COX REGRESSION AS A TOOL FOR PREDICTING ADVERSE CLINICAL OUTCOMES IN PREGNANT WOMEN WITH CORONAVIRUS INFECTION
Abstract
The Cox proportional hazards model, or Cox regression, is widely used in biomedical research. This statistical model characterizes the relationship between time endpoints and independent variables before the event occurs. The coronavirus pandemic has forced the medical community to look for new opportunities in diagnosing, treating and predicting the course of this infection, including using the Cox regression method. Purpose of the study: to identify prognostic criteria for unfavorable outcome in pregnant women with severe and extremely severe forms of COVID-19 and, based on them, to build a prognostic model. Methodology: a cohort single-center retrospective study was conducted, which included 83 patients who were treated in the intensive care unit (ICU) from January 1 to December 31, 2021. Of these, 13 patients had an unfavorable outcome — death, and 70 patients with a favorable outcome — recovery. Clinical and laboratory parameters of patients of both groups during hospitalization in the ICU were analyzed. Results. The Cox regression analysis identified laboratory parameters, the values of which upon admission to the ICU are associated with the development of an unfavorable outcome (death). These indicators were used as variables in a linear regression equation. The equations for calculating the prognostic index met the criteria for a statistically significant model. The equation for calculating the prognostic index upon admission to the ICU is sensitivity 61.5%, specificity 67.1%, area under the operating characteristic curve (AUROC — Area Under Receiver Operator Curve) — 0.695 (95% confidence interval [95% CI] 0.523–0.866). Conclusion. Cox regression allows identifying indicators associated with unfavorable clinical outcome. Their numerical transformation allows us to obtain an objective indicator — a prognostic index. Using this criterion, it is possible to predict the development of an unfavorable outcome in a given clinical case, concentrate the work of a multidisciplinary team, attract additional reserves of a medical institution and/or evacuate such
patients to high-level hospitals.
References
Внебольничные пневмонии у беременных: дифференциальная диагностика, особенности лечения, акушерская тактика в условиях пандемии новой коронавирусной инфекции COVID-19. МКБ-10 (J13–J16 и J18; U07.1, U07.2): Учебное пособие / под ред. проф. В.Ф. Беженаря, проф. И.Е. Зазерской. СПб.: Эко-Вектор, 2020. 95 с. DOI: 10.17816/JOWDS20202.
Временные методические рекомендации. Профилактика, диагностика и лечение новой коронавирусной инфекции (COVID-19). Версия 10 от 8 февраля 2021 г. Москва: Министерство здравоохранения Российской Федерации. 2021. С. 261. Ссылка активна на 06.06.2023 г. https://static-0.minzdrav.gov.ru/system/attachments/attaches/000/054/588/original/%D0%92%D1%80%D0%B5%D0%BC%D0%B5%D0%BD%D0%BD%D1%8B%D0%B5_%D0%9C%D0%A0_COVID-19_%28v.10%29-08.02.2021_%281%29.pdf.
Григорьев С.Г., Лобзин Ю.В., Скрипченко Н.В. Роль и место логистической регрессии и ROC-анализа в решении медицинских диагностических задач // Журнал инфектологии. 2016. Т. 8, № 4. С. 36-45. DOI: 10.22625/2072-6732-2016-8-4-36-45.
Дрягина Н.В., Лестева Н.А., Денисова А.А., Кондратьева Е.А., Шабунина М.Ю., Кондратьев А.Н. Прогностическая значимость лабораторных показателей в определении тяжести течения и исхода новой коронавирусной инфекции (COVID-19) // Вестник анестезиологии и реаниматологии. 2023. Т. 20, № 2. С. 54–65. DOI: 10.24884/2078-5658-2022-20-2-54-65.
Крамаренко И.В., Константинова Л.А. Особенности применения регрессии Кокса в различных инструментальных средах // Вестник университета. 2022. № 10. С. 80-88. DOI: 10.26425/1816-4277-2022-10-80-88.
Лахин Р.Е., Жирнова Е.А., Щеголев А.В., Железняк И.С., Меньков И.А., Чугунов А.А. Ультразвуковой индекс поражения легких как предиктор исходов лечения: когортное исследование 388 пациентов с коронавирусной инфекцией // Вестник интенсивной терапии им. А.И. Салтанова. 2022. № 3. С. 45-56. DOI: 10.21320/1818-474X-2022-3-45-56.
Организация оказания медицинской помощи беременным, роженицам, родильницам и новорожденным при новой коронавирусной инфекции COVID-19. Методические рекомендации. Минздрав России. Версия 4. 05.07.2021. 131 c. Ссылка активна на 06.06.2023 г. https://static-0.minzdrav.gov.ru/system/attachments/attaches/000/057/333/original/05072021_MR_Preg_v4.pdf
Allotey J., Stallings E., Bonet M. et al. Clinical manifestations, risk factors, and maternal and perinatal outcomes of coronavirus disease 2019 in pregnancy: living systematic review and meta-analysis // BMJ. 2020. Vol. 370. Р. m3320. DOI: 10.1136/bmj.m3320.
Kalafat E., Prasad S., Birol P. et al. An internally validated prediction model for critical COVID-19 infection and intensive care unit admission in symptomatic pregnant women // Am J Obstet Gynecol. 2022. Vol. 226, № 3. Р. 403e1-403e13. DOI: 10.1016/j.ajog.2021.09.024.
Reis Z.S., Pires M.C., Ramos L.E. et al. Mechanical ventilation and death in pregnant patients admitted for COVID-19: a prognostic analysis from the Brazilian COVID-19 registry score // BMC Pregnancy Childbirth. 2023. Vol. 23, №1. P. 18. DOI: 10.1186/s12884-022-05310-w.
Tutiya C., Mello F., Chaccur G. et al. Risk factors for severe and critical COVID-19 in pregnant women in a single center in Brazil // J Matern Fetal Neonatal Med. 2021. Vol. 35, № 25. Р. 5389-5392.
DOI: 10.1080/14767058.2021.1880561.
