Machine-Learning-Based Predictive Model for Bothersome Stress Urinary Incontinence Among Parous Women in Southeastern China

Sussman RD, Syan R, Brucker BM. Guideline of guidelines: urinary incontinence in women. BJU Int. 2020;125:638–55. https://doi.org/10.1111/bju.14927.

Article  PubMed  Google Scholar 

Zhang L, Zhu L, Xu T, Lang J, Li Z, Gong J, et al. A population-based survey of the prevalence, potential risk factors, and symptom-specific bother of lower urinary tract symptoms in adult Chinese women. Eur Urol. 2015;68:97–112. https://doi.org/10.1016/j.eururo.2014.12.012.

Article  PubMed  Google Scholar 

Wang Q, Que Y, Yang Y, Wan X, Lin C. A population-based cross-sectional survey on the prevalence, severity, risk factors, and self-perception of female urinary incontinence in rural Fujian, China. Int Urogynecol J. 2023;34:2089–97. https://doi.org/10.1007/s00192-023-05518-0.

Article  PubMed  Google Scholar 

Vaughan CP, Markland AD. Urinary incontinence in women. Ann Intern Med. 2020;172:ITC17–32. https://doi.org/10.7326/AITC202002040.

Article  PubMed  Google Scholar 

Siahkal SF, Iravani M, Mohaghegh Z, Sharifipour F, Zahedian M. Maternal, obstetrical and neonatal risk factors’ impact on female urinary incontinence: a systematic review. Int Urogynecol J. 2020;31:2205–24. https://doi.org/10.1007/s00192-020-04442-x.

Article  PubMed  Google Scholar 

Jelovsek JE, Piccorelli A, Barber MD, Tunitsky-Bitton E, Kattan MW. Prediction models for postpartum urinary and fecal incontinence in primiparous women. Urogynecology. 2013;19:110–8. https://doi.org/10.1097/SPV.0b013e31828508f0.

Article  Google Scholar 

Chen L, Luo D, Chen X, Jin M, Yu X, Cai W. Development of predictive risk models of postpartum stress urinary incontinence for primiparous and multiparous women. Urol Int. 2020;104:824–32. https://doi.org/10.1159/000508416.

Article  PubMed  Google Scholar 

Xu C, Guo Y, Chi X, Chen Y, Chu L, Chen X. Establishment and validation of a simple nomogram for predicting early postpartum stress urinary incontinence among women with vaginal delivery: a retrospective study. BMC Womens Health. 2023;23:1–10. https://doi.org/10.1186/s12905-023-02160-2.

Article  Google Scholar 

Cheng H, Gong F, Shen Y, OuYang P, Ni R, Gao H. A nomogram model predicting the risk of postpartum stress urinary incontinence in primiparas: a multicenter study. Taiwan J Obstet Gynecol. 2022;61:580–4. https://doi.org/10.1016/j.tjog.2022.04.004.

Article  PubMed  Google Scholar 

Liu W, Qian L. Establishment and validation of a risk prediction model for postpartum stress urinary incontinence based on pelvic floor ultrasound and clinical data. Int Urogynecol J. 2022;33:3491–7. https://doi.org/10.1007/s00192-022-05395-z.

Article  PubMed  PubMed Central  Google Scholar 

Wang X, Jin Y, Xu X, Wang H, Feng S. Development and validation of a predictive model for urinary incontinence postpartum: a prospective longitudinal study. Int Urogynecol J. 2022;33:1609–15. https://doi.org/10.1007/s00192-022-05105-9.

Article  PubMed  Google Scholar 

Wang Q, Que YZ, Wan XY, Lin CQ. Prevalence, risk factors, and impact on life of female urinary incontinence: an epidemiological survey of 9584 women in a region of Southeastern China. Risk Manag Healthc Policy. 2023;16:1477–87. https://doi.org/10.2147/RMHP.S421488.

Article  PubMed  PubMed Central  Google Scholar 

Oh S, Lee S, Hwang WY, Suh DH, Jeon MJ. Development and validation of a prediction model for bothersome stress urinary incontinence after prolapse surgery: a retrospective cohort study. BJOG. 2022;129:1158–64. https://doi.org/10.1111/1471-0528.17036.

Article  PubMed  Google Scholar 

Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. Ann Intern Med. 2015;162:55–63. https://doi.org/10.7326/M14-0697.

Article  PubMed  Google Scholar 

Huang L, Zhang S, Wu S, Ma L, Deng X. The Chinese version of ICIQ: a useful tool in clinical practice and research on urinary incontinence. Neurourol Urodyn. 2008;27:522–4. https://doi.org/10.1002/nau.20546.

Article  PubMed  Google Scholar 

Jelovsek JE, Hill AJ, Chagin KM, Kattan MW, Barber MD. Predicting risk of urinary incontinence and adverse events after midurethral sling surgery in women. Obstet Gynecol. 2016;127:330–40. https://doi.org/10.1097/AOG.0000000000001269.

Article  PubMed  Google Scholar 

Van der Ploeg JM, Steyerberg EW, Zwolsman SE, van der Vaart CH, Roovers JPW. Stress urinary incontinence after vaginal prolapse repair: development and internal validation of a prediction model with and without the stress test. Neurourol Urodyn. 2019;38:1086–92. https://doi.org/10.1002/nau.23958.

Article  PubMed  Google Scholar 

Nambiar AK, Bosch R, Cruz F, Lemack GE, Thiruchelvam N, Tubaro A, Burkhard FC. EAU guidelines on assessment and nonsurgical management of urinary incontinence. Eur Urol. 2018;73:596–609. https://doi.org/10.1016/j.eururo.2017.12.031.

Article  PubMed  Google Scholar 

Ben AM, Haddar I, Truong A, Ayena CJ, Ouakrim Y, El KL, Mezghani N. Non-invasive wearable devices for urinary incontinence detection—a mini review. Front Sens. 2023;4:1279158. https://doi.org/10.3389/fsens.2023.1279158.

Article  Google Scholar 

Nyström E, Söderström L, Samuelsson E. Self-management of incontinence using a free mobile app: factors associated with improvement. Int Urogynecol J. 2022;33:877–85. https://doi.org/10.1007/s00192-021-04755-5.

Article  PubMed  Google Scholar 

Dufour S, Clancy A, Wu M. Technical update No. 433: eHealth solutions for urinary incontinence among women. J Obstet Gynaecol Can. 2023;45:150–9. https://doi.org/10.1016/j.jogc.2022.10.005.

Article  PubMed  Google Scholar 

Dufour S, Wu M. No. 397–conservative care of urinary incontinence in women. J Obstet Gynaecol Can. 2020;42:510–22. https://doi.org/10.1016/j.jogc.2019.04.009.

Article  PubMed  Google Scholar 

Wlaźlak E, Surkont G, Shek KL, Dietz HP. Can we predict urinary stress incontinence by using demographic, clinical, imaging and urodynamic data? Eur J Obstet Gynecol Reprod Biol. 2015;193:114–7. https://doi.org/10.1016/j.ejogrb.2015.07.012.

Article  PubMed  Google Scholar 

Xiao T, Xiao T, Chen Y, Gan Y, Xu J, Huang W, Zhang X. Can stress urinary incontinence be predicted by ultrasound? Am J Roentgenol. 2019;213:1163–9. https://doi.org/10.2214/AJR.18.20893.

Article  Google Scholar 

Troko J, Bach F, Toozs-Hobson P. Predicting urinary incontinence in women in later life: a systematic review. Maturitas. 2016;94:110–6. https://doi.org/10.1016/j.maturitas.2016.09.006.

Article  PubMed  Google Scholar 

Bradley CS, Erickson BA, Messersmith EE. Evidence of the impact of diet, fluid intake, caffeine, alcohol and tobacco on lower urinary tract symptoms: a systematic review. J Urol. 2017;198:1010–20. https://doi.org/10.1016/j.juro.2017.04.097.

Article  PubMed  PubMed Central  Google Scholar 

Dallosso HM, McGrother CW, Matthews RJ. The association of diet and other lifestyle factors with overactive bladder and stress incontinence: a longitudinal study in women. BJU Int. 2003;92:69–77. https://doi.org/10.1046/j.1464-410X.2003.04271.x.

Article  CAS  PubMed  Google Scholar 

Dallosso H, Matthews R, McGrother C. Diet as a risk factor for the development of stress urinary incontinence: a longitudinal study in women. Eur J Clin Nutr. 2004;58:920–6. https://doi.org/10.1038/sj.ejcn.1601913.

Article  CAS  PubMed  Google Scholar 

Ngiam KY, Khor W. Big data and machine learning algorithms for health-care delivery. Lancet Oncol. 2019;20:e262–73. https://doi.org/10.1016/S1470-2045(19)30149-4.

Article  PubMed  Google Scholar 

留言 (0)

沒有登入
gif