Objective:To analyze the risk factors for children with severe community-acquired pneumonia (CAP) being admitted to the pediatric intensive care unit (PICU),and establish a clinical prediction model,then evaluate the clinical application value of this model.Methods:A retrospective analysis was performed on children diagnosed with severe CAP at the Children's Hospital Affiliated to School of Medicine of Shanghai Jiao Tong University from January to June 2023.The children were divided into the PICU group and the non-PICU group based on whether they were admitted to PICU at admission.The differences in pediatric early warning score（PEWS），clinical characteristics，and laboratory test results between the two groups at their last visit before admission were compared. The independent risk factors for children with severe CAP admitted to PICU were analyzed,and a clinical prediction model was established,which was validated through the receiver operating characteristic (ROC) curve.Results:A total of 274 children were included,including 141 males and 133 females,with a median age of 50 (24,81) months. There were 43 cases in PICU group and 231 cases in non-PICU group.There were no statistically significant differences in gender and age between the two groups of children ( P>0.05). The PEWS score,white blood cell count,neutrophil count,neutrophil/lymphocyte ratio,procalcitonin (PCT),and lactate levels of children in the PICU group were significantly higher than those of children in the non-PICU group.While the duration of fever,peak temperature,and percutaneous arterial oxygen saturation (SpO 2) were significantly lower in the PICU group than those in the non-PICU group. All these differences were statistically significant ( P<0.05).Binary Logistic regression analysis showed that PEWS>4 points（ OR=6.583，95% CI 1.763 - 24.588， P<0.05），PCT>0.42 μg/L（ OR=19.046，95% CI 4.362-83.159， P<0.05），and SpO 2<93%（ OR=21.670，95% CI 3.843-122.184， P<0.05）were independent risk factors for children with severe CAP to be admitted to PICU.A clinical prediction model was constructed based on the above three independent risk factors.The area under ROC curve of the clinical prediction model was 0.941（95% CI 0.913-0.968， P<0.05），the sensitivity was 95.3%，the specificity was 80.5%，the positive predictive value was 83.0%，and the negative predictive value was 94.5%. Conclusion:For children with severe CAP，if they have PEWS > 4,an elevated PCT level，and a decreased SpO 2，it is recommended that they be admitted to PICU for further monitoring and treatment.The clinical prediction model for admission to the PICU for children with severe CAP，constructed by combining PEWS with commonly used clinical information in pediatric emergency，has a relatively high predictive efficacy and can provide a reference for the stratified diagnosis and treatment of children with severe CAP in the future.

Objective:To analyze the risk factors for children with severe community-acquired pneumonia (CAP) being admitted to the pediatric intensive care unit (PICU),and establish a clinical prediction model,then evaluate the clinical application value of this model.Methods:A retrospective analysis was performed on children diagnosed with severe CAP at the Children's Hospital Affiliated to School of Medicine of Shanghai Jiao Tong University from January to June 2023.The children were divided into the PICU group and the non-PICU group based on whether they were admitted to PICU at admission.The differences in pediatric early warning score（PEWS），clinical characteristics，and laboratory test results between the two groups at their last visit before admission were compared. The independent risk factors for children with severe CAP admitted to PICU were analyzed,and a clinical prediction model was established,which was validated through the receiver operating characteristic (ROC) curve.Results:A total of 274 children were included,including 141 males and 133 females,with a median age of 50 (24,81) months. There were 43 cases in PICU group and 231 cases in non-PICU group.There were no statistically significant differences in gender and age between the two groups of children ( P>0.05). The PEWS score,white blood cell count,neutrophil count,neutrophil/lymphocyte ratio,procalcitonin (PCT),and lactate levels of children in the PICU group were significantly higher than those of children in the non-PICU group.While the duration of fever,peak temperature,and percutaneous arterial oxygen saturation (SpO 2) were significantly lower in the PICU group than those in the non-PICU group. All these differences were statistically significant ( P<0.05).Binary Logistic regression analysis showed that PEWS>4 points（ OR=6.583，95% CI 1.763 - 24.588， P<0.05），PCT>0.42 μg/L（ OR=19.046，95% CI 4.362-83.159， P<0.05），and SpO 2<93%（ OR=21.670，95% CI 3.843-122.184， P<0.05）were independent risk factors for children with severe CAP to be admitted to PICU.A clinical prediction model was constructed based on the above three independent risk factors.The area under ROC curve of the clinical prediction model was 0.941（95% CI 0.913-0.968， P<0.05），the sensitivity was 95.3%，the specificity was 80.5%，the positive predictive value was 83.0%，and the negative predictive value was 94.5%. Conclusion:For children with severe CAP，if they have PEWS > 4,an elevated PCT level，and a decreased SpO 2，it is recommended that they be admitted to PICU for further monitoring and treatment.The clinical prediction model for admission to the PICU for children with severe CAP，constructed by combining PEWS with commonly used clinical information in pediatric emergency，has a relatively high predictive efficacy and can provide a reference for the stratified diagnosis and treatment of children with severe CAP in the future.

Objective:To retrospectively analyze the independent risk factors of complicated appendicitis(CA)in children under five years old and establish a clinical prediction model, and to evaluate the clinical application of this model.Methods:A retrospective analysis was performed on children under five years old who underwent appendectomy at Children′s Hospital of Shanghai Jiao Tong University School of Medicine from January 2018 to December 2021.The children were divided into CA group and uncomplicated appendicitis group according to whether there was sign of perforation or gangrene in appendiceal tissue after operation.The differences in clinical features and preoperative laboratory test results between two groups were compared.The independent risk factors of CA were identified and a clinical prediction model was established.The clinical prediction model was verified by receiver operating characteristic curve.Results:A total of 140 children were enrolled in this study, including 84 cases in the CA group and 56 cases in uncomplicated appendicitis group.Univariate and binary Logistic regression analysis showed that the duration of symptoms>23.5 h( OR=6.650, 95% CI 2.469-17.912, P<0.05), abdominal muscle tension( OR=3.082, 95% CI 1.190-7.979, P<0.05) and C-reactive protein>41 mg/L ( OR=3.287, 95% CI 1.274-8.480, P<0.05) were independent risk factors for CA( P<0.05). The clinical prediction model of CA was constructed by the above mentioned three independent risk factors.The area under the receiver operating characteristic curve of the clinical prediction model was 0.881(95% CI 0.825-0.936), the sensitivity was 77.4%, the specificity was 87.5%, the positive predictive value was 91.3% and the negative predictive value was 70.0%. Conclusion:Acute appendicitis in children under five years old is more likely to progress to CA if the duration of symptoms>23.5 h, the level of C-reactive protein is increased, and the abdominal muscle tension is accompanied.The clinical prediction model of CA constructed by common clinical information in pediatric clinics has good prediction efficiency, which provides a simple and feasible reference method for clinicians to distinguish CA from uncomplicated appendicitis.

Objective:To establish a decision tree model of pediatric complicated appendicitis (CA) based on Pediatric Appendicitis Score (PAS) combined with inflammatory indicators, and to evaluate its clinical application efficacy in pediatrics.Methods:The clinical data of 544 children diagnosed with appendicitis in Children′s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2018 to December 2021 was retrospectively analyzed. According to postoperative pathology, the children were divided into uncomplicated appendicitis group and CA group. The independent risk factors of CA were screened by univariate and multivariate logistic regression analysis, and these parameters were included to establish the decision tree model. The accuracy of the decision tree model was verified by receiver operating characteristic (ROC) curve.Results:Binary logistic regression analysis indicated that the PAS, C-reactive protein (CRP) and neutrophil to lymphocyte ratio (NLR) were identified as independent risk factors for complicated appendicitis in children (all P<0.05). PAS, CRP and NLR were included as covariables to construct the decision tree model and binary logistic regression model for predicting CA. The decision tree demonstrated an overall accuracy of 79.2% with a sensitivity of 86.7% and specificity of 71.9%, and achieved an area under curve (AUC) of 0.821(95% CI: 0.786-0.857). The binary logistic regression model had a sensitivity of 79.6% and specificity of 69.1%, with an overall accuracy of 75.1% and achieved an AUC of 0.808(95% CI: 0.770-0.845). Conclusions:The decision tree model based on PAS score combined with CRP, NLR is a simple, intuitive and effective tool , which can provide pediatric emergency physicians a reliable basis for diagnosis of pediatric CA.