Incidence and Predictors of Thrombotic Complications in 4742 Patients with COVID-19 or Other Acute Infectious Respiratory Diseases: A Propensity Score-Matched Study.

BACKGROUND: A prothrombotic state, attributable to excessive inflammation, cytokine storm, hypoxia, and immobilization, is a feature of SARS-CoV-2 infection. Up to 30% of patients with severe COVID-19 remain at high risk of thromboembolic events despite anticoagulant administration, with adverse impact on in-hospital prognosis. METHODS: We retrospectively studied 4742 patients with acute infectious respiratory disease (AIRD); 2579 were diagnosed to have COVID-19 and treated with heparin, whereas 2163 had other causes of AIRD. We compared the incidence and predictors of total, arterial, and venous thrombosis, both in the whole population and in a propensity score-matched subpopulation of 3036 patients (1518 in each group). RESULTS: 271 thrombotic events occurred in the whole population: 121 (4.7%) in the COVID-19 group and 150 (6.9%) in the no-COVID-19 group (p < 0.001). No differences in the incidence of total (p = 0.11), arterial (p = 0.26), and venous (p = 0.38) thrombosis were found between the two groups after adjustment for confounding clinical variables and in the propensity score-matched subpopulation. Likewise, there were no significant differences in bleeding rates between the two groups. Clinical predictors of arterial thrombosis included age (p = 0.006), diabetes mellitus (p = 0.034), peripheral artery disease (p < 0.001), and previous stroke (p < 0.001), whereas history of solid cancer (p < 0.001) and previous deep vein thrombosis (p = 0.007) were associated with higher incidence of venous thrombosis. CONCLUSIONS: Hospitalized patients with COVID-19 treated with heparin do not seem to show significant differences in the cumulative incidence of thromboembolic events as well as in the incidence of arterial and venous thrombosis separately, compared with AIRD patients with different etiological diagnosis.

Electrocardiographic findings at presentation and clinical outcome in patients with SARS-CoV-2 infection.

AIMS: The main severe complications of SARS-CoV-2 infection are pneumonia and respiratory distress syndrome. Recent studies, however, reported that cardiac injury, as assessed by troponin levels, is associated with a worse outcome in these patients. No study hitherto assessed whether the simple standard electrocardiogram (ECG) may be helpful for risk stratification in these patients. METHODS AND RESULTS: We studied 324 consecutive patients admitted to our Emergency Department with a confirmed diagnosis of SARS-CoV-2 infection. Standard 12-lead ECG recorded on admission was assessed for cardiac rhythm and rate, atrioventricular and intraventricular conduction, abnormal Q/QS wave, ST segment and T wave changes, corrected QT interval, and tachyarrhythmias. At a mean follow-up of 31 ± 11 days, 44 deaths occurred (13.6%). Most ECG variables were significantly associated with mortality, including atrial fibrillation (P = 0.002), increasing heart rate (P = 0.002), presence of left bundle branch block (LBBB; P < 0.001), QRS duration (P <0 .001), a QRS duration of ≥110 ms (P < 0.001), ST segment depression (P < 0.001), abnormal Q/QS wave (P = 0.034), premature ventricular complexes (PVCs; P = 0.051), and presence of any ECG abnormality [hazard ratio (HR) 4.58; 95% confidence interval (CI) 2.40-8.76; P < 0.001]. At multivariable analysis, QRS duration (P = 0.002), QRS duration ≥110 ms (P = 0.03), LBBB (P = 0.014) and presence of any ECG abnormality (P = 0.04) maintained a significant independent association with mortality. CONCLUSION: Our data show that standard ECG can be helpful for an initial risk stratification of patients admitted for SARS-CoV-2 infectious disease.

Rapid Exclusion of COVID Infection With the Artificial Intelligence Electrocardiogram.

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.

Regional Survey in Lombardy, Northern Italy, on Vascular Surgery Intervention Outcomes During The COVID-19 Pandemic.

OBJECTIVE: The characteristics and outcomes of patients undergoing vascular surgery hospitalised and managed in Lombardy are described with a comparison of patients tested positive for COVID-19 (CV19-pos) vs. those tested negative (CV19-neg). METHODS: This was a multicentre, retrospective, observational cohort study which involved all vascular surgery services in Lombardy, Northern Italy. Data were retrospectively merged into a combined dataset covering the nine weeks of the Italian COVID-19 pandemic phase 1 (8 March 2020 to 3 May 2020). The primary outcome was freedom from in hospital death, secondary outcomes were re-thrombosis rate after peripheral revascularisation, and freedom from post-operative complication. RESULTS: Among 674 patients managed during the outbreak, 659 (97.8%) were included in the final analysis: 121 (18.4%) were CV19-pos. CV19-pos status was associated with a higher rate of complications (OR 4.5; p < .001, 95% CI 2.64 - 7.84), and a higher rate of re-thrombosis after peripheral arterial revascularisation (OR 2.2; p = .004, 95% CI 1.29 - 3.88). In hospital mortality was higher in CV19-pos patients (24.8% vs. 5.6%; OR 5.4, p < .001;95% CI 2.86 - 8.92). Binary logistic regression analysis identified CV19-pos status (OR 7.6; p < .001, 95% CI 3.75 - 15.28) and age > 80 years (OR 3.2; p = .001, 95% CI 1.61 - 6.57) to be predictors of in hospital death. CONCLUSION: In this experience of the vascular surgery group of Lombardy, COVID-19 infection was a marker of poor outcomes in terms of mortality and post-operative complications for patients undergoing vascular surgery treatments.

Differences in hub and spoke vascular units practice during the novel Coronavirus-19 (COVID-19) outbreak in Lombardy, Italy.

BACKGROUND: To highlight differences in clinical practice among referral (hub, HH) or satellite (spoke, SH) hospital vascular surgery units (VSUs) in Lombardy, during the COVID-19 pandemic "phase 1" period (March 8 - May 3, 2020). METHODS: The Vascular Surgery Group of Regione Lombardia Register, a real-word, multicenter, retrospective register was interrogated. All patients admitted with vascular disease were included. Patients' data on demographics, COVID-19 positivity, comorbidities and outcomes were extrapolated. Two cohorts were obtained: patients admitted to HH or SH. Primary endpoint was 30-day mortality rate. Secondary outcomes were 30-day complications and amputation (in case of peripheral artery disease [PAD]) rates. Univariate and multivariate analysis were used to compare HH and SH groups and predictors of poor outcomes. RESULTS: During the study period, 659 vascular patients in 4 HH and 27 SH were analyzed. Among these, 321 (48.7%) were admitted to a HH. No difference in COVID-19 positive patients was described (21.7% in HH vs. 15.9% in SH; P=0.058). After 30 days from intervention, HH and SH experienced similar mortality and no-intervention-related complication rate (12.1% vs. 10.0%; P=0.427 and 10.3% vs. 8.3%; P=0.377, respectively). Conversely, in HH postoperative complications were higher (23.4% vs. 16.9%, P=0.038) and amputations in patients treated for PAD were lower (10.8% vs. 26.8%; P<0.001) than in SH. Multivariate analysis demonstrated in both cohorts COVID-19-related pneumonia as independent predictor of death and postoperative complications, while age only for death. CONCLUSIONS: HH and SH ensured stackable results in patients with vascular disease during COVID-19 "phase 1." Despite this, poor outcomes were observed in both HH and SH cohorts, due to COVID-19 infection and its related pneumonia.

Electrocardiographic Findings and Clinical Outcome in Patients with COVID-19 or Other Acute Infectious Respiratory Diseases.

BACKGROUND: Cardiac involvement in coronavirus SARS-CoV-2 infection (COVID-19) has been reported in a sizeable proportion of patients and associated with a negative outcome; furthermore, a pre-existing heart disease is associated with increased mortality in these patients. In this prospective single-center case-control study we investigated whether COVID-19 patients present different rates and clinical implications of an abnormal electrocardiogram (ECG) compared to patients with an acute infectious respiratory disease (AIRD) caused by other pathogens. METHODS: We studied 556 consecutive patients admitted to the emergency department of our hospital with symptoms of AIRD; 324 were diagnosed to have COVID-19 and 232 other causes of AIRD (no-COVID-19 group). Standard 12-lead ECG performed on admission was assessed for various kinds of abnormalities, including ST segment/T wave changes, atrial fibrillation, ventricular arrhythmias, and intraventricular conduction disorders. RESULTS: ECG abnormalities were found in 120 (37.0%) and 101 (43.5%) COVID-19 and no-COVID-19 groups, respectively (p = 0.13). No differences in ECG abnormalities were found between the 2 groups after adjustment for clinical and laboratory variables. During a follow-up of 45 ± 16 days, 51 deaths (15.7%) occurred in the COVID-19 and 30 (12.9%) in the no-COVID-19 groups (p = 0.39). ST segment depression ≥ 0.5 mm (p = 0.016), QRS duration (p = 0.016) and presence of any ECG abnormality (p = 0.027) were independently associated with mortality at multivariable Cox regression analysis. CONCLUSION: Among patients hospitalized because of AIRD, we found no significant differences in abnormal ECG findings between COVID-19 vs. no-COVID-19 patients. The ECG on admission was helpful to identify patients with increased risk of death in both groups of patients.