Risk Factors for In-hospital Nonhemorrhagic Stroke in Patients With Acute Myocardial Infarction Treated With Thrombolysis: Results from GUSTO-I

BACKGROUND: Nonhemorrhagic stroke occurs in 0.1% to 1.3% of patients with acute myocardial infarction who are treated with thrombolysis, with substantial associated mortality and morbidity. Little is known about the risk factors for its occurrence. METHODS AND RESULTS: We studied the 247 patients with nonhemorrhagic stroke who were randomly assigned to one of four thrombolytic regimens within 6 hours of symptom onset in the GUSTO-I trial. We assessed the univariable and multivariable baseline risk factors for nonhemorrhagic stroke and created a scoring nomogram from the baseline multivariable modeling. We used time-dependent Cox modeling to determine multivariable in-hospital predictors of nonhemorrhagic stroke. Baseline and in-hospital predictors were then combined to determine the overall predictors of nonhemorrhagic stroke. Of the 247 patients, 42 (17%) died and another 98 (40%) were disabled by 30-day follow-up. Older age was the most important baseline clinical predictor of nonhemorrhagic stroke, followed by higher heart rate, history of stroke or transient ischemic attack, diabetes, previous angina, and history of hypertension. These factors remained statistically significant predictors in the combined model, along with worse Killip class, coronary angiography, bypass surgery, and atrial fibrillation/flutter. CONCLUSIONS: Nonhemorrhagic stroke is a serious event in patients with acute myocardial infarction who are treated with thrombolytic, antithrombin, and antiplatelet therapy. We developed a simple nomogram that can predict the risk of nonhemorrhagic stroke on the basis of baseline clinical characteristics. Prophylactic anticoagulation may be an important treatment strategy for patients with high probability for nonhemorrhagic stroke, but further study is needed

Stroke in Patients With Acute Coronary Syndromes: Incidence and Outcomes in the Platelet Glycoprotein IIb/IIIa in Unstable Angina: Receptor Suppression Using Integrilin Therapy (PURSUIT) Trial

BACKGROUND: The incidence of stroke in patients with acute coronary syndromes has not been clearly defined because few trials in this patient population have been large enough to provide stable estimates of stroke rates. METHODS AND RESULTS: We studied the 10 948 patients with acute coronary syndromes without persistent ST-segment elevation who were randomly assigned to placebo or the platelet glycoprotein IIb/IIIa receptor inhibitor eptifibatide in the Platelet Glycoprotein IIb/IIIa in Unstable Angina: Receptor Suppression Using Integrilin Therapy (PURSUIT) trial to determine stroke rates, stroke types, clinical outcomes in patients with stroke, and independent baseline clinical predictors for nonhemorrhagic stroke. Stroke occurred in 79 (0.7%) patients, with 66 (0.6%) nonhemorrhagic, 6 intracranial hemorrhages, 3 cerebral infarctions with hemorrhagic conversion, and 4 of uncertain cause. There were no differences in stroke rates between patients who received placebo and those assigned high-dose eptifibatide (odds ratios and 95% confidence intervals 0.82 [0.59, 1.14] and 0.70 [0.49, 0.99], respectively). Of the 79 patients with stroke, 17 (22%) died within 30 days, and another 26 (32%) were disabled by hospital discharge or 30 days, whichever came first. Higher heart rate was the most important baseline clinical predictor of nonhemorrhagic stroke, followed by older age, prior anterior myocardial infarction, prior stroke or transient ischemic attack, and diabetes mellitus. These factors were used to develop a simple scoring nomogram that can predict the risk of nonhemorrhagic stroke. CONCLUSIONS: Stro

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Effects of stroke on medical resource use and costs in acute myocardial infarction. GUSTO I Investigators. Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries Study

BACKGROUND: Stroke occurs concurrently with myocardial infarction (MI) in approximately 30 000 US patients each year. This number is expected to rise with the increasing use of thrombolytic therapy for MI. However, no data exist for the economic effect of stroke in the setting of acute MI (AMI). The purpose of this prospective study was to assess the effect of stroke on medical resource use and costs in AMI patients in the United States. METHODS AND RESULTS: Medical resource use and cost data were prospectively collected for 2566 randomly selected US GUSTO I patients (from 23 105 patients) and for the 321 US GUSTO I patients who developed non-bypass surgery-related stroke during the baseline hospitalization. Follow-up was for 1 year. All costs are expressed in 1993 US dollars. During the baseline hospitalization, stroke was associated with a reduction in cardiac procedure rates and an increase in length of stay, despite a hospital mortality rate of 37%. Together with stroke-related procedural costs of $2220 per patient, the baseline medical costs increased by 44$29 242 versus $20 301, P<0.0001). Follow-up medical costs were substantially higher for stroke survivors ($22 400 versus $5282, P<0.0001), dominated by the cost of institutional care. The main determinant for institutional care was discharge disability status. The cumulative 1-year medical costs for stroke patients were$15 092 higher than for no-stroke patients. Hemorrhagic stroke patients had a much higher hospital mortality rate than non-hemorrhagic stroke patients (53% versus 15%, P<0.001), which was associated with approximately $7200 lower mean baseline hospitali

An Investigation of B(d)0 and B(s)0 oscillation

Bd0 and Bs0 oscillation is studied using almost a million hadronic Z decays collected by the ALEPH experiment at LEP. Events are selected with two leptons present, on opposite sides of the event and with high transverse momentum. The leptons are expected to be dominantly from b decays; a topological vertexing technique is applied to measure the decay length of the b hadrons, and their momentum is determined using an energy-flow method. The fraction of events in which the leptons have the same charge is studied as a function of the measured decay time, and clear evidence is seen for the time-dependent nature of mixing. The frequency measured for the oscillation corresponds to a mass difference for the Bd0 mass eigenstates Δmd = (3.3−0.4+0.5 ± 0.7) × 10−4 eV/c2. Allowing a second frequency component for the Bs0 a high value for Δms is favoured, leading to the limit Δms > 12 × 10−4 eV/c2 (95% CL), from which (Δm/Γ)s > 2.0 is derived

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease