Tenecteplase (TNK) is a promising candidate to replace alteplase as the standard of care for acute ischemic stroke (AIS); however, the optimal dosage is still to be investigated. Therefore, we aim to evaluate the safety and efficacy of TNK versus alteplase and to investigate the optimal TNK dosage. A systematic review, pairwise, and network meta-analysis synthesizing randomized controlled trials (RCTs) from WOS, SCOPUS, EMBASE, and PubMed until July 26th, 2022. We used the risk ratio (RR) for dichotomous outcomes presented with the corresponding 95% confidence interval (CI). We registered our protocol in PROSPERO with ID: CRD42022352038. Nine RCTs with a total of 3,707 patients were included. TNK significantly led to complete recanalization (RR: 1.27 with 95% CI [1.02, 1.57], P = 0.03); however, we found no difference regarding early neurological improvement (RR: 1.07 with 95% CI [0.94, 1.21], P = 0.33) and excellent neurological recovery (RR: 1.03 with 95% CI [0.96, 1.10], P = 0.42). Also, TNK was similar to alteplase regarding mortality (RR: 0.99 with 95% CI [0.82, 1.18], P = 0.88), intracranial haemorrhage (RR: 1.00 with 95% CI [0.85, 1.18], P = 0.99), and parenchymal hematoma (RR: 1.13 with 95% CI [0.83, 1.54], P = 0.44). TNK in the dose of 0.25 mg is a viable candidate to displace alteplase as the standard of care in patients with an AIS within 4.5 h of presentation due to its better rate of early neurological recovery and non-inferiority in terms of safety outcomes. However, the evidence regarding TNK’s role in AIS presenting after 4.5 h from symptoms onset, wake-up stroke, and minor stroke/TIA is still lacking, necessitating further double-blinded pragmatic RCTs in this regard.

Aims:Increased left ventricular (LV) wall thickness is frequently encountered in transthoracic echocardiography (TTE). While accurate and early diagnosis is clinically important, given the differences in available therapeutic options and prognosis, an extensive workup is often required to establish the diagnosis. We propose the first echo-based, automated deep learning model with a fusion architecture to facilitate the evaluation and diagnosis of increased left ventricular (LV) wall thickness. Methods and Results: Patients with an established diagnosis of increased LV wall thickness (hypertrophic cardiomyopathy (HCM), cardiac amyloidosis (CA), and hypertensive heart disease (HTN)/others) between 1/2015 and 11/2019 at Mayo Clinic Arizona were identified. The cohort was divided into 80%/10%/10% for training, validation, and testing sets, respectively. Six baseline TTE views were used to optimize a pre-trained InceptionResnetV2 model. Each model output was used to train a meta-learner under a fusion architecture. Model performance was assessed by multiclass area under the receiver operating characteristic curve (AUROC). A total of 586 patients were used for the final analysis (194 HCM, 201 CA, and 191 HTN/others). The mean age was 55.0 years, and 57.8% were male. Among the individual view-dependent models, the apical 4-chamber model had the best performance (AUROC: HCM: 0.94, CA: 0.73, and HTN/other: 0.87). The final fusion model outperformed all the view-dependent models (AUROC: HCM: 0.93, CA: 0.90, and HTN/other: 0.92). Conclusion: The echo-based InceptionResnetV2 fusion model can accurately classify the main etiologies of increased LV wall thickness and can facilitate the process of diagnosis and workup.

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Patients hospitalized for acute myocardial infarction (AMI) may have concomitant positive coronavirus disease 2019 (COVID-19). We aimed to compare the risk of in-hospital mortality in patients primarily hospitalized for AMI with or without concomitant COVID-19 positive status. Using the random-effects model, we conducted a systematic review and meta-analysis of published articles from December 1, 2019, to April 1, 2022. There were eight studies with 10,128 patients, including 612 patients with COVID and 9516 patients without COVID. A total of 261 patients (42.64%) with COVID-19 positive and 612 patients (6.43%) with negative COVID-19 status died in the hospital. Pooled data showed that patients with a primary diagnosis of AMI with COVID-19 infection had more than five times increased risk of in-hospital mortality compared to patients without COVID-19 (OR: 5.06, 95% CI: 3.61, 7.09; I 2 = 35%, P < 0.001). However, pooled data from five studies with adjustment of baseline differences in patient demographics and characteristics, comorbidities, and in-hospital pharmacology revealed more than three times increased risk of in-hospital mortality compared to patients who had primary AMI without COVID-19 infection (aOR: 3.47, 95% CI: 2.21, 5.45; I 2 = 0%, P < 0.001). In subgroup analysis, ST-elevation myocardial infarction (STEMI) had lower in-hospital mortality (OR 4.23, 95% CI: 3.31, 5.40; I 2 = 0%, P < 0.001) compared to non-ST-segment elevation myocardial infarction (NSTEMI) (OR 9.97, 95% CI: 5.71, 17.41; I 2 = 0%, P < 0.001) (p-value = 0.006). Our study shows that COVID-19 infection is associated with increased in-hospital mortality in patients with index hospitalization for AMI.