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Aims Readmission after hospitalization for acute decompensated heart failure (HF) remains a major public health problem. Use of remote dielectric sensing (ReDS) to measure lung water volume allows for an objective assessment of volume status and may guide medical optimization for HF. We hypothesized that the use of ReDS would lower 30 day readmission in patients referred to rapid follow‐up (RFU) clinic after HF discharge. Methods and results We conducted a retrospective analysis of the use of ReDS for patients scheduled for RFU within 10 days post‐discharge for HF at Mount Sinai Hospital between 1 July 2017 and 31 July 2018. Diuretics were adjusted using a pre‐specified algorithm. The association between use of ReDS and 30 day readmission was evaluated. A total of 220 patients were included. Mean age was 62.9 ± 14.7 years, and 36.4% were female. ReDS was performed in 80 (36.4%) and led to medication adjustment in 52 (65%). Use of ReDS was associated with a lower rate of 30 day cardiovascular readmission [2.6% vs. 11.8%, hazard ratio (HR): 0.21; 95% confidence interval (CI): 0.05–0.89; P = 0.04] and a trend towards lower all‐cause readmission (6.5% vs. 14.1%, HR: 0.43; 95% CI: 0.16–1.15; P = 0.09) as compared with patients without a ReDS assessment. Conclusions ReDS‐guided HF therapy during RFU after HF hospitalization may be associated with lower risk of 30 day readmission.

Background Delirium is a common neuropsychiatric disorder associated with prolonged hospital stays, and increased morbidity and mortality. Diagnosis is frequently missed due to varying disease presentation and lack of standardized testing. We examined biomarkers as diagnostic or prognostic indicators of delirium, and provide a rational basis for future studies. Method Systematic review of literature published between Jan 2000 and June 2019. Searches included: PubMed; Web of Science; CINAHL; EMBASE; COCHRANE and Medline. Additional studies were identified by searching bibliographies of eligible articles. Results 2082 relevant papers were identified from all sources. Seventy-three met the inclusion criteria, all of which were observational. These assessed a range of fourteen biomarkers. All papers included were in the English language. Assessment methods varied between studies, including: DSM criteria; Confusion Assessment Method (CAM) or CAM-Intensive Care Unit (ICU). Delirium severity was measured using the Delirium Rating Scale (DRS). Delirium was secondary to post-operative dysfunction or acute medical conditions. Conclusion Evidence does not currently support the use of any one biomarker. However, certain markers were associated with promising results and may warrant evaluation in future studies. Heterogeneity across study methods may have contributed to inconclusive results, and more clarity may arise from standardization of methods of clinical assessment. Adjusting for comorbidities may improve understanding of the pathophysiology of delirium, in particular the role of confounders such as inflammation, cognitive disorders and surgical trauma. Future research may also benefit from inclusion of other diagnostic modalities such as EEG as well as analysis of genetic or epigenetic factors.