Objectives: Respiratory syncytial virus (RSV) is a leading cause of hospitalization for acute lower respiratory tract infections (ALRIs) in children, with bacterial coinfection complicating diagnosis and often driving antibiotic overuse. This study aimed to develop and validate a clinical prediction model using common laboratory biomarkers to enable early, accurate identification of clinically significant bacterial coinfection in children with RSV infection. Methods: A single-center, retrospective cohort study was conducted at Fujian Children’s Hospital, enrolling 518 hospitalized children with RSV infection, which was confirmed via targeted next-generation sequencing (tNGS). Patients were randomly divided into a training set (n = 363) and a test set (n = 155) at a 7:3 ratio. The primary outcome, bacterial coinfection, was defined by a composite reference standard integrating etiological evidence from tNGS with clinical, inflammatory, and imaging data, and adjudicated by a blinded expert panel. LASSO regression identified independent predictors, followed by multivariable logistic regression modeling. Model performance was assessed via discrimination (AUC), calibration (Hosmer–Lemeshow test), and clinical utility (Decision Curve Analysis) in both sets. Results: Neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), and serum amyloid A (SAA) were selected as predictors. The model achieved an AUC of 0.832 (95% CI: 0.788–0.875) in the training set and 0.811 (95% CI: 0.737–0.885) in the test set, with well-calibrated predictions (p > 0.05). Decision curve analysis demonstrated net clinical benefit across 10–80% threshold probabilities. A nomogram was developed for practical application. Conclusions: This study established a model integrating NLR, CRP, and SAA. It offers a reliable tool for the early detection of bacterial coinfection in RSV-infected children, enabling targeted antibiotic stewardship and improving clinical outcomes.

Community-acquired pneumonia (CAP) remains one of the leading causes of death among pediatric patients under the age of 5, making timely and accurate diagnosis crucial for subsequent treatment. While numerous artificial intelligence diagnostic methods for pneumonia have shown reliable results, most of them still exhibit significant limitations: (a) They only rely on single-modality data, which have limitations in capturing comprehensive clinical information; (b) They do not consider differences in postures among pediatric patients, resulting in constrained diagnostic performance and generalizability. To address these challenges, we construct a real-world pediatric CAP dataset from tertiary hospital records, and develop a multimodal framework for the precise diagnosis of pediatric CAP. In order to simulate clinical diagnostic workflows, the developed model not only integrates frontal chest X-ray images but also considers laboratory test results and clinical texts, enabling comprehensive diagnosis of diverse symptoms, enhancing diagnostic accuracy and generalizability. Experimental results based on the constructed dataset demonstrate that our multimodal approach achieves an impressive diagnostic result, with an accuracy of 94.2%, showing significant improvement over single-modality baselines and validating the potential as an auxiliary diagnostic tool to enhance the clinical practice for pediatric CAP screening.

Background & Objective: The clinical impact of testing timing for targeted next-generation sequencing (tNGS) in pediatric community-acquired pneumonia (CAP) is poorly understood. We hypothesized that early tNGS implementation accelerates clinical recovery and evaluated its comprehensive value. Methodology: In a retrospective study at Fujian Children's Hospital (2021-2023), 199 hospitalized children with CAP (BALF tested) were analyzed. Patients were grouped by tNGS vs. conventional testing (CT), with the tNGS group stratified into early (≤48h) and late (>48h) testing. We compared diagnostic yield, clinical outcomes, therapeutic adjustments, and costs. Results: tNGS demonstrated significantly higher sensitivity than CT for both bacteria (86.0% vs. 19.0%, P<0.001) and viruses (88.1% vs. 26.2%, P<0.001), and excelled at identifying mixed infections (55.8%). Critically, the early-testing group showed significantly shorter times to cough improvement (median 6.0 vs. 9.0 days, P=0.002) and rale resolution (median 7.0 vs. 8.0 days, P=0.027) compared to the late-testing group. This was associated with more timely therapeutic adjustments (P<0.05). A non-significant trend toward lower costs and shorter hospital stays was also observed. Conclusion: Early tNGS implementation in pediatric CAP not only enhances diagnostic yield but, more importantly, accelerates clinical recovery by facilitating timely, targeted therapeutic interventions. These findings provide strong evidence for integrating early tNGS into clinical workflows, marking a shift from simple pathogen identification to an outcome-driven diagnostic strategy.

Purpose: To evaluate the association of ambroxol hydrochloride and clenbuterol hydrochloride oral solution (AHCHOS) with respiratory symptom improvement and safety in Chinese children with pneumonia using real-world data. Methods: A propensity score-matched (PSM) cohort study was conducted. Children patients (≤ 14 years) with a diagnosis of pneumonia between May, 2018 and July, 2019 were considered as the study population. The main outcome of interest was the overall rate of improvement of respiratory symptoms in treatment groups with or without AHCHOS at day 7 using respiratory symptom scores (QS) and Visual Analog Scale (VAS) score of severity of respiratory signs. Secondary end points include medication adherence assessment and safety assessment. Results: A total of 3103 children with a diagnosis of pneumonia were included. After propensity score matching, a sample of 1428 patients was analyzed. AHCHOS use was associated with greater improvement in cough score (p=0.01) and day 7 clinical sign improvement rate (p=0.03) compared with no AHCHOS use. Exploratory subgroup analyses suggested larger differences in children aged 3– 6 years and in selected severity strata. Medication adherence assessmentdid not differ significantly between groups at days 4, 7, 14, and 28. Adverse events were similar between groups. Conclusion: In this real-world propensity score-matched analysis, AHCHOS use was associated with improved respiratory symptom outcomes in children with pneumonia and appeared to have an acceptable safety profile. These findings should be interpreted as observational and hypothesis-generating. Trial Registration Number: The study was registered at Chinese Clinical Trial Registry (https://www.chictr.org.cn/, ChiCTR1800015818).

Human metapneumovirus (hMPV) is a significant pathogen of acute respiratory infection in children. While previous studies have relied on conventional diagnostics that underestimate complex polymicrobial interactions, this study aimed to utilize targeted next-generation sequencing (tNGS) to comprehensively profile the dynamics of its co-colonization or co-infection pathogen spectrum and their impact on disease severity, thereby informing clinical risk stratification. This retrospective study enrolled 526 hospitalized children with hMPV infection. Targeted next-generation sequencing (tNGS) was used to comprehensively analyze the co-colonization or co-infection spectrum stratified by age, gender, sample origin, immune deficiency, and immunization status. Multivariable logistic regression was employed to assess independent associations with host factors and severe clinical outcomes (ICU [intensive care unit] admission, mechanical ventilation, septic shock, pneumonia on imaging). The median age of the inpatients was 36 months, and 15.6% required ICU admission. The overall prevalence of co-detection among the cohort was 100% since we identified at least one pathogen in the existing results from tNGS. The co-colonization or co-infection pathogen spectrum demonstrated significant age specificity, temporal dynamics, and sample type dependency. Multivariable analysis identified several pathogens independently associated with severe outcomes. Specifically, opportunistic and atypical pathogens (such as Cytomegalovirus [prevalence: 7.22%], Herpes Simplex Virus type 1 [1.71%], Klebsiella aerogenes [0.76%], and Tropheryma whipplei [1.90%]) were strong risk factors for ICU admission, invasive ventilation, and septic shock (adjusted Odds Ratios [aOR] ranging from 4.57 to 28.69). Conversely, Fusobacterium nucleatum (25.67%) consistently exhibited a protective effect (eg, aOR=0.43 for ICU admission). Mycoplasma pneumoniae (12.93%) was an independent risk factor for pneumonia on imaging (aOR=2.25), while Human RSV A (1.14%) showed a significant protective association (aOR=0.09). Despite limitations including a single-center retrospective design and the absence of an hMPV-negative control group, the co-colonization or co-infection pathogen spectrum in children with hMPV infection is complex and closely related to host characteristics. Early identification of high-risk co-pathogens (eg, CMV or K. aerogenes) via tNGS should trigger intensified clinical monitoring. Future prospective controlled studies are needed to validate these findings and confirm causality.