| BackgroundWith the popularization and promotion of total knee arthroplasty(TKA)in clinic,it is by far the most effective treatment for patients with end-stage knee osteoarthritis(KOA).However,complications caused by surgery-related or other factors have also increased,resulting in an increase in the rate of unplanned readmission within 30 days after discharge in recent years.Unplanned readmission not only affects the physical and mental health and economic level of inpatients,but also increases the shortage of hospitalization costs and social medical resources,and is also one of the international monitoring indicators of hospital medical quality.At present,there is no consensus on the influencing factors of unplanned readmission within 30 days after discharge of patients with total knee arthroplasty,so the factors affecting unplanned readmission are still controversial in academic circles.ObjectiveA retrospective study was conducted to explore and screen the risk factors of unplanned readmission within 30 days after discharge from patients with knee osteoarthritis,and to build a clinical prediction model.By providing clinicians with a more reliable risk prediction model of unplanned readmission,in order to provide a reference basis for dealing with the risk factors of readmission in time.MethodsThe patients who underwent total knee arthroplasty for knee osteoarthritis in our hospital from January 2020 to April 2022 were collected according to whether they were re-admitted within 30 days after discharge.47 patients with unplanned total knee arthroplasty within 30 days after discharge were collected,and 872 patients without unplanned readmission within 30 days after discharge were selected as the control group.The follow-up period was up to August 2022.The baseline data of body mass index(BMI),sex,age composition,nationality,type of payment,education level,history of basic diseases and bad habits of smoking and alcohol were statistically analyzed and compared between the two groups.According to the preoperative condition of the patients,the data of American Association of Anesthesiologists(ASA)grade,Charlson complication index(ACCI)after age correction,preoperative laboratory indexes(hemoglobin,white blood cell,C-reactive protein,albumin,D-dimer),anesthetic method,operation time,intraoperative blood loss and blood transfusion were collected according to the patient’s intraoperative condition.According to the postoperative condition of the patients,the data of discharge,laboratory indexes(hemoglobin,white blood cells,C-reactive protein,albumin,D-dimer)and hospital stay on the first day after operation were collected.All the relevant factors that may cause unplanned readmission within 30 days after discharge were analyzed by univariate data analysis,and the statistically significant factors were included in multiple unconditional logistic linear regression analysis to screen out the risk factors affecting unplanned readmission.Finally,R software was used to incorporate the above risk factors and build a clinical prediction model to evaluate and predict the risk probability of unplanned readmission within 30 days after discharge.ResultsIn this study,it was found that the causes of unplanned readmission included 28 cases of poor incision healing,7 cases of periprosthetic infection,5 cases of joint stiffness,3 cases of surgical incision infection,3 cases of postoperative periprosthetic pain and 1 case of atrial fibrillation.Univariate data analysis showed that there was no significant difference between the two groups in terms of nationality,basic disease history,bad habit of smoking and alcohol,blood transfusion and laboratory indexes(hemoglobin,white blood cell,C-reactive protein,albumin,D-dimer)before and after operation(P>0.05).Univariate analysis showed that there were significant differences between the two groups in terms of BMI,age composition,sex,education level,type of payment,length of stay,ASA grade,ACCI,mode of anesthesia,operation time,intraoperative blood loss and discharge location.The above univariate analysis showed that the variables with statistical significance were included in multiple unconditional logistic linear regression analysis.The results showed that age,BMI,education level,payment type,ACCI,operation time,intraoperative blood loss and discharge location were significantly correlated with unplanned readmission within 30 days after discharge.The difference was statistically significant.According to the non-conditional logistic linear regression analysis,the risk factors with statistical differences are obtained,and the line chart risk prediction model is constructed by R software.The ROC curve is used to predict the accuracy of the model,and the area under the ROC curve is 0.834,indicating that the clinical prediction model has a good prediction performance.At the same time,the calibration curve is used to evaluate the prediction efficiency of the model.The results show that the predicted risk curve fits well with the ideal curve,and the predicted value is basically consistent with the measured value.C-index is used to evaluate the effect of the calibration curve,the results show that the C-index is 0.83(0.78～0.89),the correction C-index is 0.78,which shows that the nomogram prediction model has a good prediction ability.ConclusionAge,BMI,education level,payment type,ACCI,operation time,intraoperative blood loss and discharge were independent risk factors for unplanned readmission within 30 days after discharge.The nomogram constructed in this study has a good predictive effect on the risk probability of unplanned readmission within 30 days after discharge of TKA patients,and provides a reference for clinicians to deal with the risk factors of readmission in time.However,these risk factors still need to be further clarified by continuous improvement of research design conditions and forward-looking,multicenter,large sample research. |
