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Development and validation of a nomogram for predicting in-hospital mortality of patients with cervical spine fractures without spinal cord injury.

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Title: Development and validation of a nomogram for predicting in-hospital mortality of patients with cervical spine fractures without spinal cord injury.
Authors: Xing, Zhibin, Cai, Lingli, Wu, Yuxuan, Shen, Pengfei, Fu, Xiaochen, Xu, Yiwen, Wang, Jing
Source: European Journal of Medical Research; 1/29/2024, Vol. 29, p1-9, 9p
Subject Terms: VERTEBRAL fractures, CERVICAL vertebrae, HOSPITAL mortality, NOMOGRAPHY (Mathematics), SYSTOLIC blood pressure, SPINAL cord injuries
Abstract: Background: The incidence of cervical spine fractures is increasing every day, causing a huge burden on society. This study aimed to develop and verify a nomogram to predict the in-hospital mortality of patients with cervical spine fractures without spinal cord injury. This could help clinicians understand the clinical outcome of such patients at an early stage and make appropriate decisions to improve their prognosis. Methods: This study included 394 patients with cervical spine fractures from the Medical Information Mart for Intensive Care III database, and 40 clinical indicators of each patient on the first day of admission to the intensive care unit were collected. The independent risk factors were screened using the Least Absolute Shrinkage and Selection Operator regression analysis method, a multi-factor logistic regression model was established, nomograms were developed, and internal validation was performed. A receiver operating characteristic (ROC) curve was drawn, and the area under the ROC curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were calculated to evaluate the discrimination of the model. Moreover, the consistency between the actual probability and predicted probability was reflected using the calibration curve and Hosmer–Lemeshow (HL) test. A decision curve analysis (DCA) was performed, and the nomogram was compared with the scoring system commonly used in clinical practice to evaluate the clinical net benefit. Results: The nomogram indicators included the systolic blood pressure, oxygen saturation, respiratory rate, bicarbonate, and simplified acute physiology score (SAPS) II. The results showed that our model had satisfactory predictive ability, with an AUC of 0.907 (95% confidence interval [CI] = 0.853–0.961) and 0.856 (95% CI = 0.746–0.967) in the training set and validation set, respectively. Compared with the SAPS-II system, the NRI values of the training and validation sets of our model were 0.543 (95% CI = 0.147–0.940) and 0.784 (95% CI = 0.282–1.286), respectively. The IDI values of the training and validation sets were 0.064 (95% CI = 0.004–0.123; P = 0.037) and 0.103 (95% CI = 0.002–0.203; P = 0.046), respectively. The calibration plot and HL test results confirmed that our model prediction results showed good agreement with the actual results, where the HL test values of the training and validation sets were P = 0.8 and P = 0.95, respectively. The DCA curve revealed that our model had better clinical net benefit than the SAPS-II system. Conclusion: We explored the in-hospital mortality of patients with cervical spine fractures without spinal cord injury and constructed a nomogram to predict their prognosis. This could help doctors assess the patient's status and implement interventions to improve prognosis accordingly. [ABSTRACT FROM AUTHOR]
Copyright of European Journal of Medical Research is the property of BioMed Central and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Label: Title
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  Data: Development and validation of a nomogram for predicting in-hospital mortality of patients with cervical spine fractures without spinal cord injury.
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  Data: <searchLink fieldCode="AR" term="%22Xing%2C+Zhibin%22">Xing, Zhibin</searchLink><br /><searchLink fieldCode="AR" term="%22Cai%2C+Lingli%22">Cai, Lingli</searchLink><br /><searchLink fieldCode="AR" term="%22Wu%2C+Yuxuan%22">Wu, Yuxuan</searchLink><br /><searchLink fieldCode="AR" term="%22Shen%2C+Pengfei%22">Shen, Pengfei</searchLink><br /><searchLink fieldCode="AR" term="%22Fu%2C+Xiaochen%22">Fu, Xiaochen</searchLink><br /><searchLink fieldCode="AR" term="%22Xu%2C+Yiwen%22">Xu, Yiwen</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Jing%22">Wang, Jing</searchLink>
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  Label: Source
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  Data: European Journal of Medical Research; 1/29/2024, Vol. 29, p1-9, 9p
– Name: Subject
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  Group: Su
  Data: <searchLink fieldCode="DE" term="%22VERTEBRAL+fractures%22">VERTEBRAL fractures</searchLink><br /><searchLink fieldCode="DE" term="%22CERVICAL+vertebrae%22">CERVICAL vertebrae</searchLink><br /><searchLink fieldCode="DE" term="%22HOSPITAL+mortality%22">HOSPITAL mortality</searchLink><br /><searchLink fieldCode="DE" term="%22NOMOGRAPHY+%28Mathematics%29%22">NOMOGRAPHY (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22SYSTOLIC+blood+pressure%22">SYSTOLIC blood pressure</searchLink><br /><searchLink fieldCode="DE" term="%22SPINAL+cord+injuries%22">SPINAL cord injuries</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: The incidence of cervical spine fractures is increasing every day, causing a huge burden on society. This study aimed to develop and verify a nomogram to predict the in-hospital mortality of patients with cervical spine fractures without spinal cord injury. This could help clinicians understand the clinical outcome of such patients at an early stage and make appropriate decisions to improve their prognosis. Methods: This study included 394 patients with cervical spine fractures from the Medical Information Mart for Intensive Care III database, and 40 clinical indicators of each patient on the first day of admission to the intensive care unit were collected. The independent risk factors were screened using the Least Absolute Shrinkage and Selection Operator regression analysis method, a multi-factor logistic regression model was established, nomograms were developed, and internal validation was performed. A receiver operating characteristic (ROC) curve was drawn, and the area under the ROC curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were calculated to evaluate the discrimination of the model. Moreover, the consistency between the actual probability and predicted probability was reflected using the calibration curve and Hosmer–Lemeshow (HL) test. A decision curve analysis (DCA) was performed, and the nomogram was compared with the scoring system commonly used in clinical practice to evaluate the clinical net benefit. Results: The nomogram indicators included the systolic blood pressure, oxygen saturation, respiratory rate, bicarbonate, and simplified acute physiology score (SAPS) II. The results showed that our model had satisfactory predictive ability, with an AUC of 0.907 (95% confidence interval [CI] = 0.853–0.961) and 0.856 (95% CI = 0.746–0.967) in the training set and validation set, respectively. Compared with the SAPS-II system, the NRI values of the training and validation sets of our model were 0.543 (95% CI = 0.147–0.940) and 0.784 (95% CI = 0.282–1.286), respectively. The IDI values of the training and validation sets were 0.064 (95% CI = 0.004–0.123; P = 0.037) and 0.103 (95% CI = 0.002–0.203; P = 0.046), respectively. The calibration plot and HL test results confirmed that our model prediction results showed good agreement with the actual results, where the HL test values of the training and validation sets were P = 0.8 and P = 0.95, respectively. The DCA curve revealed that our model had better clinical net benefit than the SAPS-II system. Conclusion: We explored the in-hospital mortality of patients with cervical spine fractures without spinal cord injury and constructed a nomogram to predict their prognosis. This could help doctors assess the patient's status and implement interventions to improve prognosis accordingly. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of European Journal of Medical Research is the property of BioMed Central and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1186/s40001-024-01655-4
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        Text: English
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      – SubjectFull: VERTEBRAL fractures
        Type: general
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              Text: 1/29/2024
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