BACKGROUND:Periprosthetic joint infection is the most common cause of early failure after total knee replacement.The current methods of preventing periprosthetic joint infection by improving the surface of the prosthesis have limitations to varying degrees.OBJECTIVE:To construct a coating material that can stably improve the surface of the implant,prevent the initial floating bacterial infection of periprosthetic infection,and regulate the bone transfer function around the implant.METHODS:(1)Material preparation:YGF polypeptide(which promotes bone formation),LL-37 polypeptide(with antibacterial properties)and YGF+LL-37 composite peptide were prepared by Fmoc solid phase peptide synthesis technology.The titanium-based materials were immersed in the three polypeptide solutions for 2 hours to obtain YGF coating,LL-37 coating and composite peptide coating coated titanium sheets.(2)In vitro experiment:Uncoated titanium sheets and coated titanium sheets were co-cultured with Escherichia coli(or Staphylococcus aureus)and the colonies were counted by plate method.MC3T3 cells were inoculated on the surface of uncoated titanium sheet and coated titanium sheet,respectively.Alizarin red staining was used to observe the calcium salt deposition on the surface of the material.Western blot assay was used to detect the protein expression of RUNX2,osteocalcin,osteopontin,and bone morphogenetic protein 2.(3)Animal experiment:24 SD rats were randomly divided into three groups:the blank group(n=8)was implanted with uncoated titanium nails in the femoral medullary canal;the control group(n=8)was implanted with uncoated titanium nails in the femoral medullary canal+intra-articular injection of Staphylococcus aureus suspension;the experimental group(n=8)was implanted with composite peptide coated titanium nails in the femoral medullary canal+intra-articular injection of Staphylococcus aureus suspension.After 5 weeks of implantation,micro-CT examination,hematoxylin-eosin staining and immunohistochemical staining of femur specimens were performed.RESULTS AND CONCLUSION:(1)In vitro experiment:Compared with uncoated titanium sheet and YGF coated titanium sheet,LL-37 coated and composite peptide coated titanium sheet could significantly inhibit the growth and reproduction of Escherichia coli and Staphylococcus aureus.Compared with uncoated titanium sheets and LL-37-coated titanium sheets,YGF-coated and composite peptide-coated titanium sheets could promote calcium salt deposition in osteoblasts and increase the protein expression of RUNX2,osteocalcin,osteopontin and bone morphogenetic protein 2.(2)Animal experiment:Micro-CT test showed that the control group had less bone mass than the blank group and the experimental group.Hematoxylin-eosin staining showed that there was a large amount of fibrous tissue around the nail channel in the control group,only a small amount of tissue fibrosis around the nail channel in the blank group,and only a small amount of tissue fibrosis around the nail channel in the experimental group.Immunohistochemical staining showed that the protein expression of interleukin 1β and tumor necrosis factor α in the control group was higher than that in the blank group and the experimental group,and the expression of osteocalcin,RUNX2 and osteopontin in the experimental group was higher than that in the blank group and the control group.(3)The results show that the titanium-based material coated with YGF+LL-37 composite peptide coating has good antibacterial ability and can promote bone transfer around the implant.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

BACKGROUND:Periprosthetic joint infection is the most common cause of early failure after total knee replacement.The current methods of preventing periprosthetic joint infection by improving the surface of the prosthesis have limitations to varying degrees.OBJECTIVE:To construct a coating material that can stably improve the surface of the implant,prevent the initial floating bacterial infection of periprosthetic infection,and regulate the bone transfer function around the implant.METHODS:(1)Material preparation:YGF polypeptide(which promotes bone formation),LL-37 polypeptide(with antibacterial properties)and YGF+LL-37 composite peptide were prepared by Fmoc solid phase peptide synthesis technology.The titanium-based materials were immersed in the three polypeptide solutions for 2 hours to obtain YGF coating,LL-37 coating and composite peptide coating coated titanium sheets.(2)In vitro experiment:Uncoated titanium sheets and coated titanium sheets were co-cultured with Escherichia coli(or Staphylococcus aureus)and the colonies were counted by plate method.MC3T3 cells were inoculated on the surface of uncoated titanium sheet and coated titanium sheet,respectively.Alizarin red staining was used to observe the calcium salt deposition on the surface of the material.Western blot assay was used to detect the protein expression of RUNX2,osteocalcin,osteopontin,and bone morphogenetic protein 2.(3)Animal experiment:24 SD rats were randomly divided into three groups:the blank group(n=8)was implanted with uncoated titanium nails in the femoral medullary canal;the control group(n=8)was implanted with uncoated titanium nails in the femoral medullary canal+intra-articular injection of Staphylococcus aureus suspension;the experimental group(n=8)was implanted with composite peptide coated titanium nails in the femoral medullary canal+intra-articular injection of Staphylococcus aureus suspension.After 5 weeks of implantation,micro-CT examination,hematoxylin-eosin staining and immunohistochemical staining of femur specimens were performed.RESULTS AND CONCLUSION:(1)In vitro experiment:Compared with uncoated titanium sheet and YGF coated titanium sheet,LL-37 coated and composite peptide coated titanium sheet could significantly inhibit the growth and reproduction of Escherichia coli and Staphylococcus aureus.Compared with uncoated titanium sheets and LL-37-coated titanium sheets,YGF-coated and composite peptide-coated titanium sheets could promote calcium salt deposition in osteoblasts and increase the protein expression of RUNX2,osteocalcin,osteopontin and bone morphogenetic protein 2.(2)Animal experiment:Micro-CT test showed that the control group had less bone mass than the blank group and the experimental group.Hematoxylin-eosin staining showed that there was a large amount of fibrous tissue around the nail channel in the control group,only a small amount of tissue fibrosis around the nail channel in the blank group,and only a small amount of tissue fibrosis around the nail channel in the experimental group.Immunohistochemical staining showed that the protein expression of interleukin 1β and tumor necrosis factor α in the control group was higher than that in the blank group and the experimental group,and the expression of osteocalcin,RUNX2 and osteopontin in the experimental group was higher than that in the blank group and the control group.(3)The results show that the titanium-based material coated with YGF+LL-37 composite peptide coating has good antibacterial ability and can promote bone transfer around the implant.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

ObjectiveTo explore the potential mechanism of Weicanqing Formula （微残清方， WF） combined with chemotherapy in treating acute myeloid leukemia （AML） based on malic enzyme 2 （ME2）-mediated bone marrow immune-metabolic homeostasis and . MethodsSixty-five male C57BL/6N mice were randomly divided into control group， model group， WF group， chemotherapy group， and the combination group （WF plus chemotherapy）， with 13 mice per group. Except for the control group， mice were injected with C1498 cells （appro-ximately 1×10⁶ cells per mouse） via the tail vein on day 1 to establish an AML model. Starting from day 8， mice in the chemotherapy group and the combination group were administered with cytarabine at 30 mg/（kg·d） via subcutaneous injection， once daily for 3 consecutive days； WF group and the combination group received WF at 7.54 g/（kg·d） by gavage， once daily for 21 consecutive days. On days 1， 7， 14， 21 and 28， hemoglobin （Hb） and white blood cell （WBC） levels were determined in each group. On day 28， Giemsa staining was used to observe morphological changes in bone marrow cells. Flow cytometry was employed to detect the expression levels of bone marrow T lympthocyte subsets， including CD8⁺， CD4⁺， and regulatory T lymphocytes （Treg）. The contents of glutamine （Gln）， nicotinamide adenine dinucleotide phosphate （NADP⁺）， and reduced nicotinamide adenine dinucleotide phosphate （NADPH） in bone marrow were determined using visible spectrophotometry. Adenosine triphosphate （ATP） concentration in bone marrow was measured by chemiluminescence assay. The mRNA expression of malic enzyme 2 （ME2） in bone marrow was detected by RT-qPCR， and the protein expression level of ME2 was determined by Western blotting. ResultsCompared to the control group， the model group showed decreased Hb levels on day 14， 21， and 28， and increased WBC levels on day 7， 14， 21， and 28 （P＜0.05）. On day 28， bone marrow CD8⁺ and CD8⁺/CD4⁺ levels decreased， while Treg cells， ATP， Gln， NADP⁺， NADPH， ME2 mRNA， and their corresponding protein levels increased （P＜0.05）. Compared to the model group， the chemotherapy group and the combination group both exhibited reduced Hb level on day 14， 21 and 28， as well as the increased WBC level； the combination group showed increased CD8⁺ level， decreased Treg， ATP， Gln， and NADPH content， as well as reduced ME2 mRNA expression and protein levels （P＜0.05）. Compared to the chemotherapy group， the combination group showed significantly increased Hb level on days 21 and 28， and increased WBC level on day 28 （P＜0.05）. Bone marrow smear pathology revealed that， in the model group， myeloid blast cells exhibited cytoplasmic vacuoles indicative of abnormal metabolic activity. In contrast， both the chemotherapy group and the combination group showed large numbers of metamyelocytes and band neutrophils， with only a few immature granulocytic blast cells observed. ConclusionWF may improve the prognosis of AML when used as an adjunct to chemotherapy by modulating ME2 expression， inhibiting metabolic energy competition within the bone marrow microenvironment， and reshaping the distribution of T lymphocyte subsets in the bone marrow.

Objective To explore the characteristics of fluid flow within loaded osteons under different boundary conditions.Methods The COMSOL Multiphysics software was used to establish a three-dimensional(3D)finite element model of osteons with different boundary conditions,and the variation rules of pore pressure and flow velocity of osteons under different inner wall pulsating blood pressures and outer wall elastic constraint conditions were analyzed.Results As the pulsatile blood pressure inside the osteon increased from 0 mmHg(1 mmHg=0.133 kPa)to 300 mmHg,the peak pore pressure within the osteon correspondingly increased from 26 kPa to 68 kPa.As the elastic constraint on the outer wall of osteons changed from being completely elastic to completely constrained,the peak pore pressure within osteons increased from 15 kPa to 26 kPa,and the peak flow velocity increased from 0.04 um/s to 0.07 um/s.Conclusions This study reveals the influence laws of changes in boundary conditions such as the pulsatile blood pressure on the inner wall and the elastic constraint on the outer wall of osteons on fluid flow characteristics within loaded osteons.These findings are conducive to a deeper understanding of the mechanical response mechanisms of bone tissues in both physiological and pathological states,and provide an important theoretical basrs for further researches on bone mechanotransduction.

Objective To explore the characteristics of fluid flow within loaded osteons under different boundary conditions.Methods The COMSOL Multiphysics software was used to establish a three-dimensional(3D)finite element model of osteons with different boundary conditions,and the variation rules of pore pressure and flow velocity of osteons under different inner wall pulsating blood pressures and outer wall elastic constraint conditions were analyzed.Results As the pulsatile blood pressure inside the osteon increased from 0 mmHg(1 mmHg=0.133 kPa)to 300 mmHg,the peak pore pressure within the osteon correspondingly increased from 26 kPa to 68 kPa.As the elastic constraint on the outer wall of osteons changed from being completely elastic to completely constrained,the peak pore pressure within osteons increased from 15 kPa to 26 kPa,and the peak flow velocity increased from 0.04 um/s to 0.07 um/s.Conclusions This study reveals the influence laws of changes in boundary conditions such as the pulsatile blood pressure on the inner wall and the elastic constraint on the outer wall of osteons on fluid flow characteristics within loaded osteons.These findings are conducive to a deeper understanding of the mechanical response mechanisms of bone tissues in both physiological and pathological states,and provide an important theoretical basrs for further researches on bone mechanotransduction.

Objective:To evaluate the efficacy and safety of fecal microbiota transplantation (FMT) for treating functional constipation, analyze the incidence of, and factors that influence, adverse events, and provide scientific evidence for optimizing FMT treatment.Methods:This retrospective, multicenter, single-arm, pre–post real-world study included 1529 patients with functional constipation from four clinical centers. Eligibility criteria comprised meeting the diagnostic criteria for functional constipation, having undergone at least one FMT treatment, complete pre- and post-treatment data available, and age ≥18 years. Patients who had received other interventions affecting gut function within 1 month before treatment and those with severe organic diseases or immune deficiencies were excluded. Applying the above criteria yielded 1529 eligible patients with functional constipation from four medical centers (1405 from the Shanghai Tenth People's Hospital Affiliated to Tongji University, 20 from the Central Hospital of Wuhan, 67 from the Shanxi Bethune Hospital and 37 from the Longgang District People's Hospital of Shenzhen). The study cohort comprised 746 male (48.8%) and 783 female patients (51.2%) of mean age (51.4 ± 17.4) years, mean body mass index (26.4 ± 4.9) kg/m2, and mean duration of disease (15.0 ± 8.3) years. The primary outcomes were the incidence, types, and severity of adverse reactions during treatment, and their impact on patients' quality of life. Secondary outcomes included: (1) the efficacy of FMT in treating constipation. This was assessed based on changes in Patient Assessment of Constipation Symptoms (PAC-SYM) scores, where higher score indicates worse symptom. (2) Subjective satisfaction, evaluated through questionnaires or rating scales, reflecting patients' acceptance of and satisfaction with the treatment, with scores ranging from 1 to 5, where higher scores indicated greater satisfaction. Paired t-tests and Wilcoxon signed-rank tests were used to evaluate changes in symptom scores and biochemical indicators before and after treatment. Logistic regression was performed to analyze factors influencing adverse events, and subgroup analyses to explored differences in efficacy between patient groups.Results:In this cohort of 1529 patients with functional constipation, adverse reactions were primarily mild to moderate (1048/1529,68.5%). They comprised fever in 54 patients (3.5%), dizziness or fatigue in 218 (14.3%), throat discomfort in 806 (52.7%), nausea and vomiting in 166 (10.9%), and abdominal distension or pain in 415 (27.1%). According to multivariate logistic regression analysis, PAC-SYM scores were associated with the rate of adverse reactions, higher scores indicating a lower risk (OR = 0.958, 95% CI: 0.923–0.993, P=0.021). Among the 1529 patients, 274 (17.9%) underwent two or more treatment courses. After one treatment course, the patients' PAC-SYM scores decreased from (37.7 ± 3.2) pre-treatment to (23.7 ± 8.6) (mean difference 14.0 ± 9.1). PAC-SYM scores decreased by (20.7 ± 7.7) after two courses of FMT, and by (19.4 ± 6.3) after three courses. After treatment, 50.7%(775/1529) of patients reported satisfaction scores of ≥4. Adverse reactions impacted satisfaction; specifically, dizziness/fatigue, throat discomfort, and abdominal distension/pain were significantly associated with satisfaction (all P < 0.05). Conclusions:FMT achieved good relief of symptoms of functional constipation and multiple treatment courses have a cumulative effect. Adverse reactions, mainly dizziness/fatigue, throat discomfort, and abdominal distension/pain, had significant negative impacts on patient satisfaction.

Objective:To evaluate the efficacy and safety of fecal microbiota transplantation (FMT) for treating functional constipation, analyze the incidence of, and factors that influence, adverse events, and provide scientific evidence for optimizing FMT treatment.Methods:This retrospective, multicenter, single-arm, pre–post real-world study included 1529 patients with functional constipation from four clinical centers. Eligibility criteria comprised meeting the diagnostic criteria for functional constipation, having undergone at least one FMT treatment, complete pre- and post-treatment data available, and age ≥18 years. Patients who had received other interventions affecting gut function within 1 month before treatment and those with severe organic diseases or immune deficiencies were excluded. Applying the above criteria yielded 1529 eligible patients with functional constipation from four medical centers (1405 from the Shanghai Tenth People's Hospital Affiliated to Tongji University, 20 from the Central Hospital of Wuhan, 67 from the Shanxi Bethune Hospital and 37 from the Longgang District People's Hospital of Shenzhen). The study cohort comprised 746 male (48.8%) and 783 female patients (51.2%) of mean age (51.4 ± 17.4) years, mean body mass index (26.4 ± 4.9) kg/m2, and mean duration of disease (15.0 ± 8.3) years. The primary outcomes were the incidence, types, and severity of adverse reactions during treatment, and their impact on patients' quality of life. Secondary outcomes included: (1) the efficacy of FMT in treating constipation. This was assessed based on changes in Patient Assessment of Constipation Symptoms (PAC-SYM) scores, where higher score indicates worse symptom. (2) Subjective satisfaction, evaluated through questionnaires or rating scales, reflecting patients' acceptance of and satisfaction with the treatment, with scores ranging from 1 to 5, where higher scores indicated greater satisfaction. Paired t-tests and Wilcoxon signed-rank tests were used to evaluate changes in symptom scores and biochemical indicators before and after treatment. Logistic regression was performed to analyze factors influencing adverse events, and subgroup analyses to explored differences in efficacy between patient groups.Results:In this cohort of 1529 patients with functional constipation, adverse reactions were primarily mild to moderate (1048/1529,68.5%). They comprised fever in 54 patients (3.5%), dizziness or fatigue in 218 (14.3%), throat discomfort in 806 (52.7%), nausea and vomiting in 166 (10.9%), and abdominal distension or pain in 415 (27.1%). According to multivariate logistic regression analysis, PAC-SYM scores were associated with the rate of adverse reactions, higher scores indicating a lower risk (OR = 0.958, 95% CI: 0.923–0.993, P=0.021). Among the 1529 patients, 274 (17.9%) underwent two or more treatment courses. After one treatment course, the patients' PAC-SYM scores decreased from (37.7 ± 3.2) pre-treatment to (23.7 ± 8.6) (mean difference 14.0 ± 9.1). PAC-SYM scores decreased by (20.7 ± 7.7) after two courses of FMT, and by (19.4 ± 6.3) after three courses. After treatment, 50.7%(775/1529) of patients reported satisfaction scores of ≥4. Adverse reactions impacted satisfaction; specifically, dizziness/fatigue, throat discomfort, and abdominal distension/pain were significantly associated with satisfaction (all P < 0.05). Conclusions:FMT achieved good relief of symptoms of functional constipation and multiple treatment courses have a cumulative effect. Adverse reactions, mainly dizziness/fatigue, throat discomfort, and abdominal distension/pain, had significant negative impacts on patient satisfaction.

OBJECTIVE: To investigate the analgesic effect of locally injecting a "cocktail" analgesia containing a high-dose compound betamethasone during revision hip arthroplasty, and also to study the usage of opioid drugs. METHODS: A retrospective analysis was conducted on the clinical data of 180 patients who underwent revision hip arthroplasty due to aseptic loosening of the hip prosthesis between January 2015 and December 2021. Among them, 95 patients received intraoperative injection of "cocktail" analgesia containing high-dose compound betamethasone (group A), and 85 patients received intraoperative injection of traditional "cocktail" analgesia (group B). There was no significant difference in baseline data such as gender, age, body mass index, presence or absence of diabetes mellitus between the two groups ( P>0.05). The hospital stay, use of opioid drugs within 72 hours, and the incidence of adverse reactions within 72 hours after operation [including nausea and vomiting, insomnia, deep venous thrombosis (DVT), infection, etc.] were recorded and compared between the two groups. The pain relief of patients was evaluated using the static and dynamic visual analogue scale (VAS) scores at 12, 24, 48, and 72 hours after operation. The incidence of complications (including prosthesis re-loosening, hip joint dislocation, hip joint stiffness, limping, chronic pain, etc.) at 2 years after operation was recorded, and the Harris Hip Score (HHS) was used to evaluate the function at 2 years after operation. RESULTS: In group A, the utilization rate of opioid drugs within 72 hours after operation was significantly lower than that in group B ( P<0.05). However, there was no significant difference between the two groups in terms of hospital stay, as well as the incidence of adverse reactions such as nausea and vomiting, insomnia, DVT, and infection within 72 hours after operation ( P>0.05). The VAS scores of both groups decreased with time, and the differences between different time points were significant ( P<0.05). The static and dynamic VAS scores of group A were significantly lower than those of group B at 12, 24, and 48 hours after operation ( P<0.05), but there was no significant difference in static and dynamic VAS scores between the two groups at 72 hours after operation ( P>0.05). All patients in both groups were followed up 2-8 years, with an average of 5.73 years. At 2 years after operation, no significant difference was found between the two groups in the incidence of complications and HHS score ( P>0.05). CONCLUSION "Cocktail" analgesia containing a high-dose compound betamethasone for early analgesia after revision hip arthroplasty can effectively reduce postoperative pain and the use of opioid drugs, but will not increase the incidence of infection and DVT after operation.
Humans ; Arthroplasty, Replacement, Hip/adverse effects* ; Betamethasone/therapeutic use* ; Retrospective Studies ; Male ; Female ; Analgesics, Opioid/administration & dosage* ; Pain, Postoperative/prevention & control* ; Middle Aged ; Reoperation ; Aged ; Analgesia/methods* ; Adult ; Pain Measurement ; Pain Management/methods* ; Prosthesis Failure ; Hip Prosthesis