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 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 10  |  Issue : 2  |  Page : 73-77

The mathematical model to select an optimal treatment option for tubal pregnancy


Department of Obstetrics and Gynecological, Pyongyang Medical College, Kim Il Sung University, Pyongyang, Democratic People's Republic of Korea

Date of Web Publication24-Jan-2020

Correspondence Address:
Dr. Jin Jong Hwa
Ryonhwa-Dong, Central District, Pyongyang,
Democratic People's Republic of Korea
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/mjmsr.mjmsr_42_18

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  Abstract 


Background: Tubal pregnancy is one of the most common diseases in the gynecological department, and to conserve the reproductive ability and guarantee the quality of life, it is very important to select the prompt and correct treatment options. We studied to formulate the mathematical model to select optimal treatment option of tubal pregnancy and evaluate its effectiveness. Materials and Methods: Chi-square test and the analysis of quantization category II were used for the comparison of parameters between two groups. We underwent case–control study of 59 patients with medical treatment and 44 patients with surgical treatment in Pyongyang Maternity Hospital from October 2013 to February 2015. Results: We analyzed the anamnestic, subjective symptom, objective symptom parameters, compared the correlation coefficients, and defined 15 parameters. Conclusion: We assessed the appearance of parameters to select the treatment option of tubal pregnancy, and the sensitivity, specificity, and predictive value of the mathematical model were 93.2%, 90.9%, and 0.932, respectively.

Keywords: Mathematical model, treatment, tubal pregnancy


How to cite this article:
Hwa JJ, Yong KS, Son PU. The mathematical model to select an optimal treatment option for tubal pregnancy. Muller J Med Sci Res 2019;10:73-7

How to cite this URL:
Hwa JJ, Yong KS, Son PU. The mathematical model to select an optimal treatment option for tubal pregnancy. Muller J Med Sci Res [serial online] 2019 [cited 2020 Oct 21];10:73-7. Available from: https://www.mjmsr.net/text.asp?2019/10/2/73/276692




  Introduction Top


A tubal pregnancy can be treated medically or surgically, but the choice depends on several conditions.[1] In studies, methotrexate (MTX) was proven to be nonsurgical, spares the tube, and does not subject patients to surgical intervention.[2] Rigorous patient selection is the main factor in successful medical treatment.

In clinical medicine, the clinicians can select treatment options subjectively. However, to select the option more correctly and rapidly and to conserve the reproductive ability and guarantee the quality of life, objective method using a mathematical model is required.

We studied to formulate the mathematical model to select the prompt and correct treatment of tubal pregnancy and evaluate its effectiveness.


  Materials and Methods Top


Materials

The study group consisted of 59 tubal pregnancy women with medical treatment and the control group consisted of 44 tubal pregnancy women with surgical treatment who hospitalized in Pyongyang Maternity Hospital from October 2013 to February 2015.

Methods

In our research, we analyzed 51 parameters (these include menstrual period, parity, prior infertility, intrauterine device, prior tubal pregnancy, gynecologic diseases, pregnancy weeks, size of adnexal mass, amount of irregular bleeding, and culdocentesis.), and we underwent Chi-square test to assess the significant differences between the study and control groups, discarded some parameters that have no significant differences, and then collected the significant parameters to undergo the analysis of quantization category II.


  Results Top


The manifestation frequency of some parameters according to the treatment method

Anamnestic parameters

[Table 1] shows the manifestation frequency of anamnestic parameters according to the treatment method, and among anamnestic parameters, only in a prior tubal pregnancy, there was statistically significant difference (P< 0.05).
Table 1: Anamnestic parameters in the study and control groups

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Manifestation frequency of clinical symptoms

We compared the subjective symptoms between the study and control group, and there was a statistically significant difference in nausea (P< 0.05) [Table 2].
Table 2: Objective symptoms in the study and control groups

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Comparing the objective symptoms between the study and control groups, there were statistically significant differences in Blumberg's sign, posterior vaginal fornix tenderness, fluctuation, and posterior vaginal fornix distention (P< 0.05).

We compared the vital signs between the study and control groups, and there were significant differences in systolic blood pressure and diastolic blood pressure (P< 0.05), but no difference was found in body temperature, pulse rate, and respiratory rate [Table 3].
Table 3: Inspection in the study and control groups

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Comparing the inspection and pregnancy weeks between the study and control groups, there were statistically significant differences (P< 0.05).

Manifestation frequency of gynecological tests

We compared the size of adnexal mass, ultrasonography, vaginal discharge, blood test, culdocentesis, and human chorionic gonadotropin (hCG) test between the study and control groups, and there were significant differences in the size of adnexal mass, fluid in cul-de-sac of Douglas in ultrasound, amount of irregular bleeding, characteristics of vaginal discharge, hemoglobin, culdocentesis, and hCG measurement (P< 0.05).

Formulating of a mathematical model to select the treatment option

After assessing the appearance of 51 parameters, we discarded some parameters that have less significant differences between the study and control groups, and we used 15 parameters eventually. With those 15 parameters, we underwent the analysis of quantization category II to assess the correlation coefficient and regarded it as a mathematical model.

[Table 4] shows the result of the analysis of quantization category II.
Table 4: Regressive coefficient and correlation coefficient by parameters of the mathematical model

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From [Table 4], we formulated the mathematical model, and it is as follows.

Y = −0.55954X11+ 0.18894X12+ 0.15999X21− 0.47382X22+ 0.11309X31 − 0.31833X32+ 0.13499X41

−0.23945X42− 1.09431X43− 0.02997X51+ 0.17581X52− 0.05506X61+ 0.41757X62− 0.08848X71

+0.22577X72+ 0.00458X81+ 0.14766X82− 0.45753X83− 0.18957X91+ 0.23490X92− 0.01601X101

+0.21957X102+ 0.16891X111+ 0.18180X112+ 0.09004X113− 0.13361X114− 0.33396X115

−0.21299X116− 0.53260X117+ 0.13511X121− 0.40012X122+ 0.07496X131− 0.51206X132+ 0.91064X133

+0.73140X141+ 0.01714X142− 0.04940X143− 0.35754X144+ 0.23865X151+ 0.57599X152− 0.05001X153

Using this mathematical model, we developed “Computer Aided Treatment System” to select the prompt and correct treatment of tubal pregnancy.

To select the treatment choice, what you need is just input the parameters into the interface of “Computer Aided Treatment System,” and then, the system will calculate its functional value (Y) immediately and pass judgments. If the functional value is below the boundary value (−0.116895), surgical treatment is regarded, and if it is above the boundary value, medical treatment is preferential.

The effectiveness of the mathematical model

We estimated the sensitivity, specificity, and predictive value of the mathematical model, and the details are as [Table 5].
Table 5: Data for evaluating the treatment choice

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Sensitivity: 55/59 × 100 = 93.2 (%).

Specificity: 40/44 × 100 = 90.9 (%).

Predictive value: 55/(55 + 4) = 0.932.

The sensitivity of the mathematical model was 93.2%, specificity was 90.9%, and the predictive value was 0.932.

As the sensitivity, specificity, and predictive value have statistical significance, the mathematical model that we formulated can be used to select the treatment option of tubal pregnancy more accurate and faster.


  Discussion Top


Tubal pregnancy can be treated by medical or surgical treatment.[1] However, if the patient underwent surgical treatment, she may lose the reproductive ability; medical treatment is preferred by most if feasible.[3]

MTX is a folinic acid antagonist that inactivates dihydrofolate reductase resulting in the depletion of tetrahydrofolate, a cofactor essential for deoxyribonucleic acid and ribonucleic acid synthesis.[4],[5] It thus interferes with DNA synthesis, repair, and cellular replication. Actively proliferating tissue, such as trophoblast cells of a tubal pregnancy, is generally more sensitive to these effects of MTX.[5],[6]

In several studies, MTX was proven to be a cost-saving treatment for tubal pregnancy, which is nonsurgical and spares the  Fallopian tube More Details.[7],[8] Moreover, receiving MTX treatment does not subject patients to surgical intervention and the possible associated complications. Thus, at present, MTX is considered to be the treatment of choice for tubal pregnancy.[8],[9]

As MTX has been extensively studied as an alternate to surgical therapy, the doctors are in this way which is more economic in the conservation of reproductive ability, cost of surgery, and postoperative sequel and so on.[10]

Hemodynamically stable patients without active bleeding or signs of hemoperitoneum are candidates for medical therapy, and they should comply with follow-up care.[11] Absolute contraindications to medical therapy include breastfeeding, immunodeficiency, alcoholism, and hepatic/pulmonary/renal/hematological dysfunction, known sensitivity to MTX, blood dyscrasias, or peptic ulcer disease. Relative contraindications for MTX treatments include embryonic cardiac activity and a gestational sac of 3.5 cm or more.[12],[13]

It is clear that the main factor in successful medical treatment is rigorous patient selection.

In clinical medicine, the clinicians can select treatment options subjectively. However, to select the option more correctly and rapidly, the objective method using a mathematical model is required.

In our research, after assessed the appearance of 51 parameters, we discarded some parameters that have less significant differences between the study and control groups and eventually we used 15 parameters. With those 15 parameters, we underwent an analysis of quantization to assess the correlation coefficient and regarded it as mathematical model. The parameters include amount of irregular bleeding, prior tubal pregnancy, size of an adnexal mass, posterior vaginal fornix distention, culdocentesis, and pregnancy weeks. We developed “Computer-Aided Treatment System” with the use of 15 parameters, and using this; we would save more time and the better outcome.


  Conclusion Top


We clarified the significant parameters those are useful for our mathematical model; there include amount of bleeding, prior tubal pregnancy, culdocentesis, size of adnexal mass, weeks of gestation, posterior vaginal fornix distention, etc. With the use of 15 parameters, we developed the diagnostic program to select the treatment option of tubal pregnancy. The sensitivity of the mathematical model was 93.2%, specificity was 90.9% and predictive value was 0.932.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent forms. In the form, the patients have given their consent for their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published, and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Lawani OL, Anozie OB, Ezeonu PO. Ectopic pregnancy: A life-threatening gynecological emergency. International Journal of Women's Health 2013;5:515-21.  Back to cited text no. 1
    
2.
Rajiv B, Gala MD. Ectopic pregnancy. William's Gynecology. Sec. 1, Ch. 7. New York: McGraw-Hill Professional Publishing; 2008.  Back to cited text no. 2
    
3.
Tulandi T. Patient Information: Ectopic (Tubal) Pregnancy (Beyond the Basics); 2012. p. 1-5.  Back to cited text no. 3
    
4.
ACEP Clinical Policies Committee and Clinical Policies Subcommittee on Early Pregnancy American College of Emergency Physicians. Clinical policy: Critical issues in the initial evaluation and management of patients presenting to the emergency department in early pregnancy. Ann Emerg Med 2003;41:123-33.  Back to cited text no. 4
    
5.
Reece EA, Hobbins JC. Ectopic and Heterotopic Pregnancies, Clinical Obstetrics: The Fetus and Mother. Massachusetts: Blackwell Publishing Inc.; 2007. p. 161-76.  Back to cited text no. 5
    
6.
World Health Organization. Task force on intrauterine devices for fertility regulation. A multinational case-control study of ectopic pregnancy. Clin Reprod Fertil 2005;3:131-43.  Back to cited text no. 6
    
7.
Meagher SE. Ectopic Pregnancy, Ultrasound in Medicine and Biology, Monash Ultrasound for Women in Australia; 2006.  Back to cited text no. 7
    
8.
Wiznitzer A, Sheiner. E Ectopic and heterotopic pregnancies. Clinical Obstetrics. Oxford: Blackwell Publishing Inc.; 2007. p. 166-7.  Back to cited text no. 8
    
9.
da Costa Soares R, Elito J Jr., Han KK, Camano L. Endometrial thickness as an orienting factor for the medical treatment of unruptured tubal pregnancy. Acta Obstet Gynecol Scand 2004;83:289-92.  Back to cited text no. 9
    
10.
Stead LG, Behera SR. Ectopic pregnancy. J Emerg Med 2007;32:205-6.  Back to cited text no. 10
    
11.
Tulandi T. Methotrexate Treatment of Tubal and Interstitial Ectopic Pregnancy; 2012. p. 7.  Back to cited text no. 11
    
12.
Fu J, Wang C, Hu L. Can ectopic pregnancy become normal pregnancy? Med Hypotheses 2010;74:390.  Back to cited text no. 12
    
13.
Padubidri V. G., Shirish Daftary. Ectopic gestation. Shaw's Textbook of Gynecology. Elsevier India: New Delhi 2008. p. 238-54.  Back to cited text no. 13
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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