Abstract
Background The outbreaks of coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain a huge threat to the public health worldwide. Clinical data is limited up to now regarding the risk factors in favor of severe conversion of non-severe case with COVID-19.
Aims This study analyzed a hospital staff data to figure out general clinical features of COVID-19 in terms of the association of cardiovascular manifestations (CVMs) with in-hospital outcomes of COVID-19 cases.
Methods Retrospective, single-center case series of 41 consecutive hospitalized health staff with confirmed COVID-19 were collected at the Central Hospital of Wuhan in Wuhan, China, from January 15 to January 24, 2020. Epidemiological, demographic, clinical, laboratory, radiological, treatment data and in-hospital adverse events were collected and analyzed. Final date of follow-up was March 3, 2020. A comparative study was applied between cases with CVMs and those without CVMs.
Results Of all, clinicians and clinical nurses accounted for 80.5%, while 87.8% of all had history of patient contact. The population was presented with a mean age of 39.1 ± 9.2 and less comorbidities than community population. The three most frequent symptoms of COVID-19 cases analyzed were fever (82.9%), myalgia or fatigue (80.5%) and cough (63.4%). While, the three most frequent initial symptoms were myalgia or fatigue (80.5%), fever (73.2%) and cough (41.5%). There were 95.1% cases featured as non-severe course of disease according to the official standard in China. Patients with CVMs and those without CVMs accounted for 58.5% and 41.5%, respectively. Compared with cases without CVMs, patients with CVMs were presented with lower baseline lymphocyte count (0.99 ± 0.43 and 1.55 ± 0.61, P<0.001), more who had at least once positive nucleic acid detection of throat swab during admission (50.0% and 11.8%, P=0.011), and more received oxygen support (79.2% and 23.5%, P<0.001). The rate of in-hospital adverse events was significantly higher in patients with CVMs group (75.0% and 23.5%, P=0.001). Multivariable logistic regression model indicated that, coexisting with CVMs in COVID-19 patients was not independently associated with in-hospital adverse events.
Conclusions Most of hospital staff with COVID-19 had history of patient contact, featured non-severe course of disease. Cases with CVMs suffered from more in-hospital adverse events than those without CVMs. But concomitant CVMs were not independently associated with in-hospital adverse events in COVID-19 patients.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
Science and Technology Department of Hubei Province (No. 2019CFC843); Beijing United Heart Foundation (No. BJUHFCSOARF201901-19)
Author Declarations
All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.
Yes
All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.
Yes
I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
Yes
I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.
Yes
Footnotes
Conflicts of interest: None
Authorship declaration None of the article contents are under consideration for publication in any other journal or have been published in any journal. All authors have participated in the work and have reviewed and agree with the content of the article. We have no conflict of interest to disclose.
Data Availability
All data, models, or code generated or used during the study are available from the corresponding author by request.
