A meta-analysis on the risk factors adjusted association between cardiovascular disease and COVID-19 severity

Xu, Jie; Xiao, Wenwei; Liang, Xuan; Shi, Li; Zhang, Peihua; Wang, Ying; Wang, Yadong; Yang, Haiyan

doi:10.1186/s12889-021-11051-w

Cited by 49 publications

(45 citation statements)

References 208 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In line with these meta-analyses, our study identified that hypertension, cardiovascular disease, diabetes, and obesity were the most prevalent among COVID-19 patients. Moreover, compared with the discharged COVID-19 patients, nondischarged patients were more likely to have three or more comorbidities, which is consistent with other previous results showing that patients with multiple morbidities are at the highest risk of developing complications leading to death [73,74].…”

Section: Discussionsupporting

confidence: 90%

Risk of Death in Comorbidity Subgroups of Hospitalized COVID-19 Patients Inferred by Routine Laboratory Markers of Systemic Inflammation on Admission: A Retrospective Study

Cocoș

Mahler

Turcu-Știolică

et al. 2022

Viruses

View full text Add to dashboard Cite

Our study objective was to construct models using 20 routine laboratory parameters on admission to predict disease severity and mortality risk in a group of 254 hospitalized COVID-19 patients. Considering the influence of confounding factors in this single-center study, we also retrospectively assessed the correlations between the risk of death and the routine laboratory parameters within individual comorbidity subgroups. In multivariate regression models and by ROC curve analysis, a model of three routine laboratory parameters (AUC 0.85; 95% CI: 0.79–0.91) and a model of six laboratory factors (AUC 0.86; 95% CI: 0.81–0.91) were able to predict severity and mortality of COVID-19, respectively, compared with any other individual parameter. Hierarchical cluster analysis showed that inflammatory laboratory markers grouped together in three distinct clusters including positive correlations: WBC with NEU, NEU with neutrophil-to-lymphocyte ratio (NLR), NEU with systemic immune-inflammation index (SII), NLR with SII and platelet-to-lymphocyte ratio (PLR) with SII. When analyzing the routine laboratory parameters in the subgroups of comorbidities, the risk of death was associated with a common set of laboratory markers of systemic inflammation. Our results have shown that a panel of several routine laboratory parameters recorded on admission could be helpful for early evaluation of the risk of disease severity and mortality in COVID-19 patients. Inflammatory markers for mortality risk were similar in the subgroups of comorbidities, suggesting the limited effect of confounding factors in predicting COVID-19 mortality at admission.

show abstract

Section: Discussionsupporting

confidence: 90%

Risk of Death in Comorbidity Subgroups of Hospitalized COVID-19 Patients Inferred by Routine Laboratory Markers of Systemic Inflammation on Admission: A Retrospective Study

Cocoș

Mahler

Turcu-Știolică

et al. 2022

Viruses

View full text Add to dashboard Cite

show abstract

“…Unfortunately, comparisons with national trends is limited because data on age dis-tributions in the early pandemic period (January-April 2020) were excluded from national reports because of inconsistent COVID-19 testing availability (Boehmer et al, 2020). However, this sample reflected broader national norms in terms of prevalence of comorbidities such as heart conditions and obesity that have been shown to contribute to the severity of COVID-19 (Simonnet et al, 2020;Xu et al, 2021). Much of the sample resided in geographic areas that are largely comprised of people from diverse racial and ethnic backgrounds, including several minority/majority areas.…”

Section: Key Resultsmentioning

confidence: 99%

Nurse‐sensitive indicators during COVID‐19

Banister

Carroll

Dickins

et al. 2022

Int J of Nursing Knowl

View full text Add to dashboard Cite

Purpose: Nurses are on the forefront of delivering care to patients hospitalized with COVID-19. Nurses' impact on patient care can be discerned through assessment and documentation strategies, including structured and unstructured narratives, clinical pathways, flowsheets, and problem-based approaches. To date, there are no published reports regarding nursing assessment and documentation during the COVID-19 pandemic using an assessment framework to capture clinical decision making, nursing diagnoses, and key social determinant of health (SDoH) data. Hence, the purpose of this investigation was to conduct an exploratory nursing documentation audit of patients hospitalized with COVID-19 during the first surge to identify types and frequency of nurse-sensitive indicators, including SDoH.Method: This pilot study utilized a retrospective chart review design at a single academic medical center, utilizing Gordon's Eleven Functional Health Patterns (FHP) framework to extract clinical, social, and nursing assessment data for patients hospitalized with COVID-19. Descriptive statistics were computed for continuous variables and counts/percentages for categorical variables.Findings: Data from 94 patient records were analyzed. Most patients were male (59.6%), with a mean age of 58 years. Nearly 15% of patients were Black and 12.8% were Hispanic, most residing in four geographic areas. Nine of the 11 FHPs were reflected in nursesensitive indicators documented in the electronic health record. SDoH data were inconsistently documented, including race, education, history of neglect/abuse, and occupation. Conclusion:The FHP framework captured many nurse-sensitive indicators during the first COVID-19 surge, although screening for and documenting SDoH data were limited.

show abstract

“…In the elderly population, we saw that multimorbidity networks with metabolic and cardiovascular diseases had the highest risk of COVID-19 hospitalization and mortality. Cardiovascular comorbidity has been associated with poorer prognosis in SARS-CoV-2 infected individuals, and many authors have suggested that people with preexisting cardiovascular diseases may need special attention [ 12 , 13 , 14 , 55 ]. In the general population, especially in the elderly, a cardiorespiratory pattern has been identified; the association between cardiovascular and pulmonary diseases is well known in the literature and of great importance in clinical practice [ 18 , 56 ].…”

Section: Discussionmentioning

confidence: 99%

Multimorbidity Profiles and Infection Severity in COVID-19 Population Using Network Analysis in the Andalusian Health Population Database

Carmona-Pírez

Ioakeim-Skoufa

Gimeno-Miguel

et al. 2022

IJERPH

View full text Add to dashboard Cite

Identifying the population at risk of COVID-19 infection severity is a priority for clinicians and health systems. Most studies to date have only focused on the effect of specific disorders on infection severity, without considering that patients usually present multiple chronic diseases and that these conditions tend to group together in the form of multimorbidity patterns. In this large-scale epidemiological study, including primary and hospital care information of 166,242 patients with confirmed COVID-19 infection from the Spanish region of Andalusia, we applied network analysis to identify multimorbidity profiles and analyze their impact on the risk of hospitalization and mortality. Our results showed that multimorbidity was a risk factor for COVID-19 severity and that this risk increased with the morbidity burden. Individuals with advanced cardio-metabolic profiles frequently presented the highest infection severity risk in both sexes. The pattern with the highest severity associated in men was present in almost 28.7% of those aged ≥80 years and included associations between cardiovascular, respiratory, and metabolic diseases; age-adjusted odds ratio (OR) 95% confidence interval (1.71 (1.44–2.02)). In women, similar patterns were also associated the most with infection severity, in 7% of 65–79-year-olds (1.44 (1.34–1.54)) and in 29% of ≥80-year-olds (1.35 (1.18–1.53)). Patients with mental health patterns also showed one of the highest risks of COVID-19 severity, especially in women. These findings strongly recommend the implementation of personalized approaches to patients with multimorbidity and SARS-CoV-2 infection, especially in the population with high morbidity burden.

show abstract

A meta-analysis on the risk factors adjusted association between cardiovascular disease and COVID-19 severity

Cited by 49 publications

References 208 publications

Risk of Death in Comorbidity Subgroups of Hospitalized COVID-19 Patients Inferred by Routine Laboratory Markers of Systemic Inflammation on Admission: A Retrospective Study

Risk of Death in Comorbidity Subgroups of Hospitalized COVID-19 Patients Inferred by Routine Laboratory Markers of Systemic Inflammation on Admission: A Retrospective Study

Nurse‐sensitive indicators during COVID‐19

Multimorbidity Profiles and Infection Severity in COVID-19 Population Using Network Analysis in the Andalusian Health Population Database

Contact Info

Product

Resources

About