Studies reported post-COVID-19 fatigue in the general population, but not among pregnant women. Our objectives were to determine prevalence, duration, and risk factors of post-viral fatigue among pregnant women with SARS-CoV-2. This study involved 588 pregnant women with SARS-CoV-2 during pregnancy or delivery in Brazil. Three groups were investigated: G1 (n = 259, symptomatic infection during pregnancy); G2 (n = 131, positive serology at delivery); G3 (n = 198, negative serology at delivery). We applied questionnaires investigating fatigue at determined timepoints after infection for G1, and after delivery for all groups; fatigue prevalence was then determined. Cox regression was used to estimate hazard ratio (HR) and 95% CI of the risk of remaining with fatigue in G1. Overall fatigue prevalence in G1 at six weeks, three months and six months were 40.6%, 33.6%, and 27.8%, respectively. Cumulative risk of remaining with fatigue increased over time, with HR of 1.69 (95% CI: 0.89–3.20) and 2.43 (95% CI: 1.49–3.95) for women with moderate and severe symptoms, respectively. Multivariate analysis showed cough and myalgia as independent risk factors in G1. Fatigue prevalence was significantly higher in G1 compared to G2 and G3. Post-viral fatigue prevalence is higher in women infected during pregnancy; fatigue’s risk and duration increased with the severity of infection.

Background: Gestational diabetes mellitus (GDM) is one of the most common complications affecting pregnant women. While most women will achieve adequate glycemic levels with diet and exercise, some will require pharmacological treatment to reach and maintain glucose levels between the desired thresholds. Identifying these patients early in pregnancy could help direct resources and interventions. Methods: This retrospective cohort of women with GDM diagnosed with an abnormal 75g-OGTT presents data from 869 patients (724 in the diet group and 145 in the insulin group). Univariate logistic regression was used to compare the groups, and multivariable logistic regression was used to identify independent factors associated with the need for insulin. A log-linear function was used to estimate the probability of requiring pharmacological treatment. Results: Women in the insulin group had higher pre-pregnancy BMI index (29.8 vs 27.8 kg/m², odds ratio [OR] 1.06, 95% confidence interval [CI] 1.03–1.09), more frequent history of previous GDM (19.4% vs. 7.8%, OR 2.84, 95% CI 1.59–5.05), were more likely to have chronic hypertension (31.7% vs. 23.2%, OR 1.54, 95% CI 1.04–2.27), and had higher glucose levels at all three OGTT points. Multivariable logistic regression final model included age, BMI, previous GDM status, and the three OGTT values as predictors of insulin requirement. Conclusions: We can use regularly collected data from patients (age, BMI, previous GDM status, and the three OGTT values) to calculate the risk of a woman with GDM diagnosed in OGTT needing insulin. Identifying patients with a greater risk of requiring pharmacological treatment could help healthcare services to better allocate resources and offer closer follow-up to high-risk patients.

Background: Recognizing that hyperglycemia in pregnancy can impact both individually a patient’s health and collectively the healthcare system and that different levels of hyperglycemia incur different consequences, we aimed to evaluate the differences and similarities between patients who met the diagnostic criteria for gestational diabetes mellitus (GDM) or diabetes in pregnancy (DIP) according to the World Health Organization diagnostic criteria based on the 75 g oral glucose tolerance test (OGTT). Methods: This retrospective study included a cohort of 1064 women followed-up at the Gestational Diabetes Unit of Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo (Sao Paulo, Brazil). Patients were classified into GDM and DIP groups, according to their OGTT results. Their electronic charts were reviewed to obtain clinical and laboratory data for all participants. Results: Women in the DIP group had a higher pre-pregnancy body mass index (30.5 vs 28.1 kg/m², odds ratio [OR] 1.07, 95% confidence interval [CI] 1.02–1.11), more frequently experienced GDM in a previous pregnancy (25% vs. 11%, OR 2.71, 95% CI 1.17–6.27), and were more likely to have chronic hypertension (43.1% vs. 23.5%, OR 2.46, 95% CI 1.47–4.11), a current twin pregnancy (10.8% vs. 2.9%, OR 4.04, 95% CI 1.70–9.61), or require insulin (46.1% vs. 14.3%, OR 5.14, 95% CI 3.06–8.65) than those in the GDM group. Patients in the DIP group also had a higher frequency of large-for-gestational-age infants (12.3% vs. 5.1%, OR 2.78, 95% CI 1.23–6.27) and abnormal postpartum OGTT (45.9% vs. 12.6%, OR 5.91, 95% CI 2.93–11.90) than those in the GDM group. Nevertheless, in more than half of the DIP patients, glucose levels returned to normal after birth. Conclusions: Diabetes in pregnancy is associated with an increased risk of adverse perinatal outcomes but does not equate to a diagnosis of diabetes post-pregnancy. It is necessary to identify and monitor these women more closely during and after pregnancy. Keeping patients with hyperglycemia in pregnancy engaged in healthcare is essential for accurate diagnosis and prevention of complications related to abnormal glucose metabolism.

Gestational diabetes mellitus (GDM) is one of the most common complications in pregnancy. It may be diagnosed using a fasting plasma glucose (FPG) early in pregnancy (eGDM) or a 75-g oral glucose tolerance test (OGTT) (late GDM). This retrospective cohort of women with GDM presents data from 1891 patients (1004 in the eGDM and 887 in the late GDM group). Student’s t-test, chi-squared or Fisher’s exact test and the Bonferroni test for post hoc analysis were used to compare the groups. Women with eGDM had higher pre-pregnancy BMI, more frequent family history of DM, more frequent history of previous GDM, and were more likely to have chronic hypertension. They were more likely to deliver by cesarean section and to present an abnormal puerperal OGTT. Even though they received earlier treatment and required insulin more frequently, there was no difference in neonatal outcomes. Diagnosing and treating GDM is necessary to reduce complications and adverse outcomes, but it is still a challenge. We believe that women with eGDM should be treated and closely monitored, even though this may increase healthcare-related costs.

This study aimed to analyze cesarean section rates among women with GDM classified according to the Robson system and to identify independent factors associated with vaginal delivery. A retrospective cohort study was conducted with pregnant women receiving care at the Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, between 2012 and 2020. A total of 1508 pregnant women with GDM were included and divided into two groups based on the mode of delivery. Statistical analyses were performed to assess differences between groups and identify predictive factors for vaginal delivery using Binary logistic regression. The overall c-section rate was 65.3 %. Robson group 5 was the most representative, accounting for 39.53 % of all cesarean deliveries, with a single previous uterine scar being the primary indication (40.2 %). Spontaneous labor onset was the strongest independent predictor of vaginal delivery (OR = 8.601, 95 % CI 6.029‒12.270), whereas previous cesarean delivery (OR = 0.093, 95 % CI 0.065‒0.134), fetal distress (OR = 0.110, 95 % CI 0.071‒0.171), and multiple pregnancy (OR = 0.096, 95 % CI 0.036‒0.259) significantly reduced this likelihood. The high cesarean section rate among women with GDM, particularly in group 5, highlights the importance of previous uterine scar in determining the mode of delivery in this population. Encouraging spontaneous labor onset, provided that maternal and fetal conditions are adequately monitored, may be an effective strategy to reduce unnecessary cesarean sections in pregnancies complicated by GDM.

Gestational Diabetes Mellitus (GDM) is a common pregnancy complication and is linked to high cesarean rates, particularly in Brazil, where national data on the subject is limited. This study analyzed risk factors and primary indications for c-sections among GDM-affected pregnancies. It included a retrospective cohort of women receiving prenatal care at a tertiary hospital from January 2012 to March 2020, totaling 866 cases that met criteria: diagnosed GDM, pregnancies beyond 20 weeks, and delivery at this hospital. The cohort was divided into VAGINAL and CESAREAN groups, with statistical comparisons made between them. Of the 866 cases, 323 (37.3%) were vaginal deliveries, and 545 (62.7%) were c-sections. Primary indications for c-section included prior uterine surgeries (20.07%), iterative c-section (18.78%), fetal distress (9.76% intrapartum; 8.84% antepartum), non-cephalic presentation (7.37%), and functional dystocia (7.0%). Univariate analysis identified several factors associated with higher c-section risk, such as advanced maternal age (p<0.001), higher BMI (p=0.016), previous c-sections (p<0.001), hypertension (p=0.024), high glucose levels during pregnancy (p=0.031 for early fasting plasma glucose; p=0.002 for 1h and p<0.001 for 2h after glucose overload), nulliparity (p=0.012), multiple gestation (p<0.001), preeclampsia (p=0.012), and placenta previa (p=0.010). Conversely, spontaneous labor onset (p<0.001) and preterm labor (p=0.001) were associated with lower c-section rates. Multivariate analysis confirmed that age (OR 1,048), nulliparity (OR 2.892), previous c-section (OR 14.49), and spontaneous labor onset (OR 0.199) were independent predictors of c-section. The findings emphasize that prior uterine scars significantly increase c-section risk. In contrast, spontaneous labor onset reduces this risk by almost 80%.