Mortality predictors in an acute care geriatric unit in Singapore

Aim: Admission to an acute care geriatric unit may lead to adverse outcomes. It is therefore important to identify high-risk patients early so that appropriate management can be instituted to prevent or delay onset of adverse events. The aim of this study is to evaluate one-year mortality and its associated risk factors among hospitalized patients. Methods: This is a retrospective cohort study on consecutive patients admitted to an acute geriatric ward in a Singapore hospital from March to April 2013.Demographic and clinical information was collected from patient medical records. Linkage with death records from a national registry was performed. Results: Of the 196 patients assessed, 4.6%, 20.9% and 35.7% died during admission, within six months post-admission and within one year post-admission respectively. Pneumonia and cardiovascular diseases accounted for most of the death cases. In the multivariable logistic regression adjusted by age and gender, abbreviated mental test (AMT) score, admission for falls and depression were found to be significantly associated with death within one year post-admission. In the analysis stratified by gender, AMT score and depression were found to be significantly associated with death in males whereas AMT score and admission for falls were significantly associated with death in females. Conclusions: This study offers significant insight into mortality trends and risk factors for clinicians, hence guiding them in individualizing their management plan for acutely ill geriatric patients. Predicting long-term prognosis will enhance rehabilitation goal-setting and advance care-planning

IDentif.AI: Rapidly optimizing combination therapy design against severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2) with digital drug development

Bioengineering & Translational Medicine6

IDentif.AI: Rapidly optimizing combination therapy design against severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2) with digital drug development

10.1002/btm2.10196Bioengineering and Translational Medicine61e1019

The IDentif.AI-x pandemic readiness platform: Rapid prioritization of optimized COVID-19 combination therapy regimens.

10.1038/s41746-022-00627-4NPJ Digit Med5183

A Circulating miRNA Signature for Stratification of Breast Lesions among Women with Abnormal Screening Mammograms

Although mammography is the gold standard for breast cancer screening, the high rates of false-positive mammograms remain a concern. Thus, there is an unmet clinical need for a non-invasive and reliable test to differentiate between malignant and benign breast lesions in order to avoid subjecting patients with abnormal mammograms to unnecessary follow-up diagnostic procedures. Serum samples from 116 malignant breast lesions and 64 benign breast lesions were comprehensively profiled for 2,083 microRNAs (miRNAs) using next-generation sequencing. Of the 180 samples profiled, three outliers were removed based on the principal component analysis (PCA), and the remaining samples were divided into training (n = 125) and test (n = 52) sets at a 70:30 ratio for further analysis. In the training set, significantly differentially expressed miRNAs (adjusted p < 0.01) were identified after correcting for multiple testing using a false discovery rate. Subsequently, a predictive classification model using an eight-miRNA signature and a Bayesian logistic regression algorithm was developed. Based on the receiver operating characteristic (ROC) curve analysis in the test set, the model could achieve an area under the curve (AUC) of 0.9542. Together, this study demonstrates the potential use of circulating miRNAs as an adjunct test to stratify breast lesions in patients with abnormal screening mammograms

Development of a microRNA Panel for Classification of Abnormal Mammograms for Breast Cancer

10.3390/cancers13092130CANCERS13