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Introduction Transcatheter mitral valve repair (TMVr) has shown to reduce heart failure (HF) rehospitalization and all cause mortality. However, the 30-day all-cause readmission remains high (∼15%) after TMVr. Therefore, we sought to develop and validate a 30-day readmission risk calculator for TMVr. Methods Nationwide Readmission Database from January 2014 to December 2017 was utilized. A linear calculator was developed to determine the probability for 30-day readmission. Internal calibration with bootstrapped calculations were conducted to assess model accuracy. The root mean square error and mean absolute error were calculated to determine model performance. Results Of 8,339 patients who underwent TMVr, 1,246 (14.2%) were readmitted within 30 days. The final 30-day readmission risk prediction tool included the following variables: Heart failure, Atrial Fibrillation, Anemia, length of stay ≥4 days, Acute kidney injury (AKI), and Non-Home discharge, Non-Elective admission and Bleeding/Transfusion. The c-statistic of the prediction model was 0.63. The validation c-statistic for readmission risk tool was 0.628. On internal calibration, our tool was extremely accurate in predicting readmissions up to 20%. Conclusion A simple and easy to use risk prediction tool identifies TMVr patients at increased risk of 30-day readmissions. The tool can guide in optimal discharge planning and reduce resource utilization.

Objective: To present an overview of import need for wound care and burn dressings in India. This article provides a complete analysis of the import-export value of wound care and burn dressings in India. It helps in preparing growth strategies, knowledge about leading players, recent developments, business strategies, and manufacturing status of the wound care and burn dressings in India. Methodology: A trend analysis of import-export was carried out for wound and burn dressings in India. Raw data of the years (2008-2017) were collected from various market research analysis sites and import need was identified. Results and Discussion: The detailed analysis reveals that India is a growing market for wound and burn dressings and spends a lot of the exchequer on importing the subject commodity. Wound dressing export is averaged to the same from 2013 to 2017. India saw a rise in wound dressing export after 2012. India saw a rise of wound dressing import over the past 10 years. It averaged 502.6 million from 2008 to 2017 and it reached its all-time high of 765 million in 2016. The import value was found quite high as compared to export. Conclusion: The report of import and export analysis very clearly highlights that there is a strong demand for dressings in the country and due to lack of own manufacturers of such dressing in India, these are imported. Since these products are expensive, there is a large outflow of Indian currency due to imports. It is imperative that such products get government attention and should be manufactured within the country.

We present DeepMVI, a deep learning method for missing value imputation in multidimensional time-series datasets. Missing values are commonplace in decision support platforms that aggregate data over long time stretches from disparate sources, and reliable data analytics calls for careful handling of missing data. One strategy is imputing the missing values, and a wide variety of algorithms exist spanning simple interpolation, matrix factorization methods like SVD, statistical models like Kalman filters, and recent deep learning methods. We show that often these provide worse results on aggregate analytics compared to just excluding the missing data. DeepMVI uses a neural network to combine fine-grained and coarse-grained patterns along a time series, and trends from related series across categorical dimensions. After failing with off-the-shelf neural architectures, we design our own network that includes a temporal transformer with a novel convolutional window feature, and kernel regression with learned embeddings. The parameters and their training are designed carefully to generalize across different placements of missing blocks and data characteristics. Experiments across nine real datasets, four different missing scenarios, comparing seven existing methods show that DeepMVI is significantly more accurate, reducing error by more than 50% in more than half the cases, compared to the best existing method. Although slower than simpler matrix factorization methods, we justify the increased time overheads by showing that DeepMVI is the only option that provided overall more accurate analytics than dropping missing values., Comment: Accepted to VLDB 2021

Objective: The objective of the study was to present an overview of regulatory requirements for wound and burn care dressings.Methods: A total of 80 research and review articles including regulatory guidelines to control the marketing of wound and burn care dressings recommended by international regulatory agencies were reviewed.Results: A wide range of dressings, as a new target of the healing process, have been developed due to continued growth and innovations in the field. Ideal dressings should be safe and achieve healing at a reasonable cost with minimum inconvenience to patients. It is mandatory that manufacture and sale of such dressings are approved by the relevant health authority of each country. This article provides manufacturers with an overview regarding regulatory approval procedures for marketing such dressings in different countries and addresses the gaps and challenges in the existing guidelines aimed at maintaining product quality. It provides a comparative analysis of the differences in regulatory requirements and highlights that ongoing discussions and appropriate actions are required to support the continuous development of these dressings. Most countries have their own regulatory guidelines, and the approval processes differ according to the country. Quality parameters concerning the type of material, pore size, sterilization methods, shape and size, and labeling are not discussed in guidelines; therefore, innovators and manufacturers are facing tough challenges to showcase their products in the market, and this further leads to either lack of market availability or high cost of such dressings.Conclusion: Development of common quality guidelines is essential for market availability of low-cost, high-quality dressings.

The blood-brain barrier (BBB) presents a combination of physical and electrostatic barriers. It is a highly complex structure that tightly regulates the movement of molecules from the blood to brain, protecting it from injuries and diseases. However, the BBB also significantly precludes the delivery of drugs to the brain, thus, preventing the therapy of a number of neurological disorders like brain cancer, epilepsy, Alzheimer’s disease, schizophrenia etc. Numerous drug delivery strategies have been developed to circumvent this barrier. Out of those, one popular approach is the use of nanoparticles. Nanoparticles form solid, colloidal drug delivery system that consists of macromolecular materials in which the active principle is dissolved, entrapped or encapsulated or onto which the active principle is adsorbed or attached. Brain targeted polymeric nanoparticles have been found to increase the therapeutic efficacy and reduce the toxicity for a large number of drugs. By coating the nanoparticles with surfactants, higher concentrations of the drugs can be delivered. The article presents various approaches used in design and delivery of nanoparticles to brain. It also reviews various patents that describe the use of nanoparticles to deliver various neurotherapeutics to brain.

Laboratory dialysis, one of the most widely used techniques in biological research is truly a ' gateway technology' . The analogy is to that of a ' gate' of a building through which everybody has to pass, even though they may wish to go to different departments. Similarly, researchers may be working in altogether different areas but all may need to use laboratory dialysis at one stage or the other during the course of their research. Biochemists may use it to purify enzymes, an immunologist may use it to purify monoclonal antibodies from culture supernatants, a chemist may use it as a step in the crystallography process or for purification of ionic liquids, a biotechnologist may use it to study the effectiveness of enzyme immobilization and a drug discovery scientist may use it for determining drug-protein interaction. The present article reviews patents in the field of laboratory dialysis from inception till date, focusing on the various developmental and innovation related milestones during evolution of the technique. It captures the full panorama of a very interesting technique which continues to be as relevant today as it was in 1866 when the term ' dialysis' was first coined.

The brain is one of the least accessible organs of the body, thus making the delivery of neurotherapeutics almost a challenge. Despite its relatively high nutrient support and exchange requirements, the uptake of any compound is strictly regulated by the blood brain barrier (BBB). As a consequence, BBB prevents effective treatment of many severe and life threatening diseases like brain cancer, epilepsy, Alzheimer's disease, schizophrenia etc. Numerous drug delivery strategies have been developed to circumvent this barrier. One such approach is the use of nanoparticles. Nanoparticles form solid, colloidal drug delivery system that consists of macromolecular materials in which the active principle is dissolved, entrapped or encapsulated or onto which the active principle is adsorbed or attached. Brain targeted polymeric nanoparticles have been found to increase the therapeutic efficacy and reduce the toxicity for a large number of drugs. By coating the nanoparticles with surfactants, higher concentrations of drugs can be delivered to the brain. The article presents various approaches used in design and delivery of nanoparticles to brain. It also reviews various patents that describe the use of nanoparticles to deliver various neurotherapeutics and neurodiagnostics to brain.