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Objective To construct a risk assessment scale for postoperative delirium(POD)in elderly patients undergoing hip and knee joint replacement and evaluate the effect.Methods A total of 474 elderly patients undergoing hip and knee arthroplasty from March 2021 to May 2022 were collected as the training set,and a total of 153 the homogeneous patients from January 2022 to May 2022 were collected as the validation set.The patients were divided into two groups based on whether or not POD occurred:non-POD group and POD group.Risk factors of POD in the training set were analyzed by univariate analysis and multifactorial logistic regression.The consistency of the model was evaluated by Homser-Lemeshow goodness of fit test.The postoperative delirium risk assessment scale was established after the selected variables as-signed value according to OR value,and the predictive efficacy of the scale was evaluated by receiver oper-ating characteristic(ROC)curve.The patients in the training set and the validation set were divided into two groups according to the cut-off value:high-risk and low-risk.The incidence rate of POD with different risk stratification was calculated and the applicability of the risk assessment scale was evaluated.Results Fifty-eight patients(12.2%)with POD in the training set,and nineteen patients(12.4%)with POD in the validation set.Multifactor logistic regression showed that age≥85 years,ASA physical status Ⅲ or Ⅳ,the mini-mental state examination(MMSE)score≤24 points,preoperative sleep disorder,comorbid neu-rological disorders,use of general anesthesia,and non-use of dexmedetomidine were independent risk factors of POD.The POD risk assessment scale was then published based the seven risk factors.The ROC curve showed that the area under the curve(AUC)for this scale to predict the risk of POD was 0.956(95%CI 0.937-0.975),and the risk stratification was performed with a cut-off value of 44.5 points,which divided the patients into low-risk and high-risk.Compared with low-risk,the incidence rate of POD in high-risk patients group was significantly increased(P＜0.001).Conclusion A risk assessment scale based on the seven risk factors:age≥85 years,ASA physical status Ⅲ or Ⅳ,MMSE score≤24 points,preoperative sleep disorder,combined neurological disease,use of general anesthetic modality,and non-use of dexmedetomidine,can effectively identify elderly patients undergoing hip and knee replacement who are at high risk of developing POD.
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Objective To observe the value of intratumoral and peritumoral radiomics based on diffusion weighted imaging(DWI)for predicting histological grade of breast cancer.Methods Preoperative DWI data of 700 patients with single breast cancer diagnosed by pathology were retrospectively analyzed.The patients were divided into training set(n= 560,including 381 of grade Ⅰ+Ⅱ and 179 of grade Ⅲ)and test set(n=140,including 95 of grade Ⅰ+Ⅱ and 45 of grade Ⅲ)at the ratio of 8∶2.Intratumoral ROI(ROIintra)was manually delineated on DWI,which was automatically expanded by 3 mm and 5 mm to decline peritumoral ROI(ROIperi,including ROI3 mm and ROI5 mm),then intratumoral-peritumoral ROI(ROIintra+3 mm,ROIintra+5 mm)were obtained.The optimal radiomics features were extracted and screened,and the radiomics model(RM)for predicting the histological grade of breast cancer were constructed.Receiver operating characteristic curves were drawn,and the areas under the curve(AUC)were calculated to evaluate the predictive efficacy of each model.Calibration curve method was used to evaluate the calibration degree,while decision curve analysis(DCA)was performed to explore the clinical practicability of each model.Results AUC of RMintra,RM+3 mm,RM+5mm,RMintra+3 mm and RMintra+5 mm was 0.750,0.724,0.749,0.833 and 0.807 in training set,while was 0.723,0.718,0.736,0.759 and 0.782 in test set,respectively.In training set,significant differences of AUC was found(all P＜0.01),while in test set,no significant difference of AUC was found among models(all P＞0.05).The calibrations of models were all high.DCA showed that taken 0.02-0.88 as the threshold,the clinical net benefit of RMintra+per were greater in training set,while taken 0.40-0.72 as the threshold,the clinical net benefit of RMintra+per was greater in test set.Conclusion Both DWI intratumoral and peritumoral radiomics could effectively predict histological grade of breast cancer.Combination of intratumoral and peritumoral radiomics was more effective.
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A 3-year-old male patient was diagnosed with neurofibromatosis type 1(NF1) for two years. The patient has multiple neurofibromas in retroperitoneum, lumbococcygeal paravertebral, lumbosacral spinal canal, and foramina. Due to retroperitoneal mass compression, the child suffered from urological complications such as hydronephrosis, ureterdilation, neurogenic bladder, etc., which seriously affected the urination function and resulted in multiple surgical treatments. Currently, the patient has been treated with mitogen activates extracelluar signal-regulated kinases(MEK) inhibitor selumetinib targeted therapy, and has voluntarily urinated, and his general state is better than before medication. The diagnosis and treatment of this case reflects the importance of multidisciplinary collaboration in the diagnosis and treatment of rare diseases.
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Objective The aim of this study was to evaluate whether PRDM16 gene polymorphisms were associated with dyslipidemia. Methods The polymorphisms of rs2651899, rs2236518, rs870171, and rs2282198 in PRDM16 gene in 528 participants were genotyped by the method of snapshot or ligase detection reaction. The genotype differences and the allele differences between the case group and the control group were analyzed. Linkage disequilibrium analysis was performed with SHE-sis online software. The interaction between rs2651899, rs2236518, rs870171, rs2282198 and gender, age, BMI were analyzed by MDR software. Results The frequency of allele A in rs2651899 locus was significantly higher in low HDL-C group compared with that in control group[OR(95%CI)=1.32(1.02-1.71), P=0.033]. The frequency of A/C genotype in rs870171 was significantly different between LDL-C abnormal group and control group[OR(95% CI)=1.97(1.01-3.86), P=0.037]. There may be interaction between rs2236518 and sex, which is a risk factor for low HDL-C[Model Ⅱ: OR(95% CI)=1.958(1.366-2.809), P<0.01]. There may be interactions among rs2651899, rs2236518, rs870171, and rs2282198, which seemed to be risk factors for lower HDL-C[Model Ⅳ: OR(95% CI)=3.991(2.707-5.884), P<0.01]. rs870171, rs2282198 may have interaction with age, which is a risk factor for high LDL-C [Model Ⅶ: OR(95%CI)=3.991(2.707-5.884), P<0.01]. Conclusion Allele A of rs2651899 may be a risk factor to low HDL-C. Under the codominant inheritance patterns, genotype A/C of rs870171 may be a risk factor to high LDL-C. In addition, there may be interaction between SNPs with gender and age.