Objective To compare the efficacy of fixed bearing(FB) and rotating bearing(RB) in total knee arthroplasty (TKA) for knee valgus. Methods Data of 203 cases with valgus knee deformity who had undergone TKA procedure from January 2007 to December 2013 were retrospectively analyzed. 181 cases were primary joint replacement. They were divided into FB group and RB group. 168 patients (168 knees) were followed?up for more than 2 years. 83 cases (83 knees) were in FB group, and 85 cases (85knees) were in RB group. There were 57 males and 111 females, aged from 40 to 79 years, with an average age of 59.3 ± 7.2 years. Among them, 153 cases were osteoarthritis and 15 cases were rheumatoid arthritis. Activities of the knee , tibio?femoral angle on X?ray, Hospital for Special Surgery (Hospital for Special Surgery, HSS) knee score and the SF?36 scale scores were recorded before surgery and at the final follow?up. Results All patients were followed up for 24 to 84 months (average, 37.4 months). The average knee activities of the fixed bearing and rotating mobile bearing were from 72.8°±13.1°and 71.2°±12.8° be?fore surgery to 106.5°±9.8°and 115.4°±7.9° at final follow?up. The average tibiofemoral angle on X?ray decreased from 16.8°±5.3° and 15.2° ± 4.7° preoperatively to 5.6° ± 2.3 and 5.2° ± 2.1° at the final follow?up. The HSS knee score improved from 47.5 ± 7.1 points and 49.6±8.9 points to 89.1±4.6 points and 90.2±5.3 points at final follow?up. The SF?36 scale scores improved from 52.3± 15.4 points and 50.1±17.9 points to 81.6±12.3 points and 82.2±14.5 points at the final follow?up. At the latest follow?up, except the Range of motion, there were no statistically significant in any other indicator between two groups. Two cases appeared postoper?ative deep venous thrombosis symptoms. One case had joint stiffness early, and the symptoms improved after strengthen functional exercise. No infections, delayed knee instability, implant loosening or subsidence was found during the follow?up. Conclusion For patients with mild to moderate knee valgus, both fixed and rotating bearing with same soft tissue balance technique can improve the knee function and correct the valgus deformity, and the recent results are satisfactory.

BACKGROUND:In order to avoid heterotopic ossification after total hip arthroplasty, nonsteroidal anti-inflammatory drugs are commonly used for prevention.
OBJECTIVE:To compare the effect of meloxicam and indomethacin in the prevention of heterotopic ossification after total hip arthroplasty.
METHODS:Fifty-one patients who treated in the Department of Orthopedics, the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine from 2010 to 2011 were col ected. Among the 51 patients, nine patients were treated with bilateral total hip arthroplasty, and al the patients had total hip arthroplasty with the posterior-lateral approach. The patients were divided into the control group and the experimental group according to the drugs used after replacement, and the patients in the two groups were administered with indomethacin sustained-release tablet 25 mg+omeprazole capsule 20 mg or meloxicam tablet 15 mg after replacement.
RESULTS AND CONCLUSION:There were no significant differences in the incidence of heterotopic ossification, pain, modified D’Aubigne and Postel scores after replacement between two groups (P>0.05). But, the gastrointestinal adverse reactions of the experimental group were less than those of the control group. The application of meloxicam only can effectively avoid the heterotopic ossification and release pain. Consequently, we recommend meloxicam as postoperative drug for the prevention of heterotopic ossification and pain remission fol owing total hip arthroplasty.

OBJECTIVETo deepen the understanding of patients with complete necrosis of the ureter after renal transplantation for early diagnosis and treatment.

METHODSOf 5 patients with complete necrosis of the ureter after renal transplantatioin between January 1991 and April 2001 in our hospital, 4 were male and 1 was female (mean age, 35 years). Seven to 12 days after renal transplantation, native pyeloureterestomy was performed for 1 patient, and the remaining 4 patients received the cutting of the diatal necrosis ureter and vesicoureterostomy because of urine leakage. Six to seven weeks later when the ureter stents were pull out, native pyeloureterestomy or pyeloureteroplasty was performed for the 4 patients because of uropenia and hydronephrosis.

RESULTSFive patients showed normal function of the kidney postopcreation (follow up: 6 - 12 months) without hydronephrosis.

CONCLUSIONSWhen distal necrosis of the ureter is observed after renal transplantation, complete necrosis of the ureter may occur. Native pyeloureterostomy or pyeloureteroplasty is an effective treatment.

Adult ; Cadaver ; Female ; Humans ; Kidney Transplantation ; Male ; Middle Aged ; Necrosis ; Postoperative Complications ; Ureter ; pathology ; surgery

Objective To observe the value of 3D Res2Net deep learning model for predicting volume doubling time(VDT)of solid pulmonary nodule.Methods Chest CT data of 734 patients with solid pulmonary nodules were retrospectively analyzed.The patients were divided into progressive group(n=218)and non-progressive group(n=516)according to whether lung nodule volume increased by ≥25％during follow-up or not,also assigned into training set(n=515)and validation set(n=219)at a ratio of 7∶3.Then a clinical model was constructed based on clinical factors being significantly different between groups,CT features model was constructed based on features of nodules on 2D CT images using convolutional neural network,and 3D Res2Net model was constructed based on Res2Net network using 3D CT images as input.Receiver operating characteristic curve was drawn,and the area under the curve(AUC)was calculated.Taken actual VDT as gold standard,the efficacy of the above models for predicting solid pulmonary nodule'VDT≤400 days were evaluated.Results No significant difference of predicting efficacy for solid pulmonary nodule'VDT≤400 days was found among clinical model,CT feature model and 3D Res2Net model,the AUC of which was 0.689,0.698 and 0.734 in training set,0.692,0.714 and 0.721 in validation set,respectively.3D Res2Net model needed 5-7 s to predict VDT of solid pulmonary nodules,with an average time of(5.92±1.08)s.Conclusion 3D Res2Net model could be used to predict VDT of solid pulmonary nodules,which might obviously reduce manual interpreting time.

Objective:To construct an intelligent foreign bodies detection model based on Faster R-convolutional neural network in posterior-anterior chest X-ray and evaluate the performance of the model.Methods:Totally 5 567 adult posterior-anterior DR chest radiographs from Zhejiang Provincial People′s Hospital and Chun′an County People′s Hospital from June 2019 to March 2020, with 4 247 foreign body-containing chest radiographs were analyzed retrospectively. All data were randomly divided into training set (2 911 foreign body-containing), validation set ( n=1 456, 733 foreign body-containing, 723 free of foreign body) and testing set ( n=1 200, 603 foreign body-containing, 597 free of foreign body). The reference gold standard was set as the results of each chest radiography with foreign body annotated by two radiology residents and reviewed and corrected by a senior radiographer. The receiver operating characteristic (ROC) curve and the area under the curve were used to analyze the efficiency of the deep learning model to distinguish the presence or absence of foreign bodies on chest radiography in the testing set. The precision-recall curve and mean precision (mAP) were used to analyze the stability of the model at different levels. Finally, the influence of different locations, patient gender, and patient age on the foreign body recall of the deep learning model were analyzed. Results:In the testing set, the sensitivity of the deep learning model in diagnosing whether chest radiograph contained foreign bodies was 93.2%(562/603), the specificity was 92.6%(553/597), and the F1 score was 0.94. The area under the ROC curve was 0.97, and the mAP value was 0.69. For foreign bodies in different locations, the recall rates of foreign bodies in lung field and outside lung field were 91.2% (674/739) and 89.0% (1 411/1 585), respectively. For different genders, the recall rates for male and female foreign body detection were 87.3% (337/386) and 90.0%(1 745/1 938), respectively. For different age ranges, the recall rate of foreign body detection was 92.5% (1 041/1 126) for 18-38 years old, 89.7%(505/563) for 39-58 years old, 83.5%(335/401) for 59-78 years old and 85.9% (201/234) for patients ≥79 years old.Conclusion:The constructed deep learning-based foreign body detection model for adult posterior-anterior chest X-ray provides high sensitivity and stability, which can identify foreign bodies in chest radiography quickly and accurately.

Objective To observe the value of feature pyramid network(FPN)for automatic segmentation and semantic feature classification of spontaneous intracerebral hemorrhage(sICH)hematoma showed on non-contrast CT.Methods Non-contrast CT images of 408 sICH patients in hospital A(training set)and 103 sICH patients in hospital B(validation set)were retrospectively analyzed.Deep learning(DL)segmentation model was constructed based on FPN to segment the hematoma region,and its efficacy was assessed using intersection over union(IoU),Dice similarity coefficient(DSC)and accuracy.Then DL classification model was established to identify the semantic features of sICH hematoma.Receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the efficacy of DL classification model for recognizing semantic features of sICH hematoma.Results The IoU,DSC and accuracy of DL segmentation model for 95％sICH hematoma in training set was 0.84±0.07,0.91±0.04 and(88.78±8.04)％,respectively,which was 0.83±0.07,0.91±0.05 and(88.59±7.76)％in validation set,respectively.The AUC of DL classification model for recognizing irregular shape,uneven density,satellite sign,mixed sign and vortex sign of sICH hematoma were 0.946-0.993 and 0.714-0.833 in training set and validation set,respectively.Conclusions FPN could accurately,effectively and automatically segment hematoma of sICH,hence having high efficacy for identifying semantic features of sICH hematoma.

Humans ; Asthma/diagnosis* ; HMGB1 Protein