| Literature DB >> 35677974 |
James E Siegler1, Mohamad Abdalkader2, Patrik Michel3, Thanh N Nguyen2.
Abstract
As of May 2022, there have been more than 400 million cases (including re-infections) of the systemic acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), and nearly 5 million deaths worldwide. Not only has the coronavirus disease 2019 (COVID-19) pandemic been responsible for diagnosis and treatment delays of a wide variety of conditions, and overwhelmed the allocation of healthcare resources, it has impacted the epidemiology and management of cerebrovascular disease. In this narrative review, we summarize the changing paradigms and latest data regarding the complex relationship between COVID-19 and cerebrovascular disease. Paradoxically, although SARS-CoV-2 has been associated with many thrombotic complications-including ischemic stroke-there have been global declines in ischemic stroke and other cerebrovascular diseases. These epidemiologic shifts may be attributed to patient avoidance of healthcare institutions due to fear of contracting the novel human coronavirus, and also related to declines in other transmissible infectious illnesses which may trigger ischemic stroke. Despite the association between SARS-CoV-2 and thrombotic events, there are inconsistent data regarding targeted antithrombotics to prevent venous and arterial events. In addition, we provide recommendations for the conduct of stroke research and clinical trial planning during the ongoing COVID-19 pandemic, and for future healthcare crises.Entities:
Keywords: COVID-19; Epidemiology; Intracranial hemorrhages; Outcomes research; Stroke
Year: 2022 PMID: 35677974 PMCID: PMC9194541 DOI: 10.5853/jos.2022.00843
Source DB: PubMed Journal: J Stroke ISSN: 2287-6391 Impact factor: 8.632
Utilization of the estimands framework to address intercurrent events (such as COVID-19 diagnosis in a trial patient)
| Strategy name | Approach | Limitations |
|---|---|---|
| Treatment policy strategy | The trial is largely conducted on the “intention-to-treat” principle. | The outcome must be acquired irrespective of IE (e.g., Mortality would be an acceptable outcome, given that it can be determined in patients with or without COVID-19. However, re-stenosis following angioplasty/stenting at 7 days may not be feasible in some critically ill COVID-19 patients who are too unstable to undergo repeat imaging). |
| Hypothetical strategy | Investigator imputes outcome data based on absence of IE for a given patient. | The outcome(s) may not accurately reflect a response or association with the exposure due to confounding by the IE (e.g., Intracranial hemorrhage risk can be estimated for a patient, assuming they did not develop COVID-19). |
| Composite strategy | The IE can be woven into one (or more) other outcomes into a composite endpoint (e.g., development of COVID-19 or hemorrhagic transformation following recanalization). | This approach is less effective when the composite outcome includes events which do not occur naturally, and when the IE is not anticipated to influence the outcome of interest (e.g., delayed extreme hypertension [systolic blood pressure >180 mm Hg] 90 days after stroke and/or COVID-19). |
| This is most useful when an IE can affect the outcome of interest, and a pre-specified outcome can be selected knowing that the IE can influence it (e.g., 90-Day functional dependence is influenced by COVID-19 status). | ||
| While on treatment strategy | The outcome variable should occur prior to the IE. This is advantageous when there are repeated measures over time (e.g., Serial NIHSS scores may be collected until the day the patient becomes symptomatic of COVID-19, at which point remaining events are censored). | This strategy is less effective when an IE may occur prior to the index or primary outcome event (e.g., Readmission within 30 days may be influenced by COVID-19 status). |
| Principal stratum strategy | This approach involves planned subgroup analysis of patients based on IE. This is particularly useful if the relationship between the exposure and outcome should exist within a particular population (e.g., pre-specification of a subgroup analysis based on patients who never develop COVID-19 during the study period). | Sample size estimates need to account for expected IE rate(s), which may require more funding or follow-up in clinical trials. |
COVID-19, coronavirus disease 2019; IE, intercurrent event; NIHSS, National Institutes of Health Stroke Scale.
Figure 1.Application of the estimands framework in stroke research during the coronavirus disease 2019 (COVID-19) pandemic. Image generated using biorender.com. SARS-CoV-2, systemic acute respiratory syndrome-coronavirus 2.