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Objective:To evaluate the radiological and clinical outcomes of the aged patients with unstable proximal humeral fracture (UPHF) treated with a locking plate and an intramedullary titanium mesh.Methods:A retrospective study was conducted to analyze the 43 aged patients with UPHF who had been admitted to Department of Orthopedics, Zhongda Hospital Affiliated to Southeast University from January 2017 to July 2019. There were 13 males and 30 females with an age of (71.3±10.3) years (from 60 to 83 years). All patients were treated with a locking plate and an intramedullary titanium mesh to support. The postoperative imaging measurements included changes in humeral head height (HHH) and neck-shaft angle (NSA) (the difference between 3 years after surgery and the second day after surgery, taken as an absolute value); the postoperative clinical measurements included visual analogue scale (VAS), range of shoulder motion, Constant-Murley shoulder functional score (Constant score), American Shoulder and Elbow Surgeons (ASES) score, and incidence of complications.Results:All patients were followed up for (39.2±2.3) months after surgery. The change in HHH at 3 years after surgery was (1.5±1.1) mm, and the change in NSA at 3 years after surgery 3.3°±2.6°. At 3 years after surgery, the VAS score was (2.2±1.3) points, the Constant score (79.2±9.1) points, and the ASES score (78.9±9.2) points; the range of forward extension was 143.2°±20.8°, the range of outward extension 139.3°±23.1°, and the range of outward rotation 55.1°±4.7°. Complications after surgery were found in 6 patients, including humeral head necrosis in 2 cases, ectopic ossification in 1 case, and infection in 3 cases.Conclusion:In the treatment of the aged patients with UPHF, a locking plate combined with an intramedullary titanium mesh can help to restore the medial column support, leading to fine radiological and clinical outcomes.
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Objective:To summarize the experience and the clinical data of patients with primary hyperparathyroidism undergoing endoscopic parathyroidectomy.Methods:A total of 24 patients who underwent endoscopic parathyroidectomy for primary hyperparathyroidism in Peking Union Medical College Hospital during Feb. 2021 to May. 2022 were concluded in this study (20 cases of parathyroidectomy via axillary approach and 4 cases of parathyroidectomy via thoracic and breast approach) . The operation time, postoperative drainage, length of stay, level of parathyroid hormone and serum calcium of those patients were collected. Postoperative complications and recurrence of hyperparathyroidism were also observed.Results:The postoperative levels of serum parathyroid hormone and serum calcium were significantly reduced (over 50%) compared with preoperative level ( P<0.05) . The average operation time was (96±22) min (64-157 min) . The mean postoperative drainage volume was (47±16) ml on day 1, (46±11) ml on day 2, and (30±9) ml on day 3, respectively. The average length of postoperative hospital stay was (2.8±1.1) days (2-6 days) . In one case of parathyroidectomy via axillary approach, the operation was converted to open surgery because of the low position of lesion. Other cases completed endoscopic surgery and obtained satisfactory cosmetic results. There were no postoperative complications such as bleeding, permanent hoarseness, coughing while drinking water, or surgical site infection. The mean follow-up time was (7.4±4.2) months (1-16 months) . There was no obvious discomfort and no recurrence during follow-up. Conclusion:Endoscopic parathyroidectomy is safe and effective in the treatment of primary hyperparathyroidism, which can be used as a surgical option for patients with cosmetic requirements.
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Objective:To explore whether deep learning could apply to recognize the recurrent laryngeal nerve (RLN) in videos of endoscopic thyroidectomy (ETE) via breast approach.Methods:Videos of ETE via breast approach in Peking Union Medical College Hospital from Feb. 2020 to Aug. 2021 were collected. Videos containing RLN were selected, and the outline of RLN was marked by two thyroid surgeons. Then data were divided into a training set and a test set in a ratio of 5:1 and classified into the high and low difficulty group according to a senior thyroid surgeon’s opinion. Those pictures were input to D-LinkNet model. Precision, sensitivity and mean dice index was calculated.Results:A total of 46 videos including 153, 520 frames of pictures were included in this study. 131,039 frames of 39 videos were in the training set and 22,481 frames of 7 videos were in the test set. When the intersection over union threshold was 0.1, the sensitivity and precision was 92.9%/72.8% and 47.6%/54.9% in high and low recognition group, respectively. When the intersection over union threshold was 0.5, the sensitivity and precision turned to 85.8%/67.2% and 37.6%/43.5% in high and low difficulty group, respectively. Mean Dice index was 0.781 and 0.663 in high and low difficulty group, respectively.Conclusions:RLN recognition based on deep learning is feasible and has potential application value in ETE, which may help surgeons reduce the risk of accidental injury of RLN and improve the safety of thyroidectomy.
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Objective:To explore whether deep learning could apply to recognize the recurrent laryngeal nerve in the video of unilateral axillary approach endoscopic thyroidectomy.Methods:Videos of endoscopic thyroidectomy via unilateral axillary approach in Peking Union Medical College Hospital from Jul. 1st, 2020 to May. 1st, 2021 were collected. Videos containing the recurrent laryngeal nerve were selected, and the outline of recurrent laryngeal nerve were marked by two senior thyroid surgeons and staffs. Data were divided into training set and test set in a ratio of 5:1, and classified into high, medium and low recognition group according to difficulty of recognizing the outline of the nerve. The neuron network was based on PSPNet combined with Resnet50. All data were analyzed by R (ver. 4.0.2) .Results:A total of 38 videos including 35,501 frames of pictures were included in this study. 29, 704 frames of 32 videos were in our training set and 5797 frames of 6 videos were in the test set. When the intersection over union (IOU) threshold is 0.1, the sensitivity and precision is 100.0%/92.1%, 95.8%/80.2% and 81.0%/80.6% in high, medium and low recognition group respectively. When the IOU threshold is 0.5, the sensitivity and precision is 92.6%/85.3%, 71.7%/60.5% and 38.1%/37.9% in high, medium and low recognition group respectively, indicating that neuron network could located the outline of recurrent laryngeal nerve in high and medium recognition group. False negatives were often due to small targets and unclear boundaries.Conclusion:Recurrent laryngeal nerve recognition based on deep learning is feasible and has potential application value in endoscopic thyroidectomy, which may help surgeons reduce the risk of accidental injury of recurrent laryngeal nerve and improve the safety of thyroidectomy.
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Objective:To investigate the application value of machine learning algorithms for gauze detection in laparoscopic pancreatic surgery.Methods:The retrospective and descriptive study was conducted. The 80 intact laparoscopic pancreatic surgery videos from Peking Union Medical College Hospital of Chinese Academy of Medical Sciences with timing of July 2017 to July 2020 were collected. The training set was used to train the neural network, and the test set was used to test the ability of neural network for gauze detection under different difficulties. Under the supervision of two superior doctors, videos that containing gauze were selected and classified according to recognition difficulty into three difficulty level including easy, normal and hard difficulty, and further divided based on random number method into training set with 61 videos and test set with 19 videos in a ratio of 3:1 roughly. The minimum enclosing rectangle of the gauze were marked frame by frame. All images were input to the neural network model for training after normalization and preprocessing. For every image, the output of neural network is the predicted minimum enclosing rectangle of gauze. The intersection over union >0.5 was identified as positive result. Observation indicators: (1) video annotation and classification; (2) test outcomes of neural network for test set.Count data were represented as absolute numbers or percentages.Results:(1) Video annotation and classification: a total of 26 893 frames of images form 80 videos were annotated, with 61 videos including 22 564 frames of images as the training set and 19 videos including 4 329 frames of images as the test set. Of the training set, 19 videos including 5 791 frames of images were classifed as easy difficulty, 38 videos including 15 771 frames of images were classifed as normal difficulty, 4 videos including 1 002 frames of images were classifed as hard difficulty, respectively. Of the test set, 4 videos including 1 684 frames of images were classifed as easy difficulty, 6 videos including 1 016 frames of images were classifed as normal difficulty, 9 videos including 1 629 frames of images were classifed as hard difficulty, respectively. (2) Test outcomes of neural network for test set: the overall sensitivity and accuracy of gauze detection by neural network in the test set were 78.471%(3 397/4 329) and 69.811%(3 397/4 866), respectively. The sensitivity and accuracy of gauze detection by neural network were 94.478%(1 591/1 684) and 83.168%(1 591/1 913) in easy difficulty test set. The sensitivity and accuracy of gauze detection by neural network were 80.413%(817/1 016) and 70.859%(817/1 153) in normal difficulty test set, 60.712%(989/1 629) and 54.944%(989/1 800)in hard difficulty test set. The frame rate reached more than or equally to 15 fps. The overall false negative rate and false positive rate of gauze detection by neural network in the test set were 21.529%(932/4 329) and 30.189%(1 469/4 866), respectively. The false negative was mainly due to the existence of blurred images, too small gauze exposure or blood immersion of gauze. The false positive was caused by the reflection of connective tissue or body fluids.Conclusion:The machine learning algorithms for gauze detection in laparoscopic pancreatic surgery is feasible, which could help medical staff identify gauze.
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Objective To compare scene simulation teaching method with traditional methods on training in cardiopulmonary resuscitation (CPR) for the practice students. Methods A convenience sample of 62 nursing students in the emergency department of our hospital in 2014 were recruited as the observation group,and 75 practice students in 2013 were recruited as the control group. The observation group used the scene simulation teaching method for students and the control group used the traditional methods. The students′theoretical knowledge, operation skill of CPR and total score of core capability were compared between two groups. Results The theoretical knowledge, operation skill of CPR and total score of core capability in the observation group were (85.23±6.36), (86.90±4.85), (217.98±6.06), significantly higher than those of the control group, which were (75.36±7.77), (82.38±8.84), (209.33±8.91), t= 8.02, 3.60 and 6.50, P<0.01. Conclusions The scene simulation teaching method is an effective form of emergency department training in CPR, help to improve students practice ability and the ability of emergency cardiopulmonary resuscitation.
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Objective To investigate the correlation between plasma brain natriuretic peptide (BNP) ,central aortic systolic pres-sure with the degree of coronary artery lesion .Methods One hundred and fifty patients with coronary artery disease ,positive coro-nary angiographic results and without heart failure in the cardiological department of this hospital from March to June 2011 were selected and divided into the hypertension group (n=90) and the non-hypertension group(n=60) according to the blood pressure . The plasma BNP before angiography was detected by ELISA .The coronary lesion vessels and clinical scores were assessed after an-giography .The central aortic pressure before angiography was measured by the noninvasive measurement method and the diastolic blood pressure(DBP) ,systolic blood pressure(SBP) and pulse pressure(PP)were recorded .The correlation between PP and BNP was analyzed by Logistic regression .Results The plasma BNP concentration in the hypertension group was significantly higher than that in the non-hypertension group(P<0 .05) .The SBP level in 2 vessels ,3 vessels was significantly higher than that in the momal coronary group(P<0 .05) ,the PP in 3 vessels was significantly higher than that in the momal coronary group (P<0 .05) . The BNP level in 3 vessels ,2 vessels and single vessel of coronary artery lesion was significantly higher than that in the normal cor-onary artery group(P<0 .05) .The Logistic regression analysis on the PP influencing factors found that PP was closely related with the number of coronary artery lesion vessels ,lesion score ,LVEF and BNP ;the multiple correlation coefficient between PP with the number of coronary artery lesion vessels ,lesion score and BPN was 0 .91 ,its linear model was PP=0 .543 lesion vessels number +0 .656 lesion score + 0 .864 BNP .Conclusion PP of the central aortic pressure is a risk factor for the development and progress of coronary artery stenosis occurrence .BNP may be used as a plasma marker of the degree of coronary artery stenosis .