26 research outputs found

    SARS-CoV-2 infection in high-risk children following tixagevimab–cilgavimab (Evusheld) pre-exposure prophylaxis: a single-center observational study

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    From 8 December 2021 to 26 January 2023, tixagevimab–cilgavimab (T-C) was authorized for pre-exposure prophylaxis of COVID-19. During this period, we used a multidisciplinary team to communicate, screen, approach, and administer T-C to eligible patients. Twenty-seven patients were eligible. Of these, 24 (88.9%) received at least one dose of T-C and three patients received two doses. Majority of patients were White, non-Hispanic, and women. Only two patients had COVID-19 prior to receiving T-C. Seventeen (70.8%) had received two or more doses of SARS-CoV-2 vaccine. No serious adverse events were noted. Seven patients developed SARS-CoV-2 infection within 180 days of receiving T-C (median 102 days; range 28–135), and only one patient developed severe COVID-19 requiring intensive mechanical ventilation in the intensive care unit

    Effect of aliskiren on post-discharge outcomes among diabetic and non-diabetic patients hospitalized for heart failure: insights from the ASTRONAUT trial

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    Aims The objective of the Aliskiren Trial on Acute Heart Failure Outcomes (ASTRONAUT) was to determine whether aliskiren, a direct renin inhibitor, would improve post-discharge outcomes in patients with hospitalization for heart failure (HHF) with reduced ejection fraction. Pre-specified subgroup analyses suggested potential heterogeneity in post-discharge outcomes with aliskiren in patients with and without baseline diabetes mellitus (DM). Methods and results ASTRONAUT included 953 patients without DM (aliskiren 489; placebo 464) and 662 patients with DM (aliskiren 319; placebo 343) (as reported by study investigators). Study endpoints included the first occurrence of cardiovascular death or HHF within 6 and 12 months, all-cause death within 6 and 12 months, and change from baseline in N-terminal pro-B-type natriuretic peptide (NT-proBNP) at 1, 6, and 12 months. Data regarding risk of hyperkalaemia, renal impairment, and hypotension, and changes in additional serum biomarkers were collected. The effect of aliskiren on cardiovascular death or HHF within 6 months (primary endpoint) did not significantly differ by baseline DM status (P = 0.08 for interaction), but reached statistical significance at 12 months (non-DM: HR: 0.80, 95% CI: 0.64-0.99; DM: HR: 1.16, 95% CI: 0.91-1.47; P = 0.03 for interaction). Risk of 12-month all-cause death with aliskiren significantly differed by the presence of baseline DM (non-DM: HR: 0.69, 95% CI: 0.50-0.94; DM: HR: 1.64, 95% CI: 1.15-2.33; P < 0.01 for interaction). Among non-diabetics, aliskiren significantly reduced NT-proBNP through 6 months and plasma troponin I and aldosterone through 12 months, as compared to placebo. Among diabetic patients, aliskiren reduced plasma troponin I and aldosterone relative to placebo through 1 month only. There was a trend towards differing risk of post-baseline potassium ≥6 mmol/L with aliskiren by underlying DM status (non-DM: HR: 1.17, 95% CI: 0.71-1.93; DM: HR: 2.39, 95% CI: 1.30-4.42; P = 0.07 for interaction). Conclusion This pre-specified subgroup analysis from the ASTRONAUT trial generates the hypothesis that the addition of aliskiren to standard HHF therapy in non-diabetic patients is generally well-tolerated and improves post-discharge outcomes and biomarker profiles. In contrast, diabetic patients receiving aliskiren appear to have worse post-discharge outcomes. Future prospective investigations are needed to confirm potential benefits of renin inhibition in a large cohort of HHF patients without D

    Vehicle classification through detection and color segmentation of registration plates running on raspberry Pi 3 model B

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    © BEIESP. Classification of license plates provides useful information regarding the nature of the vehicle, whether it is used for public transport, a privately-owned vehicle, an official vehicle, or a special vehicle. In the Philippines, the registration plates of vehicles are classified by colors. Colors such as red, green blue, black, yellow are used to identify what vehicle classification the plate belongs to. The information is useful to applications in statistics and transport regulation. This paper discusses a convolutional neural network based embedded system that runs on Raspberry Pi 3 Model B. The said system provides a process of classifying vehicles using plate detection using Convolutional Neural Networks and color thresholding of registration plates using the RGB color space. TensorFlow and OpenCV libraries were utilized for the detection and classification

    Prediction of attributable mortality in pediatric patients with cancer admitted to the intensive care unit for suspected infection: A comprehensive evaluation of risk scores

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    Abstract Objective To evaluate the performance of existing sepsis scores for prediction of adverse outcomes in children with cancer admitted to the ICU with suspected sepsis. Design Retrospective chart review using data available at 1, 6, 12, and 24 h after ICU admission to calculate the Pediatric Risk of Mortality 3 (PRISM‐3), Pediatric Sequential Organ Failure Assessment (pSOFA), Paediatric Logistic Organ Dysfunction 2 (PELOD‐2), and Quick Pediatric Sequential Organ Failure Assessment (qSOFA) scores. Area under the receiver operator characteristic curve (AUROC) was used to evaluate performance for prediction of attributable mortality. Sensitivity analyses included recalculation of scores using worst preceding values for each variable, excluding hematologic parameters, and prediction of alternative outcomes. Setting St. Jude Children's Research Hospital, a pediatric comprehensive cancer center in the USA. Patients Pediatric patients (<25 years of age) receiving conventional therapy for cancer admitted to the ICU with suspected sepsis between 2013 and 2019. Results Of 207 included episodes of suspected sepsis, attributable mortality was 16 (7.7%) and all evaluated sepsis scores performed poorly (maximal AUROC of 0.73 for qSOFA at 1 and 24 h). Sensitivity analyses did not identify an alternative approach that significantly improved prediction. Conclusions Currently available sepsis scores perform poorly for prediction of attributable mortality in children with cancer who present to ICU with suspected sepsis. More research is needed to identify reliable predictors of adverse outcomes in this population

    Comparative study on the level of knowledge between licensed medical professionals working in public and private hospitals in Cavite regarding the Unang Yakap program of the Department of Health

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    This study specifically determined the level of knowledge of medical professionals (Obstetrician and Gynecologists, Pediatricians, nurses and midwives) both in private and public hospitals in Cavite regarding the Unang Yakap program of the Department of Health; compared the differences in the private and public hospitals knowledge of the Unang Yakap and identified the medical professionals source of knowledge about the said program using analytic – observational research. The study population included all medical professionals working in the private and public hospitals in Cavite. A total of 82 (32.8%) licensed medical professionals, where 34 (33.7)% individuals came from public hospitals and 48 (32.2%) came private sector have knowledge with regards to Unang Yakap . Simple random sampling was used to identify the respondents. A self-administered questionnaire was used as tool and data was analysed using standard deviation, frequency, percentage, and chi-square. There was no insufficient evidence to reject the claim that there is no difference in the level of knowledge of licensed medical professionals working in both public and private hospitals in Cavite. Variables including age, gender, profession and years of experience were significant determinants in having knowledge or not having knowledge in Unang Yakap

    Effects of alirocumab on types of myocardial infarction: insights from the ODYSSEY OUTCOMES trial

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    Effect of Alirocumab on Lipoprotein(a) and Cardiovascular Risk After Acute Coronary Syndrome

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