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Development of a Dynamic Nomogram for Predicting the Probability of Satisfactory Recovery after 6 Months for Cervical Traumatic Spinal Cord Injury
OBJECTIVE: Cervical traumatic spinal cord injury (CTSCI) is a seriously disabling disease that severely affects the physical and mental health of patients and imposes a huge economic burden on patients and their families. Accurate identification of the prognosis of CTSCI patients helps clinicians to...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons Australia, Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102307/ https://www.ncbi.nlm.nih.gov/pubmed/36782280 http://dx.doi.org/10.1111/os.13679 |
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author | Yan, Xin He, Yaozhi Jia, Mengxian Yang, Jiali Huang, Kelun Zhang, Peng Lai, Jiaxin Chen, Minghang Fan, Shikang Li, Sheng Fan, Ziwei Teng, Honglin |
author_facet | Yan, Xin He, Yaozhi Jia, Mengxian Yang, Jiali Huang, Kelun Zhang, Peng Lai, Jiaxin Chen, Minghang Fan, Shikang Li, Sheng Fan, Ziwei Teng, Honglin |
author_sort | Yan, Xin |
collection | PubMed |
description | OBJECTIVE: Cervical traumatic spinal cord injury (CTSCI) is a seriously disabling disease that severely affects the physical and mental health of patients and imposes a huge economic burden on patients and their families. Accurate identification of the prognosis of CTSCI patients helps clinicians to design individualized treatment plans for patients. For this purpose, a dynamic nomogram was developed to predict the recovery of CTSCI patients after 6 months. METHODS: We retrospectively included 475 patients with CTSCI in our institution between March 2013 and January 2022. The outcome variable of the current study was a satisfactory recovery of patients with CTSCI at 6 months. Univariate analyses and univariate logistic regression analyses were used to assess the factors affecting the prognosis of patients with CTSCI. Subsequently, variables (P < 0.05) were included in the multivariate logistic regression analysis to evaluate these factors further. Eventually, a nomogram model was constructed according to these independent risk factors. The concordance index (C‐index) and the calibration curve were utilized to assess the model's predictive ability. The discriminating capacity of the prediction model was measured by the receiver operating characteristic (ROC) area under the curve (AUC). One hundred nine patients were randomly selected from 475 patients to serve as the center's internal validation test cohort. RESULTS: The multivariate logistic regression model further screened out six independent factors that impact the recovery of patients with CTSCI. Including admission to the American Spinal Injury Association Impairment Scale (AIS) grade, the length of high signal in the spinal cord, maximum spinal cord compression (MSCC), spinal segment fractured, admission time, and hormonal therapy within 8 h after injury. A nomogram prediction model was developed based on the six independent factors above. In the training cohort, the AUC of the nomogram that included these predictors was 0.879, while in the test cohort, it was 0.824. The nomogram C‐index incorporating these predictors was 0.872 in the training cohort and 0.813 in the test cohort, while the calibration curves for both cohorts also indicated good consistency. Furthermore, this nomogram was converted into a Web‐based calculator, which provided individual probabilities of recovery to be generated for individuals with CTSCI after 6 months and displayed in a graphical format. CONCLUSION: The nomogram, including ASIA grade, the length of high signal in the spinal cord, MSCC, spinal segment fractured, admission time, and hormonal therapy within 8 h after injury, is a promising model to predict the probability of content recovery in patients with CTSCI. This nomogram assists clinicians in stratifying patients with CTSCI, enhancing evidence‐based decision‐making, and individualizing the most appropriate treatment. |
format | Online Article Text |
id | pubmed-10102307 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley & Sons Australia, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-101023072023-04-15 Development of a Dynamic Nomogram for Predicting the Probability of Satisfactory Recovery after 6 Months for Cervical Traumatic Spinal Cord Injury Yan, Xin He, Yaozhi Jia, Mengxian Yang, Jiali Huang, Kelun Zhang, Peng Lai, Jiaxin Chen, Minghang Fan, Shikang Li, Sheng Fan, Ziwei Teng, Honglin Orthop Surg Clinical Articles OBJECTIVE: Cervical traumatic spinal cord injury (CTSCI) is a seriously disabling disease that severely affects the physical and mental health of patients and imposes a huge economic burden on patients and their families. Accurate identification of the prognosis of CTSCI patients helps clinicians to design individualized treatment plans for patients. For this purpose, a dynamic nomogram was developed to predict the recovery of CTSCI patients after 6 months. METHODS: We retrospectively included 475 patients with CTSCI in our institution between March 2013 and January 2022. The outcome variable of the current study was a satisfactory recovery of patients with CTSCI at 6 months. Univariate analyses and univariate logistic regression analyses were used to assess the factors affecting the prognosis of patients with CTSCI. Subsequently, variables (P < 0.05) were included in the multivariate logistic regression analysis to evaluate these factors further. Eventually, a nomogram model was constructed according to these independent risk factors. The concordance index (C‐index) and the calibration curve were utilized to assess the model's predictive ability. The discriminating capacity of the prediction model was measured by the receiver operating characteristic (ROC) area under the curve (AUC). One hundred nine patients were randomly selected from 475 patients to serve as the center's internal validation test cohort. RESULTS: The multivariate logistic regression model further screened out six independent factors that impact the recovery of patients with CTSCI. Including admission to the American Spinal Injury Association Impairment Scale (AIS) grade, the length of high signal in the spinal cord, maximum spinal cord compression (MSCC), spinal segment fractured, admission time, and hormonal therapy within 8 h after injury. A nomogram prediction model was developed based on the six independent factors above. In the training cohort, the AUC of the nomogram that included these predictors was 0.879, while in the test cohort, it was 0.824. The nomogram C‐index incorporating these predictors was 0.872 in the training cohort and 0.813 in the test cohort, while the calibration curves for both cohorts also indicated good consistency. Furthermore, this nomogram was converted into a Web‐based calculator, which provided individual probabilities of recovery to be generated for individuals with CTSCI after 6 months and displayed in a graphical format. CONCLUSION: The nomogram, including ASIA grade, the length of high signal in the spinal cord, MSCC, spinal segment fractured, admission time, and hormonal therapy within 8 h after injury, is a promising model to predict the probability of content recovery in patients with CTSCI. This nomogram assists clinicians in stratifying patients with CTSCI, enhancing evidence‐based decision‐making, and individualizing the most appropriate treatment. John Wiley & Sons Australia, Ltd 2023-02-13 /pmc/articles/PMC10102307/ /pubmed/36782280 http://dx.doi.org/10.1111/os.13679 Text en © 2023 The Authors. Orthopaedic Surgery published by Tianjin Hospital and John Wiley & Sons Australia, Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Clinical Articles Yan, Xin He, Yaozhi Jia, Mengxian Yang, Jiali Huang, Kelun Zhang, Peng Lai, Jiaxin Chen, Minghang Fan, Shikang Li, Sheng Fan, Ziwei Teng, Honglin Development of a Dynamic Nomogram for Predicting the Probability of Satisfactory Recovery after 6 Months for Cervical Traumatic Spinal Cord Injury |
title | Development of a Dynamic Nomogram for Predicting the Probability of Satisfactory Recovery after 6 Months for Cervical Traumatic Spinal Cord Injury |
title_full | Development of a Dynamic Nomogram for Predicting the Probability of Satisfactory Recovery after 6 Months for Cervical Traumatic Spinal Cord Injury |
title_fullStr | Development of a Dynamic Nomogram for Predicting the Probability of Satisfactory Recovery after 6 Months for Cervical Traumatic Spinal Cord Injury |
title_full_unstemmed | Development of a Dynamic Nomogram for Predicting the Probability of Satisfactory Recovery after 6 Months for Cervical Traumatic Spinal Cord Injury |
title_short | Development of a Dynamic Nomogram for Predicting the Probability of Satisfactory Recovery after 6 Months for Cervical Traumatic Spinal Cord Injury |
title_sort | development of a dynamic nomogram for predicting the probability of satisfactory recovery after 6 months for cervical traumatic spinal cord injury |
topic | Clinical Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102307/ https://www.ncbi.nlm.nih.gov/pubmed/36782280 http://dx.doi.org/10.1111/os.13679 |
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