Your browser doesn't support javascript.
COVID-19 Outcomes Amongst Patients With Pre-existing Cardiovascular Disease and Hypertension.
Chakinala, Raja Chandra; Shah, Chail D; Rakholiya, Jigisha H; Martin, Mehwish; Kaur, Nirmaljot; Singh, Harmandeep; Okafor, Toochukwu L; Nwodika, Chika; Raval, Payu; Yousuf, Salma; Lakhani, Komal; Yogarajah, Angelina; Malik, Preeti; Singh, Jagmeet; Kichloo, Asim; Patel, Urvish K.
  • Chakinala RC; Medicine, Geisinger Commonwealth School of Medicine, Danville, USA.
  • Shah CD; Medicine, Guthrie Robert Packer Hospital, Sayre, USA.
  • Rakholiya JH; Medicine, Mahatma Gandhi Medical College and Research Institute, Navi Mumbai, IND.
  • Martin M; Internal Medicine, Mayo Clinic, Rochester, USA.
  • Kaur N; Public Health, Icahn School of Medicine at Mount Sinai, New York, USA.
  • Singh H; Internal Medicine, Sri Guru Ramdas Institute of Medical Sciences and Research, Amritsar, IND.
  • Okafor TL; Internal Medicine, Sri Guru Ramdas University of Health Sciences, Amritsar, IND.
  • Nwodika C; Internal Medicine, Larkin Community Hospital, Hialeah, USA.
  • Raval P; Internal Medicine, Oba Okunade Sijuwade College of Medicine, Igbinedion University, Okada, NGA.
  • Yousuf S; Internal Medicine, siParadigm Diagnostic Informatics, Pine Brook, USA.
  • Lakhani K; Public Health, Icahn School of Medicine at Mount Sinai, New York, USA.
  • Yogarajah A; Internal Medicine, Lenox Hill Hospital, New York, USA.
  • Malik P; Internal Medicine, Medical University of the Americas, Devens, USA.
  • Singh J; Public Health, Icahn School of Medicine at Mount Sinai, New York, USA.
  • Kichloo A; Neurology, Massachusetts General Hospital, Andover, USA.
  • Patel UK; Nephrology, Geisinger Commonwealth School of Medicine, Scranton, USA.
Cureus ; 13(2): e13420, 2021 Feb 18.
Article in English | MEDLINE | ID: covidwho-1143806
Semantic information from SemMedBD (by NLM)
1. Patients USES Preexisting Condition Coverage
Subject
Patients
Predicate
USES
Object
Preexisting Condition Coverage
2. COVID-19 COEXISTS_WITH Cardiovascular Diseases
Subject
COVID-19
Predicate
COEXISTS_WITH
Object
Cardiovascular Diseases
3. COVID-19 COEXISTS_WITH Hypertensive disease
Subject
COVID-19
Predicate
COEXISTS_WITH
Object
Hypertensive disease
4. COVID-19 COEXISTS_WITH risk factors
Subject
COVID-19
Predicate
COEXISTS_WITH
Object
risk factors
5. COVID-19 PROCESS_OF Patients
Subject
COVID-19
Predicate
PROCESS_OF
Object
Patients
6. Cardiovascular Diseases PROCESS_OF Patients
Subject
Cardiovascular Diseases
Predicate
PROCESS_OF
Object
Patients
7. Hypertensive disease PROCESS_OF Patients
Subject
Hypertensive disease
Predicate
PROCESS_OF
Object
Patients
8. Patients USES Preexisting Condition Coverage
Subject
Patients
Predicate
USES
Object
Preexisting Condition Coverage
9. COVID-19 COEXISTS_WITH Cardiovascular Diseases
Subject
COVID-19
Predicate
COEXISTS_WITH
Object
Cardiovascular Diseases
10. COVID-19 COEXISTS_WITH Hypertensive disease
Subject
COVID-19
Predicate
COEXISTS_WITH
Object
Hypertensive disease
11. COVID-19 COEXISTS_WITH risk factors
Subject
COVID-19
Predicate
COEXISTS_WITH
Object
risk factors
12. COVID-19 PROCESS_OF Patients
Subject
COVID-19
Predicate
PROCESS_OF
Object
Patients
13. Cardiovascular Diseases PROCESS_OF Patients
Subject
Cardiovascular Diseases
Predicate
PROCESS_OF
Object
Patients
14. Hypertensive disease PROCESS_OF Patients
Subject
Hypertensive disease
Predicate
PROCESS_OF
Object
Patients
ABSTRACT

INTRODUCTION:

 Coronavirus disease 2019 (COVID-19) has multiorgan involvement and its severity varies with the presence of pre-existing risk factors like cardiovascular disease (CVD) and hypertension (HTN). Therefore, it is important to evaluate their effect on outcomes of COVID-19 patients. The objective of this meta-analysis and meta-regression is to evaluate outcomes of COVID-19 amongst patients with CVD and HTN.

METHODS:

English full-text observational studies having data on epidemiological characteristics of patients with COVID-19 were identified searching PubMed from December 1, 2019, to July 31, 2020, following Meta-analysis Of Observational Studies in Epidemiology (MOOSE) protocol. Studies having pre-existing CVD and HTN data that described outcomes including mortality and invasive mechanical ventilation (IMV) utilization were selected. Using random-effects models, risk of composite poor outcomes (meta-analysis) and isolated mortality and IMV utilization (meta-regression) were evaluated. Pooled prevalence of CVD and HTN, correlation coefficient (r) and odds ratio (OR) were estimated. The forest plots and correlation plots were created using random-effects models.

RESULTS:

Out of 29 studies (n=27,950) that met the criteria, 28 and 27 studies had data on CVD and HTN, respectively. Pooled prevalence of CVD was 18.2% and HTN was 32.7%. In meta-analysis, CVD (OR 3.36; 95% CI 2.29-4.94) and HTN (OR 1.94; 95% CI 1.57-2.40) were associated with composite poor outcome. In age-adjusted meta-regression, pre-existing CVD was having significantly higher correlation of IMV utilization (r 0.28; OR 1.3; 95% CI 1.1-1.6) without having any association with mortality (r -0.01; OR 0.9; 95% CI 0.9-1.1) among COVID-19 hospitalizations. HTN was neither correlated with higher IMV utilization (r 0.01; OR 1.0; 95% CI 0.9-1.1) nor correlated with higher mortality (r 0.001; OR 1.0; 95% CI 0.9-1.1).

CONCLUSION:

In age-adjusted analysis, though we identified pre-existing CVD as a risk factor for higher utilization of mechanical ventilation, pre-existing CVD and HTN had no independent role in increasing mortality.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study / Randomized controlled trials / Reviews / Risk factors Language: English Journal: Cureus Year: 2021 Document Type: Article Affiliation country: Cureus.13420

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study / Randomized controlled trials / Reviews / Risk factors Language: English Journal: Cureus Year: 2021 Document Type: Article Affiliation country: Cureus.13420