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Total 793 results found since Jan 2013.

Time‐varying effect modeling with longitudinal data truncated by death: conditional models, interpretations, and inference
Recent studies found that infection‐related hospitalization was associated with increased risk of cardiovascular (CV) events, such as myocardial infarction and stroke in the dialysis population. In this work, we develop time‐varying effects modeling tools in order to examine the CV outcome risk trajectories during the time periods before and after an initial infection‐related hospitalization. For this, we propose partly conditional and fully conditional partially linear generalized varying coefficient models (PL‐GVCMs) for modeling time‐varying effects in longitudinal data with substantial follow‐up truncation ...
Source: Statistics in Medicine - December 9, 2015 Category: Statistics Authors: Jason P. Estes, Danh V. Nguyen, Lorien S. Dalrymple, Yi Mu, Damla Şentürk Tags: Research Article Source Type: research

Group sequential control of overall toxicity incidents in clinical trials - non-Bayesian and Bayesian approaches
In some small clinical trials, toxicity is not a primary endpoint; however, it often has dire effects on patients’ quality of life and is even life-threatening. For such clinical trials, rigorous control of the overall incidence of adverse events is desirable, while simultaneously collecting safety information. In this article, we propose group sequential toxicity monitoring strategies to control overall toxicity incidents below a certain level as opposed to performing hypothesis testing, which can be incorporated into an existing study design based on the primary endpoint. We consider two sequential methods: a non-B...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Yu, J., Hutson, A. D., Siddiqui, A. H., Kedron, M. A. Tags: Articles Source Type: research

A Review of Techniques for Detection of Movement Intention Using Movement-Related Cortical Potentials.
In this study, we recapitulate the features such as signal's acquisition, processing, and enhancement and different electrode montages used for EEG data recoding from different studies that used MRCPs to predict the upcoming real or imaginary movement. An authentic identification of human movement intention, accompanying the knowledge of the limb engaged in the performance and its direction of movement, has a potential implication in the control of external devices. This information could be helpful in development of a proficient patient-driven rehabilitation tool based on brain-computer interfaces (BCIs). Such a BCI parad...
Source: Computational and Mathematical Methods in Medicine - February 19, 2016 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Group sequential designs with prospectively planned rules for subpopulation enrichment
We propose a class of randomized trial designs aimed at gaining the advantages of wider generalizability and faster recruitment while mitigating the risks of including a population for which there is greater a priori uncertainty. We focus on testing null hypotheses for the overall population and a predefined subpopulation. Our designs have preplanned rules for modifying enrollment criteria based on data accrued at interim analyses. For example, enrollment can be restricted if the participants from a predefined subpopulation are not benefiting from the new treatment. Our designs have the following features: the multiple tes...
Source: Statistics in Medicine - April 12, 2016 Category: Statistics Authors: Michael Rosenblum, Brandon Luber, Richard E. Thompson, Daniel Hanley Tags: Research Article Source Type: research

A clinical trial design using the concept of proportional time using the generalized gamma ratio distribution
Traditional methods of sample size and power calculations in clinical trials with a time‐to‐event end point are based on the logrank test (and its variations), Cox proportional hazards (PH) assumption, or comparison of means of 2 exponential distributions. Of these, sample size calculation based on PH assumption is likely the most common and allows adjusting for the effect of one or more covariates. However, when designing a trial, there are situations when the assumption of PH may not be appropriate. Additionally, when it is known that there is a rapid decline in the survival curve for a control group, such as from pr...
Source: Statistics in Medicine - August 16, 2017 Category: Statistics Authors: Milind A. Phadnis, James B. Wetmore, Matthew S. Mayo Tags: RESEARCH ARTICLE Source Type: research

Investigation of 2 ‐stage meta‐analysis methods for joint longitudinal and time‐to‐event data through simulation and real data application
ConclusionsWhere evidence of association between longitudinal and time‐to‐event outcomes exists, results from joint models over standalone analyses should be pooled in 2‐stage meta‐analyses.
Source: Statistics in Medicine - December 18, 2017 Category: Statistics Authors: Maria Sudell, Catrin Tudur Smith, Fran çois Gueyffier, Ruwanthi Kolamunnage‐Dona Tags: RESEARCH ARTICLE Source Type: research

Sensitivity analysis for unobserved confounding of direct and indirect effects using uncertainty intervals
To estimate direct and indirect effects of an exposure on an outcome from observed data, strong assumptions about unconfoundedness are required. Since these assumptions cannot be tested using the observed data, a mediation analysis should always be accompanied by a sensitivity analysis of the resulting estimates. In this article, we propose a sensitivity analysis method for parametric estimation of direct and indirect effects when the exposure, mediator, and outcome are all binary. The sensitivity parameters consist of the correlations between the error terms of the exposure, mediator, and outcome models. These correlation...
Source: Statistics in Medicine - February 21, 2018 Category: Statistics Authors: Anita Lindmark, Xavier Luna, Marie Eriksson Tags: RESEARCH ARTICLE Source Type: research

Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards
We present a new estimator of the restricted mean survival time in randomized trials where there is right censoring that may depend on treatment and baseline variables. The proposed estimator leverages prognostic baseline variables to obtain equal or better asymptotic precision compared to traditional estimators. Under regularity conditions and random censoring within strata of treatment and baseline variables, the proposed estimator has the following features: (i) it is interpretable under violations of the proportional hazards assumption; (ii) it is consistent and at least as precise as the Kaplan –Meier and inverse pr...
Source: Lifetime Data Analysis - February 28, 2018 Category: Statistics Source Type: research

A Review on the Extraction of Quantitative Retinal Microvascular Image Feature.
Authors: Kipli K, Hoque ME, Lim LT, Mahmood MH, Sahari SK, Sapawi R, Rajaee N, Joseph A Abstract Digital image processing is one of the most widely used computer vision technologies in biomedical engineering. In the present modern ophthalmological practice, biomarkers analysis through digital fundus image processing analysis greatly contributes to vision science. This further facilitates developments in medical imaging, enabling this robust technology to attain extensive scopes in biomedical engineering platform. Various diagnostic techniques are used to analyze retinal microvasculature image to enable geometric fe...
Source: Computational and Mathematical Methods in Medicine - August 3, 2018 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Machine learning methods for leveraging baseline covariate information to improve the efficiency of clinical trials
Clinical trials are widely considered the gold standard for treatment evaluation, and they can be highly expensive in terms of time and money. The efficiency of clinical trials can be improved by incorporating information from baseline covariates that are related to clinical outcomes. This can be done by modifying an unadjusted treatment effect estimator with an augmentation term that involves a function of covariates. The optimal augmentation is well characterized in theory but must be estimated in practice. In this article, we investigate the use of machine learning methods to estimate the optimal augmentation. We consid...
Source: Statistics in Medicine - November 25, 2018 Category: Statistics Authors: Zhiwei Zhang, Shujie Ma Tags: RESEARCH ARTICLE Source Type: research

Parameter estimation in a minimal model of cardio-pulmonary interactions.
Abstract Mechanical ventilation is a widely used breathing support for patients in intensive care. Its effects on the respiratory and cardiovascular systems are complex and difficult to predict. This work first presents a minimal mathematical model representing the mechanics of both systems and their interaction, in terms of flows, pressures and volumes. The aim of this model is to get insight on the two systems' status when mechanical ventilation settings, such as positive end-expiratory pressure, are changing. The parameters of the model represent cardiac elastances and vessel compliances and resistances. As a s...
Source: Mathematical Biosciences - May 21, 2019 Category: Statistics Authors: de Bournonville S, Pironet A, Pretty C, Chase JG, Desaive T Tags: Math Biosci Source Type: research

Influential Factors of an Asynchronous BCI for Movement Intention Detection.
Authors: Rodpongpun S, Janyalikit T, Ratanamahatana CA Abstract In recent years, asynchronous brain computer interface (BCI) systems have been utilized in many domains such as robot controlling, assistive technology, and rehabilitation. In such BCI systems, movement intention detection algorithms are used to detect movement desires. In recent years, movement-related cortical potential (MRCP), an electroencephalogram (EEG) pattern representing voluntary movement intention, attracts wide attention in movement intention detection. Unfortunately, low MRCP detection accuracy makes the asynchronous BCI system impractical...
Source: Computational and Mathematical Methods in Medicine - April 12, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Functional modeling of pedaling kinematics for the Stroke patients
Source: Journal of Biopharmaceutical Statistics - July 2, 2020 Category: Statistics Authors: Chakraborty Dey Mukherjee Alberts Linder Source Type: research

A Semantic Analysis and Community Detection-Based Artificial Intelligence Model for Core Herb Discovery from the Literature: Taking Chronic Glomerulonephritis Treatment as a Case Study.
Authors: Zhang Y, Liu Y, Zhu J, Zhai S, Jin R, Wen C Abstract The Traditional Chinese Medicine (TCM) formula is the main treatment method of TCM. A formula often contains multiple herbs where core herbs play a critical therapeutic effect for treating diseases. It is of great significance to find out the core herbs in formulae for providing evidences and references for the clinical application of Chinese herbs and formulae. In this paper, we propose a core herb discovery model CHDSC based on semantic analysis and community detection to discover the core herbs for treating a certain disease from large-scale literatur...
Source: Computational and Mathematical Methods in Medicine - September 23, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

National hospital discharge survey: 2006 annual summary
This report presents 2006 national estimates and selected trend data on the use of nonfederal short-stay hospitals in the United States. Estimates are provided by selected patient and hospital characteristics, diagnoses, and surgical and nonsurgical procedures performed. Estimates of diagnoses and procedures are presented according to the International Classification of Diseases, Ninth Revision, Clinical Modification codes. Methods-The estimates are based on data collected through the National Hospital Discharge Survey (NHDS). The survey has been conducted annually since 1965. In 2006, data were collected for approximately...
Source: Vital Health Statistics Series 13 - October 1, 2014 Category: Statistics Authors: Verita C Buie Maria F Owings Carol J DeFrances Alexander Golosinskiy Source Type: research