Association between antidepressant use and reduced risk of intubation or death in hospitalized patients with COVID-19: results from an observational study
Abstract A prior meta-analysis showed that antidepressant use in major depressive disorder was associated with reduced plasma levels of several pro-inflammatory mediators, which have been associated with severe COVID-19. Recent studies also suggest that several antidepressants may inhibit acid sphingomyelinase activity, which may prevent the infection of epithelial cells with SARS-CoV-2, and that the SSRI fluoxetine may exert in-vitro antiviral effects on SARS-CoV-2. We examined the potential usefulness of antidepressant use in patients hospitalized for COVID-19 in an observational multicenter retrospective cohort study conducted at AP-HP Greater Paris University hospitals. Of 7230 adults hospitalized for COVID-19, 345 patients (4.8%) received an antidepressant within 48 h of hospital admission. The primary endpoint was a composite of intubation or death. We compared this endpoint between patients who received antidepressants and those who did not in time-to-event analyses adjusted for patient characteristics, clinical and biological markers of disease severity, and other psychotropic medications. The primary analysis was a multivariable Cox model with inverse probability weighting. This analysis showed a significant association between antidepressant use and reduced risk of intubation or death (HR, 0.56; 95% CI, 0.43–0.73, p < 0.001). This association remained significant in multiple sensitivity analyses. Exploratory analyses suggest that this association was also significant for SSRI and non-SSRI antidepressants, and for fluoxetine, paroxetine, escitalopram, venlafaxine, and mirtazapine (all p < 0.05). These results suggest that antidepressant use could be associated with lower risk of death or intubation in patients hospitalized for COVID-19. Double-blind controlled randomized clinical trials of antidepressant medications for COVID-19 are needed.
Introduction Global spread of the novel coronavirus SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19), has created an unprecedented infectious disease crisis worldwide. In the current absence of a vaccine or curative treatment, the search for an effective treatment for patients with COVID-19 among all available medications is urgently needed Both COVID-19 and severe acute respiratory syndrome (SARS) are characterized by an overexuberant inflammatory response and, for COVID-19, viral load is associated with the worsening of symptoms Accumulating evidence suggests that severe COVID-19 is associated with an increased plasma level of inflammatory mediators including cytokines and chemokines such as interleukin (IL)-2, IL-6, IL-7, IL-10, tumor necrosis factor alpha (TNF-α), monocyte chemoattractant protein-1 (MCP1; also known as CCL2), macrophage inflammatory protein 1 alpha (MIP1α; also known as CCL3), C-reactive protein, ferritin, and D-dimers . A recent meta-analysis [8] of studies conducted in individuals with major depressive disorder following antidepressant treatment, mostly including selective serotonin reuptake inhibitors (SSRIs), supports that, overall, antidepressants may be associated with decreased plasma levels of 4 of 16 tested inflammatory mediators, including IL-10, TNF-α, and CCL-2, which are associated with COVID-19 severity as well as IL-6, which is highly correlated with disease mortality [. Furthermore, a recent study [10] suggests that functional inhibitors of acid sphingomyelinase activity (FIASMA), including several SSRI and non-SSRI antidepressants, may prevent the infection of epithelial cells with SARS-CoV-2 . A recent in-vitro study also supports antiviral effects of the SSRI fluoxetine on SARS-CoV-2, although this effect was not observed for other SSRIs, including paroxetine and escitalopram. Finally, a recent randomized trial suggests that fluvoxamine, a SSRI, sigma-1 receptor (S1R) agonist and FIASMA, may prevent clinical deterioration in outpatients with acute COVID-19 compared to placebo [13]. In this context, we hypothesized that antidepressants could be potentially useful in reducing the risk of intubation or death in patients with COVID-19. Short-term use of low to moderate doses of antidepressants, and particularly of SSRIs, is generally well tolerated [14], and notably in older adults [15,16,17]. To our knowledge, no clinical study has examined to date the potential usefulness of antidepressants in patients hospitalized for COVID-19. Observational studies of patients with COVID-19 taking medications for other indications can help decide which treatment should be prioritized for randomized clinical trials and minimize the risk for patients of being exposed to potentially harmful and ineffective treatments. We took advantage of the Assistance Publique-Hôpitaux de Paris (AP-HP) Health Data Warehouse, which includes data on all patients with COVID-19 who had been consecutively admitted to any of the 39 AP-HP Greater Paris University hospitals. In this report, we examined the association between antidepressant use and the risk of intubation or death among adult patients who have been admitted to these medical centers with COVID-19. If a significant protective association were found, we sought to perform exploratory analyses to examine whether this association may be specific to certain classes of antidepressants (i.e. SSRIs, serotonin–norepinephrine reuptake inhibitors (SNRIs), tricyclic, tetracyclic and α2-antagonist antidepressants) or certain individual antidepressant medications, in order to help guide future studies. Our main hypothesis was that antidepressant use would be associated with reduced risk of intubation or death in time-to-event analyses adjusting for patient characteristics, clinical and biological markers of disease severity, and other psychotropic medications.
Methods
Setting We conducted a multicenter observational retrospective study at AP-HP, which includes 39 hospitals of which 23 are acute, 20 are adult and 3 are pediatric hospitals. We included all adults aged 18 years or over who have been admitted with COVID-19 to these medical centers from the beginning of the epidemic in France, i.e. January 24th, until April 1st. COVID-19 was ascertained by a positive reverse-transcriptase–polymerase-chain-reaction (RT-PCR) test from analysis of nasopharyngeal or oropharyngeal swab specimens. This observational study using routinely collected data received approval from the Institutional Review Board of the AP-HP clinical data warehouse (decision CSE-20-20_COVID19, IRB00011591, April 8th, 2020). AP-HP clinical Data Warehouse initiative ensures patient information and informed consent regarding the different approved studies through a transparency portal in accordance with European Regulation on data protection and authorization n°1980120 from National Commission for Information Technology and Civil Liberties (CNIL). All procedures related to this work adhered to the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Data sources We used data from the AP-HP Health Data Warehouse (‘Entrepôt de Données de Santé (EDS)’). This warehouse contains all the clinical data available on all inpatient visits for COVID-19 to any of the 39 AP-HP Greater Paris University hospitals. The data obtained included patient demographic characteristics, vital signs, laboratory test and RT-PCR test results, medication administration data, medication lists during current and past hospitalizations in AP-HP hospitals, current diagnoses, discharge disposition, ventilator use data, and death certificates. Variables assessed We obtained the following data for each patient at the time of the hospitalization through electronic health records:] sex, age, hospital, obesity, self-reported current smoking status, any medical condition associated with increased risk of severe COVID-19 , any medication prescribed according to compassionate use or as part of a clinical trial [22], clinical and biological markers of disease severity at admission, any current mood or anxiety disorder, any other current psychiatric disorder, and any psychotropic medication, including any antidepressant, benzodiazepine or Z-drug, mood stabilizer (i.e. lithium or antiepileptic medications with mood stabilizing effects), and antipsychotic medication These variables are detailed in Supplementary Text 1. Antidepressant use Study baseline was defined as the date of hospital admission. Antidepressant use was defined as receiving any antidepressant within the first 48 h of hospital admission and before the end of the index hospitalization or intubation or death. We used this delay because we considered that, in a context of overwhelming of all hospital units during the COVID-19 peak incidence, patients may not have received or been prescribed the treatment the first day of their admission. Primary endpoint The primary endpoint was the time from study baseline to intubation or death. For patients who died after intubation, the timing of the primary endpoint was defined as the time of intubation. Patients without an end-point event had their data censored on May 20th, 2020. Statistical analysis We calculated frequencies and means (±standard deviations (SD)) of each baseline characteristic described above in patients receiving or not receiving antidepressants and compared them using chi-square tests or Welch’s t-tests. To examine the associations between the use of any antidepressant, each class of antidepressants, and each individual antidepressant with the composite endpoint of intubation or death, we performed Cox proportional-hazards regression models. To help account for the nonrandomized prescription of antidepressants and reduce the effects of confounding, the primary analyses used a propensity score analysis with inverse probability weighting . The individual propensities for exposures were estimated by multivariable logistic regression models that included sex, age, hospital, obesity, smoking status, any medical condition, any medication prescribed according to compassionate use or as part of a clinical trial, clinical and biological markers of severity of COVID-19, the presence of mood or anxiety or other current psychiatric disorders, and any prescribed benzodiazepine or Z-drug, mood stabilizer, and antipsychotic medication. In the inverse-probability-weighted analyses, the predicted probabilities from the propensity-score models were used to calculate the stabilized inverse-probability-weighting weights . Associations of any antidepressant, each class of antidepressants, and each individual antidepressant with the primary endpoint were then estimated using multivariable Cox regression models including the inverse-probability-weighting weights. Kaplan–Meier curves were performed using the inverse-probability-weighting weight], and their pointwise 95% confidence intervals were estimated using the nonparametric bootstrap method [. We conducted sensitivity analyses, including multivariable Cox regression models comprising as covariates the same variables as the inverse-probability-weighted analyses, and univariate Cox regression models in matched analytic samples. For these latter analyses, we decided a priori to select one control for each exposed case for exposures to any antidepressant and each class of antidepressants, and two controls for each exposed case for individual antidepressant medications, based on the same variables used for both the inverse-probability-weighted and the multivariable Cox regression analyses. Weighted Cox regression models were used when proportional hazards assumption was not met. To reduce the effects of confounding, optimal matching was used in order to obtain the smallest average absolute distance across all clinical characteristics between exposed patients and non-exposed matched controls. We also performed several additional analyses. First, to increase our confidence that the results might not be due to unmeasured confounding or indication bias, we examined whether the primary endpoint differed between patients receiving an antidepressant only in the 3 months before hospital admission (during a prior hospitalization in a AP-HP hospital) and those who received it during the visit only. Second, to examine a potential immortal bias in the exposed group, we performed additional Cox regression analyses to compare the potential effect of antidepressant use to that of an active comparator, i.e., the benzodiazepine diazepam. Third, we performed multivariable Cox regression models including interaction terms to examine whether the association between antidepressant use and the endpoint significantly differed across subgroups defined by baseline characteristics. Fourth, we examined a potential dose-effect relationship by testing the association between the daily dose received (converted into fluoxetine-equivalent dose and dichotomized at the median value) with the endpoint among patients receiving antidepressants. Fifth, we examined whether exposure to a combination of antidepressants was associated with a significantly different risk of intubation or death than exposure to only one antidepressant. Finally, we reproduced the main analyses (i) among patients with critical COVID-19 hospitalized in intensive care units (ICUs) and (ii) using death and intubation as separate endpoints. For all associations, we performed residual analyses to assess the fit of the data, check assumptions, including proportional hazards assumptions, and examined the potential influence of outliers. We followed the recommendations of The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative . Our main analysis focused on the association between antidepressant use and the primary endpoint. Statistical significance was fixed a priori at two-sided p value < 0.05. Only if a significant protective association were found, we planned to perform exploratory analyses and examine the associations between each class of antidepressants and each individual antidepressant medication with the endpoint. All analyses were conducted in R software version 2.4.3 (R Project for Statistical Computing).
Results Characteristics of the cohort Of the 9509 patients consecutively admitted to 33 participating AP-HP Greater Paris University hospitals with COVID-19, 2164 patients (22.8%) were excluded because of missing data or their young age (i.e. less than 18 years of age). In addition, 115 patients who were prescribed an antidepressant were excluded because they received it more than 48 h from hospital admission or after intubation. Of the remaining 7230 adult inpatients, 345 patients (4.8%) received an antidepressant within 48 h of hospital admission at a mean fluoxetine-equivalent dose of 21.6 mg (SD = 14.1) per day (Fig. 1). Doses of each antidepressant medication are described in Supplementary Table 1. Among patients exposed to antidepressants, 298 (86.4%) were exposed to only one antidepressant, and 47 (15.8%) were exposed to at least two antidepressants.
Credited to molecular psychiatry
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