Escitalopram and the Risk of Serious Adverse Events

Background Many older adults experience mental health disorders, such as depression and anxiety, alongside having low kidney function. Escitalopram, a selective serotonin reuptake inhibitor, is a commonly prescribed antidepressant to older adults for depression and anxiety treatment, but aging and low kidney function can lead to increased plasma levels and a higher risk of adverse events. Inconsistent starting dose adjustments for patients with low kidney function have been noted in prescribing references, product monographs, and other standard sources. This may be one reason for the inconsistent dosing observed in routine practice, where many older adults with low kidney function are initiated on escitalopram at a dose of 10 mg per day. Such a dose, compared to the lower dose of 5 mg per day, may be associated with a higher rate of falls, fractures, gastrointestinal bleeding, arrhythmias, hospitalization, and mortality. Despite these concerns, there is a lack of real-world evaluation. Using a novel high-throughput approach using Ontario healthcare databases, the investigators identified an increased risk of adverse outcomes in patients with advanced CKD (estimated glomerular filtration rate (eGFR) \<45 mL/min/1.73 m² without a history of dialysis or a kidney transplant) who were newly prescribed Escitalopram compared to a similar cohort of non-users. To advance and validate these early findings, the investigators plan to conduct a population-based retrospective cohort study among older adults in Ontario, Canada. This study will use data to investigate the 30-day risk of serious adverse events after starting high versus low doses of escitalopram in older adults with low kidney function, aiming to enhance safer prescribing practices. Methods In this population-based retrospective cohort study, eligible participants will include older adults (≥66 years) with eGFR \<45 mL/min/1.73 m2 (not receiving dialysis or having a history of kidney transplantation) from Ontario (and possibly Alberta) who were dispensed a new outpatient prescription for oral Escitalopram (5 or 10 mg/day) with a day supply of ≥7 days. In Ontario, accrual will occur between January 1, 2008, and January 1, 2025. Based on the prescribed daily dose, individuals will be divided into two groups: low-dose (5 mg/day) and high-dose (10 mg/day). Propensity score weighting will be used to ensure both groups are well-balanced on a comprehensive set of measured baseline characteristics. The primary outcome will be a 30-day composite of all-cause hospitalization, emergency department visit, or mortality. Objectives Is there a higher 30-day risk of a composite outcome of all-cause hospitalization, all-cause emergency department visit, or all-cause mortality among older adults with low kidney function (an eGFR \<45 mL/min per 1.73 m2 but not receiving dialysis or having a history of kidney transplantation) who initiate a high dose (10 mg/day) versus a low dose (5 mg/day) escitalopram in the outpatient setting? Does the category of baseline eGFR modify the risk of a 30-day composite outcome, , among patients who initiate a higher dose versus a lower dose of escitalopram in the outpatient setting? The cohort will be expanded to include all levels of baseline eGFR, and eGFR will be categorized as ≥60, 45-59, and \<45 mL/min per 1.73 m². Study Design and Setting Data Sources: The investigators propose a population-based retrospective cohort study using using linked administrative health data from Ontario, Canada. If the Ontario cohort is small to generate reliable estimates, the investigators will augment the sample size by performing the same analysis using Alberta health administrative data. Ontario data will be sourced from ICES (ices.on.ca). It offers secure, encrypted individual-level data for Ontario residents, all with universal access to hospital and physician services under a government-funded, single-payer healthcare system. The use of data in this study is authorized under section 45 of Ontario's Personal Health Information Protection Act, which does not require review by a research ethics board. The study will use Ontario's comprehensive health databases, such as the Ontario Drug Benefit (ODB) for prescription data, the Registered Persons Database (RPDB) for demographics and vital status, Canadian Institute for Health Information Discharge Abstract Database (CIHI-DAD)and National Ambulatory Care Reporting System (NACRS) for hospitalizations and emergency visits, Ontario Health Insurance Plan (OHIP) Database for physician billing claims, and Ontario Laboratories Information System (OLIS) for laboratory data, including serum creatinine, to estimate kidney function. If the investigators proceed with conducting the study in Alberta, the Alberta data will be accessed through the Alberta Kidney Disease Network (AKDN). This dataset ends in \~ 2021. The investigators are publicly registering the study protocol and documenting the study description, design, and statistical analysis prior to conducting outcome analyses. The results of this study will be reported adhering to RECORD reporting guidelines. Study Population The investigators will include all older adults (≥66 years) with an eGFR \<45 mL/min per 1.73 m2 (not receiving dialysis or having a history of kidney transplantation) who received a new outpatient prescription for oral escitalopram with an initial dose of 5 or 10 mg/day and a day supply of ≥7 days between 2008 and 2024. The dispensing date of the prescription will serve as the index date, and only the first eligible prescription will be included to ensure unique cohort entry. Each individual can enter the cohort only once. Patients will be categorized into "high-dose" and "low-dose" SSRI users. Baseline Characteristics Health records, census files, hospital records, laboratory data, and physician claims will provide baseline variables, including demographic characteristics (such as age, sex, rurality, and neighborhood income quintile), comorbidities, and medication use. Baseline comorbidities and healthcare utilization will be assessed using 5-year and 1-year look-back periods from the index date, respectively. Baseline medication use will be assessed within 120 days prior to the index date. Patients are required to have an outpatient serum creatinine level measured within 365 days prior to cohort entry, allowing for the estimation of eGFR using the 2021 CKD-EPI equation. Exclusion criteria include end-stage kidney disease (on dialysis or having received a kidney transplant). Outcomes The prespecified primary outcome is defined as the 30-day composite outcome of all-cause hospitalization, emergency department visit, or mortality. Only the first hospitalization or emergency department visit in the first 30 days is counted. The components of the primary composite outcome (all-cause hospitalization, all-cause emergency department visits, or all-cause mortality) is accurately coded in ICES data. The observation window for study outcomes will begin on the date of prescription fill and will last 30 days post-initiation. Loss to follow-up for study outcomes is expected to be \<0.3% as the observation window for outcomes will be \<90 days, and provincial emigration in this age group (the only reason for loss to follow-up) is \<0.5% annually. Participant observation time will be censored at the time of the first occurrence of the outcome of interest, death (if not the outcome of interest), or 30 days after the index date, whichever comes first. Secondary outcomes will include 1. Components of the primary composite outcome: 30-day all-cause hospitalization, all-cause emergency department visit, and all-cause mortality, each of which is examined separately. 2. 30-day composite outcome of a hospital encounter (hospital admission or emergency department visit) with delirium or encephalopathy (disorientation, transient alteration of awareness, other and unspecified symptoms and signs involving cognitive function) or hospital encounter with receipt of an urgent computed tomography scan of the head. 3. 30-day composite outcome of a hospital encounter (hospital admission or emergency department visit) with fracture (hip, femur, humerus, wrist/forearm, pelvis, and spine), falls, hypotension, or syncope 4. 30-day hospital encounter (hospital admission or emergency department visit) with composite outcome of atrial fibrillation/flutter or ventricular arrhythmia, or other arrhythmia (including pacemaker insertion, palpitations, tachycardia unspecified, atrioventricular block, supraventricular tachycardia, other conduction disorders, implantable cardiac defibrillator) Statistical analysis plan Categorical variables will be summarized as frequencies and proportions, while continuous variables will be summarized as means with standard deviations (SD) or medians with interquartile ranges (IQR), as appropriate. Baseline characteristics will be compared between the groups, starting with the high-dose (10 mg/day) and the low-dose (5 mg/day) groups, using standardized mean differences (SMDs). An absolute SMD greater than 10% will be considered indicative of a meaningful imbalance. Balancing comparator group: The investigators will use inverse probability of treatment weighting (IPTW) on the propensity score to balance baseline characteristics between the high-dose (10 mg/day) and low-dose (5 mg/day) groups, including known predictors of escitalopram use. Propensity scores will be generated using a multivariable logistic regression model with all baseline characteristics. The average treatment effect in the treated (ATT) weights will be used, where patients in the low-dose group will be assigned weights calculated as (propensity score / \[1 - propensity score\]), and patients in the high-dose group will receive a weight of 1. This method will produce a weighted pseudo-sample of patients in the referent group, i.e., low-dose escitalopram (5 mg/day), with a similar distribution of measured baseline characteristics as the high-dose escitalopram (10 mg/day) group. Baseline characteristics will be compared between groups using standardized differences in both unweighted and weighted samples. Regression analysis: To evaluate the primary outcome composite measure of all-cause hospitalization, all-cause emergency department visit, or all-cause mortality, the investigators will apply a modified Poisson regression analysis to estimate the risk ratio (95% CI) and binomial regression to estimate the risk difference (95% CI) using the weighted cohort, with the low-dose escitalopram (5 mg/day) group as the referent. Secondary analyses: The investigators will conduct independent testing for all secondary outcomes without adjusting for multiple comparisons. Each test will be performed and reported independently. In line with best practices, the primary outcome will be presented with its P-value, and the investigators will report all secondary outcomes using point estimates with 95% confidence intervals. Additional analyses The investigators plan to conduct five additional analyses. 1. Effect measure modification (EMM): For EMM, the investigators will expand the cohort to all the eGFR levels and categorize them into three groups: eGFR ≥60, 45-\<60, and \<45 mL/min/1.73 m2. Baseline characteristics between high-dose (10 mg/day) and low-dose (5 mg/day) escitalopram groups will be assessed using standardized differences for all renal function categories combined and then within each of three eGFR categories (≥60, 45-\<60, and \<45 mL/min/1.73 m²). To balance baseline characteristics between high-dose and low-dose escitalopram groups, the investigators will apply the IPTW method (described above), based on propensity scores for all the eGFR categories combined and within each of the three eGFR categories. EMM will be assessed on both the additive and multiplicative scales. * For additive interaction, the investigators will use binomial regression with an identity link to estimate risk differences, including an interaction term between low-dose and high-dose escitalopram groups and eGFR strata. * For multiplicative interaction, the investigators will use modified Poisson regression analysis to estimate risk ratios, including an interaction term between low-dose and high-dose escitalopram groups and eGFR strata. 2. The high-throughput computing analysis in which the investigators executed 700+ population-based, new-user cohort studies, each comparing 74 acute (30-day) outcomes across strata of kidney function (PMID: 38186562) suggested escitalopram use versus no use causes harm in patients with low kidney function. The high-throughput computing analysis used Ontario data from January 1, 2008 to March 1, 2020. A subgroup analysis will be performed for the primary analysis restricting the cohort to before March 1, 2020 (overlap with high-throughput computing period) and after March 1, 2020 (no overlap). 3. Compute the hazard ratio for all outcomes within 30 days, illustrating the effect of the intervention on each outcome over time. The investigators expect hazard ratios to be similar to risk ratios. 4. Perform E-value analyses to determine the minimum association strength an unmeasured confounder would need with both the prescription drug and the outcome of interest to eliminate the observed association. 5. The investigators will compare risk of the primary outcome between a group of new users of 10 mg/day of escitalopram vs. a group of older adults with no escitalopram use (non-users). The same will also be done with a group of new users of 5 mg/day of escitalopram vs. a group of older adults with no escitalopram use (non-users). The investigators will utilize the same baseline characteristics, and employ the statistical analysis methods used in the primary analysis. Combining Outcome Results from Ontario and Alberta \*This approach will only be used if the investigators proceed with analyzing Alberta data. Privacy-preserving methods: In Canada, the investigators are unable to connect individual-level patient data from different provinces due to privacy concerns. However, the investigators will combine results from both provinces (Ontario and Alberta) using a privacy-preserving method, to maintain data privacy and regulatory compliance. The proposed method requires only a single transfer of summary-level outputs from each province to the research team (will be adapted from the techniques of Shu et al. 2025).