Abstract:Objectives
To analyze the epidemiological characteristics of COVID-19 related deaths in Wuhan, China and comprehend the changing trends of this epidemic along with analyzing the prevention and control measures in Wuhan.
Methods
Through the China’s Infectious Disease Information System, we collected information about COVID-19 associated deaths from December 15, 2019 to February 24, 2020 in Wuhan. We analyzed the patient’s demographic characteristics… Show more
“… 6 Furthermore, severe complications of COVID-19, including cerebral ischemia, have been established to be higher in males with cardiovascular risk factors than in females. 26 …”
Carotid free-floating thrombus is an uncommon entity that usually presents with neurologic symptoms. Crescendo transient ischemic attack is an accepted indication for urgent carotid endarterectomy. COVID-19 is associated with severe thromboembolic complications. We report the case of a 61-year-old man who developed, 2 weeks after the diagnosis of COVID-19, crescendo transient ischemic attack, complicating a large intraluminal floating thrombus within the right common carotid artery. A carotid thromboendarterectomy under local anesthesia, with patch closure was immediately performed without complications. We conducted a literature review to identify cases of common carotid artery thrombus related to COVID-19. Carotid free-floating thrombus in the common carotid artery is exceptional. However, since the beginning of the COVID-19 pandemic, 15 cases have been published.
“… 6 Furthermore, severe complications of COVID-19, including cerebral ischemia, have been established to be higher in males with cardiovascular risk factors than in females. 26 …”
Carotid free-floating thrombus is an uncommon entity that usually presents with neurologic symptoms. Crescendo transient ischemic attack is an accepted indication for urgent carotid endarterectomy. COVID-19 is associated with severe thromboembolic complications. We report the case of a 61-year-old man who developed, 2 weeks after the diagnosis of COVID-19, crescendo transient ischemic attack, complicating a large intraluminal floating thrombus within the right common carotid artery. A carotid thromboendarterectomy under local anesthesia, with patch closure was immediately performed without complications. We conducted a literature review to identify cases of common carotid artery thrombus related to COVID-19. Carotid free-floating thrombus in the common carotid artery is exceptional. However, since the beginning of the COVID-19 pandemic, 15 cases have been published.
“…Infectious disease, especially acute infection will bring adverse prognosis and death risk to the elderly. The elderly should be regarded as the key population for epidemic prevention and control [20,21]. Sex was also closely related to the severity and death.…”
Section: Discussionmentioning
confidence: 99%
“…The male bias in severity and mortality of COVID-19 stems from the pathogenesis of SARS-CoV-2 infection. X chromosome and estrogen protect females from lethal infection [21,23]; besides, numerous studies indicted ACE2, which used by SARS-CoV-2 to enter into the host cells [24,25], generally has a higher expression in males than in females; moreover, females and males vary in their susceptibility and response to viral infections, the number and activity of innate immune cells, and immune responses are higher in females than in males [26]. There were some influencing factors that had opposite effects on the clinical outcomes in the two groups.…”
Background
To put COVID-19 patients into hospital timely, the clinical diagnosis had been implemented in Wuhan in the early epidemic. Here we compared the epidemiological characteristics of laboratory-confirmed and clinically diagnosed cases with COVID-19 in Wuhan.
Methods
Demographics, case severity and outcomes of 29,886 confirmed cases and 21,960 clinically diagnosed cases reported between December 2019 and February 24, 2020, were compared. The risk factors were estimated, and the effective reproduction number (Rt) of SARS-CoV-2 was also calculated.
Results
The age and occupation distribution of confirmed cases and clinically diagnosed cases were consistent, and their sex ratio were 1.0 and 0.9, respectively. The epidemic curve of clinical diagnosis cases was similar to that of confirmed cases, and the city centers had more cumulative cases and higher incidence density than suburbs in both of two groups. The proportion of severe and critical cases (21.5 % vs. 14.0 %, P < 0.0001) and case fatality rates (5.2 % vs. 1.2 %, P < 0.0001) of confirmed cases were all higher than those of clinically diagnosed cases. Risk factors for death we observed in both of two groups were older age, male, severe or critical cases. Rt showed the same trend in two groups, it dropped below 1.0 on February 6 among confirmed cases, and February 8 among clinically diagnosed cases.
Conclusions
The demographic characteristics and spatiotemporal distributions of confirmed and clinically diagnosed cases are roughly similar, but the disease severity and clinical outcome of clinically diagnosed cases are better than those of confirmed cases. In cases when detection kits are insufficient during the early epidemic, the implementation of clinical diagnosis is necessary and effective.
COVID-19 has substantially affected our lives during 2020. Since its beginning, several epidemiological models have been developed to investigate the specific dynamics of the disease. Early COVID-19 epidemiological models were purely statistical, based on a curve-fitting approach, and did not include causal knowledge about the disease. Yet, these models had predictive capacity; thus they were used to ground important political decisions, in virtue of the understanding of the dynamics of the pandemic that they offered. This raises a philosophical question about how purely statistical models can yield understanding, and if so, what the relationship between prediction and understanding in these models is. Drawing on the model that was developed by the Institute of Health Metrics and Evaluation, we argue that early epidemiological models yielded a modality of understanding that we call descriptive understanding, which contrasts with the so-called explanatory understanding which is assumed to be the main form of scientific understanding. We spell out the exact details of how descriptive understanding works, and efficiently yields understanding of the phenomena. Finally, we vindicate the necessity of studying other modalities of understanding that go beyond the conventionally assumed explanatory understanding.
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