Predictive Model for the Non-Invasive Diagnosis of Endometriosis Based on Clinical Parameters
Abstract
:1. Introduction
2. Material and Methods
Statistics
3. Results
3.1. General Parameters
3.2. Dysmenorrhea
3.3. CPP and Dysuria (Painful Urination)
3.4. Dyschezia (Painful Defecation), Obstipation, and Diarrhea
3.5. Dyspareunia (Painful Intercourse)
3.6. Other Pain Parameters
3.7. PainDETECT and Pain Localization
3.8. Decision Tree and Prediction of Endometriosis
4. Discussion
4.1. Strengths and Weaknesses
4.2. Implications
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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No EM N = 92 | MD | EM N = 177 | MD | p Value | |
---|---|---|---|---|---|
Age (yrs), mean (SD) | 35.1 (8.8) | 0 | 34.3 (6.7) | 0 | 0.485 |
BMI, mean (SD) | 24.2 (4.9) | 1 | 24.2 (5.3) | 0 | 0.921 |
Age Menarche, mean (SD) | 13.1 (1.5) | 2 | 13.0 (1.5) | 2 | 0.698 |
Smoker (%) | 24 (26.1) | 0 | 52 (29.4) | 0 | 0.669 |
Allergies (%) | 43 (46.7) | 0 | 106 (60.6) | 2 | 0.038 |
Cycle duration in days (SD) | 27.5 (5.1) | 4 | 27.4 (5.5) | 8 | 0.689 |
Menstruation duration in days (SD) | 5.2 (1.9) | 3 | 6.1 (4.0) | 2 | 0.119 |
Irregular Cycle | 28 (31.5) | 3 | 55 (32.4) | 7 | 1.0 |
Abnormal Menses | 29 (34.1) | 7 | 61 (36.7) | 11 | 0.781 |
Use of analgesics (%) | 47 (51.1) | 0 | 143 (80.8) | 0 | 0.0001 |
Analgesics before menses (%) | 5 (13.2) | 0 | 9 (7.4) | 0 | 0.274 |
Analgesics during menses (%) | 27 (71.0) | 0 | 69 (56.6) | 0 | 0.113 |
Analgesics before/during menses (%) | 6 (15.8%) | 0 | 42 (34.4%) | 0 | 0.029 |
Analgesics before/during/after menses (%) | 0 (0%) | 0 | 2 (1.6%) | 0 | 0.7 |
Neg | Pos | Neg | Pos | ||
Nulliparous | 39 | 0 | 54 | 0 | |
Fertility (%) | 11 (20.8) | 42 (79.2) | 61 (49.6) | 62 (50.4) | 0.0004 |
Abortion (%) | 40 (70.5) | 13 (24.5) | 87 (70.7) | 36 (29.3) | 0.714 |
No EM N = 92 | EM N = 177 | p Value | MD | |||
---|---|---|---|---|---|---|
No | Yes | No | Yes | |||
Dysmenorrhea (PP) | 24 | 68 | 5 | 172 | 0.0001 | 0 |
PP, NRS ≤ 3 | 35 | 57 | 6 | 171 | 0.0001 | 0 |
PP, NRS score (SD) | 5.1 (3.8) | 7.8 (2.2) | 0.0001 | 0 | ||
PP before menses (%) | 8 (11.9) | 12 (7.4) | 0.304 | |||
PP during menses (%) | 22 (32.8) | 28 (17.2) | 0.013 | |||
PP before/during menses (%) | 27 (40.3) | 58 (35.6) | 0.549 | |||
PP before/during/after menses (%) | 8 (11.9) | 65 (39.9) | 0.0001 | |||
PP after menses (%) | 0 (0) | 0 (0) | 1.0 | |||
PP during/after menses (%) | 2 (3.0) | 5 (3.1) | 1.0 | |||
PP before/after menses (%) | 0 (0) | 1 (.6) | 1.0 | |||
Chronic pelvic pain (CPP) | 73 | 19 | 95 | 82 | 0.0001 | 0 |
CPP, NRS score (SD) | 1.4 (2.9) | 2.9 (3.4) | 0.0001 | 0 | ||
Dysuria (painful urination) | 88 | 4 | 120 | 57 | 0.0001 | 0 |
Dysuria, NRS score (SD) | 0.22 (1.1) | 1.63 (2.7) | 0.0001 | 0 | ||
Dyschezia (painful defecation) | 78 | 14 | 94 | 83 | 0.0001 | 0 |
Dyschezia (NRS ≤ 1) | 79 | 13 | 94 | 83 | 0.0001 | 0 |
Dyschezia, NRS score (SD) | 0.85 (2.2) | 3.03 (3.5) | 0.0001 | 0 | ||
Dyspareunia (painful intercourse) | 59 | 26 | 72 | 104 | 0.0001 | 7/1 |
Dyspareunia (NRS ≤ 1) | 60 | 25 | 72 | 104 | 0.0001 | 7/1 |
Dyspareunia, NRS score (SD) | 1.5 (2.6) | 3.5 (3.4) | 0.0001 | 7/1 | ||
Obstipation | 78 | 14 | 106 | 71 | 0.0001 | 0 |
Diarrhea | 73 | 19 | 114 | 63 | 0.0122 | 0 |
No EM N = 92 | EM N = 177 | p Value | |||
---|---|---|---|---|---|
No | Yes | No | Yes | ||
Cramping | 45 | 47 | 39 | 138 | 0.0001 |
Tearing | 77 | 15 | 105 | 72 | 0.0001 |
Pulling | 52 | 40 | 53 | 124 | 0.0001 |
Stinging | 58 | 34 | 76 | 101 | 0.0020 |
Pulsatile | 81 | 11 | 136 | 41 | 0.0338 |
Touch-sensitivity | 79 | 13 | 128 | 49 | 0.0143 |
Burning | 86 | 6 | 148 | 29 | 0.0225 |
Pressing | 86 | 6 | 154 | 23 | 0.1459 |
Diffuse | 84 | 8 | 152 | 25 | 0.2420 |
Heat | 87 | 5 | 161 | 16 | 0.3469 |
Flashing | 82 | 10 | 154 | 23 | 0.6979 |
No EM N = 92 | EM N = 177 | p Value | |||
---|---|---|---|---|---|
Neg | Pos | Neg | Pos | ||
Pain now | 68 | 24 | 88 | 89 | 0.0001 |
Pain now, NRS (SD) | 1.07 (2.2) | 2.0 (2.6) | 0.0003 | ||
Strongest pain/4 wks | 37 | 55 | 11 | 166 | 0.0001 |
Strongest pain, NRS (SD) | 4.3 (4.0) | 7.6 (2.7) | 0.0001 | ||
Average pain | 42 | 50 | 18 | 159 | 0.0001 |
Average pain, NRS (SD) | 2.7 (2.9) | 4.9 (2.7) | 0.0001 | ||
Lower abdomen | 40 | 52 | 18 | 159 | 0.0001 |
Lumbar spine pain | 65 | 27 | 60 | 117 | 0.0001 |
Thighs/lower extremities | 78 | 14 | 117 | 60 | 0.001 |
Hips/groins | 85 | 7 | 144 | 33 | 0.018 |
Upper abdomen | 89 | 3 | 159 | 18 | 0.055 |
Vagina/Mons pubis | 81 | 11 | 152 | 25 | 0.708 |
Gluteal region | 88 | 4 | 168 | 9 | 1.0 |
Pain course pattern | 38 | 54 | 10 | 167 | 0.0001 |
| 5 (9.3) | 17 (10.2) | 1.0 | ||
| 22 (40.7) | 50 (29.9) | 0.186 | ||
| 24 (44.4) | 72 (43.1) | 0.241 | ||
| 3 (5.6) | 28 (16.8) | 0.0427 | ||
Final score (Neuropathic pain) | |||||
| 87 (94.6) | 136 (76.8) | 0.0001 | ||
| 4 (4.3) | 33 (18.6) | 0.0012 | ||
| 1 (1.1) | 8 (4.5) | 0.1721 | ||
Final score, mean (SD) | 3.7 (4.8) | 8.5 (5.5) | 0.0001 | ||
| 42 | 50 | 12 | 165 | 0.0001 |
| 55 | 37 | 37 | 140 | 0.0001 |
No EM N = 92 | EM N = 177 | p Value | |||
---|---|---|---|---|---|
No | Yes | No | Yes | ||
Significant parameters (SD) | 7.8 (5.8) | 14.1 (4.2) | <0.0001 | ||
Cut-off of 8 | 46 | 46 | 12 | 165 | <0.0001 |
Positive predictive value (95% CI) | 0.782 (0.7203–0.8358) | ||||
Negative predictive value (95% CI) | 0.7931 (0.6666–0.8881) | ||||
Sensitivity (95% CI) | 0.9322 (0.8843–0.9645) | ||||
Specificity (95% CI) | 0.5000 (0.3942–0.6058) | ||||
Odds ratio (95% CI) | 13.75 (6.729–28.097) | ||||
Relative risk (95% CI) | 3.78 (2.272–6.288) | ||||
Decision tree | 69 | 23 | 17 | 160 | <0.0001 |
Positive predictive value (95% CI) | 0.8743 (0.8175–0.9187) | ||||
Negative predictive value (95% CI) | 0.8023 (0.7028–0.8802) | ||||
Sensitivity (95% CI) | 0.904 (0.8508–0.943) | ||||
Specificity (95% CI) | 0.75 (0.6485–0.8341) | ||||
Odds ratio (95% CI) | 28.235 (14.195–56.163) | ||||
Relative risk (95% CI) | 4.423 (2.879–6.795) |
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Konrad, L.; Fruhmann Berger, L.M.; Maier, V.; Horné, F.; Neuheisel, L.M.; Laucks, E.V.; Riaz, M.A.; Oehmke, F.; Meinhold-Heerlein, I.; Zeppernick, F. Predictive Model for the Non-Invasive Diagnosis of Endometriosis Based on Clinical Parameters. J. Clin. Med. 2023, 12, 4231. https://doi.org/10.3390/jcm12134231
Konrad L, Fruhmann Berger LM, Maier V, Horné F, Neuheisel LM, Laucks EV, Riaz MA, Oehmke F, Meinhold-Heerlein I, Zeppernick F. Predictive Model for the Non-Invasive Diagnosis of Endometriosis Based on Clinical Parameters. Journal of Clinical Medicine. 2023; 12(13):4231. https://doi.org/10.3390/jcm12134231
Chicago/Turabian StyleKonrad, Lutz, Lea M. Fruhmann Berger, Veronica Maier, Fabian Horné, Laura M. Neuheisel, Elisa V. Laucks, Muhammad A. Riaz, Frank Oehmke, Ivo Meinhold-Heerlein, and Felix Zeppernick. 2023. "Predictive Model for the Non-Invasive Diagnosis of Endometriosis Based on Clinical Parameters" Journal of Clinical Medicine 12, no. 13: 4231. https://doi.org/10.3390/jcm12134231
APA StyleKonrad, L., Fruhmann Berger, L. M., Maier, V., Horné, F., Neuheisel, L. M., Laucks, E. V., Riaz, M. A., Oehmke, F., Meinhold-Heerlein, I., & Zeppernick, F. (2023). Predictive Model for the Non-Invasive Diagnosis of Endometriosis Based on Clinical Parameters. Journal of Clinical Medicine, 12(13), 4231. https://doi.org/10.3390/jcm12134231