Objective To externally validate a prediction model based on clinical and CT imaging features for the preoperative identification of high-grade patterns (HGP), such as micropapillary and solid subtypes, in early-stage lung adenocarcinoma, in order to guide clinical treatment decisions. Methods This study conducted an external validation of a previously developed prediction model using a cohort of patients with clinical stage ⅠA lung adenocarcinoma from the Fourth Hospital of Hebei Medical University. The model, which incorporated factors including tumor size, density, and lobulation, was assessed for its discrimination, calibration performance, and clinical impact. Results A total of 650 patients (293 males, 357 females; age range: 30-82 years) were included. The validation showed that the model demonstrated good performance in discriminating HGP (area under the curve>0.7). After recalibration, the model's calibration performance was improved. Decision curve analysis (DCA) indicated that at a threshold probability>0.6, the number of HGP patients predicted by the model closely approximated the actual number of cases. Conclusion This study confirms the effectiveness of a clinical and imaging feature-based prediction model for identifying HGP in stage ⅠA lung adenocarcinoma in a clinical setting. Successful application of this model may be significant for determining surgical strategies and improving patients' prognosis. Despite certain limitations, these findings provide new directions for future research.

Objective    To study the relationship between preoperative heart rate variability (HRV) and postoperative atrial fibrillation (POAF) after off-pump coronary artery bypass grafting (OPCAB). Methods    A retrospective analysis was performed on the clinical data of 290 patients who were admitted to the Department of Cardiovascular Surgery, General Hospital of Northern Theater Command from May to September 2020 and received OPCAB. There were 217 males and 73 females aged 36-80 years. According to the incidence of POAF, the patients were divided into two groups: a non-atrial fibrillation group (208 patients) and an atrial fibrillation group (82 patients). The time domain and frequency domain factors of mean HRV 7 days before operation were calculated: standard deviation of all normal-to-normal intervals (SDNN), root mean square of successive differences, percentage difference between adjacent normal-to-normal intervals that were greater than 50 ms, low frequency power (LF), high frequency power (HF), LF/HF. Results    The HRV value of patients without POAF was significantly lower than that of patients with POAF (P<0.05). The median SDNN of the two groups were 78.90 ms and 91.55 ms, respectively. Age (OR=3.630, 95%CI 2.015-6.542, P<0.001), left atrial diameter (OR=1.074, 95%CI 1.000-1.155, P=0.046), and SDNN (OR=1.017, 95%CI 1.002-1.032, P=0.024) were independently associated with the risk of POPAF after OPCAB. Conclusion     SDNN may be an independent predictor of POAF after OPCAB.

Computer-aided diagnosis (CAD) systems play a very important role in modern medical diagnosis and treatment systems, but their performance is limited by training samples. However, the training samples are affected by factors such as imaging cost, labeling cost and involving patient privacy, resulting in insufficient diversity of training images and difficulty in data obtaining. Therefore, how to efficiently and cost-effectively augment existing medical image datasets has become a research hotspot. In this paper, the research progress on medical image dataset expansion methods is reviewed based on relevant literatures at home and abroad. First, the expansion methods based on geometric transformation and generative adversarial networks are compared and analyzed, and then improvement of the augmentation methods based on generative adversarial networks are emphasized. Finally, some urgent problems in the field of medical image dataset expansion are discussed and the future development trend is prospected.
Humans ; Diagnosis, Computer-Assisted ; Diagnostic Imaging ; Datasets as Topic

Magnetic ferrite nanoparticles (MFNPs) have great application potential in biomedical fields such as magnetic resonance imaging, targeted drugs, magnetothermal therapy and gene delivery. MFNPs can migrate under the action of a magnetic field and target specific cells or tissues. However, to apply MFNPs to organisms, further modifications on the surface of MFNPs are required. In this paper, the common modification methods of MFNPs are reviewed, their applications in medical fields such as bioimaging, medical detection, and biotherapy are summarized, and the future application directions of MFNPs are further prospected.
Ferric Compounds ; Magnetic Resonance Imaging/methods* ; Magnetics ; Magnetite Nanoparticles/therapeutic use* ; Nanoparticles

Medical image segmentation based on deep learning has become a powerful tool in the field of medical image processing. Due to the special nature of medical images, image segmentation algorithms based on deep learning face problems such as sample imbalance, edge blur, false positive, false negative, etc. In view of these problems, researchers mostly improve the network structure, but rarely improve from the unstructured aspect. The loss function is an important part of the segmentation method based on deep learning. The improvement of the loss function can improve the segmentation effect of the network from the root, and the loss function is independent of the network structure, which can be used in various network models and segmentation tasks in plug and play. Starting from the difficulties in medical image segmentation, this paper first introduces the loss function and improvement strategies to solve the problems of sample imbalance, edge blur, false positive and false negative. Then the difficulties encountered in the improvement of the current loss function are analyzed. Finally, the future research directions are prospected. This paper provides a reference for the reasonable selection, improvement or innovation of loss function, and guides the direction for the follow-up research of loss function.
Algorithms ; Image Processing, Computer-Assisted

Bioactive glass (BG) has been widely used in the preparation of artificial bone scaffolds due to its excellent biological properties and non-cytotoxicity, which can promote bone and soft tissue regeneration. However, due to the brittleness, poor mechanical strength, easy agglomeration and uncontrollable structure of glass material, its application in various fields is limited. In this regard, most current researches mainly focus on mixing BG with organic or inorganic materials by freeze-drying method, sol-gel method, etc., to improve its mechanical properties and brittleness, so as to increase its clinical application and expand its application field. This review introduces the combination of BG with natural organic materials, metallic materials and non-metallic materials, and demonstrates the latest technology and future prospects of BG composite materials through the development of scaffolds, injectable fillers, membranes, hydrogels and coatings. The previous studies show that the addition of BG improves the mechanical properties, biological activity and regeneration potential of the composites, and broadens the application of BG in the field of bone tissue engineering. By reviewing the recent BG researches on bone regeneration, the research potential of new materials is demonstrated, in order to provide a reference for future related research.
Bone Regeneration ; Bone and Bones ; Freeze Drying ; Glass ; Hydrogels

Glaucoma is one of blind causing diseases. The cup-to-disc ratio is the main basis for glaucoma screening. Therefore, it is of great significance to precisely segment the optic cup and disc. In this article, an optic cup and disc segmentation model based on the linear attention and dual attention is proposed. Firstly, the region of interest is located and cropped according to the characteristics of the optic disc. Secondly, linear attention residual network-34 (ResNet-34) is introduced as a feature extraction network. Finally, channel and spatial dual attention weights are generated by the linear attention output features, which are used to calibrate feature map in the decoder to obtain the optic cup and disc segmentation image. Experimental results show that the intersection over union of the optic disc and cup in Retinal Image Dataset for Optic Nerve Head Segmentation (DRISHTI-GS) dataset are 0.962 3 and 0.856 4, respectively, and the intersection over union of the optic disc and cup in retinal image database for optic nerve evaluation (RIM-ONE-V3) are 0.956 3 and 0.784 4, respectively. The proposed model is better than the comparison algorithm and has certain medical value in the early screening of glaucoma. In addition, this article uses knowledge distillation technology to generate two smaller models, which is beneficial to apply the models to embedded device.
Humans ; Optic Disk/diagnostic imaging* ; Glaucoma/diagnosis* ; Algorithms ; Diagnostic Techniques, Ophthalmological ; Databases, Factual

OBJECTIVE: To investigate the effects of enhanced recovery after surgery (ERAS) on postoperative function and pain in total hip arthroplasty (THA) patients with high comorbidity. METHODS: Patients with THA who were admitted between January 2020 and January 2022 were selected as the study objects, and a total of 223 patients with high comorbidity met the selection criteria. Patients were randomly divided into two groups using the random envelope method. During perioperative period, 112 cases in the ERAS group were treated according to the ERAS protocol and 111 cases in the control group with the traditional protocol. There was no significant difference in gender, age, body mass index, Charlson comorbidity index, preoperative diagnosis, the type and number of the comorbidities, preoperative visual analogue scale (VAS) score between the two groups ( P>0.05). However, the Harris score of ERAS group was significantly lower than that of control group before operation ( P<0.05). Preoperative and postoperative hospital stays were recorded. The VAS score was used to evaluate the pain before operation, at 1 day after operation, at the leaving bed time, at the day after discharge, and at 2 weeks after operation. Harris score was used to evaluate hip function before operation and at 2 weeks, 1 month, 3 months, 6 months, and 12 months after operation. The incidence of complications, 30-day readmission rate, mortality rate, and patient's satisfaction were recorded. RESULTS: The length of preoperative hospital stay in ERAS group was significantly shorter than that in control group ( P<0.05). But there was no significant difference in the length of postoperative hospital stay between groups ( P>0.05). All patients in the two groups were followed up 12 months. The VAS score in the two groups after operation was lower than that before operation, and showed a gradually trend with the extension of time, with significant differences between different time points ( P<0.05). VAS scores of ERAS group were significantly lower than those of control group at different time points after operation ( P<0.05). The postoperative Harris scores in both groups were higher than those before operation, and showed a gradually increasing trend with the extension of time, with significant differences between different time points ( P<0.05). Harris scores of ERAS group at 2 weeks, 1 month, and 3 months after operation were significantly higher than those of control group ( P<0.05). Complications occurred in 2 cases (1.79%) of the ERAS group and 6 cases (5.41%) of the control group, with no significant difference in incidence ( P>0.05). In the control group, 1 case was readmitted within 30 days after operation, and 1 case died of severe pneumonia within 1 year of follow-up. There was no readmission or death in ERAS group, and there was no significant difference in the above indexes between the two groups ( P>0.05). At last follow-up, the satisfaction rate of patients in ERAS group was slightly higher than that in control group, but the difference was not significant ( P>0.05). CONCLUSION For THA patients with high comorbidity, ERAS protocol can shorten preoperative waiting time, better reduce pain, and improve hip function.
Humans ; Arthroplasty, Replacement, Hip ; Enhanced Recovery After Surgery ; Comorbidity ; Pain ; Postoperative Period

Objective    To investigate the safety of endoscopic thoracic sympathicotomy in the treatment of primary hyperhidrosis based on ambulatory surgery mode. Methods    Retrospective analysis was performed on the clinical data of 158 patients with primary hyperhidrosis who received endoscopic thoracic sympathicotomy in the Affiliated Hospital of Zunyi Medical University from January 2019 to March 2021. There were 68 (43.2%) males and 90 (56.8%) females with an average age of 14-33 (20.5±3.1) years. The basic information of the patients, operation time, intraoperative blood loss, postoperative pain score, hospitalization expenses and postoperative complications were observed and recorded. Results    All surgeries were successfully completed and the patients were discharged as planned. The operation time was 41.8±13.9 min, the intraoperative blood loss was 10.5±7.3 mL, the postoperative anesthesia recovery time was 15.0±5.9 min, and the pain score was 3.0±0.9 points. The total length of hospitalization was 1.6±1.0 days. The total postoperative expenses were 9 471.7±1 698.9 yuan. Pneumothorax occurred after the operation in 3 patients. Telephone follow-up on the 30th day after the operation showed no recurrence of sweaty hands, pneumothorax or rapid heart rate, and no serious complications or death related to the day operation within 30 days after the operation. Conclusion    Endoscopic thoracic sympathicotomy based on ambulatory surgery mode is safe and effective in the treatment of primary hyperhidrosis.

Objective: Patients undergoing coronary artery bypass graft (CABG) surgery remain at high cardiovascular risk; however, few studies have evaluated lipid management and attainment of lipid targets in these patients. We investigated the proportion of CABG surgery patients who attained low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (HDL-C) targets. Methods: Data were retrospectively obtained from patients undergoing CABG surgery at an Australian tertiary hospital between February 2015 and August 2020. The most recent lipid profile was recorded (at least 3 weeks post-operatively). We studied patients with electronically available data to ensure accuracy. Target LDL-C was defined as <1.4 (54 mg/dL) and <1.8 mmol/L (70 mg/dL), and target non-HDL-C as <2.2 (85 mg/dL) and <2.6 mmol/L (100 mg/dL), as per the 2019 and 2016 European dyslipidaemia guidelines, respectively. Results: Follow-up lipid results were available for 484 patients (median post-operative follow-up, 483 days; interquartile range, 177.5–938.75 days). The mean age was 62.7±10.5 years and 387 (80.1%) were male. At discharge, 469 (96.9%) patients were prescribed statins, 425 (90.6%) high-intensity. Ezetimibe was prescribed for 62 (12.8%) patients and a proprotein convertase subtilisin-kexin type 9 inhibitor for 1. LDL-C levels <1.4 and <1.8 mmol/L were attained in 118 (24.4%) and 231 (47.7%) patients, respectively, and non-HDL-C levels <2.2 and <2.6 mmol/L in 140 (28.9%) and 237 (49.0%) patients, respectively. Conclusion The use of non-statin lipid-lowering therapies was limited, and many CABG surgery patients did not attain lipid targets despite high-intensity statins. Further studies are required to optimise lipid management in this very high-risk population.