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

Caught in the act - Migration of a large right atrial thrombus to pulmonary artery during transthoracic echocardiography - A case report

In cases of pulmonary embolism, the visualization of a free-floating right heart thrombus on conventional transthoracic echocardiography is extremely rare. Even rarer is an echocardiographic recording of migration of a free-floating clot from the right heart into the pulmonary vasculature leading to pulmonary embolism. We present a unique case of an elderly man who presented with dyspnoea, in whom a routine 2-D bed side transthoracic echo recorded the live transit of a free floating thrombus from the right heart into the pulmonary artery resulting in pulmonary embolism. The patient remained haemodynamically stable and was managed with anticoagulation. Our case objectively highlights the rare occurrence of free floating right heart thrombi and their association with pulmonary embolism and also focuses on the options of management of such thrombi

Cough, Hemoptysis and Hair Expectoration: An Intrapulmonary Teratoma

Teratomas can be found in different organs of the body and may involve gonads, saccrococcygeal region, mediastinum and other sites. Intrathoracic teratomas always occur in mediastinum and less often arise within the lung. As teratomas mostly involve sex organs (gonads), they rarely occur as extra-gonadal tumors accounting for only 3% of all the cases and very small percentage of such tumors occur in mediastinum.We reported an interesting case of middle aged male who presented to us with symptoms of cough, hemoptysis and trichoptysis (hair expectoration).We found that patient had intrapulmonary teratoma that was initially being treated as case of pulmonary tuberculosis. He underwent surgical resection of his cavitatory lesion and diagnosis of intrapulmonary teratoma was confirmed by histopathology as well. The patient made remarkable recovery with complete disappearance of his symptoms. From Pakistan no such case has ever been reported. Although it is very unusual but in patient with cavitatory lesion, intrapulmonary teratoma should always be kept in mind as differential diagnosis

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

Spectrum of interstitial lung disease from a tertiary care hospital in Karachi

Objective: To determine the clinical features and patterns of interstitial lung disease.Methods: This retrospective study was conducted at the Aga Khan University Hospital, Karachi, and comprised record of patients diagnosed with interstitial lung disease from January 2005 to December 2015. All patients aged 16 years and above diagnosed with interstitial lung disease on the basis of clinical features, radiological features on high-resolution computed tomography of the chest, and lung biopsies were included. SPSS 19 was used for data analysis.Results: Of the 537 patients, 324(60.3%) of the participants were females. The overall mean age was 60.5±14.9 years. The most common co-morbid condition was diabetes mellitus in 72(13.4%) patients, followed by hypertension in 48(8.9%) and ischaemic heart disease in 21(3.9%). The most common interstitial lung disease was idiopathic pulmonary fibrosis in 217(40.4%) patients, followed by non-specific interstitial pneumonia in 106(19.7%), sarcoidosis in 82(15.3%) and connective tissue disease-related interstitial lung disease in 56(10.4%) patients.Conclusions: Idiopathic pulmonary fibrosis was found to be the most common interstitial lung disease subtype followed by non-specific interstitial pneumonia, sarcoidosis and connective tissue disease-related-interstitial lung disease

Towards Integration of Artificial Intelligence into Medical Devices as a Real-Time Recommender System for Personalised Healthcare:State-of-the-Art and Future Prospects

In the era of big data, artificial intelligence (AI) algorithms have the potential to revolutionize healthcare by improving patient outcomes and reducing healthcare costs. AI algorithms have frequently been used in health care for predictive modelling, image analysis and drug discovery. Moreover, as a recommender system, these algorithms have shown promising impacts on personalized healthcare provision. A recommender system learns the behaviour of the user and predicts their current preferences (recommends) based on their previous preferences. Implementing AI as a recommender system improves this prediction accuracy and solves cold start and data sparsity problems. However, most of the methods and algorithms are tested in a simulated setting which cannot recapitulate the influencing factors of the real world. This review article systematically reviews prevailing methodologies in recommender systems and discusses the AI algorithms as recommender systems specifically in the field of healthcare. It also provides discussion around the most cutting-edge academic and practical contributions present in the literature, identifies performance evaluation matrices, challenges in the implementation of AI as a recommender system, and acceptance of AI-based recommender systems by clinicians. The findings of this article direct researchers and professionals to comprehend currently developed recommender systems and the future of medical devices integrated with real-time recommender systems for personalized healthcare