A Mathematical Model of a Thermoelectric Device for the Treatment of Whitlow by Local Hypothermia

Biomedical Engineering - A mathematical model of a thermoelectric device for the treatment of whitlow by local hypothermia is discussed. The model is based on a solution of the heat conduction task...     

RNA sequencing steps toward the first line

• DNA is the sequence that codes for proteins.
• Messenger RNA is transcribed from the DNA sequence of genes and translated into protein.
• It can be difficult to predict how a change in the DNA sequence will affect messenger RNA and protein quantity and quality.
• DNA translocation changes can cause the joining of sequences from two different genes or different parts of the same gene.
• DNA sequencing is often used clinically to predict how DNA changes might affect proteins.
• Alternatively, RNA sequencing can be used as a more direct measure of the effect of DNA changes on the protein products.
• This sequencing is important for identifying changes in cancer that may indicate response to targeted therapy, prognosis, or diagnosis.

     

Das prozessierte EEG zur personalisierten Dosierung von Anästhetika während Allgemeinanästhesie

Die Anaesthesiologie - Die Elektroenzephalogramm(EEG)-gesteuerte Anästhesie ist aus modernen Operationssälen nicht mehr wegzudenken und hat sich als Standard-Monitoring etabliert. Viele...     

Prediction of early (4-week) mortality in acute myeloid leukemia with intensive chemotherapy

The progress with intensive chemotherapy and supportive care measures has improved survival in patients with newly diagnosed acute myeloid leukemia (AML). Given the recent development of effective low intensity therapies, an optimal decision on the therapy intensity may improve survival through the avoidance of early mortality. We reviewed the outcome of 3728 patients with newly diagnosed AML who received intensive chemotherapy between August 1980 and May 2020. Intensive chemotherapy was defined as a cumulative cytarabine dose ≥ 700 mg/m² during induction therapy. We divided the whole cohort into a training and validation group at a 3:1 ratio. The population was divided into a training (2790 patients) and a validation cohort (938 patients). The median age was 55 years (range, 15-99). Among them, 442 patients (12%) had core-binding factor AML. Binary logistic regression identified older age, worse performance status, hyperbilirubinemia, elevated creatinine, hyperuricemia, cytogenetic abnormalities other than CBF and -Y, and pneumonia as adverse prognostic factors for an early 4-week mortality. This risk classification for early mortality was verified in the validation cohort of patients. In the validation cohort of more recently treated patients from 2000 to 2017, the 4-week mortality rates with intensive chemotherapy were 2%, 14%, and 50% in the low-, high-, and very high-risk group, respectively. The mortality rates with low intensity therapies were 3%, 9%, and 20%, respectively. The risk classification guides treatment intensity by the assessment of age, frailty, organ dysfunction, cytogenetic abnormality, and infection to avoid early mortality.     

The social vulnerability metric (SVM) as a new tool for public health

Objective

To derive and validate a new ecological measure of the social determinants of health (SDoH), calculable at the zip code or county level.

Data Sources and Study Setting

The most recent releases of secondary, publicly available data were collected from national U.S. health agencies as well as state and city public health departments.

Study Design

The Social Vulnerability Metric (SVM) was constructed from U.S. zip-code level measures (2018) from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality (2016), COVID-19 vaccination (2021), and emergency department visits for asthma (2018). The SVM was also compared with the existing Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to determine convergent validity and differential predictive validity.

Data Collection/Extraction Methods

The data were collected directly from published files available to the public online from national U.S. health agencies as well as state and city public health departments.

Principal Findings

The correlation between SVM scores and national age-adjusted county all-cause mortality was r = 0.68. This correlation demonstrated the SVM's robust validity and outperformed the SVI with an almost four-fold increase in explained variance (46% vs. 12%). The SVM was also highly correlated (r ≥ 0.60) to zip-code level health outcomes for the state of California and city of Chicago.

Conclusions

The SVM offers a measurement tool improving upon the performance of existing SDoH composite measures and has broad applicability to public health that may help in directing future policies and interventions. The SVM provides a single measure of SDoH that better quantifies associations with health outcomes.