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PerClot® is safe, effective in reducing the postoperative bleeding and would appear to be useful in head and neck surgery with minimal adverse effects.
Geriatric Nutritional Risk Index (GNRI) is a promising tool for predicting nutrition-related complications. This meta-analysis sought to determine the prognostic utility of GNRI in elderly patients with heart failure.
We comprehensively searched the PubMed and Embase databases from their inception to July 2019. Original studies investigating the prognostic value of GNRI in patients with heart failure were included. Outcome of interests were all-cause mortality and major cardiovascular events. The prognostic value of GNRI was expressed as risk ratios (RR) with 95% confidence intervals (CI) for the lowest versus the highest GNRI category or continuous GNRI analysis.
Eleven articles (10 studies) involving 10,589 elderly heart failure patients were included. Meta-analysis indicated that heart failure patients with the lowest GNRI had an increased risk of all-cause mortality (RR 2.11; 95% CI 1.72-2.58) and major cardiovascular events (RR 2.00; 95% CI 1.24-3.22) after adjustment for confounding. Levofloxacin nmr In addition, each unit reduction in GNRI significantly increased 6% risk of all-cause mortality.
Lower GNRI independently predicts all-cause mortality and major cardiovascular events in elderly patients with heart failure. Determination of nutritional status using GNRI may improve risk stratification in elderly patients with heart failure.
Lower GNRI independently predicts all-cause mortality and major cardiovascular events in elderly patients with heart failure. Determination of nutritional status using GNRI may improve risk stratification in elderly patients with heart failure.
To reveal that a computed tomography surveillance program (CT-surveillance) could demonstrate the epidemiologic features of COVID-19 infection and simultaneously investigate the type and frequency of CT findings using clinical CT data.
We targeted individuals with possible CT findings of viral pneumonia. Using an online questionnaire, we asked Japanese board-certified radiologists to register their patients' information including patient age and sex, the CT examination date, the results of PCR test for COVID-19 infection, CT findings, and the postal code of the medical institution that performed the CT. We compared the diurnal patient number and the cumulative regional distribution map of registrations in CT-surveillance to those of the PCR-positive patient surveillance (PCR-surveillance).
A total of 637 patients was registered from January 1 to April 17, 2020 for CT-surveillance. Their PCR test results were positive (n = 62.5-398%), negative (n = 8.9-57%), unknown (n = 26.2-167%), and other disease (n = 2.4-15%). An age peak at 60-69years and male dominance were observed in CT-surveillance. The most common CT finding was bilaterally distributed ground-glass opacities. The diurnal number and the cumulative regional distribution map by CT-surveillance showed tendencies that were similar to those revealed by PCR-surveillance.
Using clinical CT data, CT-surveillance program delineated the epidemiologic features of COVID-19 infection.
Using clinical CT data, CT-surveillance program delineated the epidemiologic features of COVID-19 infection.Because science is a modeling enterprise, a key question for educators is What kind of repertoire can initiate students into the practice of generating, revising, and critiquing models of the natural world? Based on our 20 years of work with teachers and students, we nominate variability as a set of connected key ideas that bridge mathematics and science and are fundamental for equipping youngsters for the posing and pursuit of questions about science. Accordingly, we describe a sequence for helping young students begin to reason productively about variability. Students first participate in random processes, such as repeated measure of a person's outstretched arms, that generate variable outcomes. Importantly, these processes have readily discernable sources of variability, so that relations between alterations in processes and changes in the collection of outcomes can be easily established and interpreted by young students. Following these initial steps, students invent and critique ways of visualizing and measuring distributions of the outcomes of these processes. Visualization and measure of variability are then employed as conceptual supports for modeling chance variation in components of the processes. Ultimately, students reimagine samples and inference in ways that support reasoning about variability in natural systems.
Tyrosine kinase inhibitors (TKI) treatment has transformed chronic myeloid leukemia (CML) from a fatal neoplasm to a chronic disease with normal life expectancies. Indeed, half of CML patients are able to discontinue TKI without relapse. However, it seems clearly demonstrated that exposure to TKI may result in fetal malformations. Regarding its effects on fertility, preclinical studies and clinical case reports provide inconclusive evidence. Furthermore, due to the risk of CML relapse after TKI discontinuation, the optimal time to stop TKI represents a real dilemma.
We describe a 23-year-old woman who, after more than 6 years with imatinib and 1 year in deep molecular response [(DMR), MR ≥ 4], interrupted treatment to become pregnant. After 2 failed artificial insemination cycles, she underwent one process of controlled ovarian stimulation, achieving 2 blastocyst-embryos. In the meantime, BCR-ABL1
levels increased despite interferon-alpha therapy, she lost the mayor molecular response (MMR), and the 2 embryos had to be cryopreserved. A stable second MR ≥ 4.0 was again obtained with nilotinib, and after stopping it, the 2 blastocyst-embryo transfers were unsuccessfully performed. Under DMR, a second ovarian stimulation and in vitro fertilization (IVF) was performed and 1 blastocyst embryo was transferred. This time, she became pregnant and a healthy baby was born. After more than 3 years of follow-up, she remains in treatment-free remission (TFR).
Compared with imatinib, nilotinib achieves earlier and deeper MR that allows safe and timely pregnancies in infertile CML women through IVF process, while patients remain in TFR after delivery.
Compared with imatinib, nilotinib achieves earlier and deeper MR that allows safe and timely pregnancies in infertile CML women through IVF process, while patients remain in TFR after delivery.
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