ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Objective:To explore the accuracy of in-room on-rails CT (IRCT) for image-guided radiotherapy (IGRT) and adaptive radiotherapy (ART) during proton and heavy-ion radiotherapy.Methods:The positioning accuracy and registration accuracy of IRCT were tested by using the spherical phantom and multiple imaging modality iso-centricity, and the positioning accuracy of isocenter geometric mapping and 3D-3D registration accuracy were evaluated when the phantoms were applied to IGRT. Standard water-aluminum phantom and ACR467 phantom were utilized to establish and evaluate the HU value-relative linear stopping power to water (RLSP) conversion curve. By scanning the same rigid phantom images on both IRCT and planned CT, followed by dose calculation and comparison of dose differences, the consistency of dose distribution between 2 modalities was evaluated when applied to ART in relation to the planned CT. Pre-treatment CT of patient was acquired using IRCT scan before treatment. Online qualitative analysis and offline quantitative analysis were performed. A case of prostate cancer was selected, and its online qualitative analysis ability was tested by evaluating whether IRCT could effectively identify changes in the position of clinical target volume (CTV) and critical organs at risk. One case of prostate cancer and 1 case of breast cancer were selected, and the offline quantitative analysis ability was tested by the key dose volume histogram parameters of dose recalculation on CT before treatment.Results:In IGRT application, the isocenter geometric mapping positioning accuracy was 0.1 mm. The displacement accuracy for 3D-3D registration was 0.8 mm, with a rotational accuracy of 0.6°. In ART application, a CT HU value-RLSP conversion curve was established using standard methods. The RLSP variation range for 24 representative tissues was -3.91% to 1.49%, with an average variation of -0.75%±0.95%. Calculation results performed on rigid phantoms for head, chest, and abdominal-pelvic regions showed that compared to the planned CT, the γ pass rate for proton plan dose distribution consistency on IRCT was>97%, and >95% for carbon-ion plan, both using 2%/2 mm criteria with a 10% threshold. The results of 2 representative clinical applications showed that online qualitative analysis of carbon-ion plans for prostate cancer could identify changes in patient soft tissue position relative to the planned CT, CTV, and critical organs at risk before treatment. Offline quantitative analysis could quantify dose changes in patients undergoing treatment. In the prostate cancer original plan for prostate cancer, the relative volume of CTV receiving 95% (V 95%) of the prescribed dose was 100%, which were 97.63% and 99.91% before different fractions of treatment, respectively. For the bladder and rectum, V 95% was 3.00% and 3.80%, which were changed to 0.75% and 12.36% for one session of treatment, and 2.76% and 3.08% for another session of treatment, aligning with the results of online qualitative analysis. In the original plan for breast cancer, tumor bed CTV and breast CTV V 95% were 99.93% and 99.93%, which were 100.00% and 99.57% for one session of treatment and 92.32% and 93.13% for another session of treatment, triggering re-planning. The re-planned results were improved to 99.82% and 99.93%. Conclusions:IRCT can be applied to IGRT and ART in proton and heavy-ion radiotherapy, enabling accurate patient positioning verification and adjustment, as well as online anatomical qualitative analysis and offline dose quantitative analysis.

Objective:To explore the potential profiles of health literacy in patients with chronic atrophic gastritis (CAG) and analyze their influencing factors.Methods:A cross-sectional study was conducted to select CAG patients admitted to Nanjing Hospital of Traditional Chinese Medicine or attending outpatient clinics from January 2023 to June 2024 by convenience sampling method, and all patients participated in this study two months after treatment. The General Information Questionnaire, the General Self-Efficacy Scale, and the All-around Health Literacy Measurement Scale (AAHLS) were used to conduct the questionnaire survey. The three dimensions of AAHLS were used as exogenous indicators for potential profile analysis, to compare the differences in general information and self-efficacy of patients with different potential profiles, and to analyze the influencing factors of different potential profiles of health literacy in CAG patients by multi classification Logistic regression.Results:The recovery rate of valid questionnaires was 97.71%(256/262). Among the 256 patients, there were 164 males and 92 females, with 86 patients aged 18-44 years old, 110 patients aged 45-59 years old, and 60 patients aged ≥ 60 years old. The health literacy of CAG patients was categorized into 3 potential profiles, including the high health literacy-appraisal and application competence group (14.84%, 38/256), the medium health literacy-appraisal and application competence group (32.81%, 84/256), and the low health literacy-appraisal and application competence group (52.34%, 134/256). The results of multi classification Logistic regression analysis showed that when the low health literacy-appraisal and application competence group was used as a reference, aged 18-44 years old ( OR=8.954, 95% CI 2.049-39.127), poor self-efficacy ( OR=0.089, 95% CI 0.027-0.293), duration of disease <5 years ( OR=0.049, 95% CI 0.014-0.169), per capita monthly household income<3 000 yuan ( OR=0.072, 95% CI 0.018-0.299), and primary school education or below ( OR=0.016, 95% CI 0.003-0.088) were independent influences in the the high health literacy-appraisal and application competence group (all P<0.05); poorer self-efficacy ( OR=0.458, 95% CI 0.251-0.834) and per capita monthly household income<3 000 yuan ( OR=0.212, 95% CI 0.100-0.453) were independent influences in the medium health literacy-appraisal and application competence group (both P<0.05). Conclusions:The health literacy of CAG patients is obviously heterogeneous, and healthcare professionals in clinical work should adopt targeted assessment and intervention according to the different characteristics of each category in order to improve the health literacy of CAG patients.

Objective:To investigate the distribution of CGG repeat numbers in the FMR1 gene among reproductive-age women in China, providing data reference for carrier screening and genetic counseling of Fragile X syndrome. Methods:This cross-sectional study recruited 16 610 reproductive-age women from 12 medical institutions between July 2022 and October 2023. Peripheral venous blood samples (3 mL) were collected, and genomic DNA was extracted. The number of CGG repeats in the FMR1 gene was determined using the triplet-primed polymerase chain reaction (TP-PCR) combined with capillary electrophoresis technology. Statistical analyses were performed to assess the prevalence and distribution of CGG repeat expansions. Results:Among 16 610 women of childbearing age, 5 684 (34.220%) women had the same number of CGG repeats in the two alleles of FMR1 gene, and 10 926 (65.780%) women had different numbers of repeats in the two alleles. Among the 33 220 FMR1 alleles in 16 610 women of reproductive age, the most common CGG repeat numbers were 29 [48.645% (16 160/33 220)] and 30 [26.276% (8 729/33 220)], while the most frequent CGG genotype was CGG 29/29 [24.726% (4 107/16 610)]. The CGG repeat numbers of FMR1 gene were normal in 16 498 women (99.326%). Among the 112 women (0.674%) with CGG repeat abnormities, 96 (0.578%) women were classified as intermediate carriers, 15 (0.090%) as premutation carriers, and 1 (0.006%) as a full mutation carrier, whose CGG genotype was (36, >200). Conclusion:In the general reproductive-age female population in China, the normal CGG repeat numbers of the FMR1 gene account for 99.326%, while the intermediate carrier rate is 0.578%, and the combined carrier rate of the premutation and full mutation types is 0.096%.

Objective:To investigate the distribution of CGG repeat numbers in the FMR1 gene among reproductive-age women in China, providing data reference for carrier screening and genetic counseling of Fragile X syndrome. Methods:This cross-sectional study recruited 16 610 reproductive-age women from 12 medical institutions between July 2022 and October 2023. Peripheral venous blood samples (3 mL) were collected, and genomic DNA was extracted. The number of CGG repeats in the FMR1 gene was determined using the triplet-primed polymerase chain reaction (TP-PCR) combined with capillary electrophoresis technology. Statistical analyses were performed to assess the prevalence and distribution of CGG repeat expansions. Results:Among 16 610 women of childbearing age, 5 684 (34.220%) women had the same number of CGG repeats in the two alleles of FMR1 gene, and 10 926 (65.780%) women had different numbers of repeats in the two alleles. Among the 33 220 FMR1 alleles in 16 610 women of reproductive age, the most common CGG repeat numbers were 29 [48.645% (16 160/33 220)] and 30 [26.276% (8 729/33 220)], while the most frequent CGG genotype was CGG 29/29 [24.726% (4 107/16 610)]. The CGG repeat numbers of FMR1 gene were normal in 16 498 women (99.326%). Among the 112 women (0.674%) with CGG repeat abnormities, 96 (0.578%) women were classified as intermediate carriers, 15 (0.090%) as premutation carriers, and 1 (0.006%) as a full mutation carrier, whose CGG genotype was (36, >200). Conclusion:In the general reproductive-age female population in China, the normal CGG repeat numbers of the FMR1 gene account for 99.326%, while the intermediate carrier rate is 0.578%, and the combined carrier rate of the premutation and full mutation types is 0.096%.

Objective:To analyze the human immunodeficiency virus (HIV) screening status and the resulting residual risk (RR) among blood donors across 17 provincial blood centers in China.Methods:This study used a cross-sectional study. Data on HIV infection markers per 100 000 first-time donors (FD) and repeat donors (RD) from January 2015 to December 2024 were extracted from the National Blood Establishment Performance Comparison Information Management System. Questionnaires were used to collect each center′s HIV screening strategy, algorithm, serological test (ST) kit manufacturers, gray-zone setting for ST, and nucleic acid test (NAT) modality, method, and platform. The incidence-window-period model was used to calculate the residual risk for first-time donors (RR FD), repeat donors (RR RD), and total donors (RR TD) at each center. Horizontal and vertical analysis of RR FD, RR RD, and RR TD across centers and years were performed. Results:All 17 centers applied the same HIV screening strategy which was two rounds of ST followed by one round of NAT. Eight of them operated a single screening algorithm, six employed two algorithms and three used three. Eleven centers used both imported and domestic ST kits, five relied on domestic ST kits only, and one used imported ST kits only, while four centers never set a grey zone for ST throughout the decade. For NAT modalities, eight centers adopted both individual nucleic acid test (ID-NAT) and minipool nucleic acid test (MP-NAT), eight used MP-NAT only and one used ID-NAT only. Seven centers combined transcription mediated amplification (TMA) and polymerase chain reaction (PCR), nine used PCR only and one used TMA only, and fourteen centers ran both imported and domestic NAT systems, two used imported systems only and one used a domestic system only. Over the ten-year period, the mean RR FD across the centers ranged from 2.22 to 12.33 per 10 6 person-years, RR RD from 0.83 to 3.29 per 10 6 person-years and RR TD from 1.59 to 9.29 per 10 6 person-years, with center Z4 consistently showing the lowest values for all three metrics and center U4 recording the highest RR FD and RR TD, while center D2 had the highest RR RD. In 2024 compared with 2015, eleven centers achieved a lower RR FD and ten centers achieved lower RR RD and RR TD. The RR FD and RR TD of centers W2 and U4 displayed pronounced fluctuations and an upward trend in recent years. Conclusions:The 17 provincial blood centers maintain consistent HIV screening strategies, while demonstrating variations in screening algorithm, ST kit manufacturers, NAT modalities, methods, and platform. And the RR FD, RR RD, and RR TD differ across centers. Although most centers show declining trend in RR over the ten-year period, some centers exhibite data fluctuations with a rising trend, suggesting potential for further optimization of HIV screening protocols.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective:To explore the accuracy of in-room on-rails CT (IRCT) for image-guided radiotherapy (IGRT) and adaptive radiotherapy (ART) during proton and heavy-ion radiotherapy.Methods:The positioning accuracy and registration accuracy of IRCT were tested by using the spherical phantom and multiple imaging modality iso-centricity, and the positioning accuracy of isocenter geometric mapping and 3D-3D registration accuracy were evaluated when the phantoms were applied to IGRT. Standard water-aluminum phantom and ACR467 phantom were utilized to establish and evaluate the HU value-relative linear stopping power to water (RLSP) conversion curve. By scanning the same rigid phantom images on both IRCT and planned CT, followed by dose calculation and comparison of dose differences, the consistency of dose distribution between 2 modalities was evaluated when applied to ART in relation to the planned CT. Pre-treatment CT of patient was acquired using IRCT scan before treatment. Online qualitative analysis and offline quantitative analysis were performed. A case of prostate cancer was selected, and its online qualitative analysis ability was tested by evaluating whether IRCT could effectively identify changes in the position of clinical target volume (CTV) and critical organs at risk. One case of prostate cancer and 1 case of breast cancer were selected, and the offline quantitative analysis ability was tested by the key dose volume histogram parameters of dose recalculation on CT before treatment.Results:In IGRT application, the isocenter geometric mapping positioning accuracy was 0.1 mm. The displacement accuracy for 3D-3D registration was 0.8 mm, with a rotational accuracy of 0.6°. In ART application, a CT HU value-RLSP conversion curve was established using standard methods. The RLSP variation range for 24 representative tissues was -3.91% to 1.49%, with an average variation of -0.75%±0.95%. Calculation results performed on rigid phantoms for head, chest, and abdominal-pelvic regions showed that compared to the planned CT, the γ pass rate for proton plan dose distribution consistency on IRCT was>97%, and >95% for carbon-ion plan, both using 2%/2 mm criteria with a 10% threshold. The results of 2 representative clinical applications showed that online qualitative analysis of carbon-ion plans for prostate cancer could identify changes in patient soft tissue position relative to the planned CT, CTV, and critical organs at risk before treatment. Offline quantitative analysis could quantify dose changes in patients undergoing treatment. In the prostate cancer original plan for prostate cancer, the relative volume of CTV receiving 95% (V 95%) of the prescribed dose was 100%, which were 97.63% and 99.91% before different fractions of treatment, respectively. For the bladder and rectum, V 95% was 3.00% and 3.80%, which were changed to 0.75% and 12.36% for one session of treatment, and 2.76% and 3.08% for another session of treatment, aligning with the results of online qualitative analysis. In the original plan for breast cancer, tumor bed CTV and breast CTV V 95% were 99.93% and 99.93%, which were 100.00% and 99.57% for one session of treatment and 92.32% and 93.13% for another session of treatment, triggering re-planning. The re-planned results were improved to 99.82% and 99.93%. Conclusions:IRCT can be applied to IGRT and ART in proton and heavy-ion radiotherapy, enabling accurate patient positioning verification and adjustment, as well as online anatomical qualitative analysis and offline dose quantitative analysis.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.