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1.
Cardiovasc Res ; 119(5): 1190-1201, 2023 05 22.
Article in English | MEDLINE | ID: covidwho-2188640

ABSTRACT

AIMS: Previous analyses on sex differences in case fatality rates at population-level data had limited adjustment for key patient clinical characteristics thought to be associated with coronavirus disease 2019 (COVID-19) outcomes. We aimed to estimate the risk of specific organ dysfunctions and mortality in women and men. METHODS AND RESULTS: This retrospective cross-sectional study included 17 hospitals within 5 European countries participating in the International Survey of Acute Coronavirus Syndromes COVID-19 (NCT05188612). Participants were individuals hospitalized with positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from March 2020 to February 2022. Risk-adjusted ratios (RRs) of in-hospital mortality, acute respiratory failure (ARF), acute heart failure (AHF), and acute kidney injury (AKI) were calculated for women vs. men. Estimates were evaluated by inverse probability weighting and logistic regression models. The overall care cohort included 4499 patients with COVID-19-associated hospitalizations. Of these, 1524 (33.9%) were admitted to intensive care unit (ICU), and 1117 (24.8%) died during hospitalization. Compared with men, women were less likely to be admitted to ICU [RR: 0.80; 95% confidence interval (CI): 0.71-0.91]. In general wards (GWs) and ICU cohorts, the adjusted women-to-men RRs for in-hospital mortality were of 1.13 (95% CI: 0.90-1.42) and 0.86 (95% CI: 0.70-1.05; pinteraction = 0.04). Development of AHF, AKI, and ARF was associated with increased mortality risk (odds ratios: 2.27, 95% CI: 1.73-2.98; 3.85, 95% CI: 3.21-4.63; and 3.95, 95% CI: 3.04-5.14, respectively). The adjusted RRs for AKI and ARF were comparable among women and men regardless of intensity of care. In contrast, female sex was associated with higher odds for AHF in GW, but not in ICU (RRs: 1.25; 95% CI: 0.94-1.67 vs. 0.83; 95% CI: 0.59-1.16, pinteraction = 0.04). CONCLUSIONS: Women in GW were at increased risk of AHF and in-hospital mortality for COVID-19 compared with men. For patients receiving ICU care, fatal complications including AHF and mortality appeared to be independent of sex. Equitable access to COVID-19 ICU care is needed to minimize the unfavourable outcome of women presenting with COVID-19-related complications.


Subject(s)
Acute Kidney Injury , COVID-19 , Humans , Female , Male , COVID-19/complications , COVID-19/therapy , SARS-CoV-2 , Retrospective Studies , Sex Characteristics , Cross-Sectional Studies , Risk Factors , Acute Kidney Injury/diagnosis , Acute Kidney Injury/epidemiology , Acute Kidney Injury/therapy
2.
Mayo Clin Proc ; 96(8): 2081-2094, 2021 08.
Article in English | MEDLINE | ID: covidwho-1336718

ABSTRACT

OBJECTIVE: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using artificial intelligence applied to the electrocardiogram (ECG). METHODS: A global, volunteer consortium from 4 continents identified patients with ECGs obtained around the time of polymerase chain reaction-confirmed COVID-19 diagnosis and age- and sex-matched controls from the same sites. Clinical characteristics, polymerase chain reaction results, and raw electrocardiographic data were collected. A convolutional neural network was trained using 26,153 ECGs (33.2% COVID positive), validated with 3826 ECGs (33.3% positive), and tested on 7870 ECGs not included in other sets (32.7% positive). Performance under different prevalence values was tested by adding control ECGs from a single high-volume site. RESULTS: The area under the curve for detection of acute COVID-19 infection in the test group was 0.767 (95% CI, 0.756 to 0.778; sensitivity, 98%; specificity, 10%; positive predictive value, 37%; negative predictive value, 91%). To more accurately reflect a real-world population, 50,905 normal controls were added to adjust the COVID prevalence to approximately 5% (2657/58,555), resulting in an area under the curve of 0.780 (95% CI, 0.771 to 0.790) with a specificity of 12.1% and a negative predictive value of 99.2%. CONCLUSION: Infection with SARS-CoV-2 results in electrocardiographic changes that permit the artificial intelligence-enhanced ECG to be used as a rapid screening test with a high negative predictive value (99.2%). This may permit the development of electrocardiography-based tools to rapidly screen individuals for pandemic control.


Subject(s)
Artificial Intelligence , COVID-19/diagnosis , Electrocardiography , Case-Control Studies , Humans , Predictive Value of Tests , Sensitivity and Specificity
3.
Int J Infect Dis ; 101: 180-182, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-920296

ABSTRACT

We present the case of a 51-year-old patient with acute pericarditis as the dominant manifestation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The patient was admitted to the emergency department during a coronavirus disease 2019 (COVID-19) outbreak with a suspected ST-elevation myocardial infarction. A coronary angiogram was normal. Real-time reverse transcriptase PCR for the detection of nucleic acid from SARS-CoV-2 in a nasopharyngeal swab was positive. Laboratory tests revealed an increased white blood cell count, with neutrophilia and lymphocytopenia, elevated level of C-reactive protein, borderline elevated erythrocyte sedimentation rate, and slightly elevated interleukin 6. Echocardiography showed a hyperechogenic pericardium posterolaterally with minimal localized pericardial effusion. A chest computed tomography scan showed a small zone of ground-glass opacity in the right lower lobe (classified as CO-RADS 3). In patients with chest pain, ST elevation on electrocardiogram, a normal coronary angiogram, and suspected COVID-19, we should think of pericarditis as an unusual presentation of SARS-CoV-2 infection.


Subject(s)
COVID-19/diagnosis , Pericarditis/diagnosis , Pericarditis/virology , SARS-CoV-2/physiology , COVID-19/complications , COVID-19/diagnostic imaging , COVID-19/virology , Echocardiography , Electrocardiography , Hospitalization , Humans , Lung/diagnostic imaging , Male , Middle Aged , Pericarditis/complications , Pericarditis/diagnostic imaging , Pneumonia, Viral/diagnosis , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Tomography, X-Ray Computed
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