OBJECTIVE: To compare the effectiveness and shoulder function of reverse total shoulder arthroplasty (RTSA) and open reduction and internal fixation (ORIF) in the treatment of Neer three/four-part proximal humeral fractures in the elderly. METHODS: Randomized controlled analysis was conducted on 68 patients over 70 years old with Neer three/four-part proximal humeral fractures treated with RTSA or ORIF between January 2020 and June 2022. The patients were randomly divided into RTSA group ( n=32) and ORIF group ( n=36). There was no significant difference ( P>0.05) in the baseline data such as age, gender, body mass index, injured side, Neer classification, and preoperative Charlson comorbidity index, visual analogue scale (VAS) score, Constant shoulder score, Oxford shoulder score (OSS), and hemoglobin (Hb). The operation time, intraoperative blood loss, reduction of Hb on the 3rd day after operation, hospital stay, total cost of hospitalization, complication incidence, range of motion of shoulder joint at 2 years after operation, VAS score before operation and at 5 days and 1 month after operation, Constant shoulder score and OSS score before operation and at 2 years after operation, and imaging results during follow-up were recorded and compared between the two groups. RESULTS: Compared with the ORIF group, the RTSA group had longer operation time, less intraoperative blood loss, and higher total cost of hospitalization ( P<0.05). There was no significant difference in Hb reduction on the 3rd day after operation between the two groups ( P>0.05). The VAS scores significantly improved in both groups at 5 days and 1 month after operation ( P<0.05), but there was no significant difference between the two groups ( P>0.05). All patients were followed up 26-35 months, with an average of 31.2 months. In the RTSA group, there were 2 cases of poor healing of superficial incision and 1 case of transient nerve injury. There was no complication such as bone resorption around the prosthesis, lucent band, prosthesis loosening, or periprosthetic fracture in all patients. In the ORIF group, there was 1 case of poor healing of superficial incision, 3 cases of nonunion of fracture, 1 case of arthritis secondary to humeral head necrosis, and 1 case of bone absorption of large tuberosity, and no displacement or fracture failure of internal fixation was found in all patients. There was no significant difference in the incidence of complications [9.4% (3/32) vs 16.7% (6/36)] between the two groups [ OR (95% CI): 0.828 (0.171, 4.014), P=0.814]. In the RTSA group, 28 cases were graded 0 and 4 cases were graded 1 at 2 years after operation. Constant and OSS scores of RTSA group were significantly better than those of ORIF group ( P<0.05). The Constant score was significantly better than ORIF group in activity and strength, range of motion, lifting, abduction, and external rotation ( P<0.05), and there was no significant difference in pain, daily function, and internal rotation between the two groups ( P>0.05). The RTSA group had a significantly greater range of motion in lifting, abduction, and external rotation than ORIF group ( P<0.05), but there was no significant difference in internal rotation between the two groups ( P>0.05). CONCLUSION Application of RTSA as the initial treatment of Neer three/four-part proximal humeral fractures in the elderly can achieve better rehabilitation of joint activity and lower risk of early reoperation, and improve the quality of life of elderly fracture patients. However, the difficulty of revision and the high cost of treatment require the surgeon to pay full attention and strictly grasp the indications.
Humans ; Fracture Fixation, Internal/instrumentation* ; Male ; Female ; Shoulder Fractures/surgery* ; Arthroplasty, Replacement, Shoulder/methods* ; Aged ; Bone Plates ; Open Fracture Reduction/methods* ; Range of Motion, Articular ; Treatment Outcome ; Shoulder Joint/physiopathology* ; Aged, 80 and over ; Operative Time ; Postoperative Complications/epidemiology* ; Length of Stay

Artificial intelligence (AI) researchers and cheminformatics specialists strive to identify effective drug precursors while optimizing costs and accelerating development processes. Digital molecular representation plays a crucial role in achieving this objective by making molecules machine-readable, thereby enhancing the accuracy of molecular prediction tasks and facilitating evidence-based decision making. This study presents a comprehensive review of small molecular representations and AI-driven drug discovery downstream tasks utilizing these representations. The research methodology begins with the compilation of small molecule databases, followed by an analysis of fundamental molecular representations and the models that learn these representations from initial forms, capturing patterns and salient features across extensive chemical spaces. The study then examines various drug discovery downstream tasks, including drug-target interaction (DTI) prediction, drug-target affinity (DTA) prediction, drug property (DP) prediction, and drug generation, all based on learned representations. The analysis concludes by highlighting challenges and opportunities associated with machine learning (ML) methods for molecular representation and improving downstream task performance. Additionally, the representation of small molecules and AI-based downstream tasks demonstrates significant potential in identifying traditional Chinese medicine (TCM) medicinal substances and facilitating TCM target discovery.
Artificial Intelligence ; Drug Discovery/methods* ; Humans ; Machine Learning ; Medicine, Chinese Traditional ; Small Molecule Libraries/chemistry*