Pathogenicity and Bro Gene Typing of Pediatric Lower Respiratory Tract Infections with Moraxella catarrhalis in Southwest Shandong, China

Pathogenicity and Bro Gene Typing of Pediatric Lower Respiratory Tract Infections with Moraxella catarrhalis in Southwest Shandong, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Pathogenicity and Bro Gene Typing of Pediatric Lower Respiratory Tract Infections with Moraxella catarrhalis in Southwest Shandong, China Yuhan Xiang, Jian Shi, Liang Han, Chengfan Yang, Shuhua Lu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5212547/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted 6 You are reading this latest preprint version Abstract Objective To investigate the etiology and clinical characteristics of Moraxella catarrhalis infections in the lower respiratory tract among pediatric patients in southwestern Shandong Province, China. This study aims to enhance early identification and diagnostic accuracy for laboratory physicians, while providing evidence to guide clinical diagnosis and treatment of Moraxella catarrhalis-related infections. Methods This retrospective cohort study analyzed pediatric patients with Moraxella catarrhalis lower respiratory tract infections in southwestern Shandong Province, China. Clinical isolates were obtained through standardized sputum/bronchoalveolar lavage collection protocols and subjected to microbiological identification, antimicrobial susceptibility testing, and molecular characterization of β-lactamase production and bro gene variants. Epidemiological patterns and clinical profiles were systematically evaluated using electronic medical record data spanning January 2020 to December 2023. Results During the 4-year surveillance period (2018–2021), Moraxella catarrhalis was isolated from 848 pediatric cases of lower respiratory tract infections, representing a 7.81% overall detection rate. Age-stratified analysis revealed the highest prevalence in infants aged 28 days to 1 year (9.69%), with significant seasonal variation peaking in the fourth quarter (11.58%, p < 0.05). Monomicrobial infections predominated (79.72%, 676/848), while polymicrobial cases (20.28%, 172/848) predominantly co-occurred with Streptococcus pneumoniae and Haemophilus influenzae. All isolates were confirmed through parallel testing using automated biochemical analyzers and MALDI-TOF mass spectrometry. Antimicrobial susceptibility profiling demonstrated complete susceptibility to ceftazidime, cefepime, and imipenem (100%), with ≥ 95% susceptibility rates to ciprofloxacin (98.2%), levofloxacin (97.6%), ceftriaxone (96.8%), cefuroxime (96.1%), tetracycline (95.4%), and chloramphenicol (95.1%). A concerning temporal escalation in erythromycin resistance was observed (69.73% in 2018 vs. 90.57% in 2021, χ²=41.32, p 93% across all years).β-lactamase production was detected in 96.58% (819/848) of isolates, with molecular characterization identifying bro-1 (94.51%, 774/819) and bro-2 (5.49%, 45/819) gene variants. The β-lactamase-negative subgroup (3.42%, 29/848) showed no significant epidemiological clustering. Conclusions Our surveillance study demonstrates that Moraxella catarrhalis lower respiratory tract infections in southwestern Shandong Province predominantly affect infants aged 28 days to 1 year, with significantly elevated seasonal incidence during the fourth quarter. Notably, we observed a concerning temporal escalation in erythromycin resistance and persistently high resistance rates to ampicillinand clindamycin throughout the 2018–2021 surveillance period. Crucially, β-lactamase hyperproduction particularly BRO-1 gene carriage emerged as the principal resistance mechanism against β-lactams, while maintained susceptibility to expanded-spectrum cephalosporins and carbapenems suggests preserved therapeutic options. These findings underscore the necessity for: Avoidance of macrolides and β-lactam/β-lactamase inhibitor combinations in empirical therapy; Continuous monitoring of BRO gene evolution patterns; Age-specific antimicrobial stewardship programs targeting infant populations. Health sciences/Diseases Health sciences/Medical research Moraxella catarrhalis Pediatric lower respiratory tract infections Antimicrobial resistance mechanisms β-lactamase genotypes Seasonal epidemiology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Moraxella catarrhalis (MC), a microaerophilic Gram-negative diplococcus first identified in 1896, is recognized globally as a significant respiratory pathogen and ranks as the third most common bacterial cause of pediatric lower respiratory tract infections (LRTIs)¹. MC is associated with community-acquired pneumonia and otitis media in children, chronic lower respiratory infections in adults, and poses a risk of nosocomial transmission. Epidemiological data indicate that MC accounts for 5–15% of pediatric LRTIs in high-income countries and 8–12% in resource-limited regions, with notable regional variations: studies report prevalence rates of 9–14% in India and 6–8% in Japan, where infections peak seasonally during winter months 2 , 3 . However, epidemiological studies on MC in China, particularly among pediatric populations, remain scarce. This four-year retrospective study analyzed 848 MC isolates from pediatric LRTIs in southwestern Shandong Province, a region with documented high antibiotic consumption rates. We characterized: Age-stratified incidence patterns; Temporal antimicrobial resistance trends; Molecular epidemiology of β-lactamase gene variants. Our findings address critical knowledge gaps in China's MC epidemiology while providing urgently needed evidence for updating pediatric antimicrobial stewardship programs in an era of escalating macrolide resistance. Results Clinical Infection Characteristics Over a four-year period, 10,853 pathogenic isolates were identified in pediatric lower respiratory tract infections, including 848 MC strains, yielding a detection rate of 7.81% (848/10,853). Other pathogen distributions are detailed in Table 1 . MC detection rates varied significantly across age groups: 5.34% (77/1,441), 9.69% (609/6,285), 7.11% (158/2,221), and 0.44% (4/906) (χ²=112.79, P < 0.001). Annual analysis revealed detection rates of 6.30% (185/2,936) in 2018, 6.34% (187/2,949) in 2019, 9.79% (211/2,155) in 2020, and 9.42% (265/2,813) in 2021 (χ²=39.99, P < 0.001). The seasonal distribution showed that the detection rates from the first quarter to the fourth quarter were 5.59% (146/2,611), 8.25% (189/2,290), 4.32% (105/2,428) and 11.58% (408/3,524), respectively, with statistically significant quarterly differences (χ²=113.225, P < 0.001). In the gender analysis, the detection rate was 8.11% (563/6,946) in males and 7.29% (285/3,907) in females, with no significant difference between the two groups (χ²=2.28, P = 0.131).The complete dataset is summarized in Table 2 . Multivariable logistic regression analysis assessed the independent effects of age, year, season, and gender on MC detection rates (Table 3 ). Among 848 MC-positive cases, monomicrobial infections predominated (79.72%, 676/848), while polymicrobial infections (MC co-detected with other bacteria) accounted for 20.28% (172/848) (Table 4 ). Table 1 Analysis of pathogen detection in pediatric lower respiratory tract infections Bacterial name n = 10853 percentage (%) Staphylococcus aureus 2508 23.11 Streptococcus pneumoniae 2057 18.95 Moraxelle catarrhalis 848 7.81 Klebsiella pneumoniae 823 7.58 Escherichia coli 726 6.69 Pseudomonas aeruginosa 434 4.00 Acinetobacter baumannii 238 2.19 Haemophilus influenzae 225 2.07 other 2994 27.59 Table 2 Demographic and clinical characteristics of patients with Moraxella catarrhalis infection clinical parameter Characteristic Number of positive bacteria detected( n = 10853) Number of MC strains detected( n = 848) Detection rate(%) χ 2 - value P- value Age group <=28days 1441 77 5.34 112.79 < 0.001 28days-1year 6285 609 9.69 1-6years 2221 158 7.11 6-14years 906 4 0.44 Year 2018 2936 185 6.30 39.99 < 0.001 2019 2949 187 6.34 2020 2155 211 9.79 2021 2813 265 9.42 quarter First Quarter 2611 146 5.59 128.85 < 0.001 Second Quarter 2290 189 8.25 Third Quarter 2428 105 4.32 Fourth Quarter 3524 408 11.58 Gender Male 6946 563 8.11 2.28 0.131 Female 3907 285 7.29 Table 3 Multivariable Logistic Regression Results Variable Adjusted OR 95% CI P -value Age Group (Ref: ≤28 days) 28days-1year 1.92 1.48–2.49 < 0.001 1-6years 1.35 0.99–1.83 0.054 6-14years 0.07 0.03–0.19 < 0.001 Year (Ref: 2018) 2019 1.01 0.81–1.25 0.945 2020 1.61 1.28–2.02 < 0.001 2021 1.56 1.25–1.94 < 0.001 Season (Ref: First Quarter) Second Quarter 1.55 1.23–1.95 < 0.001 Third Quarter 0.73 0.56–0.95 0.021 Fourth Quarter 2.45 2.01–2.98 < 0.001 Gender (Ref: Female) Male 1.14 0.98–1.33 0.096 Table 4 Analysis of mixed infection with Moraxella catarrhalis Mixed infection n (case) percentage (%) M. catarrhalis + Staphylococcus aureus 65 37.80 M. catarrhalis + Streptococcus pneumoniae 57 33.14 M. catarrhalis + Klebber pneumoniae 22 12.79 M. catarrhalis + Escherichia coli 11 6.40 M. catarrhalis + Haemophilus influenzae 6 3.49 M. catarrhalis + Pseudomonas aeruginosa 4 2.32 M. catarrhalis + Acinetobacter baumannii 1 0.06 M. catarrhalis + Staphylococcus aureus + Streptococcus pneumoniae 2 0.12 M. catarrhalis + Staphylococcus aureus + Escherichia coli 1 0.06 M. catarrhalis + Staphylococcus aureus + Haemophilus influenzae 2 0.12 M. catarrhalis + Escherichia coli +Streptococcus pneumoniae 1 0.06 Preliminary Identification of Moraxella catarrhalis MC is an aerobic bacterium that can be cultivated with minimal nutritional req-uirements, and it grows well at room temperature or 35°C. It thrives on various nutrient-rich media, such as blood agar and chocolate agar, on which it typically forms visible colonies within 24–48 hours. The colonies are described as "ice ball"-like in appearance, smooth, opaque, and milky white, with a diameter of 1–3 mm, and they can be easily scraped off the agar (Figs. 1 and 2 ).This bacterium does not form spores or flagella and is characterized by appears as Gram-negative diplococci upon Gram staining (Fig. 3 ). Morphologically, it can be confused with Neisseria spp. Instrumental Identification The 848 strains were identified as Moraxella catarrhalis using the NH cards provided with the fully automated microbial identification system, with 99% identification accuracy. Confirmation by VITEK-MS system also identified all strains as Moraxella catarrhalis, with an identification rate of 99.99%. The inter-method agreement reached 100% . Antibiotic Susceptibility Results The resistance profiles of MC to 13 different antimicrobial agents are presented in Table 5 : ampicillin (AMP), cefuroxime (CXM), chloramphenicol (CHL), ciprofloxacin (CIP), levofloxacin (LEV), erythromycin (ERY), tetracycline (TCY), ceftriaxone (CRO), imipenem (IPM), cefepime (FEP), clindamycin (CLI), ceftazidime (CAZ), and sulfamethoxazole (SXT). The susceptibility breakpoints were interpreted according to CLSI document M45-A2 (2016). Table 5 The antibiotic resistance rates of Moraxella catarrhalis to commonly used medications from January 2018 to December 2021.[n(%)] antimicrobial agents 2018 ( n = 185) 2019 ( n = 187) 2020 ( n = 211) 2021 ( n = 265) χ 2 - value P- value Clindamycin (DA) 184 (99.46) 187 (100) 211 (100) 265 (100) 3.588 0.218 Ampicillin (AMP) 173 (93.51) 180 (96.26) 210 (99.53) 258 (97.36) 10.382 0.01 Erythromycin (ERY) 129 (69.73) 137 (73.26) 175 (82.94) 240 (90.57) 37.515 < 0.01 Cefuroxime (CXM) 5 (2.70) 2 (1.07) 3 (1.42) 10 (3.77) 4.533 0.237 Tetracycline (TCY) 6 (3.24) 9 (4.81) 5 (2.37) 7 (2.64) 2.318 0.536 Chloramphenicol (CHL) 5 (2.70) 8 (4.28) 3 (1.42) 2 (0.75) 7.367 0.069 Ceftriaxone (CRO) 0 (0.00) 1 (0.53) 2 (0.95) 5 (1.8) 4.620 0.228 Ciprofloxacin (CIP) 0 (0.00) 0 (0.00) 0 (0.00) 1 (0.38) 2.203 1.000 Levofloxacin (LEV) 0 (0.00) 0 (0.00) 0 (0.00) 1 (0.38) 2.203 1.000 Imipenem (IPM) 0 (0.00) 0 (0.00) 0 (0.00) 0 (0.00) - - Cefepime (FEP) 0 (0.00) 0 (0.00) 0 (0.00) 0 (0.00) - - Ceftazidime (CAZ) 0 (0.00) 0 (0.00) 0 (0.00) 0 (0.00) - - Sulfamethoxazole-trimethoprim (SXT) 56 (30.27) 94 (50.27) 111 (52.61) 210 (79.25) 123.519 < 0.01 Note: "–" indicates no data available for statistical comparison. β-lactamase Assay Among the 848 strains of MC, 819 were positive for β-lactamase, accounting for 96.58%, while 29 were negative, accounting for 3.42%. Some of the results are shown in Fig. 4 . Analysis of BRO Enzyme Gene Results All 819 β-lactamase-positive strains of Moraxella catarrhalis carried the bro gene. Following PCR amplification, the bro gene was digested with a restriction endonuclease. The bro-1 gene produced a single high-quality band at 996 bp, while the bro-2 gene yielded two high-quality bands at 698 bp and 266 bp.Among the strains, 774 (94.51%) were positive for bro-1, while 45 (5.50%) carried bro-2.Some of the results are shown in Fig. 5 . Discussion Moraxella catarrhalis was long regarded as a non-pathogenic bacterium until the 1970s. In 1972, Verger and Riou first identified it as a respiratory pathogen through quantitative sputum studies. Subsequent research has systematically characterized the infectious spectrum of MC, revealing three primary clinical manifestations. First, localized infections including otitis media, sinusitis, and acute COPD exacerbations - with particular significance as a major causative agent of community-acquired pneumonia (CAP) in elderly COPD patients and children with recurrent otitis media 4,5 . Second, invasive infections such as bacteremia, meningitis, infective endocarditis, and osteomyelitis 6–9 , demonstrating its previously underestimated virulence. Third, infections in immunocompromised individuals, where it often progresses to lower respiratory tract infections (LRTI) with atypical presentations, requiring prompt treatment in HIV/AIDS patients and transplant recipients.Notably, M. catarrhalis has achieved significant clinical importance as both a key pathogen in COPD exacerbations and pediatric otitis media, and as the third most common respiratory pathogen after Streptococcus pneumoniae and Haemophilus influenzae - a status that confirms its increasing epidemiological relevance. Children represent a high-risk group for MC infection, with recent studies showing an overall isolation rate exceeding 9.0% over the past two years. This study revealed statistically significant differences in MC detection rates across pediatric age groups. Infants demonstrated the highest infection rate, followed by toddlers, with neonates showing the third highest rate and older children having the lowest prevalence. Several factors may explain these findings: neonates likely benefit from maternal antibodies that provide partial protection, while the decreasing infection rate with advancing age may reflect maturation of immune function and improved pathogen defense mechanisms. These results suggest that susceptibility to MC infection is strongly influenced by age-related immunological development 10 . MC infections demonstrate distinct seasonality, with peak isolation rates occurring in the fourth quarter (Q4) during the autumn-winter transition. Our data reveal a clear seasonal pattern: Q4 shows the highest detection rates, followed by Q2 and Q1, while Q3 consistently demonstrates the lowest prevalence. This contrasts with findings by Raveendran et al. 11 in India, where peak incidence occurred in Q1, suggesting regional variations in seasonal patterns that may correlate with local climatic conditions 12 . The Q4 surge observed in our study likely results from multiple interacting factors: cold, dry air impairs respiratory defenses; increased indoor crowding and PM 2.5 exposure enhance transmission; and concurrent viral epidemics further compromise mucosal immunity, facilitating MC colonization. In Southwest Shandong, these effects may be exacerbated by regional climate extremes and winter heating practices. These findings underscore the need for targeted interventions, including enhanced winter surveillance and environmental control measures, to effectively manage seasonal MC infection surges. MC frequently participates in polymicrobial infections alongside pathogens including Staphylococcus aureus, Streptococcus pneumoniae, and Klebsiella pneumoniae (see Table 4 for complete list). These mixed infections involve three key pathogenic mechanisms: (1) Synergistic interactions through β-lactamase production - MC secretes enzymes that inactivate penicillins and certain cephalosporins, thereby protecting β-lactam-sensitive copathogens like S. pneumoniae and promoting persistent, treatment-resistant infections 13 ; (2) Cooperative biofilm formation that enhances microbial resistance to both antibiotics and host immune defenses 13,14 ; and (3) Host susceptibility factors including immunocompromised states (e.g., diabetes, chronic liver disease, immunosuppressive therapies) and invasive medical procedures (e.g., endotracheal intubation, mechanical ventilation).The clinical management of MC-associated polymicrobial infections presents substantial challenges due to complex presentations and elevated antimicrobial resistance (AMR) risks, exacerbated by antibiotic selection pressure from overuse of broad-spectrum agents. An effective multidisciplinary approach requires: (1) Precision diagnostics combining microbiological testing, advanced imaging, and immune profiling; (2) Staged antimicrobial therapy initiating with β-lactam/β-lactamase inhibitor combinations before transitioning to targeted regimens; (3) Rigorous antimicrobial stewardship including resistance surveillance and de-escalation protocols; (4) Comprehensive supportive care encompassing respiratory support, abscess drainage, and immunomodulation; and (5) Systemic prevention through vaccination programs and infection control policies. This integrated framework addresses both individual patient outcomes and the broader AMR crisis through balanced diagnostic, therapeutic, and preventive strategies. MC exhibits colonial and cellular morphological characteristics that closely resemble those of phylogenetically related bacteria, particularly Neisseria species, posing significant challenges for accurate identification. To enhance MC isolation efficiency, our study utilized vancomycin-supplemented (50 mg/L) chocolate agar, which selectively inhibits Gram-positive bacteria while promoting MC growth. Suspected MC colonies were initially screened based on distinctive morphological features (dry surface, tough texture, grayish-white coloration, semi-transparency, and collective mobility) and confirmed by Gram staining. Definitive identification was achieved through parallel testing using both the NH card system (fully automated microbial identification) and VITEK-MS mass spectrometry, demonstrating 100% concordance between methods. The VITEK-MS platform proved particularly advantageous, offering rapid, reliable identification that could be readily implemented in appropriately equipped clinical laboratories. The global emergence of β-lactamase-producing MC has reached alarming levels, with recent studies reporting detection rates exceeding 95% 3,15–16 . These chromosomally or plasmid-mediated enzymes predominantly exist as three genotypes: Bro-1 (> 90% prevalence), Bro-2 (< 10%), and the rare Bro-3 17 . While structurally similar, Bro-1 demonstrates significantly higher enzymatic activity than Bro-2 18 . Our four-year analysis of 848 MC strains revealed 96.58% were β-lactamase producers, with Bro-1 (94.51%) and Bro-2 (5.49%) genotypes exclusively detected. This genotypic profile correlated with > 93% ampicillin resistance while maintaining susceptibility to later-generation cephalosporins.The clinical implications are profound: Bro-1-mediated β-lactamase inactivation of first-line antibiotics forces reliance on broader-spectrum alternatives like amoxicillin-clavulanate, potentially accelerating resistance in co-pathogens. Notably, MC's β-lactamase activity provides indirect protection to β-lactam-susceptible organisms in polymicrobial infections, facilitating multidrug-resistant communities. Our findings align with international reports showing 99.6% β-lactamase production in Japan 3 and 99.4% in China 19 , with concerning resistance patterns to cefaclor (80% in UK/Ireland) and cefuroxime (5%) 2 .Antimicrobial susceptibility testing revealed preserved activity against ceftazidime, cefepime, and imipenem, with minimal resistance (≤ 5%) to ciprofloxacin, levofloxacin, ceftriaxone, cefuroxime, tetracycline, and chloramphenicol - likely due to restricted pediatric use. However, we observed a disturbing temporal increase in erythromycin resistance (69.73% in 2018 vs. 90.57% in 2021; P 93%) and clindamycin (> 99%). These trends reflect regional antibiotic misuse patterns, particularly in China where macrolides are empirically prescribed for 78% of pediatric respiratory infections without microbiological confirmation 19 .To address this crisis, we recommend: (1) prioritizing β-lactamase inhibitor combinations, (2) implementing rapid Bro-1 screening for targeted therapy, and (3) accelerating vaccine development against MC outer membrane proteins. These measures should be complemented by antimicrobial stewardship programs to curb inappropriate macrolide use, particularly in high-prescribing regions like Shandong Province where 35% of pediatric antibiotic prescriptions deviate from guidelines 19 . MC employs multiple virulence mechanisms to establish infections in pediatric populations, extending beyond its well-documented antibiotic resistance. Key pathogenic factors include: (1) UspA1-mediated adhesion facilitating nasopharyngeal colonization; (2) robust biofilm formation that enhances persistence and reduces antimicrobial efficacy; and (3) sophisticated immune evasion strategies through lipooligosaccharide (LoS) modifications and complement inhibition. These virulence determinants enable MC to maintain prolonged colonization in children's upper respiratory tracts and exploit viral-induced mucosal damage to cause secondary infections. The biofilm-forming capacity presents particular therapeutic challenges by creating physical and physiological barriers to antibiotic penetration, highlighting the need for combination approaches that simultaneously target resistance mechanisms and virulence factors. Future research should focus on molecular characterization of these virulence determinants to develop novel therapeutic strategies, especially for high-risk pediatric groups with recurrent infections or compromised immunity. MC has emerged as a clinically significant pathogen, presenting substantial diagnostic and therapeutic challenges. Current research continues to elucidate its pathogenicity, resistance mechanisms, and optimal treatment strategies. Clinicians should remain vigilant regarding MC’s potential risk factors, including host susceptibility and seasonal trends, while implementing long-term surveillance of infection rates and antimicrobial resistance patterns. To combat rising resistance, antibiotic stewardship programs must emphasize pathogen-directed therapy, favoring β-lactam/β-lactamase inhibitor combinations (e.g., amoxicillin-clavulanate) or third-generation cephalosporins (e.g., ceftriaxone) over ineffective options like macrolides or ampicillin. Infants and patients presenting during winter months—when MC prevalence peaks—require particular attention, with carbapenems or cefepime reserved for severe infections. Additionally, comprehensive management strategies, including nutritional optimization, comorbidity control, and immunomodulatory support, play a crucial role in improving clinical outcomes. Vaccination represents a promising strategy to curb MC infections and associated antimicrobial resistance 20–21 . Preclinical studies of UspA (ubiquitous surface protein A)- and Hag (hemagglutinin)-based vaccine candidates have demonstrated 68–73% colonization reduction in murine model 22 , while phase I trials of MCV-101 are evaluating safety and IgG titers in healthy volunteers 23 . However, persistent challenges including antigenic drift (UspA2 allele variability > 12%) and IgA protease-mediated mucosal immune evasion require resolution. Future development should prioritize hexavalent formulations targeting MC, Streptococcus pneumoniae, and Haemophilus influenzae, aligned with WHO Expanded Program on Immunization schedules. This study has limitations. First, its single-center retrospective design and dependence on laboratory registry data may introduce ascertainment bias, limiting external validity. MC prevalence and resistance profiles may vary across climatic zones and antibiotic stewardship intensities. Second, limited enrollment of school-aged children (6–14 years; n = 4) restricts age-stratified immunological analyses. Finally, pandemic-related specimen collection reductions in 2020 (23% below baseline) may confound temporal resistance pattern interpretations. Prospective multicenter surveillance incorporating whole-genome sequencing and defined daily dose monitoring is imperative to establish causal relationships between genotype-phenotype concordance and antibiotic consumption patterns. Conclusions Lower respiratory tract infections caused by MC are predominantly observed in infants aged 28 days to 1 year, with significantly elevated incidence during the fourth quarter. Complete concordance was observed between automated biochemical identification systems and MALDI-TOF mass spectrometry. All isolates demonstrated complete susceptibility to ceftazidime, cefepime, and imipenem, with sustained high susceptibility rates to ciprofloxacin, levofloxacin, ceftriaxone, cefuroxime, tetracycline, and chloramphenicol. A significant temporal escalation in erythromycin resistance was documented, while ampicillin and clindamycin resistance remained persistently high. β-lactamase production was detected in 96.6% of clinical isolates, with bro-1 gene variants predominating. Methods Bacterial Isolate Collection A total of 848 MC clinical isolates were obtained from pediatric patients with lower respiratory tract infections at our institution between January 2018 and December 2021. Isolates were cryopreserved at -80°C in trypticase soy broth with 20% glycerol. Inclusion Criteria (1) Clinically confirmed respiratory infection (cough, fever, abnormal chest imaging); (2) Significant MC growth (semi-quantitative culture ≥++); (3) Age stratification: neonates (≤ 28 days), infants (29 days-1 year), toddlers (1–6 years), children (6–14 years); (4) Primary culture analysis without selective subculturing. Polymicrobial infections were defined by concurrent isolation of ≥ 2 pathogenic species meeting quantitative thresholds. Ethical Compliance The study protocol (Approval No. 2023-08-C020) was reviewed by the Ethics Committee of Affiliated Hospital of Jining Medical University. Legal guardians provided written informed consent prior to enrollment. All procedures adhered to the ethical principles of the Declaration of Helsinki (2013 revision). Instruments and Reagents Blood agar plates, China Blue agar plates, and Chocolate agar plates (Zhengzhou Antu); Vitek-2 Compact automated bacterial identification system, VITEK2 NH identification cards, and an automated rapid microbial mass spectrometry detection system (bioMérieux, France); Iso-Sensitest Agar (ISA), lysed horse blood, digestion solution, and antibiotic susceptibility disks (Oxoid, UK); β-lactamase detection reagents (Chongqing Pongtong); Etest antibiotic susceptibility strips (Zhengzhou Antu); Taq polymerase (Nanjing Novozymes), DNA extraction kits (Jiangsu Cowin Biotech), Bcg I restriction enzyme (BioLabs, UK), and PCR primers (BGI Genomics). The primers for the Bro gene were as follows: Forward Bro-F 5′-ATAATGATGCAACGCCGTCAT-3′ Reverse Bro-R 5′-GGCTTGTTGGGTCATAAATT-3′ Bacterial Culture and Staining After thawing, enrichment, and cultivation, the strains were isolated and cultured in accordance with the requirements of the "National Clinical Laboratory Procedures" (4th Edition). Growth was observed after 24 hours, with an observation period lasting 2 to 5 days. Suspicious single colonies were selected for smear preparation and Gram staining. Bacterial Identification Bacterial identification was performed using the Vitek-2 Compact automated bacterial identification system (NH card), and the results were confirmed with the automated rapid microbial mass spectrometry detection system (VITEK-MS). β-lactamase Assay The terminal filter paper of the β-lactamase test strip was moistened with cold condensate or clean water. A loop or a small wooden/bamboo stick was used to pick a suspicious colony to be tested and streak it on the filter paper. After incubation at 35°C ± 2°C for 1 minute, the presence of a red color indicated a positive result, while no significant color change indicated a negative result. Antibiotic Susceptibility Testing Antibiotic susceptibility testing was performed using the Kirby-Bauer (K-B) method and the E-test to assess the in vitro susceptibility of MC to commonly used antibiotics. The interpretation of susceptibility results was based on the CLSI-M45-A2 2016 Edition guidelines and standards, using quality control strains of Staphylococcus aureus ATCC 29213, ATCC 25923, and Haemophilus influenzae ATCC 49766. BRO Gene Amplification and Restriction Enzyme Analysis Genomic DNA was extracted according to the kit instructions, followed by PCR amplification. The reaction mixture included 2 µl of DNA template, 2 µl of each primer, 25 µl of Taq polymerase, and 19 µl of sterile deionized water, totaling 50 µl. The amplification conditions were as follows: initial denaturation at 95°C for 3 minutes, followed by 30 cycles consisting of 95°C for 15 seconds, 53°C for 15 seconds, and 72°C for 59 seconds, with a final extension at 72°C for 5 minutes. For restriction enzyme analysis, 15 µl of the amplified product was mixed with 2 U of BcgI enzyme and incubated at 37°C for 60 minutes, and then at 65°C for 20 minutes. The digested products were analyzed by 1.5% agarose gel electrophoresis, and the results were interpreted using the Tanon-1600 gel imaging system. Clinical Data Medical records of patients with MC lower respiratory tract infections in the pediatric department of our hospital from 2018 to 2021 were reviewed for a retrospective analysis of their epidemiological characteristics. Informed consent for participation in this study has been obtained from all participants or their legal guardians. Statistical Analysis Statistical analysis of antibiotic susceptibility results was performed using the WHONET 5.6 software. The SPSS 22.0 statistical software was utilized for the analysis of the specific data obtained. All quantitative data were expressed as mean ± standard deviation. Comparisons of continuous variables were made using the t -test, while categorical variables were compared using the Chi-square test, with n % used for representation. A multivariable logistic regression model was constructed to evaluate the independent effects of age, year, season, and gender on the detection rate of MC. A P -value of less than 0.05 was considered to indicate statistical significance. Declarations Acknowledgements None. Author contributions Yuhan Xiang and Jian Shi performed the study and composed this manuscript, while Liang Han are responsible for pictures and tables. Chengfan Yan were responsible for primary data generation and analysis. Shuhua Lu are responsible for the revision of the paper. In addition, we have a corresponding author in this manuscript. Shuhua Lu contributed to the study design and manuscript revisions. All the authors contributed to the article and approved the submitted version. Data availability statement The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request. Ethics statement The study protocol was approved by the Ethics Committee of Affiliated Hospital of Jining Medical University (2023-08-C020). Identifies the institutional and/or licensing committee that approved the experiments, including any relevant details. Funding information This work was supported by Key Research and Development Program of Jining, Shandong, China (2023YXNS191) and Nursery Project of Affiliated Hospital of Jining Medical University, Shandong,China (MP-MS-2022-020). Conflicts of interest The authors declare no competing interests. References Hou,h. et al.Establishment of a real-time fluorescence PCR assay for M. catarrhalis . Biotech (06), 693-698 (2022). https://link.cnki.net/doi/10.16519/j.cnki.1004-311x.2022.06.0109 Raveendran, S., Kumar, G., Sivanandan, R. N., & Dias, M. Moraxella catarrhalis : A Cause of Concern with Emerging Resistance and Presence of BRO Beta-Lactamase Gene-Report from a Tertiary Care Hospital in South India. International journal of microbiology , 2020, 7316257 (2020). https://doi.org/10.1155/2020/7316257 Yamada, K., Arai, K., & Saito, R. Antimicrobial susceptibility to β-lactam antibiotics and production of BRO β-lactamase in clinical isolates of Moraxella catarrhalis from a Japanese hospital. Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi , 50, 386–389 (2017). https://doi.org/10.1016/j.jmii.2016.08.003 Hirai, J. et al. Clinical characteristics of community-acquired pneumonia due to Moraxella catarrhalis in adults: a retrospective single-centre study. BMC infectious diseases , 20, 821 (2020). https://doi.org/10.1186/s12879-020-05564-9 Enosi Tuipulotu, D.et al. Immunity against Moraxella catarrhalis requires guanylate-binding proteins and caspase-11-NLRP3 inflammasomes. The EMBO journal , 42, e112558 (2023). https://doi.org/10.15252/embj.2022112558 Ishimaru, N. et al. Moraxella catarrhalis bacteremia in adult with cardiogenic pulmonary edema. Postgraduate medicine , 137, 121–125 (2025). https://doi.org/10.1080/00325481.2025.2463877 Anezaki, H., Terada, N., Kawamura, T., & Kurai, H. Moraxella catarrhalis bacteremic pneumonia. IDCases , 19, e00712 (2020). https://doi.org/10.1016/j.idcr.2020.e00712 Maierean, S. M., Marinescu, D. C., Croitoru, D. O., & Verma, A. A. Infectious endocarditis and vertebral osteomyelitis caused by Moraxella catarrhalis . BMJ case reports , 12, e228776 (2019). https://doi.org/10.1136/bcr-2018-228776 Harb, H., Al-Obaidi, H., Irannejad, K., & Bagheri, F. A Unique Case of Moraxella catarrhalis Meningitis Following Neurosurgical Intervention. Cureus , 16, e59689 (2024). https://doi.org/10.7759/cureus.59689 Liang, Y., Qin, X., Hou, G., Zhang, X., & Zhang, W. Changes of Moraxella catarrhalis infection in children before and after the COVID-19 pandemic, Zhengzhou, China. The Journal of infection , 86, 154–225 (2023). https://doi.org/10.1016/j.jinf.2022.11.029 Raveendran, S., Kumar, G., Sivanandan, R. N., & Dias, M. Moraxella catarrhalis : A Cause of Concern with Emerging Resistance and Presence of BRO Beta-Lactamase Gene-Report from a Tertiary Care Hospital in South India. International journal of microbiology , 2020, 7316257 (2020). https://doi.org/10.1155/2020/7316257 Ai, L., Zhou, C., Liu, B., Fang, L., & Gong, F. Changes in the Antimicrobial Resistance and Bacterial Epidemiology of Moraxella catarrhalis from Pediatric Community-Acquired Pneumonia Patients During the COVID-19 Pandemic: A 5-Year Study at a Tertiary Hospital of Southwest China. Microbial drug resistance (Larchmont, N.Y.) , 30, 415–421 (2024). https://doi.org/10.1089/mdr.2024.0064 Perez, A. C., & Murphy, T. F. Potential impact of a Moraxella catarrhalis vaccine in COPD. Vaccine , 37, 5551–5558 (2019). https://doi.org/10.1016/j.vaccine.2016.12.066 Schaar, V., Nordström, T., Mörgelin, M., & Riesbeck, K. Moraxella catarrhalis outer membrane vesicles carry β-lactamase and promote survival of Streptococcus pneumoniae and Haemophilus influenzae by inactivating amoxicillin. Antimicrobial agents and chemotherapy , 55, 3845–3853 (2011). https://doi.org/10.1128/AAC.01772-10 Flamm, R. K., Sader, H. S., Farrell, D. J., & Jones, R. N. Macrolide and tetracycline resistance among Moraxella catarrhalis isolates from 2009 to 2011. Diagnostic microbiology and infectious disease , 74, 198–200 (2012). https://doi.org/10.1016/j.diagmicrobio.2012.06.007 Sheikh, S. O., Fasih, N., Irfan, S., & Zafar, A. β-Lactamase production and antimicrobial susceptibility pattern of Moraxella catarrhalis isolates: report from Pakistan. Asian Pacific journal of tropical medicine , 7S1, S228–S231 (2014). https://doi.org/10.1016/S1995-7645(14)60237-6 McGregor, K., Chang, B. J., Mee, B. J., & Riley, T. V. Moraxella catarrhalis: clinical significance, antimicrobial susceptibility and BRO beta-lactamases. European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology , 17, 219–234 (1998). https://doi.org/10.1007/BF01699978 Khan, M. A. et al. bro {beta}-lactamase and antibiotic resistances in a global cross-sectional study of Moraxella catarrhalis from children and adults. The Journal of antimicrobial chemotherapy , 65, 91–97 (2010). https://doi.org/10.1093/jac/dkp401 Shi, W. et al. β-Lactamase production and antibiotic susceptibility pattern of Moraxella catarrhalis isolates collected from two county hospitals in China. BMC microbiology , 18, 77 (2018). https://doi.org/10.1186/s12866-018-1217-5 Perez, A. C., & Murphy, T. F. A Moraxella catarrhalis vaccine to protect against otitis media and exacerbations of COPD: An update on current progress and challenges. Human vaccines & immunotherapeutics , 13, 2322–2331 (2017). https://doi.org/10.1080/21645515.2017.1356951 Soltan, M. A. et al. In Silico Prediction of a Multitope Vaccine against Moraxella catarrhalis : Reverse Vaccinology and Immunoinformatics. Vaccines , 9, 669 (2021). https://doi.org/10.3390/vaccines9060669 Ysebaert, C. et al. UspA2 is a cross-protective Moraxella catarrhalis vaccine antigen. Vaccine , 39, 5641–5649 (2021). https://doi.org/10.1016/j.vaccine.2021.08.002 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Accepted 23 Apr, 2025 Reviews received at journal 14 Apr, 2025 Reviewers agreed at journal 14 Apr, 2025 Reviewers invited by journal 14 Apr, 2025 Submission checks completed at journal 10 Apr, 2025 First submitted to journal 08 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5212547","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":442865301,"identity":"6d265f20-69bc-4753-b7b2-fdbd4a92170a","order_by":0,"name":"Yuhan Xiang","email":"","orcid":"","institution":"Affiliated Hospital of Jining Medical University, Jining, China","correspondingAuthor":false,"prefix":"","firstName":"Yuhan","middleName":"","lastName":"Xiang","suffix":""},{"id":442865305,"identity":"3f63b821-2d33-4bab-b113-464eddd74ec5","order_by":1,"name":"Jian Shi","email":"","orcid":"","institution":"Jining Medical University, Jining, China","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Shi","suffix":""},{"id":442865310,"identity":"9d7e00f5-8f7f-4902-ade7-6c5033c9da79","order_by":2,"name":"Liang Han","email":"","orcid":"","institution":"Affiliated Hospital of Jining Medical University, Jining, China","correspondingAuthor":false,"prefix":"","firstName":"Liang","middleName":"","lastName":"Han","suffix":""},{"id":442865316,"identity":"c28c2397-9db0-40a2-8fa7-cfe5728d10b6","order_by":3,"name":"Chengfan Yang","email":"","orcid":"","institution":"Affiliated Hospital of Jining Medical University, Jining, China","correspondingAuthor":false,"prefix":"","firstName":"Chengfan","middleName":"","lastName":"Yang","suffix":""},{"id":442865323,"identity":"829f8b69-c05e-49e1-94c6-fa9008d62691","order_by":4,"name":"Shuhua Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYBACPgYGNgbGBiDJzNj+IfGPDQ8/ewN+LWwwLfzszMcYHjakyUj2HCBSi2Q/Wxrjw4bDNgY3HAhokUh/9ph3x2F5g8M8Zg8Sd5znYbjBwPjhYw4+LTnmxrxnDhtuOMxjbpB45jYP4+wGZsmZ2/BqYZPmbTvMCNRiIJHAdpuHWeYAGzMvXi3pz0Ba7KFazvGwAUkCWhLMQFoSZzazpUkkth3g4SGoheeNmeTctvTkfmbmwwYJZ5J5JHgONuP1Cz97+jOJt23Wtm38Bxsf/qiws7c/3nzww0c8WrABUDSNglEwCkbBKKAIAADKTk6mm1n3UAAAAABJRU5ErkJggg==","orcid":"","institution":"Affiliated Hospital of Jining Medical University, Jining, China","correspondingAuthor":true,"prefix":"","firstName":"Shuhua","middleName":"","lastName":"Lu","suffix":""}],"badges":[],"createdAt":"2024-10-06 11:08:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5212547/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5212547/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-99873-1","type":"published","date":"2025-04-29T15:57:19+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80833422,"identity":"5eb9aa55-c670-47bd-88f6-cbac3d328155","added_by":"auto","created_at":"2025-04-17 14:27:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":386772,"visible":true,"origin":"","legend":"\u003cp\u003eThe characteristics of bacterial colonies on blood agar plates.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5212547/v1/970071a5bc11df18a552c679.png"},{"id":80832178,"identity":"267ac0fe-1aa4-425b-a00f-8d8783d7f74e","added_by":"auto","created_at":"2025-04-17 14:19:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":387460,"visible":true,"origin":"","legend":"\u003cp\u003eThe characteristics of bacterial colonies on chocolate agar plates.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5212547/v1/a0344c3ac08dea09e944e75c.png"},{"id":80832179,"identity":"e70e606f-51d8-4713-b746-1755e9be7d17","added_by":"auto","created_at":"2025-04-17 14:19:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":616022,"visible":true,"origin":"","legend":"\u003cp\u003eAfter Gram staining, the morphology of bacterial colonies observed under the microscope.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5212547/v1/9aa8a55c635e94fede128d9a.png"},{"id":80831653,"identity":"0e28f1be-9602-4b3c-a394-ef4ae510aa3f","added_by":"auto","created_at":"2025-04-17 14:11:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":197835,"visible":true,"origin":"","legend":"\u003cp\u003eβ-lactamase Assay.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5212547/v1/c47f64c1a1ee90cb8b65334c.png"},{"id":80831656,"identity":"08d20d49-bf2e-46d7-9704-d5221c524070","added_by":"auto","created_at":"2025-04-17 14:11:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":155508,"visible":true,"origin":"","legend":"\u003cp\u003eThe electrophoretogram of the β-lactamase Bro gene from Moraxella catarrhalis after restriction enzyme digestion.\u003c/p\u003e\n\u003cp\u003e* M:Marker\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-5212547/v1/4871918decc950228ae0b04b.png"},{"id":81987694,"identity":"765fc9aa-9b5e-4c8d-bcfc-63be14cf2fa5","added_by":"auto","created_at":"2025-05-05 16:04:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2658307,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5212547/v1/84f92915-c5a9-4c69-a481-3e2e5afecbb0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pathogenicity and Bro Gene Typing of Pediatric Lower Respiratory Tract Infections with Moraxella catarrhalis in Southwest Shandong, China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMoraxella catarrhalis (MC), a microaerophilic Gram-negative diplococcus first identified in 1896, is recognized globally as a significant respiratory pathogen and ranks as the third most common bacterial cause of pediatric lower respiratory tract infections (LRTIs)\u0026sup1;. MC is associated with community-acquired pneumonia and otitis media in children, chronic lower respiratory infections in adults, and poses a risk of nosocomial transmission. Epidemiological data indicate that MC accounts for 5\u0026ndash;15% of pediatric LRTIs in high-income countries and 8\u0026ndash;12% in resource-limited regions, with notable regional variations: studies report prevalence rates of 9\u0026ndash;14% in India and 6\u0026ndash;8% in Japan, where infections peak seasonally during winter months\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. However, epidemiological studies on MC in China, particularly among pediatric populations, remain scarce. This four-year retrospective study analyzed 848 MC isolates from pediatric LRTIs in southwestern Shandong Province, a region with documented high antibiotic consumption rates. We characterized: Age-stratified incidence patterns; Temporal antimicrobial resistance trends; Molecular epidemiology of β-lactamase gene variants. Our findings address critical knowledge gaps in China's MC epidemiology while providing urgently needed evidence for updating pediatric antimicrobial stewardship programs in an era of escalating macrolide resistance.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eClinical Infection Characteristics\u003c/h2\u003e \u003cp\u003eOver a four-year period, 10,853 pathogenic isolates were identified in pediatric lower respiratory tract infections, including 848 MC strains, yielding a detection rate of 7.81% (848/10,853). Other pathogen distributions are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. MC detection rates varied significantly across age groups: 5.34% (77/1,441), 9.69% (609/6,285), 7.11% (158/2,221), and 0.44% (4/906) (χ\u0026sup2;=112.79, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Annual analysis revealed detection rates of 6.30% (185/2,936) in 2018, 6.34% (187/2,949) in 2019, 9.79% (211/2,155) in 2020, and 9.42% (265/2,813) in 2021 (χ\u0026sup2;=39.99, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The seasonal distribution showed that the detection rates from the first quarter to the fourth quarter were 5.59% (146/2,611), 8.25% (189/2,290), 4.32% (105/2,428) and 11.58% (408/3,524), respectively, with statistically significant quarterly differences (χ\u0026sup2;=113.225, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the gender analysis, the detection rate was 8.11% (563/6,946) in males and 7.29% (285/3,907) in females, with no significant difference between the two groups (χ\u0026sup2;=2.28, P\u0026thinsp;=\u0026thinsp;0.131).The complete dataset is summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Multivariable logistic regression analysis assessed the independent effects of age, year, season, and gender on MC detection rates (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among 848 MC-positive cases, monomicrobial infections predominated (79.72%, 676/848), while polymicrobial infections (MC co-detected with other bacteria) accounted for 20.28% (172/848) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of pathogen detection in pediatric lower respiratory tract infections\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBacterial name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10853\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003epercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStaphylococcus aureus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStreptococcus pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoraxelle catarrhalis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKlebsiella pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEscherichia\u0026nbsp;coli\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePseudomonas aeruginosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcinetobacter baumannii\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaemophilus influenzae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and clinical characteristics of patients with Moraxella catarrhalis infection\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eclinical parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of positive bacteria detected(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10853)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of MC strains detected(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;848)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDetection rate(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003cem\u003e-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;=28days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e112.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28days-1year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-6years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6-14years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e39.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2813\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003equarter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst Quarter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e128.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecond Quarter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThird Quarter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFourth Quarter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable Logistic Regression Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted \u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge Group (Ref: \u0026le;28 days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28days-1year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.48\u0026ndash;2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-6years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-14years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u0026ndash;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear (Ref: 2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.81\u0026ndash;1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.28\u0026ndash;2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.25\u0026ndash;1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeason (Ref: First Quarter)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond Quarter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.23\u0026ndash;1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThird Quarter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56\u0026ndash;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFourth Quarter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.01\u0026ndash;2.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (Ref: Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.98\u0026ndash;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of mixed infection with Moraxella catarrhalis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed infection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e(case)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003epercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Staphylococcus aureus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Streptococcus pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Klebber pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Escherichia\u0026nbsp;coli\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Haemophilus influenzae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Pseudomonas aeruginosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Acinetobacter baumannii\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Staphylococcus aureus\u0026thinsp;+\u0026thinsp;Streptococcus pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Staphylococcus aureus\u0026thinsp;+\u0026thinsp;Escherichia\u0026nbsp;coli\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Staphylococcus aureus\u0026thinsp;+\u0026thinsp;Haemophilus influenzae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. catarrhalis\u0026thinsp;+\u0026thinsp;Escherichia\u0026nbsp;coli\u0026nbsp;+Streptococcus pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePreliminary Identification of Moraxella catarrhalis\u003c/h3\u003e\n\u003cp\u003eMC is an aerobic bacterium that can be cultivated with minimal nutritional req-uirements, and it grows well at room temperature or 35\u0026deg;C. It thrives on various nutrient-rich media, such as blood agar and chocolate agar, on which it typically forms visible colonies within 24\u0026ndash;48 hours. The colonies are described as \"ice ball\"-like in appearance, smooth, opaque, and milky white, with a diameter of 1\u0026ndash;3 mm, and they can be easily scraped off the agar (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).This bacterium does not form spores or flagella and is characterized by appears as Gram-negative diplococci upon Gram staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Morphologically, it can be confused with Neisseria spp.\u003c/p\u003e \n\u003ch3\u003eInstrumental Identification\u003c/h3\u003e\n\u003cp\u003eThe 848 strains were identified as Moraxella catarrhalis using the NH cards provided with the fully automated microbial identification system, with 99% identification accuracy. Confirmation by VITEK-MS system also identified all strains as Moraxella catarrhalis, with an identification rate of 99.99%. The inter-method agreement reached 100% .\u003c/p\u003e\n\u003ch3\u003eAntibiotic Susceptibility Results\u003c/h3\u003e\n\u003cp\u003eThe resistance profiles of MC to 13 different antimicrobial agents are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: ampicillin (AMP), cefuroxime (CXM), chloramphenicol (CHL), ciprofloxacin (CIP), levofloxacin (LEV), erythromycin (ERY), tetracycline (TCY), ceftriaxone (CRO), imipenem (IPM), cefepime (FEP), clindamycin (CLI), ceftazidime (CAZ), and sulfamethoxazole (SXT). The susceptibility breakpoints were interpreted according to CLSI document M45-A2 (2016).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe antibiotic resistance rates of Moraxella catarrhalis to commonly used medications from January 2018 to December 2021.[n(%)]\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eantimicrobial\u003c/p\u003e \u003cp\u003eagents\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;185)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;187)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;211)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;265)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e \u003cem\u003e-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClindamycin (DA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e184 (99.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e211 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e265 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmpicillin (AMP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e173 (93.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180 (96.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e210 (99.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e258 (97.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErythromycin (ERY)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e129 (69.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137 (73.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e175 (82.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e240 (90.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCefuroxime (CXM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (2.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (3.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.237\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTetracycline (TCY)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (3.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (4.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (2.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (2.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChloramphenicol (CHL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (2.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (4.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCeftriaxone (CRO)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCiprofloxacin (CIP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevofloxacin (LEV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImipenem (IPM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCefepime (FEP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCeftazidime (CAZ)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSulfamethoxazole-trimethoprim (SXT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56 (30.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94 (50.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111 (52.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e210 (79.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e123.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: \"\u0026ndash;\" indicates no data available for statistical comparison.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eβ-lactamase Assay\u003c/h3\u003e\n\u003cp\u003eAmong the 848 strains of MC, 819 were positive for β-lactamase, accounting for 96.58%, while 29 were negative, accounting for 3.42%. Some of the results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of BRO Enzyme Gene Results\u003c/h2\u003e \u003cp\u003eAll 819 β-lactamase-positive strains of Moraxella catarrhalis carried the bro gene. Following PCR amplification, the bro gene was digested with a restriction endonuclease. The bro-1 gene produced a single high-quality band at 996 bp, while the bro-2 gene yielded two high-quality bands at 698 bp and 266 bp.Among the strains, 774 (94.51%) were positive for bro-1, while 45 (5.50%) carried bro-2.Some of the results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMoraxella catarrhalis was long regarded as a non-pathogenic bacterium until the 1970s. In 1972, Verger and Riou first identified it as a respiratory pathogen through quantitative sputum studies. Subsequent research has systematically characterized the infectious spectrum of MC, revealing three primary clinical manifestations. First, localized infections including otitis media, sinusitis, and acute COPD exacerbations - with particular significance as a major causative agent of community-acquired pneumonia (CAP) in elderly COPD patients and children with recurrent otitis media\u003csup\u003e4,5\u003c/sup\u003e. Second, invasive infections such as bacteremia, meningitis, infective endocarditis, and osteomyelitis\u003csup\u003e6–9\u003c/sup\u003e, demonstrating its previously underestimated virulence. Third, infections in immunocompromised individuals, where it often progresses to lower respiratory tract infections (LRTI) with atypical presentations, requiring prompt treatment in HIV/AIDS patients and transplant recipients.Notably, M. catarrhalis has achieved significant clinical importance as both a key pathogen in COPD exacerbations and pediatric otitis media, and as the third most common respiratory pathogen after Streptococcus pneumoniae and Haemophilus influenzae - a status that confirms its increasing epidemiological relevance.\u003c/p\u003e\n\u003cp\u003eChildren represent a high-risk group for MC infection, with recent studies showing an overall isolation rate exceeding 9.0% over the past two years. This study revealed statistically significant differences in MC detection rates across pediatric age groups. Infants demonstrated the highest infection rate, followed by toddlers, with neonates showing the third highest rate and older children having the lowest prevalence. Several factors may explain these findings: neonates likely benefit from maternal antibodies that provide partial protection, while the decreasing infection rate with advancing age may reflect maturation of immune function and improved pathogen defense mechanisms. These results suggest that susceptibility to MC infection is strongly influenced by age-related immunological development \u003csup\u003e10\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eMC infections demonstrate distinct seasonality, with peak isolation rates occurring in the fourth quarter (Q4) during the autumn-winter transition. Our data reveal a clear seasonal pattern: Q4 shows the highest detection rates, followed by Q2 and Q1, while Q3 consistently demonstrates the lowest prevalence. This contrasts with findings by Raveendran et al. \u003csup\u003e11\u003c/sup\u003e in India, where peak incidence occurred in Q1, suggesting regional variations in seasonal patterns that may correlate with local climatic conditions \u003csup\u003e12\u003c/sup\u003e. The Q4 surge observed in our study likely results from multiple interacting factors: cold, dry air impairs respiratory defenses; increased indoor crowding and PM 2.5 exposure enhance transmission; and concurrent viral epidemics further compromise mucosal immunity, facilitating MC colonization. In Southwest Shandong, these effects may be exacerbated by regional climate extremes and winter heating practices. These findings underscore the need for targeted interventions, including enhanced winter surveillance and environmental control measures, to effectively manage seasonal MC infection surges.\u003c/p\u003e\n\u003cp\u003eMC frequently participates in polymicrobial infections alongside pathogens including Staphylococcus aureus, Streptococcus pneumoniae, and Klebsiella pneumoniae (see Table 4 for complete list). These mixed infections involve three key pathogenic mechanisms: (1) Synergistic interactions through β-lactamase production - MC secretes enzymes that inactivate penicillins and certain cephalosporins, thereby protecting β-lactam-sensitive copathogens like S. pneumoniae and promoting persistent, treatment-resistant infections \u003csup\u003e13\u003c/sup\u003e; (2) Cooperative biofilm formation that enhances microbial resistance to both antibiotics and host immune defenses \u003csup\u003e13,14\u003c/sup\u003e; and (3) Host susceptibility factors including immunocompromised states (e.g., diabetes, chronic liver disease, immunosuppressive therapies) and invasive medical procedures (e.g., endotracheal intubation, mechanical ventilation).The clinical management of MC-associated polymicrobial infections presents substantial challenges due to complex presentations and elevated antimicrobial resistance (AMR) risks, exacerbated by antibiotic selection pressure from overuse of broad-spectrum agents. An effective multidisciplinary approach requires: (1) Precision diagnostics combining microbiological testing, advanced imaging, and immune profiling; (2) Staged antimicrobial therapy initiating with β-lactam/β-lactamase inhibitor combinations before transitioning to targeted regimens; (3) Rigorous antimicrobial stewardship including resistance surveillance and de-escalation protocols; (4) Comprehensive supportive care encompassing respiratory support, abscess drainage, and immunomodulation; and (5) Systemic prevention through vaccination programs and infection control policies. This integrated framework addresses both individual patient outcomes and the broader AMR crisis through balanced diagnostic, therapeutic, and preventive strategies.\u003c/p\u003e\n\u003cp\u003eMC exhibits colonial and cellular morphological characteristics that closely resemble those of phylogenetically related bacteria, particularly Neisseria species, posing significant challenges for accurate identification. To enhance MC isolation efficiency, our study utilized vancomycin-supplemented (50 mg/L) chocolate agar, which selectively inhibits Gram-positive bacteria while promoting MC growth. Suspected MC colonies were initially screened based on distinctive morphological features (dry surface, tough texture, grayish-white coloration, semi-transparency, and collective mobility) and confirmed by Gram staining. Definitive identification was achieved through parallel testing using both the NH card system (fully automated microbial identification) and VITEK-MS mass spectrometry, demonstrating 100% concordance between methods. The VITEK-MS platform proved particularly advantageous, offering rapid, reliable identification that could be readily implemented in appropriately equipped clinical laboratories.\u003c/p\u003e\n\u003cp\u003eThe global emergence of β-lactamase-producing MC has reached alarming levels, with recent studies reporting detection rates exceeding 95% \u003csup\u003e3,15–16\u003c/sup\u003e. These chromosomally or plasmid-mediated enzymes predominantly exist as three genotypes: Bro-1 (\u0026gt; 90% prevalence), Bro-2 (\u0026lt; 10%), and the rare Bro-3 \u003csup\u003e17\u003c/sup\u003e. While structurally similar, Bro-1 demonstrates significantly higher enzymatic activity than Bro-2 \u003csup\u003e18\u003c/sup\u003e. Our four-year analysis of 848 MC strains revealed 96.58% were β-lactamase producers, with Bro-1 (94.51%) and Bro-2 (5.49%) genotypes exclusively detected. This genotypic profile correlated with \u0026gt; 93% ampicillin resistance while maintaining susceptibility to later-generation cephalosporins.The clinical implications are profound: Bro-1-mediated β-lactamase inactivation of first-line antibiotics forces reliance on broader-spectrum alternatives like amoxicillin-clavulanate, potentially accelerating resistance in co-pathogens. Notably, MC's β-lactamase activity provides indirect protection to β-lactam-susceptible organisms in polymicrobial infections, facilitating multidrug-resistant communities. Our findings align with international reports showing 99.6% β-lactamase production in Japan\u003csup\u003e3\u003c/sup\u003e and 99.4% in China \u003csup\u003e19\u003c/sup\u003e, with concerning resistance patterns to cefaclor (80% in UK/Ireland) and cefuroxime (5%) \u003csup\u003e2\u003c/sup\u003e.Antimicrobial susceptibility testing revealed preserved activity against ceftazidime, cefepime, and imipenem, with minimal resistance (≤ 5%) to ciprofloxacin, levofloxacin, ceftriaxone, cefuroxime, tetracycline, and chloramphenicol - likely due to restricted pediatric use. However, we observed a disturbing temporal increase in erythromycin resistance (69.73% in 2018 vs. 90.57% in 2021; P \u0026lt; 0.001), alongside persistently high resistance to ampicillin (\u0026gt; 93%) and clindamycin (\u0026gt; 99%). These trends reflect regional antibiotic misuse patterns, particularly in China where macrolides are empirically prescribed for 78% of pediatric respiratory infections without microbiological confirmation \u003csup\u003e19\u003c/sup\u003e.To address this crisis, we recommend: (1) prioritizing β-lactamase inhibitor combinations, (2) implementing rapid Bro-1 screening for targeted therapy, and (3) accelerating vaccine development against MC outer membrane proteins. These measures should be complemented by antimicrobial stewardship programs to curb inappropriate macrolide use, particularly in high-prescribing regions like Shandong Province where 35% of pediatric antibiotic prescriptions deviate from guidelines \u003csup\u003e19\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eMC employs multiple virulence mechanisms to establish infections in pediatric populations, extending beyond its well-documented antibiotic resistance. Key pathogenic factors include: (1) UspA1-mediated adhesion facilitating nasopharyngeal colonization; (2) robust biofilm formation that enhances persistence and reduces antimicrobial efficacy; and (3) sophisticated immune evasion strategies through lipooligosaccharide (LoS) modifications and complement inhibition. These virulence determinants enable MC to maintain prolonged colonization in children's upper respiratory tracts and exploit viral-induced mucosal damage to cause secondary infections. The biofilm-forming capacity presents particular therapeutic challenges by creating physical and physiological barriers to antibiotic penetration, highlighting the need for combination approaches that simultaneously target resistance mechanisms and virulence factors. Future research should focus on molecular characterization of these virulence determinants to develop novel therapeutic strategies, especially for high-risk pediatric groups with recurrent infections or compromised immunity.\u003c/p\u003e\n\u003cp\u003eMC has emerged as a clinically significant pathogen, presenting substantial diagnostic and therapeutic challenges. Current research continues to elucidate its pathogenicity, resistance mechanisms, and optimal treatment strategies. Clinicians should remain vigilant regarding MC’s potential risk factors, including host susceptibility and seasonal trends, while implementing long-term surveillance of infection rates and antimicrobial resistance patterns. To combat rising resistance, antibiotic stewardship programs must emphasize pathogen-directed therapy, favoring β-lactam/β-lactamase inhibitor combinations (e.g., amoxicillin-clavulanate) or third-generation cephalosporins (e.g., ceftriaxone) over ineffective options like macrolides or ampicillin. Infants and patients presenting during winter months—when MC prevalence peaks—require particular attention, with carbapenems or cefepime reserved for severe infections. Additionally, comprehensive management strategies, including nutritional optimization, comorbidity control, and immunomodulatory support, play a crucial role in improving clinical outcomes.\u003c/p\u003e\n\u003cp\u003eVaccination represents a promising strategy to curb MC infections and associated antimicrobial resistance\u003csup\u003e20–21\u003c/sup\u003e. Preclinical studies of UspA (ubiquitous surface protein A)- and Hag (hemagglutinin)-based vaccine candidates have demonstrated 68–73% colonization reduction in murine model\u003csup\u003e22\u003c/sup\u003e, while phase I trials of MCV-101 are evaluating safety and IgG titers in healthy volunteers \u003csup\u003e23\u003c/sup\u003e. However, persistent challenges including antigenic drift (UspA2 allele variability \u0026gt; 12%) and IgA protease-mediated mucosal immune evasion require resolution. Future development should prioritize hexavalent formulations targeting MC, Streptococcus pneumoniae, and Haemophilus influenzae, aligned with WHO Expanded Program on Immunization schedules.\u003c/p\u003e\n\u003cp\u003eThis study has limitations. First, its single-center retrospective design and dependence on laboratory registry data may introduce ascertainment bias, limiting external validity. MC prevalence and resistance profiles may vary across climatic zones and antibiotic stewardship intensities. Second, limited enrollment of school-aged children (6–14 years; n = 4) restricts age-stratified immunological analyses. Finally, pandemic-related specimen collection reductions in 2020 (23% below baseline) may confound temporal resistance pattern interpretations. Prospective multicenter surveillance incorporating whole-genome sequencing and defined daily dose monitoring is imperative to establish causal relationships between genotype-phenotype concordance and antibiotic consumption patterns.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eLower respiratory tract infections caused by MC are predominantly observed in infants aged 28 days to 1 year, with significantly elevated incidence during the fourth quarter. Complete concordance was observed between automated biochemical identification systems and MALDI-TOF mass spectrometry. All isolates demonstrated complete susceptibility to ceftazidime, cefepime, and imipenem, with sustained high susceptibility rates to ciprofloxacin, levofloxacin, ceftriaxone, cefuroxime, tetracycline, and chloramphenicol. A significant temporal escalation in erythromycin resistance was documented, while ampicillin and clindamycin resistance remained persistently high. β-lactamase production was detected in 96.6% of clinical isolates, with bro-1 gene variants predominating.\u003c/p\u003e\u003c/div\u003e "},{"header":"Methods","content":"\u003ch2\u003eBacterial Isolate Collection\u003c/h2\u003e\u003cp\u003eA total of 848 MC clinical isolates were obtained from pediatric patients with lower respiratory tract infections at our institution between January 2018 and December 2021. Isolates were cryopreserved at -80°C in trypticase soy broth with 20% glycerol.\u003c/p\u003e\u003ch2\u003eInclusion Criteria\u003c/h2\u003e\u003cp\u003e(1) Clinically confirmed respiratory infection (cough, fever, abnormal chest imaging);\u003c/p\u003e\u003cp\u003e(2) Significant MC growth (semi-quantitative culture ≥++);\u003c/p\u003e\u003cp\u003e(3) Age stratification: neonates (≤ 28 days), infants (29 days-1 year), toddlers (1–6 years), children (6–14 years);\u003c/p\u003e\u003cp\u003e(4) Primary culture analysis without selective subculturing. Polymicrobial infections were defined by concurrent isolation of ≥ 2 pathogenic species meeting quantitative thresholds.\u003c/p\u003e\u003ch2\u003eEthical Compliance\u003c/h2\u003e\u003cp\u003eThe study protocol (Approval No. 2023-08-C020) was reviewed by the Ethics Committee of Affiliated Hospital of Jining Medical University. Legal guardians provided written informed consent prior to enrollment. All procedures adhered to the ethical principles of the Declaration of Helsinki (2013 revision).\u003c/p\u003e\u003ch2\u003eInstruments and Reagents\u003c/h2\u003e\u003cp\u003eBlood agar plates, China Blue agar plates, and Chocolate agar plates (Zhengzhou Antu); Vitek-2 Compact automated bacterial identification system, VITEK2 NH identification cards, and an automated rapid microbial mass spectrometry detection system (bioMérieux, France); Iso-Sensitest Agar (ISA), lysed horse blood, digestion solution, and antibiotic susceptibility disks (Oxoid, UK); β-lactamase detection reagents (Chongqing Pongtong); Etest antibiotic susceptibility strips (Zhengzhou Antu); Taq polymerase (Nanjing Novozymes), DNA extraction kits (Jiangsu Cowin Biotech), Bcg I restriction enzyme (BioLabs, UK), and PCR primers (BGI Genomics). The primers for the Bro gene were as follows:\u003c/p\u003e\u003cp\u003eForward Bro-F 5′-ATAATGATGCAACGCCGTCAT-3′\u003c/p\u003e\u003cp\u003eReverse Bro-R 5′-GGCTTGTTGGGTCATAAATT-3′\u003c/p\u003e\u003ch2\u003eBacterial Culture and Staining\u003c/h2\u003e\u003cp\u003eAfter thawing, enrichment, and cultivation, the strains were isolated and cultured in accordance with the requirements of the \"National Clinical Laboratory Procedures\" (4th Edition). Growth was observed after 24 hours, with an observation period lasting 2 to 5 days. Suspicious single colonies were selected for smear preparation and Gram staining.\u003c/p\u003e\u003ch2\u003eBacterial Identification\u003c/h2\u003e\u003cp\u003eBacterial identification was performed using the Vitek-2 Compact automated bacterial identification system (NH card), and the results were confirmed with the automated rapid microbial mass spectrometry detection system (VITEK-MS).\u003c/p\u003e\u003ch2\u003eβ-lactamase Assay\u003c/h2\u003e\u003cp\u003eThe terminal filter paper of the β-lactamase test strip was moistened with cold condensate or clean water. A loop or a small wooden/bamboo stick was used to pick a suspicious colony to be tested and streak it on the filter paper. After incubation at 35°C ± 2°C for 1 minute, the presence of a red color indicated a positive result, while no significant color change indicated a negative result.\u003c/p\u003e\u003ch2\u003eAntibiotic Susceptibility Testing\u003c/h2\u003e\u003cp\u003eAntibiotic susceptibility testing was performed using the Kirby-Bauer (K-B) method and the E-test to assess the in vitro susceptibility of MC to commonly used antibiotics. The interpretation of susceptibility results was based on the CLSI-M45-A2 2016 Edition guidelines and standards, using quality control strains of Staphylococcus aureus ATCC 29213, ATCC 25923, and Haemophilus influenzae ATCC 49766.\u003c/p\u003e\u003ch2\u003eBRO Gene Amplification and Restriction Enzyme Analysis\u003c/h2\u003e\u003cp\u003eGenomic DNA was extracted according to the kit instructions, followed by PCR amplification. The reaction mixture included 2 µl of DNA template, 2 µl of each primer, 25 µl of Taq polymerase, and 19 µl of sterile deionized water, totaling 50 µl. The amplification conditions were as follows: initial denaturation at 95°C for 3 minutes, followed by 30 cycles consisting of 95°C for 15 seconds, 53°C for 15 seconds, and 72°C for 59 seconds, with a final extension at 72°C for 5 minutes. For restriction enzyme analysis, 15 µl of the amplified product was mixed with 2 U of BcgI enzyme and incubated at 37°C for 60 minutes, and then at 65°C for 20 minutes. The digested products were analyzed by 1.5% agarose gel electrophoresis, and the results were interpreted using the Tanon-1600 gel imaging system.\u003c/p\u003e\u003ch2\u003eClinical Data\u003c/h2\u003e\u003cp\u003eMedical records of patients with MC lower respiratory tract infections in the pediatric department of our hospital from 2018 to 2021 were reviewed for a retrospective analysis of their epidemiological characteristics. Informed consent for participation in this study has been obtained from all participants or their legal guardians.\u003c/p\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eStatistical analysis of antibiotic susceptibility results was performed using the WHONET 5.6 software. The SPSS 22.0 statistical software was utilized for the analysis of the specific data obtained. All quantitative data were expressed as mean ± standard deviation. Comparisons of continuous variables were made using the \u003cem\u003et\u003c/em\u003e-test, while categorical variables were compared using the Chi-square test, with \u003cem\u003en\u003c/em\u003e% used for representation. A multivariable logistic regression model was constructed to evaluate the independent effects of age, year, season, and gender on the detection rate of MC. A \u003cem\u003eP\u003c/em\u003e-value of less than 0.05 was considered to indicate statistical significance.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u0026nbsp;\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYuhan Xiang and Jian Shi performed the study and composed this manuscript, while Liang Han are responsible for pictures and tables. Chengfan Yan were responsible for primary data generation and analysis. Shuhua Lu are responsible for the revision of the paper. In addition, we have a corresponding author in this manuscript. Shuhua Lu contributed to the study design and manuscript revisions. All the authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthics statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Ethics Committee of Affiliated Hospital of Jining Medical University (2023-08-C020). Identifies the institutional and/or licensing committee that approved the experiments, including any relevant details.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Key Research and Development Program of Jining, Shandong, China (2023YXNS191) and Nursery Project of Affiliated Hospital of Jining Medical University, Shandong,China (MP-MS-2022-020).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\n\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHou,h. et al.Establishment of a real-time fluorescence PCR assay for M. catarrhalis . \u003cem\u003eBiotech \u003c/em\u003e\u003cstrong\u003e(06),\u003c/strong\u003e693-698 (2022). https://link.cnki.net/doi/10.16519/j.cnki.1004-311x.2022.06.0109\u003c/li\u003e\n\u003cli\u003eRaveendran, S., Kumar, G., Sivanandan, R. 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UspA2 is a cross-protective Moraxella catarrhalis vaccine antigen. \u003cem\u003eVaccine\u003c/em\u003e, \u003cstrong\u003e39,\u003c/strong\u003e 5641\u0026ndash;5649 (2021). https://doi.org/10.1016/j.vaccine.2021.08.002\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Moraxella catarrhalis, Pediatric lower respiratory tract infections, Antimicrobial resistance mechanisms, β-lactamase genotypes, Seasonal epidemiology","lastPublishedDoi":"10.21203/rs.3.rs-5212547/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5212547/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo investigate the etiology and clinical characteristics of Moraxella catarrhalis infections in the lower respiratory tract among pediatric patients in southwestern Shandong Province, China. This study aims to enhance early identification and diagnostic accuracy for laboratory physicians, while providing evidence to guide clinical diagnosis and treatment of Moraxella catarrhalis-related infections.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study analyzed pediatric patients with Moraxella catarrhalis lower respiratory tract infections in southwestern Shandong Province, China. Clinical isolates were obtained through standardized sputum/bronchoalveolar lavage collection protocols and subjected to microbiological identification, antimicrobial susceptibility testing, and molecular characterization of β-lactamase production and bro gene variants. Epidemiological patterns and clinical profiles were systematically evaluated using electronic medical record data spanning January 2020 to December 2023.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eDuring the 4-year surveillance period (2018\u0026ndash;2021), Moraxella catarrhalis was isolated from 848 pediatric cases of lower respiratory tract infections, representing a 7.81% overall detection rate. Age-stratified analysis revealed the highest prevalence in infants aged 28 days to 1 year (9.69%), with significant seasonal variation peaking in the fourth quarter (11.58%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Monomicrobial infections predominated (79.72%, 676/848), while polymicrobial cases (20.28%, 172/848) predominantly co-occurred with Streptococcus pneumoniae and Haemophilus influenzae. All isolates were confirmed through parallel testing using automated biochemical analyzers and MALDI-TOF mass spectrometry. Antimicrobial susceptibility profiling demonstrated complete susceptibility to ceftazidime, cefepime, and imipenem (100%), with \u0026ge;\u0026thinsp;95% susceptibility rates to ciprofloxacin (98.2%), levofloxacin (97.6%), ceftriaxone (96.8%), cefuroxime (96.1%), tetracycline (95.4%), and chloramphenicol (95.1%). A concerning temporal escalation in erythromycin resistance was observed (69.73% in 2018 vs. 90.57% in 2021, χ\u0026sup2;=41.32, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while ampicillin and clindamycin resistance remained persistently high (\u0026gt;\u0026thinsp;93% across all years).β-lactamase production was detected in 96.58% (819/848) of isolates, with molecular characterization identifying bro-1 (94.51%, 774/819) and bro-2 (5.49%, 45/819) gene variants. The β-lactamase-negative subgroup (3.42%, 29/848) showed no significant epidemiological clustering.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur surveillance study demonstrates that Moraxella catarrhalis lower respiratory tract infections in southwestern Shandong Province predominantly affect infants aged 28 days to 1 year, with significantly elevated seasonal incidence during the fourth quarter. Notably, we observed a concerning temporal escalation in erythromycin resistance and persistently high resistance rates to ampicillinand clindamycin throughout the 2018\u0026ndash;2021 surveillance period. Crucially, β-lactamase hyperproduction particularly BRO-1 gene carriage emerged as the principal resistance mechanism against β-lactams, while maintained susceptibility to expanded-spectrum cephalosporins and carbapenems suggests preserved therapeutic options. These findings underscore the necessity for: Avoidance of macrolides and β-lactam/β-lactamase inhibitor combinations in empirical therapy; Continuous monitoring of BRO gene evolution patterns; Age-specific antimicrobial stewardship programs targeting infant populations.\u003c/p\u003e","manuscriptTitle":"Pathogenicity and Bro Gene Typing of Pediatric Lower Respiratory Tract Infections with Moraxella catarrhalis in Southwest Shandong, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 14:11:53","doi":"10.21203/rs.3.rs-5212547/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-04-23T07:27:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T17:54:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"40616017866091752516832384534154486524","date":"2025-04-14T17:38:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-14T11:31:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-10T07:09:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-08T07:23:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b344c380-3c4d-4c3b-9a3e-890c59f17245","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47149197,"name":"Health sciences/Diseases"},{"id":47149198,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2025-05-05T15:59:56+00:00","versionOfRecord":{"articleIdentity":"rs-5212547","link":"https://doi.org/10.1038/s41598-025-99873-1","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-04-29 15:57:19","publishedOnDateReadable":"April 29th, 2025"},"versionCreatedAt":"2025-04-17 14:11:53","video":"","vorDoi":"10.1038/s41598-025-99873-1","vorDoiUrl":"https://doi.org/10.1038/s41598-025-99873-1","workflowStages":[]},"version":"v1","identity":"rs-5212547","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5212547","identity":"rs-5212547","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}