Predicting the Severity of Acute Appendicitis of Young Children (<3 Years Old): Development and Assessment of a New Prediction Nomogram
Objective: There is a lack of assessment methods of acute appendicitis in little children. The purpose of this study was to develop and internally validate a nomogram for predicting the severity of acute appendicitis of young children (<3 years old).Methods: We develop a prediction model base...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:da84eb91fe2045fcb0fcbb9d55d93b7e2021-11-18T07:49:49ZPredicting the Severity of Acute Appendicitis of Young Children (<3 Years Old): Development and Assessment of a New Prediction Nomogram2296-236010.3389/fped.2021.763125https://doaj.org/article/da84eb91fe2045fcb0fcbb9d55d93b7e2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fped.2021.763125/fullhttps://doaj.org/toc/2296-2360Objective: There is a lack of assessment methods of acute appendicitis in little children. The purpose of this study was to develop and internally validate a nomogram for predicting the severity of acute appendicitis of young children (<3 years old).Methods: We develop a prediction model based on a training dataset of 121 patients (<3 years old) with acute appendicitis. Admission information was collected between January 2010 and January 2021, which contained demographic characteristic, laboratory examinations, treatment and pathology type, etc. Logistic regression analysis was used to identify independent risk factors and establish the predictive model. C-index and calibration curves were applied to evaluate the performance of the nomogram. Then corrected C-index was calculated to conduct internal verification by using the bootstrapping validation. Decision curve analysis determined clinical application of the prediction model.Results: Predictors contained in the prediction nomogram included weight for age, onset time (from developing symptoms to hospital), admission temperature, leukocyte count, neutrophil ratio, and total bilirubin. Logistic regression analysis showed that weight for age (X1) < -2.32 SD (P = 0.046), onset time (X2) > 2.5 days (P = 0.044), admission temperature (X3) > 38.5°C (P = 0.009), leukocyte count (X4) > 12.185*109/L (P = 0.045), neutrophil ratio (X5) > 68.7% (P = 0.029), and total bilirubin (X6) > 9.05 μmol/L (P = 0.035) were found to be significant for predicting the severity of appendicitis. The logistic regression equation was logit (P) = −0.149X1 + 0.51X2 + 1.734X3 + 0.238X4 + 0.061X5 + 0.098X6 – 75.229. C-index of nomogram was calculated at 0.8948 (95% Cl: 0.8332–0.9567) and it still was 0.8867 through bootstrapping validation. Decision curve analysis showed that when the threshold probability ranged from 14 to 88%, there is a net benefit of using this prediction model for severity of appendicitis in little children.Conclusion: This novel nomogram incorporating the weight for age, onset time, admission temperature, leukocyte count, neutrophil ratio, and total bilirubin could be conveniently used to estimate the severity of appendicitis of young children <3 years old) and determine appropriate treatment options in time.Yang ChenYang ChenZhiyong WangDong XiaoHongwu ZengXiaopeng MaFrontiers Media S.A.articlecomplicated appendicitisyoung childrenlaboratory examinationretrospective analysisprediction modelPediatricsRJ1-570ENFrontiers in Pediatrics, Vol 9 (2021) |
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complicated appendicitis young children laboratory examination retrospective analysis prediction model Pediatrics RJ1-570 |
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complicated appendicitis young children laboratory examination retrospective analysis prediction model Pediatrics RJ1-570 Yang Chen Yang Chen Zhiyong Wang Dong Xiao Hongwu Zeng Xiaopeng Ma Predicting the Severity of Acute Appendicitis of Young Children (<3 Years Old): Development and Assessment of a New Prediction Nomogram |
description |
Objective: There is a lack of assessment methods of acute appendicitis in little children. The purpose of this study was to develop and internally validate a nomogram for predicting the severity of acute appendicitis of young children (<3 years old).Methods: We develop a prediction model based on a training dataset of 121 patients (<3 years old) with acute appendicitis. Admission information was collected between January 2010 and January 2021, which contained demographic characteristic, laboratory examinations, treatment and pathology type, etc. Logistic regression analysis was used to identify independent risk factors and establish the predictive model. C-index and calibration curves were applied to evaluate the performance of the nomogram. Then corrected C-index was calculated to conduct internal verification by using the bootstrapping validation. Decision curve analysis determined clinical application of the prediction model.Results: Predictors contained in the prediction nomogram included weight for age, onset time (from developing symptoms to hospital), admission temperature, leukocyte count, neutrophil ratio, and total bilirubin. Logistic regression analysis showed that weight for age (X1) < -2.32 SD (P = 0.046), onset time (X2) > 2.5 days (P = 0.044), admission temperature (X3) > 38.5°C (P = 0.009), leukocyte count (X4) > 12.185*109/L (P = 0.045), neutrophil ratio (X5) > 68.7% (P = 0.029), and total bilirubin (X6) > 9.05 μmol/L (P = 0.035) were found to be significant for predicting the severity of appendicitis. The logistic regression equation was logit (P) = −0.149X1 + 0.51X2 + 1.734X3 + 0.238X4 + 0.061X5 + 0.098X6 – 75.229. C-index of nomogram was calculated at 0.8948 (95% Cl: 0.8332–0.9567) and it still was 0.8867 through bootstrapping validation. Decision curve analysis showed that when the threshold probability ranged from 14 to 88%, there is a net benefit of using this prediction model for severity of appendicitis in little children.Conclusion: This novel nomogram incorporating the weight for age, onset time, admission temperature, leukocyte count, neutrophil ratio, and total bilirubin could be conveniently used to estimate the severity of appendicitis of young children <3 years old) and determine appropriate treatment options in time. |
format |
article |
author |
Yang Chen Yang Chen Zhiyong Wang Dong Xiao Hongwu Zeng Xiaopeng Ma |
author_facet |
Yang Chen Yang Chen Zhiyong Wang Dong Xiao Hongwu Zeng Xiaopeng Ma |
author_sort |
Yang Chen |
title |
Predicting the Severity of Acute Appendicitis of Young Children (<3 Years Old): Development and Assessment of a New Prediction Nomogram |
title_short |
Predicting the Severity of Acute Appendicitis of Young Children (<3 Years Old): Development and Assessment of a New Prediction Nomogram |
title_full |
Predicting the Severity of Acute Appendicitis of Young Children (<3 Years Old): Development and Assessment of a New Prediction Nomogram |
title_fullStr |
Predicting the Severity of Acute Appendicitis of Young Children (<3 Years Old): Development and Assessment of a New Prediction Nomogram |
title_full_unstemmed |
Predicting the Severity of Acute Appendicitis of Young Children (<3 Years Old): Development and Assessment of a New Prediction Nomogram |
title_sort |
predicting the severity of acute appendicitis of young children (<3 years old): development and assessment of a new prediction nomogram |
publisher |
Frontiers Media S.A. |
publishDate |
2021 |
url |
https://doaj.org/article/da84eb91fe2045fcb0fcbb9d55d93b7e |
work_keys_str_mv |
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