Chronological Development of Cardiovascular Disease in Times of COVID-19: A Retrospective Analysis of Hospitalized Diseases of the Circulatory System and COVID-19 Patients of a German University Hospital.
Sebastian GriewingNiklas GremkeJulian KreutzBernhard SchiefferLars TimmermannBirgit MarkusPublished in: Journal of cardiovascular development and disease (2022)
This study aims at examining the chronological development of hospitalized cardiovascular and COVID-19 patients and comparing the effects on related sub-disciplines and main diagnoses for pre-pandemic (2017-2019) and pandemic (2020-2021) years in the setting of a German university maximum care provider. Data were retrospectively retrieved from the hospital performance controlling system for patient collectives with main diagnosis of diseases of the circulatory system (n Circulatory ) and COVID-19 secondary diagnosis (n COVID-19 ). The cardiovascular patient collective (n Circulatory = 25,157) depicts a steady state in terms of relative yearly development of patient numbers (+0.4%, 2019-2020, +0.1%, 2020-2021). Chronological assessment points towards monthly decline during lockdowns and phases of high regional incidence of COVID-19 (i.e., 2019-2020: March -10.2%, April -12.4%, December -14.8%). Main diagnoses of congestive heart failure (+16.1% 2019/2020; +19.2% 2019/2021) and acute myocardial infarction show an increase in case numbers over the course of the whole pandemic (+15.4% 2019/2020; +9.4% 2019/2021). The results confirm negative effects on the cardiovascular care situation during the entire pandemic in the setting of a university maximum care provider. A general increase in cardiac disorders and a worrisome turn in case development of acute myocardial infarction emphasize the feared cardiovascular burden of COVID-19.
Keyphrases
- sars cov
- coronavirus disease
- acute myocardial infarction
- respiratory syndrome coronavirus
- healthcare
- heart failure
- cardiovascular disease
- palliative care
- left ventricular
- case report
- extracorporeal membrane oxygenation
- primary care
- quality improvement
- percutaneous coronary intervention
- type diabetes
- pain management
- machine learning
- emergency department
- electronic health record
- sensitive detection
- atrial fibrillation
- deep learning
- metabolic syndrome
- acute coronary syndrome
- cardiovascular events
- big data
- data analysis
- living cells