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Influence of COVID-19 on Long-Term Consequences of Pre-Pandemic Performed Extra and Intracranial Atherosclerotic Stenting: Tertiary Institutional Experience
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Preprints on COVID-19 and SARS-CoV-2
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06 December 2024
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06 December 2024
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Abstract
Background: Endovascular stenting for atherosclerotic stenosis in the intra- and extracranial arteries is a minimally invasive procedure, but comprehensive studies on long-term complications following COVID-19 infection are lacking. Given the potential for increased rates of stent thrombosis, stroke, myocardial infarction, and mortality among COVID-19 patients, understanding the long-term outcomes of stenting for extra- and intracranial atherosclerotic stenosis is crucial for public health. This study addresses the dearth of extensive research on the long-term adverse outcomes associated with endovascular stenting procedures in patients who have experienced atherosclerotic stenosis in intracranial and extracranial arteries following COVID-19 infection. Methods: This retrospective study analyzed data from a tertiary hospital database, focusing on individuals who underwent extracranial or intracranial atherosclerotic stenting procedures at the Central Clinical Hospital JSC, Department of Neurosurgery, between 2016 and 2017, before the COVID-19 pandemic. The primary outcome measures to be evaluated include the incidence of stent thrombosis, ischemic stroke, myocardial infarction, and all-cause mortality. Results: The study followed 93 patients via telephone survey, but 12 did not respond, leaving 81 participants. Of these, 32 reported a prior COVID-19 infection confirmed by PCR testing, forming the COVID-19 group. The remaining 49 without confirmed COVID-19 infection comprised the control group. The 81 participants included 32 in the COVID-19 group and 49 in the control group, with no statistically significant differences in sex or age between the two cohorts. The binary logistic regression analysis revealed that the number of cigarettes smoked per day was a statistically significant predictor of myocardial infarction. This risk factor accounted for 23.6% of the observed myocardial infarctions, demonstrating a direct relationship between the number of cigarettes smoked and the probability of experiencing a myocardial infarction. Conclusion: The study found no significant differences in mortality, stroke, and heart attack rates between the COVID-19 and control groups. However, high blood pressure, heavy smoking, and high stress were linked to worse long-term outcomes.
Keywords:
Subject: Medicine and Pharmacology - Medicine and Pharmacology
1. Introduction
Utilizing newer stent technologies and improved antiplatelet regimens, stent thrombosis rates have typically ranged from 1 to 4% in recent years [1,2]. However, reports have indicated a significant surge in-stent thrombosis incidence, ranging from 8.1% to 21%, during the COVID-19 pandemic [3]. Multiple studies suggest an elevated propensity for both arterial and venous thrombosis in COVID-19 patients, which may contribute to an increased risk of cerebrovascular events, acute myocardial infarction, and elevated mortality rates [4,5]. This study aims to address the lack of comprehensive research on the long-term complications of endovascular stenting in patients with atherosclerotic stenosis in both intracranial and extracranial arteries following COVID-19 infection. Given the potential surge in rates of stent thrombosis, stroke, myocardial infarction, and mortality among COVID-19 patients, understanding the long-term outcomes of stenting for extra- and intracranial atherosclerotic stenosis is of critical importance for public health. Accordingly, this study evaluates the combined impact of COVID-19 and other risk factors on the long-term consequences in patients who underwent stenting in both extracranial and intracranial arteries.
2. Materials and Methods
2.1. Study Design and Patient Population
This study will retrospectively analyze data from a tertiary hospital database. The patient population will comprise individuals who underwent extracranial or intracranial atherosclerotic stenting at the Central Clinical Hospital JSC, Department of Neurosurgery, between 2016 and 2017, prior to the COVID-19 pandemic. The primary outcome measures to be evaluated are the incidence of stent thrombosis, ischemic stroke, myocardial infarction, and all-cause mortality.
Patients will be stratified into two groups based on COVID-19 infection status during the follow-up period.
2.2. Survey Questionnaire
All participants or their representatives provided voluntary informed consent and were sent the questionnaire "Assessment of the Risk of Complications Following Cerebrovascular Atherosclerotic Stenting" (copyright certificate No. 30993, issued on 09.12.2022). The questionnaire was used to collect data on: 1) treatment outcomes, including stroke, myocardial infarction, and mortality, 2) the number of months post-procedure that the outcome occurred, and 3) risk factors such as lifestyle, nutrition, medication adherence, and management of concurrent conditions. The questionnaire was presented in the Kazakh and Russian languages and consisted of 33 questions.
This study was conducted in compliance with the ethical principles outlined in the Declaration of Helsinki and received approval from the local bioethics committee of the Kazakhstan School of Public Health, a medical university in Kazakhstan.
2.3. Statistical Analysis
To assess the normality of the distribution of the measured variables, the Shapiro-Wilk test was employed. For the analysis of non-parametric quantitative data, the Mann-Whitney U-test was utilized, while parametric data was analyzed using Student's t-test. Fisher's exact test was applied to examine nominal data. Pearson's chi-square test was leveraged to evaluate the strength of the associations, as per the Chaddock scale. Furthermore, the effect size was quantified using Cramer's V metric.
Binary logistic regression modeling was utilized to evaluate the impact of various factors on the likelihood of developing complications. The coefficient of determination was calculated using the Nagelkerke method. Additionally, sensitivity and specificity were ascertained through the formulas: Se=TP/ 100%; and Sp=TN/ 100%, as well as by constructing an ROC curve.
Statistical significance was set at a p-value of less than 0.05. All analyses were conducted using the SPSS statistical software, version 26.
2.4. Predictive Model
A predictive model was developed using binary logistic regression to estimate the probability of mortality, stroke, and myocardial infarction based on various risk factors. The model incorporated factors such as the severity and treatment setting of COVID-19 infection, location of atherosclerotic plaques, smoking status, body mass index, changes in body weight, sex, age, stress levels, sleep duration, physical activity patterns, adherence to medication regimens, and the type of stent used during the surgical procedure.
The relationship was described by the following equation:
The P stands for the percent probability of developing a complication post-procedure.
The equation for mortality risk was as follows:
The stands for the systolic blood pressure (mm Hg), the stands for the stress level (assessed on a 5-point scale), and the stands for the stent used during surgery (1=Biotronic, 2=Orsiro, 3=Promus PREMIER, 4=XIENCEXpedition, 5=CristalloIdeal, 6=CarotidWall stent, 7=Casper, 8=Resolute Integrity, 9=Terumo Ultimaster, 10=Protege).
The equation for stroke risk was as follows:
The stands for the maximum increase in systolic blood pressure (mm Hg), and the stands for the number of cigarettes per day.
The equation for myocardial infarction risk was as follows:
The stands for the number of cigarettes per day.
The values of the determination coefficient were determined using the Nagelkerke R2 method
3. Results
This The study followed a total of 93 patients via telephone survey, however, 12 patients did not respond, resulting in a final sample size of 81 participants. Of these, 32 patients reported a prior COVID-19 infection confirmed by PCR testing, comprising the COVID-19 group. The remaining 49 patients without confirmed COVID-19 infection formed the control group.
3.1. Patient Characteristics
The study population comprised 81 participants, with 32 individuals in the COVID-19 group and 49 in the control group. The two cohorts did not exhibit statistically significant differences in terms of sex or age as seen in Table 1.
In the COVID-19 group, the severity of illness varied, with 9 patients experiencing mild, 16 moderate, and 7 severe COVID-19 cases. Regarding the treatment setting, 16 patients were managed at home, 4 received day patient care, and 12 required full hospitalization as seen in Table 2.
The most common endovascular stent used in the study participants was the Protégé stent. Medication adherence, including antiplatelet therapy, was assessed in both the COVID-19 and control groups. All patients were required to take antiplatelet agents for 6 months following their endovascular procedure. In the COVID-19 group, 10 patients fully adhered to the antiplatelet regimen, 13 adhered intermittently or in cycling patterns, and 9 did not take the medication as prescribed. Similarly, in the control group, 21 patients adhered to the antiplatelet therapy, 15 adhered partially or cyclically, and 13 did not take the medication. The differences in medication adherence between the two groups were not statistically significant as seen in Table 3.
3.2. Long-Term Outcomes
The surveys were conducted at an average of 3 months/years after the initial procedure for the COVID-19 group and 3 months/years for the control group.
Mortality rates were 21.9% in the COVID-19 group and 34.7% in the control group, a difference that was not statistically significant. The causes of mortality in the COVID-19 group included stroke, COVID-19, other causes, and unknown causes. Similarly, in the control group, the causes of mortality were stroke, myocardial infarction, other causes, and unknown causes. These differences in mortality causes between the two groups were not statistically significant as seen in Table 4.
In the COVID-19 group, the myocardial infarction rate was 3.1%, while in the control group it was 4.1%. Similarly, the stroke rate was 56.4% in the COVID-19 group and 44.9% in the control group. However, these differences were not found to be statistically significant. The data showed that patients who had COVID-19 infection had 1.4 times higher odds of developing a stroke compared to the control group, while the odds ratios for mortality and myocardial infarction were both 0.5. However, these differences were not found to be statistically significant as seen in Table 4.
3.3. Predictors of Outcomes
The binary logistic regression analyses revealed that overall, maximum systolic blood pressure, stress levels, and the type of stent used were statistically significant predictors of mortality. Collectively, these factors accounted for 41.2% of the observed mortality. Specifically, higher maximum systolic blood pressure and greater stress levels demonstrated a significant positive association with the likelihood of death, whereas the type of stent utilized exhibited an inverse relationship with the probability of a lethal outcome as seen in Table 5.
The binary logistic regression analysis revealed statistically significant associations between stroke and elevated maximum systolic blood pressure as well as the number of cigarettes smoked per day. These two risk factors collectively accounted for 53.4% of the observed strokes. Specifically, higher maximum systolic blood pressure demonstrated a significant positive relationship with the likelihood of experiencing a stroke as seen in Table 6.
The binary logistic regression analysis revealed that the number of cigarettes smoked per day was a statistically significant predictor of myocardial infarction. This risk factor accounted for 23.6% of the observed myocardial infarctions, with a direct relationship between the number of cigarettes smoked and the probability of experiencing a myocardial infarction as seen in Table 7.
4. Discussion
This study examines the impact of the COVID-19 pandemic on the long-term outcomes of patients who underwent endovascular stenting procedures prior to the pandemic. It is one of the first investigations of this nature conducted in Kazakhstan, exploring the association between COVID-19 infection, various risk factors, and the development of long-term complications following neuroendovascular interventions.
During the COVID-19 pandemic, primary stroke centers and healthcare facilities witnessed a significant decline in the number of stroke-related hospitalizations. This reduction was associated with a global decrease in various medical interventions, such as intravenous thrombolysis treatments and endovascular procedures. These procedures, including cerebral angiograms, carotid artery stent placements for both symptomatic and asymptomatic stenoses, as well as intracranial angioplasty and/or stent placements for stenosis, experienced notable decreases of 55.4% and 45%, respectively [6,7].
Despite the lack of confirmed COVID-19 infection, patients undergoing endovascular procedures during the pandemic experienced serious complications. For instance, the VERN and COVER international multicenter observational study conducted during the COVID-19 pandemic revealed a significant increase in mortality rates across all types of endovascular interventions, even though most participants did not exhibit SARS-CoV-2 infection [8]. Before the pandemic, the reported in-hospital mortality rate following carotid stenting was 1%, while during the pandemic, the in-hospital mortality rate in the COVER study was 10.7%. Additionally, some researchers have identified an elevated susceptibility to both arterial and venous thrombosis, as well as a higher risk of thrombotic microangiopathy involving multiple organs, in COVID-19 patients, including an increased likelihood of stent thrombosis [6,7]. These factors synergistically contributed to a disproportionately high intraluminal thrombus burden relative to mild underlying atherosclerotic plaque [9,10]. As a result, the authors recommended considering the possibility of deferring endovascular procedures [8].
The analysis of our results revealed that despite patients undergoing endovascular stenting before the pandemic, the long-term complications did not show statistically significant differences between the COVID-19 and control groups. While the rates of mortality, stroke, and myocardial infarction were similar across the two groups, we identified the impact of other risk factors. Specifically, we found that elevated blood pressure in the long term was significantly correlated with an increased probability of death and stroke. Furthermore, the number of cigarettes smoked per day exhibited a significant association with the likelihood of myocardial infarction, and higher stress levels demonstrated a significant relationship with the probability of mortality.
The complications observed during COVID-19 infection can be attributed to a cascade of pathological processes, including systemic inflammation throughout the body, impaired blood clotting, and local inflammation of the blood vessel lining. To mitigate the complications associated with systemic inflammation and coagulation disorders, some researchers have advocated for the surgical removal of atherosclerotic plaques in extracranial atherosclerotic lesions [11]. Nevertheless, the impact of COVID-19 on intracranial artery stenting continues to be an unexamined area of research.
Conversely, some researchers advocate for a "Carotid Artery Stenting first" approach during the COVID-19 pandemic, arguing that it is a safe and justified strategy. This perspective suggests that prioritizing CAS as the initial treatment may help mitigate the burden on healthcare facilities and ensure the timely and sufficient provision of care to patients, particularly when healthcare resources are constrained [12]. Existing research suggests that prioritizing carotid artery stenting as the initial treatment approach may be a safe and justified strategy, even during the COVID-19 pandemic. This perspective contends that a CAS-first approach for managing symptomatic carotid artery stenosis can remain a safe and effective intervention, particularly for patients concurrently affected by COVID-19 infection [13].
Unfortunately, the existing literature lacks comprehensive, rigorous data examining the long-term outcomes and associated risk factors following stenting procedures for both intra- and extracranial arteries and how these factors may impact subsequent prognoses. This significant knowledge gap has been recognized by numerous researchers during the COVID-19 pandemic era. Factors such as resource limitations, service closures to curb virus transmission, and guidance to postpone surgeries until more urgent clinical presentations have likely hindered surgeons' ability to optimize patient care before interventions.
The study authors acknowledge several limitations, including a small sample size, limited post-procedure follow-up, and a lack of autopsy data on stent thrombosis for fatal cases. Furthermore, the number of patients tested for COVID-19 was unclear due to low clinical suspicion. Additionally, the retrospective design of the study inherently restricts the ability to establish causal relationships. Moreover, the single-institution nature of the study limits the external validity and generalizability of the findings to broader populations or different clinical settings.
5. Conclusions
The analysis revealed that the rates of mortality, stroke, and myocardial infarction did not differ significantly between the COVID-19 group and the control group. However, elevated blood pressure, increased cigarette consumption, and higher stress levels were identified as significant predictors of long-term adverse outcomes. To better comprehend the impact of COVID-19 on extra- and intracranial atherosclerotic stenting, more rigorous and prospective data are required.
Supplementary Materials
The following supporting information can be downloaded at the website of this paper posted on Preprints.org.
Author Contributions
Conceptualization, M.S. and M.B.; methodology, M.B.; software, M.A.; validation, M.L., G.T. and B.T.; formal analysis, M.A.; investigation, S.M.; resources, M.B.; data curation, M.S.; writing—original draft preparation, M.S.; writing—review and editing, M.A.; visualization, G.T.; supervision, M.B.; project administration, M.L.; funding acquisition, B.T. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of NAME OF INSTITUTE (protocol code XXX and date of approval).” for studies involving humans. OR “The animal study protocol was approved by the Ethics Committee of Kazakhstan School of Public Health OF INSTITUTE (protocol code 286 on dec13 2022.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
We encourage all authors of articles published in MDPI journals to share their research data. In this section, please provide details regarding where data supporting reported results can be found, including links to publicly archived datasets analyzed or generated during the study. Where no new data were created, or where data is unavailable due to privacy or ethical restrictions, a statement is still required. Suggested Data Availability Statements are available in section “MDPI Research Data Policies” at https://www.mdpi.com/ethics.
Acknowledgments
Nill.
Conflicts of Interest
The authors declare no conflicts of interest.
Appendix A
Questionnaire used.
References
- Wang, T.; Luo, J.; Wang, X.; Yang, K.; Jadhav, V.; Gao, P.; Ma, Y.; Zhao, N.; Jiao, L. Endovascular therapy versus medical treatment for symptomatic intracranial artery stenosis. Cochrane Database Syst. Rev. 2020, 2020. [Google Scholar] [CrossRef]
- Iakovou, I.; Schmidt, T.; Bonizzoni, E.; Ge, L.; Sangiorgi, G.M.; Stankovic, G.; Airoldi, F.; Chieffo, A.; Montorfano, M.; Carlino, M.; et al. Incidence, Predictors, and Outcome of Thrombosis After Successful Implantation of Drug-Eluting Stents. JAMA 2005, 293, 2126–2130. [Google Scholar] [CrossRef]
- Kuchulakanti, P.K.; Chu, W.W.; Torguson, R.; Ohlmann, P.; Rha, S.-W.; Clavijo, L.C.; Kim, S.-W.; Bui, A.; Gevorkian, N.; Xue, Z.; et al. Correlates and Long-Term Outcomes of Angiographically Proven Stent Thrombosis With Sirolimus- and Paclitaxel-Eluting Stents. Circulation 2006, 113, 1108–1113. [Google Scholar] [CrossRef]
- Katsanos, A.H.; Palaiodimou, L.; Zand, R.; Yaghi, S.; Kamel, H.; Navi, B.B.; Turc, G.; Romoli, M.; Sharma, V.K.; Mavridis, D.; et al. The Impact of SARS-CoV-2 on Stroke Epidemiology and Care: A Meta-Analysis. Ann. Neurol. 2020, 89, 380–388. [Google Scholar] [CrossRef] [PubMed]
- Cornelissen, A.; Kutyna, M.; Cheng, Q.; Sato, Y.; Kawakami, R.; Sakamoto, A.; Kawai, K.; Mori, M.; Fernandez, R.; Guo, L.; et al. Effects of Simulated COVID-19 Cytokine Storm on Stent Thrombogenicity. Cardiovasc. Revascularization Med. 2021, 35, 129–138. [Google Scholar] [CrossRef] [PubMed]
- Qureshi, A.I.; Agunbiade, S.; Huang, W.; Akhtar, I.N.; Abraham, M.G.; Akhtar, N.; Al-Mufti, F.; Aytac, E.; Balgetir, F.; Grigoryan, M.; et al. Changes in Neuroendovascular Procedural Volume During the COVID-19 Pandemic: An International Multicenter Study. J. Neuroimaging 2020, 31, 171–179. [Google Scholar] [CrossRef] [PubMed]
- Nogueira, R.G.; Qureshi, M.M.; Abdalkader, M.; Martins, S.O.; Yamagami, H.; Qiu, Z.; Mansour, O.Y.; Sathya, A.; Czlonkowska, A.; Tsivgoulis, G.; et al. Global Impact of COVID-19 on Stroke Care and IV Thrombolysis. Neurology 2021, 96, e2824–e2838. [Google Scholar] [CrossRef] [PubMed]
- Benson, R.A.B.; Nandhra, S.M. Outcomes of Vascular and Endovascular Interventions Performed During the Coronavirus Disease 2019 (COVID-19) Pandemic. Ann. Surg. 2020, 273, 630–635. [Google Scholar] [CrossRef]
- Connors, J.M.; Levy, J.H. Thromboinflammation and the hypercoagulability of COVID-19. J. Thromb. Haemost. 2022, 18, 1559–1561. [Google Scholar] [CrossRef] [PubMed]
- Jackson, S.P.; Darbousset, R.; Schoenwaelder, S.M. Thromboinflammation: challenges of therapeutically targeting coagulation and other host defense mechanisms. Blood 2019, 133, 906–918. [Google Scholar] [CrossRef] [PubMed]
- Buja, L.M.; Wolf, D.A.; Zhao, B.; Akkanti, B.; McDonald, M.; Lelenwa, L.; Reilly, N.; Ottaviani, G.; Elghetany, M.T.; Trujillo, D.O.; et al. The emerging spectrum of cardiopulmonary pathology of the coronavirus disease 2019 (COVID-19): Report of 3 autopsies from Houston, Texas, and review of autopsy findings from other United States cities. Cardiovasc. Pathol. 2020, 48, 107233–107233. [Google Scholar] [CrossRef] [PubMed]
- Varga, Z.; Flammer, A.J.; Steiger, P.; Haberecker, M.; Andermatt, R.; Zinkernagel, A.S.; Mehra, M.R.; Schuepbach, R.A.; Ruschitzka, F.; Moch, H. Endothelial cell infection and endotheliitis in COVID-19. Lancet 2020, 395, 1417–1418. [Google Scholar] [CrossRef]
- Esenwa, C.; Cheng, N.; Lipsitz, E.; Hsu, K.; Zampolin, R.; Gersten, A.; Antoniello, D.; Soetanto, A.; Kirchoff, K.; Liberman, A.; et al. COVID-19-Associated Carotid Atherothrombosis and Stroke. Am. J. Neuroradiol. 2020, 41, 1993–1995. [Google Scholar] [CrossRef]
Table 1.
Patient characteristics.
| COVID-19 | Control | p-value | Effect size | |
|---|---|---|---|---|
| Sex | ||||
| Male | 81.3% (26/32) | 65.3% (32/49) | 0.095 | 0.173 (0.138) |
| Female | 18.8% (6/32) | 34.7% (17/49) | ||
| Age | 65.3±7.1 | 66.6±6.9 | 0.947 |
Data are % (n/N) or Mean±SD. SD: standard deviation.
Table 2.
Characteristics of COVID-19.
| COVID-19 Characteristic | % (n/N) |
| Severity of COVID-19 | |
| Mild | 28.1% (9/32) |
| Average | 50.0% (16/32) |
| Severe | 21.9% (7/32) |
| Location of treatment | |
| At home | 50.0% (16/32) |
| Day patient facility | 12.5% (4/32) |
| Hospital | 37.5% (12/32) |
Table 3.
Medications and adherence to prescribed dosage.
| Medication Type | Adherence | COVID-19 | Control | p-value | Effect size |
|---|---|---|---|---|---|
| Anti-hypertension | Yes | 50.0% (16/32) | 63.3% (31/49) | 0.421 | 0.183 (0.421) |
| Only when hypertension was elevated | 28.1% (9/32) | 12.2% (6/49) | |||
| Irregular usage | 9.4% (3/32) | 8.2% (4/49) | |||
| No | 12.5% (4/32) | 16.3% (8/49) | |||
| Lipid-lowering | Yes | 31.3% (10/32) | 42.9% (21/49) | 0.699 | 0.092 (0.699) |
| Sometimes or in dosing cycles | 40.6% (13/32) | 30.6% (15/49) | |||
| No | 28.1% (9/32) | 26.5% (13/49) | |||
| Antiplatelet | Yes | 31.3% (10/32) | 42.9% (21/49) | 0.699 | 0.092 (0.699) |
| Sometimes or in dosing cycles | 40.6% (13/32) | 30.6% (15/32) | |||
| No | 28.1% (9/32) | 26.5% (13/49) | |||
| Mandatory course of antiplatelet agents after surgery | Yes | 15.6% (5/32) | 24.5% (12/49) | 0.299 | 0.294 (0.299) |
| Stopped after 1 month | 12.5% (4/32) | 20.4% (10/49) | |||
| Stopped after 3 months | 28.1% (9/32) | 12.2% (6/49) | |||
| Stopped after 6 months | 37.6% (12/32) | 24.5% (12/49) | |||
| Stopped after 12 months | 0% (0/32) | 8.2% (4/49) | |||
| No | 6.2% (2/32) | 6.1% (3/49) | |||
| Unknown | 0% (0/32) | 4.1% (2/49) | |||
| Blood sugar lowering | Yes | 31.3% (10/32) | 38.8% (19/49) | 0.399 | 0.092 (0.399) |
| No | 68.6% (22/32) | 61.2% (30/49) |
Data are % (n/N).
Table 4.
Long-term outcomes.
| Outcome | COVID-19 | Control | OR (95% CI) | p-value | Effect size |
|---|---|---|---|---|---|
| Mortality | 21.9% (7/32) | 34.7% (17/49) | 0.5 (0.212, 1.551) |
0.271 | 0.114 (90.271) |
| Before the pandemic | 0% (0/7) | 29.4% (5/17) | |||
| Missed | 0 | 3 | |||
| Causes of mortality | 0 | 0.651 | 0.329 (0.651) | ||
| Stroke | 14.3% (1/7) | 17.6% (3/17) | |||
| Myocardial infarction | 0% (0/7) | 11.8% (2/17) | |||
| COVID-19 | 57.1% (4/7) | 0% (0/17) | |||
| Other | 14.3% (1/7) | 52.9% (9/17) | |||
| Unknown | 14.3% (1/7) | 17.6% (3/17) | |||
| Myocardial infarction | 3.1% (1/32) | 4.1% (2/49) | 0.5 (0.053, 5.366) |
0.588 | 0.092 (0.588) |
| Before the pandemic | 0% (0/1) | 0% (0/2) | |||
| Missed | 100% (1/1) | 50.0% (1/2) | |||
| Stroke | 56.3% (18/32) | 44.9% (22/49) | 1.4 (0.550, 3.251) |
0.521 | 0.070 (0.531) |
| Before the pandemic | |||||
| Missed | 0 | 4.5% (1/22) |
CI: confidence interval; OR: odds ratio.
Table 5.
Predictors of mortality.
| Risk factor | Unadjusted OR (95% CI) | p-value | Adjusted OR (95% CI) |
p-value |
|---|---|---|---|---|
| Мах systolic blood pressure | 1.005 (0.992 -1.018) | 0.466 | 1.042 (1.000, 1.085) | 0.049* |
| Stress | 1.586 (1.069-2.354) | 0.022* | 3.612 (1.192, 10.943) | 0.023* |
| Stent | 0.942 (0.775 -1.145) | 0.548 | 0.660 (0.404, 1.088) | 0.098 |
| Sensitivity | 0 | |||
| Specificity | 100% | |||
| Total percentage | 74.3% | |||
| Nagelkerke R2 | 0.412 | |||
| p-value | 0.021* | |||
CI: confidence interval, OR: odds ratio. *p<0.05.
Table 6.
Predictors of stroke.
| Risk factor | Unadjusted OR (95% CI) | p-value | Adjusted OR (95% CI) |
p-value |
|---|---|---|---|---|
| Мах systolic blood pressure | 1.015 (1.001, 1.028) | 0.035* | 1.046 (1.007, 1.086) | 0.019* |
| Number of cigarettes per day | 1.025 (0.976, 1.077) | 0.320 | 1.077 (0.966, 1.2) | 0.182 |
| Sensitivity | 0 | |||
| Specificity | 100% | |||
| Total percentage | 53.8% | |||
| Nagelkerke R2 | 0.534 | |||
| p-value | 0.017* | |||
CI: confidence interval, OR: odds ratio. *p<0.05.
Table 7.
Predictors of myocardial infarction.
| Risk factor | Unadjusted OR (95% CI) | p-value | Adjusted OR (95% CI) |
p-value |
|---|---|---|---|---|
| Number of cigarettes per day | 1.035 (0.993, 1.080) | 0.107 | 1.037 (0.993, 1.083) | 0.1 |
| Sensitivity | 0 | |||
| Specificity | 100% | |||
| Total percentage | 74.3% | |||
| R-Nigel Kirk square | 0.236 | |||
| p-value | 0.03* | |||
CI: confidence interval, OR: odds ratio. *p<0.05.
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