Objective:To explore the effect of the combination of robot-assisted total knee arthroplasty and pressure sensor on early postoperative outcomes.Methods:Twenty patients who underwent YUANHUA robot-assisted TKA between September 2024 and December 2024 were prospectively enrolled. After randomization and exclusion of one patient lost to follow-up, 10 patients were included in the pressure-sensor group and 10 in the control (no-pressure) group. In the pressure-sensor group, surgeons used a pressure sensor to assist in soft tissue balancing after osteotomy, whereas in the control group, balancing was performed empirically. In both groups, medial and lateral compartment pressures of the knee at 10°, 45°, 90°, and 120° of flexion were recorded using a pressure sensor prior to component implantation. Clinical outcomes were evaluated preoperatively and at 1 day, 3 days, 1 week, 2 weeks, 6 weeks, and 3 months postoperatively using the visual analog scale (VAS), Knee Society Score (KSS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and Forgotten Joint Score (FJS).Results:All 20 procedures were completed successfully, and patients were followed for at least 3 months. At 10° of knee flexion, the difference between medial and lateral compartment pressures was significantly smaller in the pressure-sensor group (0.99±59.44 N) than in the control group (97.18±84.34 N; t=-2.948, P=0.009). At 45° of flexion, the corresponding differences were -12.99±36.20 N and 51.48±76.40 N, respectively ( t=-2.411, P=0.032). No significant differences in VAS, KSS, or WOMAC scores were observed between groups preoperatively ( P>0.05). At 3 months postoperatively, the KSS was significantly higher in the pressure-sensor group (174.40±16.39) compared with the control group (138.50±38.35, t=2.722, P=0.014). The WOMAC and VAS scores were significantly lower in the pressure-sensor group (12.70±11.00 and 1.20±0.92, respectively) than in the control group (27.30±18.54 and 2.70±2.00; t=-2.142, P=0.046; t=-2.153, P=0.045). At 2 weeks and 3 months postoperatively, the FJS scores in the pressure-sensor group [70.00±26.06 and 88.07(83.52, 95.83)] were significantly higher than those in the control group [37.92±32.42 and 50.00(32.50, 67.75); t=2.439, P=0.025; Z=-2.466, P=0.014]. Conclusion:The combination of precise osteotomy using robot-assisted TKA and soft tissue balancing guided by a pressure sensor provided more accurate medial-lateral compartment balance and significantly enhanced early postoperative clinical outcomes.

Objective:To explore the effect of the combination of robot-assisted total knee arthroplasty and pressure sensor on early postoperative outcomes.Methods:Twenty patients who underwent YUANHUA robot-assisted TKA between September 2024 and December 2024 were prospectively enrolled. After randomization and exclusion of one patient lost to follow-up, 10 patients were included in the pressure-sensor group and 10 in the control (no-pressure) group. In the pressure-sensor group, surgeons used a pressure sensor to assist in soft tissue balancing after osteotomy, whereas in the control group, balancing was performed empirically. In both groups, medial and lateral compartment pressures of the knee at 10°, 45°, 90°, and 120° of flexion were recorded using a pressure sensor prior to component implantation. Clinical outcomes were evaluated preoperatively and at 1 day, 3 days, 1 week, 2 weeks, 6 weeks, and 3 months postoperatively using the visual analog scale (VAS), Knee Society Score (KSS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and Forgotten Joint Score (FJS).Results:All 20 procedures were completed successfully, and patients were followed for at least 3 months. At 10° of knee flexion, the difference between medial and lateral compartment pressures was significantly smaller in the pressure-sensor group (0.99±59.44 N) than in the control group (97.18±84.34 N; t=-2.948, P=0.009). At 45° of flexion, the corresponding differences were -12.99±36.20 N and 51.48±76.40 N, respectively ( t=-2.411, P=0.032). No significant differences in VAS, KSS, or WOMAC scores were observed between groups preoperatively ( P>0.05). At 3 months postoperatively, the KSS was significantly higher in the pressure-sensor group (174.40±16.39) compared with the control group (138.50±38.35, t=2.722, P=0.014). The WOMAC and VAS scores were significantly lower in the pressure-sensor group (12.70±11.00 and 1.20±0.92, respectively) than in the control group (27.30±18.54 and 2.70±2.00; t=-2.142, P=0.046; t=-2.153, P=0.045). At 2 weeks and 3 months postoperatively, the FJS scores in the pressure-sensor group [70.00±26.06 and 88.07(83.52, 95.83)] were significantly higher than those in the control group [37.92±32.42 and 50.00(32.50, 67.75); t=2.439, P=0.025; Z=-2.466, P=0.014]. Conclusion:The combination of precise osteotomy using robot-assisted TKA and soft tissue balancing guided by a pressure sensor provided more accurate medial-lateral compartment balance and significantly enhanced early postoperative clinical outcomes.

Objective To analyze the clinical infection distribution and drug resistance status of 442 strains of Escherichia coli to provide the basise for the treatment of Escherichia coli infection and the control of nosocomial infection.Methods The clinically submitted various kinds of specimens during 2013 were performed the bacterial culture and identification.The susceptibility of Escherichia coli to commonly used bacterial drugs were detected by adopting the MIC method.The data were analyzed by WHO-NET V5.5 and SPSS V13.0 softwares.Results 442 strains of Escherichia coli were isolated from the middle urine and secretion. The detection rate of ESBLs-producing Escherichia coli was 61.3%.442 strains of Escherichia coli had the high resistance to peni-cillins,cephalosporins and fluoroquinolones,better sensitivity toβ-lactam/β-lactamase inhibitor compounds and highest sensitivity to carbapenems.ESBLs-producing Escherichia coli had the higher resistance to commonly used antibacterial drugs than non-ESBLs-producing Escherichia coli .Conclusion The drug resistance of Escherichia coli is severe.ESBLs-producing Escherichia coli are u-sually resistant to many different types of antimicrobial drugs.Carbapenems are the first choice to treatment of severe infections of Escherichia coli .