Development and Validation of a Dynamic Nomogram to Predict the Risk of Neonatal White Matter Damage
PurposeWhite matter damage (WMD) was defined as the appearance of rough and uneven echo enhancement in the white matter around the ventricle. The aim of this study was to develop and validate a risk prediction model for neonatal WMD.Materials and MethodsWe collected data for 1,733 infants hospitaliz...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-02-01
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| Series: | Frontiers in Human Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnhum.2020.584236/full |
| _version_ | 1818849264531406848 |
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| author | Wenjun Cao Chenghan Luo Mengyuan Lei Min Shen Wenqian Ding Mengmeng Wang Min Song Jian Ge Qian Zhang |
| author_facet | Wenjun Cao Chenghan Luo Mengyuan Lei Min Shen Wenqian Ding Mengmeng Wang Min Song Jian Ge Qian Zhang |
| author_sort | Wenjun Cao |
| collection | DOAJ |
| description | PurposeWhite matter damage (WMD) was defined as the appearance of rough and uneven echo enhancement in the white matter around the ventricle. The aim of this study was to develop and validate a risk prediction model for neonatal WMD.Materials and MethodsWe collected data for 1,733 infants hospitalized at the Department of Neonatology at The First Affiliated Hospital of Zhengzhou University from 2017 to 2020. Infants were randomly assigned to training (n = 1,216) or validation (n = 517) cohorts at a ratio of 7:3. Multivariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to establish a risk prediction model and web-based risk calculator based on the training cohort data. The predictive accuracy of the model was verified in the validation cohort.ResultsWe identified four variables as independent risk factors for brain WMD in neonates by multivariate logistic regression and LASSO analysis, including gestational age, fetal distress, prelabor rupture of membranes, and use of corticosteroids. These were used to establish a risk prediction nomogram and web-based calculator (https://caowenjun.shinyapps.io/dynnomapp/). The C-index of the training and validation sets was 0.898 (95% confidence interval: 0.8745–0.9215) and 0.887 (95% confidence interval: 0.8478–0.9262), respectively. Decision tree analysis showed that the model was highly effective in the threshold range of 1–61%. The sensitivity and specificity of the model were 82.5 and 81.7%, respectively, and the cutoff value was 0.099.ConclusionThis is the first study describing the use of a nomogram and web-based calculator to predict the risk of WMD in neonates. The web-based calculator increases the applicability of the predictive model and is a convenient tool for doctors at primary hospitals and outpatient clinics, family doctors, and even parents to identify high-risk births early on and implementing appropriate interventions while avoiding excessive treatment of low-risk patients. |
| first_indexed | 2024-12-19T06:30:28Z |
| format | Article |
| id | doaj.art-0a965383c1f04817b44de145f4e4d1c1 |
| institution | Directory Open Access Journal |
| issn | 1662-5161 |
| language | English |
| last_indexed | 2024-12-19T06:30:28Z |
| publishDate | 2021-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Human Neuroscience |
| spelling | doaj.art-0a965383c1f04817b44de145f4e4d1c12022-12-21T20:32:24ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612021-02-011410.3389/fnhum.2020.584236584236Development and Validation of a Dynamic Nomogram to Predict the Risk of Neonatal White Matter DamageWenjun CaoChenghan LuoMengyuan LeiMin ShenWenqian DingMengmeng WangMin SongJian GeQian ZhangPurposeWhite matter damage (WMD) was defined as the appearance of rough and uneven echo enhancement in the white matter around the ventricle. The aim of this study was to develop and validate a risk prediction model for neonatal WMD.Materials and MethodsWe collected data for 1,733 infants hospitalized at the Department of Neonatology at The First Affiliated Hospital of Zhengzhou University from 2017 to 2020. Infants were randomly assigned to training (n = 1,216) or validation (n = 517) cohorts at a ratio of 7:3. Multivariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to establish a risk prediction model and web-based risk calculator based on the training cohort data. The predictive accuracy of the model was verified in the validation cohort.ResultsWe identified four variables as independent risk factors for brain WMD in neonates by multivariate logistic regression and LASSO analysis, including gestational age, fetal distress, prelabor rupture of membranes, and use of corticosteroids. These were used to establish a risk prediction nomogram and web-based calculator (https://caowenjun.shinyapps.io/dynnomapp/). The C-index of the training and validation sets was 0.898 (95% confidence interval: 0.8745–0.9215) and 0.887 (95% confidence interval: 0.8478–0.9262), respectively. Decision tree analysis showed that the model was highly effective in the threshold range of 1–61%. The sensitivity and specificity of the model were 82.5 and 81.7%, respectively, and the cutoff value was 0.099.ConclusionThis is the first study describing the use of a nomogram and web-based calculator to predict the risk of WMD in neonates. The web-based calculator increases the applicability of the predictive model and is a convenient tool for doctors at primary hospitals and outpatient clinics, family doctors, and even parents to identify high-risk births early on and implementing appropriate interventions while avoiding excessive treatment of low-risk patients.https://www.frontiersin.org/articles/10.3389/fnhum.2020.584236/fullneonatalwhite matter damagenomogramprediction modelperinatalweb-based calculator |
| spellingShingle | Wenjun Cao Chenghan Luo Mengyuan Lei Min Shen Wenqian Ding Mengmeng Wang Min Song Jian Ge Qian Zhang Development and Validation of a Dynamic Nomogram to Predict the Risk of Neonatal White Matter Damage Frontiers in Human Neuroscience neonatal white matter damage nomogram prediction model perinatal web-based calculator |
| title | Development and Validation of a Dynamic Nomogram to Predict the Risk of Neonatal White Matter Damage |
| title_full | Development and Validation of a Dynamic Nomogram to Predict the Risk of Neonatal White Matter Damage |
| title_fullStr | Development and Validation of a Dynamic Nomogram to Predict the Risk of Neonatal White Matter Damage |
| title_full_unstemmed | Development and Validation of a Dynamic Nomogram to Predict the Risk of Neonatal White Matter Damage |
| title_short | Development and Validation of a Dynamic Nomogram to Predict the Risk of Neonatal White Matter Damage |
| title_sort | development and validation of a dynamic nomogram to predict the risk of neonatal white matter damage |
| topic | neonatal white matter damage nomogram prediction model perinatal web-based calculator |
| url | https://www.frontiersin.org/articles/10.3389/fnhum.2020.584236/full |
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