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.

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.

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.

Integrated Measurement for Early Detection (MIDO) as a digital strategy for timely assessment of non-communicable disease profiles and factors associated with unawareness and control: a retrospective observational study in primary healthcare facilities in Mexico.

OBJECTIVES: The Carlos Slim Foundation implemented the Integrated Measurement for Early Detection (MIDO), a screening strategy for non-communicable diseases (NCDs) in Mexico as part of CASALUD, a portfolio of digital health services focusing on healthcare delivery and prevention/management of NCDs. We investigated the disease profile of the screened population and evaluated MIDO's contribution to the continuum of care of the main NCDs. DESIGN: Using data from MIDO and the chronic diseases information system, we quantified the proportion of the population screened and diagnosed with NCDs, and measured care linkage/retention and level of control achieved. We analysed comorbidity patterns and estimated prevalence of predisease stages. Finally, we estimated characteristics associated with unawareness and control of NCDs, and examined efficacy of the CASALUD model in improving NCD control. SETTING: Public primary health centres in 27/32 Mexican states. PARTICIPANTS: Individuals aged ≥20 years lacking healthcare access. RESULTS: From 2014 to 2018, 743 000 individuals were screened using MIDO. A predisease or disease condition was detected in ≥70% of the population who were unaware of their NCD status. The screening identified 38 417 new cases of type 2 diabetes, 53 133 new cases of hypertension and 208 627 individuals with obesity. Dyslipidaemia was found in 77.3% of individuals with available blood samples. Comorbidities were highly prevalent, especially in people with obesity. Only 5.47% (n=17 774) of individuals were linked with their corresponding primary health centre. Factors associated with unawareness of and uncontrolled NCDs were sex, age, and social determinants, for example, rural/urban environment, access to healthcare service, and education level. Patients with type 2 diabetes treated at clinics under the CASALUD model were more likely to achieve disease control (OR: 1.32, 95% CI: 1.09 to 1.61). CONCLUSION: Patient-centred screening strategies such as MIDO are urgently needed to improve screening, access, retention and control for patients with NCDs.

Supply-side interventions to improve health: Findings from the Salud Mesoamérica Initiative.

BACKGROUND: Results-based aid (RBA) is increasingly used to incentivize action in health. In Mesoamerica, the region consisting of southern Mexico and Central America, the RBA project known as the Salud Mesoamérica Initiative (SMI) was designed to target disparities in maternal and child health, focusing on the poorest 20% of the population across the region. METHODS AND FINDINGS: Data were first collected in 365 intervention health facilities to establish a baseline of indicators. For the first follow-up measure, 18 to 24 months later, 368 facilities were evaluated in these same areas. At both stages, we measured a near-identical set of supply-side performance indicators in line with country-specific priorities in maternal and child health. All countries showed progress in performance indicators, although with different levels. El Salvador, Honduras, Nicaragua, and Panama reached their 18-month targets, while the State of Chiapas in Mexico, Guatemala, and Belize did not. A second follow-up measurement in Chiapas and Guatemala showed continued progress, as they achieved previously missed targets nine to 12 months later, after implementing a performance improvement plan. CONCLUSIONS: Our findings show an initial success in the supply-side indicators of SMI. Our data suggest that the RBA approach can be a motivator to improve availability of drugs and services in poor areas. Moreover, our innovative monitoring and evaluation framework will allow health officials with limited resources to identify and target areas of greatest need.

Online continuing medical education as a key link for successful noncommunicable disease self-management: the CASALUD™ Model.

PURPOSE: The purpose of this study is to evaluate how the benefits of online continuing medical education (CME) provided to health care professionals traveled along a patient "educational chain". In this study, the educational chain begins with the influence that CME can have on the quality of health care, with subsequent influence on patient knowledge, disease self-management, and disease biomarkers. METHODS: A total of 422 patients with at least one noncommunicable disease (NCD) treated in eight different Mexican public health clinics were followed over 3 years. All clinics were participants in the CASALUD Model, an NCD care model for primary care, where all clinic staff were offered CME. Data were collected through a questionnaire on health care, patient disease knowledge, and self-management behaviors; blood samples and anthropometric measurements were collected to measure patient disease biomarkers. RESULTS: Between 2013 and 2015, the indexes measuring quality of health care, patient health knowledge, and diabetes self-management activities rose moderately but significantly (from 0.54 to 0.64, 0.80 to 0.84, and 0.62 to 0.67, respectively). Performing self-care activities - including owning and using a glucometer and belonging to a disease support group - saw the highest increase (from 0.65 to 0.75). A1C levels increased between 2013 and 2015 from 7.95 to 8.41% (63-68 mmol/mol) (P<0.001), and blood pressure decreased between 2014 and 2015 from 143.7/76.8 to 137.5/74.4 (systolic/diastolic reported in mmHg) (P<0.001). The mean levels of other disease biomarkers remained statistically unchanged, despite the improvements seen in the previous "links" of the educational chain. CONCLUSION: Online CME can effect certain changes in the educational chain linking quality of health care, patient knowledge, and self-management behaviors. However, in order to assure adequate NCD control, the entire health care system must be improved in tandem. Online CME programs, such as CASALUD's, are feasible strategies for impacting changes in disease self-management at a clinic level throughout a country.

A Policy Analysis on the Proactive Prevention of Chronic Disease: Learnings from the Initial Implementation of Integrated Measurement for Early Detection (MIDO).

Mexico, like many low- and middle-income countries (LMICs), faces an epidemic of chronic non-communicable diseases (NCDs), specifically diabetes, hypertension, obesity, and lipid disorders. Many people with these NCDs may not be aware that they have a disease, pointing to the need for broader screening programs. The traditional prevention policy in Mexico was based on screening with a paper-based risk factor questionnaire. However, this was used to screen patients already seeking healthcare services at facilities, and screening goals were set as a function of the number of questionnaires applied, not number of individuals screened. Due to this, Fundación Carlos Slim developed Medición Integrada para la Detección Oportuna (MIDOTM), or Integrated Measurement for Early Detection, an NCD screening and proactive prevention policy. This document is a policy analysis based on early learnings from the initial implementation of MIDO in eight primary healthcare centers in two central Mexican states. MIDO was found to expand screening programs beyond clinic walls, systematize community screening strategies, emphasize the detection of pre-disease phases, incorporate lifestyle counseling, and propose screening goals based on population targets. In collaboration with the Mexican Ministry of Health, MIDO has successfully screened over 500 000 individuals-about 40% of whom would not have been screened under previous policies. Of these more than 500 000 screened individuals, 13.4% had pre-diabetes (fasting glucose between 100 and 125 mg/dL), and 5.8% had undiagnosed diabetes (defined as fasting glucose above 126 mg/dL or random glucose above 200 mg/dL). However, there is still room for improvement in linking positive results from screening with disease confirmation and with patient incorporation into disease management. The experience of implementing MIDO in Mexico suggests that primary and secondary prevention programs in other parts of the world should consider the need for population-based screening targets, a greater focus on pre-disease stages, and the streamlining of the transition between screening, confirmation of diagnosis, and incorporation of patients into the healthcare system.

Enablers and inhibitors of the implementation of the Casalud Model, a Mexican innovative healthcare model for non-communicable disease prevention and control.

BACKGROUND: The Mexican healthcare system is under increasing strain due to the rising prevalence of non-communicable diseases (especially type 2 diabetes), mounting costs, and a reactive curative approach focused on treating existing diseases and their complications rather than preventing them. Casalud is a comprehensive primary healthcare model that enables proactive prevention and disease management throughout the continuum of care, using innovative technologies and a patient-centred approach. METHODS: Data were collected over a 2-year period in eight primary health clinics (PHCs) in two states in central Mexico to identify and assess enablers and inhibitors of the implementation process of Casalud. We used mixed quantitative and qualitative data collection tools: surveys, in-depth interviews, and participant and non-participant observations. Transcripts and field notes were analyzed and coded using Framework Analysis, focusing on defining and describing enablers and inhibitors of the implementation process. RESULTS: We identified seven recurring topics in the analyzed textual data. Four topics were categorized as enablers: political support for the Casalud model, alignment with current healthcare trends, ongoing technical improvements (to ease adoption and support), and capacity building. Three topics were categorized as inhibitors: administrative practices, health clinic human resources, and the lack of a shared vision of the model. CONCLUSIONS: Enablers are located at PHCs and across all levels of government, and include political support for, and the technological validity of, the model. The main inhibitor is the persistence of obsolete administrative practices at both state and PHC levels, which puts the administrative feasibility of the model's implementation in jeopardy. Constructing a shared vision around the model could facilitate the implementation of Casalud as well as circumvent administrative inhibitors. In order to overcome PHC-level barriers, it is crucial to have an efficient and straightforward adaptation and updating process for technological tools. One of the key lessons learned from the implementation of the Casalud model is that a degree of uncertainty must be tolerated when quickly scaling up a healthcare intervention. Similar patient-centred technology-based models must remain open to change and be able to quickly adapt to changing circumstances.