A method for predicting the risk of patellofemoral pain syndrome

Abstract

The invention discloses a method for predicting the risk of patellofemoral pain syndrome, which belongs to the technical field of disease prevention. The prediction is completed by case-control experiments, and the method comprises the following steps: S1, 120 patients with patellofemoral pain syndrome are included; S2, 120 healthy sports enthusiasts are matched according to 1:1; S3, isokinetic muscle strength testing technology is performed; S4, the statistical method of conditional logistic regression is used to determine the strength index affecting the onset of patellofemoral pain syndrome, and a related equation is constructed; S5, the strength of knee extension, hip extension, hip flexion and hip adduction of susceptible people is measured, and the strength is brought into the related equation of S5, so that the risk of patellofemoral pain syndrome can be calculated. The method for predicting the risk of patellofemoral pain syndrome uses conditional logistic regression that can predict the risk of onset as a statistical method to construct a related equation, and the strength of knee extension, hip extension, hip flexion and hip adduction of susceptible people is measured, and the strength is brought into the equation to calculate the risk of patellofemoral pain syndrome.

Description

Technical Field

[0001] The present invention belongs to the technical field of disease prevention, and specifically relates to a method for predicting the risk of developing patellofemoral pain syndrome. Background Art

[0002] Patellofemoral pain syndrome (PFPS) has a high incidence, especially among sports enthusiasts, where the incidence can reach 40%, and is very easy to relapse, affecting the quality of life. However, accurate estimation of the risk of injury and disease in sports people before they develop the disease, and preventive intervention targeting risk factors can effectively reduce the incidence of the disease.

[0003] In the prior art, only the statistical method of univariate analysis (t-test) is used to obtain the clinical phenomenon that the patient's knee extensor strength (or quadriceps strength), hip extensor strength (or gluteus maximus strength), and hip abductor strength (or gluteus medius strength) are reduced compared with healthy people. However, due to the limitation of statistical methods, it is impossible to draw a conclusion on the causal relationship between the two (i.e., whether the injury is caused by the decrease in strength, or the injury causes the decrease in strength), nor is it possible to analyze the difference in the degree of influence of the decrease in the above strength on the occurrence of injuries (i.e., which kind of strength decrease is most likely to cause injuries). For lower limb muscles, knee extensor / flexor, hip extensor / flexor, and hip adduction / abduction are considered to be three pairs of antagonistic muscles. The strength of each pair of antagonistic muscles can affect each other. For example, overactive knee flexor strength may inhibit knee extensor muscle strength. Therefore, in order to establish a PFPS pathogenesis model, in addition to incorporating knee extensor, hip extensor, and hip abductor muscle strength, the respective antagonistic muscles must also be included. However, existing studies rarely consider antagonistic muscles.

[0004] To this end, we proposed a method to predict the risk of patellofemoral pain syndrome. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides a method for predicting the risk of developing patellofemoral pain syndrome to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a method for predicting the risk of patellofemoral pain syndrome, which is completed by a case-control experiment, comprising the following steps:

[0007] S1. 120 patients with patellofemoral pain syndrome were included;

[0008] S2. According to the number of patients with patellofemoral pain syndrome, 120 healthy sports enthusiasts were matched on a 1:1 basis.

[0009] S3. The knee extension / flexion, hip extension / flexion, and hip adduction / abduction strength of all subjects were measured by isokinetic strength testing technology.

[0010] S4. Use conditional logistic statistical methods to determine the muscle strength indexes that need to be statistically analyzed and construct relevant equations;

[0011] S5. By measuring the knee extension, hip extension, hip flexion and hip adduction strength of susceptible people and substituting them into the relevant equation of S5, the risk of patellofemoral pain syndrome can be calculated.

[0012] To further optimize the technical solution, in S1, the included patients with patellofemoral pain syndrome are required to be sports enthusiasts who need to exercise 2-5 times a week, each time for 30-60 minutes, and professional athletes are excluded.

[0013] To further optimize the technical solution, in S2, the matching method is to match each patient with a corresponding healthy person based on age and gender. The age requirement is within ±3 years old. The healthy person also has the same exercise habits as the patient, and the healthy person is required to have no musculoskeletal injuries in the past 6 months.

[0014] To further optimize the technical solution, in S4, the increase or decrease in knee flexion and hip abduction muscle strength has nothing to do with the occurrence of patellofemoral pain syndrome, so the above two indicators are not included in the relevant equation.

[0015] To further optimize the technical solution, in S4, the relevant equation is set to:

[0016] Y=β 1 Knee extension strength + β 2 Hip extension strength + β 3 Hip flexion strength + β 4 Hip adduction strength

[0017] Where Y is the probability of patellofemoral pain syndrome, β 1 ~β 4 is the coefficient of each indicator affecting the incidence.

[0018] To further optimize the technical solution, the probability Y of developing patellofemoral pain syndrome is <1. The larger the absolute value of the indicator coefficient, the greater the influence of the corresponding indicator on the onset of patellofemoral pain syndrome. A positive coefficient means that the greater the force, the higher the risk of disease. A negative coefficient means that the greater the force, the lower the risk.

[0019] Compared with the prior art, the present invention provides a method for predicting the risk of patellofemoral pain syndrome, which has the following beneficial effects:

[0020] This method for predicting the risk of patellofemoral pain syndrome uses conditional logistic regression as a statistical method to predict the risk of disease. This method has high requirements on the number of cases, and previous studies often did not meet the minimum sample size requirement. At the same time, three pairs of six strengths, namely knee extension / flexion, hip extension / flexion, and hip adduction / abduction, were analyzed to construct a related equation. By measuring the knee extension, hip extension, hip flexion, and hip adduction strength of susceptible people and substituting them into the equation, their risk of disease can be calculated. DETAILED DESCRIPTION

[0021] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Embodiment 1:

[0023] A method for predicting the risk of developing patellofemoral pain syndrome, performed by a case-control trial, comprises the following steps:

[0024] S1. 120 patients with patellofemoral pain syndrome were included;

[0025] S2. According to the number of patients with patellofemoral pain syndrome, 120 healthy sports enthusiasts were matched on a 1:1 basis.

[0026] S3. The knee extension / flexion, hip extension / flexion, and hip adduction / abduction strength of all subjects were measured by isokinetic strength testing technology.

[0027] S4. Use the statistical method of conditional logistic regression to determine the force index that affects the onset of patellofemoral pain syndrome and construct the relevant equation;

[0028] S5. By measuring the knee extension, hip extension, hip flexion and hip adduction strength of susceptible people and substituting them into the relevant equation of S5, the risk of patellofemoral pain syndrome can be calculated.

[0029] Specifically, in S1, the included patients with patellofemoral pain syndrome are required to be sports enthusiasts who need to exercise 2-5 times a week, each time for 30-60 minutes, and professional athletes are excluded.

[0030] Specifically, in S2, the matching method is to match each patient with a corresponding healthy person based on age and gender. The age requirement is within ±3 years. The healthy person also has the same exercise habits as the patient, and the healthy person is required not to have any musculoskeletal injuries in the past 6 months.

[0031] Specifically, in S4, the increase or decrease in knee flexion and hip abduction muscle strength has nothing to do with the occurrence of patellofemoral pain syndrome, so the above two indicators are not included in the relevant equation.

[0032] Specifically, in S4, the relevant equation is set as:

[0033] Y=β 1 Knee extension strength + β 2 Hip extension strength + β 3 Hip flexion strength + β 4 Hip adduction strength

[0034] Where Y is the probability of patellofemoral pain syndrome, β 1 ~β 4 is the coefficient of each indicator affecting the incidence.

[0035] Specifically, the probability Y of developing patellofemoral pain syndrome is less than 1. The larger the absolute value of the indicator coefficient, the greater the influence of the corresponding indicator on the onset of patellofemoral pain syndrome. A positive coefficient means that the greater the force, the higher the risk of disease. A negative coefficient means that the greater the force, the lower the risk.

[0036] Embodiment 2:

[0037] A method for predicting the risk of developing patellofemoral pain syndrome, performed by a case-control trial, comprises the following steps:

[0038] S1. 140 patients with patellofemoral pain syndrome were included;

[0039] S2. According to the number of patients with patellofemoral pain syndrome, 140 healthy sports enthusiasts were matched on a 1:1 basis.

[0040] S3. The knee extension / flexion, hip extension / flexion, and hip adduction / abduction strength of all subjects were measured by isokinetic strength testing technology.

[0041] S4. Use the statistical method of conditional logistic regression to determine the force index that affects the onset of patellofemoral pain syndrome and construct the relevant equation;

[0042] S5. By measuring the knee extension, hip extension, hip flexion and hip adduction strength of susceptible people and substituting them into the relevant equation of S5, the risk of patellofemoral pain syndrome can be calculated.

[0043] Specifically, in S1, the included patients with patellofemoral pain syndrome are required to be sports enthusiasts who need to exercise 2-5 times a week, each time for 30-60 minutes, and professional athletes are excluded.

[0044] Specifically, in S2, the matching method is to match each patient with a corresponding healthy person based on age and gender. The age requirement is within ±3 years. The healthy person also has the same exercise habits as the patient, and the healthy person is required not to have any musculoskeletal injuries in the past 6 months.

[0045] Specifically, in S4, the increase or decrease in knee flexion and hip abduction muscle strength has nothing to do with the occurrence of patellofemoral pain syndrome, so the above two indicators are not included in the relevant equation.

[0046] Specifically, in S4, the relevant equation is set as:

[0047] Y=β 1 Knee extension strength + β 2 Hip extension strength + β 3 Hip flexion strength + β 4 Hip adduction strength

[0048] Where Y is the probability of patellofemoral pain syndrome, β 1 ~β 4 is the coefficient of each indicator affecting the incidence.

[0049] Specifically, the probability Y of developing patellofemoral pain syndrome is less than 1. The larger the absolute value of the indicator coefficient, the greater the influence of the corresponding indicator on the onset of patellofemoral pain syndrome. A positive coefficient means that the greater the force, the higher the risk of disease. A negative coefficient means that the greater the force, the lower the risk.

[0050] Embodiment three:

[0051] A method for predicting the risk of developing patellofemoral pain syndrome, performed by a case-control trial, comprises the following steps:

[0052] S1. 100 patients with patellofemoral pain syndrome were included;

[0053] S2. According to the number of patients with patellofemoral pain syndrome, 100 healthy sports enthusiasts were matched at a 1:1 ratio;

[0054] S3. The knee extension / flexion, hip extension / flexion, and hip adduction / abduction strength of all subjects were measured by isokinetic strength testing technology.

[0055] S4. Use the statistical method of conditional logistic regression to determine the force index that affects the onset of patellofemoral pain syndrome and construct the relevant equation;

[0056] S5. By measuring the knee extension, hip extension, hip flexion and hip adduction strength of susceptible people and substituting them into the relevant equation of S5, the risk of patellofemoral pain syndrome can be calculated.

[0057] Specifically, in S1, the included patients with patellofemoral pain syndrome are required to be sports enthusiasts who need to exercise 2-5 times a week, each time for 30-60 minutes, and professional athletes are excluded.

[0058] Specifically, in S2, the matching method is to match each patient with a corresponding healthy person based on age and gender. The age requirement is within ±3 years. The healthy person also has the same exercise habits as the patient, and the healthy person is required not to have any musculoskeletal injuries in the past 6 months.

[0059] Specifically, in S4, the increase or decrease in knee flexion and hip abduction muscle strength has nothing to do with the occurrence of patellofemoral pain syndrome, so the above two indicators are not included in the relevant equation.

[0060] Specifically, in S4, the relevant equation is set as:

[0061] Y=β 1 Knee extension strength + β 2 Hip extension strength + β 3 Hip flexion strength + β 4 Hip adduction strength

[0062] Where Y is the probability of patellofemoral pain syndrome, β 1 ~β 4 is the coefficient of each indicator affecting the incidence.

[0063] Specifically, the probability Y of developing patellofemoral pain syndrome is less than 1. The larger the absolute value of the indicator coefficient, the greater the influence of the corresponding indicator on the onset of patellofemoral pain syndrome. A positive coefficient means that the greater the force, the higher the risk of disease. A negative coefficient means that the greater the force, the lower the risk.

[0064] The beneficial effect of the present invention is that the method for predicting the risk of patellofemoral pain syndrome can predict the risk of patellofemoral pain syndrome by using conditional logistic regression as a statistical method. The method has high requirements on the number of cases, and previous studies often do not meet the minimum sample size requirement. At the same time, three pairs of six strengths, namely knee extension / knee flexion, hip extension / hip flexion, and hip adduction / hip abduction, are analyzed, and a related equation is constructed. By measuring the knee extension, hip extension, hip flexion, and hip adduction strength of susceptible people and substituting them into the equation, the risk of the disease can be calculated.

[0065] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for predicting the risk of patellofemoral pain syndrome, wherein the prediction is performed by a case-control trial, characterized in that: The following steps are involved: S1. 120 patients with patellofemoral pain syndrome were included; S2. According to the number of patients with patellofemoral pain syndrome, 120 healthy sports enthusiasts were matched on a 1:1 basis. The matching method is to match each patient with a corresponding healthy person based on age and gender. The age requirement is within ±3 years. The healthy person also has the same exercise habits as the patient and does not have any musculoskeletal injuries in the past 6 months. S3. The knee extension / flexion, hip extension / flexion, and hip adduction / abduction strength of all subjects were measured by isokinetic strength testing techniques. S4. Use conditional logistic statistical methods to determine the force indexes that affect the onset of patellofemoral pain syndrome and construct relevant equations; The increase or decrease of knee flexion and hip abduction muscle strength has nothing to do with the occurrence of patellofemoral pain syndrome, so the above two indicators are not included in the relevant equation; S5, the relevant equation is set as: Y=β1 knee extension strength + β2 hip extension strength + β3 hip flexion strength + β4 hip adduction strength Where Y is the probability of patellofemoral pain syndrome, β 1～ β4 is the coefficient of each indicator affecting the incidence; The probability Y of patellofemoral pain syndrome is less than 1. The greater the absolute value of the index coefficient, the greater the influence of the corresponding index on the onset of patellofemoral pain syndrome. A positive coefficient means that the greater the force, the higher the risk of disease, and a negative coefficient means that the greater the force, the lower the risk; S6. By measuring the knee extension, hip extension, hip flexion and hip adduction strength of susceptible people and substituting them into the relevant equation of S5, the risk of patellofemoral pain syndrome can be calculated.

2. A method for predicting the risk of patellofemoral pain syndrome according to claim 1, characterized in that: In S1, the included patients with patellofemoral pain syndrome are required to be sports enthusiasts who need to exercise 2-5 times a week, each time for 30-60 minutes, and professional athletes are excluded.