PLR/SII/D-dimer Iron Triangle: A Novel Precision Prediction Strategy for Mycoplasma pneumoniae Pneumonia-Associated Plastic Bronchitis in Children

Minxuan Feng^1*Wenyan Li²Tao Ai¹Yinghong Fan¹Lei Zhang¹Wanmin Xia¹Cheng Xie^1*

• ¹Chengdu Women and Children’s Central Hospital, Chengdu, China
• ²Guangzhou Medical University Guangzhou Women and Children's Medical Center, Guangzhou, China

Objective: Plastic bronchitis (PB) is a life-threatening pulmonary infection disease, and the early recognition and diagnostic prediction of PB are currently not well established. This study aims to identify independent risk factors for PB and develop a clinically applicable predictive model to help clinicians make earlier and more accurate judgments about the potential occurrence of PB. This is a provisional file, not the final typeset article Methods: This study included 132 hospitalized patients with lobar pneumonia caused by Mycoplasma pneumoniae infection who underwent fiberoptic bronchoscopy. The study group consisted of 44 PB patients and 88 non-PB patients. Clinical data were collected and analyzed using chi-square tests, t-tests, non-parametric tests, Pearson χ² tests, continuity-corrected χ² tests, and Fisher's exact probability tests. Univariate analysis was performed to identify potential risk factors, and logistic regression analysis was used to determine the main independent risk factors for PB. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive potential of single-factor models and a combined model of platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and D-dimer for PB occurrence. Results: The results of univariate analysis showed that N%, L%, NLR, PLR, CRP, PCT, SII, LDH, D-dimer, and the duration of macrolide antibiotic therapy were all independent risk factors for PB. It was also suggested that continued use of macrolides after two courses did not significantly reduce the occurrence of PB. The results of multivariate regression analysis indicated that a combined analysis of PLR, SII, and D-dimer had higher predictive value for PB occurrence. This was further supported by plotting ROC curves and establishing a triad model of these indicators to achieve simple data calculation for predicting PB in clinical practice. Conclusion: This study demonstrates that PLR, SII, and D-dimer are important indicators for predicting the occurrence of PB in children. The combined model of these three indicators is more sensitive and specific than the individual risk factors in predicting PB occurrence. Additionally, this model provides synergistic guidance for the duration of macrolide antibiotic therapy.