Clinical diagnosis model Construction of endometriosis based on clinical data*

Clinical diagnosis model Construction of endometriosis based on clinical data* | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical diagnosis model Construction of endometriosis based on clinical data* Wenwen Zhang, Qiucheng Jia, Huimin Tang, Yao Chen, Wulin Shan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3890783/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Screen the relevant diagnostic indicators of endometriosis, build a diagnostic model and verify it, so as to provide a scientific basis for diagnosis and differentiation.zig. Method(s) A total of 625 patients with pathologically confirmed endometriosis were selected from December 2016 to June 2022 in Hainan Provincial people's Hospital. 308 patients with endometriosis were selected as case group and 317 patients without endometriosis as control group. There were 41 cases in the case group and 28 cases in the control group. The clinical characteristics and laboratory indexes of patients in the case group and the control group were compared: age, dysmenorrhea, progressive aggravation of symptoms, dysuria, abnormal menstruation, difficulty in sexual intercourse, low back and abdominal pain, infertility, carbohydrate antigen 125, monocyte percentage, monocyte absolute value, platelet, mean platelet volume, platelet volume distribution width, platelet volume ratio, lactate dehydrogenase, alkaline phosphatase. The independent risk factors were screened by binary Logistic regression analysis and the prediction model was constructed. Hosmer-Lemeshow was used to test the goodness of fit of the model and the subject working characteristic curve was used to judge the prediction efficiency of the model. Result(s) There were significant differences in age, dysmenorrhea, progressive aggravation of symptoms, abnormal menstruation, infertility, CA125, PCT, LDH and ALP between the two groups. The higher the CA125, the higher the risk of endometriosis, with statistical significance [OR = 1.023 (95% CI:1.016–1.029)], dysmenorrhea symptoms [OR = 3.467 (95% CI:2.052–5.859)], progressive symptoms [OR = 4.501 (95% CI:1.389–14.584)] and infertility [OR = 2.776 (95% CI:1.216–6.335)]. The higher the risk of endometriosis. The higher the LDH [OR = 0.993 (95% CI:0.987–0.999)] and the higher the ALP [OR = 0.977 (95% CI:0.962–0.991)], the lower the risk of endometriosis. The constructed model was verified by Hmurl and the result showed that P = 0.103, which suggested that the model fitted well. When the area under the model curve was 0.846 (95%CI:0.815–0.873) and the Jordan index was 0.5498, the best critical value was 0.478, the sensitivity was 69.81 and the specificity was 85.17. Conclusion(s) The model has good degree of fit and distinguishing ability, and can be used as an auxiliary means. Endometriosis Diagnosis model Dysmenorrhea CA125 Figures Figure 1 Introduction Endometriosis (Ems) is an estrogen-dependent disease in which endometrial tissue, including glands and mesenchyme, exists and grows in the cavity of the uterus outside the overlying lining and uterus. It often causes pain, infertility and pelvic masses. About 10–15% of women of childbearing age may be affected, affecting about 190 million women worldwide. The prevalence ranges from 2–11% in asymptomatic women, 5–50% in infertile women, and 5–21% in women with pelvic pain.EMs have a high recurrence rate, up to 30.5% after systemic treatment, and there is no effective treatment for recurrence. The pathogenesis of EMs is complex and the exact pathogenesis is still unknown.Theories of origin that have been put forward include the retrograde flow of menstrual blood theory, somatic epithelial metaplasia, lymphatic and vascular metastases. Menstrual reflux refers to the reflux of menstrual debris containing viable endometrial cells through the fallopian tubes into the peritoneal cavity where they grow and form ectopic foci, which is the classic theory for the origin of endometriosis. cysts, peritoneal endometriosis (SPE), i.e. various foci in the pelvis, peritoneal endometriosis (SPE), i.e. various foci in the pelvic peritoneum, and deep infiltrating endometriosis (DIE), i.e. foci infiltrating to a depth of more than 5 mm [ 1 – 3 ] .OEC is the most common clinical type, accounting for 17–44% of all endometriosis [ 4 ] . The American Society for Reproductive Medicine (ASRM) staging system is commonly used: stage I microscopic lesions, stage II mild, stage III moderate and stage IV severe. Diagnosis of endometriosis includes clinical and surgical diagnosis. Laparoscopy is a common means of diagnosing endometriosis [5], which is an invasive examination with high costs, surgical risks and the possibility of postoperative adhesion formation. In clinical practice, laparoscopy is more commonly used for the surgical treatment of endometriosis. Transvaginal ultrasound (TVUS) and magnetic resonance imaging (MRI) have high sensitivity and specificity for the diagnosis of endometriosis [ 6 , 7 ] . However, delayed diagnosis of endometriosis is common and leads to exacerbation of the disease. Therefore, early or timely diagnosis of endosteopathy is of great importance for the management of the disease. Based on the above clinical problems, this paper proposes to establish a clinical diagnostic model for endosteopathy based on clinical features and basic examinations to provide alternative means and methods for timely diagnosis of endosteopathy. 1 Information and methodology 1.1 Information 1.1.1 Research Objectives Patients who underwent surgical treatment with pathologically confirmed diagnosis at Hainan Hospital affiliated to Hainan Medical College (formerly Hainan Provincial People's Hospital) from December 2016 to June 2022 were selected, with 308 cases in the endometriosis group and 317 cases in the non-endometriosis group as the control group, for a total of 625 cases as modelling data. In addition, 41 cases of endometriosis and 28 cases of non-endometriosis were used as validation data. The American Fertility Society (AFS) staging method was used to stage the endometriosis group. The study was approved by the Ethics Committee of Hainan Provincial People's Hospital. See Tables 1 – 1 and 1 – 2 . Table 1 1 Number and disease composition of endometriosis group and control group (test set) disease group n comparison group n DIE 14 uterine fibroids 87 DIE combined OEC 8 SPE 5 benign ovarian cysts 207 SPE combined uterine fibroids 10 SPE combined benign ovarian cysts 12 SPE combined OEC 22 OEC 149 Pelvic inflammatory disease 23 OEC combined uterine fibroids 45 OEC combined benign ovarian cysts 13 OEC combined adenomyosis 30 Stage I/II 48 —— Stage Ⅲ 129 —— Stage Ⅳ 130 —— Table 1 2 The number and clinical data of endometriosis group and control group (verification set) validation set disease group control subjects DIE 1 —— SPE 2 —— OEC 38 —— uterine fibroids —— 12 benign ovarian cysts —— 14 Pelvic inflammatory disease —— 2 age 33(28–43) 37(30.5–42) Symptoms of menstrual cramps 14(82.4%) 3(17.6%) Progressive exacerbation of symptoms 5(83.3%) 1(16.7%) menstrual abnormality 3(33.3%) 6(66.7%) infertility 5(62.5%) 3(37.5%) CA125 81.3(42.5-175.85) 12.8(9.625–17.35) LDH 165.8(152-197.55) 188.5(166.05-224.35) ALP 57.5(44.85–66.5) 59.2(59.97–65.32) Table 2 Comparison of clinical data and laboratory indexes between endometriosis group and control group disease group comparison group χ/z values P-value age 32(27–38) 34(28–43) -2.828 0.005 Symptoms of menstrual cramps 143(46.4%) 32(10.1%) 102.297 0.000 Progressive exacerbation of symptoms 58(18.8%) 4(1.3%) 53.964 0.000 difficulty in urinating and defecating 6(1.9%) 4(1.3%) 0.133 0.715 menstrual abnormality 12(3.9%) 36(11.4%) 12.263 0.000 dyspareunia 3(1%) 0(0%) 1.399 0.237 abdominal and lower back pain 45(14.6%) 41(12.9%) 0.370 0.543 infertility 32(10.4%) 10(3.2%) 13.045 0.000 CA125 50.05(27.97–97.1) 17.4(12.85–26.55) -14.084 0.000 MONOP 7.2(6.1–8.47) 7.2(6.1–8.4) -0.186 0.852 MONON 0.46(0.37–0.56) 0.45(0.375–0.53) -1.433 0.152 PLT 281(240.25–325.5) 276(240–317) -1.279 0.201 MPV 10.25(9.7–10.8) 10.1(9.6–10.9) -0.904 0.366 PDW 11.5(10.5–12.6) 11.4(10.4–12.8) -0.083 0.933 PCT 0.28(0.25–0.34) 0.28(0.25–0.32) -2.013 0.044 LDH 162.25(144.07-179.35) 170.8(150.65–192.7) -3.088 0.002 ALP 49.75(43-58.02) 51.8(43.55–62.15) -2.033 0.042 1.1.2 Inclusion and exclusion criteria Inclusion criteria: surgery in our hospital and confirmed by postoperative pathology; fulfilling the criteria of the Endometriosis Diagnosis and Treatment Guidelines; complete medical history; no use of hormonal drugs in the 6 months prior to surgery. Exclusion criteria: severe chronic diseases combined with systemic diseases such as heart, brain, lung, kidney, liver failure and thyroid dysfunction in the case and control groups; malignant tumours and diseases of the immune system; patients with severe psychiatric disorders; cases with endometriosis in the control group; and incomplete medical history data. The hospital's electronic medical record system was used to search for the medical records of the study population: admission and discharge records, medical course records, surgical records, laboratory and imaging data. 1.2 Methods 1.2.1 Information collection Clinical data and some laboratory findings were collected from patients in the endometriosis group and the control group: age, dysmenorrhoea with or without progressive worsening, dyspareunia, menstrual abnormalities, dyspareunia, lumbar and abdominal pain, infertility, carbohydrate antigen 125 (CA125), monocyte percentage(MONOP), monocyte absolute value(MONON), platelet(PLT), mean platelet volume (MPV), Platelet Volume Distribution Width (PDW), platelet volume ratio (PCT), lactate dehydrogenase (LDH), alkaline phosphatase (ALP). Valuable indicators were screened by comparing the two groups. 1.2.2 Constructing diagnostic models and model validation Indicators with statistically significant differences were first subjected to one-way analysis, and those with statistically significant differences in one-way analysis (P < 0.1) were subjected to multifactorial logistic regression analysis, which was used to construct the diagnostic model. Goodness of fit and discrimination of the model were also assessed. The kappa consistency test was used to verify the predictive power of the model on data from 69 cases in the validation set. 1.3 Statistical treatment Data were analysed using SPSS 25.0 statistical software. Measurements were expressed as median and interquartile range, and comparisons between the two groups were made using the Mann-Whitney U rank-sum test; count data were expressed as cases (%), and comparisons were made using the χ2 test. Binary logistic regression analysis was used to screen for independent risk factors and to construct a prediction model, and the goodness of fit of the model was assessed by the Hosmer-Lemeshow (H-L) test. The predictive ability of the model was determined by plotting the receiver operating characteristic (ROC) curve using MedCal 2.0. p < 0.05 was considered statistically significant. 2 Results 2.1 Comparison of clinical characteristics between the two groups Differences in clinical data between the two groups were compared by χ2 or rank sum test. The differences between the two groups in terms of age, dysmenorrhoea symptoms, progressive worsening of symptoms, menstrual abnormalities, infertility, CA125, PCT, LDH, ALP were statistically significant (P 0.05). See Table 2 . 2.2 Logistic regression analysis of diagnostic indicators of endomorphism and their constructed models Statistically different indicators were subjected to univariate analysis of variance Indicators with P < 0.1 were used as independent variables, i.e. age, dysmenorrhoea symptoms, progressive worsening of symptoms, menstrual abnormalities, infertility, CA125, PCT, LDH, ALP. Multifactorial logistic regression equations were constructed using the forward stepwise method. The results showed that there was a statistically significant higher risk of developing endometriosis with higher CA125 [OR = 1.023 (95% CI: 1.016–1.029)], dysmenorrhoea symptoms [OR = 3.467 (95% CI: 2.052–5.859)], progressive worsening of symptoms [OR = 4.501 (95% CI: 1. Higher LDH [OR = 0.993 (95% CI: 0.987–0.999)], ALP [OR = 0.977 (95% CI: 0.962–0.991)] were statistically associated with a lower risk of developing endogamy (p < 0.05). A diagnostic model for endogamy was constructed as follows: Logistic (P) = (1.085) + 1.243 × dysmenorrhoea + 1.504 × progressive worsening of symptoms + (-1.461) × menstrual abnormality + 0.023 × CA125 + (-0.007) × LDH + (-0.024) × ALP. See Table 3 . Table 3 Parameters of Logistic regression analysis for modeling endometriosis B-value standard error Wald P-value OR value 95%CI Symptoms of menstrual cramps 1.243 0.268 21.579 0.000 3.467 2.052 5.859 progressive exacerbation 1.504 0.6 6.288 0.12 4.501 1.389 14.584 menstrual abnormality -1.461 0.455 10.307 0.001 0.232 0.095 0.566 infertility 1.021 0.421 5.88 0.015 2.776 1.216 6.335 CA125 0.023 0.003 45.884 0.000 1.023 1.016 1.029 LDH -0.007 0.003 4.807 0.028 0.993 0.987 0.999 ALP -0.024 0.008 9.691 0.002 0.977 0.962 0.991 constant 1.085 0.633 2.942 0.086 2.959 2.3 Validation of the predictive efficacy of the diagnostic model for endometriosis The H-L validation results showed P = 0.103, indicating that the model was well fitted. The area under the ROC curve of this diagnostic model was 0.846 (95% CI: 0.815–0.873), and the optimal critical value of 0.478 was selected when the Yoden index was 0.5498, at which point the sensitivity of the ROC curve was 69.81 and the specificity was 85.17 (Fig. 1 ). In the clinical model validation, a further 69 patients in this study were selected and included in the model formula, when the cut-off value ≥ 0.478 the diagnosis of endometriosis was considered, kappa = 0.659 (P = 0.000), suggesting that the diagnosis was basically consistent with the pathological findings. See Table 4 . Table 4 Validation set results Case results negatives positive total Model results negatives 27 11 38 positive 1 30 31 total 28 41 69 3 Discussion EMs is a common condition in women of reproductive age, with a prevalence of approximately 10% [ 8 ] . The main clinical manifestations are infertility, dysmenorrhoea, chronic pelvic pain, dyspareunia and painful bowel movements. It has a high recurrence rate and an infertility rate that can be as high as 50%, causing great harm to women's reproductive health and a socioeconomic burden [ 8 , 9 ] . Despite the high prevalence, not everyone is aware of the disease; there is a delay of up to 9 years between symptom onset and diagnosis [ 6 ] , and the majority of patients may be misdiagnosed and not effectively treated. This allows the disease to progress, causing great physical and psychological harm to patients. Early diagnosis, early treatment, improved quality of life and improved reproductive function, therefore finding more efficient and reliable diagnostic methods is one of the main research focuses in EM. Currently, laparoscopy is the gold standard for diagnosing EMs. This procedure is invasive, carries some surgical risk and requires an experienced physician [ 7 ], and reliance on laparoscopy to diagnose EMs may delay the timing of this complex disease [ 3 ] . Transvaginal ultrasound is most sensitive for OEC, but less sensitive for mild forms, SPE and DIE, and is dependent on personal experience with the procedure [ 6 , 7 ] . Magnetic resonance imaging is sensitive for DIE, but is more expensive. The prevalence of EM is high (45%-50%) in patients with chronic pelvic pain and in asymptomatic women, and the absence of a clearly visible lesion or negative histology does not exclude EM, so clinical symptoms may be more helpful in making a diagnosis than exact lesions [ 3 ] . The development of a diagnostic model based on clinical symptoms and simple laboratory indicators for rapid and effective screening to provide a basis for further diagnosis and treatment [ 6 ] was the main aim of our present study. We selected dysmenorrhoea, progressive exacerbation of symptoms, menstrual abnormalities, infertility, CA125, LDH, ALP, dysuria, dyspareunia, dyspareunia, lumbar and abdominal pain, MONOP, MONON, PLT, MPV, PDW, PCT as diagnostic indices and constructed the diagnostic model using one-way and multifactorial logistic regression analysis. Unfortunately, in the results of our study: dysuria, dyspareunia, low back and abdominal pain, MONOP, MONON, PLT, MPV, PDW were not statistically different from the control group (P > 0.05); the difference between the menstrual abnormalities endometriosis group was lower than that of the control group was statistically significant (P < 0.05). Dysmenorrhoea, progressive worsening of symptoms, infertility and CA125 were independent risk factors for EM. There were no statistically significant differences between the case and control groups for difficulty with bowel and urinary functions, difficulty with sexual intercourse, and back and abdominal pain. This may be due to the small number of positive cases in the data from the trials we included to compare the differences. Inflammation can trigger the recruitment of monocytes from the bone marrow into the peripheral blood, where they infiltrate the tissues and develop into macrophages, which differentiate in the diseased tissue into pro-inflammatory M1 macrophages (which mainly secrete pro-inflammatory factors, initiate inflammation, play an important role in the early stages of inflammation, remove cellular debris of pathogenic microorganisms, etc.) and anti-inflammatory M2 macrophages (which secrete pro-inflammatory factors, initiate inflammation, play an important role in the early stages of inflammation, remove cellular debris of pathogenic microorganisms, etc.). ) and anti-inflammatory M2 macrophages (which inhibit inflammatory responses, tissue repair, pro-fibrotic activity, and are able to induce immune tolerance and fibrotic activity. and are able to induce immune tolerance and angiogenesis) [ 10 , 11 ] .Antonio Simone Lagan et al. reported a trend towards a progressive decrease in M1 macrophages and a gradual increase in M2 macrophages from stage I to stage IV in endometriosis. This trend contributes to the formation of a pro-inflammatory microenvironment in the early stages of the disease and the development of pro-fibrotic activity in the later stages [ 12 ] . The important role of monocytes in the development of EMs has been reported in the literature [ 13 , 14 ] , so they were included in our study index. However, in our results, the difference between the MONOP and MONON groups was not statistically significant when compared. This may be due to the fact that we did not select monocytes from the lesion site, but monocytes from peripheral blood, and only analysed the total number of monocytes and not their subtypes. A significant increase in peritoneal M2-type macrophages in patients with ovarian endometriotic cysts has been reported previously and is directly proportional to disease severity [ 12 ] . Cyclic bleeding of endometriosis lesions leads to repeated tissue damage and repair, activating platelets and immune cells in the lesion microenvironment, causing the ectopic lesion to undergo epithelial-mesenchymal transition and fibroblast-myofibroblast transition, and ultimately fibrosis [ 15 – 17 ] . Platelets can induce endothelial cell proliferation, which allows endothelial cells to acquire new capabilities such as contraction, migration, invasion and collagen production. Platelets play a key role in the progression of ectopic foci and fibrosis formation and could be a potential target for the treatment of endometriosis [ 18 ] . Unfortunately, in our study, platelets did not differ between the two groups, which may be related to platelet physiological processes. Platelets are activated by a complex activation process that starts with the formation of a tightly packed 'core' of mainly fibrin-rich, P-selectin-positive platelets at the site of injury and a 'shell' of loose platelets that are arranged outside the core by attachment and adhesion. The platelets are then recruited to the circulating platelets. Circulating platelets are further recruited to act at the beginning of the lesion [ 19 ] . Therefore, platelets at the lesion site may be more variable than in peripheral blood [ 18 , 20 ] . Dysmenorrhoea is divided into primary dysmenorrhoea PD (Primary Dysmenorrhoea PD) and secondary dysmenorrhoea SD (Secondary Dysmenorrhoea SD).PD usually occurs 6–12 months after the onset of menstruation, occurs before or at the start of menstruation, lasts 8–72 hours, and is most severe on the first or second day of menstruation. Secondary dysmenorrhoea is caused by other conditions such as endometriosis, adenomyosis and pelvic inflammatory disease. It usually occurs 2–5 years after the onset of menstruation and can be associated with dyspareunia, chronic pelvic pain and infertility. Endometriosis is the most common cause of secondary dysmenorrhoea [ 21 ] .EMs is a well-recognised chronic inflammatory disease that can lead to increased production of pro-inflammatory cytokines, prostaglandin overproduction, peripheral and central sensitisation and an abnormal stress response, resulting in secondary dysmenorrhoea with severe symptoms [ 21 ] . Progressive worsening of symptoms should raise a high index of suspicion for EMs, and the severity of primary dysmenorrhoea does not increase over time. Chronic inflammation of the peritoneal cavity in patients with EMs leads to ovarian dysfunction, altered fertilisation, pelvic adhesions affecting conception and increasing the likelihood of infertility [ 22 ] , and the infertility rate can be as high as 50%, and infertility is a good diagnostic indicator. CA125 is a well-established tumour marker produced in the epithelial cells of the body cavities during embryonic development, and its use in the diagnostic role of ovarian cancer has been widely accepted, and it is also elevated to varying degrees in the serum of patients with EMs [ 23 ] , with particularly high sensitivity in stage III/IV. For CA125 > 30U/mL, the sensitivity was 52.4% (95% CI 37.9–66.4%), the specificity was 92.7% (95% CI 89.4–95.1%), and for CA125 > 35.0U/mL, the sensitivity was 0.40 (95% CI 0.32–0.49), the specificity was 0.91 (95% CI 0.88–0.94) [ 24 ] . 0.94) [ 23 ] . Numerous studies have recommended the use of CA125 to aid in the diagnosis of patients with EMs [ 24 – 28 ] , but sensitivity is low when used alone. Lactate dehydrogenase, which is involved in the last step of glycolysis and plays an important role in metabolic reactions, is widely distributed in a variety of organs and tissues and has been used as an important diagnostic marker for common diseases such as cancer, infectious diseases and tuberculosis. It plays a key role in the clinical diagnosis of a variety of common and rare diseases, and the abnormal levels of isoforms of this enzyme are important biomarkers for various diseases [ 29 – 34 ] . A study by Yijuan Kang et al. indicated that the expression of the subunit of lactate dehydrogenase (LDHB) was significantly decreased in the cyst wall tissue of ovarian endometriotic cysts, suggesting an increase in glycolysis, which may be related to the tumour-like invasive and metastatic behaviour of endometriosis [ 35 ] .ALP is a metalloproteinase that catalyses the hydrolysis and transfer of phosphate groups under alkaline conditions. Four alkaline phosphatase isoenzymes are present in the human body: tissue non-specific alkaline phosphatase (TNALP), intestinal-type alkaline phosphatase (IALP), placental-type alkaline phosphatase (PALP) and germ cell alkaline phosphatase (GCAP). IALP, PALP and germ cell ALP are expressed in specific tissues (duodenum, syncytiotrophoblast and testis respectively), whereas TNALP is expressed in various tissues [ 36 ] . A study by Jae O. Kang et al. showed that the total alkaline phosphatase level was higher in the endometriosis group than in the control group, but the elevation could be due to a specific isoform, and because of the extremely low levels of the serum species, it was suggested that specific assays should be used to aid in the diagnosis of endometriosis [ 43 ] . For the first time, we used alkaline phosphatase as an indicator to construct a diagnostic model, but our findings were different from previous ones [ 43 , 44 ] . This may be due to the bias caused by detecting the total serum level without detecting the specific subtype. The diagnostic model of EMs constructed according to the above risk factors has a good fit and diagnostic efficacy, and can be used as an auxiliary tool for the preliminary clinical diagnosis of EMs. The proposed interventions for the proposed EMs are: (1) increase knowledge of EMs in key populations such as dysmenorrhoea and infertility, especially in adolescents and women of reproductive age; (2) pay attention to changes in serological indices; (3) provide early pharmacological intervention, if necessary; (4) promote active reproduction in women with reproductive needs. We included all patients with pathological findings after surgery and excluded the possibility of including patients with endogamy in the control group. However, the data in our study were based on a single-centre retrospective study and may have been inadequately collected. For example, for dysmenorrhoea, we made a simple distinction between presence and absence without further consideration of the type of pain (tingling, burning, aching, etc.) and the type of pain (e.g. dysmenorrhoea, non-cyclic pelvic pain, dyspareunia, etc.) as well as changes with the menstrual cycle. These deficiencies will be improved in our subsequent studies. The diagnostic model we have constructed for endometriosis has a good fit and discriminatory ability, and the indicators are easy to obtain, making it a reliable and practical diagnostic tool. Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Hainan General Hospital.The data used in this study was anonymized before it s use . Our study was a retrospective analysis and therefore no informed consent waiver was obtained from Ethics Committee of Hainan General Hospital. All patients were older than 18 years. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Conflict of Interests The authors declare no competing interests. Funding This work was supported by grants from Top Talent of Changzhou “The 14th Five-Year Plan” High-Level Health Talents Training Project (2022CZBJ074), the maternal and child health key talent project of Jiangsu Province (RC202101), the maternal and child health research project of Jiangsu Province (F202138) Authors' contributions Wenwen Zhang , Qiucheng Jia， Huimin Tang:Conceptualization、Methodology、Writing - Original Draft： Yao Chen, Wulin Shan:Methodology、Software、Validation、Formal analysis, Jiming Chen, Genhai Zhu :Writing - Review & Editing、Visualization、Supervision、Project administration、Funding acquisition References Serdar E, Bulun MD. Endometriosis[J]. N Engl J Med,2009, 360: 268-279. Giudice LC. Clinical practice. Endometriosis[J]. N Engl J Med,2010, 362(25): 2389-2398. Taylor HS, Kotlyar AM, Flores VA. Endometriosis is a chronic systemic disease: clinical challenges and novel innovations[J]. The Lancet,2021, 397(10276): 839-852. Li XY, Chao XP, Leng JH, et al. Risk factors for postoperative recurrence of ovarian endometriosis: long-term follow-up of 358 women[J]. J Ovarian Res,2019, 12(1): 79. Dunselman GA, Vermeulen N, Becker C, et al. ESHRE guideline: management of women with endometriosis[J]. Hum Reprod,2014, 29(3): 400-412. Rogers PA, Adamson GD, Al-Jefout M, et al. Research Priorities for Endometriosis[J]. Reprod Sci,2017, 24(2): 202-226. Rolla E. Endometriosis: advances and controversies in classification, pathogenesis, diagnosis, and treatment[J]. F1000Res,2019, 8: 529. Zondervan KT, Becker CM, Missmer SA. Endometriosis[J]. N Engl J Med,2020, 382(13): 1244-1256. Lang JH. History, current status and development of the understanding of endometriosis[J]. Chinese Journal of Practical Gynaecology and Obstetrics,2020, 36(03): 193-196. Jakubzick CV, Randolph GJ, Henson PM. Monocyte differentiation and antigen-presenting functions[J]. Nat Rev Immunol,2017, 17(6): 349-362. Kratofil RM, Kubes P, Deniset JF. Monocyte Conversion During Inflammation and Injury[J]. Arterioscler Thromb Vasc Biol,2017, 37(1): 35-42. Laganà AS, Salmeri FM, Ban Frangež H, et al. Evaluation of M1 and M2 macrophages in ovarian endometriomas from women affected by endometriosis at different stages of the disease[J]. Gynecol Endocrinol,2020, 36(5): 441-444. Sturlese E, Salmeri FM, Retto G, et al. Dysregulation of the Fas/FasL system in mononuclear cells recovered from peritoneal fluid of women with endometriosis[J]. J Reprod Immunol,2011, 92(1-2): 74-81. Salmeri FM, Laganà AS, Sofo V, et al. Behavior of tumor necrosis factor-α and tumor necrosis factor receptor 1/tumor necrosis factor receptor 2 system in mononuclear cells recovered from peritoneal fluid of women with endometriosis at different stages[J]. Reprod Sci,2015, 22(2): 165-172. Guo SW, Ding D, Shen M, et al. Dating Endometriotic Ovarian Cysts Based on the Content of Cyst Fluid and its Potential Clinical Implications[J]. Reprod Sci,2015, 22(7): 873-883. Zhang Q, Duan J, Liu X, et al. Platelets drive smooth muscle metaplasia and fibrogenesis in endometriosis through epithelial-mesenchymal transition and fibroblast-to-myofibroblast transdifferentiation[J]. Mol Cell Endocrinol,2016, 428: 1-16. Brosens IA. Endometriosis--a disease because it is characterized by bleeding[J]. Am J Obstet Gynecol,1997, 176(2): 263-267. Yan D, Liu X, Xu H, et al. Platelets induce endothelial-mesenchymal transition and subsequent fibrogenesis in endometriosis[J]. Reprod Biomed Online,2020, 41(3): 500-517. Holinstat M. Normal platelet function[J]. Cancer Metastasis Rev,2017, 36(2): 195-198. Ding D, Liu X, Duan J, et al. Platelets are an unindicted culprit in the development of endometriosis: clinical and experimental evidence[J]. Hum Reprod,2015, 30(4): 812-832. Clemenza S, Vannuccini S, Capezzuoli T, et al. Is primary dysmenorrhea a precursor of future endometriosis development?[J]. Gynecol Endocrinol,2021, 37(4): 287-293. Chapron C, Marcellin L, Borghese B, et al. Rethinking mechanisms, diagnosis and management of endometriosis[J]. Nat Rev Endocrinol,2019, 15(11): 666-682. Coutinho LM, Ferreira MC, Rocha ALL, et al. New biomarkers in endometriosis[J]. Adv Clin Chem,2019, 89: 59-77. O'Shaughnessy A, Check JH, Nowroozi K, et al. CA 125 levels measured in different phases of the menstrual cycle in screening for endometriosis[J]. Obstet Gynecol,1993, 81(1): 99-103. Dai Kemiao. Clinical value of serum cancer antigen 125, neutrophil activating peptide-78 and monocyte chemotactic protein-1 in the diagnosis of endometriosis[J]. China Maternal and Child Health, 2021, 36(24): 5677-5679. Tang T, Lai H, Huang X, et al. Application of serum markers in diagnosis and staging of ovarian endometriosis[J]. J Obstet Gynaecol Res,2021, 47(4): 1441-1450. LI Na, YAN Fu-Tian. Application value of combined ultrasound and CA125 in the diagnosis of ovarian endometriotic cysts[J]. Tibetan Medicine,2022, 43(03): 25-28. ZHU Xiaoqin, QIAN Jin, WANG Yongxia, et al. Expression of COX-2 and MMP-14 and correlation with serum CA125 in endometriosis[J]. Chinese Journal of Family Planning,2022, 30(03): 668-671. Khan AA, Allemailem KS, Alhumaydhi FA, et al. The Biochemical and Clinical Perspectives of Lactate Dehydrogenase: An Enzyme of Active Metabolism[J]. Endocr Metab Immune Disord Drug Targets,2020, 20(6): 855-868. Di Peipei, Xiao Wenrong, Lv Huifen, et al. Evaluation of cerebrospinal fluid heparin-binding protein, lactate dehydrogenase, and ortho-pentameric protein 3 assays for the diagnosis and prognosis of intracranial infections[J]. Chinese Journal of Health Inspection,2022, 32(19): 2389-2393. Zhu Ying, Hong Hui, Zhang Yu, et al. Analysis of the diagnostic value of lactate dehydrogenase and D-dimer assays for Mycoplasma pneumoniae pneumonia[J]. China Medical Innovation, 2022, 19(15): 42-45. LU Yanxing. Correlation analysis between preoperative lactate dehydrogenase/albumin ratio and prognosis in breast cancer[J]. Jilin Medical Science,2022, 43(09): 2522-2524. WANG Yun, NIU Hua, FANG Hao Hui. Prognostic value of C-reactive protein/clear protein ratio of lactate dehydrogenase in patients with non-small cell lung cancer[J]. Anhui Medicine,2022, 43(08): 912-917. CHEN Pengjuan, LU Shaobei, HAO Yingying. The value of combined ADA and LDH testing in the diagnosis and disease assessment of pulmonary tuberculosis[J]. Quality Safety and Inspection,2020, 30(06): 142-145. Kang Yijuan. Correlation study of LDHB expression in endometriosis and its significance[D]. Huazhong University of Science and Technology,2013. Haarhaus M, Brandenburg V, Kalantar-Zadeh K, et al. Alkaline phosphatase: a novel treatment target for cardiovascular disease in CKD[J]. Nat Rev Nephrol,2017, 13(7): 429-442. WU Yi, TANG Shenhong, YU Xia. Relationship between serum CRP, IG and ALP levels and the condition and prognosis of children with MPP[J]. Journal of Molecular Diagnosis and Therapy,2022, 14(09): 1566-1569. LI Sirong, KONG Lingchao, LI Genhai, et al. Expression and clinical significance of serum ApoA, LDH and ALP in chronic heart failure[J]. Journal of Molecular Diagnosis and Therapy,2022, 14(04): 697-700. LI Yanqiu, LIU Peiming, FAND Sheng. Correlation between preoperative serum r-GT and ALP levels and the efficacy of transcatheter hepatic artery chemoembolisation in patients with advanced hepatocellular carcinoma[J]. Journal of Sichuan North Medical College,2022, 37(07): 898-901+913. Zong Yi, Wang Jia. Clinical value of serum 5'NT, LAP, ALP and GGT tests in liver diseases[J]. Medical Food Therapy and Health,2022, 20(16): 193-195. MA Lijuan, WANG Yun, LI Dianming. Analysis of the correlation and diagnostic value of serum CEA, CYFRA21-1, ALP, ALB and KPS score in lung cancer patients[J]. Laboratory Medicine and Clinics,2022, 19(04): 454-458. YU Yan, YANG Shufang, SHEN Dongmei. Correlation between serum ALB, TP, PLT, ALP, LDH and D-D levels and the severity of preeclampsia[J]. Practical Gynaecological Endocrinology Electronic Journal,2021, 8(21): 24-26. Kang JO, Hudak WA, Crowley WJ, et al. Placental-type alkaline phosphatase in peritoneal fluid of women with endometriosis[J]. Clin Chim Acta,1990, 186(2): 285-294. Trapero C, Jover L, Fernández-Montolí ME, et al. Analysis of the ectoenzymes ADA, ALP, ENPP1, and ENPP3, in the contents of ovarian endometriomas as candidate biomarkers of endometriosis[J]. Am J Reprod Immunol,2018, 79(2): Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3890783","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":283145275,"identity":"383a1555-ed02-400f-8d68-00467af6382b","order_by":0,"name":"Wenwen Zhang","email":"","orcid":"","institution":"Hainan Medical College","correspondingAuthor":false,"prefix":"","firstName":"Wenwen","middleName":"","lastName":"Zhang","suffix":""},{"id":283145276,"identity":"bc88aef5-2fdd-414f-810b-87966741f0fb","order_by":1,"name":"Qiucheng Jia","email":"","orcid":"","institution":"The Affiliated Changzhou Second People's Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qiucheng","middleName":"","lastName":"Jia","suffix":""},{"id":283145277,"identity":"6d487bc8-d8fa-4345-b2ca-981e142ba632","order_by":2,"name":"Huimin Tang","email":"","orcid":"","institution":"The Affiliated Changzhou Second People's Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huimin","middleName":"","lastName":"Tang","suffix":""},{"id":283145278,"identity":"d0b529c0-d626-4867-98d1-08b61093ca25","order_by":3,"name":"Yao Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of USTC, University of Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Yao","middleName":"","lastName":"Chen","suffix":""},{"id":283145279,"identity":"fe43a825-55fc-4dff-84ae-5d5a0d1be5f4","order_by":4,"name":"Wulin Shan","email":"","orcid":"","institution":"The First Affiliated Hospital of USTC, University of Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Wulin","middleName":"","lastName":"Shan","suffix":""},{"id":283145280,"identity":"f845cf10-e43b-420d-946b-c4ac2ce2951f","order_by":5,"name":"Genhai Zhu","email":"","orcid":"","institution":"The affiliated Hainan Hospital of Hainan Medical College","correspondingAuthor":false,"prefix":"","firstName":"Genhai","middleName":"","lastName":"Zhu","suffix":""},{"id":283145281,"identity":"85201c98-6605-4660-928b-93e989ee0076","order_by":6,"name":"Jiming Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArElEQVRIiWNgGAWjYFCCA0DIYMPDz95AmpY0GcmeA6RZddjG4IYDkWr5G08nHi74dZ6H4QYD44ePOURokThwdsPhmX23eRhnNzBLztxGhBYDBqAW3p7bPMwyB9iYeUnQco6HTSKBFC08Pw7w8BCtBewX3oZkHgmeg83E+YV/xtnNn3n+2NnbH28++OEjMVqA1jAwMLaBWIwNxKgHWQNS+IdIxaNgFIyCUTAyAQChZTvL1QqUuQAAAABJRU5ErkJggg==","orcid":"","institution":"The Affiliated Changzhou Second People's Hospital of Nanjing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Jiming","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-01-23 10:29:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3890783/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3890783/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53663503,"identity":"4176a76c-5ad0-47aa-88e4-40de08c7e260","added_by":"auto","created_at":"2024-03-28 16:29:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":55365,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curve of endometriosis model group\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3890783/v1/9032fa993a8eba03e10e5ad5.png"},{"id":57214820,"identity":"28e68792-8c75-4986-889c-349ba8149ab8","added_by":"auto","created_at":"2024-05-27 13:39:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1228001,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3890783/v1/0d667f2d-78e2-4723-82b9-8c64013e0a2a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical diagnosis model Construction of endometriosis based on clinical data*","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEndometriosis (Ems) is an estrogen-dependent disease in which endometrial tissue, including glands and mesenchyme, exists and grows in the cavity of the uterus outside the overlying lining and uterus. It often causes pain, infertility and pelvic masses. About 10\u0026ndash;15% of women of childbearing age may be affected, affecting about 190\u0026nbsp;million women worldwide. The prevalence ranges from 2\u0026ndash;11% in asymptomatic women, 5\u0026ndash;50% in infertile women, and 5\u0026ndash;21% in women with pelvic pain.EMs have a high recurrence rate, up to 30.5% after systemic treatment, and there is no effective treatment for recurrence. The pathogenesis of EMs is complex and the exact pathogenesis is still unknown.Theories of origin that have been put forward include the retrograde flow of menstrual blood theory, somatic epithelial metaplasia, lymphatic and vascular metastases. Menstrual reflux refers to the reflux of menstrual debris containing viable endometrial cells through the fallopian tubes into the peritoneal cavity where they grow and form ectopic foci, which is the classic theory for the origin of endometriosis. cysts, peritoneal endometriosis (SPE), i.e. various foci in the pelvis, peritoneal endometriosis (SPE), i.e. various foci in the pelvic peritoneum, and deep infiltrating endometriosis (DIE), i.e. foci infiltrating to a depth of more than 5 mm \u003csup\u003e[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.OEC is the most common clinical type, accounting for 17\u0026ndash;44% of all endometriosis \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. The American Society for Reproductive Medicine (ASRM) staging system is commonly used: stage I microscopic lesions, stage II mild, stage III moderate and stage IV severe. Diagnosis of endometriosis includes clinical and surgical diagnosis. Laparoscopy is a common means of diagnosing endometriosis [5], which is an invasive examination with high costs, surgical risks and the possibility of postoperative adhesion formation. In clinical practice, laparoscopy is more commonly used for the surgical treatment of endometriosis. Transvaginal ultrasound (TVUS) and magnetic resonance imaging (MRI) have high sensitivity and specificity for the diagnosis of endometriosis \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. However, delayed diagnosis of endometriosis is common and leads to exacerbation of the disease. Therefore, early or timely diagnosis of endosteopathy is of great importance for the management of the disease. Based on the above clinical problems, this paper proposes to establish a clinical diagnostic model for endosteopathy based on clinical features and basic examinations to provide alternative means and methods for timely diagnosis of endosteopathy.\u003c/p\u003e"},{"header":"1 Information and methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Information\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e1.1.1 Research Objectives\u003c/h2\u003e \u003cp\u003ePatients who underwent surgical treatment with pathologically confirmed diagnosis at Hainan Hospital affiliated to Hainan Medical College (formerly Hainan Provincial People's Hospital) from December 2016 to June 2022 were selected, with 308 cases in the endometriosis group and 317 cases in the non-endometriosis group as the control group, for a total of 625 cases as modelling data. In addition, 41 cases of endometriosis and 28 cases of non-endometriosis were used as validation data. The American Fertility Society (AFS) staging method was used to stage the endometriosis group. The study was approved by the Ethics Committee of Hainan Provincial People's Hospital. See Tables\u0026nbsp;\u0026lt;link rid=\"tb2\"\u0026gt;\u0026lt;link rid=\"tb2\"\u0026gt;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u0026lt;/link\u0026gt;\u0026lt;/link\u0026gt;\u003c/span\u003e\u0026ndash;\u0026lt;link rid=\"tb2\"\u0026gt;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u0026lt;/link\u0026gt;\u003c/span\u003e and \u0026lt;link rid=\"tb2\"\u0026gt;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u0026lt;/link\u0026gt;\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e1 Number and disease composition of endometriosis group and control group (test set)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003edisease group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecomparison group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDIE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003euterine fibroids\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDIE combined OEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSPE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ebenign ovarian cysts\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e207\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSPE combined uterine fibroids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSPE combined benign ovarian cysts\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSPE combined OEC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOEC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e149\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePelvic inflammatory disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOEC combined uterine fibroids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e45\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOEC combined benign ovarian cysts\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOEC combined adenomyosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e30\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStage I/II\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e48\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStage Ⅲ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e129\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStage Ⅳ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e130\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e2 The number and clinical data of endometriosis group and control group (verification set)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003evalidation set\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003edisease group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003econtrol subjects\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDIE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSPE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOEC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003euterine fibroids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ebenign ovarian cysts\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePelvic inflammatory disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e33(28\u0026ndash;43)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e37(30.5\u0026ndash;42)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptoms of menstrual cramps\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e14(82.4%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3(17.6%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProgressive exacerbation of symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e5(83.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1(16.7%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003emenstrual abnormality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3(33.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6(66.7%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003einfertility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e5(62.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3(37.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCA125\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e81.3(42.5-175.85)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e12.8(9.625\u0026ndash;17.35)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e165.8(152-197.55)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e188.5(166.05-224.35)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e57.5(44.85\u0026ndash;66.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e59.2(59.97\u0026ndash;65.32)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of clinical data and laboratory indexes between endometriosis group and control group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003edisease group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecomparison group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ/z values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32(27\u0026ndash;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(28\u0026ndash;43)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.828\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptoms of menstrual cramps\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143(46.4%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(10.1%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102.297\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProgressive exacerbation of symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e58(18.8%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4(1.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e53.964\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003edifficulty in urinating and defecating\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6(1.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4(1.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.133\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.715\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003emenstrual abnormality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e12(3.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e36(11.4%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e12.263\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003edyspareunia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3(1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0(0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.399\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.237\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eabdominal and lower back pain\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e45(14.6%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e41(12.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.370\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.543\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003einfertility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e32(10.4%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e10(3.2%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e13.045\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCA125\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e50.05(27.97\u0026ndash;97.1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e17.4(12.85\u0026ndash;26.55)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-14.084\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMONOP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7.2(6.1\u0026ndash;8.47)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.2(6.1\u0026ndash;8.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-0.186\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.852\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMONON\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.46(0.37\u0026ndash;0.56)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.45(0.375\u0026ndash;0.53)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-1.433\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.152\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePLT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e281(240.25\u0026ndash;325.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e276(240\u0026ndash;317)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-1.279\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.201\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMPV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10.25(9.7\u0026ndash;10.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e10.1(9.6\u0026ndash;10.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-0.904\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.366\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePDW\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11.5(10.5\u0026ndash;12.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e11.4(10.4\u0026ndash;12.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-0.083\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.933\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.28(0.25\u0026ndash;0.34)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.28(0.25\u0026ndash;0.32)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-2.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e162.25(144.07-179.35)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170.8(150.65\u0026ndash;192.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-3.088\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e49.75(43-58.02)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e51.8(43.55\u0026ndash;62.15)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-2.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.1.2 Inclusion and exclusion criteria\u003c/h2\u003e \u003cp\u003e Inclusion criteria: surgery in our hospital and confirmed by postoperative pathology; fulfilling the criteria of the Endometriosis Diagnosis and Treatment Guidelines; complete medical history; no use of hormonal drugs in the 6 months prior to surgery. Exclusion criteria: severe chronic diseases combined with systemic diseases such as heart, brain, lung, kidney, liver failure and thyroid dysfunction in the case and control groups; malignant tumours and diseases of the immune system; patients with severe psychiatric disorders; cases with endometriosis in the control group; and incomplete medical history data. The hospital's electronic medical record system was used to search for the medical records of the study population: admission and discharge records, medical course records, surgical records, laboratory and imaging data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Methods\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e1.2.1 Information collection\u003c/h2\u003e \u003cp\u003eClinical data and some laboratory findings were collected from patients in the endometriosis group and the control group: age, dysmenorrhoea with or without progressive worsening, dyspareunia, menstrual abnormalities, dyspareunia, lumbar and abdominal pain, infertility, carbohydrate antigen 125 (CA125), monocyte percentage(MONOP), monocyte absolute value(MONON), platelet(PLT), mean platelet volume (MPV), Platelet Volume Distribution Width (PDW), platelet volume ratio (PCT), lactate dehydrogenase (LDH), alkaline phosphatase (ALP). Valuable indicators were screened by comparing the two groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e1.2.2 Constructing diagnostic models and model validation\u003c/h2\u003e \u003cp\u003eIndicators with statistically significant differences were first subjected to one-way analysis, and those with statistically significant differences in one-way analysis (P\u0026thinsp;\u0026lt;\u0026thinsp;0.1) were subjected to multifactorial logistic regression analysis, which was used to construct the diagnostic model. Goodness of fit and discrimination of the model were also assessed. The kappa consistency test was used to verify the predictive power of the model on data from 69 cases in the validation set.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e1.3 Statistical treatment\u003c/h2\u003e \u003cp\u003eData were analysed using SPSS 25.0 statistical software. Measurements were expressed as median and interquartile range, and comparisons between the two groups were made using the Mann-Whitney U rank-sum test; count data were expressed as cases (%), and comparisons were made using the χ2 test. Binary logistic regression analysis was used to screen for independent risk factors and to construct a prediction model, and the goodness of fit of the model was assessed by the Hosmer-Lemeshow (H-L) test. The predictive ability of the model was determined by plotting the receiver operating characteristic (ROC) curve using MedCal 2.0. p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"2 Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Comparison of clinical characteristics between the two groups\u003c/h2\u003e \u003cp\u003eDifferences in clinical data between the two groups were compared by χ2 or rank sum test. The differences between the two groups in terms of age, dysmenorrhoea symptoms, progressive worsening of symptoms, menstrual abnormalities, infertility, CA125, PCT, LDH, ALP were statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); and there was no statistically significant difference between the two groups in terms of dysuria, dyspareunia, dyspareunia, lumbar and abdominal pain, MONOP, MONON, PLT, MPV, PDW (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). See Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Logistic regression analysis of diagnostic indicators of endomorphism and their constructed models\u003c/h2\u003e \u003cp\u003eStatistically different indicators were subjected to univariate analysis of variance Indicators with P\u0026thinsp;\u0026lt;\u0026thinsp;0.1 were used as independent variables, i.e. age, dysmenorrhoea symptoms, progressive worsening of symptoms, menstrual abnormalities, infertility, CA125, PCT, LDH, ALP. Multifactorial logistic regression equations were constructed using the forward stepwise method. The results showed that there was a statistically significant higher risk of developing endometriosis with higher CA125 [OR\u0026thinsp;=\u0026thinsp;1.023 (95% CI: 1.016\u0026ndash;1.029)], dysmenorrhoea symptoms [OR\u0026thinsp;=\u0026thinsp;3.467 (95% CI: 2.052\u0026ndash;5.859)], progressive worsening of symptoms [OR\u0026thinsp;=\u0026thinsp;4.501 (95% CI: 1. Higher LDH [OR\u0026thinsp;=\u0026thinsp;0.993 (95% CI: 0.987\u0026ndash;0.999)], ALP [OR\u0026thinsp;=\u0026thinsp;0.977 (95% CI: 0.962\u0026ndash;0.991)] were statistically associated with a lower risk of developing endogamy (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A diagnostic model for endogamy was constructed as follows: Logistic (P) = (1.085)\u0026thinsp;+\u0026thinsp;1.243 \u0026times; dysmenorrhoea\u0026thinsp;+\u0026thinsp;1.504 \u0026times; progressive worsening of symptoms + (-1.461) \u0026times; menstrual abnormality\u0026thinsp;+\u0026thinsp;0.023 \u0026times; CA125 + (-0.007) \u0026times; LDH + (-0.024) \u0026times; ALP. See Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParameters of Logistic regression analysis for modeling endometriosis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003estandard error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptoms of menstrual cramps\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.243\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.579\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.467\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.052\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.859\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eprogressive exacerbation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.504\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.288\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.501\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.389\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.584\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003emenstrual abnormality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-1.461\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.455\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e10.307\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.232\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.095\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.566\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003einfertility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.421\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5.88\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.776\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1.216\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e6.335\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCA125\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e45.884\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1.029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e4.807\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.993\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.987\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.999\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e9.691\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.977\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.962\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.991\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003econstant\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.085\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.633\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.942\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.086\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.959\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Validation of the predictive efficacy of the diagnostic model for endometriosis\u003c/h2\u003e \u003cp\u003eThe H-L validation results showed P\u0026thinsp;=\u0026thinsp;0.103, indicating that the model was well fitted. The area under the ROC curve of this diagnostic model was 0.846 (95% CI: 0.815\u0026ndash;0.873), and the optimal critical value of 0.478 was selected when the Yoden index was 0.5498, at which point the sensitivity of the ROC curve was 69.81 and the specificity was 85.17 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the clinical model validation, a further 69 patients in this study were selected and included in the model formula, when the cut-off value\u0026thinsp;\u0026ge;\u0026thinsp;0.478 the diagnosis of endometriosis was considered, kappa\u0026thinsp;=\u0026thinsp;0.659 (P\u0026thinsp;=\u0026thinsp;0.000), suggesting that the diagnosis was basically consistent with the pathological findings. See Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eValidation set results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCase results\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003etotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel results\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003enegatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003etotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3 Discussion","content":"\u003cp\u003eEMs is a common condition in women of reproductive age, with a prevalence of approximately 10% \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. The main clinical manifestations are infertility, dysmenorrhoea, chronic pelvic pain, dyspareunia and painful bowel movements. It has a high recurrence rate and an infertility rate that can be as high as 50%, causing great harm to women's reproductive health and a socioeconomic burden \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Despite the high prevalence, not everyone is aware of the disease; there is a delay of up to 9 years between symptom onset and diagnosis \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, and the majority of patients may be misdiagnosed and not effectively treated. This allows the disease to progress, causing great physical and psychological harm to patients. Early diagnosis, early treatment, improved quality of life and improved reproductive function, therefore finding more efficient and reliable diagnostic methods is one of the main research focuses in EM. Currently, laparoscopy is the gold standard for diagnosing EMs. This procedure is invasive, carries some surgical risk and requires an experienced physician \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e],\u003c/sup\u003e and reliance on laparoscopy to diagnose EMs may delay the timing of this complex disease \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Transvaginal ultrasound is most sensitive for OEC, but less sensitive for mild forms, SPE and DIE, and is dependent on personal experience with the procedure \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Magnetic resonance imaging is sensitive for DIE, but is more expensive. The prevalence of EM is high (45%-50%) in patients with chronic pelvic pain and in asymptomatic women, and the absence of a clearly visible lesion or negative histology does not exclude EM, so clinical symptoms may be more helpful in making a diagnosis than exact lesions \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. The development of a diagnostic model based on clinical symptoms and simple laboratory indicators for rapid and effective screening to provide a basis for further diagnosis and treatment \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e was the main aim of our present study.\u003c/p\u003e \u003cp\u003eWe selected dysmenorrhoea, progressive exacerbation of symptoms, menstrual abnormalities, infertility, CA125, LDH, ALP, dysuria, dyspareunia, dyspareunia, lumbar and abdominal pain, MONOP, MONON, PLT, MPV, PDW, PCT as diagnostic indices and constructed the diagnostic model using one-way and multifactorial logistic regression analysis. Unfortunately, in the results of our study: dysuria, dyspareunia, low back and abdominal pain, MONOP, MONON, PLT, MPV, PDW were not statistically different from the control group (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05); the difference between the menstrual abnormalities endometriosis group was lower than that of the control group was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Dysmenorrhoea, progressive worsening of symptoms, infertility and CA125 were independent risk factors for EM.\u003c/p\u003e \u003cp\u003eThere were no statistically significant differences between the case and control groups for difficulty with bowel and urinary functions, difficulty with sexual intercourse, and back and abdominal pain. This may be due to the small number of positive cases in the data from the trials we included to compare the differences.\u003c/p\u003e \u003cp\u003eInflammation can trigger the recruitment of monocytes from the bone marrow into the peripheral blood, where they infiltrate the tissues and develop into macrophages, which differentiate in the diseased tissue into pro-inflammatory M1 macrophages (which mainly secrete pro-inflammatory factors, initiate inflammation, play an important role in the early stages of inflammation, remove cellular debris of pathogenic microorganisms, etc.) and anti-inflammatory M2 macrophages (which secrete pro-inflammatory factors, initiate inflammation, play an important role in the early stages of inflammation, remove cellular debris of pathogenic microorganisms, etc.). ) and anti-inflammatory M2 macrophages (which inhibit inflammatory responses, tissue repair, pro-fibrotic activity, and are able to induce immune tolerance and fibrotic activity. and are able to induce immune tolerance and angiogenesis) \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.Antonio Simone Lagan et al. reported a trend towards a progressive decrease in M1 macrophages and a gradual increase in M2 macrophages from stage I to stage IV in endometriosis. This trend contributes to the formation of a pro-inflammatory microenvironment in the early stages of the disease and the development of pro-fibrotic activity in the later stages \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. The important role of monocytes in the development of EMs has been reported in the literature \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, so they were included in our study index. However, in our results, the difference between the MONOP and MONON groups was not statistically significant when compared. This may be due to the fact that we did not select monocytes from the lesion site, but monocytes from peripheral blood, and only analysed the total number of monocytes and not their subtypes. A significant increase in peritoneal M2-type macrophages in patients with ovarian endometriotic cysts has been reported previously and is directly proportional to disease severity \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCyclic bleeding of endometriosis lesions leads to repeated tissue damage and repair, activating platelets and immune cells in the lesion microenvironment, causing the ectopic lesion to undergo epithelial-mesenchymal transition and fibroblast-myofibroblast transition, and ultimately fibrosis \u003csup\u003e[\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Platelets can induce endothelial cell proliferation, which allows endothelial cells to acquire new capabilities such as contraction, migration, invasion and collagen production. Platelets play a key role in the progression of ectopic foci and fibrosis formation and could be a potential target for the treatment of endometriosis \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Unfortunately, in our study, platelets did not differ between the two groups, which may be related to platelet physiological processes. Platelets are activated by a complex activation process that starts with the formation of a tightly packed 'core' of mainly fibrin-rich, P-selectin-positive platelets at the site of injury and a 'shell' of loose platelets that are arranged outside the core by attachment and adhesion. The platelets are then recruited to the circulating platelets. Circulating platelets are further recruited to act at the beginning of the lesion \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Therefore, platelets at the lesion site may be more variable than in peripheral blood \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDysmenorrhoea is divided into primary dysmenorrhoea PD (Primary Dysmenorrhoea PD) and secondary dysmenorrhoea SD (Secondary Dysmenorrhoea SD).PD usually occurs 6\u0026ndash;12 months after the onset of menstruation, occurs before or at the start of menstruation, lasts 8\u0026ndash;72 hours, and is most severe on the first or second day of menstruation. Secondary dysmenorrhoea is caused by other conditions such as endometriosis, adenomyosis and pelvic inflammatory disease. It usually occurs 2\u0026ndash;5 years after the onset of menstruation and can be associated with dyspareunia, chronic pelvic pain and infertility. Endometriosis is the most common cause of secondary dysmenorrhoea \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.EMs is a well-recognised chronic inflammatory disease that can lead to increased production of pro-inflammatory cytokines, prostaglandin overproduction, peripheral and central sensitisation and an abnormal stress response, resulting in secondary dysmenorrhoea with severe symptoms \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Progressive worsening of symptoms should raise a high index of suspicion for EMs, and the severity of primary dysmenorrhoea does not increase over time. Chronic inflammation of the peritoneal cavity in patients with EMs leads to ovarian dysfunction, altered fertilisation, pelvic adhesions affecting conception and increasing the likelihood of infertility\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e, and the infertility rate can be as high as 50%, and infertility is a good diagnostic indicator. CA125 is a well-established tumour marker produced in the epithelial cells of the body cavities during embryonic development, and its use in the diagnostic role of ovarian cancer has been widely accepted, and it is also elevated to varying degrees in the serum of patients with EMs \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e, with particularly high sensitivity in stage III/IV. For CA125\u0026thinsp;\u0026gt;\u0026thinsp;30U/mL, the sensitivity was 52.4% (95% CI 37.9\u0026ndash;66.4%), the specificity was 92.7% (95% CI 89.4\u0026ndash;95.1%), and for CA125\u0026thinsp;\u0026gt;\u0026thinsp;35.0U/mL, the sensitivity was 0.40 (95% CI 0.32\u0026ndash;0.49), the specificity was 0.91 (95% CI 0.88\u0026ndash;0.94) \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. 0.94) \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Numerous studies have recommended the use of CA125 to aid in the diagnosis of patients with EMs \u003csup\u003e[\u003cspan additionalcitationids=\"CR25 CR26 CR27\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e, but sensitivity is low when used alone. Lactate dehydrogenase, which is involved in the last step of glycolysis and plays an important role in metabolic reactions, is widely distributed in a variety of organs and tissues and has been used as an important diagnostic marker for common diseases such as cancer, infectious diseases and tuberculosis. It plays a key role in the clinical diagnosis of a variety of common and rare diseases, and the abnormal levels of isoforms of this enzyme are important biomarkers for various diseases \u003csup\u003e[\u003cspan additionalcitationids=\"CR30 CR31 CR32 CR33\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. A study by Yijuan Kang et al. indicated that the expression of the subunit of lactate dehydrogenase (LDHB) was significantly decreased in the cyst wall tissue of ovarian endometriotic cysts, suggesting an increase in glycolysis, which may be related to the tumour-like invasive and metastatic behaviour of endometriosis \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e.ALP is a metalloproteinase that catalyses the hydrolysis and transfer of phosphate groups under alkaline conditions. Four alkaline phosphatase isoenzymes are present in the human body: tissue non-specific alkaline phosphatase (TNALP), intestinal-type alkaline phosphatase (IALP), placental-type alkaline phosphatase (PALP) and germ cell alkaline phosphatase (GCAP). IALP, PALP and germ cell ALP are expressed in specific tissues (duodenum, syncytiotrophoblast and testis respectively), whereas TNALP is expressed in various tissues \u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. A study by Jae O. Kang et al. showed that the total alkaline phosphatase level was higher in the endometriosis group than in the control group, but the elevation could be due to a specific isoform, and because of the extremely low levels of the serum species, it was suggested that specific assays should be used to aid in the diagnosis of endometriosis \u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e. For the first time, we used alkaline phosphatase as an indicator to construct a diagnostic model, but our findings were different from previous ones \u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e. This may be due to the bias caused by detecting the total serum level without detecting the specific subtype.\u003c/p\u003e \u003cp\u003eThe diagnostic model of EMs constructed according to the above risk factors has a good fit and diagnostic efficacy, and can be used as an auxiliary tool for the preliminary clinical diagnosis of EMs. The proposed interventions for the proposed EMs are: (1) increase knowledge of EMs in key populations such as dysmenorrhoea and infertility, especially in adolescents and women of reproductive age; (2) pay attention to changes in serological indices; (3) provide early pharmacological intervention, if necessary; (4) promote active reproduction in women with reproductive needs.\u003c/p\u003e \u003cp\u003eWe included all patients with pathological findings after surgery and excluded the possibility of including patients with endogamy in the control group. However, the data in our study were based on a single-centre retrospective study and may have been inadequately collected. For example, for dysmenorrhoea, we made a simple distinction between presence and absence without further consideration of the type of pain (tingling, burning, aching, etc.) and the type of pain (e.g. dysmenorrhoea, non-cyclic pelvic pain, dyspareunia, etc.) as well as changes with the menstrual cycle. These deficiencies will be improved in our subsequent studies.\u003c/p\u003e \u003cp\u003eThe diagnostic model we have constructed for endometriosis has a good fit and discriminatory ability, and the indicators are easy to obtain, making it a reliable and practical diagnostic tool.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Hainan General Hospital.The data used in this study was anonymized before it s use .\u003c/p\u003e\n\u003cp\u003eOur study was a retrospective analysis and therefore no informed consent waiver was obtained from Ethics Committee of Hainan General Hospital. All patients were older than 18 years.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from Top Talent of Changzhou\u0026nbsp;\u0026ldquo;The 14th Five-Year Plan\u0026rdquo;\u0026nbsp;High-Level Health Talents Training Project (2022CZBJ074), the maternal and child health key talent project of Jiangsu Province (RC202101), the maternal and child health research project of Jiangsu Province (F202138)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWenwen Zhang , Qiucheng Jia， Huimin Tang:Conceptualization、Methodology、Writing - Original Draft： Yao Chen, Wulin Shan:Methodology、Software、Validation、Formal analysis, Jiming Chen, Genhai Zhu :Writing - Review \u0026amp; Editing、Visualization、Supervision、Project administration、Funding acquisition\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSerdar E, Bulun MD. Endometriosis[J]. N Engl J Med,2009, 360: 268-279.\u003c/li\u003e\n\u003cli\u003eGiudice LC. Clinical practice. Endometriosis[J]. N Engl J Med,2010, 362(25): 2389-2398.\u003c/li\u003e\n\u003cli\u003eTaylor HS, Kotlyar AM, Flores VA. Endometriosis is a chronic systemic disease: clinical challenges and novel innovations[J]. The Lancet,2021, 397(10276): 839-852.\u003c/li\u003e\n\u003cli\u003eLi XY, Chao XP, Leng JH, et al. Risk factors for postoperative recurrence of ovarian endometriosis: long-term follow-up of 358 women[J]. J Ovarian Res,2019, 12(1): 79.\u003c/li\u003e\n\u003cli\u003eDunselman GA, Vermeulen N, Becker C, et al. ESHRE guideline: management of women with endometriosis[J]. Hum Reprod,2014, 29(3): 400-412.\u003c/li\u003e\n\u003cli\u003eRogers PA, Adamson GD, Al-Jefout M, et al. Research Priorities for Endometriosis[J]. Reprod Sci,2017, 24(2): 202-226.\u003c/li\u003e\n\u003cli\u003eRolla E. Endometriosis: advances and controversies in classification, pathogenesis, diagnosis, and treatment[J]. F1000Res,2019, 8: 529.\u003c/li\u003e\n\u003cli\u003eZondervan KT, Becker CM, Missmer SA. Endometriosis[J]. N Engl J Med,2020, 382(13): 1244-1256.\u003c/li\u003e\n\u003cli\u003eLang JH. History, current status and development of the understanding of endometriosis[J]. Chinese Journal of Practical Gynaecology and Obstetrics,2020, 36(03): 193-196.\u003c/li\u003e\n\u003cli\u003eJakubzick CV, Randolph GJ, Henson PM. Monocyte differentiation and antigen-presenting functions[J]. Nat Rev Immunol,2017, 17(6): 349-362.\u003c/li\u003e\n\u003cli\u003eKratofil RM, Kubes P, Deniset JF. Monocyte Conversion During Inflammation and Injury[J]. Arterioscler Thromb Vasc Biol,2017, 37(1): 35-42.\u003c/li\u003e\n\u003cli\u003eLagan\u0026agrave; AS, Salmeri FM, Ban Frangež H, et al. Evaluation of M1 and M2 macrophages in ovarian endometriomas from women affected by endometriosis at different stages of the disease[J]. Gynecol Endocrinol,2020, 36(5): 441-444.\u003c/li\u003e\n\u003cli\u003eSturlese E, Salmeri FM, Retto G, et al. Dysregulation of the Fas/FasL system in mononuclear cells recovered from peritoneal fluid of women with endometriosis[J]. J Reprod Immunol,2011, 92(1-2): 74-81.\u003c/li\u003e\n\u003cli\u003eSalmeri FM, Lagan\u0026agrave; AS, Sofo V, et al. Behavior of tumor necrosis factor-\u0026alpha; and tumor necrosis factor receptor 1/tumor necrosis factor receptor 2 system in mononuclear cells recovered from peritoneal fluid of women with endometriosis at different stages[J]. Reprod Sci,2015, 22(2): 165-172.\u003c/li\u003e\n\u003cli\u003eGuo SW, Ding D, Shen M, et al. Dating Endometriotic Ovarian Cysts Based on the Content of Cyst Fluid and its Potential Clinical Implications[J]. Reprod Sci,2015, 22(7): 873-883.\u003c/li\u003e\n\u003cli\u003eZhang Q, Duan J, Liu X, et al. Platelets drive smooth muscle metaplasia and fibrogenesis in endometriosis through epithelial-mesenchymal transition and fibroblast-to-myofibroblast transdifferentiation[J]. Mol Cell Endocrinol,2016, 428: 1-16.\u003c/li\u003e\n\u003cli\u003eBrosens IA. Endometriosis--a disease because it is characterized by bleeding[J]. Am J Obstet Gynecol,1997, 176(2): 263-267.\u003c/li\u003e\n\u003cli\u003eYan D, Liu X, Xu H, et al. Platelets induce endothelial-mesenchymal transition and subsequent fibrogenesis in endometriosis[J]. Reprod Biomed Online,2020, 41(3): 500-517.\u003c/li\u003e\n\u003cli\u003eHolinstat M. Normal platelet function[J]. Cancer Metastasis Rev,2017, 36(2): 195-198.\u003c/li\u003e\n\u003cli\u003eDing D, Liu X, Duan J, et al. Platelets are an unindicted culprit in the development of endometriosis: clinical and experimental evidence[J]. Hum Reprod,2015, 30(4): 812-832.\u003c/li\u003e\n\u003cli\u003eClemenza S, Vannuccini S, Capezzuoli T, et al. Is primary dysmenorrhea a precursor of future endometriosis development?[J]. Gynecol Endocrinol,2021, 37(4): 287-293.\u003c/li\u003e\n\u003cli\u003eChapron C, Marcellin L, Borghese B, et al. Rethinking mechanisms, diagnosis and management of endometriosis[J]. Nat Rev Endocrinol,2019, 15(11): 666-682.\u003c/li\u003e\n\u003cli\u003eCoutinho LM, Ferreira MC, Rocha ALL, et al. New biomarkers in endometriosis[J]. Adv Clin Chem,2019, 89: 59-77.\u003c/li\u003e\n\u003cli\u003eO\u0026apos;Shaughnessy A, Check JH, Nowroozi K, et al. CA 125 levels measured in different phases of the menstrual cycle in screening for endometriosis[J]. Obstet Gynecol,1993, 81(1): 99-103.\u003c/li\u003e\n\u003cli\u003eDai Kemiao. Clinical value of serum cancer antigen 125, neutrophil activating peptide-78 and monocyte chemotactic protein-1 in the diagnosis of endometriosis[J]. China Maternal and Child Health, 2021, 36(24): 5677-5679. \u003c/li\u003e\n\u003cli\u003eTang T, Lai H, Huang X, et al. Application of serum markers in diagnosis and staging of ovarian endometriosis[J]. J Obstet Gynaecol Res,2021, 47(4): 1441-1450.\u003c/li\u003e\n\u003cli\u003eLI Na, YAN Fu-Tian. Application value of combined ultrasound and CA125 in the diagnosis of ovarian endometriotic cysts[J]. Tibetan Medicine,2022, 43(03): 25-28.\u003c/li\u003e\n\u003cli\u003eZHU Xiaoqin, QIAN Jin, WANG Yongxia, et al. Expression of COX-2 and MMP-14 and correlation with serum CA125 in endometriosis[J]. Chinese Journal of Family Planning,2022, 30(03): 668-671.\u003c/li\u003e\n\u003cli\u003eKhan AA, Allemailem KS, Alhumaydhi FA, et al. The Biochemical and Clinical Perspectives of Lactate Dehydrogenase: An Enzyme of Active Metabolism[J]. Endocr Metab Immune Disord Drug Targets,2020, 20(6): 855-868.\u003c/li\u003e\n\u003cli\u003eDi Peipei, Xiao Wenrong, Lv Huifen, et al. Evaluation of cerebrospinal fluid heparin-binding protein, lactate dehydrogenase, and ortho-pentameric protein 3 assays for the diagnosis and prognosis of intracranial infections[J]. Chinese Journal of Health Inspection,2022, 32(19): 2389-2393.\u003c/li\u003e\n\u003cli\u003eZhu Ying, Hong Hui, Zhang Yu, et al. Analysis of the diagnostic value of lactate dehydrogenase and D-dimer assays for Mycoplasma pneumoniae pneumonia[J]. China Medical Innovation, 2022, 19(15): 42-45. \u003c/li\u003e\n\u003cli\u003eLU Yanxing. Correlation analysis between preoperative lactate dehydrogenase/albumin ratio and prognosis in breast cancer[J]. Jilin Medical Science,2022, 43(09): 2522-2524. \u003c/li\u003e\n\u003cli\u003eWANG Yun, NIU Hua, FANG Hao Hui. Prognostic value of C-reactive protein/clear protein ratio of lactate dehydrogenase in patients with non-small cell lung cancer[J]. Anhui Medicine,2022, 43(08): 912-917. \u003c/li\u003e\n\u003cli\u003eCHEN Pengjuan, LU Shaobei, HAO Yingying. The value of combined ADA and LDH testing in the diagnosis and disease assessment of pulmonary tuberculosis[J]. Quality Safety and Inspection,2020, 30(06): 142-145. \u003c/li\u003e\n\u003cli\u003eKang Yijuan. Correlation study of LDHB expression in endometriosis and its significance[D]. Huazhong University of Science and Technology,2013.\u003c/li\u003e\n\u003cli\u003eHaarhaus M, Brandenburg V, Kalantar-Zadeh K, et al. Alkaline phosphatase: a novel treatment target for cardiovascular disease in CKD[J]. Nat Rev Nephrol,2017, 13(7): 429-442.\u003c/li\u003e\n\u003cli\u003eWU Yi, TANG Shenhong, YU Xia. Relationship between serum CRP, IG and ALP levels and the condition and prognosis of children with MPP[J]. Journal of Molecular Diagnosis and Therapy,2022, 14(09): 1566-1569. \u003c/li\u003e\n\u003cli\u003eLI Sirong, KONG Lingchao, LI Genhai, et al. Expression and clinical significance of serum ApoA, LDH and ALP in chronic heart failure[J]. Journal of Molecular Diagnosis and Therapy,2022, 14(04): 697-700. \u003c/li\u003e\n\u003cli\u003eLI Yanqiu, LIU Peiming, FAND Sheng. Correlation between preoperative serum r-GT and ALP levels and the efficacy of transcatheter hepatic artery chemoembolisation in patients with advanced hepatocellular carcinoma[J]. Journal of Sichuan North Medical College,2022, 37(07): 898-901+913. \u003c/li\u003e\n\u003cli\u003eZong Yi, Wang Jia. Clinical value of serum 5\u0026apos;NT, LAP, ALP and GGT tests in liver diseases[J]. Medical Food Therapy and Health,2022, 20(16): 193-195. \u003c/li\u003e\n\u003cli\u003eMA Lijuan, WANG Yun, LI Dianming. Analysis of the correlation and diagnostic value of serum CEA, CYFRA21-1, ALP, ALB and KPS score in lung cancer patients[J]. Laboratory Medicine and Clinics,2022, 19(04): 454-458.\u003c/li\u003e\n\u003cli\u003eYU Yan, YANG Shufang, SHEN Dongmei. Correlation between serum ALB, TP, PLT, ALP, LDH and D-D levels and the severity of preeclampsia[J]. Practical Gynaecological Endocrinology Electronic Journal,2021, 8(21): 24-26. \u003c/li\u003e\n\u003cli\u003eKang JO, Hudak WA, Crowley WJ, et al. Placental-type alkaline phosphatase in peritoneal fluid of women with endometriosis[J]. Clin Chim Acta,1990, 186(2): 285-294.\u003c/li\u003e\n\u003cli\u003eTrapero C, Jover L, Fern\u0026aacute;ndez-Montol\u0026iacute; ME, et al. Analysis of the ectoenzymes ADA, ALP, ENPP1, and ENPP3, in the contents of ovarian endometriomas as candidate biomarkers of endometriosis[J]. Am J Reprod Immunol,2018, 79(2): \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Endometriosis, Diagnosis model, Dysmenorrhea, CA125","lastPublishedDoi":"10.21203/rs.3.rs-3890783/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3890783/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eScreen the relevant diagnostic indicators of endometriosis, build a diagnostic model and verify it, so as to provide a scientific basis for diagnosis and differentiation.zig.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod(s)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 625 patients with pathologically confirmed endometriosis were selected from December 2016 to June 2022 in Hainan Provincial people's Hospital. 308 patients with endometriosis were selected as case group and 317 patients without endometriosis as control group. There were 41 cases in the case group and 28 cases in the control group. The clinical characteristics and laboratory indexes of patients in the case group and the control group were compared: age, dysmenorrhea, progressive aggravation of symptoms, dysuria, abnormal menstruation, difficulty in sexual intercourse, low back and abdominal pain, infertility, carbohydrate antigen 125, monocyte percentage, monocyte absolute value, platelet, mean platelet volume, platelet volume distribution width, platelet volume ratio, lactate dehydrogenase, alkaline phosphatase. The independent risk factors were screened by binary Logistic regression analysis and the prediction model was constructed. Hosmer-Lemeshow was used to test the goodness of fit of the model and the subject working characteristic curve was used to judge the prediction efficiency of the model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult(s)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were significant differences in age, dysmenorrhea, progressive aggravation of symptoms, abnormal menstruation, infertility, CA125, PCT, LDH and ALP between the two groups. The higher the CA125, the higher the risk of endometriosis, with statistical significance [OR = 1.023 (95% CI:1.016–1.029)], dysmenorrhea symptoms [OR = 3.467 (95% CI:2.052–5.859)], progressive symptoms [OR = 4.501 (95% CI:1.389–14.584)] and infertility [OR = 2.776 (95% CI:1.216–6.335)]. The higher the risk of endometriosis. The higher the LDH [OR = 0.993 (95% CI:0.987–0.999)] and the higher the ALP [OR = 0.977 (95% CI:0.962–0.991)], the lower the risk of endometriosis. The constructed model was verified by Hmurl and the result showed that P = 0.103, which suggested that the model fitted well. When the area under the model curve was 0.846 (95%CI:0.815–0.873) and the Jordan index was 0.5498, the best critical value was 0.478, the sensitivity was 69.81 and the specificity was 85.17.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion(s)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe model has good degree of fit and distinguishing ability, and can be used as an auxiliary means.\u003c/p\u003e","manuscriptTitle":"Clinical diagnosis model Construction of endometriosis based on clinical data*","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-28 16:29:50","doi":"10.21203/rs.3.rs-3890783/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9fd0232a-cdb9-4ee2-9c04-6ceac982ed25","owner":[],"postedDate":"March 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-27T13:31:31+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-28 16:29:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3890783","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3890783","identity":"rs-3890783","version":["v1"]},"buildId":"B-jG_2CBjPDmsCi4Wdhf-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}