ABSTRACT
Background Few studies have used real-world data to evaluate the impact of antidepressant use on the risk of developing severe outcomes after SARS-CoV-2 Omicron infection. Methods This is a retrospective cohort study using propensity-score matching to examine the relationship between antidepressant use and COVID-19 severity. Inpatient and medication records of all adult COVID-19 patients in Hong Kong during the Omicron-predominated period were obtained. Severe clinical outcomes including intensive care unit admission and inpatient death after the first positive results of reverse transcription polymerase chain reaction as well as a composite outcome of both were studied. Cox proportional hazard models were applied to estimate the crude and adjusted hazard ratios (HR). Findings Of 60,903 hospitalised COVID-19 patients admitted, 40,459 were included for matching, among which 3821 (9.4%) were prescribed antidepressants. The rates of intensive care unit admission, inpatient death, and the composite event were 3.9%, 25.5%, and 28.3% respectively in the unexposed group, 1.3%, 20.0%, and 21.1% respectively in the exposed group, with adjusted HR equal to 0.332 (95% CI, 0.245–0.449), 0.868 (95% CI, 0.800–0.942), and 0.786 (95% CI, 0.727–0.850) respectively. The result was generally consistent when stratified by selective serotonin reuptake inhibitors (SSRIs) and non-SSRIs. Antidepressants with functional inhibition of acid sphingomyelinase activity, specifically fluoxetine, were also negatively associated with the outcomes. The effect of antidepressants was more apparent in female and fully vaccinated COVID-19 patients. Interpretation Antidepressant use was associated with a lower risk of severe COVID-19. The findings support the continuation of antidepressants in patients with COVID-19, and provide evidence for the treatment potential of antidepressants for severe COVID-19. Funding This research was supported by Health and Medical Research Fund [grant numbers COVID190105, COVID19F03, INF-CUHK-1], Collaborative Research Fund of University Grants Committee [grant numbers C4139-20G], 10.13039/501100001809National Natural Science Foundation of China (NSFC) [71974165], and Group Research Scheme from The 10.13039/501100004853Chinese University of Hong Kong.
ABSTRACT
Background: Few studies have used real-world data to evaluate the impact of antidepressant use on the risk of developing severe outcomes after SARS-CoV-2 Omicron infection. Methods: This is a retrospective cohort study using propensity-score matching to examine the relationship between antidepressant use and COVID-19 severity. Inpatient and medication records of all adult COVID-19 patients in Hong Kong during the Omicron-predominated period were obtained. Severe clinical outcomes including intensive care unit admission and inpatient death after the first positive results of reverse transcription polymerase chain reaction as well as a composite outcome of both were studied. Cox proportional hazard models were applied to estimate the crude and adjusted hazard ratios (HR). Findings: Of 60,903 hospitalised COVID-19 patients admitted, 40,459 were included for matching, among which 3821 (9.4%) were prescribed antidepressants. The rates of intensive care unit admission, inpatient death, and the composite event were 3.9%, 25.5%, and 28.3% respectively in the unexposed group, 1.3%, 20.0%, and 21.1% respectively in the exposed group, with adjusted HR equal to 0.332 (95% CI, 0.245-0.449), 0.868 (95% CI, 0.800-0.942), and 0.786 (95% CI, 0.727-0.850) respectively. The result was generally consistent when stratified by selective serotonin reuptake inhibitors (SSRIs) and non-SSRIs. Antidepressants with functional inhibition of acid sphingomyelinase activity, specifically fluoxetine, were also negatively associated with the outcomes. The effect of antidepressants was more apparent in female and fully vaccinated COVID-19 patients. Interpretation: Antidepressant use was associated with a lower risk of severe COVID-19. The findings support the continuation of antidepressants in patients with COVID-19, and provide evidence for the treatment potential of antidepressants for severe COVID-19. Funding: This research was supported by Health and Medical Research Fund [grant numbers COVID190105, COVID19F03, INF-CUHK-1], Collaborative Research Fund of University Grants Committee [grant numbers C4139-20G], National Natural Science Foundation of China (NSFC) [71974165], and Group Research Scheme from The Chinese University of Hong Kong.
ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic has posed a severe threat to public health and economic activity. Governments all around the world have taken positive measures to, on the one hand, contain the epidemic spread and, on the other hand, stimulate the economy. Without question, tightened anti-epidemic policy measures restrain people's mobility and deteriorate the levels of social and economic activity. Meanwhile, loose policy measures bring little harm to the economy temporarily but could accelerate the transmission of the virus and ultimately wreck social and economic development. Therefore, these two kinds of governmental decision-making behaviors usually conflict with each other. With the purpose of realizing optimal socio-economic benefit over the full duration of the epidemic and to provide a helpful suggestion for the government, a trade-off is explored in this paper between the prevention and control of the epidemic, and economic stimulus. First, the susceptible-infectious-recovered (SIR) model is introduced to simulate the epidemic dynamics. Second, a state equation is constructed to describe the system state variable-the level of socio-economic activity dominated by two control variables. Specifically, these two variables are the strengths of the measures taken for pandemic prevention and control, and economic stimulus. Then, the objective function used to maximize the total socio-economic benefit over the epidemic's duration is defined, and an optimal control problem is developed. The statistical data of the COVID-19 epidemic in Wuhan are used to validate the SIR model, and a COVID-19 epidemic scenario is used to evaluate the proposed method. The solution is discussed in both static and dynamic strategies, according to the knowledge of the epidemic's duration. In the static strategy, two scenarios with different strengths (in terms of anti-epidemic and economic stimulus measures) are analyzed and compared. In the dynamic strategy, two global optimization algorithms, including the dynamic programming (DP) and Pontryagin's minimum principle (PMP), respectively, are used to acquire the solutions. Moreover, a sensitivity analysis of model parameters is conducted. The results demonstrate that the static strategy, which is independent of the epidemic's duration and can be easily solved, is capable of finding the optimal strengths of both policy measures. Meanwhile, the dynamic strategy, which generates global optimal trajectories of the control variables, can provide the path that leads to attaining the optimal total socio-economic benefit. The results reveal that the optimal total socio-economic benefit of the dynamic strategy is slightly higher than that of the static strategy.
Subject(s)
COVID-19 , Pandemics , Humans , Pandemics/prevention & control , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2 , Public Health , GovernmentABSTRACT
BACKGROUND: Previous studies demonstrate a reduced risk of thrombosis and mortality with anticoagulant treatment in patients with COVID-19 than in those without anticoagulation treatment. However, an open question regarding the efficacy and safety of therapeutic anticoagulation (T-AC) versus a lower dose, prophylaxis anticoagulation (P-AC) in COVID-19 patients is still controversial. METHODS: We systematically reviewed currently available randomized clinical trials (RCTs) and observational studies (OBs) from January 8, 2019, to January 8, 2022, and compared prophylactic and therapeutic anticoagulant treatment in COVID-19 patients. The primary outcomes were risk of mortality, major bleeding, and the secondary outcomes included venous and arterial thromboembolism. Subgroup analysis was also performed between critically ill and non-critically ill patients with COVID-19 and between patients with higher and lower levels of D-dimer. Sensitivity analysis was performed to decrease the bias and the impact of population heterogeneity. RESULTS: We identified 11 RCTs and 17 OBs fulfilling our inclusion criteria. In the RCTs analyses, there was no statistically significant difference in the relative risk of mortality between COVID-19 patients with T-AC treatment and those treated with P-AC (RR 0.95, 95% CI, 0.78-1.15, P = 0.60). Similar results were also found in the OBs analyses (RR 1.21, 95% CI, 0.98-1.49, P = 0.08). The pooling meta-analysis using a random-effects model combined with effect sizes showed that in the RCTs and OBs analyses, patients with COVID-19 who received T-AC treatment had a significantly higher relative risk of the major bleeding event than those with P-AC treatment in COVID-19 patients (RCTs: RR 1.76, 95% CI, 1.19-2.62, P = 0.005; OBs: RR 2.39, 95% CI, 1.56-3.68, P < 0.0001). Compared with P-AC treatment in COVID-19 patients, patients with T-AC treatment significantly reduced the incidence of venous thromboembolism (RR 0.51, 95% CI, 0.39-0.67, P<0.00001), but it is not associated with arterial thrombosis events (RR 0.97, 95% CI, 0.66-1.42, P = 0.87). The subgroup analysis of OBs shows that the mortality risk significantly reduces in critically ill COVID-19 patients treated with T-AC compared with those with P-AC treatment (RR 0.58, 95% CI, 0.39-0.86, P = 0.007), while the mortality risk significantly increases in non-critically ill COVID-19 patients treated with T-AC (RR 1.56, 95% CI, 1.34-1.80, P < 0.00001). In addition, T-AC treatment does not reduce the risk of mortality in COVID-19 patients with high d-dimer levels in RCTs. Finally, the overall sensitivity analysis after excluding two RCTs studies remains consistent with the previous results. CONCLUSIONS: In our integrated analysis of included RCTs and OBs, there is no significant difference between the mortality of T-AC and P-AC treatment in unselected patients with COVID-19. T-AC treatment in COVID-19 patients significantly reduced the incidence of venous thromboembolism but showed a higher risk of bleeding than those with P-AC treatment. In addition, P-AC treatment was superior to T-AC treatment in non-critically ill COVID-19 patients, the evidence supporting the necessity for T-AC treatment in critically ill COVID-19 patients came only from OBs. TRIAL REGISTRATION: Protocol registration: The protocol was registered at PROSPERO (CRD42021293294).