Method and system for predicting whether perineum is cut open or not during delivery and application of method and system

Abstract

The invention provides a method and system for predicting whether perineum is cut open or not during delivery and application of the method and system, and belongs to the technical field of medicine. The invention provides a method for predicting whether perineum is cut open or not during delivery. The method comprises the following steps: acquiring parameter assignment of an individual; substituting into a prediction model for calculation; if P is larger than or equal to 0.330, the perineum needs to be cut open; if P is less than 0.330, the perineum does not need to be cut open. According to the invention, through multi-factor Logistic regression analysis, perineotomy decision influence factors except confounding factors are objectively eliminated, and the perineotomy prediction method and system during delivery are formed. The invention also establishes a perineal incision decision-making auxiliary system during delivery, the system is convenient and rapid to use and simple to apply, calculation is not needed, recommended suggestions can be rapidly obtained only by checking risk factors, and effective working reference is provided for the midwife to select perineal protection modes before the midwife goes to a platform for midwifery.

Description

Technical Field

[0001] The present invention belongs to the field of medical technology, and in particular relates to a method and system for predicting whether episiotomy is performed during childbirth and application thereof. Background Art

[0002] Episiotomy (EP) is a surgical procedure performed during childbirth to widen the vaginal opening. In emergencies such as shoulder dystocia, fetal distress, and forceps delivery, timely and appropriate episiotomy can reduce the obstruction of the perineum to the fetal head and widen the vaginal outlet. However, routine episiotomy (ROE) may bring a series of short-term and long-term effects to the parturient, including severe perineal lacerations, postpartum pain, infection, bleeding, and impact on sexual life.

[0003] In the past, it was believed that episiotomy could expand the birth canal outlet, speed up the delivery process, and prevent third- and fourth-degree perineal lacerations. However, more and more studies have found that episiotomy is not a protective factor for severe perineal lacerations, and may even increase a series of birth canal injuries, including perineal lacerations, incision edema, and anal sphincter injury, to a certain extent. At the same time, episiotomy itself is a serious trauma for parturients. Episiotomy can directly damage pelvic floor tissues, including skin, vaginal mucosa, labia frenulum, bulbospongiosus muscle, superficial transverse perineal muscle, and even part of the deep transverse perineal muscle. More tissues are cut, the tension is greater, the suture time is longer, and the blood vessels cannot be avoided during the incision, resulting in more bleeding. In addition, the perineal incision is close to the urethra and anus, and the removal of postpartum lochia, if postpartum care is not appropriate, it is very easy to cause incision infection. If the incision infection is not well handled, it is easy to cause repeated infection. In severe cases, abscesses and fistulas may even form, which brings great trouble to the daily life of parturients and seriously affects their physical and mental health.

[0004] Although routine episiotomy is not recommended, it is still necessary to perform episiotomy restrictively when necessary and after full evaluation. Restrictive episiotomy (REE) refers to avoiding unnecessary episiotomy as much as possible during head-presenting delivery to reduce perineal injury and maintain the integrity of the perineum to the greatest extent. It is also called selective episiotomy. However, the implementation of restrictive episiotomy does not mean that all parturients should blindly choose perineal protection and cannot perform episiotomy. Instead, it means that midwives should conduct a full, careful, and dynamic assessment of the mother and child during delivery to determine whether the parturient has an indication for episiotomy. After weighing the pros and cons, they should decide whether to perform episiotomy to minimize the risk of severe perineal lacerations, better maintain the integrity of the perineum, and reduce perineal injury, sutures, and postpartum complications.

[0005] Although restrictive episiotomy has more benefits than conventional episiotomy, the current episiotomy rate remains high. In many hospitals, episiotomy has almost become a routine in natural childbirth. The reason for this phenomenon is not only related to the traditional concepts of some medical institutions and medical staff, but more importantly, it is due to the lack of corresponding evaluation and judgment indicators. Clinical midwives lack the basis for perineal protection methods. At present, there is no gold standard for episiotomy indications in this field. Women with relative episiotomy indications such as forceps delivery, fetal distress, and shoulder dystocia only account for a small part of all women who undergo episiotomy. Most of the women who undergo episiotomy are often midwives who choose protective episiotomy to avoid severe perineal lacerations. There is a lack of clear episiotomy indications. As the main decision maker of perineal protection methods, midwives often rely on their own experience and judgment to choose the corresponding perineal protection method since the implementation of restrictive episiotomy. However, in clinical work, each midwife has different understandings and experiences, and it is difficult to form a unified standard. In addition, during the teaching process of young midwives, their own experience is difficult to directly transform into text or teaching plans, which is not as easy to impart as quantitative indicators, and the formation of experience requires the accumulation of long-term practice. This also leads to the inability of young midwives to quickly master the decision-making method of choosing the perineal protection method, which causes troubles in their clinical work.

[0006] The key point of restrictive episiotomy is to select the most appropriate perineal protection method through adequate evaluation, while ensuring the safety of mother and baby, and reducing episiotomy as much as possible. In recent years, more and more scholars have paid attention to the important role of evaluation during delivery in the decision-making of perineal protection methods. Related studies have also increased, and many reports have shown that it can improve the integrity of the perineum, effectively reduce the episiotomy rate, and have a positive impact on the delivery outcomes of parturients. However, in general, there are still problems in its use, such as insufficient objectivity of the evaluation content, unreasonable score setting, and relatively complicated use. Specifically, for example, (1) the item setting of the scoring table and indication table is defective: the summary classification mainly includes the following five aspects: ① not choosing 30° episiotomy; ② episiotomy should not be performed frequently for premature delivery; ③ the probability of episiotomy is high in abnormal fetal position; ④ median episiotomy must meet specific conditions; ⑤ there are too many indications for 45° episiotomy. (2) The score distribution of the scoring table is unreasonable: In the evaluation of the existing system, the proportion of perineal conditions is still relatively small, which means that women with poor perineal conditions may have a higher overall score due to other factors such as perineal protection intention and labor force, and are therefore included in the group of people who do not need perineal incision. However, in actual operation, due to the limitations of perineal conditions, some midwives are unable to implement perineal protection for women according to the perineal protection method recommended in the indication table. (3) It is not convenient to use overall: childbirth is an ever-changing process. With the extension of labor time and the continuous descent of the fetal head, the comprehensive conditions of the parturient will continue to change, especially the changes in perineal conditions. Therefore, the assessment of perineal conditions can only be carried out before delivery. In the short time before going on stage to deliver the baby, the midwife needs to complete the assessment of the relevant items in the scoring table, then add up the scores of all items to get the total score, and then match the total score to the indication table, and finally choose the appropriate perineal protection method according to the recommendation of the indication table. Such cumbersome operations make the entire evaluation process very hasty, and sometimes there is not enough time to conduct a full evaluation, which greatly reduces the effectiveness of the system. The reason for this result may be related to the formation process of the system. Most of the existing systems are formed through multiple rounds of expert group discussions, so it is difficult to avoid a certain degree of expert subjectivity. Therefore, this field urgently needs a simple and objective evaluation method that conforms to the existing clinical workflow to help clinical midwives make decisions on perineal protection methods. Summary of the invention

[0007] In view of this, one of the purposes of the present invention is to provide a simple, objective and accurate method for predicting whether episiotomy is performed during childbirth.

[0008] A second object of the present invention is to provide a system for evaluating whether a perineum incision is required during childbirth, which can quickly, accurately and objectively evaluate whether a perineum incision is required during childbirth.

[0009] The third purpose of the present invention is to provide an episiotomy decision support system during delivery, which is simpler than the prediction model and does not require calculation. Recommendations can be quickly obtained by simply checking risk factors, providing an effective working reference for midwives to choose perineal protection methods before going on stage to assist in delivery.

[0010] In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions:

[0011] The present invention provides a method for predicting whether episiotomy is performed during childbirth, comprising the following steps:

[0012] Obtain individual parameter assignments: the parameters include good perineum elasticity, poor perineum elasticity, whether the perineum is edematous, whether the vagina is lacerated, and whether macrosomia is estimated; the assignment method of good perineum elasticity is: 1 for good perineum elasticity, 0 for general or poor perineum elasticity; the assignment method of poor perineum elasticity is: 1 for poor perineum elasticity, 0 for general or good perineum elasticity; the assignment method of whether the perineum is edematous is: 1 for edema, 0 for no edema; the assignment method of whether the vagina is lacerated is: 1 for laceration, 0 for no laceration; the assignment method of whether macrosomia is estimated is: 1 for macrosomia, 0 for not macrosomia;

[0013] Substitute the obtained parameter assignment results into the prediction model for calculation: the prediction model is P = 1 / (1 + y), where y = exp{-(-3.193 good perineum elasticity + 4.386 poor perineum elasticity + 1.725 perineum edema + 1.542 vaginal laceration + 6.243 estimated macrosomia - 0.744)};

[0014] The calculated results were used to predict whether episiotomy was required during delivery: if P ≥ 0.330, episiotomy was required; if P < 0.330, episiotomy was not required.

[0015] The present invention also provides application of the method in preparing a product for evaluating whether perineum incision is performed during childbirth.

[0016] The present invention also provides a system for evaluating whether perineum is incised during childbirth, the system comprising a data input module, a data calculation module and an output module; the data input module comprises the following input submodules: a good perineum elasticity module, a poor perineum elasticity module, a perineum edema module, a vaginal laceration module and an estimated macrosomia module; the data calculation module substitutes the input value of the data input module into a prediction model for calculation, the prediction model is P=1 / (1+y), wherein y=exp{-(-3.193 good perineum elasticity+4.386 poor perineum elasticity+1.725 perineum edema+1.542 vaginal laceration+6.243 estimated macrosomia-0.744)}; the output module compares the P value obtained by the data calculation module with 0.330, if P≥0.330, then outputs that perineum incision is required; if P<0.330, then outputs that perineum incision is not required.

[0017] Preferably, the value assignment method of the module with good perineum elasticity is: 1 if the perineum elasticity is good, and 0 if the perineum elasticity is average or poor; the value assignment method of the module with poor perineum elasticity is: 1 if the perineum elasticity is poor, and 0 if the perineum elasticity is average or good; the value assignment method of the module with perineum edema is: 1 if yes, and 0 if no; the value assignment method of the module with vaginal laceration is: 1 if yes, and 0 if no; the value assignment method of the module with estimated macrosomia is: 1 if yes, and 0 if no.

[0018] The present invention also provides a decision support system for episiotomy during childbirth, the support system comprising an influencing factor module and an analysis output module;

[0019] The influencing factor module is composed of a protective factor module and a risk factor module; the protective factor module includes a good perineum elasticity unit; the risk factor module is composed of a medium-risk factor submodule and a high-risk factor submodule, the medium-risk factor submodule includes a perineal edema unit and a vaginal laceration unit, and the high-risk factor submodule includes an estimated macrosomia unit and a poor perineum elasticity unit;

[0020] The operation standard of the analysis output module is: when the protective factor module is not checked and any unit in the risk factor module is checked, "episiotomy" is output; when the risk factor module is not checked, regardless of whether the protective factor module is checked, "no need for episiotomy" is output; when the protective factor module is checked, if one unit in the medium-risk factor submodule is checked, "no need for episiotomy" is output; if more than one unit in the medium-risk factor submodule is checked, "episiotomy" is output; when any unit in the high-risk factor submodule is checked, "episiotomy" is output regardless of whether the protective factor module is checked.

[0021] Preferably, the criterion for judging the elasticity of the perineum is as follows: when the fetal head is exposed for 3 to 4 cm, the index finger and the middle finger are inserted between the perineum and the fetal presenting part, and the perineal tissue is pulled outward to evaluate the elasticity of the perineum: if two fingers can be inserted, and the fingers can prop up the perineal skin outward by at least 1 to 2 cm, and the skin color is normal when propped up, without paleness, small cracks in the skin, and without bleeding or tearing of the hymen or vaginal mucosa, then the perineum is judged to be elastic; if only one finger can be inserted, or if two fingers can be inserted but there is no extra space, the fingers cannot prop up the perineal skin, or there is already vaginal mucosal laceration and bleeding, then the perineum is judged to be elastic. If the perineum skin is shiny, pale, and there are fine thread-like cracks on the epidermis, it is judged that the elasticity of the perineum is poor; perineal elasticity generally refers to the elasticity of the perineum being between good and poor; the criteria for judging perineal edema are: perineal edema that occurs in the second stage of labor or before the midwife comes on stage to assist in the delivery, including edema of the perineum, labia majora and minora, and anterior vaginal wall; the criteria for judging vaginal laceration are: laceration of the inner wall of the vagina that already exists in the second stage of labor or before the midwife comes on stage to assist in the delivery; the criteria for estimating macrosomia are: the fetal weight may exceed 4000g based on maternal B-ultrasound, uterine height and abdominal circumference, or four-part palpation method before going on stage to assist in the delivery.

[0022] Preferably, the episiotomy is an episiotomy with an incision angle of 45° to 60°.

[0023] Beneficial effects of the present invention:

[0024] The present invention eliminates the influence of the subjective will of individual researchers and research teams through multi-factor Logistic regression analysis, obtains objective influencing factors of midwives' episiotomy decision-making excluding confounding factors, and forms a method and system for predicting episiotomy decision-making during delivery.

[0025] The present invention establishes an episiotomy decision-making support system during childbirth based on the episiotomy decision-making prediction method and system during childbirth. The system is convenient, fast and simple to apply. It has only 4 influencing factors, clear items, lists the measurement and judgment criteria of the influencing factors, and gives recommendations. The episiotomy decision-making support system provided by the present invention is more objective than the previous perineum assessment system, and is simpler than the original prediction method and system. It does not require calculation, and only requires simple risk factor selection to quickly obtain recommendations, which provides an effective work reference for midwives to choose perineum protection methods before going on stage to assist in childbirth.

[0026] The present invention has a significant application effect and can reduce the episiotomy rate without increasing the severe perineal laceration rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 Schematic diagram of a system for assessing whether an episiotomy was performed during childbirth;

[0028] Figure 2 Decision tree diagram for episiotomy during childbirth;

[0029] Figure 3 Schematic diagram of the episiotomy decision support system during delivery. DETAILED DESCRIPTION

[0030] The present invention provides a method for predicting whether episiotomy is performed during childbirth, comprising the following steps:

[0031] Obtain individual parameter assignments: the parameters include good perineum elasticity, poor perineum elasticity, whether the perineum is edematous, whether the vagina is lacerated, and whether macrosomia is estimated; the assignment method of good perineum elasticity is: 1 for good perineum elasticity, 0 for general or poor perineum elasticity; the assignment method of poor perineum elasticity is: 1 for poor perineum elasticity, 0 for general or good perineum elasticity; the assignment method of whether the perineum is edematous is: 1 for edema, 0 for no edema; the assignment method of whether the vagina is lacerated is: 1 for laceration, 0 for no laceration; the assignment method of whether macrosomia is estimated is: 1 for macrosomia, 0 for not macrosomia;

[0032] Substitute the obtained parameter assignment results into the prediction model for calculation: the prediction model is P = 1 / (1 + y), where y = exp{-(-3.193 good perineum elasticity + 4.386 poor perineum elasticity + 1.725 perineum edema + 1.542 vaginal laceration + 6.243 estimated macrosomia - 0.744)};

[0033] The calculated results were used to predict whether episiotomy was required during delivery: if P ≥ 0.330, episiotomy was required; if P < 0.330, episiotomy was not required.

[0034] In the present invention, the evaluation standard of perineal elasticity is: when the fetal head is exposed 3-4cm, insert the index finger and the middle finger between the perineum and the fetal presenting part, and pull the perineal tissue outward to evaluate the elasticity of the perineum: if two fingers can be inserted, and the fingers can prop up the perineal skin outward by at least 1-2cm, and the skin color is normal when propped up, there is no paleness, no small skin cracks, no bleeding and tearing of the hymen and vaginal mucosa, then it is judged that the perineum elasticity is good; if only one finger can be inserted, or although two fingers can be inserted, there is no extra space, the fingers cannot prop up the perineal skin, or there is vaginal mucosal laceration and bleeding, the perineal skin is shiny, pale, and the epidermis has filamentous cracks, then it is judged that the perineum elasticity is poor; perineal elasticity generally refers to the perineum elasticity between good and poor. In the present invention, perineal edema refers to the perineal edema that occurs in the second stage of labor or before the midwife comes on stage to assist in delivery, including edema of the perineum, labia majora and minora, and the anterior wall of the vagina. In the present invention, vaginal laceration refers to vaginal laceration that already exists in the second stage of labor or before the midwife goes on stage to assist in the delivery. In the present invention, estimated macrosomia refers to the fetal weight estimated to be more than 4000g based on maternal B-ultrasound, uterine height and abdominal circumference or four-part palpation method before going on stage.

[0035] The present invention also provides application of the prediction method in preparing a product for evaluating whether episiotomy is performed during childbirth.

[0036] The present invention also provides a system for evaluating whether the perineum is incised during childbirth, the system comprising a data input module, a data calculation module and an output module; the data input module comprises the following input submodules: a perineum elasticity good module, a perineum elasticity poor module, a perineum edema module, a vaginal laceration module and a macrosomia estimation module;

[0037] The data calculation module substitutes the input value of the data input module into the prediction model for calculation, and the prediction model is P=1 / (1+y), where y=exp{-(-3.193 good perineum elasticity+4.386 poor perineum elasticity+1.725 perineum edema+1.542 vaginal laceration+6.243 estimated macrosomia-0.744)};

[0038] The output module compares the P value obtained by the data calculation module with 0.330, and if P≥0.330, outputs that episiotomy is needed; if P<0.330, outputs that episiotomy is not needed.

[0039] The schematic diagram of the system for evaluating whether episiotomy is performed during childbirth provided by the present invention is as follows: Figure 1In the system of the present invention, the value assignment method of the module of good perineum elasticity is: if the perineum elasticity is good, it is 1, and if the perineum elasticity is general or poor, it is 0; the value assignment method of the module of poor perineum elasticity is: if the perineum elasticity is poor, it is 1, and if the perineum elasticity is general or good, it is 0; the value assignment method of the module of perineum edema is: if yes, it is 1, and if no, it is 0; the value assignment method of the module of vaginal laceration is: if yes, it is 1, and if no, it is 0; the value assignment method of the module of estimating macrosomia is: if yes, it is 1, and if no, it is 0.

[0040] The present invention also provides a decision support system for episiotomy during childbirth, the support system comprising an influencing factor module and an analysis output module;

[0041] The influencing factor module is composed of a protective factor module and a risk factor module; the protective factor module includes a good perineum elasticity unit; the risk factor module is composed of a medium-risk factor submodule and a high-risk factor submodule, the medium-risk factor submodule includes a perineal edema unit and a vaginal laceration unit, and the high-risk factor submodule includes an estimated macrosomia unit and a poor perineum elasticity unit;

[0042] The operation standard of the analysis output module is: when the protective factor module is not checked and any unit in the risk factor module is checked, "episiotomy" is output; when the risk factor module is not checked, regardless of whether the protective factor module is checked, "no need for episiotomy" is output; when the protective factor module is checked, if one unit in the medium-risk factor submodule is checked, "no need for episiotomy" is output; if more than one unit in the medium-risk factor submodule is checked, "episiotomy" is output; when any unit in the high-risk factor submodule is checked, "episiotomy" is output regardless of whether the protective factor module is checked.

[0043] The schematic diagram of the episiotomy decision support system during childbirth provided by the present invention is as follows Figure 3 As shown. In the perineal incision decision-making support system of the present invention, the criterion for judging perineal elasticity is: when the fetal head is exposed 3 to 4 cm, insert the index finger and the middle finger between the perineum and the fetal presenting part, and pull the perineal tissue outward to evaluate the elasticity of the perineum: if two fingers can be inserted, and the fingers can prop up the perineal skin outward by at least 1 to 2 cm, and the skin color is normal when propped up, there is no paleness, no small skin cracks, and no bleeding or tearing of the hymen or vaginal mucosa, then the perineum is judged to be good in elasticity; if only one finger can be inserted, or if two fingers can be inserted but there is no extra space, the fingers cannot prop up the perineal skin, or there is already vaginal mucosal laceration and bleeding, the perineal skin is shiny and pale, and fine thread-like cracks appear on the epidermis, then the perineum is judged to be poor in elasticity; perineal elasticity generally refers to the perineum elasticity being between good and poor;

[0044] The criteria for perineal edema are: perineal edema that occurs during the second stage of labor or before the midwife comes on stage to assist in delivery, including edema of the perineum, labia majora and minora, and anterior vaginal wall;

[0045] The criteria for determining vaginal lacerations are: vaginal lacerations that already existed during the second stage of labor or before the midwife came on stage to assist in the birth;

[0046] The criteria for determining macrosomia are: before going on stage, it is estimated that the fetal weight may exceed 4000g based on maternal B-ultrasound, uterine height and abdominal circumference or four-part palpation method.

[0047] In the present invention, the condition of normal perineal elasticity is included in the auxiliary system, and the condition of normal perineal elasticity is the condition where the protective factor does not exist. In the perineal incision decision auxiliary system of the present invention, the perineal incision is selected as episiotomy, and the incision angle is preferably 45° to 60°.

[0048] The technical solutions provided by the present invention are described in detail below in conjunction with the embodiments, but they should not be construed as limiting the protection scope of the present invention.

[0049] In the following embodiments, unless otherwise specified, all of them are conventional methods.

[0050] Unless otherwise specified, the materials and reagents used in the following examples can be obtained from commercial sources.

[0051] Example 1

[0052] Model Construction

[0053] (1) Research subjects

[0054] Parturients who gave birth at the research site from April to August 2018 and met the inclusion criteria were selected. A total of 685 parturients were included, including 667 primiparas (97.37%), 18 vaginal deliveries by cesarean section, aged 17-41 (27.79±4.284) years, gestational age 201-292 (275.74±9.617) days, neonatal weight 1250-4700 (3333.55±428.575) g, and total labor time 45-2090 (592.92±327.195) min. 80% of all 685 research subjects were used as modeling subjects, a total of 548 subjects.

[0055] (2) Univariate analysis

[0056] Taking whether episiotomy was performed as the dependent variable, all influencing factors were analyzed with the dependent variable one by one, and significant variables were screened for multivariate analysis. To avoid missing important factors, the inclusion standard selected for univariate analysis was P ≤ 0.1. A total of 14 influencing factors were included, including perineal length (P<0.001), perineal elasticity (P<0.001), perineal color (P<0.001), perineal thickness (P<0.001), perineal edema (P<0.001), perineal skin laceration (P=0.006), hymen laceration (P=0.045), vaginal laceration (P<0.001), estimated fetal size (P<0.001), fetal position (P<0.001), maternal cooperation (P<0.001), uterine contraction (P<0.001), epidural analgesia (P=0.026) and second stage of labor time (P=0.007); one influencing factor, maternal age (P=0.317), was excluded.

[0057] (3) Multivariate Logistic Regression Analysis and Model Establishment

[0058] A. Basic Tests of the Model

[0059] Binary logistic regression was used to evaluate the effects of 14 factors, including perineal length, perineal elasticity, perineal color, perineal thickness, perineal edema, perineal skin laceration, hymen laceration, vaginal laceration, estimated macrosomia, abnormal fetal position, maternal cooperation, maternal uterine contraction, maternal epidural analgesia use, and maternal second stage of labor, on whether midwives chose episiotomy during delivery. The Box-Tidwell method was used to test the linear relationship between the continuous independent variable (second stage of labor) and the logit-transformed value of the dependent variable (episiotomy). In the diagnosis of collinearity between independent variables, no independent variables with tolerance less than 0.1 or variance inflation factor (VIF) greater than 10 were found, so it can be inferred that there is no collinearity between the independent variables. Among the 548 included observations, 15 observations had studentized residuals greater than 2 times the standard deviation, so they were eliminated in the subsequent analysis, and 533 observations were finally included.

[0060] B. Theoretical predictive power of the model

[0061] The Logistic model X obtained by the present invention 2=8.429, P=0.004, less than 0.05 significance level, indicating that the model is statistically significant. When there is no independent variable, the model can correctly classify 55.3% of the observations. When the independent variable is included, the model can correctly classify 86.1% of the observations, proving that the inclusion of independent variables can improve the predictive ability of the model. The sensitivity of the model is 76.1%, the specificity is 94.2%, the positive predictive value is 91.4%, and the negative predictive value is 83.0%, see Table 1. Among them, sensitivity refers to the people who are predicted to be positive and actually positive, which refers to the people who are predicted to be incised and actually incised: 181 / (57+181)=0.7605. Specificity refers to the people who are predicted to be negative and actually negative, which refers to the people who are predicted to be not incised and actually not incised: 278 / (17+278)=0.942. The positive predictive value refers to the number of people predicted to be positive among all positive people, here refers to the number of people predicted to be cut among all incision people: 181 / (17+181)=0.914. The negative predictive value refers to the number of people predicted to be negative among all negative people, here refers to the number of people predicted to be not cut among all non-incision people: 278 / (278+57)=0.8298.

[0062] Table 1 Theoretical prediction ability of the model

[0063]

[0064] Note: Cutting value is 0.500

[0065] C. Results of multivariate logistic regression analysis

[0066] With P < 0.05 as the inclusion criterion, the results of multivariate logistic regression analysis showed that perineal elasticity (X2), perineal edema (X5), vaginal laceration (X8) and estimated macrosomia (X9) were independent influencing factors affecting midwives' choice of perineal protection method (see Table 2).

[0067] Table 2 Logistic regression analysis results for predicting episiotomy in parturients

[0068]

[0069]

[0070] D. Establishing the regression equation

[0071] Taking whether episiotomy will be performed as the dependent variable, the above multivariate logistic regression analysis took the factors that affect episiotomy (perineal elasticity, perineal edema, vaginal laceration, and estimated macrosomia) as independent variables, and the regression equation was as follows:

[0072]

[0073] Good perineum elasticity +4.386 Poor perineum elasticity +1.725 Perineum edema +1.542 Vaginal laceration +6.243 Estimated macrosomia

[0074] The assignment principle of the above regression equation is as follows: P is the probability of episiotomy; α is the constant term; β m is the regression coefficient; X m Assignment of risk factors: ① When the risk factor is a binary variable (this model includes perineal edema, vaginal laceration and estimated macrosomia), when the risk factor exists, X m =1; when the risk factor does not exist, X m =0. ② When the risk factor is an unordered multi-classification variable (perineum elasticity in this model), a dummy variable is used for processing, that is, when a dummy variable exists, X m =1; when this dummy variable does not exist, X m =0.

[0075] E. Build a prediction probability model

[0076] According to the above regression equation, the clinical episiotomy probability prediction model (P) can be obtained as follows: P = 1 / (1+y), where y = exp{-(-0.744-3.193X 2-1 +4.386X 2-2 +1.725X5+1.542X8+6.243X9)}=exp{-(-3.193 good perineum elasticity+4.386 poor perineum elasticity+1.725 perineum edema+1.542 vaginal laceration+6.243 estimated macrosomia-0.744)}.

[0077] The values ​​assigned by the above prediction probability model are: the value for good perineum elasticity is 1 if the perineum elasticity is good, and 0 if the perineum elasticity is average or poor; the value for poor perineum elasticity is 1 if the perineum elasticity is poor, and 0 if the perineum elasticity is average or good; the value for the presence of perineal edema is 1, and 0 if the perineum edema is not present; the value for the presence of vaginal laceration is 1, and 0 if the vaginal laceration is not present; the value for estimated macrosomia is 1, and 0 if the fetus is not estimated to be macrosomia.

[0078] The evaluation criteria for perineal elasticity in the above prediction model are as follows: when the fetal head is exposed 3 to 4 cm, insert the index and middle fingers between the perineum and the fetal presenting part, and pull the perineal tissue outward to evaluate the elasticity of the perineum: if two fingers can be inserted, and the fingers can prop up the perineal skin at least 1 to 2 cm, and the skin color is normal when propped up, there is no paleness, no small skin cracks, and no bleeding and tearing of the hymen or vaginal mucosa, then the perineum is judged to be good elasticity; if only one finger can be inserted, or if two fingers can be inserted, but there is no extra space, the fingers cannot prop up the perineal skin, or there is vaginal mucosal laceration and bleeding, the perineal skin is shiny, pale, and there are filamentous cracks on the epidermis, then the perineum is judged to be poor elasticity; perineal elasticity generally refers to the perineum elasticity between good and poor. Perineal edema refers to perineal edema that occurs in the second stage of labor or before the midwife comes on stage to assist in delivery, including edema of the perineum, labia majora and minora, and the anterior wall of the vagina. Vaginal laceration refers to a laceration of the vaginal wall that already exists during the second stage of labor or before the midwife goes on stage to assist. Estimated macrosomia refers to an estimate of the fetal weight that may exceed 4000g based on maternal B-ultrasound, uterine height and abdominal circumference, or four-part palpation before going on stage.

[0079] (4) Efficacy test of episiotomy risk assessment prediction model

[0080] The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the predictive ability of each scoring method. The predicted probability of episiotomy was calculated according to the regression model, and the ROC curve was used to calculate the area under the curve. The larger the area under the curve, the higher the accuracy. The area under the curve (AUC) of this model was 0.928, and the 95% confidence interval was (0.907-0.949), which was statistically significant (P < 0.001), indicating that the prediction equation for episiotomy-related influencing factors has a good diagnostic value.

[0081] (5) Determination of model diagnostic threshold

[0082] Once the ROC curve is determined, it is hoped that an optimal diagnostic cut-off value can be found so that both sensitivity and specificity can be as close to "1" as possible. By moving the judgment point (cutoff point), many combined results of the false positive rate (1-specificity) and sensitivity can be obtained on the ROC curve. Since the horizontal axis of the ROC curve is 1-specificity, the point closest to the upper left corner of the ROC curve, that is, the point where the sensitivity plus specificity reaches the maximum value, is the point corresponding to the diagnostic cut-off value to be found. The best cut-off value of the ROC curve can be calculated based on the Youden index, that is, sensitivity-(1-specificity). The point corresponding to the maximum value of the Youden index is the best cut-off value. The maximum value of the Youden index of this ROC curve is 0.704, and the corresponding best cut-off value is 0.330, the sensitivity is 76.5%, and the specificity is 93.9%.

[0083] Example 2

[0084] According to the prediction model P=1 / (1+y) obtained in Example 1 for evaluating whether the perineum is incised during delivery, the effect of perineum incision was verified for 137 parturients who did not participate in the modeling. Wherein y=exp{-(-3.193 good perineum elasticity+4.386 poor perineum elasticity+1.725 perineum edema+1.542 vaginal laceration+6.243 estimated macrosomia-0.744)}; the value of good perineum elasticity is: 1 for good perineum elasticity, 0 for general perineum elasticity or poor perineum elasticity; the value of poor perineum elasticity is: 1 for poor perineum elasticity, 0 for general perineum elasticity or good perineum elasticity; 1 for perineum edema, 0 for no perineum edema; 1 for vaginal laceration, 0 for no vaginal laceration; 1 for estimated macrosomia, 0 for estimated non-macrosomia.

[0085] The judgment standard is: according to the diagnostic threshold of the prediction model obtained in Example 1, when P≥0.330, the parturient will have an episiotomy, and when P<0.330, the parturient will not have an episiotomy.

[0086] The results are shown in Table 3. The actual episiotomy results of the 137 parturients were that 73 parturients did not undergo episiotomy, and 64 parturients underwent episiotomy, while the prediction model provided by the present invention predicted that 79 parturients would not undergo episiotomy, and 58 parturients would undergo episiotomy. Comparing the two, it is known that the accuracy of the prediction model provided by the present invention is 76.6%, the sensitivity is 70.3%, the specificity is 82.2%, the positive predictive value is 77.6%, and the negative predictive value is 75.9%. The calculation method of the sensitivity, specificity, positive predictive value and negative predictive value in this embodiment is the same as that in Example 1.

[0087] Table 3 Clinical application effect of the prediction model

[0088]

[0089] Since the application of the prediction model provided by the present invention, the episiotomy rate in a certain tertiary hospital has been effectively reduced, with the average episiotomy rate dropping from 34.08% in 2022 to 17.78% in 2024, and no serious perineal laceration occurred.

[0090] Example 3

[0091] A method for predicting whether episiotomy is performed during childbirth comprises the following steps:

[0092] Obtain individual parameter assignments: the parameters include good perineum elasticity, poor perineum elasticity, whether the perineum is edematous, whether the vagina is lacerated, and whether macrosomia is estimated; the assignment method of good perineum elasticity is: 1 for good perineum elasticity, 0 for general or poor perineum elasticity; the assignment method of poor perineum elasticity is: 1 for poor perineum elasticity, 0 for general or good perineum elasticity; the assignment method of whether the perineum is edematous is: 1 for edema, 0 for no edema; the assignment method of whether the vagina is lacerated is: 1 for laceration, 0 for no laceration; the assignment method of whether macrosomia is estimated is: 1 for macrosomia, 0 for not macrosomia;

[0093] Substitute the obtained parameter assignment results into the prediction model for calculation: the prediction model is P = 1 / (1 + y), where y = exp{-(-3.193 good perineum elasticity + 4.386 poor perineum elasticity + 1.725 perineum edema + 1.542 vaginal laceration + 6.243 estimated macrosomia - 0.744)};

[0094] The calculated results were used to predict whether episiotomy was required during delivery: if P ≥ 0.330, episiotomy was required; if P < 0.330, episiotomy was not required.

[0095] The evaluation criteria of perineal elasticity in the above method are: when the fetal head is exposed 3-4cm, the index finger and the middle finger are inserted between the perineum and the fetal presenting part, and the perineal tissue is pulled outward to evaluate the elasticity of the perineum: if two fingers can be inserted, and the fingers can prop up the perineal skin outward by at least 1-2cm, and the skin color is normal when propped up, there is no paleness, no small skin cracks, no hymen, and vaginal mucosal bleeding and tearing, then it is determined that the perineum has good elasticity; if only one finger can be inserted, or although two fingers can be inserted, there is no extra space, the fingers cannot prop up the perineal skin, or there is bleeding from vaginal mucosal lacerations, the perineal skin is shiny, pale, and the epidermis has filamentous cracks, then it is determined that the perineum has poor elasticity. In the present invention, perineal edema refers to perineal edema that occurs in the second stage of labor or before the midwife goes on stage to assist in childbirth, including edema at the perineum, labia majora and minora, and the anterior wall of the vagina. Vaginal laceration refers to vaginal wall laceration that already exists in the second stage of labor or before the midwife goes on stage to assist in childbirth. Estimated macrosomia refers to the estimate that the fetal weight may exceed 4000g based on maternal B-ultrasound, uterine height and abdominal circumference or palpation of the four parts before delivery.

[0096] Example 4

[0097] A system for evaluating whether episiotomy is performed during childbirth, the system comprising a data input module, a data calculation module and an output module;

[0098] The data input module is composed of the following input submodules: a good perineum elasticity module, a poor perineum elasticity module, a perineum edema module, a vaginal laceration module, and a macrosomia estimation module;

[0099] The data calculation module substitutes the input value of the data input module into the prediction model for calculation, and the prediction model is P=1 / (1+y), where y=exp{-(-3.193 good perineum elasticity+4.386 poor perineum elasticity+1.725 perineum edema+1.542 vaginal laceration+6.243 estimated macrosomia-0.744)};

[0100] The output module compares the P value obtained by the data calculation module with 0.330, and if P≥0.330, outputs that episiotomy is needed; if P<0.330, outputs that episiotomy is not needed.

[0101] The value assignment method of the module with good perineum elasticity is: 1 if the perineum elasticity is good, and 0 if the perineum elasticity is average or poor; the value assignment method of the module with poor perineum elasticity is: 1 if the perineum elasticity is poor, and 0 if the perineum elasticity is average or good; the value assignment method of the module with perineum edema is: 1 if yes, and 0 if no; the value assignment method of the module with vaginal laceration is: 1 if yes, and 0 if no; the value assignment method of the module with estimated macrosomia is: 1 if yes, and 0 if no.

[0102] The schematic diagram of the above system is as follows Figure 1 shown.

[0103] Example 5

[0104] Example 1 Clinical practical transformation of the obtained prediction model

[0105] Although the prediction model obtained in Example 1 can obtain accurate prediction results, its calculation is often complicated and requires the use of computing tools such as computers and electronic software. In order to enable the prediction model obtained in the embodiment to be better used clinically, this embodiment can simplify the use process of the model as much as possible while ensuring accuracy. Since the model provided by the present invention ultimately only includes 4 influencing factors, all influencing factors are arranged and combined in sequence and the corresponding prediction probabilities are calculated. When the predicted probability is above the optimal threshold value of the predicted probability (0.330), episiotomy is recommended. When the predicted probability is less than the optimal threshold value of the predicted probability (0.330), non-episiotomy is recommended and perineum protection is performed. The calculation arrangement of all predicted probabilities is presented in a decision tree diagram, see Figure 2 .

[0106] get Figure 2 The process of the decision tree diagram is as follows: The prediction model (P) obtained according to Example 1 is: P = 1 / (1 + y), where y = exp{-(-3.193 good perineum elasticity + 4.386 poor perineum elasticity + 1.725 perineum edema + 1.542 vaginal laceration + 6.243 estimated macrosomia - 0.744)}, because the final included influencing factors are relatively few, Figure 1 The resulting decision tree calculates all the possible P values ​​according to the above prediction model, as follows:

[0107] The first step is when the fetus is estimated to be macrosomia, at this time, assuming that other conditions, such as good perineal elasticity, poor perineal elasticity, perineal edema and vaginal laceration, do not exist, and only the condition of estimated macrosomia is met, then at this time y = exp{-(-3.193*0+4.386*0+1.725*0+1.542*0+6.243*1-0.744)} = exp{-(5.499)} = 0.0040909, then P = 1 / (1+0.0040909) = 0.9959≥0.330, so episiotomy is required. It can be seen that when only the condition of estimated macrosomia is met, episiotomy is required, then other conditions can be ignored, and episiotomy can be directly selected.

[0108] In the second step, if the factor of macrosomia is estimated to be non-existent, we proceed to the next step and come to the second level of the decision tree, the evaluation of perineal conditions. The premise of the evaluation at this time is that the fetus is not macrosomia, so the value of macrosomia is estimated to be 0, and it is still assumed that the two conditions of perineal edema and vaginal laceration do not exist. At the same time, since good, average and poor perineal elasticity cannot exist at the same time, when taking values, as long as one of them exists, the other two will automatically take the value of 0. At the same time, average perineal elasticity means that the perineal elasticity is neither good nor poor. Therefore, when taking values ​​at this time, the values ​​of good perineal elasticity and poor perineal elasticity are both 0. 1. When the perineal elasticity is poor: y = exp{-(-3.193*0+4.386*1+1.725*0+1.542*0+6.243*0-0.744)} = exp{-(3.642)} = 0.0261999, then P = 1 / (1+0.0261999) = 0.9744≥0.330, so perineal incision is required. 2. When the elasticity of the perineum is normal: y = exp{-(-3.193*0+4.386*0+1.725*0+1.542*0+6.243*0-0.744)} = exp{-(-0.744)} = 2.104336, then P = 1 / (1+2.104336) = 0.32212<0.330, so perineal incision is not required. 3. When the perineum is elastic: y = exp{-(-3.193*1+4.386*0+1.725*0+1.542*0+6.243*0-0.744)} = exp{-(-3.937)} = 51.264577, then P = 1 / (1+51.264577) = 0.019133418<0.330, so perineal incision is not required.

[0109] The third step is to verify the situation that episiotomy is not needed, that is, we come to the third level of the decision tree, which is the judgment of perineal edema. At this time, the default estimate of macrosomia is still 0, and it is assumed that there is no perineal laceration, and the value is 0. 1. When the elasticity of the perineum is normal and there is perineal edema: y = exp{-(-3.193*0+4.386*0+1.725*1+1.542*0+6.243*0-0.744)} = exp{-

[0110] (0.981)}=0.374936, then P=1 / (1+0.374936)=0.727306≥0.330, so episiotomy is required. 2. When the perineum is elastic and there is perineal edema: y=exp{-(-3.193*1+

[0111] 4.386*0+1.725*1+1.542*0+6.243*0-0.744)}=exp{-(-2.212)}=9.1339661, then P=1 / (1+9.1339661)=0.098678<0.330, so episiotomy is not needed.

[0112] Step 4: For cases where episiotomy is not necessary, the final step of judging vaginal (perineal) laceration is performed, and the values ​​of other conditions are determined according to the branching of the decision tree. 1. Normal perineal elasticity, no perineal edema, and vaginal laceration: y = exp{-(-3.193*0+4.386*0+1.725*0+1.542*1+6.243*0-0.744)} = exp{-(0.798)} = 0.45022, then P = 1 / (1+0.45022) = 0.68954 ≥ 0.330, so episiotomy is required. 2. Good perineum elasticity, no perineum edema, vaginal laceration: y = exp{-(-3.193*1+4.386*0+1.725*0+1.542*1+6.243*0-0.744)} = exp{-

[0113] (-2.395)}=10.968, then P=1 / (1+10.968)=0.08355<0.330, so no episiotomy is needed. 3. Good perineal elasticity, perineal edema, and vaginal laceration: y=exp{-(-3.193*1+4.386*0+1.725*1+1.542*1+6.243*0-0.744)}=exp{-(-0.67)}=1.95423, then P=1 / (1+1.95423)=0.33849≥0.330, so episiotomy is needed.

[0114] According to the above calculation results, this embodiment simplifies the original prediction model, removes the complex calculation process, and instead gives a recommendation on whether to perform an episiotomy based on the selection of influencing factors, thereby forming an auxiliary method for episiotomy decision-making during delivery, which is as follows:

[0115] The influencing factors are divided into as shown in Table 4, and the evaluation criteria for perineal elasticity in Table 4 are: when the fetal head is exposed 3-4cm, the index finger and the middle finger are inserted between the perineum and the fetal presenting part, and the perineal tissue is pulled outward to evaluate the elasticity of the perineum: if two fingers can be inserted, and the fingers can prop up the perineal skin outward by at least 1-2cm, and the skin color is normal when propped up, there is no paleness, no small skin cracks, no hymen or vaginal mucosa bleeding and tearing, then it is judged that the perineum has good elasticity; if only one finger can be inserted, or although two fingers can be inserted, there is no extra space, the fingers cannot prop up the perineal skin, or there is vaginal mucosal laceration and bleeding, the perineal skin is shiny, pale, and the epidermis has filamentous cracks, then it is judged that the perineum has poor elasticity. In the present invention, perineal edema refers to perineal edema that occurs in the second stage of labor or before the midwife goes on stage to assist in childbirth, including edema of the perineum, labia majora and minora, and the anterior wall of the vagina. Vaginal laceration refers to a laceration of the vaginal wall that already exists during the second stage of labor or before the midwife goes on stage to assist. Estimated macrosomia refers to an estimate of the fetal weight that may exceed 4000g based on maternal B-ultrasound, uterine height and abdominal circumference, or four-part palpation before going on stage.

[0116] The recommendations are as follows: (1) When protective factors do not exist but any one of the risk factors exists, episiotomy is recommended; when risk factors do not exist, no episiotomy is required regardless of whether protective factors exist; (2) When protective factors exist, episiotomy is not required if any one of the moderate risk factors exists. If two moderate risk factors exist at the same time, episiotomy is recommended; (3) When high risk factors exist, episiotomy is recommended regardless of whether protective factors exist; (4) For episiotomy, episiotomy is recommended, and the recommended incision angle is 45° to 60°. The above recommendations are only used as a reference for clinical midwives to make decisions on episiotomy. Midwives should still make the final decision based on the specific circumstances of the mother and child.

[0117] Table 4 Selection of influencing factors

[0118]

[0119] Example 6

[0120] An auxiliary system for episiotomy decision-making during childbirth, the auxiliary system comprising an influencing factor module and an analysis output module;

[0121] The influencing factor module is composed of a protective factor module and a risk factor module; the protective factor module includes a good perineum elasticity unit; the risk factor module is composed of a medium-risk factor submodule and a high-risk factor submodule, the medium-risk factor submodule includes a perineal edema unit and a vaginal laceration unit, and the high-risk factor submodule includes an estimated macrosomia unit and a poor perineum elasticity unit;

[0122] The operating standard of the analysis output module is: when the protective factor module is not checked, and any unit in the risk factor module is checked, "episiotomy" is output; when the risk factor module is not checked, regardless of whether the protective factor module is checked, "no need for episiotomy" is output; when the protective factor module is checked, if one unit in the medium-risk factor submodule is checked, "no need for episiotomy" is output, and if more than one unit in the medium-risk factor submodule is checked, "episiotomy" is output; when any unit in the high-risk factor submodule is checked, "episiotomy" is output regardless of whether the protective factor module is checked. The episiotomy selects episiotomy, and the incision angle is preferably 45° to 60°.

[0123] The schematic diagram of the above-mentioned episiotomy decision support system during childbirth is as follows Figure 3 shown.

[0124] In the perineal incision decision-making support system, the criterion for judging perineal elasticity is as follows: when the fetal head is exposed 3 to 4 cm, the index finger and the middle finger are inserted between the perineum and the fetal presenting part, and the perineal tissue is pulled outward to evaluate the elasticity of the perineum: if two fingers can be inserted, and the fingers can prop up the perineal skin outward by at least 1 to 2 cm, and the skin color is normal when propped up, there is no paleness, no small skin cracks, and no bleeding or tearing of the hymen or vaginal mucosa, then the perineum is judged to be good in elasticity; if only one finger can be inserted, or if two fingers can be inserted but there is no extra space, the fingers cannot prop up the perineal skin, or there is already vaginal mucosal laceration and bleeding, the perineal skin is shiny and pale, and fine thread-like cracks appear on the epidermis, then the perineum is judged to be poor in elasticity; perineal elasticity generally refers to the perineum elasticity being between good and poor;

[0125] The criteria for perineal edema are: perineal edema that occurs during the second stage of labor or before the midwife comes on stage to assist in delivery, including edema of the perineum, labia majora and minora, and anterior vaginal wall;

[0126] The criteria for determining vaginal lacerations are: vaginal lacerations that already existed during the second stage of labor or before the midwife came on stage to assist in the birth;

[0127] The criteria for determining macrosomia are: before going on stage, it is estimated that the fetal weight may exceed 4000g based on maternal B-ultrasound, uterine height and abdominal circumference or four-part palpation method.

[0128] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for predicting whether episiotomy is performed during childbirth, characterized in that: The steps include: Obtain individual parameter assignments: the parameters include good perineum elasticity, poor perineum elasticity, whether the perineum is edematous, whether the vagina is lacerated, and whether macrosomia is estimated; the assignment method of good perineum elasticity is: 1 for good perineum elasticity, 0 for general or poor perineum elasticity; the assignment method of poor perineum elasticity is: 1 for poor perineum elasticity, 0 for general or good perineum elasticity; the assignment method of whether the perineum is edematous is: 1 for edema, 0 for no edema; the assignment method of whether the vagina is lacerated is: 1 for laceration, 0 for no laceration; the assignment method of whether macrosomia is estimated is: 1 for macrosomia, 0 for not macrosomia; Substitute the obtained parameter assignment results into the prediction model for calculation: the prediction model is P = 1 / (1 + y), where y = exp{-(-3.193 good perineum elasticity + 4.386 poor perineum elasticity + 1.725 perineum edema + 1.542 vaginal laceration + 6.243 estimated macrosomia - 0.744)}; The calculated results were used to predict whether episiotomy was required during delivery: if P ≥ 0.330, episiotomy was required; if P < 0.330, episiotomy was not required.

2. Application of the prediction method according to claim 1 in evaluating whether episiotomy is performed during childbirth.

3. A system for evaluating whether episiotomy is performed during childbirth, characterized in that: The system includes a data input module, a data calculation module and an output module; The data input module includes the following input submodules: a good perineum elasticity module, a poor perineum elasticity module, a perineum edema module, a vaginal laceration module, and a macrosomia estimation module; The data calculation module substitutes the input value of the data input module into the prediction model for calculation, and the prediction model is P=1 / (1+y), where y=exp{-(-3.193 good perineum elasticity+4.386 poor perineum elasticity+1.725 perineum edema+1.542 vaginal laceration+6.243 estimated macrosomia-0.744)}; The output module compares the P value obtained by the data calculation module with 0.330, and if P≥0.330, outputs that episiotomy is needed; if P<0.330, outputs that episiotomy is not needed.

4. The system according to claim 3, characterized in that The value assignment method of the module with good perineum elasticity is: 1 if the perineum elasticity is good, and 0 if the perineum elasticity is average or poor; the value assignment method of the module with poor perineum elasticity is: 1 if the perineum elasticity is poor, and 0 if the perineum elasticity is average or good; the value assignment method of the module with perineum edema is: 1 if yes, and 0 if no; the value assignment method of the module with vaginal laceration is: 1 if yes, and 0 if no; the value assignment method of the module with estimated macrosomia is: 1 if yes, and 0 if no.

5. A system for assisting decision-making for episiotomy during childbirth, characterized in that: The auxiliary system includes an influencing factor module and an analysis output module; The influencing factor module is composed of a protective factor module and a risk factor module; the protective factor module includes a good perineum elasticity unit; the risk factor module is composed of a medium-risk factor submodule and a high-risk factor submodule, the medium-risk factor submodule includes a perineal edema unit and a vaginal laceration unit, and the high-risk factor submodule includes an estimated macrosomia unit and a poor perineum elasticity unit; The operation standard of the analysis output module is: when the protective factor module is not checked and any unit in the risk factor module is checked, "episiotomy" is output; when the risk factor module is not checked, regardless of whether the protective factor module is checked, "no need for episiotomy" is output; when the protective factor module is checked, if one unit in the medium-risk factor submodule is checked, "no need for episiotomy" is output; if more than one unit in the medium-risk factor submodule is checked, "episiotomy" is output; when any unit in the high-risk factor submodule is checked, "episiotomy" is output regardless of whether the protective factor module is checked.

6. The episiotomy decision support system according to claim 5, characterized in that: The criteria for judging perineal elasticity are as follows: when the fetal head is exposed 3 to 4 cm, insert the index and middle fingers between the perineum and the fetal presenting part, and pull the perineal tissue outward to assess the elasticity of the perineum: if two fingers can be inserted, and the fingers can prop up the perineal skin at least 1 to 2 cm, and the skin color is normal when propped up, there is no paleness, no small skin cracks, and no bleeding or tearing of the hymen or vaginal mucosa, then the perineum is judged to be elastic; if only one finger can be inserted, or if two fingers can be inserted but there is no extra space, the fingers cannot prop up the perineal skin, or there is vaginal mucosal laceration and bleeding, the perineal skin is shiny and pale, and there are fine thread-like cracks on the epidermis, then the perineum is judged to be elastic; perineal elasticity generally refers to the perineum elasticity being between good and poor; The criteria for perineal edema are: perineal edema that occurs during the second stage of labor or before the midwife comes on stage to assist in delivery, including edema of the perineum, labia majora and minora, and anterior vaginal wall; The criteria for determining vaginal lacerations are: vaginal lacerations that already existed during the second stage of labor or before the midwife came on stage to assist in the birth; The criteria for determining macrosomia are: before going on stage, it is estimated that the fetal weight may exceed 4000g based on maternal B-ultrasound, uterine height and abdominal circumference or four-part palpation method.

7. The episiotomy decision support system according to claim 5, characterized in that: The episiotomy is performed by episiotomy with an incision angle of 45° to 60°.

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