Risk factor analysis for deep vein thrombosis in children with acute hematogenous osteomyelitis

Abstract

Objective

This study aims to explore the correlation between Acute Hematogenous Osteomyelitis (AHO) and Deep Venous Thrombosis (DVT) in children. It seeks to identify independent risk factors for DVT secondary to AHO, enhance understanding of the disease, and establish a predictive model to guide clinical practice.

Methods

A retrospective analysis of clinical data from AHO patients treated at our hospital (January 2017 to December 2023) was conducted. Patients were divided into thrombosis and non-thrombosis groups based on DVT occurrence.

Univariate analysis used independent samples t-tests, Mann–Whitney U tests, and chi-square tests to screen DVT-associated variables (P < 0.1). Significant variables were included in a binary logistic regression model to identify independent risk factors for DVT secondary to AHO. Model fit was assessed using the Hosmer–Lemeshow test, and Cox-Snell R² was calculated through linear regression of P-values with the dependent variable. ROC curves were plotted, and AUC was recorded to evaluate model validity and reliability.

Results

Univariate analysis revealed significant correlations between DVT and several factors, including age, peak levels of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), and D-dimer. Additionally, the time for CRP to normalize, concurrent pneumonia, intensive care use, the severity of osteomyelitis (Lawson score), and femoral involvement in osteomyelitis were also significantly associated with DVT (P < 0.05).

Binary logistic regression identified age (OR = 1.248), D-dimer (OR = 1.600), and concurrent pneumonia (OR = 4.921) as significantly positively associated with secondary DVT (P < 0.05).

The model demonstrated good goodness-of-fit (P > 0.05), accurately explained the data (R² = 0.449, Cox-Snell R² = 0.413), and had strong predictive performance (AUC = 0.895).

Conclusion

Age, peak levels of CRP/ESR/PCT/D-dimer, osteomyelitis severity (Lawson score), femoral involvement in osteomyelitis, and concurrent pneumonia were significantly associated with secondary deep vein thrombosis (DVT) in pediatric acute hematogenous osteomyelitis (AHO). Among these, age, peak D-dimer levels, and concurrent pneumonia were identified as independent risk factors for DVT in children with AHO.

The current predictive model demonstrated good performance in this cohort, providing early warning for potential DVT risk in pediatric AHO patients. However, multicenter studies are needed to further validate its generalizability.

Pediatricians may use this model to assess the necessity of DVT screening, reduce missed diagnoses, and initiate timely antithrombotic therapy to prevent adverse outcomes.

Introduction

Acute Hematogenous Osteomyelitis (AHO) is a single or multiple bone infection caused by bacteria spreading through the bloodstream to susceptible sites. In children, AHO commonly occurs in the metaphysis of long bones in the extremities, where the rich capillary network, slow blood flow, and lack of reticuloendothelial cells make it easier for bacteria to colonize [1]. In 2014, Lawson et al. established a scoring system to assess the severity of AHO in children based on objective clinical indicators and laboratory results (Table 1) [2]. Bacteremia can lead to endothelial cell damage and the release of inflammatory factors at nearby infection sites, activation of coagulation pathways and fibrinogen, or cause local soft tissue edema resulting in blood stasis, thereby providing a microenvironment for the formation of deep venous thrombosis (DVT). The incidence of deep vein thrombosis (DVT) in children is low, approximately less than 0.01% [3]. It typically occurs following the use of central venous catheters (CVCs), trauma, infection, or surgery. In children with AHO complicated by DVT, dislodged thrombi may carry pathogenic bacteria and lead to septic thromboembolism, promoting the spread of infection [4]. If a thrombus breaks off and migrates to the lungs, it can develop into pulmonary embolism (PE). DVT and PE are collectively referred to as venous thromboembolism (VTE). In children, DVT often manifests as localized pain, which significantly overlaps with the clinical symptoms of AHO. Additionally, MRI of the affected limb's soft tissues—typically performed for AHO evaluation—is not used to assess DVT, potentially leading to delayed diagnosis and treatment, thereby increasing therapeutic challenges [5–11]. This delay may result in adverse outcomes such as respiratory distress, multi-organ failure, or even death.

Table 1.

Lawson's Severity score for osteomyelitis

	CRP initial	CRP 48 h	CRP 96 h	Respiratory rate	Febrile dats on Antibiotic	ICU admission	Disseminated disease
0	< 10	< 5	< 5	< 125%	< 2	No	No
1	10–15	5–10	5–10	> 125%	≥ 2	Yes	Yes
2	> 15	> 10	> 10

Materials and methods

Study subjects

Clinical data of AHO patients treated at our hospital from January 2017 to December 2023 were retrospectively collected.

Inclusion criteria

① Discharge date between January 2017 and December 2023 ② Age between 0 and 18 years ③ Primary diagnosis of AHO ④ No other systemic diseases.

Exclusion criteria

① Abnormal coagulation function ② Previous antithrombotic therapy ③ Use of central venous catheters (CVC) ④ Chronic osteomyelitis ⑤ No bacterial culture performed ⑥ Incomplete clinical data (Fig. 1).

Fig. 1.

Research flowchart

Admission management

Upon admission, patients immediately underwent comprehensive vital sign monitoring, including continuous observation of respiratory rate, body temperature, and blood pressure, to ensure physiological stability. Laboratory tests included complete blood count analysis to assess blood composition, C-reactive protein (CRP) and procalcitonin (PCT) levels to evaluate inflammatory response, D-dimer and fibrinogen tests to assess coagulation status, and erythrocyte sedimentation rate (ESR) to monitor inflammation or infection activity. Additionally, blood and pus cultures were performed to identify pathogens for precise antibiotic guidance. Preoperative routine chest X-rays were conducted to evaluate lung conditions and rule out complications. For patients with significant local swelling and pain, soft tissue and venous ultrasounds were performed to screen for abscesses or deep vein thrombosis (DVT). While awaiting culture results, empirical treatment with cephalosporins or vancomycin was initiated to control potential infections and prevent further deterioration. The entire treatment process strictly adhered to medical protocols to ensure optimal patient outcomes.

Evaluation metrics

After admission, a thorough review of the patient's previous medical records and history is conducted to comprehensively understand the progression of their condition and fluctuations in key laboratory indicators. This information is crucial for assessing disease progression trends and treatment responses. Understanding the patient's pre-admission antibiotic usage, including drug types, dosages, treatment duration, and efficacy, provides a reference for the current antibiotic treatment strategy and helps avoid potential drug interactions or resistance issues.

Additionally, existing magnetic resonance imaging (MRI) reports and venous ultrasound reports are collected to evaluate bone marrow edema and the progression of bone destruction at the AHO infection site, as well as to identify the location and severity of deep vein thrombosis (DVT).

All patients showed no evidence of DVT upon admission to our department. During hospitalization, routine blood tests and chest X-rays were performed for all patients upon admission. Ultimately, venous ultrasound identified AHO patients complicated with DVT.

Statistical methods

Statistical analysis was performed using SPSS 27.0. Clinical data (including age, gender, clinical features, thrombus location, laboratory results, bacteriological tests, and imaging findings) were organized, and patients were divided into the DVT group and the non-DVT group based on whether they developed secondary DVT.

For continuous variables with a normal distribution, independent samples t-tests were used, with results expressed as mean ± standard deviation (x̄ ± s). For continuous variables without a normal distribution, the Mann–Whitney U test was used, with results expressed as median and interquartile range (Q1-Q3). For categorical variables, the chi-square test was used, with results expressed as frequencies and percentages. In univariate analysis, variables with a P-value < 0.1 were included in subsequent multivariate analysis. A binary logistic regression model was used to further identify independent risk factors for acute hematogenous osteomyelitis (AHO) complicated by deep vein thrombosis (DVT), and the odds ratios (ORs) and their 95% confidence intervals were calculated. To evaluate the goodness-of-fit of the model, the Hosmer–Lemeshow test was performed, and the Cox-Snell R² value was calculated through linear regression analysis to quantify the model's explanatory power. Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated to assess the model's discriminative performance. Additionally, the optimal cutoff values for continuous variables were determined through ROC curve analysis.

Result

{Following continuous antibiotic therapy and low-molecular-weight heparin (LMWH) treatment, all patients improved without recurrence of DVT.}

According to the aforementioned inclusion and exclusion criteria, a total of 76 patients were included in this study, with 30 in the DVT group and 46 in the non-DVT group. All patients had positive blood culture results, with 72 cases (95%) caused by Staphylococcus aureus infection, including 24 cases (32%) of methicillin-resistant Staphylococcus aureus (MRSA). Among these, 12 cases (40%) were in the DVT group, a higher proportion compared to 12 cases (26.1%) in the non-DVT group (P = 0.202). The average age in the DVT group (9.18 ± 3.58) was significantly higher than that in the non-DVT group (6.07 ± 3.83) (P < 0.001). Males were predominant (63.3%) (P = 0.131). Osteomyelitis involved the femur in 41 cases (54%), the tibia in 14 cases (18%), the humerus in 10 cases (13%), and the pelvis in 7 cases (9%) (Fig. 2). DVT involved the common femoral vein in 14 cases (47%), the superficial femoral vein in 9 cases (30%), the deep femoral vein in 4 cases (13%), the external iliac vein in 4 cases (13%), the anterior tibial vein in 4 cases (13%), the small saphenous vein in 3 cases (10%), the popliteal vein in 7 cases (9%), the common iliac vein in 2 cases (6%), the great saphenous vein in 2 cases (6%), the dorsal foot vein in 2 cases (6%), the brachial vein in 2 cases (6%), the subclavian vein in 2 cases (6%), the axillary vein in 2 cases (6%), and the peroneal vein in 1 case (3%) (Fig. 3). All DVT cases originated near the AHO lesion, and one patient developed VTE (3.3%).

Fig. 2.

Comparison of groups based on the sites involved by osteomyelitis

Fig. 3.

Location of deep vein thrombosis

According to the pediatric osteomyelitis severity score provided by Lawson et al., in the DVT group, 25 cases (83%) were classified as"severe"and 5 cases (17%) as"moderate"(Fig. 4. Inner ring); in the non-DVT group, 31 cases (67%) were classified as"severe"and 4 cases (9%) as"mild"(Fig. 4. Outer ring) [2].

Fig. 4.

Classification of osteomyelitis severity

Univariate analysis using independent samples t-test revealed that age, CRP, and ESR were significantly associated with DVT secondary to pediatric AHO (P < 0.05).

Univariate analysis with the Mann–Whitney U test showed that PCT, peak D-dimer levels, and osteomyelitis severity (Lawson score) were significantly correlated with DVT secondary to pediatric AHO (P < 0.05).

Univariate analysis using the chi-square test indicated that concomitant pneumonia, femoral osteomyelitis, and ICU admission were significantly associated with DVT secondary to pediatric AHO (P < 0.05) (Table 2).

Table 2.

Univariate analysis results

	DVT(n = 30)	N-DVT(n = 46)	P
Age	9.18 ± 3.58	6.07 ± 3.83	< 0.001*
Gender(n/%) male	19(63.3%)	21(45.7%)	0.131
Side(n/%) left	15(50%)	27(58.7%)	0.456
MRSA(n/%)	12(40%)	12(26.1%)	0.202
Hospital Stay	23.5(16.7,27)	19(13,25.5)	0.114
WBC	18.67 ± 6.49	15.55(10.71,22.42)	0.212
CRP	160.2 ± 65.62	117.55 ± 59.2	0.004*
CRP Normalization Time	23.5(18,34.5)	15.5(12,20.25)	< 0.001*
ESR	95.3 ± 31.24	71.7 ± 28.21	0.001*
Fibrinogen	5.95(4.56,6.5)	4.88(4.55,6.08)	0.172
PCT	3.54(1.57,11.52)	1.1(0.2,8.72)	0.006*
D-dimer	3.42(2.13,4.97)	1.16(0.62, 2.28)	< 0.001*
Complicated Pneumonia	20(66.7%)	9(19.6%)	< 0.001*
Multiple Infection	6(20%)	12(26.1%)	0.542
Femoral Osteomyelitis	21(70%)	20(43%)	0.034*
Multiple Surgeries	7 (23.3%)	6 (13%)	0.351
ICU Admission	7(23.3%)	2(4.3%)	0.012*
AHO Severity Score	7(23.3%)	2(4.3%)	0.033*

*represents a statistically significant variable

Using backward stepwise binary logistic regression (Table 3), the following independent variables were identified: age (OR = 1.248), PCT peak (OR = 1.035), D-dimer peak (OR = 1.600), and concurrent pneumonia (OR = 4.921). Among these, age, D-dimer peak, and concurrent pneumonia remained significantly positively correlated with DVT (P < 0.05), serving as independent risk factors for secondary DVT in children with AHO.

Table 3.

Binary logistic regression analysis

(n = 1)	Wald	P	OR
Age	5.534	0.019*	1.248 (1.038, 1.501)
PCT	3.221	0.073	1.035 (0.997, 1.074)
D-dimer	3.898	0.048*	1.600 (1.003, 2.552)
Complicated Pneumonia	4.980	0.026*	4.921 (1.214, 19.944)

*represents a statistically significant variable

The goodness-of-fit test indicated that the model had a high fit (Table 4, P > 0.05). The model's R² = 0.449, explaining 44% of the variability in the dependent variable (Cox-Snell R² = 0.413) (Table 5), and demonstrated good predictive performance (AUC = 0.895) (Fig. 4, Table 6). The Youden index was calculated to determine the cutoff values for continuous variables within the model (age > 8.7 years, PCT peak > 1.44 ng/ml, D-dimer peak > 1.9 mg/L) (Fig. 5).

Table 4.

Hosmer–lemeshow goodness-of-fit test

(n = 8)	Chi-square	P
Goodness-of-Fit Test	4.890	0.769

Table 5.

Goodness-of-fit test using cox-snell R²

R	R2	Cox-Snell R2	Sig. F
0.67	0.449	0.413	.000

Table 6.

Area under the combined ROC curve of the model

Area	P
0.895	.000

Fig. 5.

Joint ROC curve of four independent risk factors

Discussion

Given that AHO and DVT share overlapping clinical manifestations (such as local redness, swelling, and pain), a definitive diagnosis cannot be made based solely on physical examination. Analyzing the risk factors for DVT complicating AHO can provide clinicians with early warning signs, enabling timely anticoagulation therapy to prevent adverse outcomes.

Among the included AHO cases, 95% were caused by Staphylococcus aureus infections. Staphylococcus aureus can release various exotoxins, among which alpha-toxin acts on cell membranes and can induce vascular smooth muscle spasm, creating a hemodynamic environment conducive to thrombosis formation [12]. Moreover, PV toxin induces neutrophil lysis, releasing α-defensins and myeloperoxidase (MPO) products, which activate platelets and promote their binding to fibrinogen, thereby facilitating thrombus formation [13]. Many scholars believe that Staphylococcus aureus infection is a significant risk factor for the development of DVT in AHO, and multiple studies have confirmed that MRSA infection is more common in AHO patients complicated with DVT [8, 9, 14, 15]. In this study, the proportion of MRSA infections in DVT patients was higher than in non-DVT patients, but the correlation between MRSA infection and secondary DVT was not significant (P > 0.05). We believe this difference may be attributed to the single-center study design, limited sample size, patient environment, racial and cultural differences, as well as genetic variations in MRSA strains [16].

We identified two cases of AHO caused by α-hemolytic Streptococcus (1 case) and Klebsiella pneumoniae (1 case) that subsequently developed DVT. Relevant studies have demonstrated that infections with these microorganisms carry a risk of secondary DVT [17–19]. Three patients with AHO caused by pathogenic bacteria, including Streptococcus pyogenes (2 cases) and Streptococcus lactis (1 case), did not develop secondary DVT.

All patients with DVT had secondary occurrences near the site of AHO involvement, with AHO affecting the pelvis and lower limbs more likely to lead to secondary DVT. Some scholars have noted that DVT commonly occurs in the femoral vein, popliteal vein, and iliac vein [8, 14, 20]. We observed similar results, with most patients developing DVT in the femoral vein (common femoral vein, deep femoral vein, superficial femoral vein) and iliac vein. There was a significant correlation between AHO involving the femur and secondary DVT (P < 0.05). We analyzed that this may be due to the thicker thigh veins with slower blood flow, numerous branches prone to vortex formation, deeper location susceptible to compression, and greater gravitational pressure leading to poor venous return.

The results demonstrated that the median age of pediatric AHO patients who developed secondary DVT (9 years) was significantly higher than that of those without DVT (6 years). We identified age as an independent risk factor for secondary DVT in children with AHO, which may be associated with vascular development and hormonal effects. Several scholars have reached similar conclusions [8, 14]. However, two other studies [5, 20] did not show a significant correlation between age and secondary DVT in AHO patients. Although their experimental groups included only 7 and 9 cases, respectively, further increasing the sample size or conducting multicenter studies is still necessary to make the conclusions more scientifically robust.

Some studies suggest that the risk of secondary DVT in AHO is related to gender, occurring more frequently in male patients [15, 20–22]. In our results {thrombosis group (boys: girls) = (19:11), non-thrombosis group (boys: girls) = (21:25)}, analysis of the data showed that this difference was not statistically significant (P > 0.05).

CRP levels rise within 4 to 6 h after tissue injury and return to normal after inflammation subsides, serving as a non-specific but sensitive indicator for diagnosing AHO in children. Some studies Have found that the peak CRP level in AHO patients is closely related to the occurrence of DVT, concluding that for every 20 mg/L increase in peak CRP, the risk of secondary DVT increases by 28% [21]. Since all AHO patients included in this study underwent multiple CRP tests, we used the highest value as the"peak"CRP level for each patient to best reflect the CRP levels during their inflammatory process. The results showed that AHO children who developed secondary DVT had significantly higher CRP levels compared to those without DVT (P < 0.05), indicating more severe conditions in the DVT group. Additionally, the time for CRP to return to normal in pediatric AHO patients was significantly correlated with the development of secondary DVT (P < 0.05). Higher CRP levels and potential prolonged hospitalization could influence the time for CRP normalization, so we conducted further regression analysis to minimize bias from confounding factors. Ultimately, we found that peak CRP levels and the time for CRP to return to normal were not independent risk factors for secondary DVT in AHO patients.

Both PCT and CRP are important clinical indicators for evaluating infections. Due to their high sensitivity and specificity for bacterial infections, PCT can be used to assess the severity of infections and guide surgical treatment [23]. Our study results indicate a significant correlation between PCT peak levels and the occurrence of secondary DVT in children with AHO (P < 0.05). After further regression analysis to eliminate interference between factors, the result exceeded the pre-set significance level (P = 0.073 > 0.05). Although the statistical evidence level is slightly lower, we believe its statistical tendency cannot be ignored, and thus PCT peak levels were included in the model for analysis.

Lawson et al.'s [2] scoring system can effectively describe the severity of acute hematogenous osteomyelitis (AHO), and our statistical analysis also revealed a significant correlation between this score and secondary deep vein thrombosis (DVT). However, further binary logistic regression showed that this score could not be included in the final model. We speculate that this may be due to reasons similar to the exclusion of CRP and MRSA—many AHO patients had received multiple treatments at local hospitals before admission. Due to the limited medical resources in non-central cities, their conditions were often already severe by the time they were first diagnosed at our hospital, which reduced the baseline differences in infection severity between our control and experimental groups. Additionally, this may also be related to the fact that the covariates included in the Lawson score had already been incorporated into the univariate analysis. This represents a limitation of our study.

Some scholars believe that the prolonged hospitalization and bed rest during AHO treatment increase the risk of secondary DVT [20, 24]. We analyzed the length of hospitalization among the included cases and found that patients who developed secondary DVT had a longer hospital stay (23.5 days) compared to those without DVT (19 days). However, since many patients had previously been hospitalized at local medical institutions before admission to our hospital, the total duration of hospitalization and referral timelines were unclear. Additionally, the length of hospitalization could be influenced by multiple factors, including prolonged treatment due to DVT, increased patient healthcare-seeking behavior, and the timing of venous ultrasound detection [8] Therefore, we could not establish a definitive correlation between the duration of hospitalization in AHO patients and the occurrence of secondary DVT.

No studies have confirmed the correlation between ESR and the development of DVT in patients with AHO [5, 6, 8]. We identified a significant correlation in the univariate analysis (P < 0.05), but the peak ESR cannot be considered an independent risk factor for secondary DVT in AHO patients (P > 0.05).

Undergoing multiple surgeries indirectly reflects the severity of AHO. Studies have found that several admission indicators (vital signs, CRP, ESR, hemoglobin) in pediatric AHO patients are associated with secondary or multiple surgeries [25]. The correlation between secondary DVT and multiple surgeries in pediatric AHO patients has not been reported. We believe that AHO children who develop secondary DVT may require more surgeries subsequently, while factors such as prolonged treatment cycles or increased risk of postoperative complications due to multiple surgeries could also contribute to the occurrence of DVT. The two may have a bidirectional causal relationship, necessitating more comprehensive statistical analysis.

Coagulation-related markers are associated with hemodynamic changes. Fibrinogen can directly or indirectly promote coagulation, activate platelets, facilitate platelet adhesion, and promote thrombus formation [26]. D-dimer, a degradation product of fibrin, has blood levels directly correlated with thrombus formation [27, 28]. In our study results, D-dimer was identified as an independent risk factor for secondary DVT in children with AHO (P < 0.05). Our conclusions can enable orthopedic surgeons to have a more comprehensive understanding and appreciation of various examination indicators when dealing with AHO patients, clarify diagnostic thinking, and minimize the rate of missed diagnoses of DVT as much as possible.

AHO caused by Staphylococcus aureus often involves pulmonary complications [29]. Studies suggest that patients with AHO who develop DVT are more prone to pneumonia or VTE [9]. Through routine chest X-rays of newly admitted children, we found that the majority (66.7%) of AHO patients with secondary DVT had varying degrees of pneumonia (before DVT was suspected and diagnosed by venous ultrasound), while this proportion was much smaller (19.6%) in AHO patients without secondary DVT. We hypothesize that secondary DVT is associated with AHO complicated by pneumonia. In further logistic regression analysis, we found a significant correlation between the two (P < 0.05), indicating that pneumonia is an independent risk factor for secondary DVT in children with AHO. However, the exact chronological sequence between pulmonary lesions and secondary DVT remains undetermined. Due to the uneven distribution of healthcare resources in China, most patients admitted to our hospital were referrals from local institutions, making it difficult to obtain first-visit medical records. This may have obscured the temporal relationship between pulmonary abnormalities and DVT onset, representing a limitation of our study. Nevertheless, all patients with abnormal chest radiographs were diagnosed with pneumonia before developing overt DVT-related symptoms. We therefore speculate that radiographic abnormalities may still possess predictive value for DVT secondary to AHO and could potentially guide clinical management.

The limitations of this study lie in its retrospective design and relatively small sample size. Over the 7-year period, more than 200 children with AHO were hospitalized at our institution, but only 76 cases were ultimately included. While most exclusions were due to incomplete clinical data, the high exclusion rate may still potentially affect the generalizability of the results. Cases with incomplete clinical information were excluded based on indicators mentioned in relevant guidelines and literature, which enhanced the homogeneity of the study population and facilitated comparative analysis. This approach allowed us to identify statistically significant factors through regression analysis, thereby improving the standardization of the statistical results.

Conclusion

Age, peak levels of CRP/ESR/PCT/D-dimer, osteomyelitis severity (Lawson score), femoral involvement in osteomyelitis, and concurrent pneumonia were significantly associated with secondary deep vein thrombosis (DVT) in pediatric acute hematogenous osteomyelitis (AHO). Among these, age, peak D-dimer levels, and concurrent pneumonia were identified as independent risk factors for DVT in children with AHO.

The current predictive model demonstrated good performance in this cohort, providing early warning for potential DVT risk in pediatric AHO patients. However, multicenter studies are needed to further validate its generalizability.

Pediatricians may use this model to assess the necessity of DVT screening, reduce missed diagnoses, and initiate timely antithrombotic therapy to prevent adverse outcomes.

Authors’ contributions

Acknowledgments Firstly, I would like to express my gratitude to Professor Qiang Wang, my esteemed teacher, for his invaluable feedback on revisions and technical guidance. Jiale Guo, offering formal analysis and associated corrections. Hanwen Zhang, writing assistance, or proofreading the article. Baojian Song, providing spiritual motivation and empirical evidence support. Wei Feng/Danjiang Zhu/Yuwei Wen, assisting with ideas, language creating illustrations, and generating tables. All authors read and approved the final manuscript. The study was conducted without any financial support. Thank you immensely for your invaluable assistance.

Funding

Supported by Beijing Natural Science Foundation (L242167).

Data availability

Availability of Data and Materials The datasets and analysis materials used in this study are available from the corresponding author upon reasonable request. Due to patient privacy and ethical restrictions, some data may require anonymization or approval from the relevant ethics committee before being provided. If further adjustments are needed or if there are specific journal requirements, please let me know!

If further adjustments are needed or if there are specific journal requirements, please let me know!

Declarations

Ethics approval and consent to participate

This study has been approved by the Ethics Committee of Beijing Children's Hospital, affiliated with Capital Medical University, in compliance with Chinese laws and regulations as well as the Declaration of Helsinki. Informed consent was obtained from all participants, and the study has been authorized to be conducted at our hospital (Ethics Approval Number: [2025] -E-082-R).

Consent for publication

All participants or their legal guardians provided written consent for the publication of the data and results obtained from this study.

Competing interests

The authors declare no competing interests.