The value of a novel model of remote monitoring alert classification of cardiac implantable devices

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
F Mendez Zurita ◽  
M Grande Osorio ◽  
C Gonzalez Matos ◽  
E Rodriguez Font ◽  
J Guerra Ramos ◽  
...  
Keyword(s):  
Remote Monitoring ◽  
Clinical Information ◽  
Implantable Devices ◽  
Classification Model ◽  
Healthcare Team ◽  
Clinical Criteria ◽  
Center Care ◽  
Initial Classification

Abstract Introduction Remote monitoring (RM) is commonly used in the follow-up of patients with cardiac implantable devices (CID). However, there are a significant amount of automatic alerts of low clinical relevance. An alert classification model designed to optimize the management of RM alert in CID receivers can improve the analysis. Purpose Assess the effectiveness of a local protocol for review and classification of MR alerts. Methods Retrospective study, single center. We included all patients with ICD +/− CRT in the RM program between september 2016 and december 2019. All transmission received were analyzed. The priority of the transmissions was established based on clinical criteria and device parameters, classified into 3 categories from lowest to highest priority: green, yellow and red. Each category involved a specific action protocol (Figure 1). The categorization by colors was initially carried out by a remote support center, based on data from the devices; and later, reviewed by arrhythmia nurse team who incorporated clinical information data. In case of discrepancy, the alert was again evaluated together with the cardiologist. The degree of concordance in the categorization of alerts was analyzed, as well as the transmission response time (TRT): support center- care team. Results In our center a total of 1013 patients were included (68±14 years old, 76% male), who completed 8755 remote transmissions. The initial classification of transmissions by the support center was: 6890 (78.7%) green, 1497 (17.1%) yellow and 368 (4.2%) red. Only 0.62% of transmissions required reclassification by the healthcare team. No alert initially classified as yellow or green should be reclassified to red. The TRT was 3.35 hours for the red transmissions and 5.6 hours for the yellow ones. Conclusion The categorization of alerts in our RM system allows an efficient and safe organization of assitance to patients with CID. Funding Acknowledgement Type of funding source: None

Automatic Remote Monitoring of Implantable Cardiac Devices in Clinical Practice – The Lumos-T Safely Reduces Routine Office Device Follow-up (TRUST) Trial

2010 ◽  
Vol 6 (3) ◽  
pp. 87
Author(s):  
Niraj Varma ◽  
Keyword(s):  
Clinical Practice ◽  
Remote Monitoring ◽  
Home Monitoring ◽  
Implantable Devices ◽  
Cardiac Device ◽  
Cardiac Devices ◽  
Enhance Patient Safety ◽  
Implantable Cardiac Devices ◽  
Post Implantation

The use of implantable electronic cardiac devices is increasing. Post-implantation follow-up is important for monitoring both device function and patient condition; however, clinical practice is inconsistent. For example, implantable cardioverter–defibrillator follow-up schedules vary from every three months to yearly according to facility and physician preference and the availability of resources. Importantly, no surveillance occurs between follow-up visits. By contrast, implantable devices with automatic remote monitoring capability provide a means for performing constant surveillance, with the ability to identify salient problems rapidly. The Lumos-T Reduces Routine Office Device Follow-up Study (TRUST) demonstrated that remote home monitoring reduced clinic burden and allowed early detection of patient and/or system problems, enabling efficient monitoring and an opportunity to enhance patient safety. The results of the trial have significant implications for the management of patients receiving all forms of implantable electronic cardiac device.

scholarly journals Language aspects of children infected with HIV

Revista CEFAC ◽  
2013 ◽  
Vol 15 (6) ◽  
pp. 1621-1626 ◽  
Author(s):  
Raphaela Barroso Guedes Granzotti ◽  
Silvia Fabiana Biason de Moura Negrini ◽  
Marisa Tomoe Hebihara Fukuda ◽  
Osvaldo Massaiti Takayanagui
Keyword(s):  
Early Stage ◽  
Clinical Classification ◽  
Significant Relation ◽  
Immunological Parameters ◽  
Clinical Criteria ◽  
Immunological Profile ◽  
Viral Burden ◽  
Study Population

PURPOSE: to assess the lexical proficiency and the incidence of phonologic disorders in the language of children infected with HIV. METHOD: the study population consisted of 31 children between three and seven year-old. For evaluation purposes the Test of Infantile Language - ABFW was applied in the areas of phonology and vocabulary. RESULTS: the results obtained were analyzed according to the clinical criteria for the classification of the disease proposed by the CDC and regarding the immunological profile and the viral burden using the Mann-Whitney test for statistical analysis. In the vocabulary evaluation, 100% of the children presented an inappropriate response for their age in at least two distinct conceptual fields. In the phonologic evaluation, 67.7% of the assessed children were considered to be affected by some phonologic disorder. When we compared adequate and inadequate results of phonologic evaluation to the clinical and immunological parameters of AIDS such as clinical classification (p=0,16), CD4 count (p=0,37) and viral burden (p=0,82), we did not detect a statistically significant relation between language alterations and disease severity. CONCLUSION: this research has shown that the studied group presents a high risk for language disorders and that constant phonoaudiological follow-up is essential to identify the alterations in early stage.

Classification of Surgical Complications

2017 ◽  
Author(s):  
Andrew Gonzalez ◽  
SreyRam Kuy
Keyword(s):  
Length Of Stay ◽  
Study Design ◽  
Surgical Complications ◽  
Clinical Case ◽  
Classification Model ◽  
Design Study ◽  
Study Intervention

This landmark paper proposed a graded classification model for surgical complications and determined that there is a direct correlation between complication grade and patient length of stay. This chapter describes the basics of the study, including funding, year study began, year study was published, study location, who was studied, who was excluded, how many patients, study design, study intervention, follow-up, endpoints, results, and criticism and limitations. The chapter briefly reviews other relevant studies and information, gives a summary and discusses implications, and concludes with a relevant clinical case.

Remote Follow-Up of Implantable Cardioverter Defibrillators

2013 ◽  
pp. 162-172
Author(s):  
David L. Scher ◽  
Franco Naccarella ◽  
Zhang Feng ◽  
Giovanni Rinaldi
Keyword(s):  
Remote Monitoring ◽  
Clinical Information ◽  
Medical Industry ◽  
Implantable Cardioverter Defibrillators ◽  
Remote Monitoring System ◽  
Patients With Heart Failure ◽  
New Literature ◽  
Cardioverter Defibrillators ◽  
Monitoring Devices

In this chapter, the authors introduce some concepts about the remote follow-up of Implantable Cardioverter Defibrillators (ICD). Even if this type of remote monitoring system is relatively new, literature has demonstrated the utilization in clinical practice and during the last few years, the medical industry has provided different devices. Starting from the background, some models of utilizations are presented, focusing on the description of the main functions provided by some devices offered on the market. Next the motivations for which remote follow-up is needed are explored; a better management of the patient is described in several studies, and the integration of clinical information from monitoring devices in Electronic Medical Records is presented as the important step in order to provide comprehensive clinical information about the patient. Also, economic issues are shown. Then, some experiences realized in U.S. are explored, and at last, a number of questions are proposed to the discussion as contribution to the next research. Some Italian recent experiences in the field of remote monitoring and home care of patients with heart failure with and without implantable devices are reported.

scholarly journals Reassessing the Net Benefit of Cancer Drugs With Evolution of Evidence Using the ASCO Value Framework

2021 ◽  
Vol 19 (7) ◽  
pp. 815-820
Author(s):  
Seanthel Delos Santos ◽  
Noah Witzke ◽  
Bishal Gyawali ◽  
Vanessa Sarah Arciero ◽  
Amanda Putri Rahmadian ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Health Benefit ◽  
Net Benefit ◽  
Hazard Ratios ◽  
Fda Approval ◽  
Initial Classification

Background: Regulatory approval of oncology drugs is often based on interim data or surrogate endpoints. However, clinically relevant data, such as long-term overall survival and quality of life (QoL), are often reported in subsequent publications. This study evaluated the ASCO-Value Framework (ASCO-VF) net health benefit (NHB) at the time of approval and over time as further evidence arose. Methods: FDA-approved oncology drug indications from January 2006 to December 2016 were reviewed to identify clinical trials scorable using the ASCO-VF. Subsequent publications of clinical trials relevant for scoring were identified (until December 2019). Using ASCO-defined thresholds (≤40 for low and ≥45 for substantial benefit), we assessed changes in classification of benefit at 3 years postapproval. Results: Fifty-five eligible indications were included. At FDA approval, 40.0% were substantial, 10.9% were intermediate, and 49.1% were low benefit. We then identified 90 subsequent publications relevant to scoring, including primary (28.9%) and secondary endpoint updates (47.8%), safety updates (31.1%), and QoL reporting (47.8%). There was a change from initial classification of benefit in 27.3% of trials (10.9% became substantial, 9.1% became low, and 7.3% became intermediate). These changes were mainly due to updated hazard ratios (36.4%), toxicities (56.4%), new tail-of-the-curve bonus (9.1%), palliation bonus (14.5%), or QoL bonus (18.2%). Overall, at 3 years postapproval, 40.0% were substantial, 9.1% were intermediate, and 50.9% were low benefit. Conclusions: Because there were changes in classification for more than one-quarter of indications, in either direction, reassessing the ASCO-VF NHB as more evidence becomes available may be beneficial to inform clinical shared decision-making. On average, there was no overall improvement in the ASCO-VF NHB with longer follow-up and evolution of evidence.

Die Wirksamkeit eines Frühinterventionsprogramms für Jugendliche mit Computerspiel- und Internetabhängigkeit: Mittelfristige Effekte der PROTECT+ Studie

2020 ◽  
Vol 48 (1) ◽  
pp. 3-14 ◽  
Author(s):  
Carolin Szász-Janocha ◽  
Eva Vonderlin ◽  
Katajun Lindenberg
Keyword(s):  
Internet Use ◽  
Health Problems ◽  
Reliable Change Index ◽  
Gaming Disorder ◽  
Statistical Classification ◽  
Reliable Change ◽  
Classification Of Diseases ◽  
International Statistical Classification

Zusammenfassung. Fragestellung: Das junge Störungsbild der Computerspiel- und Internetabhängigkeit hat in den vergangenen Jahren in der Forschung zunehmend an Aufmerksamkeit gewonnen. Durch die Aufnahme der „Gaming Disorder“ in die ICD-11 (International Statistical Classification of Diseases and Related Health Problems) wurde die Notwendigkeit von evidenzbasierten und wirksamen Interventionen avanciert. PROTECT+ ist ein kognitiv-verhaltenstherapeutisches Gruppentherapieprogramm für Jugendliche mit Symptomen der Computerspiel- und Internetabhängigkeit. Die vorliegende Studie zielt auf die Evaluation der mittelfristigen Effekte nach 4 Monaten ab. Methodik: N = 54 Patientinnen und Patienten im Alter von 9 bis 19 Jahren (M = 13.48; SD = 1.72) nahmen an der Frühinterventionsstudie zwischen April 2016 und Dezember 2017 in Heidelberg teil. Die Symptomschwere wurde zu Beginn, zum Abschluss der Gruppentherapie sowie nach 4 Monaten anhand von standardisierten Diagnostikinstrumenten erfasst. Ergebnisse: Mehrebenenanalysen zeigten eine signifikante Reduktion der Symptomschwere anhand der Computerspielabhängigkeitsskala (CSAS) nach 4 Monaten. Im Selbstbeurteilungsbogen zeigte sich ein kleiner Effekt (d = 0.35), im Elternurteil ein mittlerer Effekt (d = 0.77). Der Reliable Change Index, der anhand der Compulsive Internet Use Scale (CIUS) berechnet wurde, deutete auf eine starke Heterogenität im individuellen Symptomverlauf hin. Die Patientinnen und Patienten bewerteten das Programm zu beiden Follow-Up-Messzeitpunkten mit einer hohen Zufriedenheit. Schlussfolgerungen: Die vorliegende Arbeit stellt international eine der wenigen Studien dar, die eine Reduktion der Symptome von Computerspiel- und Internetabhängigkeit im Jugendalter über 4 Monate belegen konnte.

Remote monitoring of implantable devices

2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Giovanni B. Perego ◽  
Francesco M. Brasca
Keyword(s):  
Remote Monitoring ◽  
Implantable Devices

Connectionist Temporal Classification Model for Dynamic Hand Gesture Recognition using RGB and Optical flow Data

2020 ◽  
Vol 17 (4) ◽  
pp. 497-506
Author(s):  
Sunil Patel ◽  
Ramji Makwana
Keyword(s):  
Neural Network ◽  
Optical Flow ◽  
Gesture Recognition ◽  
Hand Gesture Recognition ◽  
Classification Model ◽  
Hand Gesture ◽  
Flow Data ◽  
Dynamic Hand Gesture Recognition ◽  
Connectionist Temporal Classification

Automatic classification of dynamic hand gesture is challenging due to the large diversity in a different class of gesture, Low resolution, and it is performed by finger. Due to a number of challenges many researchers focus on this area. Recently deep neural network can be used for implicit feature extraction and Soft Max layer is used for classification. In this paper, we propose a method based on a two-dimensional convolutional neural network that performs detection and classification of hand gesture simultaneously from multimodal Red, Green, Blue, Depth (RGBD) and Optical flow Data and passes this feature to Long-Short Term Memory (LSTM) recurrent network for frame-to-frame probability generation with Connectionist Temporal Classification (CTC) network for loss calculation. We have calculated an optical flow from Red, Green, Blue (RGB) data for getting proper motion information present in the video. CTC model is used to efficiently evaluate all possible alignment of hand gesture via dynamic programming and check consistency via frame-to-frame for the visual similarity of hand gesture in the unsegmented input stream. CTC network finds the most probable sequence of a frame for a class of gesture. The frame with the highest probability value is selected from the CTC network by max decoding. This entire CTC network is trained end-to-end with calculating CTC loss for recognition of the gesture. We have used challenging Vision for Intelligent Vehicles and Applications (VIVA) dataset for dynamic hand gesture recognition captured with RGB and Depth data. On this VIVA dataset, our proposed hand gesture recognition technique outperforms competing state-of-the-art algorithms and gets an accuracy of 86%

scholarly journals Growth Stages Classification of Potato Crop Based on Analysis of Spectral Response and Variables Optimization

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3995 ◽  
Author(s):  
Ning Liu ◽  
Ruomei Zhao ◽  
Lang Qiao ◽  
Yao Zhang ◽  
Minzan Li ◽  
...  
Keyword(s):  
Growth Stage ◽  
Spectral Response ◽  
Classification Model ◽  
Growth Stages ◽  
Potato Field ◽  
Spectral Bands ◽  
Svm Model ◽  
Selection Algorithms ◽  
Potato Crops

Potato is the world’s fourth-largest food crop, following rice, wheat, and maize. Unlike other crops, it is a typical root crop with a special growth cycle pattern and underground tubers, which makes it harder to track the progress of potatoes and to provide automated crop management. The classification of growth stages has great significance for right time management in the potato field. This paper aims to study how to classify the growth stage of potato crops accurately on the basis of spectroscopy technology. To develop a classification model that monitors the growth stage of potato crops, the field experiments were conducted at the tillering stage (S1), tuber formation stage (S2), tuber bulking stage (S3), and tuber maturation stage (S4), respectively. After spectral data pre-processing, the dynamic changes in chlorophyll content and spectral response during growth were analyzed. A classification model was then established using the support vector machine (SVM) algorithm based on spectral bands and the wavelet coefficients obtained from the continuous wavelet transform (CWT) of reflectance spectra. The spectral variables, which include sensitive spectral bands and feature wavelet coefficients, were optimized using three selection algorithms to improve the classification performance of the model. The selection algorithms include correlation analysis (CA), the successive projection algorithm (SPA), and the random frog (RF) algorithm. The model results were used to compare the performance of various methods. The CWT-SPA-SVM model exhibited excellent performance. The classification accuracies on the training set (Atrain) and the test set (Atest) were respectively 100% and 97.37%, demonstrating the good classification capability of the model. The difference between the Atrain and accuracy of cross-validation (Acv) was 1%, which showed that the model has good stability. Therefore, the CWT-SPA-SVM model can be used to classify the growth stages of potato crops accurately. This study provides an important support method for the classification of growth stages in the potato field.

External validation of a heart failure risk prediction model in a remote monitoring cohort submitted to cardiac resynchronization therapy

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
I Cardoso ◽  
M Coutinho ◽  
G Portugal ◽  
A Valentim ◽  
A.S Delgado ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
High Risk ◽  
Remote Monitoring ◽  
Hospital Admissions ◽  
External Validation ◽  
Left Ventricular Ejection ◽  
National Database ◽  
Failure Risk

Abstract Background Patients (P) submitted to cardiac ressynchronization therapy (CRT) are at high risk of heart failure (HF) events during follow-up. Continuous analysis of various physiological parameters, as reported by remote monitoring (RM), can contribute to point out incident HF admissions. Tailored evaluation, including multi-parameter modelling, may further increase the accuracy of such algorithms. Purpose Independent external validation of a commercially available algorithm (“Heart Failure Risk Status” HFRS, Medtronic, MN USA) in a cohort submitted to CRT implantation in a tertiary center. Methods Consecutive P submitted to CRT implantation between January 2013 and September 2019 who had regular RM transmissions were included. The HFRS algorithm includes OptiVol (Medtronic Plc., MN, USA), patient activity, night heart rate (NHR), heart rate variability (HRV), percentage of CRT pacing, atrial tachycardia/atrial fibrillation (AT/AF) burden, ventricular rate during AT/AF (VRAF), and detected arrhythmia episodes/therapy delivered. P were classified as low, medium or high risk. Hospital admissions were systematically assessed by use of a national database (“Plataforma de Dados de Saúde”). Accuracy of the HFRS algorithm was evaluated by random effects logistic regression for the outcome of unplanned hospital admission for HF in the 30 days following each transmission episode. Results 1108 transmissions of 35 CRT P, corresponding to 94 patient-years were assessed. Mean follow-up was 2.7 yrs. At implant, age was 67.6±9.8 yrs, left ventricular ejection fraction 28±7.8%, BNP 156.6±292.8 and NYHA class >II in 46% of the P. Hospital admissions for HF were observed within 30 days in 9 transmissions. Stepwise increase in HFRS was significantly associated with higher risk of HF admission (odds ratio 12.7, CI 3.2–51.5). HFRS had good discrimination for HF events with receiving-operator curve AUC 0.812. Conclusions HFRS was significantly associated with incident HF admissions in a high-risk cohort. Prospective use of this algorithm may help guide HF therapy in CRT recipients. Funding Acknowledgement Type of funding source: None

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