Skip to main content
SpringerLink
Log in

Predictors and a scoring model for maternal near-miss and maternal death in Southern Thailand: a case-control study

  • Maternal-Fetal Medicine
  • Published:
Archives of Gynecology and Obstetrics Aims and scope Submit manuscript

Abstract

Purpose

To identify predictors and develop a scoring model to predict maternal near-miss (MNM) and maternal mortality.

Methods

A case–control study of 1,420 women delivered between 2014 and 2020 was conducted. Cases were women with MNM or maternal death, controls were women who had uneventful deliveries directly after women in the cases group. Antenatal characteristics and complications were reviewed. Multivariate logistic regression and Akaike information criterion were used to identify predictors and develop a risk score for MNM and maternal mortality.

Results

Predictors for MNM and maternal mortality (aOR and score for predictive model) were advanced age (aOR 1.73, 95% CI 1.25–2.39, 1), obesity (aOR 2.03, 95% CI 1.22–3.39, 1), parity ≥ 3 (aOR 1.75, 95% CI 1.27–2.41, 1), history of uterine curettage (aOR 5.13, 95% CI 2.47–10.66, 3), history of postpartum hemorrhage (PPH) (aOR 13.55, 95% CI 1.40–130.99, 5), anemia (aOR 5.53, 95% CI 3.65–8.38, 3), pregestational diabetes (aOR 5.29, 95% CI 1.27–21.99, 3), heart disease (aOR 13.40, 95%CI 4.42–40.61, 5), multiple pregnancy (aOR 5.57, 95% CI 2.00–15.50, 3), placenta previa and/or placenta-accreta spectrum (aOR 48.19, 95% CI 22.75–102.09, 8), gestational hypertension/preeclampsia without severe features (aOR 5.95, 95% CI 2.64–13.45, 4), and with severe features (aOR 16.64, 95% CI 9.17–30.19, 6), preterm delivery <37 weeks (aOR 1.65, 95%CI 1.06–2.58, 1) and < 34 weeks (aOR 2.71, 95% CI 1.59–4.62, 2). A cut-off score of ≥4 gave the highest chance of correctly classified women into high risk group with 74.4% sensitivity and 90.4% specificity.

Conclusions

We identified predictors and proposed a scoring model to predict MNM and maternal mortality with acceptable predictive performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. World Health Organization (2011) Evaluating the quality of care for severe pregnancy complications: the WHO near-miss approach for maternal health. WHO. https://www.who.int/publications/i/item/9789241502221. Accessed 1 October 2023

  2. Lu MC, Highsmith K, de la Cruz D, Atrash HK (2015) Putting the “M” back in the Maternal and Child Health Bureau: reducing maternal mortality and morbidity. Matern Child Health J 19(7):1435–1439. https://doi.org/10.1007/s10995-015-1665-6

    Article  PubMed  Google Scholar 

  3. UNICEF (2023) Maternal mortality rates and statistics. UNICEF Data. https://data.unicef.org/topic/maternal-health/maternal-mortality/. Accessed 1 October 2023

  4. The United Nations (2022) United Nations sustainable development goals. goal 3: ensure healthy lives and promote well-being for all at all ages. The United Nations. https://www.un.org/sustainabledevelopment/health/. Accessed 12 August 2022

  5. Thai Ministry of Public Health (2022) Thai Ministry of Public Health KPI. Thai Ministry of Public Health. http://healthkpi.moph.go.th/kpi2/kpi/index/?id=1848&kpi_year=2565. Accessed 7 November 2022

  6. Department of Health, Thai Ministry of Public Health (2020) Maternal death situation in Thailand 2019–2020. Thai Ministry of Public Health. https://hp.anamai.moph.go.th/web-upload/4xceb3b571ddb70741ad132d75876bc41d/tinymce/OPDC/OPDC2564-F/IDC1_6/opdc_2564_IDC1-6_01.pdf. Accessed 9 November 2022

  7. Waterstone M, Bewley S, Wolfe C (2001) Incidence and predictors of severe obstetric morbidity: case-control study. BMJ 322(7294):1089–1094. https://doi.org/10.1136/bmj.322.7294.1089

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Goffman D, Madden RC, Harrison EA, Merkatz IR, Chazotte C (2007) Predictors of maternal mortality and near-miss maternal morbidity. J Perinatol 27(10):597–601. https://doi.org/10.1038/sj.jp.7211810

    Article  CAS  PubMed  Google Scholar 

  9. Wianwiset W (2012) Maternal near miss (severe morbidity) at Sisaket hospital. Thai J Obstet Gynecol 20(2):69–76

    Google Scholar 

  10. Bateman BT, Mhyre JM, Hernandez-Diaz S, Huybrechts KF, Fischer MA, Creanga AA, Callaghan WM, Gagne JJ (2013) Development of a comorbidity index for use in obstetric patients. Obstet Gynecol 122(5):957–965. https://doi.org/10.1097/AOG.0b013e3182a603bb

    Article  PubMed  Google Scholar 

  11. Noor NM, Nik Hussain NH, Sulaiman Z, Abdul Razak A (2015) Contributory factors for severe maternal morbidity: a 10-year review of the literature. Asia Pac J Public Health 27(Suppl. 8):9S-18S. https://doi.org/10.1177/1010539515589811

    Article  PubMed  Google Scholar 

  12. Leonard SA, Main EK, Carmichael SL (2019) The contribution of maternal characteristics and cesarean delivery to an increasing trend of severe maternal morbidity. BMC Pregnancy Childbirth 19(1):16. https://doi.org/10.1186/s12884-018-2169-3

    Article  PubMed  PubMed Central  Google Scholar 

  13. Howland RE, Angley M, Won SH, Wilcox W, Searing H, Liu SY, Johansson EW (2019) Determinants of severe maternal morbidity and its racial/ethnic disparities in New York City, 2008–2012. Matern Child Health J 23(3):346–355. https://doi.org/10.1007/s10995-018-2682-z

    Article  PubMed  Google Scholar 

  14. Chhabra P, Guleria K, Bhasin SK, Kumari K, Singh S, Lukhmana S (2019) Severe maternal morbidity and maternal near miss in a tertiary hospital of Delhi. Natl Med J India 32(5):270–276. https://doi.org/10.4103/0970-258X.295967

    Article  PubMed  Google Scholar 

  15. Brown CC, Adams CE, George KE, Moore JE (2020) Associations between comorbidities and severe maternal morbidity. Obstet Gynecol 136(5):892–901. https://doi.org/10.1097/AOG.0000000000004057

    Article  PubMed  PubMed Central  Google Scholar 

  16. Dessalegn FN, Astawesegn FH, Hankalo NC (2020) Factors associated with maternal near miss among women admitted in west Arsi zone public hospitals, Ethiopia: matched case-control study. J Pregnancy 2020:6029160. https://doi.org/10.1155/2020/6029160

    Article  PubMed  PubMed Central  Google Scholar 

  17. Metcalfe A, Lix LM, Johnson JA, Currie G, Lyon AW, Bernier F, Tough SC (2015) Validation of an obstetric comorbidity index in an external population. BJOG 122(13):1748–1755. https://doi.org/10.1111/1471-0528.13254

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Easter SR, Bateman BT, Sweeney VH, Manganaro K, Lassey SC, Gagne JJ, Robinson JN (2019) A comorbidity-based screening tool to predict severe maternal morbidity at the time of delivery. Am J Obstet Gynecol 221(3):271.e1-271.e10. https://doi.org/10.1016/j.ajog.2019.06.025

    Article  PubMed  Google Scholar 

  19. Bliddal M, Möller S, Vinter CA, Rubin KH, Gagne JJ, Pottegård A (2020) Validation of a comorbidity index for use in obstetric patients: a nationwide cohort study. Acta Obstet Gynecol Scand 99(3):399–405. https://doi.org/10.1111/aogs.13749

    Article  PubMed  Google Scholar 

  20. Cooke CM, Davidge ST (2019) Advanced maternal age and the impact on maternal and offspring cardiovascular health. Am J Physiol Heart Circ Physiol 317(2):H387–H394. https://doi.org/10.1152/ajpheart.00045.2019

    Article  CAS  PubMed  Google Scholar 

  21. Ramsay JE, Ferrell WR, Crawford L, Wallace AM, Greer IA, Sattar N (2002) Maternal obesity is associated with dysregulation of metabolic, vascular, and inflammatory pathways. J Clin Endocrinol Metab 87(9):4231–4237. https://doi.org/10.1210/jc.2002-020311

    Article  CAS  PubMed  Google Scholar 

  22. Wu P, Gulati M, Kwok CS, Wong CW, Narain A, O’Brien S, Chew-Graham CA, Verma G, Kadam UT, Mamas MA (2018) Preterm delivery and future risk of maternal cardiovascular disease: a systematic review and meta-analysis. J Am Heart Assoc 7(2):e007809. https://doi.org/10.1161/JAHA.117.007809

    Article  PubMed  PubMed Central  Google Scholar 

  23. Bai J, Wong FW, Bauman A, Mohsin M (2002) Parity and pregnancy outcomes. Am J Obstet Gynecol 186(2):274–278. https://doi.org/10.1067/mob.2002.119639

    Article  PubMed  Google Scholar 

  24. Gardosi J, Madurasinghe V, Williams M, Malik A, Francis A (2013) Maternal and fetal risk factors for stillbirth: population based study. BMJ 346:f108. https://doi.org/10.1136/bmj.f108

    Article  PubMed  PubMed Central  Google Scholar 

  25. Cunningham FG, Leveno KJ, Dashe JS, Hoffman BL, Spong CY, Casey BM (2022) Williams obstetrics, 26th edn. McGraw-Hill Education, New York

    Google Scholar 

  26. American College of Obstetricians and Gynecologists, & Society for Maternal-Fetal Medicine (2018) Obstetric Care Consensus No. 7: Placenta Accreta Spectrum. Obstet Gynecol 132(6):e259–e275. https://doi.org/10.1097/AOG.0000000000002983

  27. Ma G, Yang Y, Fu Q (2023) The incidence, indications, risk factors and pregnancy outcomes of peripartum hysterectomy at a tertiary hospital between 2013 and 2022. Arch Gynecol Obstet. https://doi.org/10.1007/s00404-023-07276-2

    Article  PubMed  PubMed Central  Google Scholar 

  28. Oberg AS, Hernandez-Diaz S, Palmsten K, Almqvist C, Bateman BT (2014) Patterns of recurrence of postpartum hemorrhage in a large population-based cohort. Am J Obstet Gynecol 210(3):229.e1-229.e8. https://doi.org/10.1016/j.ajog.2013.10.872

    Article  PubMed  Google Scholar 

  29. Lohmann-Bigelow J, Longo SA, Jiang X, Robichaux AG 3rd (2007) Does dilation and curettage affect future pregnancy outcomes? Ochsner J 7(4):173–176

    PubMed  PubMed Central  Google Scholar 

  30. Cavoretto PI, Rovere-Querini P, Candiani M (2022) Toward risk assessment for amniotic fluid embolisms. JAMA Netw Open 5(11):e2242850. https://doi.org/10.1001/jamanetworkopen.2022.42850

    Article  PubMed  Google Scholar 

  31. Lin LH, Lin Q, Wang XM, Zhang RH, Zheng LH, Zhang H (2023) The possible impact of the universal two-child policy on pregnancy outcomes. Arch Gynecol Obstet. https://doi.org/10.1007/s00404-023-07283-3

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank Associate professor Sutham Pinjaroen for valuable contributions to the study conceptualization, and Ms. Walailuk Jitpiboon of the Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, for assistance in data analysis.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Author information

Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand

    Wipawan Raktong, Rapphon Sawaddisan, Krantarat Peeyananjarassri & Chitkasaem Suwanrath

  2. Department of Epidemiology, Faculty of Medicine, Prince of Songkla, University, Songkhla, Thailand

    Alan Geater

Authors
  1. Wipawan Raktong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rapphon Sawaddisan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Krantarat Peeyananjarassri
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chitkasaem Suwanrath
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alan Geater
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

RW: Project development, Data collection and management, Data analysis, Manuscript writing; SR: Project development, Data collection and management, Data analysis, Manuscript writing and editing; PK: Project development, Data analysis, Manuscript editing; SC: Project development, Data analysis, Manuscript editing; GA: Project development, Data management, Data analysis, Manuscript editing.

Corresponding author

Correspondence to Rapphon Sawaddisan.

Ethics declarations

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the Faculty of Medicine, Prince of Songkla University, Thailand (Date 24 September 2021/No 64-381-12-4).

Consent to participate

With the approval from the Ethics Committee, participants’ informed consents for this retrospective study were not obtained. The researchers kept all the personal data strictly confidential.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 85 KB)

Supplementary file2 (PDF 104 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Raktong, W., Sawaddisan, R., Peeyananjarassri, K. et al. Predictors and a scoring model for maternal near-miss and maternal death in Southern Thailand: a case-control study. Arch Gynecol Obstet (2024). https://doi.org/10.1007/s00404-024-07539-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00404-024-07539-6

Keywords

Search

Navigation