Clinical Factors for Predicting Neurophysiological Improvements Upon Extension and Flexion in Cervical Spondylotic Myelopathy Patients: A Retrospective Cohort Study

BackgroundCervical extension and flexion are generally thought to be harmful to CSM patients. Contrary to previous notions, a proportion of CSM patients presented DSSEP improvement upon extension and/or flexion. This study aims to determine the prediction criteria for DSSEP improvement upon extension and flexion with clinical and neutral-position imaging.MethodsCSM patients between 2015 and 2019 were retrospectively evaluated. The recorded outcomes were DSSEP changes upon extension and flexion, disease duration, modified Japanese Orthopedic Association (mJOA) score, gait impairment presence, weakness of upper limb muscles, and positive Hoffmann sign designation. The collection of MRI data included the compression ratio, the number of stenotic levels, the Mühle stenosis grade and disc degeneration stage of the most severe segment, and the presence of ligamentum flavum hypertrophy and intramedullary T2WI hyperintensity. Cervical alignment types were evaluated on plain cervical lateral radiographs.ResultsForty-nine patients were finally enrolled. Nine (18.4%) and 11 (22.4%) patients showed DSSEP improvement upon extension and flexion, respectively. Logistic regression analysis showed that an involved segment number ≤ 2 (P=0.018) and a straight/sigmoid cervical alignment (P=0.033) were significant criteria for predicting DSSEP improvement upon extension (probability: 85.7%). Mühle grade 3 (P=0.022) and disease duration ≤ 6 months (P=0.04) were significant criteria for predicting improvement upon flexion (probability: 85.7%).ConclusionsCervical extension and flexion might not necessarily cause deterioration and can even improve some CSM patients' neurological function at DSSEP examination. The involved segment number and cervical alignment were related to extension DSSEP improvement, while the stenosis grade and disease durations were related to flexion improvement. Our work suggests potential significance of educating CSM patients on maintaining individualized neck positions based on their clinical and radiographic findings.BaTrial registrationThe trial was retrospectively registered on April 30th, 2020 and the registration number is "[2020]151".

Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand

Background: Risk assessment criteria for predicting dengue outbreak must be appropriated at village levels. We aimed to develop risk dengue village prediction criteria, predict village dengue risk, and strengthen dengue prevention based on community participation. Methods: This participatory research conducted in Southern Thailand included the following 5 phases: (i) preparing communities in 3 districts; (ii) developing risk dengue village prediction criteria; (iii) applying computer program; (iv) predicting village dengue risk with 75 public health providers in 39 PCUs; and (v) utilizing findings to strengthen dengue prevention activities in 220 villages. Data collecting for prediction used secondary data from primary care units in the past 5 year and current year. Descriptive statistics used calculating criteria and comparing with standard level to adjust score of risk. Results: Risk dengue village assessment criteria had 2 aspects: dengue severity (3 factors) and dengue outbreak opportunity (3 factors). Total scores were 33 points and cut-off of 17 points for high and low dengue risks villages. All criteria were applied using computer program ( http://surat.denguelim.com ). Risk prediction involved stakeholder participation in 220 villages, and used for strengthening dengue prevention activities. The concept of integrated vector management included larval indices surveillance system, garbage management, larval indices level lower than the standard, community capacity activities for dengue prevention, and school-based dengue prevention. The risk prediction criteria and process mobilized villages for dengue prevention activities to decrease morbidity rate. Conclusion: Dengue risk assessment criteria were appropriated within the village, with its smallest unit, the household, included. The data can be utilized at village levels for evaluating dengue outbreak risks.

Technological failures in sheet stamping

The prediction criteria of technological failures in sheet stamping are considered. Particular attention is paid to failures as billet destruction and stability loss during deformation.

Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research

PurposePartial least squares structural equation modeling (PLS-SEM) has become popular in the information systems (IS) field for modeling structural relationships between latent variables as measured by manifest variables. However, while researchers using PLS-SEM routinely stress the causal-predictive nature of their analyses, the model evaluation assessment relies exclusively on criteria designed to assess the path model's explanatory power. To take full advantage of the purpose of causal prediction in PLS-SEM, it is imperative for researchers to comprehend the efficacy of various quality criteria, such as traditional PLS-SEM criteria, model fit, PLSpredict, cross-validated predictive ability test (CVPAT) and model selection criteria.Design/methodology/approachA systematic review was conducted to understand empirical studies employing the use of the causal prediction criteria available for PLS-SEM in the database of Industrial Management and Data Systems (IMDS) and Management Information Systems Quarterly (MISQ). Furthermore, this study discusses the details of each of the procedures for the causal prediction criteria available for PLS-SEM, as well as how these criteria should be interpreted. While the focus of the paper is on demystifying the role of causal prediction modeling in PLS-SEM, the overarching aim is to compare the performance of different quality criteria and to select the appropriate causal-predictive model from a cohort of competing models in the IS field.FindingsThe study found that the traditional PLS-SEM criteria (goodness of fit (GoF) by Tenenhaus, R2 and Q2) and model fit have difficulty determining the appropriate causal-predictive model. In contrast, PLSpredict, CVPAT and model selection criteria (i.e. Bayesian information criterion (BIC), BIC weight, Geweke–Meese criterion (GM), GM weight, HQ and HQC) were found to outperform the traditional criteria in determining the appropriate causal-predictive model, because these criteria provided both in-sample and out-of-sample predictions in PLS-SEM.Originality/valueThis research substantiates the use of the PLSpredict, CVPAT and the model selection criteria (i.e. BIC, BIC weight, GM, GM weight, HQ and HQC). It provides IS researchers and practitioners with the knowledge they need to properly assess, report on and interpret PLS-SEM results when the goal is only causal prediction, thereby contributing to safeguarding the goal of using PLS-SEM in IS studies.