Objective:To discuss the correlation of International Society of Urological Pathology (ISUP) pathological grading with 18F-prostate specific membrane antigen (PSMA)-1007 positron emission tomography-computed tomography (PET/CT) parameters and serum total prostate specific antigen (tPSA) in prostate cancer, and assess the clinical value of PET/CT combined with tPSA in predicting the ISUP pathological grade of prostate cancer. Methods:The correlation of ISUP pathological grade with primary parameters of PET/CT images and serum tPSA of 117 patients diagnosed with prostate cancer at Shanxi Cancer Hospital from August 2018 to February 2023 and taken 18F-PSMA-1007 PET/CT imaging were retrospectively analyzed. Univariate and multivariate logistic regressions were used to identify the independent influencing factors for ISUP pathological grading of prostate cancer. The receiver operating characteristic (ROC) curves were used to predict the efficacy between the high and low ISUP grades for prostate cancer. Results:Of the 117 patients, 20 were in ISUP Group 1, 25 in Group 2, 18 in Group 3, 32 in Group 4, and 22 in Group 5. Of these, 63 were in the low-grade group (Groups 1-3) and 54 were in the high-grade group (Groups 4-5). The tumor long diameter was 3.10 (2.05, 4.25) cm, the prostate volume was 40.11 (33.13, 51.85) cm 3, the serum tPSA was 19.71 (12.25, 42.83) ng/ml, the prostate specific antigen density (PSAD) was 0.51 (0.31, 1.01) ng·ml -1·cm -3, the maximum standard uptake value of the lesion (SUVmax) was 15.24 (10.87, 22.03), and the tumor/spleen uptake ratio (TSR) was 1.61 (1.08, 2.15) in the 117 patients. The correlation analysis displayed that the SUVmax, TSR, and tPSA were positively correlated with ISUP groups ( r=0.640, 0.619, and 0.500, P＜0.01). The differences among SUVmax, TSR, long diameter, tPSA, and PSAD were statistically significant when compared among the five ISUP groups ( H=48.98, 45.63, 26.82, 33.95, and 23.81, P＜0.001). The differencesin serum tPSA ( z=5.19), PSAD ( z=4.64), long diameter ( z=3.19), SUVmax ( z=5.57), and TSR ( z=5.53) of the patients between the low-grade group and the high-grade group were statistically significant ( P＜0.01). In multivariate analysis, TSR ( OR=4.172, 95% CI: 2.095-8.308, P＜0.001) and the serum tPSA ( OR=1.042, 95% CI: 1.014-1.070, P＜0.01) were independent influencing factors for ISUP grades. ROC analysis revealed that the area under the curve for the 18F-PSMA-1007 PET/CT parameters SUVmax and TSR to predict low- or high-grade ISUP for prostate cancer was 0.800 (95% CI: 0.717-0.883) and 0.797 (95% CI: 0.713-0.881), respectively. Among the 70 patients who underwent radical prostatectomy, the postoperative recurrence rate of high-grade ISUP patients was higher than that of low-grade patients (54.8% and 25.6%, χ 2=6.21, P＜0.05). Conclusions:18F-PSMA-1007 PET/CT has good application in predicting ISUP grading of prostate cancer. TSR and the serum tPSA are independent predictors for the pathological grade.

"Weibing" is a fundamental concept in traditional Chinese medicine (TCM), representing a transitional state characterized by diminished self-regulatory abilities without overt physiological or social dysfunction. This perspective delves into the biological foundations and quantifiable markers of Weibing, aiming to establish a research framework for early disease intervention. Here, we propose the "Health Quadrant Classification" system, which divides the state of human body into health, sub-health, disease-susceptible state, and disease. We suggest the disease-susceptible stage emerges as a pivotal point for TCM interventions. To understand the intrinsic dynamics of this state, we propose laboratory and clinical studies utilizing time-series experiments and stress-induced disease susceptibility models. At the molecular level, bio-omics technologies and bioinformatics approaches are highlighted for uncovering intricate changes during disease progression. Furthermore, we discuss the application of mathematical models and artificial intelligence in developing early warning systems to anticipate and avert the transition from health to disease. This approach resonates with TCM's preventive philosophy, emphasizing proactive health maintenance and disease prevention. Ultimately, our perspective underscores the significance of integrating modern scientific methodologies with TCM principles to propel Weibing research and early intervention strategies forward.

Objective:This study aims to develop a rapid identification technique for various genotypes of extended-spectrum β-lactamase (ESBL) producing Escherichia coli using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) in conjunction with machine learning algorithms. Methods:A total of 158 Escherichia coli strains were isolated from the clinical laboratory of the First Hospital of Jilin University from August 2018 to December 2022. Polymerase chain reaction (PCR) was employed to detect the CTX-M-1, CTX-M-8, CTX-M-9, and SHV genes. Mass spectral data of the bacterial strains were acquired by MALDI-TOF MS with a cooperative matrix of (E)-propyl α-cyano-4-hydroxycinnamate (CHCA-C3). Models based on random forest (RF), logistic regression (LR), and support vector machine (SVM) algorithms were constructed. The performance of the constructed models was evaluated using metrics including accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Mass spectral peaks exhibiting sensitivity and specificity exceeding 80% in the models were designated as characteristic peaks. To validate the efficacy of the cooperative matrix of CHCA-C3, clinical isolates of ESBL-producing Escherichia coli were analyzed by MALDI-TOF MS using the conventional CHCA matrix for comparative purposes. Results:Among the 158 strains of Escherichia coli, 91 strains produced ESBL, all of which were CTX-M genotype. The AUC values for the respective models were as follows: CTX-M-1 genotype exhibited AUC values of 0.98 for LR, 1.00 for RF, and 0.73 for SVM; CTX-M-9 genotype exhibited AUC values of 0.93 for LR, 0.99 for RF, and 0.76 for SVM; for CTX-M-8, all models achieved an AUC of 1.00, indicating excellent classification performance with respect to accuracy, specificity, and sensitivity. The characteristic mass spectral peaks associated with each genotype included: CTX-M-1 genotype at m/z 6 390; CTX-M-8 genotype at m/z 5 224, m/z 5 393, and m/z 9 021; CTX-M-9 genotype at m/z 5 161 and m/z 5 273. In the MALDI-TOF MS analysis conducted with the conventional CHCA matrix, the characteristic peak at m/z 9 021 for CTX-M-8 was the only one detected, with the characteristic peaks for CTX-M-1 and CTX-M-9 remaining undetected. Conclusion:The application of cooperative matrix of CHCA-C3 in conjunction with MALDI-TOF MS and machine learning algorithms facilitates the rapid and precise identification of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli. This approach offers a feasible solution for evidence-based clinical therapy and the control of healthcare-associated infections.

Objective:To discuss the correlation of pathologic findings after radical prostatectomy and preoperative 18F-PSMA-1007 PET/CT parameters with the prognosis of patients with prostate cancer. Methods:A retrospective case series study was conducted. The clinicopathological data of 48 patients with prostate cancer who underwent radical prostatectomy in Shanxi Province Cancer Hospital between January 2019 and August 2023 were retrospectively analyzed. All patients underwent 18F-PSMA-1007 PET/CT imaging before surgery. The age, the preoperative serum total prostate-specific antigen (tPSA), prostate-specific antigen density (PSAD), prostate volume, tumor diameter, TNM staging, the pathologic data after radical prostatectomy [International Society of Urological Pathology (ISUP) grade, resection margin status, nerve invasion], and preoperative maximum standard uptake value (SUV max) were collected. The receiver operating characteristic (ROC) curves were used to evaluate the efficacy of PET/CT parameter SUV max in predicting tumor recurrence after prostate cancer surgery. The recurrence-free survival (RFS) was analyzed by using the Kaplan-Meier method and log-rank test was performed. Cox proportional risk model was used to analyze the factors influencing RFS after radical prostatectomy. Results:All 48 patients were acinar adenocarcinoma. The median level of the patients' serum tPSA was 19.16 (10.50, 30.99) ng/ml; the median prostate volume was 36.20 (31.83, 45.48) ml; the median tumor diameter was 2.80 (1.60, 4.00) cm; the median PSAD was 0.48 (0.31,1.02) ng·ml -1·cm -3. The primary SUV max of prostate cancer was 13.61 (8.10, 20.20) . Of the 48 patients, 1 case died of heart disease and 1 case died of COVID-19 within 3 to 6 months after surgery, and the rest 46 patients were analyzed for prognosis. Among 46 cases, 26 were in the ISUP low-grade group and 20 were in the high-grade group; 17 were positive and 29 were negative for nerve invasion; 7 were positive and 39 were negative for margin status. The median follow-up time was 18.5 (8-64) months. There were 30 recurrence-free patients and 16 recurrent patients by the follow-up in April 2024. The median RFS time was 15 months; and there were statistically significant differences in RSF among the ISUP high-grade and low-grade groups, preoperative SUV max ≥ 16.77 and < 16.77 groups, positive and negative resection margin groups (all P < 0.01). SUV max was positively correlated with ISUP pathological grade and tPSA level ( r value was 0.634, 0.584, respectively; both P < 0.01). The differences in preoperative serum tPSA level, PSAD, tumor diameter, and SUV max were statistically significant between the ISUP low-grade group and the high-grade group (all P < 0.01); the differences in preoperative serum tPSA, PSAD, and tumor diameter were statistically significant between the nerve invasion positive group and nerve invasion negative group (all P < 0.01); the differences in preoperative serum tPSA, PSAD, tumor diameter, and SUV max between patients with positive resection margins or not were not statistically significant (all P > 0.05). Multivariate Cox regression analysis showed that the tumor resection margin status (negativity vs. positivity: HR = 7.82,95% CI: 1.97-31.07, P < 0.01), ISUP pathological grade (low grade vs. high grade: HR = 4.34,95% CI:1.21-15.62, P < 0.05), and the preoperative SUV max (<16.77 vs. ≥ 16.77: HR = 4.18, 95% CI:1.36-12.85 , P < 0.05) were independent influencing factors for RFS in patients with prostate cancer after radical prostatectomy. Conclusions:Pathological grading after radical prostatectomy and the preoperative 18F-PSMA-1007 PET/CT parameters are associated with the prognosis of patients with prostate cancer.

Objective:To discuss the correlation of International Society of Urological Pathology (ISUP) pathological grading with 18F-prostate specific membrane antigen (PSMA)-1007 positron emission tomography-computed tomography (PET/CT) parameters and serum total prostate specific antigen (tPSA) in prostate cancer, and assess the clinical value of PET/CT combined with tPSA in predicting the ISUP pathological grade of prostate cancer. Methods:The correlation of ISUP pathological grade with primary parameters of PET/CT images and serum tPSA of 117 patients diagnosed with prostate cancer at Shanxi Cancer Hospital from August 2018 to February 2023 and taken 18F-PSMA-1007 PET/CT imaging were retrospectively analyzed. Univariate and multivariate logistic regressions were used to identify the independent influencing factors for ISUP pathological grading of prostate cancer. The receiver operating characteristic (ROC) curves were used to predict the efficacy between the high and low ISUP grades for prostate cancer. Results:Of the 117 patients, 20 were in ISUP Group 1, 25 in Group 2, 18 in Group 3, 32 in Group 4, and 22 in Group 5. Of these, 63 were in the low-grade group (Groups 1-3) and 54 were in the high-grade group (Groups 4-5). The tumor long diameter was 3.10 (2.05, 4.25) cm, the prostate volume was 40.11 (33.13, 51.85) cm 3, the serum tPSA was 19.71 (12.25, 42.83) ng/ml, the prostate specific antigen density (PSAD) was 0.51 (0.31, 1.01) ng·ml -1·cm -3, the maximum standard uptake value of the lesion (SUVmax) was 15.24 (10.87, 22.03), and the tumor/spleen uptake ratio (TSR) was 1.61 (1.08, 2.15) in the 117 patients. The correlation analysis displayed that the SUVmax, TSR, and tPSA were positively correlated with ISUP groups ( r=0.640, 0.619, and 0.500, P＜0.01). The differences among SUVmax, TSR, long diameter, tPSA, and PSAD were statistically significant when compared among the five ISUP groups ( H=48.98, 45.63, 26.82, 33.95, and 23.81, P＜0.001). The differencesin serum tPSA ( z=5.19), PSAD ( z=4.64), long diameter ( z=3.19), SUVmax ( z=5.57), and TSR ( z=5.53) of the patients between the low-grade group and the high-grade group were statistically significant ( P＜0.01). In multivariate analysis, TSR ( OR=4.172, 95% CI: 2.095-8.308, P＜0.001) and the serum tPSA ( OR=1.042, 95% CI: 1.014-1.070, P＜0.01) were independent influencing factors for ISUP grades. ROC analysis revealed that the area under the curve for the 18F-PSMA-1007 PET/CT parameters SUVmax and TSR to predict low- or high-grade ISUP for prostate cancer was 0.800 (95% CI: 0.717-0.883) and 0.797 (95% CI: 0.713-0.881), respectively. Among the 70 patients who underwent radical prostatectomy, the postoperative recurrence rate of high-grade ISUP patients was higher than that of low-grade patients (54.8% and 25.6%, χ 2=6.21, P＜0.05). Conclusions:18F-PSMA-1007 PET/CT has good application in predicting ISUP grading of prostate cancer. TSR and the serum tPSA are independent predictors for the pathological grade.

Objective:To discuss the correlation of pathologic findings after radical prostatectomy and preoperative 18F-PSMA-1007 PET/CT parameters with the prognosis of patients with prostate cancer. Methods:A retrospective case series study was conducted. The clinicopathological data of 48 patients with prostate cancer who underwent radical prostatectomy in Shanxi Province Cancer Hospital between January 2019 and August 2023 were retrospectively analyzed. All patients underwent 18F-PSMA-1007 PET/CT imaging before surgery. The age, the preoperative serum total prostate-specific antigen (tPSA), prostate-specific antigen density (PSAD), prostate volume, tumor diameter, TNM staging, the pathologic data after radical prostatectomy [International Society of Urological Pathology (ISUP) grade, resection margin status, nerve invasion], and preoperative maximum standard uptake value (SUV max) were collected. The receiver operating characteristic (ROC) curves were used to evaluate the efficacy of PET/CT parameter SUV max in predicting tumor recurrence after prostate cancer surgery. The recurrence-free survival (RFS) was analyzed by using the Kaplan-Meier method and log-rank test was performed. Cox proportional risk model was used to analyze the factors influencing RFS after radical prostatectomy. Results:All 48 patients were acinar adenocarcinoma. The median level of the patients' serum tPSA was 19.16 (10.50, 30.99) ng/ml; the median prostate volume was 36.20 (31.83, 45.48) ml; the median tumor diameter was 2.80 (1.60, 4.00) cm; the median PSAD was 0.48 (0.31,1.02) ng·ml -1·cm -3. The primary SUV max of prostate cancer was 13.61 (8.10, 20.20) . Of the 48 patients, 1 case died of heart disease and 1 case died of COVID-19 within 3 to 6 months after surgery, and the rest 46 patients were analyzed for prognosis. Among 46 cases, 26 were in the ISUP low-grade group and 20 were in the high-grade group; 17 were positive and 29 were negative for nerve invasion; 7 were positive and 39 were negative for margin status. The median follow-up time was 18.5 (8-64) months. There were 30 recurrence-free patients and 16 recurrent patients by the follow-up in April 2024. The median RFS time was 15 months; and there were statistically significant differences in RSF among the ISUP high-grade and low-grade groups, preoperative SUV max ≥ 16.77 and < 16.77 groups, positive and negative resection margin groups (all P < 0.01). SUV max was positively correlated with ISUP pathological grade and tPSA level ( r value was 0.634, 0.584, respectively; both P < 0.01). The differences in preoperative serum tPSA level, PSAD, tumor diameter, and SUV max were statistically significant between the ISUP low-grade group and the high-grade group (all P < 0.01); the differences in preoperative serum tPSA, PSAD, and tumor diameter were statistically significant between the nerve invasion positive group and nerve invasion negative group (all P < 0.01); the differences in preoperative serum tPSA, PSAD, tumor diameter, and SUV max between patients with positive resection margins or not were not statistically significant (all P > 0.05). Multivariate Cox regression analysis showed that the tumor resection margin status (negativity vs. positivity: HR = 7.82,95% CI: 1.97-31.07, P < 0.01), ISUP pathological grade (low grade vs. high grade: HR = 4.34,95% CI:1.21-15.62, P < 0.05), and the preoperative SUV max (<16.77 vs. ≥ 16.77: HR = 4.18, 95% CI:1.36-12.85 , P < 0.05) were independent influencing factors for RFS in patients with prostate cancer after radical prostatectomy. Conclusions:Pathological grading after radical prostatectomy and the preoperative 18F-PSMA-1007 PET/CT parameters are associated with the prognosis of patients with prostate cancer.

Objective:This study aims to develop a rapid identification technique for various genotypes of extended-spectrum β-lactamase (ESBL) producing Escherichia coli using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) in conjunction with machine learning algorithms. Methods:A total of 158 Escherichia coli strains were isolated from the clinical laboratory of the First Hospital of Jilin University from August 2018 to December 2022. Polymerase chain reaction (PCR) was employed to detect the CTX-M-1, CTX-M-8, CTX-M-9, and SHV genes. Mass spectral data of the bacterial strains were acquired by MALDI-TOF MS with a cooperative matrix of (E)-propyl α-cyano-4-hydroxycinnamate (CHCA-C3). Models based on random forest (RF), logistic regression (LR), and support vector machine (SVM) algorithms were constructed. The performance of the constructed models was evaluated using metrics including accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Mass spectral peaks exhibiting sensitivity and specificity exceeding 80% in the models were designated as characteristic peaks. To validate the efficacy of the cooperative matrix of CHCA-C3, clinical isolates of ESBL-producing Escherichia coli were analyzed by MALDI-TOF MS using the conventional CHCA matrix for comparative purposes. Results:Among the 158 strains of Escherichia coli, 91 strains produced ESBL, all of which were CTX-M genotype. The AUC values for the respective models were as follows: CTX-M-1 genotype exhibited AUC values of 0.98 for LR, 1.00 for RF, and 0.73 for SVM; CTX-M-9 genotype exhibited AUC values of 0.93 for LR, 0.99 for RF, and 0.76 for SVM; for CTX-M-8, all models achieved an AUC of 1.00, indicating excellent classification performance with respect to accuracy, specificity, and sensitivity. The characteristic mass spectral peaks associated with each genotype included: CTX-M-1 genotype at m/z 6 390; CTX-M-8 genotype at m/z 5 224, m/z 5 393, and m/z 9 021; CTX-M-9 genotype at m/z 5 161 and m/z 5 273. In the MALDI-TOF MS analysis conducted with the conventional CHCA matrix, the characteristic peak at m/z 9 021 for CTX-M-8 was the only one detected, with the characteristic peaks for CTX-M-1 and CTX-M-9 remaining undetected. Conclusion:The application of cooperative matrix of CHCA-C3 in conjunction with MALDI-TOF MS and machine learning algorithms facilitates the rapid and precise identification of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli. This approach offers a feasible solution for evidence-based clinical therapy and the control of healthcare-associated infections.

Objective:To compare the prognostic values of different classification by using transpulmonary pressure gradient (TPG), diastolic pressure gradient (DPG) and pulmonary vascular resistance (PVR) in patients with pulmonary hypertension due to left heart disease (PH-LHD), and investigated hemodynamic and clinical factors associated with mortality in patients with PH-LHD.Methods:This was a single-center prospective cohort study. In-hospital patients diagnosed with PH-LHD via right heart catheterization at the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University, from September 2013 to December 2019 were enrolled. Patients were divided according to TPG (cutoff value 12 mmHg; 1 mmHg=0.133 kPa), DPG (cutoff value 7 mmHg), PVR (cutoff value 3 Wood Units), and the combination of TPG and PVR. Baseline characteristic was recorded. All patients were followed up until the occurrence of endpoint event, defined as all-cause death that occurred during the follow-up period, or until April 18, 2022. Receiver operating characteristic curves were used to compare the predictive value of 3 classification methods for all-cause death in PH-LHD patients. The optimal cutoff values were calculated using Jorden index. Survival analysis was performed using Kaplan-Meier analysis, and log-rank test was used to compare the predictive efficacy of classification methods based on optimal cutoff values or guidance-recommended thresholds for the survival of PH-LHD patients. Variables showing statistical significance in the univariate analysis were incorporated into multivariate Cox regression model to analyze the independent risk factors for all-cause mortality.Results:A total of 243 patients were enrolled, aged (54.9±12.7) years old, including 169 (69.5%) males. During a median follow-up of 57 months, there were 101 (41.6%) deaths occurred. Grouping results were as follows: (1) TPG: TPG≤12 mmHg group 115 patients, TPG>12 mmHg group 128 patients; (2) DPG: DPG<7 mmHg group 193 patients, DPG≥7 mmHg group 50 patients; (3) PVR: PVR≤3 Wood Units group 108 patients, PVR>3 Wood Units group 135 patients; (4) TPG and PVR: TPG≤12 mmHg and PVR≤3 Wood Units group 89 patients, TPG>12 mmHg and PVR>3 Wood Units group 109 patients. PVR ( AUC=0. 698,95% CI:0.631-0.766) had better predictive value for all-cause mortality than TPG ( AUC=0.596, 95% CI: 0.523-0.669) and DPG ( AUC=0.526, 95% CI: 0.452-0.601) (all P<0.05). The optimal cutoff values for TPG, DPG, and PVR were13.9 mmHg, 2.8 mmHg, and 3.8 Wood Units, respectively. Kaplan-Meier analysis based on the optimal cutoff values or guidance-recommended thresholds showed that PVR and TPG were the predictors of survival ( P<0.05), while DPG did not showed significance ( P>0.05). Multivariate Cox regression analysis showed that age, PVR and log 2N-terminal pro-B-type natriuretic peptide were independent risk factors for all-cause mortality in PH-LHD patients (all P<0.05). Conclusion:Classification according to PVR was most valuable in predicting all-cause death in PH-LHD patients, while TPG showed moderate predictive ability and DPG had no predictive value.

ObjectiveTo explore the effects of different intensity of wearable lower limb rehabilitation robot-assisted training on walking function, lower limb motor function, balance function and functional independence of stroke patients. MethodsFrom November, 2021 to December, 2022, 60 stroke patients hospitalized in Beijing Bo'ai Hospital were randomly divided into control group (n = 20), observation group 1 (n = 20) and observation group 2 (n = 20). All the groups received routine rehabilitation, while the control group received routine walking training 30 minutes a day, the observation group 1 received wearable lower limb rehabilitation robot-assisted training 30 minutes a day, and the observation group 2 received wearable lower limb rehabilitation robot-assisted training 60 minutes a day, for four weeks. They were assessed with Functional Ambulation Category scale (FAC), Fugl-Meyer Assessment-Lower Extremities (FMA-LE), Berg Balance Scale (BBS) and Rivermead Mobility Index (RMI) before and after treatment. ResultsOne case in the observation group 1 and three cases in the observation group 2 dropped down. The FAC, FMA-LE, BBS and RMI scores improved in all the three groups after treatment (|Z| > 3.448, |t| > 8.102, P < 0.001), and there was no significant difference in all the indexes among the three groups (|H| < 4.643, F = 1.454, P > 0.05); however, the improvement of BBS score was more in the observation group 1 than in the control group (P < 0.05), and the improvement of all the indexes was more in the observation group 2 than in the control group (P < 0.05). ConclusionThe wearable lower limb rehabilitation robot-assisted training may promote the recovery of walking function, lower limb motor function, balance function and functional independence of stroke patients, and high-intensity training seems to be more effective.

Objective:To investigate the effects of breast milk to total milk intake ratio during hospitalization on the duration of antibiotic therapy in preterm infants less than 34 weeks of gestation.Methods:Clinical data of preterm infants ( n=1 792) less than 34 gestational weeks were retrospectively collected in 16 hospitals of Jiangsu Province Neonatal-Perinatal Cooperation Network from January 1, 2019, to December 31, 2021. The days of therapy (DOT) were used to evaluate the duration of antibiotic administration. The median DOT was 15.0 d (7.0-27.0 d). The patients were divided into four groups based on the quartiles of DOT: Q 1 (DOT≤7.0 d), Q 2 (7.0 d27.0 d) groups. According to the breast milk intake ratio (breast milk intake to total milk intake during hospitalization×100%), they were also divided into four groups: very-low-ratio breastfeeding group (breast milk intake ratio≤25%), low-ratio breastfeeding group (25%75%). Univariate analysis ( Chi-square test and Kruskal-Wallis rank-sum test) was used to analyze the factors influencing DOT. Spearman correlation analysis and trend Chi-square test were used to explore the relationship between breast milk intake ratio and DOT. After using multiple imputations to address missing data, two models were constructed after adjusting for different factors, and multinomial logistic regression model was applied to evaluate the effects of the breast milk intake ratio on DOT. Finally, sensitivity analysis was conducted to assess the stability of the models. Results:(1) Of the 1 792 preterm infants, there were 507 (28.3%) in the Q 1 group, 422 (23.5%) in the Q 2 group, 438 (24.4%) in the Q 3 group and 425 (23.7%) in the Q 4 group. (2) The median values of DOT in the very-low-ratio, low-ratio, medium-ratio and high-ratio breastfeeding groups were 20.0 d (11.0-31.0 d), 20.0 d (11.0-32.0 d), 13.0 d (6.0-25.8 d) and 10.0 d (4.0-21.0 d), respectively. Compared with the very-low-ratio and low-ratio breastfeeding groups, the medium-ratio and high-ratio breastfeeding groups had shorter DOT (all P<0.05). (3) After adjusting for factors with P<0.1 (prenatal glucocorticoid exposure, antimicrobial use within 24 h before delivery, gestational age at delivery, birth weight, Apgar score≤7 at 1 min, neonatal respiratory distress syndrome, infectious pneumonia and early-onset neonatal sepsis) between the DOT quartile groups, it showed that medium-ratio and high-ratio breastfeeding were protective factors in contrast to very-low-ratio breastfeeding in the Q 2, Q 3 and Q 4 groups as compared with the Q 1 group [Q 2 group: OR=0.50 (95% CI: 0.30-0.85) and OR=0.36 (95% CI: 0.26-0.51); Q 3 group: OR=0.31 (95% CI: 0.18-0.55) and OR=0.20 (95% CI: 0.14-0.29); Q 4 group: OR=0.22 (95% CI: 0.12-0.42) and OR=0.17 (95% CI: 0.12-0.26)]. Conclusion:Breast milk intake accounting for over 50% of total milk intake has a positive impact on reducing DOT in premature infants requiring antibiotics, which suggests that breastfeeding should be actively encouraged.