2 of category percentiles was not applied
considering the limited amount of events. *statistically significant at
p\textless{}0.05 & Data is presented in Hazard Ratio with 95\%
confidence interval. N = number of plasma concentration. Number of
events=57 \textsuperscript{a} Model 1: adjusted for age and gender.
\textsuperscript{b} Model 2 of median concentration and z-score adjusted
for DDD, other covariates did not influence the model. Model 2 of
category percentiles was not applied considering the limited amount of
events. *statistically significant at p\textless{}0.05\tabularnewline
\bottomrule
\end{longtable}

3.3 SSRI concentration at follow-up visit \& fall risk

The results of the association between plasma concentrations of SSRIs at
follow-up and fall risk prior study visit are presented in Supporting
information \textbf{Table S3.} An increased fall risk was found for
users with concentrations in the middle tertile compared to users with
the lowest concentrations (OR 4.67, 95\% CI 1.09-19.9). However, after
adjusting for confounders this association disappeared.

3.4 TCA concentration at baseline \& time to first fall

The results of the association between plasma concentrations of TCAs and
time to first fall are presented in \textbf{Table 3.} A significantly
increased fall risk was seen for higher TCA plasma concentrations
compared to the lowest plasma concentrations (HR 2.50 (1.07-5.87).



\textbf{Table 3. Association between TCA baseline plasma concentration
and time to first fall}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
& \textbf{N} & \textbf{Crude model} \textsuperscript{a} &
\textbf{P-value*}\tabularnewline
\midrule
\endhead
Concentration divided on median & 41 & 1.50 (0.67-3.35) &
0.32\tabularnewline
Concentrations below LLQ \& lowest tertile concentrations & 31 & Ref.
&\tabularnewline
Middle \& highest tertile concentrations & 10 & 2.50 (1.07-5.87) &
0.04\tabularnewline
Z-score & 41 & 1.25 (0.86-1.81) & 0.25\tabularnewline
Data is presented in Hazard ratio with 95\% confidence interval. N =
number of plasma concentration samples. Number of events=24
\textsuperscript{a} Model 1 was not applied due to the limited amount of
events. *statistically significant at p\textless{}0.05 & Data is
presented in Hazard ratio with 95\% confidence interval. N = number of
plasma concentration samples. Number of events=24 \textsuperscript{a}
Model 1 was not applied due to the limited amount of events.
*statistically significant at p\textless{}0.05 & Data is presented in
Hazard ratio with 95\% confidence interval. N = number of plasma
concentration samples. Number of events=24 \textsuperscript{a} Model 1
was not applied due to the limited amount of events. *statistically
significant at p\textless{}0.05 & Data is presented in Hazard ratio with
95\% confidence interval. N = number of plasma concentration samples.
Number of events=24 \textsuperscript{a} Model 1 was not applied due to
the limited amount of events. *statistically significant at
p\textless{}0.05\tabularnewline
\bottomrule
\end{longtable}

3.5 TCA concentration at follow-up visit \& fall risk

There were no significant associations between plasma concentrations at
follow-up visit and fall risk prior to study visit (\textbf{Supporting
information table S4)} .

3.6 Plasma concentration over time

To investigate if change in plasma concentration over time was
associated with fall risk, we analyzed 73 SSRI and 27 TCA samples with
complete data. An increase of concentration over time was not
significantly associated with fall risk (\textbf{Supporting information
table S5} ).

3.7 Role of dosage

No dose-response association was found for the different antidepressant
groups regarding fall risk in antidepressant users \textbf{(Supporting
information table S6)} .



\textbf{4. Discussion}

Our results showed that the risk of falling in older users of TCAs is
possibly associated with drug exposure, whereas no association was found
in users of SSRIs. These results need to be interpreted with caution
considering the small sample size and subsequently confinement to
unadjusted analysis for the TCA users.

To our knowledge, this is the first study to assess whether
antidepressant blood concentrations are associated with fall risk within
antidepressant users. Falls have been established to be an important ADE
in community-dwelling older persons. Previous studies have consistently
established the association between antidepressant use and
falls\textsuperscript{4}. However, literature linking antidepressant
plasma concentrations and falls is scarce. A first indication that
measuring antidepressant plasma concentrations might be of value in
falls prevention was demonstrated in a case series of patients with
drug-induced falls. This study suggested that TDM may help identify
patients with drug-induced falls and confirm clinical suspicion of an
ADE \textsuperscript{21}. The observed possible association between TCA
concentrations and fall risk is in line with earlier studies that
addressed the role of antidepressant plasma concentrations in
fall-related outcomes, e.g. orthostatic hypotension
(OH)\textsuperscript{22}. Significant correlations between serum
concentrations of amitriptyline and fluvoxamine and orthostatic blood
pressure drop have been demonstrated \textsuperscript{22}. OH is
considered an important fall risk factor and pathway in drug-related
falls \textsuperscript{23}. OH results in transient cerebral
hypoperfusion upon standing, which may result in a syncope and/or fall.
OH is a prevalent ADE in antidepressants, best known for TCAs, but also
seen with SSRIs \textsuperscript{7}. Furthermore, anticholinergic
activity, which can increase fall risk, by among others risk of delirium
and visual disturbances, increases with increasing plasma concentrations
of nortriptyline (even at therapeutic levels) \textsuperscript{24}.

We observed a possible increased fall risk for users with higher plasma
concentrations of TCA , which is in line with our hypothesis. However,
the sample size was small. Furthermore, especially for amitriptyline the
measured concentrations were below reference range for therapeutic
effect or in therapeutic range, thus we cannot generalize our findings
to potentially toxic concentrations. However, older adults are more at
risk for adverse events due to altered pharmacokinetics and --
dynamics\textsuperscript{25}. TDM for TCAs is well-established in
clinical practice, both for therapeutic effect and
toxicity\textsuperscript{26-29}. For SSRIs, the clinical use of TDM is
less frequently employed, especially in older adults
\textsuperscript{30}. For most SSRIs therapeutic reference ranges are
wide, evidence for a relationship between drug concentration and
therapeutic outcome is weak and risk for toxicity is relatively low
compared to TCAs\textsuperscript{29, 31, 32}. So in general, available
data do not suggest benefit for (routine) monitoring of SSRI plasma
concentrations\textsuperscript{31}. However, TDM for SSRIs is
recommended in specific populations like advanced age
\textsuperscript{13, 32}. Since, studies have shown higher exposure to
antidepressant concentrations compared to younger patients
\textsuperscript{33, 34}. And also adequate use of TDM has been shown to
be cost effective in older adults \textsuperscript{35, 36}. Thus, the
lack of applying TDM and lack of lower blood concentrations as target,
can possibly contribute to the risk of falls, an important ADE.

An important strength of our study is the prospective nature, using fall
calendars. In falls research this method is considered the golden
standard to avoid recall bias \textsuperscript{37}. Also, data on
medication use was collected thoroughly, using both pharmacy
prescription data and self-reported medication lists. Our study also has
some important limitations. First, limited power was a problem. Despite
the large B-PROOF database, the remaining group of participants that met
the inclusion criteria was small as prevalence of antidepressant usage
was low. Due to small groups, we needed to pool the data and needed to
standardize and categorize the plasma concentrations. Second,
information about plasma concentrations during the fall incident was not
available, since such an unplanned event cannot be anticipated for. Thus
we only had blood samples from baseline and follow-up study visit.
Baseline or follow-up plasma concentrations might not be representative
for the plasma concentration at the time of the fall incidents. Also,
for some participants follow-up samples were missing. Thus it was unsure
whether they were an actual antidepressant user at the time of the fall
incident. However, this issue probably did not affect our results, since
when repeating the analyses in the participants with baseline and
follow-up samples, the results did not change significantly (data not
shown). Third, for the association between delta concentrations and fall
risk cannot be ruled out that concentrations changes did not reflect
clinical relevant differences. By coding them binary (either increase or
decrease) it could be that not relevant changes are mixed with clinical
relevant changes. Fourth, our cohort consisted of relatively healthy
community-dwelling older people. Frail older adults, can exhibit
different patient characteristics, different pharmacokinetics which
could lead to different results \textsuperscript{25}.

\textbf{5.Conclusion}

Our explorative study showed a possible association between plasma
concentrations and fall risk in older TCA users, but not in SSRI users.
However, this needs to be interpreted with caution due to the small
sample size and accompanying impossibility to perform multivariate
analyses in this group. The current study has no direct clinical
implications as our findings should be further re-evaluated in a larger
cohort. Ideally replication would not only include multivariate
assessment, but also include information about medication adherence and
concentration measurements around the fall incident. However, this topic
is important since it would give us more detailed insight in risk
factors determining medication related fall risk and has the potential
to personalize clinical decision making, maximizing benefit and
minimizing harm in antidepressant use for older persons at risk of
falling.

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