scholarly journals Gait Analysis with Wearables Can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6992
Author(s):  
Rana Zia Ur Rehman ◽  
Yuhan Zhou ◽  
Silvia Del Din ◽  
Lisa Alcock ◽  
Clint Hansen ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Fall Risk ◽  
Clinical Decision Making ◽  
Principal Component ◽  
Clinical Decision ◽  
Poor Quality ◽  
Neurological Patients ◽  
Stride Duration

Falls are the leading cause of mortality, morbidity and poor quality of life in older adults with or without neurological conditions. Applying machine learning (ML) models to gait analysis outcomes offers the opportunity to identify individuals at risk of future falls. The aim of this study was to determine the effect of different data pre-processing methods on the performance of ML models to classify neurological patients who have fallen from those who have not for future fall risk assessment. Gait was assessed using wearables in clinic while walking 20 m at a self-selected comfortable pace in 349 (159 fallers, 190 non-fallers) neurological patients. Six different ML models were trained on data pre-processed with three techniques such as standardisation, principal component analysis (PCA) and path signature method. Fallers walked more slowly, with shorter strides and longer stride duration compared to non-fallers. Overall, model accuracy ranged between 48% and 98% with 43–99% sensitivity and 48–98% specificity. A random forest (RF) classifier trained on data pre-processed with the path signature method gave optimal classification accuracy of 98% with 99% sensitivity and 98% specificity. Data pre-processing directly influences the accuracy of ML models for the accurate classification of fallers. Using gait analysis with trained ML models can act as a tool for the proactive assessment of fall risk and support clinical decision-making.

scholarly journals Chromosome aneuploidy analysis in embryos derived from in vivo and in vitro matured human oocytes

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jianhua Li ◽  
Jing Chen ◽  
Tiecheng Sun ◽  
Shuiwen Zhang ◽  
Tingting Jiao ◽  
...  
Keyword(s):  
In Vitro Fertilization ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Poor Quality ◽  
Vitro Fertilization ◽  
Aneuploidy Rate ◽  
Significant Difference

Abstract Background In vitro oocyte maturation (IVM) is being increasingly approached in assisted reproductive technology (ART). This study aimed to evaluate the quality of embryos generated by in-vitro matured immature follicles, as a guideline for further clinical decision-making. Methods A total of 52 couples with normal karyotypes underwent in vitro fertilization, and 162 embryos were donated for genetic screening. Embryos in IVF group were generated by mature follicles retrieved during gonadotrophin-stimulated in vitro fertilization (IVF) cycles. And embryos in IVM group were fertilized from IVM immature oocytes. Results The average age of the women was 30.50 ± 4.55 years (range 21–42 years) with 87 embryos from IVF group and 75 embryos from IVM group. The rate of aneuploid with 28 of the 87 (32.2%) embryos from IVF group and 21 of the 75 (28%) embryos from IVM group, with no significant difference. The frequency of aneuploid embryos was lowest in the youngest age and increased gradually with women’s age, whether in IVF group or IVM group and risen significantly over 35 years old. The embryos with morphological grade 1 have the lowest aneuploidy frequency (16.6%), and increase by the grade, especially in IVF group. In grade 3, embryos in IVM group were more likely to be euploid than IVF group (60% vs 40%, respectively). Conclusions IVM does not affect the quality of embryos and does not increase the aneuploidy rate of embryos. It is clinically recommended that women more than 35 years have a high aneuploidy rate and recommended to test by PGS (strongly recommended to screened by PGS for women more than 40 years). Women aged less than 35 years old for PGS according to their physical and economic conditions. Embryo with poor quality is also recommended to test by PGS, especially for grade III embryos.

The Usability, Acceptability, and Functionality of Smart Oral Multidose Dispensing Systems for Medication Adherence: A Scoping Review

2020 ◽  
pp. 089719002097775
Author(s):  
Sadaf Faisal ◽  
Jessica Ivo ◽  
Catherine Lee ◽  
Caitlin Carter ◽  
Tejal Patel
Keyword(s):  
Medication Adherence ◽  
Scoping Review ◽  
Clinical Decision Making ◽  
Relevant Literature ◽  
Clinical Decision ◽  
Poor Quality ◽  
Future Studies ◽  
Adherence Data

Background: Medication non-adherence is a leading cause of non-optimal disease management, resulting in poor health outcomes, poor quality of life, and increased healthcare costs. Smart oral multidose dispensing systems (SOMDS) are being developed to address non-adherence; however, little is known about their integration into daily use by patients. Methods: Using Arksey and O’Malley’s scoping review framework, relevant literature was searched for in electronic databases (PubMed, EMBASE, International Pharmaceutical Abstracts, and Scopus). Observational and interventional studies reporting the integration and impact on adherence from SOMDS in adults ≥18 years and published after 1960 were included. Results: Thirteen articles including one case study, 8 cohort studies, and 4 randomized trials were eligible. SOMDS included smart blister packaging, automated dispensers, and electronic medication trays. The number of medications dispensed per SOMDS was one (n = 3), >1 (n = 2), placebo (n = 1) and not reported (n = 7). Reported outcomes included impact on medication adherence (n = 3), integration (n = 2) and both parameters (n = 8). Conclusion: Although most studies reported that SOMDS appear usable, there was significant variability in the SOMDS types, patient populations, medication adherence definitions, and measurements; impacting the interpretation of results. Future studies should be designed to address effectiveness of SOMDS on medication adherence in patients with multi-drug therapy and the utilization of real-time adherence data for informing clinical decision making.

scholarly journals The Effect of Correction Algorithms on Knee Kinematics and Kinetics during Gait of Patients with Knee Osteoarthritis

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Hanna Ulbricht ◽  
Meijin Hou ◽  
Xiangbin Wang ◽  
Jian He ◽  
Yanxin Zhang
Keyword(s):  
Knee Joint ◽  
Knee Osteoarthritis ◽  
Gait Analysis ◽  
Clinical Decision Making ◽  
Knee Kinematics ◽  
Principal Component ◽  
Clinical Decision ◽  
Joint Angles ◽  
Knee Oa ◽  
Flexion Moment

In gait analysis, the accuracy of knee joint angles and moments is critical for clinical decision-making. The purpose of this study was to determine the efficacy of two existing algorithms for knee joint axis correction under pathological conditions. Gait data from 20 healthy participants and 20 patients with knee osteoarthritis (OA) were collected using a motion capture system. An algorithm based on Principal Component Analysis (PCA) and a functional joint-based algorithm (FJA) were used to define the knee joint flexion axis. The results show that PCA decreased crosstalk for both groups, and FJA reduced crosstalk in patients with knee OA only. PCA decreased the range of motions of patients with knee OA in the direction of abduction/adduction significantly. There was a significant increase in the maximum knee flexion moment of patients with knee OA by FJA. The results indicate that both algorithms can efficiently reduce crosstalk for gait from patients with knee OA, which can further influence the results of knee joint angles and moments. We recommend that the correction algorithms be applied in clinical gait analysis with patients with knee OA.

Clinical decision making in spastic bilateral CP – Planning interventions using clinical gait analysis: A case study

2015 ◽  
Vol 42 ◽  
pp. S37
Author(s):  
M. Alvela ◽  
M. Bergmann ◽  
M.-L. Ööpik ◽  
Ü. Kruus ◽  
K. Englas ◽  
...  
Keyword(s):  
Decision Making ◽  
Gait Analysis ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Clinical Gait Analysis

scholarly journals Warning systems in a computerized nursing process for Intensive Care Units

2014 ◽  
Vol 48 (1) ◽  
pp. 125-132 ◽  
Author(s):  
Daniela Couto Carvalho Barra ◽  
Grace Teresinha Marcon Dal Sasso ◽  
Camila Rosália Antunes Baccin
Keyword(s):  
Patient Safety ◽  
Intensive Care ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Healthcare Research ◽  
Pelvic Surgery ◽  
Warning Systems ◽  
Nursing Process ◽  
Promote Patient Safety

A hybrid study combining technological production and methodological research aiming to establish associations between the data and information that are part of a Computerized Nursing Process according to the ICNP® Version 1.0, indicators of patient safety and quality of care. Based on the guidelines of the Agency for Healthcare Research and Quality and the American Association of Critical Care Nurses for the expansion of warning systems, five warning systems were developed: potential for iatrogenic pneumothorax, potential for care-related infections, potential for suture dehiscence in patients after abdominal or pelvic surgery, potential for loss of vascular access, and potential for endotracheal extubation. The warning systems are a continuous computerized resource of essential situations that promote patient safety and enable the construction of a way to stimulate clinical reasoning and support clinical decision making of nurses in intensive care.

scholarly journals Interpretable Detection and Location of Myocardial Infarction Based on Ventricular Fusion Rule Features

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Wenzhi Zhang ◽  
Runchuan Li ◽  
Shengya Shen ◽  
Jinliang Yao ◽  
Yan Peng ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Clinical Decision Making ◽  
Human Life ◽  
Principal Component ◽  
Fusion Rule ◽  
Clinical Decision ◽  
Gradient Boosting ◽  
Discrete Wavelet ◽  
Extreme Gradient Boosting ◽  
Ventricular Activity

Myocardial infarction (MI) is one of the most common cardiovascular diseases threatening human life. In order to accurately distinguish myocardial infarction and have a good interpretability, the classification method that combines rule features and ventricular activity features is proposed in this paper. Specifically, according to the clinical diagnosis rule and the pathological changes of myocardial infarction on the electrocardiogram, the local information extracted from the Q wave, ST segment, and T wave is computed as the rule feature. All samples of the QT segment are extracted as ventricular activity features. Then, in order to reduce the computational complexity of the ventricular activity features, the effects of Discrete Wavelet Transform (DWT), Principal Component Analysis (PCA), and Locality Preserving Projections (LPP) on the extracted ventricular activity features are compared. Combining rule features and ventricular activity features, all the 12 leads features are fused as the ultimate feature vector. Finally, eXtreme Gradient Boosting (XGBoost) is used to identify myocardial infarction, and the overall accuracy rate of 99.86% is obtained on the Physikalisch-Technische Bundesanstalt (PTB) database. This method has a good medical diagnosis basis while improving the accuracy, which is very important for clinical decision-making.

scholarly journals Opioid Analgesia: Perspectives on Right Use and Utility

2007 ◽  
Vol 3;10 (5;3) ◽  
pp. 479-491 ◽  
Author(s):  
Jane C. Ballantyne
Keyword(s):  
Quality Of Life ◽  
Chronic Pain ◽  
Side Effects ◽  
Clinical Decision Making ◽  
Analgesic Efficacy ◽  
Clinical Decision ◽  
Opioid Analgesia ◽  
Opioid Treatment

The ability of opioids to effectively and safely control acute and cancer pain has been one of several arguments used to support extending opioid treatment to patients with chronic pain, against a backdrop of considerable caution that has been based upon fears of addiction. Of course, opioids may cause addiction, but the “principle of balance” may justify that “…efforts to address abuse should not interfere with legitimate medical practice and patient care.” Yet, situations are increasingly encountered in which opioid-maintained patients are refractory to analgesia during periods of pain, or even during the course of chronic treatment. The real question is whether analgesic efficacy of opioids can be maintained over time. Overall, the evidence supporting long-term analgesic efficacy is weak. The putative mechanisms for failed opioid analgesia may be related to tolerance or opioid-induced hyperalgesia. Advances in basic sciences may help in understanding these phenomena, but the question of whether long-term opioid treatment can improve patients’ function or quality of life remains a broader issue. Opioid side effects are well known, but with chronic use, most (except constipation) subside. Still, side effects can negatively affect the outcomes and continuity of therapy. This paper addresses 1) what evidence supports the long-term utility of opioids for chronic pain; 2) how side effects may alter quality of life; 3) the nature of addiction and why it is different in pain patients, and 4) on what grounds could pain medication be denied? These questions are discussed in light of patients’ rights, and warrant balancing particular responsibilities with risks. These are framed within the Hippocratic tradition of “producing good for the patient and protecting from harm,” so as to enable 1) more informed clinical decision making, and 2) progress towards right use and utility of opioid treatment for chronic pain. Key Words: Opioids, chronic pain, addiction, side effects, utility, ethics

Beyond the Development of Health-Related Quality-of-Life (HRQOL) Measures: A Checklist for Evaluating HRQOL Outcomes in Cancer Clinical Trials—Does HRQOL Evaluation in Prostate Cancer Research Inform Clinical Decision Making?

2003 ◽  
Vol 21 (18) ◽  
pp. 3502-3511 ◽  
Author(s):  
Fabio Efficace ◽  
Andrew Bottomley ◽  
David Osoba ◽  
Carolyn Gotay ◽  
Henning Flechtner ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Decision Making ◽  
Clinical Trials ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Cancer Clinical Trials ◽  
Health Related Quality ◽  
Related Quality ◽  
Health Related

Purpose: The aim of this study was to evaluate whether the inclusion of health-related quality of life (HRQOL), as a part of the trial design in a randomized controlled trial (RCT) setting, has supported clinical decision making for the planning of future medical treatments in prostate cancer. Materials and Methods: A minimum standard checklist for evaluating HRQOL outcomes in cancer clinical trials was devised to assess the quality of the HRQOL reporting and to classify the studies on the grounds of their robustness. It comprises 11 key HRQOL issues grouped into four broader sections: conceptual, measurement, methodology, and interpretation. Relevant studies were identified in a number of databases, including MEDLINE and the Cochrane Controlled Trials Register. Both their HRQOL and traditional clinical reported outcomes were systematically analyzed to evaluate their consistency and their relevance for supporting clinical decision making. Results: Although 54% of the identified studies did not show any differences in traditional clinical end points between treatment arms and 17% showed a difference in overall survival, 74% of the studies showed some difference in terms of HRQOL outcomes. One third of the RCTs provided a comprehensive picture of the whole treatment including HRQOL outcomes to support their conclusions. Conclusion: A minimum set of criteria for assessing the reported outcomes in cancer clinical trials is necessary to make informed decisions in clinical practice. Using a checklist developed for this study, it was found that HRQOL is a valuable source of information in RCTs of treatment in metastatic prostate cancer.

scholarly journals Quality of life of elderly patients with solid tumours undergoing adjuvant cancer therapy: a systematic review

BMJ Open ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. e018101 ◽  
Author(s):  
Karis Kin-Fong Cheng ◽  
Ethel Yee-Ting Lim ◽  
Ravindran Kanesvaran
Keyword(s):  
Quality Of Life ◽  
Systematic Review ◽  
Adjuvant Chemotherapy ◽  
Adjuvant Therapy ◽  
Elderly Patients ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Risk Of Bias ◽  
Solid Tumours

ObjectivesThe measurement of quality of life (QoL) in elderly cancer population is increasingly being recognised as an important element of clinical decision-making and the evaluation of treatment outcome. This systematic review aimed to summarise the evidence of QoL during and after adjuvant therapy in elderly patients with cancer.MethodsA systematic search was conducted of studies published in CINAHL plus, CENTRAL, PubMed, PsycINFO and Web of Science from the inception of these databases to December 2016. Eligible studies included RCTs and non-RCTs in which QoL was measured in elderly patients (aged 65 years or above) with stage I–III solid tumours who were undergoing adjuvant chemotherapy and/or radiotherapy. Because of the heterogeneity and the insufficient data among the included studies, the results were synthesised narratively.ResultsWe included 4 RCTs and 14 non-RCTs on 1785 participants. In all four RCTs, the risk of bias was low or unclear for most items but high for detection. Of the 14 non-RCTs, 5 studies were judged to have a low or moderate risk of bias for all domains, and the other 9 studies had a serious risk of bias in at least one domain. The bias was observed mainly in the confounding and in the selection of participants for the study. For most elderly patients with breast cancer, the non-significant negative change in the QoL was transient. A significant increase in the QoL during the course of temozolomide in elderly patients with glioblastoma but a decreasing trend in QoL after radiotherapy was shown. This review also shows a uniform trend of stable or improved QoL during adjuvant therapy and at follow-up evaluations across the studies with prostate, colon or cervical cancer population.ConclusionsThis review suggests that adjuvant chemotherapy and radiotherapy may not have detrimental effects on QoL in most elderly patients with solid tumours.

Neurological Disorders, Rehabilitation, and Associated Technologies

2019 ◽  
pp. 26-38
Author(s):  
Sateesh Reddy Avutu ◽  
Dinesh Bhatia
Keyword(s):  
Quality Of Life ◽  
Neurological Disorders ◽  
Nuclear Families ◽  
Fundamental Knowledge ◽  
Development Organizations ◽  
Personal Stress ◽  
Neurological Patients ◽  
Rehabilitation Devices

Patients with neurological disorders are increasing globally due to various factors such as change in lifestyle patterns, professional and personal stress, small nuclear families, etc. Neurological rehabilitation is an area focused by the several research and development organizations and scientists from different disciplines to invent new and advanced rehabilitation devices. This chapter starts with the classification of different neurological disorders and their potential causes. The rehabilitation devices available globally for neurological patients with their underlying associated technologies are explained in the chapter. Towards the end of the chapter, the reader can acquire the fundamental knowledge about the different neurological disorders and the mal-functionality associated with the corresponding organs. The utilization of advanced technologies such as artificial intelligence, machine learning, and deep learning by researchers to fabricate neuro rehabilitation devices to improve patients' quality of life (QOL) are discussed in concluding section of the chapter.

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