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1.
Front Cardiovasc Med ; 10: 1134601, 2023.
Article in English | MEDLINE | ID: mdl-37304946

ABSTRACT

Background: Respiratory infections are one of the most common comorbidities identified in hospitalized patients. The coronavirus disease 2019 (COVID-19) pandemic greatly impacted healthcare systems, including acute cardiac services. Aim: This study aimed to describe the echocardiographic findings of patients with COVID-19 infections and their correlations with inflammatory biomarkers, disease severity, and clinical outcomes. Methods: This observational study was conducted between June 2021 and July 2022. The analysis included all patients diagnosed with COVID-19 who had transthoracic echocardiographic (TTE) scans within 72 h of admission. Results: The enrolled patients had a mean age of 55.6 ± 14.7 years, and 66.1% were male. Of the 490 enrolled patients, 203 (41.4%) were admitted to the intensive care unit (ICU). Pre-ICU TTE findings showed significantly higher incidence right ventricular dysfunction (28 [13.8%] vs. 23 [8.0%]; P = 0.04) and left ventricular (LV) regional wall motion abnormalities (55 [27.1%] vs. 29 [10.1%]; p < 0.001) in ICU patients compared to non-ICU patients. In-hospital mortality was 11 (2.2%), all deaths of ICU patients. The most sensitive predictors of ICU admission (p < 0.05): cardiac troponin I level (area under the curve [AUC] = 0.733), followed by hs-CRP (AUC = 0.620), creatine kinase-MB (AUC = 0.617), D-dimer (AUC = 0.599), and lactate dehydrogenase (AUC = 0.567). Binary logistic regression showed that reduced LV ejection fraction (LVEF), elevated pulmonary artery systolic pressure, and dilated right ventricle were echocardiographic predictors of poor outcomes (p < 0.05). Conclusion: Echocardiography is a valuable tool in assessing admitted patients with COVID-19. Lower LVEF, pulmonary hypertension, higher D-dimer, C-reactive protein, and B-type natriuretic peptide levels were predictors of poor outcomes.

2.
Saudi Med J ; 41(12): 1336-1343, 2020 Dec.
Article in English | MEDLINE | ID: mdl-33294892

ABSTRACT

OBJECTIVES: To analyze the clinical characteristics and in-hospital outcomes among coronavirus disease 2019 (COVID-19) positive medical staff compared with those of public. Methods: A total of 108 COVID-19-positive medical staff patients were included in the study from March 23, 2020 to June 15, 2020. Patients were analyzed for demographic data, clinical presentations, and in-hospital outcomes and compared against 661 COVID-19-infected patients of non-medical personel. Results: Mean age of medical staff patients was 44.05±13.9 years, most of whom were women (63.9%). The infected medical staff members consisted of 63 nurses (58.3%), 37 physicians (34.3%), 5 technicians (4.6%), and 3 pharmacists (2.8%). Smoking (60.2%) was the most frequent, followed by diabetes mellitus (37%). Of 108 COVID-19 infected medical staff, 18 (16.6%) were isolated in the intensive care unit (ICU), of which 14 (77.8%) were male, 16 (88.9%) were smokers, and 16 (88.9%) presented with pneumonia. Fatality ratio among medical staff patients was 4.6%. Male gender with odds ratios (OR) of 7.771 and 95% confidence intervals (CI) of 0.837-72.195 and a history of chronic kidney disease of (OR=10.778, 95% CI: 1.503-77.287) were predictors of death among the medical staff group. Conclusion: The incidence of COVID-19 infection among medical staff is quite high, but the occurrence of extreme illness and death is significantly low compared with the general community. Training should be implemented for all hospital staff on infection prevention techniques. Reliable and quick access for testing medical personnel is essential to maintain health, safety, and availability of health care workers during this pandemic.


Subject(s)
COVID-19/diagnosis , Health Personnel , Hospitalization , Adult , COVID-19/epidemiology , COVID-19/therapy , COVID-19 Testing , Comorbidity , Cross-Sectional Studies , Female , Hospital Mortality , Humans , Incidence , Male , Middle Aged , Prognosis , Retrospective Studies , Risk Factors , Saudi Arabia/epidemiology
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