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      A Clinical Predictive Nomogram for Traumatic Brain Parenchyma Hematoma Progression

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          Abstract

          Introduction

          Acute traumatic intraparenchymal hematoma (tICH) expansion is a major cause of clinical deterioration after brain contusion. Here, an accurate prediction tool for acute tICH expansion is proposed.

          Methods

          A multicenter hospital-based study for multivariable prediction model was conducted among patients (889 patients in a development dataset and 264 individuals in an external validation dataset) with initial and follow-up computed tomography (CT) imaging for tICH volume evaluation. Semi-automated software was employed to assess tICH expansion. Two multivariate predictive models for acute tICH expansion were developed and externally validated.

          Results

          A total of 198 (22.27%) individuals had remarkable acute tICH expansion. The novel Traumatic Parenchymatous Hematoma Expansion Aid (TPHEA) model retained several variables, including age, coagulopathy, baseline tICH volume, time to baseline CT time, subdural hemorrhage, a novel imaging marker of multihematoma fuzzy sign, and an inflammatory index of monocyte-to-lymphocyte ratio. Compared with multihematoma fuzzy sign, monocyte-to-lymphocyte ratio, and the basic model, the TPHEA model exhibited optimal discrimination, calibration, and clinical net benefits for patients with acute tICH expansion. A TPHEA nomogram was subsequently introduced from this model to facilitate clinical application. In an external dataset, this device showed good predicting performance for acute tICH expansion.

          Conclusions

          The main predictive factors in the TPHEA nomogram are the monocyte-to-lymphocyte ratio, baseline tICH volume, and multihematoma fuzzy sign. This user-friendly tool can estimate acute tICH expansion and optimize personalized treatments for individuals with brain contusion.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s40120-021-00306-8.

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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            mice: Multivariate Imputation by Chained Equations inR

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              Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration

              The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.
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                Author and article information

                Contributors
                jtsheng@stu.edu.cn
                wqchen@stu.edu.cn
                Journal
                Neurol Ther
                Neurol Ther
                Neurology and Therapy
                Springer Healthcare (Cheshire )
                2193-8253
                2193-6536
                2 December 2021
                2 December 2021
                March 2022
                : 11
                : 1
                : 185-203
                Affiliations
                [1 ]GRID grid.411679.c, ISNI 0000 0004 0605 3373, Department of Microbiology and Immunology, Guangdong Provincial Key Laboratory of Infectious Disease and Molecular Immunopathology, , Shantou University Medical College, ; 22 Xinling Road, Shantou, 515041 Guangdong China
                [2 ]GRID grid.412614.4, ISNI 0000 0004 6020 6107, Department of Neurosurgery, , First Affiliated Hospital of Shantou University Medical College, ; 57 Changping Road, Shantou, 515041 Guangdong China
                [3 ]GRID grid.452836.e, ISNI 0000 0004 1798 1271, Department of Neurosurgery, , Second Affiliated Hospital of Shantou University Medical College, ; Shantou, Guangdong China
                [4 ]GRID grid.12981.33, ISNI 0000 0001 2360 039X, Department of Neurosurgery, , Affiliated Jieyang Hospital of Sun Yat-Sen University, ; Jieyang, Guangdong China
                [5 ]GRID grid.12955.3a, ISNI 0000 0001 2264 7233, Department of Neurosurgery, , Affiliated East Hospital of Xiamen University Medical College, ; Fuzhou, Fujian China
                Author information
                http://orcid.org/0000-0002-2612-0890
                Article
                306
                10.1007/s40120-021-00306-8
                8857351
                34855160
                4180ffe9-d67f-4bc7-a6c8-d83cf2f3ee04
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 10 July 2021
                : 22 November 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002858, China Postdoctoral Science Foundation;
                Award ID: 2018M633091
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003453, Natural Science Foundation of Guangdong Province;
                Award ID: 2019A1515010649
                Award Recipient :
                Funded by: Medical Scientific Research Foundation of Guangdong Province
                Award ID: A2017168
                Award Recipient :
                Categories
                Original Research
                Custom metadata
                © The Author(s) 2022

                cerebral contusion,hematoma expansion,nomogram,multihematoma fuzzy sign,monocyte-to-lymphocyte ratio

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