1.In Vitro Anti-psoriatic Effect of Kangfuxin Liquid via Inhibiting Cell Proliferation and Migration Ability and Blocking JAK3/STAT3 Signaling Pathway
Shuai LI ; Xuan LIU ; Wenyan TANG ; Zhenqi WU ; Chunhui CHEN ; Dadan QIU ; Yi XU ; Chenggui ZHANG ; Jianquan ZHU ; Jiali ZHU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(10):123-133
ObjectiveThis paper aims to explore the in vitro anti-psoriasis activity and potential mechanism of Kangfuxin liquid (KFX liquid), providing experimental evidence for the anti-psoriasis effect of KFX liquid. MethodsFirstly, the uninduced human immortalized keratinocyte cells (HaCaT cells) were divided into seven groups, namely the control group and KFX liquid groups with different doses (5, 10, 20, 40, 80, 160 g·L-1). After being treated with different concentrations of KFX liquid, the effect of KFX liquid on the normal cell proliferation was detected by using the cell counting kit-8 (CCK-8) method. Secondly, the uninduced HaCaT cells were divided into six groups, namely the control group and recombinant human interleukin-7A (rh-IL-7A) groups with different doses (5, 10, 50, 100, 120 g·L-1). After being treated with different concentrations of recombinant human interleukin-17A (rh IL-17A) liquid, the effect of rh IL-17A on cell proliferation was detected. The optimal induction concentration was screened. Then, normal HaCaT cells were divided into a control group and KFX liquid groups with different doses (5, 10, 20, 40, 80, 160 g·L-1). Except for the control group, the other groups established psoriasis cell models with the optimal induction concentration of rh IL-17A. After being treated with different concentrations of KFX liquid, the effects of KFX liquid on the psoriasis-like HaCaT cell proliferation were investigated. Finally, the uninduced HaCaT cells were divided into six groups, namely the control group, rh IL-17A group, methotrexate (MTX) group, and KFX liquid groups with different doses (20, 40, 80 g·L-1). Except for the control group, the other groups used the optimal induction concentration of rh IL-17A to establish psoriasis cell models. After being treated with different drugs, the cell migration levels were detected through scratch assays, and real-time quantitative polymerase chain reaction (Real-time PCR) was used to detect the relative mRNA expression levels of Ki-67 antigen (Ki67), S100 calcium-binding protein A7 (S100A7), S100 calcium-binding protein A8 (S100A8), and S100 calcium-binding protein A9 (S100A9), thereby comprehensively evaluating the in vitro anti-psoriasis activity of KFX liquid. By detecting the relative mRNA expression levels of interleukin-1β (IL-1β), interleukin-6 (IL-6), and chemokine-20 (CXCL-20) inflammatory-related factors in psoriasis-like HaCaT cells and the protein expression levels of Janus kinase 3 (JAK3), phosphorylated Janus kinase 3 (p-JAK3), signal transducer and activator of transcription 3 (STAT3), and phosphorylated signal transducer and activator of transcription 3 (p-STAT3), the mechanism was explored. ResultsCompared with that of control group, when treated with 80 g·L-1 KFX liquid for 72 h (P<0.05) and at different times with 160 g·L-1 KFX liquid, the HaCaT cell proliferation activity was significantly affected (P<0.01), while the other concentrations of KFX liquid had no significant differences in cell morphology and cell proliferation activity at different times, indicating that the KFX liquid is relatively safe for HaCaT cells and has no obvious toxic side effects. Compared with that of control group, when treated with different concentrations of rh IL-17A for 24 h, the HaCaT cell proliferation activity was significantly enhanced, and the cell activity was the strongest when the concentration was 100 μg·L-1 (P<0.05), with a density close to 100% and intact cell morphology, indicating that 100 μg·L-1 is the optimal concentration for inducing HaCaT cell proliferation. The results of the KFX liquid treatment on rh IL-17A-induced psoriasis-like cells show that the KFX liquid not only effectively inhibits the rh IL-17A-induced psoriasis-like HaCaT cell proliferation activity (P<0.01), but also significantly reduces the migration ability of rh IL-17A-induced psoriasis-like HaCaT cells (P<0.01), and the relative mRNA expression levels of Ki67, S100A7, S100A8, and S100A9 (P<0.01). Moreover, the KFX liquid can significantly reduce the relative mRNA expression levels of IL-1β, IL-6, and CXCL-20 in rh IL-17A-induced psoriasis-like cells (P<0.01), and significantly inhibit the phosphorylation levels of JAK3 and STAT3 proteins (P<0.05, P<0.01). ConclusionThe KFX liquid has no obvious toxicity to uninduced HaCaT cells. It can inhibit rh IL-17A-induced psoriasis-like HaCaT cell proliferation, reduce the cell migration ability, and has good in vitro anti-psoriasis activity. Its action mechanism may be related to downregulating the expression levels of inflammation-related cytokines in the JAK3/STAT3 signaling pathway and inhibiting the phosphorylation levels of JAK3 and STAT3 proteins.
2.In Vitro Anti-psoriatic Effect of Kangfuxin Liquid via Inhibiting Cell Proliferation and Migration Ability and Blocking JAK3/STAT3 Signaling Pathway
Shuai LI ; Xuan LIU ; Wenyan TANG ; Zhenqi WU ; Chunhui CHEN ; Dadan QIU ; Yi XU ; Chenggui ZHANG ; Jianquan ZHU ; Jiali ZHU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(10):123-133
ObjectiveThis paper aims to explore the in vitro anti-psoriasis activity and potential mechanism of Kangfuxin liquid (KFX liquid), providing experimental evidence for the anti-psoriasis effect of KFX liquid. MethodsFirstly, the uninduced human immortalized keratinocyte cells (HaCaT cells) were divided into seven groups, namely the control group and KFX liquid groups with different doses (5, 10, 20, 40, 80, 160 g·L-1). After being treated with different concentrations of KFX liquid, the effect of KFX liquid on the normal cell proliferation was detected by using the cell counting kit-8 (CCK-8) method. Secondly, the uninduced HaCaT cells were divided into six groups, namely the control group and recombinant human interleukin-7A (rh-IL-7A) groups with different doses (5, 10, 50, 100, 120 g·L-1). After being treated with different concentrations of recombinant human interleukin-17A (rh IL-17A) liquid, the effect of rh IL-17A on cell proliferation was detected. The optimal induction concentration was screened. Then, normal HaCaT cells were divided into a control group and KFX liquid groups with different doses (5, 10, 20, 40, 80, 160 g·L-1). Except for the control group, the other groups established psoriasis cell models with the optimal induction concentration of rh IL-17A. After being treated with different concentrations of KFX liquid, the effects of KFX liquid on the psoriasis-like HaCaT cell proliferation were investigated. Finally, the uninduced HaCaT cells were divided into six groups, namely the control group, rh IL-17A group, methotrexate (MTX) group, and KFX liquid groups with different doses (20, 40, 80 g·L-1). Except for the control group, the other groups used the optimal induction concentration of rh IL-17A to establish psoriasis cell models. After being treated with different drugs, the cell migration levels were detected through scratch assays, and real-time quantitative polymerase chain reaction (Real-time PCR) was used to detect the relative mRNA expression levels of Ki-67 antigen (Ki67), S100 calcium-binding protein A7 (S100A7), S100 calcium-binding protein A8 (S100A8), and S100 calcium-binding protein A9 (S100A9), thereby comprehensively evaluating the in vitro anti-psoriasis activity of KFX liquid. By detecting the relative mRNA expression levels of interleukin-1β (IL-1β), interleukin-6 (IL-6), and chemokine-20 (CXCL-20) inflammatory-related factors in psoriasis-like HaCaT cells and the protein expression levels of Janus kinase 3 (JAK3), phosphorylated Janus kinase 3 (p-JAK3), signal transducer and activator of transcription 3 (STAT3), and phosphorylated signal transducer and activator of transcription 3 (p-STAT3), the mechanism was explored. ResultsCompared with that of control group, when treated with 80 g·L-1 KFX liquid for 72 h (P<0.05) and at different times with 160 g·L-1 KFX liquid, the HaCaT cell proliferation activity was significantly affected (P<0.01), while the other concentrations of KFX liquid had no significant differences in cell morphology and cell proliferation activity at different times, indicating that the KFX liquid is relatively safe for HaCaT cells and has no obvious toxic side effects. Compared with that of control group, when treated with different concentrations of rh IL-17A for 24 h, the HaCaT cell proliferation activity was significantly enhanced, and the cell activity was the strongest when the concentration was 100 μg·L-1 (P<0.05), with a density close to 100% and intact cell morphology, indicating that 100 μg·L-1 is the optimal concentration for inducing HaCaT cell proliferation. The results of the KFX liquid treatment on rh IL-17A-induced psoriasis-like cells show that the KFX liquid not only effectively inhibits the rh IL-17A-induced psoriasis-like HaCaT cell proliferation activity (P<0.01), but also significantly reduces the migration ability of rh IL-17A-induced psoriasis-like HaCaT cells (P<0.01), and the relative mRNA expression levels of Ki67, S100A7, S100A8, and S100A9 (P<0.01). Moreover, the KFX liquid can significantly reduce the relative mRNA expression levels of IL-1β, IL-6, and CXCL-20 in rh IL-17A-induced psoriasis-like cells (P<0.01), and significantly inhibit the phosphorylation levels of JAK3 and STAT3 proteins (P<0.05, P<0.01). ConclusionThe KFX liquid has no obvious toxicity to uninduced HaCaT cells. It can inhibit rh IL-17A-induced psoriasis-like HaCaT cell proliferation, reduce the cell migration ability, and has good in vitro anti-psoriasis activity. Its action mechanism may be related to downregulating the expression levels of inflammation-related cytokines in the JAK3/STAT3 signaling pathway and inhibiting the phosphorylation levels of JAK3 and STAT3 proteins.
3.Efficacy and Safety of Automated Insulin Delivery Systems in Patients with Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis
Wenqi FAN ; Chao DENG ; Ruoyao XU ; Zhenqi LIU ; Richard David LESLIE ; Zhiguang ZHOU ; Xia LI
Diabetes & Metabolism Journal 2025;49(2):235-251
Background:
Automated insulin delivery (AID) systems studies are upsurging, half of which were published in the last 5 years. We aimed to evaluate the efficacy and safety of AID systems in patients with type 1 diabetes mellitus (T1DM).
Methods:
We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov until August 31, 2023. Randomized clinical trials that compared AID systems with other insulin-based treatments in patients with T1DM were considered eligible. Studies characteristics and glycemic metrics was extracted by three researchers independently.
Results:
Sixty-five trials (3,623 patients) were included. The percentage of time in range (TIR) was 11.74% (95% confidence interval [CI], 9.37 to 14.12; P<0.001) higher with AID systems compared with control treatments. Patients on AID systems had more pronounced improvement of time below range when diabetes duration was more than 20 years (–1.80% vs. –0.86%, P=0.031) and baseline glycosylated hemoglobin lower than 7.5% (–1.93% vs. –0.87%, P=0.033). Dual-hormone full closed-loop systems revealed a greater improvement in TIR compared with hybrid closed-loop systems (–19.64% vs. –10.87%). Notably, glycemia risk index (GRI) (–3.74; 95% CI, –6.34 to –1.14; P<0.01) was also improved with AID therapy.
Conclusion
AID systems showed significant advantages compared to other insulin-based treatments in improving glucose control represented by TIR and GRI in patients with T1DM, with more favorable effect in euglycemia by dual-hormone full closedloop systems as well as less hypoglycemia for patients who are within target for glycemic control and have longer diabetes duration.
4.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
5.Efficacy and Safety of Automated Insulin Delivery Systems in Patients with Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis
Wenqi FAN ; Chao DENG ; Ruoyao XU ; Zhenqi LIU ; Richard David LESLIE ; Zhiguang ZHOU ; Xia LI
Diabetes & Metabolism Journal 2025;49(2):235-251
Background:
Automated insulin delivery (AID) systems studies are upsurging, half of which were published in the last 5 years. We aimed to evaluate the efficacy and safety of AID systems in patients with type 1 diabetes mellitus (T1DM).
Methods:
We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov until August 31, 2023. Randomized clinical trials that compared AID systems with other insulin-based treatments in patients with T1DM were considered eligible. Studies characteristics and glycemic metrics was extracted by three researchers independently.
Results:
Sixty-five trials (3,623 patients) were included. The percentage of time in range (TIR) was 11.74% (95% confidence interval [CI], 9.37 to 14.12; P<0.001) higher with AID systems compared with control treatments. Patients on AID systems had more pronounced improvement of time below range when diabetes duration was more than 20 years (–1.80% vs. –0.86%, P=0.031) and baseline glycosylated hemoglobin lower than 7.5% (–1.93% vs. –0.87%, P=0.033). Dual-hormone full closed-loop systems revealed a greater improvement in TIR compared with hybrid closed-loop systems (–19.64% vs. –10.87%). Notably, glycemia risk index (GRI) (–3.74; 95% CI, –6.34 to –1.14; P<0.01) was also improved with AID therapy.
Conclusion
AID systems showed significant advantages compared to other insulin-based treatments in improving glucose control represented by TIR and GRI in patients with T1DM, with more favorable effect in euglycemia by dual-hormone full closedloop systems as well as less hypoglycemia for patients who are within target for glycemic control and have longer diabetes duration.
6.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
7.Efficacy and Safety of Automated Insulin Delivery Systems in Patients with Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis
Wenqi FAN ; Chao DENG ; Ruoyao XU ; Zhenqi LIU ; Richard David LESLIE ; Zhiguang ZHOU ; Xia LI
Diabetes & Metabolism Journal 2025;49(2):235-251
Background:
Automated insulin delivery (AID) systems studies are upsurging, half of which were published in the last 5 years. We aimed to evaluate the efficacy and safety of AID systems in patients with type 1 diabetes mellitus (T1DM).
Methods:
We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov until August 31, 2023. Randomized clinical trials that compared AID systems with other insulin-based treatments in patients with T1DM were considered eligible. Studies characteristics and glycemic metrics was extracted by three researchers independently.
Results:
Sixty-five trials (3,623 patients) were included. The percentage of time in range (TIR) was 11.74% (95% confidence interval [CI], 9.37 to 14.12; P<0.001) higher with AID systems compared with control treatments. Patients on AID systems had more pronounced improvement of time below range when diabetes duration was more than 20 years (–1.80% vs. –0.86%, P=0.031) and baseline glycosylated hemoglobin lower than 7.5% (–1.93% vs. –0.87%, P=0.033). Dual-hormone full closed-loop systems revealed a greater improvement in TIR compared with hybrid closed-loop systems (–19.64% vs. –10.87%). Notably, glycemia risk index (GRI) (–3.74; 95% CI, –6.34 to –1.14; P<0.01) was also improved with AID therapy.
Conclusion
AID systems showed significant advantages compared to other insulin-based treatments in improving glucose control represented by TIR and GRI in patients with T1DM, with more favorable effect in euglycemia by dual-hormone full closedloop systems as well as less hypoglycemia for patients who are within target for glycemic control and have longer diabetes duration.
8.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
9.Efficacy and Safety of Automated Insulin Delivery Systems in Patients with Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis
Wenqi FAN ; Chao DENG ; Ruoyao XU ; Zhenqi LIU ; Richard David LESLIE ; Zhiguang ZHOU ; Xia LI
Diabetes & Metabolism Journal 2025;49(2):235-251
Background:
Automated insulin delivery (AID) systems studies are upsurging, half of which were published in the last 5 years. We aimed to evaluate the efficacy and safety of AID systems in patients with type 1 diabetes mellitus (T1DM).
Methods:
We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov until August 31, 2023. Randomized clinical trials that compared AID systems with other insulin-based treatments in patients with T1DM were considered eligible. Studies characteristics and glycemic metrics was extracted by three researchers independently.
Results:
Sixty-five trials (3,623 patients) were included. The percentage of time in range (TIR) was 11.74% (95% confidence interval [CI], 9.37 to 14.12; P<0.001) higher with AID systems compared with control treatments. Patients on AID systems had more pronounced improvement of time below range when diabetes duration was more than 20 years (–1.80% vs. –0.86%, P=0.031) and baseline glycosylated hemoglobin lower than 7.5% (–1.93% vs. –0.87%, P=0.033). Dual-hormone full closed-loop systems revealed a greater improvement in TIR compared with hybrid closed-loop systems (–19.64% vs. –10.87%). Notably, glycemia risk index (GRI) (–3.74; 95% CI, –6.34 to –1.14; P<0.01) was also improved with AID therapy.
Conclusion
AID systems showed significant advantages compared to other insulin-based treatments in improving glucose control represented by TIR and GRI in patients with T1DM, with more favorable effect in euglycemia by dual-hormone full closedloop systems as well as less hypoglycemia for patients who are within target for glycemic control and have longer diabetes duration.
10.Analysis of effectiveness of Holosight robot navigation-assisted percutaneous cannulated screw fixation in treatment of femoral neck fractures.
Weizhen XU ; Zhenqi DING ; Hui LIU ; Jinhui ZHANG ; Yuanfei XIONG ; Jin WU
Chinese Journal of Reparative and Reconstructive Surgery 2025;39(6):673-679
OBJECTIVE:
To investigate the effectiveness of Holosight robotic navigation-assisted percutaneous cannulated screw fixation for femoral neck fractures.
METHODS:
A retrospective analysis was conducted on 65 patients with femoral neck fractures treated with cannulated screw fixation between January 2022 and February 2024. Among them, 31 patients underwent robotic navigation-assisted screw placement (navigation group), while 34 underwent conventional freehand percutaneous screw fixation (freehand group). Baseline characteristics, including age, gender, fracture side, injury mechanism, Garden classification, Pauwels classification, and time from injury to operation, showed no significant differences between the two groups ( P>0.05). The operation time, intraoperative blood loss, fluoroscopy frequency, fracture healing time, and complications were recorded and compared, and hip function was evaluated by Harris score at last follow-up. Postoperative anteroposterior and lateral hip X-ray films were taken to assess screw distribution accuracy, including deviation from the femoral neck axis, inter-screw parallelism, and distance from screws to the femoral neck cortex.
RESULTS:
No significant difference was observed in operation time between the two groups ( P>0.05). However, the navigation group demonstrated superior outcomes in intraoperative blood loss, fluoroscopy frequency, deviation from the femoral neck axis, inter-screw parallelism, and distance from screws to the femoral neck cortex ( P<0.05). No incision infections or deep vein thrombosis occurred. All patients were followed up 12-18 months (mean, 16 months). In the freehand group, 1 case suffered from cannulated screw dislodgement and nonunion secondary to osteonecrosis of femoral head at 1 year after operation, 1 case suffered from screw penetration secondary to osteonecrosis of femoral head at 5 months after operation; and 1 case suffered from nonunion secondary to osteonecrosis of femoral head at 6 months after operation in the navigation group. All the 3 patients underwent internal fixators removal and total hip arthroplasty. There was no significant difference in the incidence of complications between the two groups ( P>0.05). The fracture healing time and hip Harris score at last follow-up in the navigation group were significantly better than those in the freehand group ( P<0.05).
CONCLUSION
Compared to freehand percutaneous screw fixation, Holosight robotic navigation-assisted cannulated screw fixation for femoral neck fractures achieves higher precision, reduced intraoperative radiation exposure, smaller incisions, and superior postoperative hip function recovery.
Humans
;
Femoral Neck Fractures/diagnostic imaging*
;
Bone Screws
;
Fracture Fixation, Internal/instrumentation*
;
Male
;
Female
;
Retrospective Studies
;
Robotic Surgical Procedures/methods*
;
Middle Aged
;
Aged
;
Adult
;
Treatment Outcome
;
Operative Time
;
Fracture Healing
;
Surgery, Computer-Assisted/methods*
;
Fluoroscopy

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