Abstract
Objective This study analyzed the relationship between clinical parameters and prognosis in
children with Mycoplasma pneumoniae (MP)-positive lobar pneumonia and developed an early identification model.
Methods Relevant clinical parameters were collected. Patients were then categorized into
two groups based on their length of hospital stay: 116 cases in the refractory group
(≥10 days) and 94 cases in the non-refractory group (<10 days). A univariate analysis
of variance and binary logistic regression were utilized to develop a predictive model,
accompanied by the construction of a nomogram. The model's performance was assessed
using receiver operating characteristic (ROC) curves, diagnostic calibration curves,
and decision curve analysis (DCA) curves. Furthermore, clinical data from 100 additional
cases of MP-positive lobar pneumonia in children treated at other centers were gathered
for external validation of the model.
Results Binary logistic regression analysis identified four independent risk factors for
prolonged disease duration in children with MP-positive lobar pneumonia: erythrocyte
sedimentation rate (ESR), globulin, lactate dehydrogenase (LDH), and SF. We constructed
a nomogram model based on these risk factors. In the training set, the area under
the curve (AUC) was 0.869 (95% CI: 0.822–0.917), with a sensitivity of 68.54% and
a specificity of 82.61%. For the test set, the AUC increased to 0.918 (95% CI: 0.866–0.971),
demonstrating a sensitivity of 91.67% and a specificity of 78.69%. The DeLong test
results indicated that the difference in AUC between the two datasets was not statistically
significant (D = − 1.724, p = 0.086). Calibration curve analysis confirmed that the nomogram model exhibited
a good fit in both the training set (Hosmer–Lemeshow test, χ2 = 8.120, p = 0.421) and the validation set (Hosmer–Lemeshow test, χ2 = 14.601, p = 0.067). DCA further demonstrated that the model performed significantly across
a range of threshold probabilities.
Conclusion The nomogram model developed for predicting refractory MP-positive lobar pneumonia
in children has significant clinical value and can guide personalized treatment strategies.
Keywords
model - MP - refractory - lobar pneumonia - pediatric
