Gestational Diabetes Mellitus Subtypes Classified by Oral Glucose Tolerance Test and Maternal and Perinatal Outcomes: Results of a Mexican Multicenter Prospective Cohort Study "Cuido Mi Embarazo".

Purpose: This study explores the impact of gestational diabetes mellitus (GDM) subtypes classified by oral glucose tolerance test (OGTT) values on maternal and perinatal outcomes. Patients and Methods: This multicenter prospective cohort study (May 2019-December 2022) included participants from the Mexican multicenter cohort study Cuido mi Embarazo (CME). Women were classified into four groups per 75-g 2-h OGTT: 1) normal glucose tolerance (normal OGTT), 2) GDM-Sensitivity (isolated abnormal fasting or abnormal fasting in combination with 1-h or 2-h abnormal results), 3) GDM-Secretion (isolated abnormal values at 1-h or 2-h or their combination), and 4) GDM-Mixed (three abnormal values). Cesarean delivery, neonates large for gestational age (LGA), and pre-term birth rates were among the outcomes compared. Between-group comparisons were analyzed using either the t-test, chi-square test, or Fisher's exact test. Results: Of 2,056 Mexican pregnant women in the CME cohort, 294 (14.3%) had GDM; 53.7%, 34.4%, and 11.9% were classified as GDM-Sensitivity, GDM-Secretion, and GDM-Mixed subtypes, respectively. Women with GDM were older (p = 0.0001) and more often multiparous (p = 0.119) vs without GDM. Cesarean delivery (63.3%; p = 0.02) and neonate LGA (10.7%; p = 0.078) were higher in the GDM-Mixed group than the overall GDM group (55.6% and 8.4%, respectively). Pre-term birth was more common in the GDM-Sensitivity group than in the overall GDM group (10.2% vs 8.5%, respectively; p=0.022). At 6 months postpartum, prediabetes was more frequent in the GDM-Sensitivity group than in the overall GDM group (31.6% vs 25.5%). Type 2 diabetes was more common in the GDM-Mixed group than in the overall GDM group (10.0% vs 3.3%). Conclusion: GDM subtypes effectively stratified maternal and perinatal risks. GDM-Mixed subtype increased the risk of cesarean delivery, LGA, and type 2 diabetes postpartum. GDM subtypes may help personalize clinical interventions and optimize maternal and perinatal outcomes.

Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms.

INTRODUCTION: Gestational diabetes mellitus (GDM) is underdiagnosed in Mexico. Early GDM risk stratification through prediction modeling is expected to improve preventative care. We developed a GDM risk assessment model that integrates both genetic and clinical variables. RESEARCH DESIGN AND METHODS: Data from pregnant Mexican women enrolled in the 'Cuido mi Embarazo' (CME) cohort were used for development (107 cases, 469 controls) and data from the 'Mónica Pretelini Sáenz' Maternal Perinatal Hospital (HMPMPS) cohort were used for external validation (32 cases, 199 controls). A 2-hour oral glucose tolerance test (OGTT) with 75 g glucose performed at 24-28 gestational weeks was used to diagnose GDM. A total of 114 single-nucleotide polymorphisms (SNPs) with reported predictive power were selected for evaluation. Blood samples collected during the OGTT were used for SNP analysis. The CME cohort was randomly divided into training (70% of the cohort) and testing datasets (30% of the cohort). The training dataset was divided into 10 groups, 9 to build the predictive model and 1 for validation. The model was further validated using the testing dataset and the HMPMPS cohort. RESULTS: Nineteen attributes (14 SNPs and 5 clinical variables) were significantly associated with the outcome; 11 SNPs and 4 clinical variables were included in the GDM prediction regression model and applied to the training dataset. The algorithm was highly predictive, with an area under the curve (AUC) of 0.7507, 79% sensitivity, and 71% specificity and adequately powered to discriminate between cases and controls. On further validation, the training dataset and HMPMPS cohort had AUCs of 0.8256 and 0.8001, respectively. CONCLUSIONS: We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.

MIDO GDM: an innovative artificial intelligence-based prediction model for the development of gestational diabetes in Mexican women.

Given the barriers to early detection of gestational diabetes mellitus (GDM), this study aimed to develop an artificial intelligence (AI)-based prediction model for GDM in pregnant Mexican women. Data were retrieved from 1709 pregnant women who participated in the multicenter prospective cohort study 'Cuido mi embarazo'. A machine-learning-driven method was used to select the best predictive variables for GDM risk: age, family history of type 2 diabetes, previous diagnosis of hypertension, pregestational body mass index, gestational week, parity, birth weight of last child, and random capillary glucose. An artificial neural network approach was then used to build the model, which achieved a high level of accuracy (70.3%) and sensitivity (83.3%) for identifying women at high risk of developing GDM. This AI-based model will be applied throughout Mexico to improve the timing and quality of GDM interventions. Given the ease of obtaining the model variables, this model is expected to be clinically strategic, allowing prioritization of preventative treatment and promising a paradigm shift in prevention and primary healthcare during pregnancy. This AI model uses variables that are easily collected to identify pregnant women at risk of developing GDM with a high level of accuracy and precision.

Novel clinical and immunological features associated with persistent post-acute sequelae of COVID-19 after six months of follow-up: a pilot study.

BACKGROUND: Currently, there is scant information regarding the features associated to the persistence of post-COVID-19 syndrome, which is the main aim of the present study. METHODS: A cohort study of 102 COVID-19 patients was conducted. The post-COVID-19 symptoms were assessed by a standardised questionnaire. Lymphocyte immunophenotyping was performed by flow cytometry and chemokines/cytokines, neutrophil extracellular traps, the tripartite motif 63, anti-cellular, and anti-SARS-CoV-2 IgG antibodies were addressed in serum. The primary outcome was the persistence of post-COVID-19 syndrome after six months follow-up. RESULTS: Thirteen patients (12.7%) developed the primary outcome and had a more frequent history of post-COVID-19 syndrome 3 months after infection onset (p = .044), increased levels of IL-1α (p = .011) and IP-10 (p = .037) and increased CD57 expression in CD8+ T cells (p = .003). There was a trend towards higher levels of IFN-γ (p = .051), IL-1ß (p = .062) and IL-6 (p = .087). The history of post COVID-19 in the previous 3 months, obesity, baseline serum MIP-1α and IP-10, and CD57 expression in CD8+ T cells were independently associated with the persistence of post-COVID-19 syndrome. CONCLUSION: Our data suggest an important relationship between a pro-inflammatory state mediated through metabolic pathways related to obesity and increased cellular senescence as a key element in the persistence of post-COVID-19 syndrome at six months of follow-up.

Diagnostic Accuracy of Capillary Blood Glucometer Testing for Gestational Diabetes.

Purpose: Few pregnant women in low-resource settings are screened for gestational diabetes mellitus (GDM) using the gold standard oral glucose tolerance test (OGTT). This study compared capillary blood glucose testing with 2-h plasma glucose measurements obtained using the 75-g OGTT to screen for GDM at primary healthcare clinics in Mexico. Patients and Methods: Pregnant women who participated in a previous prospective multicenter longitudinal cohort study and who had not been previously diagnosed with diabetes were included. Participants were evaluated using the plasmatic 2-h 75-g OGTT with simultaneous capillary blood glucose measurements using a glucometer. The study endpoint was the comparability of the glucometer results to the gold standard OGTT when collected simultaneously. Sensitivity, specificity, and area under the curve of the glucose measurements obtained for capillary blood compared with venous plasma (gold standard) were calculated to determine diagnostic accuracy. Results: The study included 947 pregnant women who had simultaneous glucose measurements available (blood capillary [glucometer] and venous blood OGTT). Overall, capillary blood glucose testing was very sensitive (89.47%); the specificity was 66.58% and the area under the curve (95% confidence interval) was 0.78 (0.74-0.81). The sensitivity, specificity and area under the curve of each capillary measurement were: 89.47%, 66.58% and 0.78 (0.74-0.82) for the fasting measurement, 91.53%, 93.24% and 0.92 (0.88-0.96) for the one-hour measurement, and 89.80%, 93.32%, 0.91 (0.87-0.95) for the second-hour measurement, respectively. No adverse events were reported. Conclusion: Capillary OGTT is a valid alternative to the gold standard OGTT for screening of GDM in low-resource situations or in situations where there are other limitations to performing the OGTT as part of primary healthcare services.

Clinical and immunological features associated to the development of a sustained immune humoral response in COVID-19 patients: Results from a cohort study.

Background: Until now, most of the research addressing long-term humoral responses in coronavirus disease 2019 (COVID-19) had only evaluated the serum titers of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgGs, without the assessment of the baseline antiviral clinical and immune profile, which is the aim of this study and may be the key factor leading to a broad and sustained antibody response. Methods: We included 103 patients with COVID-19. When the patients sought medical attention (baseline), a blood sample was drawn to perform immunophenotype of lymphocytes by flow cytometry. The patients were assessed 15 days after baseline and then every month until the third month, followed by a last visit 6 months after recruitment. We evaluated the anti-SARS-COV-2 IgG at all time points, and the serum levels of cytokines, chemokines, anti-cellular (AC) antibodies and neutrophil extracellular traps were also assessed during the follow-up. The primary outcome of the study was the presence of a sustained immune humoral response, defined as an anti-SARS-CoV-2 IgG titer >4.99 arbitrary units/mL in at least two consecutive measures. We used generalized lineal models to assess the features associated with this outcome and to assess the effect of the changes in the cytokines and chemokines throughout time on the development of a sustained humoral immune response. Results: At baseline the features associated to a sustained immune humoral response were the diagnosis of critical disease, absolute number of lymphocytes, serum IP-10, IL-4, IL-2, regulatory T cells, CD8+ T cells, and positive AC antibodies. Critical illness and the positivity of AC antibodies were associated with a sustained humoral immune response after 3 months, whilst critical illness and serum IL-13 were the explanatory variables after 6 months. Conclusion: A sustained immune humoral response is strongly related to critical COVID-19, which is characterized by the presence of AC antibodies, quantitative abnormalities in the T cell compartment, and the serum cytokines and chemokines during acute infection and throughout time.

Symptom cluster analysis of long COVID-19 in patients discharged from the Temporary COVID-19 Hospital in Mexico City.

INTRODUCTION: Several reports have emerged describing the long-term consequences of COVID-19 and its effects on multiple systems. METHODS: As further research is needed, we conducted a longitudinal observational study to report the prevalence and associated risk factors of the long-term health consequences of COVID-19 by symptom clusters in patients discharged from the Temporary COVID-19 Hospital (TCH) in Mexico City. Self-reported clinical symptom data were collected via telephone calls over 90 days post-discharge. Among 4670 patients, we identified 45 symptoms across eight symptom clusters (neurological; mood disorders; systemic; respiratory; musculoskeletal; ear, nose, and throat; dermatological; and gastrointestinal). RESULTS: We observed that the neurological, dermatological, and mood disorder symptom clusters persisted in >30% of patients at 90 days post-discharge. Although most symptoms decreased in frequency between day 30 and 90, alopecia and the dermatological symptom cluster significantly increased (p < 0.00001). Women were more prone than men to develop long-term symptoms, and invasive mechanical ventilation also increased the frequency of symptoms at 30 days post-discharge. CONCLUSION: Overall, we observed that symptoms often persisted regardless of disease severity. We hope these findings will help promote public health strategies that ensure equity in the access to solutions focused on the long-term consequences of COVID-19.

Rapid establishment of a dedicated COVID-19 hospital in Mexico city during a public health crisis.

Healthcare systems worldwide have adapted and reorganized during the coronavirus disease 2019 (COVID-19) pandemic. Here, we provide a framework based on a public-private partnership that funded, developed, and operated a temporary COVID-19 hospital in Mexico City. We describe the creation of a collaborative network of primary healthcare triage centers and hospitals distributed throughout the city in recognition of demographic and geographic patterns that correlate with COVID-19 infections, including marginalized and impoverished areas of Mexico City. Additionally, we also report the hospital's cumulative outcomes over the 14 months of operation and show that it is feasible to transform a large public venue into a specialized hospital that incorporates a digital platform with robust clinical protocols to provide positive clinical outcomes.

During Mexico's response to the COVID-19 pandemic, the Carlos Slim Foundation (CSF), with a group of local foundations, academic institutions, and the Government of Mexico City, established a synergistic public­private partnership with the purpose of funding, designing, developing, and operating a dedicated COVID-19 hospital. This was achieved in 17 days by rapidly transforming into a hospital the largest convention center in Latin America, which is located in the heart of Mexico City. An ex professo network of eight dedicated respiratory triage community centers in coordination with other 40 federal and state primary health care clinics and hospitals was also established to streamline patient referral, thereby mitigating the impact of the COVID-19 pandemic in Mexico City's metropolitan area. We provide a framework for designing, funding, and executing the operations of a dedicated hospital in response to the COVID-19 pandemic that, from its conception, execution, operation, and closure, involved an exemplary coordination between public-private partnerships during a public health crisis. Referral, admission, treatment, clinical monitoring, discharge, and household follow-up were facilitated by the COVID360 digital health platform. The successful development and implementation of this multi-faceted digital platform allowed a lean patient-centered process, the management of clinical and administrative data, training of healthcare professionals, and the dissemination of accurate health information for data-driven decision making. This rapidly implemented temporary hospital dedicated to the comprehensive care of patients with COVID-19 was critical in coping with the increasing number of cases in Mexico City while achieving outstanding clinical outcomes.

Impact of preemptive hospitalization on health outcomes at the temporary COVID-19 hospital in Mexico City: a prospective observational study.

INTRODUCTION: In response to the evolution of the coronavirus disease 2019 (COVID-19) pandemic, the admission protocol for the temporary COVID-19 hospital in Mexico City has been updated to hospitalize patients preemptively with an oxygen saturation (SpO2) of >90%. METHODS: This prospective, observational, single-center study compared the progression and outcomes of patients who were preemptively hospitalized versus those who were hospitalized based on an SpO2 ⩽90%. We recorded patient demographics, clinical characteristics, COVID-19 symptoms, and oxygen requirement at admission. We calculated the risk of disease progression and the benefit of preemptive hospitalization, stratified by CALL Score: age, lymphocyte count, and lactate dehydrogenase (<8 and ⩾8) at admission. RESULTS: Preemptive hospitalization significantly reduced the requirement for oxygen therapy (odds ratio 0.45, 95% confidence interval 0.31-0.66), admission to the intensive care unit (ICU) (0.37, 0.23-0.60), requirement for invasive mechanical ventilation (IMV) (0.40, 0.25-0.64), and mortality (0.22, 0.10-0.50). Stratification by CALL score at admission showed that the benefit of preemptive hospitalization remained significant for patients requiring oxygen therapy (0.51, 0.31-0.83), admission to the ICU (0.48, 0.27-0.86), and IMV (0.51, 0.28-0.92). Mortality risk remained significantly reduced (0.19, 0.07-0.48). CONCLUSION: Preemptive hospitalization reduced the rate of disease progression and may be beneficial for improving COVID-19 patient outcomes.

Environmental Tobacco Exposure and Urinary Cotinine Levels in Smoking and Nonsmoking Adolescents.

Objective: We aimed to evaluate the association between environmental tobacco smoke (ETS) exposure and urinary cotinine levels in current adolescent smokers and nonsmokers. The secondary objective was to explore the association between ETS exposure and nicotine dependence in adolescent smokers. Methods: Using the results from a validation study for the 2012 Global Youth Tobacco Survey in Mexico, we quantified urinary cotinine levels in adolescent smokers and nonsmokers. We fitted a multivariate regression model to assess the association between household exposure to ETS and cotinine levels in adolescent smokers and nonsmokers. In addition, using the questionnaire's answers for morning cravings, we fitted a multivariate Poisson regression model to explore the association between household ETS exposure and nicotine dependence in adolescent smokers. Results: For each day of household ETS exposure, cotinine levels increase by 5% in adolescent smokers compared to a 2% increase in nonsmokers, adjusting for the number of cigarettes smoked per week, age and sex (exp(ß) 1.05; 95% confidence interval [CI] [1.00, 1.10]; p = .041). Morning cravings increase 11% for each day of household ETS exposure adjusting for the number of cigarettes smoked per week, age and sex (prevalence ratio [PR] 1.11; 95% CI [0.99, 1.25]; p = .064). Conclusions: There is an association between ETS exposure and cotinine levels, and ETS may contribute to nicotine dependence in adolescent smokers. If confirmed, avoiding ETS exposure could prove helpful for addiction control and quitting in adolescents. Implications: Evidence suggests that ETS increases cotinine levels in nonsmokers and adult smokers. However, no study has explored the association between ETS exposure and cotinine levels and addiction in adolescent smokers. This paper provides evidence of an association between ETS exposure and cotinine levels in adolescent smokers: each day of environmental tobacco smoke exposure at home increased cotinine levels by 5% among smokers. In addition, morning cravings in adolescent smokers increased 11% for every day of ETS exposure. ETS exposure is a significant source of nicotine for adolescent smokers and could play an important role in addiction.