Application of decision tree model in diagnosis of mycoplasma pneumoniae pneumonia with plastic bronchitis
Background To establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the application value of decision tree model in the auxiliary diagnosis of children. Methods A retrospective study was conducted to collect the cl...
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| Vydané v: | Italian journal of pediatrics Ročník 51; číslo 1; s. 95 - 7 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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London
BioMed Central
24.03.2025
Springer Nature B.V BMC |
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| ISSN: | 1824-7288, 1720-8424, 1824-7288 |
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| Abstract | Background
To establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the application value of decision tree model in the auxiliary diagnosis of children.
Methods
A retrospective study was conducted to collect the clinical data of 214 children who met the admission criteria in Fujian Children’s Hospital from June 2022 to June 2024, and they were divided into plastic bronchitis group (
n
= 66) and non-plastic bronchitis group (
n
= 148). Using R language, 70% of the data from each group of patients was randomly selected for training the model using decision tree algorithm analysis, thus generating a clinical diagnostic decision tree for Mycoplasma pneumoniae (MP) combined with PB. The generated decision tree model was validated on the validation sample dataset and the detection effect value of the model was calculated.
Result
In this study, a total of 22 indicators were employed to build the decision tree diagnostic model. Univariate statistical analysis was carried out prior to the model construction, and it was discovered that the differences of 13 indicators between the molded group and the non-molded group were statistically significant. A decision tree model with D-dimer ≥ 1.7ug/mL, C-reactive protein ≥ 15 mg/L, drug resistance or not, and serum ferritin<137 mg/L was constructed in the training sample dataset of the molded group and the non-molded group. The sensitivity of the decision tree model was 0.884, which was verified in the dataset of the remolded group and the non-molded group. The specificity was 0.727, and the area under the receiver operating characteristic curve was 0.831.
Conclusion
Decision tree model can provide reference for the application of auxiliary diagnosis in children with mycoplasma pneumoniae pneumonia complicated with plastic bronchitis. The model has good discriminative ability in general, and is worthy of clinical application and further study. |
|---|---|
| AbstractList | To establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the application value of decision tree model in the auxiliary diagnosis of children.
A retrospective study was conducted to collect the clinical data of 214 children who met the admission criteria in Fujian Children's Hospital from June 2022 to June 2024, and they were divided into plastic bronchitis group (n = 66) and non-plastic bronchitis group (n = 148). Using R language, 70% of the data from each group of patients was randomly selected for training the model using decision tree algorithm analysis, thus generating a clinical diagnostic decision tree for Mycoplasma pneumoniae (MP) combined with PB. The generated decision tree model was validated on the validation sample dataset and the detection effect value of the model was calculated.
In this study, a total of 22 indicators were employed to build the decision tree diagnostic model. Univariate statistical analysis was carried out prior to the model construction, and it was discovered that the differences of 13 indicators between the molded group and the non-molded group were statistically significant. A decision tree model with D-dimer ≥ 1.7ug/mL, C-reactive protein ≥ 15 mg/L, drug resistance or not, and serum ferritin<137 mg/L was constructed in the training sample dataset of the molded group and the non-molded group. The sensitivity of the decision tree model was 0.884, which was verified in the dataset of the remolded group and the non-molded group. The specificity was 0.727, and the area under the receiver operating characteristic curve was 0.831.
Decision tree model can provide reference for the application of auxiliary diagnosis in children with mycoplasma pneumoniae pneumonia complicated with plastic bronchitis. The model has good discriminative ability in general, and is worthy of clinical application and further study. To establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the application value of decision tree model in the auxiliary diagnosis of children.BACKGROUNDTo establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the application value of decision tree model in the auxiliary diagnosis of children.A retrospective study was conducted to collect the clinical data of 214 children who met the admission criteria in Fujian Children's Hospital from June 2022 to June 2024, and they were divided into plastic bronchitis group (n = 66) and non-plastic bronchitis group (n = 148). Using R language, 70% of the data from each group of patients was randomly selected for training the model using decision tree algorithm analysis, thus generating a clinical diagnostic decision tree for Mycoplasma pneumoniae (MP) combined with PB. The generated decision tree model was validated on the validation sample dataset and the detection effect value of the model was calculated.METHODSA retrospective study was conducted to collect the clinical data of 214 children who met the admission criteria in Fujian Children's Hospital from June 2022 to June 2024, and they were divided into plastic bronchitis group (n = 66) and non-plastic bronchitis group (n = 148). Using R language, 70% of the data from each group of patients was randomly selected for training the model using decision tree algorithm analysis, thus generating a clinical diagnostic decision tree for Mycoplasma pneumoniae (MP) combined with PB. The generated decision tree model was validated on the validation sample dataset and the detection effect value of the model was calculated.In this study, a total of 22 indicators were employed to build the decision tree diagnostic model. Univariate statistical analysis was carried out prior to the model construction, and it was discovered that the differences of 13 indicators between the molded group and the non-molded group were statistically significant. A decision tree model with D-dimer ≥ 1.7ug/mL, C-reactive protein ≥ 15 mg/L, drug resistance or not, and serum ferritin<137 mg/L was constructed in the training sample dataset of the molded group and the non-molded group. The sensitivity of the decision tree model was 0.884, which was verified in the dataset of the remolded group and the non-molded group. The specificity was 0.727, and the area under the receiver operating characteristic curve was 0.831.RESULTIn this study, a total of 22 indicators were employed to build the decision tree diagnostic model. Univariate statistical analysis was carried out prior to the model construction, and it was discovered that the differences of 13 indicators between the molded group and the non-molded group were statistically significant. A decision tree model with D-dimer ≥ 1.7ug/mL, C-reactive protein ≥ 15 mg/L, drug resistance or not, and serum ferritin<137 mg/L was constructed in the training sample dataset of the molded group and the non-molded group. The sensitivity of the decision tree model was 0.884, which was verified in the dataset of the remolded group and the non-molded group. The specificity was 0.727, and the area under the receiver operating characteristic curve was 0.831.Decision tree model can provide reference for the application of auxiliary diagnosis in children with mycoplasma pneumoniae pneumonia complicated with plastic bronchitis. The model has good discriminative ability in general, and is worthy of clinical application and further study.CONCLUSIONDecision tree model can provide reference for the application of auxiliary diagnosis in children with mycoplasma pneumoniae pneumonia complicated with plastic bronchitis. The model has good discriminative ability in general, and is worthy of clinical application and further study. BackgroundTo establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the application value of decision tree model in the auxiliary diagnosis of children.MethodsA retrospective study was conducted to collect the clinical data of 214 children who met the admission criteria in Fujian Children’s Hospital from June 2022 to June 2024, and they were divided into plastic bronchitis group (n = 66) and non-plastic bronchitis group (n = 148). Using R language, 70% of the data from each group of patients was randomly selected for training the model using decision tree algorithm analysis, thus generating a clinical diagnostic decision tree for Mycoplasma pneumoniae (MP) combined with PB. The generated decision tree model was validated on the validation sample dataset and the detection effect value of the model was calculated.ResultIn this study, a total of 22 indicators were employed to build the decision tree diagnostic model. Univariate statistical analysis was carried out prior to the model construction, and it was discovered that the differences of 13 indicators between the molded group and the non-molded group were statistically significant. A decision tree model with D-dimer ≥ 1.7ug/mL, C-reactive protein ≥ 15 mg/L, drug resistance or not, and serum ferritin<137 mg/L was constructed in the training sample dataset of the molded group and the non-molded group. The sensitivity of the decision tree model was 0.884, which was verified in the dataset of the remolded group and the non-molded group. The specificity was 0.727, and the area under the receiver operating characteristic curve was 0.831.ConclusionDecision tree model can provide reference for the application of auxiliary diagnosis in children with mycoplasma pneumoniae pneumonia complicated with plastic bronchitis. The model has good discriminative ability in general, and is worthy of clinical application and further study. Abstract Background To establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the application value of decision tree model in the auxiliary diagnosis of children. Methods A retrospective study was conducted to collect the clinical data of 214 children who met the admission criteria in Fujian Children’s Hospital from June 2022 to June 2024, and they were divided into plastic bronchitis group (n = 66) and non-plastic bronchitis group (n = 148). Using R language, 70% of the data from each group of patients was randomly selected for training the model using decision tree algorithm analysis, thus generating a clinical diagnostic decision tree for Mycoplasma pneumoniae (MP) combined with PB. The generated decision tree model was validated on the validation sample dataset and the detection effect value of the model was calculated. Result In this study, a total of 22 indicators were employed to build the decision tree diagnostic model. Univariate statistical analysis was carried out prior to the model construction, and it was discovered that the differences of 13 indicators between the molded group and the non-molded group were statistically significant. A decision tree model with D-dimer ≥ 1.7ug/mL, C-reactive protein ≥ 15 mg/L, drug resistance or not, and serum ferritin<137 mg/L was constructed in the training sample dataset of the molded group and the non-molded group. The sensitivity of the decision tree model was 0.884, which was verified in the dataset of the remolded group and the non-molded group. The specificity was 0.727, and the area under the receiver operating characteristic curve was 0.831. Conclusion Decision tree model can provide reference for the application of auxiliary diagnosis in children with mycoplasma pneumoniae pneumonia complicated with plastic bronchitis. The model has good discriminative ability in general, and is worthy of clinical application and further study. Background To establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the application value of decision tree model in the auxiliary diagnosis of children. Methods A retrospective study was conducted to collect the clinical data of 214 children who met the admission criteria in Fujian Children’s Hospital from June 2022 to June 2024, and they were divided into plastic bronchitis group ( n = 66) and non-plastic bronchitis group ( n = 148). Using R language, 70% of the data from each group of patients was randomly selected for training the model using decision tree algorithm analysis, thus generating a clinical diagnostic decision tree for Mycoplasma pneumoniae (MP) combined with PB. The generated decision tree model was validated on the validation sample dataset and the detection effect value of the model was calculated. Result In this study, a total of 22 indicators were employed to build the decision tree diagnostic model. Univariate statistical analysis was carried out prior to the model construction, and it was discovered that the differences of 13 indicators between the molded group and the non-molded group were statistically significant. A decision tree model with D-dimer ≥ 1.7ug/mL, C-reactive protein ≥ 15 mg/L, drug resistance or not, and serum ferritin<137 mg/L was constructed in the training sample dataset of the molded group and the non-molded group. The sensitivity of the decision tree model was 0.884, which was verified in the dataset of the remolded group and the non-molded group. The specificity was 0.727, and the area under the receiver operating characteristic curve was 0.831. Conclusion Decision tree model can provide reference for the application of auxiliary diagnosis in children with mycoplasma pneumoniae pneumonia complicated with plastic bronchitis. The model has good discriminative ability in general, and is worthy of clinical application and further study. |
| ArticleNumber | 95 |
| Author | Yang, Rongrong Li, Lin Wu, Ling Wang, Dong Liao, Xing |
| Author_xml | – sequence: 1 givenname: Lin surname: Li fullname: Li, Lin organization: Department of Infectious Diseases, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Children’s Hospital (Fujian Branch of Shanghai Children’s Medical Center), National Regional Medical Center, Fujian Medical University – sequence: 2 givenname: Dong surname: Wang fullname: Wang, Dong organization: Department of Infectious Diseases, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Children’s Hospital (Fujian Branch of Shanghai Children’s Medical Center), National Regional Medical Center, Fujian Medical University – sequence: 3 givenname: Rongrong surname: Yang fullname: Yang, Rongrong organization: Department of Infectious Diseases, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Children’s Hospital (Fujian Branch of Shanghai Children’s Medical Center), National Regional Medical Center, Fujian Medical University – sequence: 4 givenname: Xing surname: Liao fullname: Liao, Xing organization: Department of Infectious Diseases, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Children’s Hospital (Fujian Branch of Shanghai Children’s Medical Center), National Regional Medical Center, Fujian Medical University – sequence: 5 givenname: Ling surname: Wu fullname: Wu, Ling email: Wuling2215@163.com organization: Department of Infectious Diseases, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Children’s Hospital (Fujian Branch of Shanghai Children’s Medical Center), National Regional Medical Center, Fujian Medical University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/40128882$$D View this record in MEDLINE/PubMed |
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| Keywords | Mycoplasma pneumoniae Childhood pneumonia Diagnosis Plastic bronchitis Decision tree model |
| Language | English |
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To establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the... To establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the application... BackgroundTo establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to explore the... Abstract Background To establish a decision tree model of Mycoplasma pneumoniae pneumonia(MPP) complicated with plastic bronchitis(PB) in children, and to... |
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| SubjectTerms | Analytical chemistry Bronchitis Bronchitis - complications Bronchitis - diagnosis Bronchitis - microbiology Bronchoscopy C-reactive protein Child Child, Preschool Childhood pneumonia Children Childrens health Classification Datasets Decision making Decision tree model Decision Trees Dehydrogenases Diagnosis Disease Drug resistance Female Ferritin Fever Humans Infections Infectious Diseases and Vaccinology Kinases Male Maternal and Child Health Medicine Medicine & Public Health Mycoplasma pneumoniae Normal distribution Pediatrics Plastic bronchitis Plastics Pleural effusion Pneumonia Pneumonia, Mycoplasma - complications Pneumonia, Mycoplasma - diagnosis Retrospective Studies Statistical analysis Statistical models Tuberculosis |
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| Title | Application of decision tree model in diagnosis of mycoplasma pneumoniae pneumonia with plastic bronchitis |
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