The World Health Organization (WHO) defines the post-coronavirus disease-2019 (COVID-19) condition, or “Long COVID”, as the continuation or onset of new symptoms 3 months after the initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, with these symptoms lasting for at least 2 months and with no other explanation [1]. Thus, research into the impacts of COVID-19 in pregnant patients admitted to the intensive care unit (ICU) in Saudi Arabia is crucial, given the associated elevated risks [2]. Prior data have shown that women, particularly those of reproductive age, have a considerable level of post-COVID symptoms, such as fatigue and cognitive dysfunction. Moreover, the system of pregnant women is even more strained by the stresses of pregnancy and nursing. Meanwhile, a national study has shown that people who experience severe COVID-19, particularly in the ICU, are at the highest risk of long COVID; however, the epidemiology and long-term impact of this condition remain poorly understood. It is important to appreciate this burden to design appropriate follow-up care for Saudi mothers [2]. A significant percentage of pregnant women infected with COVID-19 require intensive care and respiratory support (42.3%), which leads to increased risk of ICU admission during pregnancy [1]. Fever, dyspnea, and hypoxemia are typical acute symptoms; in extreme situations, these symptoms can develop into acute respiratory distress syndrome (ARDS), which requires mechanical ventilation [2]. Furthermore, obstetric problems such as preterm birth, preeclampsia, and higher rates of cesarean delivery are closely associated with ICU hospitalization [3, 4]. In addition to many neonatal problems, infants born to moms with severe COVID-19 are more likely to experience [5]. Despite being uncommon, vertical transmission has been reported, which raises questions regarding possible long-term developmental repercussions in neonates exposed to it [4]. Long-term follow-up is also necessary because of new evidence that maternal COVID-19 may be a factor in postpartum respiratory and cardiovascular complications [6]. Pregnant women with COVID-19 have mild to moderate symptoms and are cured without serious consequences [2]. This variation emphasizes the importance of personal care in the management of COVID-19 among pregnant women [7, 8], highlighting the need for risk evaluation and individualized treatment strategies. According to research, one percent of pregnant women infected with COVID-19 require acute care and complementary oxygen therapy, which is closely associated with a high risk of ICU admission [9]. Fever, cough, and dyspnea are typical acute clinical signs; in severe cases, these symptoms can progress to acute respiratory distress requiring mechanical ventilation [10]. Additionally, a higher incidence of preterm labor and a higher rate of cesarean delivery are two adverse obstetric outcomes that are frequently linked to the need for ICU hospitalization [11, 12].

Long-term effects of COVID-19 on newborns, such as a higher chance of complications, including low birth weight and poorer Apgar scores, are a cause for concern. While vertical transmission is uncommon, this transmission does occur occasionally, and babies who test positive for SARS-CoV-2 may have long-term health and developmental consequences. Hence, it is important to consider the larger context of maternal health during the pandemic, including the acute and long-term effects of COVID-19 among pregnant women.

Specifically, COVID-19 in pregnant women has been linked to heightened chances of catastrophic maternal outcomes, such as ICU admissions and mechanical ventilation. To improve maternal–neonatal health outcomes and guide evidence-based therapies, this study aimed to present a thorough assessment of the acute and long-term effects of COVID-19 in severely ill pregnant women. Moreover, this study aimed to improve maternal health and clinical guidelines for future epidemic responses by combining data from Saudi Arabia and International Cohorts.

A total of 208 pregnant women with a mean maternal age of 31.9 years ($\pm$5.3 years) and laboratory-confirmed COVID-19 were included in this study (Table 1). The case-control analysis revealed significant clinical and socioeconomic disparities between the 88 women admitted to the ICU and the 120 non-ICU controls. Key risk factors for ICU admission identified through multivariate analysis included advanced maternal age, third-trimester infection, low income, education level and pre-existing comorbidities.

A significant portion of the participants (33.2%, n = 69) were aged 35 years or older. The mean gestational age at diagnosis was 29.9 weeks ($\pm$4.2), and 38.5% (n = 80) of participants were in the third trimester, reflecting the diversity of the pregnant population. More than half of the participants (52.9%, n = 110) were classified as having a low income. This high prevalence of low income among the participants underscores the potential socioeconomic challenges these individuals may face during pregnancy and COVID-19 infection.

Table 2 presents the data for pregnant women with COVID-19, stratified by ICU admission status. Significant differences were observed across multiple variables. The mean maternal age was significantly higher among women admitted to the ICU (34.5 $\pm$ 5.3 years) compared with those managed outside the ICU (30.2 $\pm$ 4.9 years; p 0.010). Consistently, a greater proportion of ICU patients were aged $>$35 years (51.1% vs. 20.0%; p 0.003).

Gestational age at diagnosis also differed significantly, with ICU patients presenting at a later stage of pregnancy (32.1 $\pm$ 4.2 weeks) compared to non-ICU patients (28.5 $\pm$ 3.6 weeks; p 0.010). More than half of the ICU group were in the third trimester (56.8%), compared with only 25.0% of the non-ICU group (p 0.010).

Marked socioeconomic disparities were observed. Low-income status was reported in 73.9% of the ICU patients versus 37.5% of the non-ICU patients (p 0.010). Conversely, only 26.1% of the ICU patients belonged to the middle- or high-income category, compared with 62.5% of the non-ICU patients (p 0.010).

Pre-existing medical conditions were more prevalent among patients admitted to the ICU. Pre-existing hypertension was reported in 34.1% of the ICU patients versus 8.3% of the non-ICU patients (p 0.010). Similarly, diabetes mellitus (DM) was more common among ICU patients (17.0%) compared with controls (4.2%; p 0.020).

Educational attainment differed significantly between groups. Nearly half (45.5%) of ICU patients had a high school education or lower, compared with 16.7% in the non-ICU group (p 0.010). In contrast, 83.3% of the non-ICU group had attained a college degree, compared with 54.5% of the ICU patients (p 0.010). Overall, these findings indicate that advanced maternal age, later gestational age at infection, lower income, lower educational level, and the presence of comorbid conditions, such as pre-existing hypertension and diabetes, were more common among pregnant women with COVID-19 requiring ICU admission.

The evaluation of risk factors associated with ICU admission among pregnant women with COVID-19 (Table 3). Pregnant women aged over 35 years exhibited a 2.5-fold increased risk of ICU admission (ORs = 2.5, 95% CI: 1.4–4.5; p 0.003). Meanwhile, women in the third trimester had an ORs of 3.1 (95% CI: 1.8–5.5; p 0.010), indicating that those in this phase of pregnancy are more than three times as likely to require ICU care. Low-income conditions were associated with an increased risk of ICU admission (ORs = 2.9, 95% CI: 1.7–4.9; p 0.010), suggesting that socioeconomic inequalities could significantly affect health outcomes for pregnant women during the COVID-19 epidemic. The likelihood of ICU admission among pregnant women surged to 4.5 (95% CI: 2.0–10.3; p 0.010).

The need for ICU care (ORs = 4.8, 95% CI: 2.2–10.4; p 0.010) in patients with pre-existing hypertension rose dramatically, which is an essential suggestion for how to care for pregnant women. DM was associated with a higher risk of ICU admission (ORs = 2.3, 95% CI: 1.1–5.0; p 0.02), indicating that women with existing health problems require close monitoring.

Women with a high school education or lower had an ORs of 3.6 (95% CI: 1.9–6.7; p 0.010) for ICU admission compared to those with higher educational attainment. These findings reveal several significant risk factors for ICU admission among pregnant women with COVID-19, including older maternal age, third-trimester pregnancies, low income, pre-existing hypertension, pre-existing diabetes, and lower educational attainment. These results underscore the necessity of identifying high-risk individuals within these demographics to facilitate targeted interventions and enhance healthcare delivery amid the current epidemic.

Model diagnostics and validation: The multivariable logistic regression models demonstrated good performance and calibration. The AUROC curve for the main ICU admission model (Table 3) was 0.85 (95% CI: 0.80–0.90), representing excellent discrimination. The model was acceptably calibrated, with a non-significant Hosmer-Lemeshow goodness-of-fit test (p = 0.42). Internal validation by bootstrap resampling (1000 iterations) yielded an optimism-corrected AUROC of 0.84. For a model predicting any adverse outcome (Table 4), the AUROC was 0.87 (95% CI: 0.82–0.92), and this model also had good calibration (Hosmer-Lemeshow p = 0.51), with an optimism-corrected AUROC for the area under the curve (AUC) of 0.86 vs. Steyerberg et al. [19]. Impact of country on bacteremia: The population blood culture positivity rate ranged from 2 to 52% across countries. There was no multicollinearity problem in either model, as all VIF values were below 2.5. Influence of observations: influential observations were not detected using Cook’s distance and DFBETAs, as no outliers were found to substantially affect the model coefficients.

The findings of the logistic regression analysis, including adverse outcomes among pregnant women with COVID-19, are summarized in Table 4. This study identified factors contributing to poor health outcomes for this population. More than 35 pregnant women exhibited high OR values (2.8; 95% CI: 1.6–5.0; p 0.002), indicating a high probability of adverse outcomes. The risk of adverse results was significantly higher for women in the third trimester, 3.4 (95% CI: 2.0–5.8; p 0.010). The probability of adverse outcomes was significantly higher among individuals with low incomes (ORs = 3.2, 95% CI: 1.9–5.4; p 0.010). Pregnant women without insurance had a considerably increased risk of unfavorable outcomes (ORs = 4.8, 95% CI: 2.3–10.7; p 0.010). With an OR of 5.1 (95% CI: 2.4–10.9; p 0.010), pre-existing hypertension was a significant risk factor for adverse outcomes, suggesting that women with this condition are more than five times more likely to suffer from serious COVID-19-related problems. Similarly, an OR of 2.6 (95% CI: 1.2–5.6; p 0.010) was associated with a significant increase in risk for diabetes. An OR of 3.9 (95% CI: 2.1–7.3; p 0.010) was observed only among women with a high school education, suggesting that educational attainment may affect access to information about maternity care and the availability of health services during the epidemic. Having more than two children was linked to a higher likelihood of adverse outcomes (ORs = 2.1, 95% CI: 1.1–4.0; p 0.030), indicating that women with COVID-19 may face more challenges following several previous pregnancies. The results also showed that obesity markedly increased the likelihood of adverse outcomes (ORs = 3.0, 95% CI: 1.5–6.0; p 0.004), suggesting that pregnant women who are overweight or obese require targeted interventions. According to these data, advanced maternal age, third-trimester gestation, low income, absence of health insurance, pre-existing diabetes and pre-existing hypertension, lower education levels, multiparity, obesity, and other key characteristics are linked to worse outcomes in pregnant women with COVID-19. These results underline the need for the high-risk population to improve health outcomes and reduce issues in the pregnant population during the ongoing COVID-19 epidemic.

Significant risk factors for ICU admission are revealed by the COVID-19 results in pregnant women (Fig. 1). The likelihood of developing a serious illness requiring intensive care is much higher for women over 35, those in the third trimester, and those with lower incomes or no health insurance. Furthermore, pre-existing diseases, such as pre-existing diabetes and hypertension, were shown to increase the risk further. The robustness of these findings is further supported by the statistically significant associations (p 0.05) observed across all identified risk factors. These findings highlight the critical need for focused interventions, such as improved prenatal care, easier access to healthcare, and customized public health initiatives, to reduce the serious consequences for high-risk pregnant COVID-19-infected women.

The analysis of the data in this study included visualizations of study group distributions, age-related trends, medical and socioeconomic circumstances, and risk factors for ICU admission to substantiate these conclusions. Meanwhile, future studies should examine specific issues in more detail, conduct more comprehensive statistical analyses, or introduce alternative visualizations.

Both the risk of ICU admission and the rate of complications increase significantly with increasing gestational age (Fig. 2), especially in the third trimester. Indeed, the third trimester is associated with more than twice the risk of the previous trimesters, with a risk ratio of 2.27. The risk ratios were significantly lower in the first and second trimesters. These results emphasize how crucial proactive care and careful observations are for pregnant women in advanced gestational stages who are infected with COVID-19.

Fig. 3 illustrates notable differences between pregnant women who required intensive care (ICU group) and those who did not (non-ICU group), based on a thorough examination of long-term COVID-19 outcomes. These data show that patients admitted to the ICU continue to face significant symptom burdens even after a year of infection.

The ICU group was 3.19 times more likely to have long-term problems than the non-ICU patients, with the most frequent cardiovascular complications. This firmness of symptoms, even after improvement in both groups, underscores the immediate need for long-term care and targeted treatments. The overall prevalence was 2.8 times higher in the ICU cohort, as ICU patients experienced a 20.22% reduction in symptoms compared with a 28.23% reduction in the non-ICU group.

The recovery rate for respiratory symptoms was nearly twice as high among non-ICU patients (32.43%) as among ICU patients (16.78%). This significant disparity of 15.65% underscores the long-term effects of severe COVID-19 on lung function, particularly in ICU patients.

The most significant disparities in recovery between groups were noted in mental health and fatigue (16.94% and 16.43%, respectively). Across all areas, non-ICU patients showed an improvement of over 29%, whereas ICU patients continued to experience difficulties (persistence ratios of 2.68 and 2.51, respectively).

Despite being the smallest recovery gap (2.05%), neurological symptoms had one of the highest firmness ratios (2.86), suggesting long-term difficulties with nerves and cognition.

With the ICU patients recovering by just 14.38% compared to 23.38% in the non-ICU group—a 9% difference—sleep problems remained moderately persistent. This persistence of sleep problems in the ICU patients underscores the need for continued care and support even after the acute phase of the disease.

According to the study, patients discharged from the ICU exhibited 2.5 to 3.2 times higher symptom persistence across all health categories than those not admitted to the ICU, indicating notable differences in long-term recovery from COVID-19. The most persistent symptoms over time were neurological and cardiovascular. Nevertheless, the most essential treatment interval was noted in mental health and exhaustion, which highlights the important requirement of integrated psychological support in post-ICU care. Non-ICU patients had a frequently high recovery rate, despite improvement being observed in both groups. This underscores the need for specialized, prolonged treatment for severe COVID-19 survivors and shows how the severity of the disease at the beginning predicts long-term prognosis. According to these findings, high-risk patients should have their cardiovascular, neurological, and mental health monitored as part of risk-stratified follow-up regimens. These results emphasize critical needs for pregnant patients for exceptional care and long-term monitoring, which recur from severe COVID-19, especially those who required ICU admission. Therefore, future studies should test targeted remedies to increase recovery rates in high-risk populations.

The persistence of symptoms at 12 months post-infection across cardiovascular, respiratory, neurological, and mental health domains was assessed (Table 5). As shown in Fig. 3, patients admitted to the ICU were significantly more likely to have symptoms persisting across all domains than those not treated in an ICU. To correct for multiple comparisons among these four major symptom domains, we applied the Benjamini–Hochberg method to the FDR. Symptom persistence between the ICU and non-ICU cohorts for each domain was treated as a family of tests for the FDR adjustment. Differences in chronicity remained significant across the four health domains after FDR correction.

This study provides a critical evaluation of the risk factors and consequences of ICU admission among pregnant patients with COVID-19 in the Bisha Province of Saudi Arabia. Our results clearly show that the following factors are significant and independent predictors of severe disease requiring intensive care: pre-existing comorbidities (diabetes and hypertension), third-trimester gestation, low socioeconomic status (as indicated by low income and lack of health insurance), advanced maternal age ($>$35 years), and lower educational attainment. These findings are not unique; rather, these findings align with a growing body of regional and global literature [19, 20, 21]. SARS-CoV-2 infection during pregnancy significantly worsens pre-existing health and socioeconomic vulnerabilities, as evidenced by the considerably higher ORs for being uninsured (ORs = 4.5) and for pre-existing hypertension (ORs = 4.8). This aligns with international meta-analyses that have repeatedly found socioeconomic deprivation and chronic hypertension to be strong risk factors for critical illness in pregnant populations [22, 23]. Given that the third trimester is characterized by decreased functional residual capacity of the lungs, an immunomodulated state, and an elevated diaphragm due to the gravid uterus, all of which increase susceptibility to severe respiratory infections, the strong correlation with advanced gestational age is physiologically plausible [24, 25]. This result aligns with research and international registries that show a disproportionate number of pregnant women in the third trimester who are admitted to ICUs [26, 27]. In addition, studies from diverse socioeconomic backgrounds have shown concern about the identification of lower education as a risk factor (ORs = 3.6), which likely reflects greater differences in health literacy, access to timely prenatal care, and the capacity to follow complex public health initiatives [28, 29].

After the acute period, we examined long-term outcomes and found a striking difference between the ICU and non-ICU patients. Cardiovascular, pulmonary, neurological, and mental health issues were among the symptoms that patients in critical care reported remaining present for 2.5 to 3.2 times longer at 12 months after infection. Thus, a substantial long-term morbidity burden that goes well beyond the immediate perinatal period is highlighted by the exceptionally high persistence of neurological and cardiovascular symptoms, as well as the large recovery gap in mental health and fatigue. The “long COVID” pattern in our obstetric cohort is consistent with findings in the general population, where prolonged recovery and multi-organ sequelae are predicted mainly by the initial severity of the disease [30, 31]. However, the prevalence of “long COVID” during the postpartum phase adds a complex dimension and may affect important processes, such as nursing, mother–infant bonding, and family dynamics, thereby increasing the burden on public health [32, 33]. Thus, psychological and psychiatric support must be urgently incorporated into standard postpartum follow-up protocols for severe COVID-19 survivors, as this area is frequently disregarded in traditional obstetric care, given the observed substantial mental health burden, which includes fatigue and likely elements of post-traumatic stress disorder from the ICU experience [34, 35].

A comprehensive public health and clinical response is necessary due to the confluence of clinical and socioeconomic risk factors identified in this study. Firstly, our results strongly support prioritizing early antiviral therapy and booster vaccinations for pregnant women, particularly those with comorbidities and in the third trimester, as these interventions are safe during pregnancy and have been shown to reduce disease severity significantly [36, 37]. Second, continuously increasing low-income support and promoting access to healthcare for pregnant women are strictly required, given the significant risk of socioeconomic disadvantage. To mitigate the effects, initiatives may include culturally sensitive patient education, strengthening social support networks, and access to prenatal care [38, 39]. Lastly, for women recuperating from severe COVID-19, long-term follow-up data require the creation of specialized, multidisciplinary postnatal clinics that provide integrated therapy to holistically treat the neurological, mental, and cardiac consequences [40, 41].

This study provides strong evidence of sufficient long-term sickness associated with severe COVID-19 during pregnancy, in addition to validating the risk variables known in settings related to Saudi Arabia. In light of the current and potential epidemic hazards, these conclusions are crucial for developing targeted interventions, informing health policy, and optimizing care for this vulnerable group.

Based on our research, we suggest a four-pillar structure for pandemic preparedness (Fig. 4): (1) improved prenatal risk assessment, (2) fair access to maternity care, (3) improved infection control during pregnancy, and (4) long-term follow-up after recovery. This comprehensive strategy prioritizes high-risk women, addressing both acute management and long-term outcomes, and ensures that the health system can protect maternal and newborn health through evidence-based, targeted interventions in the event of future medical emergency conditions.

During an epidemic, this structure provides a broad, evidence-based approach to protect the health of mothers and their embryos. This framework encompasses a comprehensive range of care, from prenatal risk evaluation to postpartum recovery, and is centered around four key interactions.

This study identified a confluence of clinical and socioeconomic factors that significantly increase the risk of severe COVID-19 in pregnancy. The substantial long-term morbidity among ICU survivors underscores the critical need for a multifaceted approach. We recommend implementing targeted prenatal risk stratification, enhancing healthcare access, and establishing dedicated post-COVID recovery clinics to mitigate risks and improve outcomes for this vulnerable population in future pandemic responses.

COVID-19, coronavirus disease-2019; ICU, intensive care unit; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; ARDS, acute respiratory distress syndrome; NICU, Neonatal Intensive Care Unit; RT-PCR, reverse transcription-polymerase chain reaction; EMRs, electronic medical records; IQR, interquartile range; OR, odds ratio; aOR, adjusted odds ratio; BMI, body mass index; IRB, Institutional Review Board; WHO, World Health Organization; FDR, false discovery rate; VIF, variance inflation factor; AUROC, area under the receiver operating characteristic; AUC, area under the curve; DM, diabetes mellitus.

The data used in this study are available from the corresponding authors upon request.

EM and AA conceived and designed the study. AMA, DA, EA, and SE were responsible for data acquisition and patient enrollment. BA performed the statistical analysis. ASH contributed to the interpretation of data and critical revision of the manuscript for important intellectual content. All authors contributed to critical revision of the manuscript for important intellectual content. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

The study protocol was reviewed and approved by the Institutional Review Board (IRB) of University of Bisha [Ref No.: UB-RELOC H-06-BH-087/(1810.24)]. The requirement for informed consent was waived by the IRB due to the retrospective nature of the study. All patient data were handled with strict confidentiality. Data were anonymized and de-identified at the point of collection and stored on a password-protected hospital server, accessible only to the principal investigators, in compliance with the Declaration of Helsinki.

We gratefully acknowledge the contributions of the medical records department and the intensive care unit team at King Abdalla Hospital. Our thanks also go to the Institutional Review Board of the University of Bisha for their guidance and approval.

The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number (Ub-11-1442).

The authors declare no conflict of interest.

During the preparation of this manuscript, the authors mainly used Grammarly, 2025 for language polishing, grammar improvement, and proofreading purposes. The AI tool was employed to enhance the clarity, readability, and grammatical accuracy of the text when the authors developed the intellectual content fully. All scientific and analytical materials, including data interpretation, conclusions, and scholars, remain the basic work of writers. The use of grammar did not affect the research method, result, or intellectual direction of study. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.