Hepatitis C in the three main health institutions in Mexico: a 13-year mortality and hospitalization analysis

There are no studies in Mexico comparing Hepatitis C virus (HCV) epidemiology among Health Institutions. In this report, we described the deaths and hospitalizations due to HCV in the three main Health Institutions in Mexico: the Mexican Institute of Social Security, the Institute of Social Security for State Workers and the Ministry of Health, during the period 2004-2017. A secondary analysis was carried out across the country using hospital administrative death databases. Adult deaths and hospitalizations rates were calculated in reference to the total affiliated population and all-cause in-hospital mortality risk were also evaluated. There were 7,914 deaths and 9,002 hospitalizations due to HCV. Mortality and hospitalization rates of these three institutions together showed a continuous decrease over the analyzed time: the mortality rate dropped from 1.25 to 0.41 per 100,000 affiliates during 2004 and 2017, respectively (66.9% of change), and the hospitalization rate dropped from 2.19 to 0.39 per 100,000 affiliates (81.9% of change). All-cause in-hospital survival accounted for 89.6%. Older age groups and Ministry of Health hospitalizations were associated with higher all-cause in-hospital death rates. In conclusion, the mortality and hospitalizations rates found in this study reflect a decrease in the burden of HCV in Mexico

SARS-CoV-2 infection by trimester of pregnancy and adverse perinatal outcomes: a Mexican retrospective cohort study.

OBJECTIVE: Conflicting evidence for the association between COVID-19 and adverse perinatal outcomes exists. This study examined the associations between maternal COVID-19 during pregnancy and adverse perinatal outcomes including preterm birth (PTB), low birth weight (LBW), small-for-gestational age (SGA), large-for-gestational age (LGA) and fetal death; as well as whether the associations differ by trimester of infection. DESIGN AND SETTING: The study used a retrospective Mexican birth cohort from the Instituto Mexicano del Seguro Social (IMSS), Mexico, between January 2020 and November 2021. PARTICIPANTS: We used the social security administrative dataset from IMSS that had COVID-19 information and linked it with the IMSS routine hospitalisation dataset, to identify deliveries in the study period with a test for SARS-CoV-2 during pregnancy. OUTCOME MEASURES: PTB, LBW, SGA, LGA and fetal death. We used targeted maximum likelihood estimators, to quantify associations (risk ratio, RR) and CIs. We fit models for the overall COVID-19 sample, and separately for those with mild or severe disease, and by trimester of infection. Additionally, we investigated potential bias induced by missing non-tested pregnancies. RESULTS: The overall sample comprised 17 340 singleton pregnancies, of which 30% tested positive. We found that those with mild COVID-19 had an RR of 0.89 (95% CI 0.80 to 0.99) for PTB and those with severe COVID-19 had an RR of 1.53 (95% CI 1.07 to 2.19) for LGA. COVID-19 in the first trimester was associated with fetal death, RR=2.36 (95% CI 1.04, 5.36). Results also demonstrate that missing non-tested pregnancies might induce bias in the associations. CONCLUSIONS: In the overall sample, there was no evidence of an association between COVID-19 and adverse perinatal outcomes. However, the findings suggest that severe COVID-19 may increase the risk of some perinatal outcomes, with the first trimester potentially being a high-risk period

Estimating the effect of realistic improvements of metformin adherence on COVID-19 mortality using targeted machine learning.

BACKGROUND: Type 2 diabetes elevates the risk of severe outcomes in COVID-19 patients, with multiple studies reporting higher case fatality rates. Metformin is a widely used medication for glycemic management. We hypothesize that improved adherence to metformin may lower COVID-19 post-infection mortality risk in this group. Utilizing data from the Mexican Social Security Institute (IMSS), we investigate the relationship between metformin adherence and mortality following COVID-19 infection in patients with chronic metformin prescriptions. METHODS: This is a retrospective cohort study consisting of 61,180 IMSS beneficiaries who received a positive polymerase chain reaction (PCR) or rapid test for SARS-CoV-2 and had at least two consecutive months of metformin prescriptions prior to the positive test. The hypothetical intervention is improved adherence to metformin, measured by proportion of days covered (PDC), with the comparison being the observed metformin adherence values. The primary outcome is all-cause mortality following COVID-19 infection. We defined the causal parameter using shift intervention, an example of modified treatment policies. We used the targeted learning framework for estimation of the target estimand. FINDINGS: Among COVID-19 positive patients with chronic metformin prescriptions, we found that a 5% and 10% absolute increase in metformin adherence is associated with a respective 0.26% (95% CI: -0.28%, 0.79%) and 1.26% (95% CI: 0.72%, 1.80%) absolute decrease in mortality risk. INTERPRETATION: Subject to the limitations of a real-world data study, our results indicate a causal association between improved metformin adherence and reduced COVID-19 post-infection mortality risk

Who is most at risk of dying if infected with SARS-CoV-2? A mortality risk factor analysis using machine learning of patients with COVID-19 over time: a large population-based cohort study in Mexico.

OBJECTIVE: COVID-19 would kill fewer people if health programmes can predict who is at higher risk of mortality because resources can be targeted to protect those people from infection. We predict mortality in a very large population in Mexico with machine learning using demographic variables and pre-existing conditions. DESIGN: Cohort study. SETTING: March 2020 to November 2021 in Mexico, nationally represented. PARTICIPANTS: 1.4 million laboratory-confirmed patients with COVID-19 in Mexico at or over 20 years of age. PRIMARY AND SECONDARY OUTCOME MEASURES: Analysis is performed on data from March 2020 to November 2021 and over three phases: (1) from March to October in 2020, (2) from November 2020 to March 2021 and (3) from April to November 2021. We predict mortality using an ensemble machine learning method, super learner, and independently estimate the adjusted mortality relative risk of each pre-existing condition using targeted maximum likelihood estimation. RESULTS: Super learner fit has a high predictive performance (C-statistic: 0.907), where age is the most predictive factor for mortality. After adjusting for demographic factors, renal disease, hypertension, diabetes and obesity are the most impactful pre-existing conditions. Phase analysis shows that the adjusted mortality risk decreased over time while relative risk increased for each pre-existing condition. CONCLUSIONS: While age is the most important predictor of mortality, younger individuals with hypertension, diabetes and obesity are at comparable mortality risk as individuals who are 20 years older without any of the three conditions. Our model can be continuously updated to identify individuals who should most be protected against infection as the pandemic evolves

SOD2gene Val16Ala polymorphism is associated with macroalbuminuria in Mexican Type 2 Diabetes patients: a comparative study and meta-analysis

Abstract Background Several studies in type 2 diabetes patients have shown significant associations between the SOD2 gene Val16Ala polymorphism and albuminuria, but this association has not been explored in the Mexican population. Methods We evaluated the association between the SOD2 gene Val16Ala polymorphism (rs4880) and macroalbuminuria in a sample of 994 unrelated Mexican type 2 diabetes patients. The study included 119 subjects with urinary albumin >300 mg/dL and 875 subjects with urinary albumin ≤ 30 mg/dL. Genotyping of the SOD2 gene Val16Ala SNP was carried out with Real-Time Polymerase Chain Reaction (RT-PCR). Results The frequency of the TT genotype was 6.7% higher in participants with macroalbuminuria than in the normoalbuminuria group (16.8% vs. 10.1%). Using a logistic regression analysis, we observed that individuals with the CC genotype had significantly lower risks of macroalbuminuria than those with the TT genotype (OR=0.42, p=0.034). We carried out a meta-analysis combining our data with data from four previous studies and estimated an odds ratio (95% CI) for the C allele (with respect to the reference T allele) of 0.65 (0.52-0.80, p<0.001). Conclusions A significant association was found between the SOD2 Val16Ala polymorphism and macroalbuminuria in a sample of Mexican type 2 diabetes patients

Who is most at risk of dying if infected with SARS-CoV-2? A mortality risk factor analysis using machine learning of patients with COVID-19 over time: a large population-based cohort study in Mexico

Objective COVID-19 would kill fewer people if health programmes can predict who is at higher risk of mortality because resources can be targeted to protect those people from infection. We predict mortality in a very large population in Mexico with machine learning using demographic variables and pre-existing conditions.Design Cohort study.Setting March 2020 to November 2021 in Mexico, nationally represented.Participants 1.4 million laboratory-confirmed patients with COVID-19 in Mexico at or over 20 years of age.Primary and secondary outcome measures Analysis is performed on data from March 2020 to November 2021 and over three phases: (1) from March to October in 2020, (2) from November 2020 to March 2021 and (3) from April to November 2021. We predict mortality using an ensemble machine learning method, super learner, and independently estimate the adjusted mortality relative risk of each pre-existing condition using targeted maximum likelihood estimation.Results Super learner fit has a high predictive performance (C-statistic: 0.907), where age is the most predictive factor for mortality. After adjusting for demographic factors, renal disease, hypertension, diabetes and obesity are the most impactful pre-existing conditions. Phase analysis shows that the adjusted mortality risk decreased over time while relative risk increased for each pre-existing condition.Conclusions While age is the most important predictor of mortality, younger individuals with hypertension, diabetes and obesity are at comparable mortality risk as individuals who are 20 years older without any of the three conditions. Our model can be continuously updated to identify individuals who should most be protected against infection as the pandemic evolves

[Procalcitonin as sepsis predictor in cardiovascular surgery with cardiopulmonary bypass]

&lt;p&gt;&lt;strong&gt;Abstract&nbsp;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Background:&nbsp;&lt;/strong&gt;Cardiopulmonary bypass generates an exacerbated response that may lead to sepsis&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective:&lt;/strong&gt;&nbsp;To describe the association between procalcitonin levels and sepsis diagnosis in cardiovascular surgery subjects with cardiopulmonary bypass.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods:&lt;/strong&gt;&nbsp; A case-series study was conducted in 142 patients. Serum procalcitonin levels were measured at 24 hours and at 72 hours after surgery using a point of care testing based on quantitative immunochromatographic method. To assess association between procalcitonin levels and sepsis status, we calculated area under the curve (AUC) and sensitivity, specificity, and predictive values for the best cut-off point.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results:&lt;/strong&gt; From 142 patients studied, 7 developed sepsis after surgery (4.9%). For 24-hours procalcitonin levels AUC was 0.921 and best cut-off point was 3.8 ng/mL (sensitivity 0.857 and specificity 0.904). In the case of 72-hours procalcitonin levels, we observed a value of 0.868 for AUC and best cut-off point was 8.4 ng/mL (sensitivity 0.86 and specificity 0.97).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions:&lt;/strong&gt; Procalcitonin levels at 24 and 72 hours after cardiovascular surgery with cardiopulmonary bypass are associated with sepsis presence at cut-off points of 3.8 and 8.4 ng/mL respectively.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Introducción: &lt;/strong&gt;la circulación extracorpórea durante la cirugía cardiovascular genera una respuesta exacerbada que puede asociarse con sepsis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objetivo:&lt;/strong&gt;&nbsp;describir la asociación entre los niveles de procalcitonina y el diagnóstico de sepsis en sujetos de cirugía cardiovascular con circulación extracorpórea.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Material y métodos:&lt;/strong&gt; se realizó un estudio de serie de casos en 142 pacientes. Los niveles de procalcitonina fueron medidos a las 24 horas y a las 72 horas después de la cirugía. Para evaluar la asociación entre los niveles de procalcitonina y la identificación de sepsis, se calculó el área bajo la curva (AUC) y la sensibilidad y especificidad identificando el mejor punto de corte.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Resultados:&lt;/strong&gt; de un total de 142 pacientes estudiados, 7 desarrollaron sepsis (4.9%). En los niveles de procalcitonina en las 24 horas, el AUC fue de 0.921 y el mejor punto de corte fue 3.8 ng/mL (sensibilidad de 0.857 y especificidad de 0.904). En el caso de los niveles de procalcitonina a las 72 horas, observamos un AUC de 0.868 y el mejor punto de corte fue 8.4 ng/mL (sensibilidad de 0.86 y especificidad de 0.97).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusiones:&lt;/strong&gt; los niveles de procalcitonina a las 24 y 72 horas de la cirugía cardiovascular con circulación extracorpórea se asociaron con la presencia de sepsis con los puntos de corte de 3.8 ng/mL y 8.4 ng/mL respectivamente.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Background:&nbsp;&lt;/strong&gt;Cardiopulmonary bypass generates an exacerbated response that may lead to sepsis&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective:&lt;/strong&gt;&nbsp;To describe the association between procalcitonin levels and sepsis diagnosis in cardiovascular surgery subjects with cardiopulmonary bypass.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods:&lt;/strong&gt;&nbsp; A case-series study was conducted in 142 patients. Serum procalcitonin levels were measured at 24 hours and at 72 hours after surgery using a point of care testing based on quantitative immunochromatographic method. To assess association between procalcitonin levels and sepsis status, we calculated area under the curve (AUC) and sensitivity, specificity, and predictive values for the best cut-off point.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results:&lt;/strong&gt; From 142 patients studied, 7 developed sepsis after surgery (4.9%). For 24-hours procalcitonin levels AUC was 0.921 and best cut-off point was 3.8 ng/mL (sensitivity 0.857 and specificity 0.904). In the case of 72-hours procalcitonin levels, we observed a value of 0.868 for AUC and best cut-off point was 8.4 ng/mL (sensitivity 0.86 and specificity 0.97).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions:&lt;/strong&gt; Procalcitonin levels at 24 and 72 hours after cardiovascular surgery with cardiopulmonary bypass are associated with sepsis presence at cut-off points of 3.8 and 8.4 ng/mL respectively.&lt;/p&gt

Genome-Wide Association Study of Body Mass Index and Body Fat in Mexican-Mestizo Children

Background: Childhood obesity is a major health problem in Mexico. Obesity prevalence estimated by body mass index (BMI) is almost half than that estimated by percent body fat (%BF) in the Childhood Obesity pediatric cohort (COIPIS). Objective. We performed a genome-wide association study (GWAS) of BMI and %BF in 828 children from the COIPIS to identify markers of predisposition to high values for both phenotypes used for obesity classification. Methods: For the GWAS we used the LAT Axiom 1, Affymetrix and 2.5 million single loci from the 1000 Genomes Phase 3 imputation panel. We used a linear model, adjusted by age, sex, and Amerindian ancestry assuming an additive inheritance model. Results. Genome-wide significance (p &le; 5.0 &times; 10&minus;8) and 80% of statistical power was reached for associations of two loci in two genes (CERS3 and CYP2E1) to BMI. Also, 11 loci in six genes (ANKS1B, ARNTL2, KCNS3, LMNB1, SRGAP3, TRPC7) reached genome-wide significance for associations to %BF, though not 80% of statistical power. Discussion: None of the SNPs were previously reported as being associated to BMI or %BF. In addition, different loci were found for BMI and %BF. These results highlight the importance of gaining deeper understanding of genetic markers of predisposition to high values for the phenotypes used for obesity diagnosis

Survival rates and worker compensation expenses in a national cohort of Mexican workers with permanent occupational disability caused by diabetes

Abstract Background Permanent occupational disability is one of the most severe consequences of diabetes that impedes the performance of usual working activities among economically active individuals. Survival rates and worker compensation expenses have not previously been examined among Mexican workers. We aimed to describe the worker compensation expenses derived from pension payments and also to examine the survival rates and characteristics associated with all-cause mortality, in a cohort of 34,014 Mexican workers with permanent occupational disability caused by diabetes during the years 2000–2013 at the Mexican Institute of Social Security. Methods A cross-sectional analysis study was conducted using national administrative records data from the entire country, regarding permanent occupational disability medical certification, pension payment and vital status. Survival rates were estimated using the Kaplan–Meier method. Multivariate Cox proportional hazard model was used to estimate adjusted hazard ratios (HR) and 95 % confidence intervals (95 % CI) in order to assess the cohort characteristics and all-cause mortality risk. Total expenses derived from pension payments for the period were accounted for in U.S. dollars (USD, 2013). Results There were 12,917 deaths in 142,725.1 person-years. Median survival time was 7.26 years. After multivariate adjusted analysis, males (HR, 1.39; 95 % CI, 1.29–1.50), agricultural, forestry, and fishery workers (HR, 1.41; 95 % CI, 1.15–1.73) and renal complications (HR, 3.49; 95 % CI, 3.18–3.83) had the highest association with all-cause mortality. The all-period expenses derived from pension payments amounted to $777.78 million USD (2013), and showed a sustained increment: from$58.28 million USD in 2000 to $111.62 million USD in 2013 (percentage increase of 91.5$ 777 million USD and showed an important increase from 2000 to 2013