Development of a new detection algorithm to identify acute coronary syndrome using electrochemical biosensors for real-world long-term monitoring

Electrochemically based technologies are rapidly moving from the laboratory to bedside applications and wearable devices, like in the field of cardiovascular disease. Major efforts have focused on the biosensor component in contrast with those employed in creating more suitable detection algorithms for long-term real-world monitoring solutions. The calibration curve procedure presents major limitations in this context. The objective is to propose a new algorithm, compliant with current clinical guidelines, which can overcome these limitations and contribute to the development of trustworthy wearable or telemonitoring solutions for home-based care. A total of 123 samples of phosphate buffer solution were spiked with different concentrations of troponin, the gold standard method for the diagnosis of the acute coronary syndrome. These were classified as normal or abnormal according to established clinical cut-off values. Off-the-shelf screen-printed electrochemical sensors and cyclic voltammetry measurements (sweep between −1 and 1 V in a 5 mV step) was performed to characterize the changes on the surface of the biosensor and to measure the concentration of troponin in each sample. A logistic regression model was developed to accurately classify these samples as normal or abnormal. The model presents high predictive performance according to specificity (94%), sensitivity (92%), precision (92%), recall (92%), negative predictive value (94%) and F-score (92%). The area under the curve of the precision-recall curve is 97% and the positive and negative likelihood ratios are 16.38 and 0.082, respectively. Moreover, high discriminative power is observed from the discriminate odd ratio (201) and the Youden index (0.866) values. The promising performance of the proposed algorithm suggests its capability to overcome the limitations of the calibration curve procedure and therefore its suitability for the development of trustworthy home-based care solutions

A review of biophysiological and biochemical indicators of stress for connected and preventive healthcare

Stress is a known contributor to several life-threatening medical conditions and a risk factor for triggering acute cardiovascular events, as well as a root cause of several social problems. The burden of stress is increasing globally and, with that, is the interest in developing effective stress-monitoring solutions for preventive and connected health, particularly with the help of wearable sensing technologies. The recent development of miniaturized and flexible biosensors has enabled the development of connected wearable solutions to monitor stress and intervene in time to prevent the progression of stress-induced medical conditions. This paper presents a review of the literature on different physiological and chemical indicators of stress, which are commonly used for quantitative assessment of stress, and the associated sensing technologies

Detection of non-ST-elevation myocardial infarction and unstable angina in the acute setting: meta-analysis of diagnostic performance of multi-detector computed tomographic angiography

<p>Abstract</p> <p>Background</p> <p>Multi-detector computed tomography angiography (MDCTA) has been increasingly used in the evaluation of the coronary arteries. The purpose of this study was to review the literature on the diagnostic performance of MDCTA in the acute setting, for the detection of non-ST-elevation myocardial infarction (NSTEMI) and unstable angina pectoris (UAP).</p> <p>Methods</p> <p>A Pubmed and manual search of the literature published between January 2000 and June 2007 was performed. Studies were included that compared MDCTA with clinical outcome and/or CA in patients with acute chest pain, presenting at the emergency department. More specifically, studies that only included patients with initially negative cardiac enzymes suspected of having NSTEMI or UAP were included. Summary estimates of diagnostic odds ratio (DOR), sensitivity and specificity, negative (NLR) and positive likelihood ratio (PLR) were calculated on a patient basis. Random-effects models and summary receiver operating curve (SROC) analysis were used to assess the diagnostic performance of MDCTA with 4 detectors or more. The proportion of non assessable scans (NAP) on MDCTA was also evaluated. In addition, the influence of study characteristics of each study on diagnostic performance and NAP was investigated with multivariable logistic regression.</p> <p>Results</p> <p>Nine studies totalling 566 patients, were included in the meta-analysis: one randomised trial and eight prospective cohort studies. Five studies on 64-detector MDCTA and 4 studies on MDCTA with less than 64 detectors were included (32 detectors n = 1, 16 detectors n = 2, 16 and 4 detectors n = 1). Pooled DOR was 131.81 (95%CI, 50.90–341.31). The pooled sensitivity and specificity were 0.95 (95%CI, 0.90–0.98) and 0.90 (95%CI, 0.87–0.93). The pooled NLR and PLR were 0.12 (95%CI, 0.06–0.21) and 8,60 (95%CI, 5.03–14,69).</p> <p>The results of the logistic regressions showed that none of the investigated variables had influence on the diagnostic performance or NAP</p> <p>Conclusion</p> <p>MDCTA of the coronary arteries performs good to excellent in the diagnosis of coronary artery disease in the acute setting and it can be used for early exclusion of NSTEMI or UAP in patients in the emergency department.</p

Early angiography after myocardial infarction: what have we learned?

-