Acute anterior myocardial infarction: Streptokinase prevents ventricular thrombosis independently of its effect on infarct size

Left ventricular thrombosis (LVT) is a frequent complication after acute anterior myocardial infarction (AMI). The purpose of this study is to evaluate whether streptokinase (SK) therapy prevents LVT, and whether this effect is due to the preservation of left ventricular function or to the fibrinolytic action of the drug. Sixty-five patients who underwent a left ventricular angiography within 2 months after a first AMI were studied. Twenty-eight patients (SK group) received SK 1,500,000 U i.v. administered over 60 min within 6 h from the onset of symptoms. A lower incidence of LVT was found in the SK group (p = 0.0003). We divided patients into two classes according to the value of akinetic-dyskinetic area (AD): the first group with a lower value of AD, the second group with a higher value of AD. In both groups, a reduced incidence of LVT was associated with SK therapy (p = 0.014, p = 0.015, respectively). Early infusion of SK during AMI seems to prevent the development of LVT, with an effect partly independent from its action on infarct size for small to large myocardial infarction

Skeletal muscle mass independently predicts peak oxygen consumption and ventilatory response during exercise in noncachectic patients with chronic heart failure

n/

Frequency of predischarge ventricular arrhythmias in postmyocardial infarction patients depends on residual left ventricular pump performance and is independent of the occurrence of acute reperfusion

AbstractObjective. To test whether acute reperfusion of the infarct-related vessel after an acute myocardial infarction is associated with a subsequent reduction in spontaneous ventricular arrhythmias that is independent of ventricular ejection fraction, 1,944 patients from the GISSI-2 study population were studied. The patients were selected on the basis of a first myocardial infarction and the availability of two-dimensional echocardiographic ejection fraction and data on the number of premature ventricular contractions per hour on Holter monitoring.Background. It has been suggested that postthrombolytic reperfusion of the culprit vessel may be associated with an increased electrical stability of the infarcted heart, irrespective of its residual pump performance.Methods. The predischarge relation between ejection fraction and number of premature ventricular contractions per hour was plotted according to the occurrence (1,309 ptients) or not (635 patients) of acute reperfusion, identified noninvasively according to the modifications of the ST segment in serial electrocardiograms obtained in the first 24 h after infarction.Results. The frequency of premature ventricular contractions increased in a linear fashion with decreasing ejection fraction in both cohorts (p < 0.005 and p < 0.0001); however, there was no significant difference between the slops and the intercepts of the two regression lines, so that the relation between ejection fraction and number of premature ventricular contractions per hour could be adequately described by a single equation: y (number of premature ventricular contractions) = 33.0 - 0.42x (ejection fraction) (r = −0.107, p < 0.0001). The results were the same even when differences between group characteristics were accounted for in a multiple regression model.Conclusions. It is concluded that 1) the number of premature ventricular contractions per hour after an acute myocardial infarction is dependent in a linear, inverse fashion on the residual ventricular ejection fraction, and 2) this relation is independent of the occurrence of reperfusion in the acute phase of infarction

A quantitative assessment of epidemiological parameters required to investigate COVID-19 burden

Solid estimates describing the clinical course of SARS-CoV-2 infections are still lacking due to under-ascertainment of asymptomatic and mild-disease cases. In this work, we quantify age-specific probabilities of transitions between stages defining the natural history of SARS-CoV-2 infection from 1965 SARS-CoV-2 positive individuals identified in Italy between March and April 2020 among contacts of confirmed cases. Infected contacts of cases were confirmed via RT-PCR tests as part of contact tracing activities or retrospectively via IgG serological tests and followed-up for symptoms and clinical outcomes. In addition, we provide estimates of time intervals between key events defining the clinical progression of cases as obtained from a larger sample, consisting of 95,371 infections ascertained between February and July 2020. We found that being older than 60 years of age was associated with a 39.9% (95%CI: 36.2–43.6%) likelihood of developing respiratory symptoms or fever ≥ 37.5 °C after SARS-CoV-2 infection; the 22.3% (95%CI: 19.3–25.6%) of the infections in this age group required hospital care and the 1% (95%CI: 0.4–2.1%) were admitted to an intensive care unit (ICU). The corresponding proportions in individuals younger than 60 years were estimated at 27.9% (95%CI: 25.4–30.4%), 8.8% (95%CI: 7.3–10.5%) and 0.4% (95%CI: 0.1–0.9%), respectively. The infection fatality ratio (IFR) ranged from 0.2% (95%CI: 0.0–0.6%) in individuals younger than 60 years to 12.3% (95%CI: 6.9–19.7%) for those aged 80 years or more; the case fatality ratio (CFR) in these two age classes was 0.6% (95%CI: 0.1–2%) and 19.2% (95%CI: 10.9–30.1%), respectively. The median length of stay in hospital was 10 (IQR: 3–21) days; the length of stay in ICU was 11 (IQR: 6–19) days. The obtained estimates provide insights into the epidemiology of COVID-19 and could be instrumental to refine mathematical modeling work supporting public health decisions

Estimating SARS-CoV-2 transmission in educational settings: a retrospective cohort study

Background School closures and distance learning have been extensively adopted to counter the COVID-19 pandemic. However, the contribution of school transmission to the spread of SARS-CoV-2 remains poorly quantified. Methods We analyzed transmission patterns associated with 976 SARS-CoV-2 exposure events, involving 460 positive individuals, as identified in early 2021 through routine surveillance and an extensive screening conducted on students, school personnel, and their household members in a small Italian municipality. In addition to population screenings and contact-tracing operations, reactive closures of class and schools were implemented. Results From the analysis of 152 clear infection episodes and 584 exposure events identified by epidemiological investigations, we estimated that approximately 50%, 21%, and 29% of SARS-CoV-2 transmission was associated with household, school, and community contacts, respectively. We found substantial transmission heterogeneities, with 20% positive individuals causing 75% to 80% of ascertained infection episodes. A higher proportion of infected individuals causing onward transmission was found among students (46.2% vs. 25%, on average), who also caused a markedly higher number of secondary cases (mean: 1.03 vs. 0.35). By reconstructing likely transmission chains from the entire set of exposures identified during contact-tracing operations, we found that clusters originated from students or school personnel were associated with a larger average cluster size (3.32 vs. 1.15) and a larger average number of generations in the transmission chain (1.56 vs. 1.17). Conclusions Uncontrolled SARS-CoV-2 transmission at school could disrupt the regular conduct of teaching activities, likely seeding the transmission into other settings, and increasing the burden on contact-tracing operations

Estimating SARS-CoV-2 transmission in educational settings: a retrospective cohort study

Background School closures and distance learning have been extensively adopted to counter the COVID-19 pandemic. However, the contribution of school transmission to the spread of SARS-CoV-2 remains poorly quantified. Methods We analyzed transmission patterns associated with 976 SARS-CoV-2 exposure events, involving 460 positive individuals, as identified in early 2021 through routine surveillance and an extensive screening conducted on students, school personnel, and their household members in a small Italian municipality. In addition to population screenings and contact-tracing operations, reactive closures of class and schools were implemented. Results From the analysis of 152 clear infection episodes and 584 exposure events identified by epidemiological investigations, we estimated that approximately 50%, 21%, and 29% of SARS-CoV-2 transmission was associated with household, school, and community contacts, respectively. We found substantial transmission heterogeneities, with 20% positive individuals causing 75% to 80% of ascertained infection episodes. A higher proportion of infected individuals causing onward transmission was found among students (46.2% vs. 25%, on average), who also caused a markedly higher number of secondary cases (mean: 1.03 vs. 0.35). By reconstructing likely transmission chains from the entire set of exposures identified during contact-tracing operations, we found that clusters originated from students or school personnel were associated with a larger average cluster size (3.32 vs. 1.15) and a larger average number of generations in the transmission chain (1.56 vs. 1.17). Conclusions Uncontrolled SARS-CoV-2 transmission at school could disrupt the regular conduct of teaching activities, likely seeding the transmission into other settings, and increasing the burden on contact-tracing operations

Increasing situational awareness through nowcasting of the reproduction number

The time varying reproduction number R is a critical variable for situational awareness during infectious disease outbreaks, but delays between infection and reporting hinder its accurate estimation in real time. We propose a nowcasting method for improving the timeliness and accuracy of R estimates, based on comparisons of successive versions of surveillance databases. The method was validated against COVID-19 surveillance data collected in Italy over an 18-month period. Compared to traditional methods, the nowcasted reproduction number reduced the estimation delay from 13 to 8 days, while maintaining a better accuracy. Moreover, it allowed anticipating the detection of periods of epidemic growth by between 6 and 23 days. The method offers a simple and generally applicable tool to improve situational awareness during an epidemic outbreak, allowing for informed public health response planning

Intrinsic generation time of the SARS-CoV-2 Omicron variant: an observational study of household transmission

Background Starting from the final months of 2021, the SARS-CoV-2 Omicron variant expanded globally, swiftly replacing Delta, the variant that was dominant at the time. Many uncertainties remain about the epidemiology of Omicron; here, we aim to estimate its generation time.Methods We used a Bayesian approach to analyze 23,122 SARS-CoV-2 infected individuals clustered in 8903 households as determined from contact tracing operations in Reggio Emilia, Italy, throughout January 2022. We estimated the distribution of the intrinsic generation time (the time between the infection dates of an infector and its secondary cases in a fully susceptible population), realized household generation time, realized serial interval (time between symptom onset of an infector and its secondary cases), and contribution of pre-symptomatic transmission.Findings We estimated a mean intrinsic generation time of 6.84 days (95% credible intervals, CrI, 5.72-8.60), and a mean realized household generation time of 3.59 days (95%CrI: 3.55-3.60). The household serial interval was 2.38 days (95%CrI 2.30-2.47) with about 51% (95%CrI 45-56%) of infections caused by symptomatic individuals being generated before symptom onset.Interpretation These results indicate that the intrinsic generation time of the SARS-CoV-2 Omicron variant might not have shortened as compared to previous estimates on ancestral lineages, Alpha and Delta, in the same geographic setting. Like for previous lineages, pre-symptomatic transmission appears to play a key role for Omicron transmission. Estimates in this study may be useful to design quarantine, isolation and contact tracing protocols and to support surveillance (e.g., for the accurate computation of reproduction numbers).Copyright (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/

Estimation of the incubation period and generation time of SARS-CoV-2 Alpha and Delta variants from contact tracing data

: Quantitative information on epidemiological quantities such as the incubation period and generation time of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is scarce. We analysed a dataset collected during contact tracing activities in the province of Reggio Emilia, Italy, throughout 2021. We determined the distributions of the incubation period for the Alpha and Delta variants using information on negative polymerase chain reaction tests and the date of last exposure from 282 symptomatic cases. We estimated the distributions of the intrinsic generation time using a Bayesian inference approach applied to 9724 SARS-CoV-2 cases clustered in 3545 households where at least one secondary case was recorded. We estimated a mean incubation period of 4.9 days (95% credible intervals, CrI, 4.4-5.4) for Alpha and 4.5 days (95% CrI 4.0-5.0) for Delta. The intrinsic generation time was estimated to have a mean of 7.12 days (95% CrI 6.27-8.44) for Alpha and of 6.52 days (95% CrI 5.54-8.43) for Delta. The household serial interval was 2.43 days (95% CrI 2.29-2.58) for Alpha and 2.74 days (95% CrI 2.62-2.88) for Delta, and the estimated proportion of pre-symptomatic transmission was 48-51% for both variants. These results indicate limited differences in the incubation period and intrinsic generation time of SARS-CoV-2 variants Alpha and Delta compared to ancestral lineages