Advances in Clinical and Experimental Medicine

Title abbreviation: Adv Clin Exp Med
JCR Impact Factor (IF) – 1.736
5-Year Impact Factor – 2.135
Index Copernicus  – 168.52
MEiN – 70 pts

ISSN 1899–5276 (print)
ISSN 2451-2680 (online)
Periodicity – monthly

Download original text (EN)

Advances in Clinical and Experimental Medicine

2020, vol. 29, nr 1, January, p. 33–44

doi: 10.17219/acem/111812

Publication type: original article

Language: English

License: Creative Commons Attribution 3.0 Unported (CC BY 3.0)

Download citation:

  • BIBTEX (JabRef, Mendeley)
  • RIS (Papers, Reference Manager, RefWorks, Zotero)

Diagnostic equivalency of mobile CTG devices and remote analysis to conventional on-site nonstress test

Renata Pilarczyk1,A,B,C,D, Mateusz Strózik1,2,A,B,C,D, Lidia Hirnle1,E,F

1 1st Department and Clinic of Gynecology and Obstetrics, Wroclaw Medical University, Poland

2 Division of Histology and Embryology, Department of Human Morphology and Embryology, Wroclaw Medical University, Poland


Background. Remote pregnancy monitoring is one of the most promising applications of telemedicine; however, the diagnostic value of self-examination using mobile cardiotocography (CTG) devices and remote analysis of the subsequent results has never been properly studied.
Objectives. The study aimed to compare the diagnostic usefulness of CTG self-examination using a mobile device to examination performed by a medical professional using a stationary device; and to evaluate the quality of CTG analysis performed remotely.
Material and Methods. Eighty-two pairs of CTG recordings were collected; each pair consisted of a single recording from an examination performed by a midwife using a stationary device, and another recording from an unassisted patient self-examination using a mobile device. Recordings were performed with a maximum time interval of 30 min. Each recording was analyzed twice. Primary analysis included a comparison of the assisted examination evaluated on-site vs the self-examination evaluated remotely in pairs. Secondary analysis was conducted by an independent expert who evaluated the unpaired recordings. Baseline fetal heart rate (BFHR) values were compared independently.
Results. We found that patients were more likely to perform inconclusive recordings than experienced midwives; however, the self-examination feasibility was satisfactory. The primary analysis showed 88.4% agreement of the recorded pairs; 11.6% of inconsistent pairs were due to inter-observer variability or medical reasons. The independent expert’s analysis showed 97.1% agreement between the assisted and unassisted examinations. Paired t-test for BFHR values showed a statistically significant but clinically negligible mean difference between the 2 devices at 1.75 bpm.
Conclusion. The CTG examinations performed using mobile devices present satisfactory feasibility and equivalent diagnostic value compared to conventional devices, while the remote evaluation of recordings is as reliable as on-site analysis. Remote pregnancy surveillance is safe, effective and may be implemented into everyday obstetric care.

Key words

teleCTG, mobile CTG, telemedicine, eHealth, remote pregnancy monitoring

References (30)

  1. WHO Global Observatory for eHealth. mHealth: New horizons for health through mobile technologies: Second global survey on eHealth. Geneva, Switzerland: World Health Organization; 2011. Accessed February 19, 2019.
  2. Lee SH, Nurmatov UB, Nwaru BI, Mukherjee M, Grant L, Pagliari C. Effectiveness of mHealth interventions for maternal, newborn and child health in low- and middle-income countries: Systematic review and meta-analysis. J Glob Health. 2016;6(1):010401. doi:10.7189/jogh.06.010401
  3. Sondaal SF, Browne JL, Amoakoh-Coleman M, et al. Assessing the effect of mhealth interventions in improving maternal and neonatal care in low- and middle-income countries: A systematic review. PLoS One. 2016;11(5):e0154664. doi:10.1371/journal.pone.0154664
  4. Wallwiener S, Müller M, Doster A, et al. Pregnancy eHealth and mHealth: User proportions and characteristics of pregnant women using web-based information sources: A cross-sectional study. Arch Gynecol Obstet. 2016;294(5):937–944.
  5. Grassl N, Nees J, Schramm K, et al. A Web-based survey assessing the attitudes of health care professionals in Germany toward the use of telemedicine in pregnancy monitoring: Cross-sectional study. JMIR Mhealth Uhealth. 2018;6(8):e10063. doi:10.2196/10063
  6. van den Heuvel JF, Groenhof TK, Veerbeek JH, et al. eHealth as the next-generation perinatal care: An overview of the literature. J Med Internet Res. 2018;20(6):e202. doi:10.2196/jmir.9262
  7. Hod M, Kerner R. Telemedicine for antenatal surveillance of high-risk pregnancies with ambulatory and home fetal heart rate monitoring: An update. J Perinat Med. 2003;31(3):195–200. doi:10.1515/JPM.2003.026
  8. Antepartum fetal surveillance. Practice Bulletin No. 145. American College of Obstetricians and Gynecologists. Obstet Gynecol. 2014;124:182–192. doi:10.1097/01.AOG.0000451759.90082.7b
  9. Lenstrup C, Haase N. Predictive value of antepartum fetal heart rate non-stress test in high-risk pregnancy. Acta Obstet Gynecol Scand. 1985;64(2):133–138.
  10. Olofsson P, Sjöberg NO, Solum T. Fetal surveillance in diabetic pregnancy. I. Predictive value of the nonstress test. Acta Obstet Gynecol Scand. 1986;65(3):241–246.
  11. Hoyer D, Żebrowski J, Cysarz D, et al. Monitoring fetal maturation: Objectives, techniques and indices of autonomic function. Physiol Meas. 2017;38(5):R61–R88. doi:10.1088/1361-6579/aa5fca
  12. Grivell RM, Alfirevic Z, Gyte GML, Devane D. Antenatal cardiotocography for fetal assessment (review). Cochrane Database Syst Rev. 2015;(9):CD007863. doi:10.1002/14651858.CD007863.pub4
  13. Kitagawa M, Akiyama Y, Omi H, Sago H, Natori M. Development and clinical application of a telemedicine support system in the field of perinatal patient management. J Obstet Gynaecol Res. 2000;26(6):427–434.
  14. Monincx WM, Birnie E, Zondervan HA, Bleker OP, Bonsel GJ. Maternal health, antenatal and at 8 weeks after delivery, in-home versus in-hospital fetal monitoring in high-risk pregnancies. Eur J Obstet Gynecol Reprod Biol. 2001;94(2):197–204.
  15. Moore KH, Sill R. Domiciliary fetal monitoring in a district maternity unit. Aust N Z J Obstet Gynaecol. 1990;30(1):36–40.
  16. Di Lieto A, Giani U, Campanile M, De Falco M, Scaramellino M, Papa R. Prenatal telemedicine: Clinical experience with conventional and computerised antepartum telecardiotocography. Eur J Obstet Gynecol Reprod Biol. 2002;103(2):114–118.
  17. Di Lieto A, De Falco M, Campanile M, et al. Regional and international prenatal telemedicine network for computerized antepartum cardiotocography. Telemed J E Health. 2008;14(1):49–54. doi:10.1089/tmj.2007.0021
  18. Wapner RJ, Cotton DB, Artal R, Librizzi RJ, Ross MG. A randomized multicenter trial assessing a home uterine activity monitoring device used in the absence of daily nursing contact. Am J Obstet Gynecol. 1995;172(3):1026–1034.
  19. Corwin MJ, Mou SM, Sunderji SG, et al. Multicenter randomized clinical trial of home uterine activity monitoring: Pregnancy outcomes for all women randomized. Am J Obstet Gynecol. 1996;175(5):1281–1285.
  20. Morrison J, Bergauer NK, Jacques D, Coleman SK, Stanziano GJ. Tele­medicine: Cost-effective management of high-risk pregnancy. Manag Care. 2001;10(11):42–46,48–49.
  21. Kerner R, Yogev Y, Belkin A, Ben-Haroush A, Zeevi B, Hod M. Maternal self-administered fetal heart rate monitoring and transmission from home in high-risk pregnancies. Int J Gynaecol Obstet. 2004;84(1):33–39.
  22. Reece EA, Hagay Z, Garofalo J, Hobbins JC. A controlled trial of self-nonstress test versus assisted nonstress test in the evaluation of fetal well-being. Am J Obstet Gynecol. 1992;166(2):489–492.
  23. Tapia-Conyer R, Lyford S, Saucedo R, et al. Improving perinatal care in the rural regions worldwide by wireless enabled antepartum fetal monitoring: A demonstration project. Int J Telemed Appl. 2015:794180. doi:10.1155/2015/794180
  24. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2018. Accessed February 19, 2019.
  25. Spilka J, Chudáček V, Janků P, et al. Analysis of obstetricians’ decision making on CTG recordings. J Biomed Inform. 2014;51:72–79. doi:10.1016/j.jbi.2014.04.010
  26. Rei M, Tavares S, Pinto P, et al. Interobserver agreement in CTG interpretation using the 2015 FIGO guidelines for intrapartum fetal monitoring. Eur J Obstet Gynecol Reprod Biol. 2016;205:27–31. doi:10.1016/j.ejogrb.2016.08.017
  27. ANGELS 2016 Annual Report. University of Arkansas for Medical Sciences. Little Rock, AR: University of Arkansas for Medical Sciences. Accessed February 19, 2019.
  28. Rauf Z, O’Brien E, Stampalija T, Ilioniu FP, Lavender T, Alfirevic Z. Home labour induction with retrievable prostaglandin pessary and continuous telemetric trans-abdominal fetal ECG monitoring. PLoS One. 2011;6(11):e28129. doi:10.1371/journal.pone.0028129
  29. Mills TA, Ricklesford C, Heazell AE, Cooke A, Lavender T. Marvelous to mediocre: Findings of national survey of UK practice and provision of care in pregnancies after stillbirth or neonatal death. BMC Pregnancy Childbirth. 2016;16:101. doi:10.1186/s12884-016-0891-2
  30. Hollander JE, Davis TM, Doarn C, et al. Recommendations from the First National Academic Consortium of Telehealth. Popul Health Manag. 2018;21(4):271–277. doi:10.1089/pop.2017.0080