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Predicting persistent inflammatory arthritis amongst early arthritis clinic patients in the UK: is musculoskeletal ultrasound required?

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ARTHRITIS RESEARCH & THERAPY 2013年第5期15卷 1-10页

作者： Pratt, Arthur G. Lorenzi, Alice R. Wilson, Gill Platt, Philip N. Isaacs, John D. Newcastle Univ Inst Cellular Med Musculoskeletal Res Grp Newcastle Upon Tyne NE1 7RU Tyne & Wear England Freeman Rd Hosp Musculoskeletal Unit Newcastle Upon Tyne Tyne & Wear England Univ Hull Fac Hlth & Social Care Kingston Upon Hull HU6 7RX N Humberside England

Introduction: Analyses of large clinical datasets from early arthritis cohorts permit the development of algorithms that may be used for outcome prediction in individual patients. The value added by routine use of musculoskeletal ultrasound (MSUS) in an early arthritis setting, as a component of such predictive algorithms, remains to be determined. Methods: The authors undertook a retrospective analysis of a large, true-to-life, observational inception cohort of early arthritis patients in Newcastle upon Tyne, UK, which included patients with inflammatory arthralgia but no clinically swollen joints. A pragmatic, 10-minute MSUS assessment protocol was developed, and applied to each of these patients at baseline. Logistic regression was used to develop two "risk metrics" that predicted the development of a persistent inflammatory arthritis (PIA), with or without the inclusion of MSUS parameters. Results: A total of 379 enrolled patients were assigned definitive diagnoses after >= 12 months follow-up (median 28 months), of whom 162 (42%) developed a persistent inflammatory arthritis. A risk metric derived from 12 baseline clinical and serological parameters alone had an excellent discriminatory utility with respect to an outcome of PIA (area under receiver operator characteristic (ROC) curve 0.91;95% Cl 0.88 to 0.94). The discriminatory utility of a similar metric, which incorporated MSUS parameters, was not significantly superior (area under ROC curve 0.91;95% Cl 0.89 to 0.94). Neither did this approach identify an added value of MSUS over the use of routine clinical parameters in an algorithm for discriminating PIA patients whose outcome diagnosis was rheumatoid arthritis (RA). Conclusions: MSUS use as a routine component of assessment in an early arthritis clinic did not add substantial discriminatory value to a risk metric for predicting PIA.

关键词： Rheumatoid Arthritis Swell Joint Count Early Arthritis predictive algorithm Undifferentiated Arthritis

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A Driving-Force Predictor for Estimating Pathway Activation in Patient-Specific Models of Deep Brain Stimulation

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NEUROMODULATION 2019年第4期22卷 403-415页

作者： Howell, Bryan Gunalan, Kabilar McIntyre, Cameron C. Case Western Reserve Univ Dept Biomed Engn Wolstein Res BldgRoom 62242103 Cornell Rd Cleveland OH 44106 USA Emory Univ Dept Psychiat & Behav Sci Atlanta GA 30322 USA

Objective Detailed biophysical modeling of deep brain stimulation (DBS) provides a theoretical approach to quantify the cellular response to the applied electric field. However, the most accurate models for performing such analyses, patient-specific field-cable (FC) pathway-activation models (PAMs), are so technically demanding to implement that their use in clinical research is greatly limited. predictive algorithms can simplify PAM calculations, but they generally fail to reproduce the output of FC models when evaluated over a wide range of clinically relevant stimulation parameters. Therefore, we set out to develop a novel driving-force (DF) predictive algorithm (DF-Howell), customized to the study of DBS, which can better match FC results. Methods We developed the DF-Howell algorithm and compared its predictions to FC PAM results, as well as to the DF-Peterson algorithm, which is currently the most accurate and generalizable DF-based method. Comparison of the various methods was quantified within the context of subthalamic DBS using activation thresholds of axons representing the internal capsule, hyperdirect pathway, and cerebellothalamic tract for various combinations of fiber diameters, stimulus pulse widths, and electrode configurations. Results The DF-Howell predictor estimated activation of the three axonal pathways with less than a 6.2% mean error with respect to the FC PAM for all 21 cases tested. In 15 of the 21 cases, DF-Howell outperformed DF-Peterson in estimating pathway activation, reducing mean-errors up to 22.5%. Conclusions DF-Howell represents an accurate predictor for estimating axonal pathway activation in patient-specific DBS models, but errors still exist relative to FC PAM calculations. Nonetheless, the tractability of DF algorithms helps to reduce the technical barriers for performing accurate biophysical modeling in clinical DBS research studies.

关键词： Computational modeling deep brain stimulation pathway activation predictive algorithm tractography

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iPREDICT: Characterization of Asthma Triggers and Selection of Digital Technology to Predict Changes in Disease Control

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JOURNAL OF ASTHMA AND ALLERGY 2024年 17卷 653-666页

作者： Castro, Mario Zavod, Merrill Rutgersson, Annika Jornten-Karlsson, Magnus Dutta, Bhaskar Hagger, Lynn Univ Kansas Div Pulm Crit Care & Sleep Med Sch Med 4000 Cambridge StMSN 3007 Kansas City KS 66160 USA AstraZeneca User Experience Wilmington DE USA AstraZeneca Digital Patient Prod Molndal Sweden AstraZeneca Digital Implementat Digital Hlth R&D Molndal Sweden AstraZeneca Patient Safety Ctr Excellence Gaithersburg MD USA AstraZeneca Content Strategy & Experience Design Digital Global Commercial Gaithersburg MD USA

Purpose: The iPREDICT program aimed to develop an integrated digital health solution capable of continuous data streaming, predicting changes in asthma control, and enabling early intervention. Patients and Methods: As part of the iPREDICT program, asthma triggers were characterized by surveying 221 patients (aged >18 years) with self-reported asthma for a risk-benefit analysis of parameters predictive of changes in disease control. Seventeen healthy volunteers (age 25-65 years) tested 13 devices to measure these parameters and assessed their usability attributes. Results: Patients identified irritants such as chemicals, allergens, weather changes, and physical activity as triggers that were the most relevant to deteriorating asthma control. Device testing in healthy volunteers revealed variable data formats/units and quality issues, such as missing data and low signal-to-noise ratio. Based on user preference and data capture validity, a spirometer, vital sign monitor, and sleep monitor formed the iPREDICT integrated system for continuous data streaming to develop a personalized/predictive algorithm for asthma control. Conclusion: These findings emphasize the need to systematically compare devices based on several parameters, including usability and data quality, to develop integrated digital technology programs for asthma care.

关键词： asthma devices digital predictive algorithm sensors

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Predictors of perioperative complications in paediatric cranial vault reconstruction surgery: a multicentre observational study from the Pediatric Craniofacial Collaborative Group

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BRITISH JOURNAL OF ANAESTHESIA 2019年第2期122卷 215-223页

作者： Goobie, S. M. Zurakowski, D. Isaac, K. V. Taicher, B. M. Fernandez, P. G. Derderian, C. K. Hetmaniuk, M. Stricker, P. A. Abruzzese, Christopher Apuya, Jesus Beethe, Amy Benzon, Hubert Binstock, Wendy Brzenskim, Alyssa Budac, Stefan Busso, Veronica Chhabada, Surendrasingh Chiao, Franklin Cladis, Franklyn Claypool, Danielle Collins, Michael Dabek, Rachel Dalesio, Nicholas Falconl, Ricardo Fernandez, Allison Fernandez, Patrick Fiadjoe, John Gangadharan, Meera Gentry, Katherine Glover, Chris Goobie, Susan M. Gosman, Amanda Grap, Shannon Gries, Heike Griffin, Allison Haberkern, Charles Hajduk, John Hall, Rebecca Hansen, Jennifer Hetmaniuk, Mali Hsieh, Vincent Huang, Henry Ingelmo, Pablo Ivanova, Iskra Jain, Ranu Kars, Michelle Kowalczyk-Derderian, Courtney Kugler, Jane Labovsky, Kristen Lakheeram, Indrani Lee, Andrew Martinez, Jose Luis Masel, Brian Medellin, Eduardo Meier, Petra Levy, Heather Mitzel Muhly, Wallis T. Muldowney, Bridget Nelson, Jonathon Nicholson, Julie Nguyen, Kim-Phuong Nguyen, Thanh Olutuye, Olutoyin Owens-Stubblefield, Margaret Parekh, Uma Ramesh Petersen, Timothy Pohl, Vanessa Post, Julian Poteet-Schwartz, Kim Prozesky, Jansie Reddy, Srijaya Reid, Russell Ricketts, Karene Rubens, Daniel Ryan, Laura Skitt, Rochelle Soneru, Codruta Spitznagel, Rachel Stricker, Paul Singh, Davinder Singhal, Neil R. Sorial, Emad Staudt, Susan Stubbeman, Bobbie Sung, Wai Syed, Tariq Szmuk, Peter Taicher, Brad M. Thompson, Douglas Tretault, Lisa Ungar-Kastner, Galit Watts, Rheana Wieser, John Wong, Karen Zamora, Lillian Harvard Med Sch Boston MA 02115 USA Boston Childrens Hosp Dept Anesthesiol Crit Care & Pain Med Boston MA 02115 USA Univ British Columbia Div Plast & Reconstruct Surg Vancouver BC Canada Duke Univ Med Ctr Durham NC USA Duke Childrens Hosp Dept Anesthesiol Durham NC USA Univ Colorado Sch Med Dept Anesthesiol Aurora CO USA Childrens Hosp Colorado Aurora CO USA Childrens Med Ctr Dallas Dept Anesthesiol & Crit Care Dallas TX USA Univ Texas Southwestern Dallas TX USA Univ Washington Seattle WA 98195 USA Seattle Childrens Hosp Dept Anesthesiol & Pain Management Seattle WA USA Childrens Hosp Philadelphia Philadelphia PA 19104 USA Univ Penn Perelman Sch Med Dept Anesthesiol & Crit Care Philadelphia PA 19104 USA Univ Wisconsin Madison Amer Family Childrens Hosp Madison WI USA Ann & Robert H Lurie Childrens Hosp Chicago Chicago IL 60611 USA Arkansas Childrens Hosp 800 Marshall St Little Rock AR 72202 USA Boston Childrens Hosp Boston MA USA Charlotte R Bloomberg Johns Hopkins Childrens Ctr Baltimore MD USA Egleston Childrens Healthcare Atlanta Atlanta GA USA Childrens Hosp & Med Ctr Omaha NE USA Childrens Hosp Colorado Denver CO USA Childrens Hosp Philadelphia Philadelphia PA 19104 USA Childrens Hosp Wisconsin Milwaukee WI 53201 USA Childrens Natl Hlth Syst Washington DC USA CHU St Justine Montreal PQ Canada Cincinnati Childrens Hosp Med Ctr Cincinnati OH 45229 USA Cleveland Clin Childrens Cleveland OH USA Driscoll Childrens Hosp Corpus Christi TX USA Duke Childrens Hosp & Hlth Ctr Durham NC USA Johns Hopkins All Childrens Hosp St Petersburg FL USA Vanderbilt Univ Med Ctr Monroe Carell Jr Childrens Hosp Vanderbilt Nashville TN USA Montreal Childrens Hosp Montreal PQ Canada New York Presbyterian Hosp Weill Cornell Med Coll New York NY USA Oregon Hlth & Sci Univ Doernbecher Childrens Hosp Portland OR 97201 USA Penn State Hershey Med Ctr Hershey PA USA Phoenix Childrens Hosp Phoenix AZ USA Seattle Childrens Hosp Seattle WA USA Texas C

Background: The current incidence of major complications in paediatric craniofacial surgery in North America has not been accurately defined. In this report, the Pediatric Craniofacial Collaborative Group evaluates the incidence and determines the independent predictors of major perioperative complications using a multicentre database. Methods: The Pediatric Craniofacial Surgery Perioperative Registry was queried for subjects undergoing complex cranial vault reconstruction surgery over a 5-year period. Major perioperative complications were identified through a structured a priori consensus process. Logistic regression was applied to identify predictors of a major perioperative complication with bootstrapping to evaluate discrimination accuracy and provide internal validity of the multivariable model. Results: A total of 1814 patients from 33 institutions in the US and Canada were analysed;15% were reported to have a major perioperative complication. Multivariable predictors included ASA physical status 3 or 4 (P = 0.005), craniofacial syndrome (P = 0.008), antifibrinolytic administered (P = 0.003), blood product transfusion >50 ml kg(-1) (P<0.001), and surgery duration over 5 h (P<0.001). Bootstrapping indicated that the predictive algorithm had good internal validity and excellent discrimination and model performance. A perioperative complication was estimated to increase the hospital length of stay by an average of 3 days (P<0.001). Conclusions: The predictive algorithm can be used as a prognostic tool to risk stratify patients and thereby potentially reduce morbidity and mortality. Craniofacial teams can utilise these predictors of complications to identify high-risk patients. Based on this information, further prospective quality improvement initiatives may decrease complications, and reduce morbidity and mortality.

关键词： predictive algorithm perioperative complications perioperative outcome craniosynostosis multivariable model paediatrics risk assessment

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PA-SPS: A predictive adaptive approach for an elastic stream processing system

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2024年 192卷

作者： Wladdimiro, Daniel Arantes, Luciana Sens, Pierre Hidalgo, Nicolas Sorbonne Univ CNRS LIP6 4 Pl Jussieu F-75005 Paris France Univ Diego Portales Ave Manuel Rodriguez 415 Santiago Chile

Stream Processing Systems (SPSs) dynamically process input events. Since the input is usually not a constant flow, presenting rate fluctuations, many works in the literature propose to dynamically replicate SPS operators, aiming at reducing the processing bottleneck induced by such fluctuations. However, these SPSs do not consider the problem of load balancing of the replicas or the cost involved in reconfiguring the system whenever the number of replicas changes. We present in this paper a predictive model which, based on input rate variation, execution time of operators, and queued events, dynamically defines the necessary current number of replicas of each operator. A predictor, composed of different models (i.e., mathematical and Machine Learning ones), predicts the input rate. We also propose a Storm -based SPS, named PA-SPS, which uses such a predictive model, not requiring reboot reconfiguration when the number of operators replica change. PA-SPS also implements a load balancer that distributes incoming events evenly among replicas of an operator. We have conducted experiments on Google Cloud Platform (GCP) for evaluation PA-SPS using real traffic traces of different applications and also compared it with Storm and other existing SPSs.

关键词： Big data Distributed stream processing Self-adaptive system Dynamic traffic predictive algorithm Google cloud platform

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Assessing the Performance of National Surgical Quality Improvement Program Surgical Risk Calculator in Elective Spine Surgery: Insights from Patients Undergoing Single-Level Posterior Lumbar Fusion

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WORLD NEUROSURGERY 2019年 126卷 E323-E329页

作者： Sebastian, Arjun Goyal, Anshit Alvi, Mohammed Ali Wahood, Waseem Elminawy, Mohamed Habermann, Elizabeth B. Bydon, Mohamad Mayo Clin Dept Orthoped Surg Rochester MN 55905 USA Mayo Clin Neuroinformat Lab Rochester MN 55905 USA Mayo Clin Dept Neurol Surg Rochester MN 55905 USA Mayo Clin Robert D & Patricia E Kern Ctr Sci Hlth Care Deli Rochester MN 55905 USA

INTRODUCTION: The American College of Surgeons-National Surgical Quality Improvement Program Surgical Risk Calculator is a tool developed to use 21 individual patient characteristics to make predictions for occurrence of 13 general and 2 procedure-specific outcomes. The goal of this study was to evaluate the performance of the Surgical Risk Calculator in predicting outcomes in patients receiving posterior lumbar fusion. METHODS: American College of Surgeons-National Surgical Quality Improvement Program Participant Use File for 2015 was queried for patients with age >= 18 years undergoing single-level posterior lumbar fusion (PLF) surgery. Individual patient characteristics were entered into the online risk calculator interface to retrieve the predicted estimated risk for perioperative outcomes and complications. Following this, predictive performance was analyzed by computing Brier score, c-statistic, and sensitivity values for all observed outcomes. RESULTS: A total of 2808 patients undergoing single-level PLF were included in the analysis. Overall, a very low incidence of 30-day postoperative complications was observed with the procedure (0.9%-6.3%). Poor predictive performance was found for all outcomes, including read-missions (c-statistic = 0.63;sensitivity = 15.28%;Brier score = 0.048) and returns to operating room (c-statistic = 0.56;sensitivity = 21.05%;Brier score = 0.032). The best performance was observed for venous thromboembolism (c-statistic = 0.66: Brier score = 0.008), although sensitivity was poor (3.85%) on account of low incidence. predictive performance for length of stay revealed good agreement between observed and predicted values with the exception of prolonged predicted hospital stays (>3.5 days). CONCLUSIONS: This study assesses the performance of the risk calculator for a homogenous population of patients undergoing a single-level PLF. Although the calculator did not fare well in predicting most outcomes, results need to be interpreted in t

关键词： Lumbar fusion NSQIP predictive algorithm Risk calculator Spine surgery

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Estimating Time-Variant Variables' Effects on a Micro Scale for Time-Based Crime Prediction 7

Estimating Time-Variant Variables' Effects on a Micro Scale ...

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7th International Conference on Business and Industrial Research (ICBIR)

作者： Ohyama, Tomoya Tohoku Univ Ctr Data Driven Sci & Artificial Intelligence Sendai Miyagi Japan

ISBN: (纸本)9781665494755

Crime prediction research has been biased toward spatial factors, and insufficient research has detailed predictions regarding temporal factors. To build an industrially practical crime prediction system, it is necessary to develop a method that considers both temporal and spatial risk factors. This study estimates the effect of time-variant variables such as the day of the week, season, weather, and events for a fundamental analysis of time-based crime prediction. However, because crime data are often imbalanced data with extremely few positive classes, subdividing the data spatially and temporally makes it difficult to estimate the parameters. Therefore, we attempted to solve this problem by dividing the city into clusters with high spatial homogeneity and analyzing each cluster. We observed different effects of time-varying factors for different types of crime.

关键词： crime prediction predictive algorithm time-variant variables spatial clustering generalized linear mixed model

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Rational design of peptide drugs: avoiding aggregation

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DRUG DISCOVERY TODAY 2005年第18期10卷 1208-1209页

作者： Bradbury, J

A future application of aggregation algorithms could be to search for inhibitors of the pathogenic aggregation that underlies Alzheimer‘s, Parkinson‘s and other neurodegenerative diseases. Author

关键词： predictive algorithm aggregation protein misfolding calcitonin amyloid fibril Subject-index terms: Pharmaceutical Science Drug Discovery Structural Biology

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Closed-loop-systeme in der diabetologie an der schwelle zum durchbruch?

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Diabetes Aktuell 2010年第8期8卷 368-373页

作者： Schönauer, Martin Thiele, Holger Thomas, Andreas Diabetologische Schwerpunktpraxis Leipzig Germany Lehrstuhl für Kardiologie Universität Leipzig Germany Medtronic GmbH Meerbusch Germany

Seit den 1960er Jahren wird an der Entwicklung einer künstlichen Bauchspeicheldrüse gearbeitet, dem sogenannten Closed-Loop-System. Es entstand aus dem technischen Verständnis für einen geschlossenen Kreislauf von Glukosemessung, Insulinabgabe und dem sich daraus ergebenden metabolischen Zustand. Seit den Anfängen sind erhebliche Fortschritte gemacht worden, sodass erste Produkte nun an der Schwelle zur Marktfähigkeit stehen. © 2010, Georg Thieme Verlag Stuttgart. Alle Rechte vorbehalten.

关键词： algorithms for insulin release artificial pancreas closed-loop system glucose sensors insulin pumps predictive algorithm

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System Architecture of the Sustainable Energy System for Performance Buildings

System Architecture of the Sustainable Energy System for Per...

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IEEE Electrical Power and Energy Conference (EPEC)

作者： Grebenyuk, Vladimir Ascent Syst Technol Sun Peaks BC V0R 5N0 Canada

ISBN: (纸本)9781479901067

Every system, however big or small, is always a part of a bigger system and in turn consists of a number of smaller subsystems. This is true for both natural and technical systems. According to Systems Architecture, in order to be successful, any complex technical system has to take into account its place in the hierarchy of other systems, as well as interdependency between the components of the system on each level. The principles of Systems Architecture are universal, but there is hardly a more important area where they need to be applied than the area of sustainability. An important conclusion of applying the principles of Systems Architecture to sustainable development is that the system itself must be sustainable. This paper presents an approach to designing sustainable system architecture for buildings based on a predictive algorithm, using a specific example of a building-integrated renewable energy control system.

关键词： sustainable system architecture predictive algorithm integrated energy control system high-performance building

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