Application Of Artificial Intelligence Pre-operative Planning System In Patients With Femoral Neck Fracture Undergoing Primary Total Hip Arthroplasty

Objective: To investigate the clinical effect and clinical significance of artificial intelligence pre-operative planning system in patients with femoral neck fracture undergoing primary total hip arthroplasty.Methods: The clinical data of 62 cases of femoral neck fracture treated with unilateral total hip arthroplasty from October 2018 to October 2020 were selected,Among them,31 cases used AIHIP for preoperative planning,Of which 13 were males,The average age is 67 years;18 females,The average age is 70 years;The average age of the group was 69,Fracture classification:18 cases of subhead fracture type,Both head and neck fracture 9 cases,Basal fracture type 4 cases,Patients category: 13 cases on the left hip,18 cases on the right hip;Preoperative planning was performed in 31 cases using pre-operative film template measurement,Of which 12 were males,The average age is 68 years,19 females,The average age is 67 years,The average age of the group was 68 years,Fracture classification: 17 cases of subhead fracture type,Both head and neck fracture 11 cases,Basal fracture type 3cases,Patient category: 14 cases on the left hip,Right hip 17 case.After admission,No obvious contraindication,scheduled total hip arthroplasty,Comparison of the actual type of the prosthesis in the two groups and the preoperative planning of the prosthesis matching,The operative time,bleeding volume,harris function score,visual pain simulation score VAS,were recorded The acetabular eccentricity difference,acetabular center height difference,femoral eccentricity difference and bilateral joint deviation were measured by film The difference of heart distance,the difference of length of both lower limbs and the angle of acetabular abduction were compared.Results: All the patients in both groups were followed up,no death cases and postoperative complications occurred.Gender ratio,age,height,weight,lesion side,fracture type were not statistically significant between the two groups before operation(P > 0.05).The complete coincidence rate of acetabular and femoral prostheses was 67.7%(21 / 31),61.3%(19 / 31)in the trial group,and 29.0%(9 / 31),29.0%(9 / 31)in the control group.The consistency of acetabular prostheses between the two groups is P = 0.002 and the consistency of femoral stalk prosthesis between the two groups P=0.011,Both groups were statistically significant(P < 0.05).Operation time:experimental group: 91.05 ± 21.32 min;The control group 113.95 ± 14.49 min.Differences were statistically significant(Z =-4.314,P = 0.000).Intraoperative bleeding: experimental group: 388.42 ± 100.51 ml;Control group :518.42 ± 109.56 ml.Differences were statistically significant(Z =-5.016,P = 0.000).The globe offste difference: experimental group 5.13 ±2.45 mm;Control group 6.53 ± 3.14 mm,There was no statistically significant difference,(t =-1.964,P = 0.054).Lower extremity length difference:experimental group: 3.73 ± 1.74 mm;control group: 7.54 ± 2.77 mm,the difference was statistically significant(t =-6.531,P = 0.000);the other index between two groups were not statistically significant(P > 0.05).Conclusions: Using artificial intelligence pre-operative planning system to guide total hip arthroplasty can shorten the operation time,reduce the amount of intraoperative bleeding,better restore the combined eccentricity and lower limb length,make the prosthesis implantation stable and reliable,improve the accuracy of operation,and provide a better learning method for young doctors.