tween nitrate and head circumference or LBW. Future studies in other populations and with data on dietary sources of nitrate are encouraged to confirm or refute these findings. https//doi.org/10.1289/EHP7331.The US response to coronavirus disease 2019 (COVID-19) has been plagued with politics driving public health and messaging. As a result, COVID-19 vaccine rollout is occurring in an environment ill equipped to achieve broad acceptance of the vaccine. Addressing public concerns unlocks the potential for high vaccine coverage; this is best achieved when science and values, not politics, inform public health. A multifaceted and thorough engagement and communication plan that is responsive to the concerns and values of different groups must be swiftly yet carefully implemented in a coordinated manner by federal, state, and local governments. Effective communication will require rapid and rigorous science to promptly differentiate between adverse events following immunization that are causally related versus simply coincidental. Health care providers, in particular, will need support to process the otherwise potentially overwhelming amount of relevant information and effectively integrate it into discussions with their patients to support their decision making. An equitable COVID-19 immunization program could substantively reduce the disproportionate risks associated with this pandemic.
Thirty-day unplanned readmission is one of the key components in measuring quality in patient care. Risk of readmission in oncology patients may be associated with a wide variety of specific factors including laboratory results and diagnoses, and it is hard to include all such features using traditional approaches such as one-hot encoding in predictive models.
We used clinical embeddings to represent complex medical concepts in lower dimensional spaces. For predictive modeling, we used gradient-boosted trees and adopted the shapley additive explanation framework to offer consistent individualized predictions. We used retrospective inpatient data between 2013 and 2018 with temporal split for training and testing.
Our best performing model predicting readmission at discharge using clinical embeddings showed a testing area under receiver operating characteristic curve of 0.78 (95% CI, 0.77 to 0.80). Use of clinical embeddings led to up to 23.1% gain in area under precision-recall curve and 6% in area under receiver operating characteristic curve. Hematology models had more performance gain over surgery and medical oncology. Our study was the first to develop (1) explainable predictive models for the hematology population and (2) dynamic models to keep track of readmission risk throughout the duration of patient visit.
To our knowledge, our study was the first to develop (1) explainable predictive models for the hematology population and (2) dynamic models to keep track of readmission risk throughout the duration of patient visit.
To our knowledge, our study was the first to develop (1) explainable predictive models for the hematology population and (2) dynamic models to keep track of readmission risk throughout the duration of patient visit.
As health inequities during the pandemic have been magnified, we evaluated how use of SARS-CoV-2 testing differed by race or ethnicity in a large cohort of breast cancer survivors and examined the correlates of testing positive.
We conducted a retrospective cohort study of 22,481 adult breast cancer survivors who were active members of a large California integrated healthcare plan in 2020. We collected data on their breast cancer diagnosis, comorbidity, and demographic characteristics. We examined SARS-CoV-2 testing utilization between March 2020 and September 2020 by race or ethnicity, comorbidity, and other patient characteristics. We also examined the correlates of a having a positive SARS-CoV-2 test result. We conducted bivariable and multivariable logistic regression to identify correlates of testing utilization and test positivity.
Of these 22,481 women, 3,288 (14.6%) underwent SARS-CoV-2 testing. The cohort included 51.8% women of color. https://www.selleckchem.com/products/Vorinostat-saha.html Of the 3,288 tested, 264 (8.0%) women had a positive test rted healthcare system, Asian or Pacific Islander patients were less likely to undergo SARS-CoV-2 testing than White survivors, but more likely to test positive. Additionally, Latinx ethnicity and high body mass index were strongly correlated with a greater odds of SARS-CoV-2 test positivity.
In 2016, there were 1,308,061 cases of cancer being treated in Indonesia, with 2.2 trillion rupiahs spent, amounting to $486,960,633 in US dollars (purchasing power parity 2016). The high burden of cancers in Indonesia requires a valid data collection to inform future cancer-related policies. The purpose of this study is to report cancer epidemiological data from 2008 to 2012 based on Hospital-Based Cancer Registry (HBCR) data from Cipto Mangunkusumo Hospital, Indonesia.
This was a descriptive study with cross-sectional design. Data were collected from Cipto Mangunkusumo Hospital HBCR 2008-2012. Demographical, diagnostic, stages of cancer, and histopathological types of cancer data were extracted.
After screening, 18,216 cases were included. A total of 12,438 patients were older than 39 years of age (68.3%), with a female-to-male ratio of 95. Most patients have cancers at advanced stages (stages III and IV, 10.2%). The most common sites of cancer were cervix uteri (2,878 cases, 15.8%), breast (2,459 castality and Prevalence 2018, which portrayed that Indonesia has been severely afflicted by cervical cancer cases more than any other Association of Southeast Asian Nations countries. The HBCR could serve as a robust database of epidemiological data for cancer cases in Indonesia.Event-based prospective memory (PM) tasks require individuals to remember to perform a previously planned action when they encounter a specific event. Often, the natural environments in which PM tasks occur are embedded are constantly changing, requiring humans to adapt by learning. We examine one such adaptation by integrating PM target learning with the prospective memory decision control (PMDC) cognitive model. We apply this augmented model to an experiment that manipulated exposure to PM targets, comparing a single-target PM condition where the target was well learned from the outset, to a multiple-target PM condition with less initial PM target exposure, allowing us to examine the effect of continued target learning opportunities. Single-target PM accuracy was near ceiling whereas multiple-target PM accuracy was initially poorer but improved throughout the course of the experiment. PM response times were longer for the multiple- compared with single-target PM task but this difference also decreased over time.