Traditional Atlantic Diet and Its Effect on Health and the Environment: A Secondary Analysis of the GALIAT Cluster Randomized Clinical Trial.

Importance: The universal call to action for healthier and more sustainable dietary choices is the framework of the United Nations's Sustainable Development Goals. The Atlantic diet, originating from the northwest of the Iberian Peninsula, represents an example of a traditional diet that aligns with these principles. Objective: To explore a 6-month intervention based on the Atlantic diet's effects on metabolic and environmental health, assessing metabolic syndrome (MetS) incidence and the carbon footprint. Design, Setting, and Participants: The Galician Atlantic Diet study was a 6-month randomized clinical trial designed to assess the effects of this regional traditional diet on families' eating habits. The study was conducted from March 3, 2014, to May 29, 2015, at a local primary health care center in the rural town of A Estrada in northwestern Spain and involved a multisectoral collaboration. Families were randomly selected from National Health System records and randomized 1:1 to an intervention or control group. This secondary analysis of the trial findings was performed between March 24, 2021, and November 7, 2023. Interventions: Over 6 months, families in the intervention group received educational sessions, cooking classes, written supporting material, and foods characteristic of the Atlantic diet, whereas those randomized to the control group continued with their habitual lifestyle. Main Outcomes and Measures: The main outcomes were MetS incidence, defined per National Cholesterol Education Program Adult Treatment Panel III guidelines, and carbon footprint emissions as an environmental metric using life cycle assessment with daily dietary intake as the functional unit. Results: Initially, 250 families were randomized (574 participants; mean [SD] age, 46.8 [15.7] years; 231 males [40.2%] and 343 females [59.8%]). The intervention group included 126 families (287 participants) and the control group, 124 families (287 participants). Ultimately, 231 families completed the trial. The intervention significantly reduced the risk of incident cases of MetS (rate ratio, 0.32; 95% CI, 0.13-0.79) and had fewer MetS components (proportional odds ratio, 0.58; 95% CI, 0.42-0.82) compared with the control condition. The intervention group did not have a significantly reduced environmental impact in terms of carbon footprint emissions compared with the control group (-0.17 [95% CI, -0.46 to 0.12] kg CO2 equivalents/person/d). Conclusions and Relevance: These findings provide important evidence that a family-focused dietary intervention based on a traditional diet can reduce the risk of incident MetS. Further research is needed to understand the underlying mechanisms and determine the generalizability to other populations, taking into account regional cultural and dietary variations. Trial Registration: ClinicalTrials.gov Identifier: NCT02391701.

Usefulness of a predictive model to hospitalize patients with low-risk community-acquired pneumonia.

INTRODUCTION: A high proportion of patients with low-risk community-acquired pneumonia (CAP) (classes I-III of the Pneumonia Severity Index) are hospitalized. The purpose of this study was to determine whether validated severity scales are used in clinical practice to make admission decisions, identify the variables that influence this decision, and evaluate the potential predictive value of these variables. MATERIALS AND METHODS: A prospective, observational study of patients ≥ 18 years of age with a diagnosis of low-risk CAP hospitalized or referred from the Emergency Department to outpatient consultations. A multivariate logistic regression predictive model was built to predict the decision to hospitalize a patient. RESULTS: The study population was composed of 1,208 patients (806 inpatients and 402 outpatients). The severity of CAP was estimated in 250 patients (20.7%). The factors that determined hospitalization were "abnormal findings in complementary studies" (643/806: 79.8%; due to respiratory failure in 443 patients) and "signs of clinical deterioration" [64/806 (7.9%): hypotension (16/64, 25%); hemoptoic expectoration (12/64, 18.8%); tachypnea (10/64, 15.6%)]. In total, ambulatory management was not contraindicated in 24.7% of hospitalized patients (199). The predictive model built to decide about hospitalization had a good power of discrimination (AUC 0.876; 95%CI: 0.855-0.897). CONCLUSIONS: Scales are rarely used to estimate the severity of CAP at the emergency department. The decision to hospitalize or not a patient largely depends on the clinical experience of the physician. Our predictive model showed a good power to discriminate the patients who required hospitalization. Further studies are warranted to validate these results.

Role of Soluble ST2 Biomarker in Predicting Recurrence of Atrial Fibrillation after Electrical Cardioversion or Pulmonary Vein Isolation.

This study aims to determine the predictive value of the soluble suppression of tumorigenicity 2 (sST2) biomarker in atrial fibrillation (AF) recurrence. This prospective, observational study included patients with AF referred for electrical cardioversion (ECV) or pulmonary vein isolation (PVI) procedures. Baseline characteristics were collected, and sST2 was determined at baseline and at 3 and 6 months of follow-up. sST2 was determined at baseline in a matched control group. Left atrial voltage mapping was performed in patients undergoing PVI. The sST2 maximal predictive capacity of AF recurrence was at the 3-month FU in the cohort of patients undergoing ECV with respect to 6-month AF recurrence with an AUC of 0.669, a cut-off point of 15,511 pg/mL, a sensitivity of 60.97%, and a specificity of 69.81%. The ROC curve of the sST2 biomarker at baseline and 3 months in the cohort of patients undergoing PVI showed AUCs of 0.539 and 0.490, respectively. The logistic regression model identified the rhythm (AF) and the sST2 biomarker at 3 months as independent factors for recurrence at 6 months in the ECV cohort. In the logistic regression model, sST2 was not an independent factor for recurrence at 6 months of follow-up in the PVI cohort. In patients who underwent ECV, sST2 values at 3 months may provide utility to predict AF recurrence at 6 months of follow-up. In patients who underwent PVI, sST2 had no value in predicting AF recurrence at 6 months of follow-up.

Reproducibility of continuous glucose monitoring results under real-life conditions in an adult population: a functional data analysis.

Continuous glucose monitoring systems (CGM) are a very useful tool to understand the behaviour of glucose in different situations and populations. Despite the widespread use of CGM systems in both clinical practice and research, our understanding of the reproducibility of CGM data remains limited. The present work examines the reproducibility of the results provided by a CGM system in a random sample of a free-living adult population, from a functional data analysis approach. Functional intraclass correlation coefficients (ICCs) and their 95% confidence intervals (CI) were calculated to assess the reproducibility of CGM results in 581 individuals. 62% were females 581 participants (62% women) mean age 48 years (range 18-87) were included, 12% had previously been diagnosed with diabetes. The inter-day reproducibility of the CGM results was greater for subjects with diabetes (ICC 0.46 [CI 0.39-0.55]) than for normoglycaemic subjects (ICC 0.30 [CI 0.27-0.33]); the value for prediabetic subjects was intermediate (ICC 0.37 [CI 0.31-0.42]). For normoglycaemic subjects, inter-day reproducibility was poorer among the younger (ICC 0.26 [CI 0.21-0.30]) than the older subjects (ICC 0.39 [CI 0.32-0.45]). Inter-day reproducibility was poorest among normoglycaemic subjects, especially younger normoglycaemic subjects, suggesting the need to monitor some patient groups more often than others.

Development of prognostic models to estimate the probability of lung injury one year after COVID-19-related hospitalization-a prospective study.

Background: Long-term effects of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection still under study. The objectives of this study were to identify persistent pulmonary lesions 1 year after coronavirus disease 2019 (COVID-19) hospitalization and assess whether it is possible to estimate the probability that a patient develops these complications in the future. Methods: A prospective study of ≥18 years old patients hospitalized for SARS-COV-2 infection who develop persistent respiratory symptoms, lung function abnormalities or have radiological findings 6-8 weeks after hospital discharge. Logistic regression models were used to identify prognostic factors associated with a higher risk of developing respiratory problems. Models performance was assessed in terms of calibration and discrimination. Results: A total of 233 patients [median age 66 years [interquartile range (IQR): 56, 74]; 138 (59.2%) male] were categorized into two groups based on whether they stayed in the critical care unit (79 cases) or not (154). At the end of follow-up, 179 patients (76.8%) developed persistent respiratory symptoms, and 22 patients (9.4%) showed radiological fibrotic lesions with pulmonary function abnormalities (post-COVID-19 fibrotic pulmonary lesions). Our prognostic models created to predict persistent respiratory symptoms [post-COVID-19 functional status at initial visit (the higher the score, the higher the risk), and history of bronchial asthma] and post-COVID-19 fibrotic pulmonary lesions [female; FVC% (the higher the FVC%, the lower the probability); and critical care unit stay] one year after infection showed good (AUC 0.857; 95% CI: 0.799-0.915) and excellent performance (AUC 0.901; 95% CI: 0.837-0.964), respectively. Conclusions: Constructed models show good performance in identifying patients at risk of developing lung injury one year after COVID-19-related hospitalization.

Multivariate reference and tolerance regions based on conditional transformation models: Application to glycemic markers.

The reference interval is the most widely used medical decision-making, constituting a central tool in determining whether an individual is healthy or not. When the results of several continuous diagnostic tests are available for the same patient, their clinical interpretation is more reliable if a multivariate reference region (MVR) is available rather than multiple univariate reference intervals. MVRs, defined as regions containing 95% of the results of healthy subjects, extend the concept of the reference interval to the multivariate setting. However, they are rarely used in clinical practice owing to difficulties associated with their interpretability and the restrictions inherent to the assumption of a Gaussian distribution. Further statistical research is thus needed to make MVRs more applicable and easier for physicians to interpret. Since the joint distribution of diagnostic test results may well change with patient characteristics independent of disease status, MVRs adjusted for covariates are desirable. The present work introduces a novel formulation for MVRs based on multivariate conditional transformation models (MCTMs). Additionally, we take into account the estimation uncertainty of such MVRs by means of tolerance regions. These conditional MVRs imply no parametric restriction on the response, and potentially nonlinear continuous covariate effects can be estimated. MCTMs allow the estimation of the effects of covariates on the joint distribution of multivariate response variables and on these variables' marginal distributions, via the use of most likely transformation estimation. Our contributions proved reliable when tested with simulated data and for a real data application with two glycemic markers.

Histological and histomorphometric study of human palatal mucosa: Implications for connective tissue graft harvesting.

AIMS: To analyse the histological structure and histomorphometric characteristics of human hard palatal mucosa in order to determine the donor site of choice for connective tissue grafts from a histological point of view. MATERIALS AND METHODS: Palatal mucosa samples from six cadaver heads were harvested at four sites: incisal, premolar, molar and tuberosity. Histological and immunohistochemical techniques were performed, as was histomorphometric analysis. RESULTS: In the current study, we found that the density and size of cells were higher in the superficial papillary layer, whereas the thickness of the collagen bundles increased in the reticular layer. Excluding the epithelium, the mean percentage of lamina propria (LP) and submucosa (SM) was 37% and 63%, respectively (p < .001). LP thickness showed similar values in the incisal, premolar and molar regions, and a significantly greater thickness in tuberosity (p < .001). The thickness of SM increased from incisal to premolar and molar, disappearing in the tuberosity (p < .001). CONCLUSIONS: As dense connective tissue of LP is the tissue of choice for connective tissue grafts, the best donor site from a histological point of view is tuberosity because it is composed only of a thick LP without the presence of a loose submucosal layer.

A cross-country study on the impact of governmental responses to the COVID-19 pandemic on perinatal mental health.

This study aimed to analyse the role of governmental responses to the coronavirus disease 2019 (COVID-19) outbreak, measured by the Containment and Health Index (CHI), on symptoms of anxiety and depression during pregnancy and postpartum, while considering the countries' Inequality-adjusted Human Development Index (IHDI) and individual factors such as age, gravidity, and exposure to COVID-19. A cross-sectional study using baseline data from the Riseup-PPD-COVID-19 observational prospective international study (ClinicalTrials.gov: NCT04595123) was carried out between June and October 2020 in 12 countries (Albania, Brazil, Bulgaria, Chile, Cyprus, Greece, Israel, Malta, Portugal, Spain, Turkey, and the United Kingdom). Participants were 7645 pregnant women or mothers in the postpartum period-with an infant aged up to 6 months-who completed the Edinburgh Postnatal Depression Scale (EPDS) or the Generalised Anxiety Disorder Assessment (GAD-7) during pregnancy or the postpartum period. The overall prevalence of clinically significant depression symptoms (EPDS ≥ 13) was 30%, ranging from 20,5% in Cyprus to 44,3% in Brazil. The prevalence of clinically significant anxiety symptoms (GAD-7 ≥ 10) was 23,6% (ranging from 14,2% in Israel and Turkey to 39,5% in Brazil). Higher symptoms of anxiety or depression were observed in multigravida exposed to COVID-19 or living in countries with a higher number of deaths due to COVID-19. Furthermore, multigravida from countries with lower IHDI or CHI had higher symptoms of anxiety and depression. Perinatal mental health is context-dependent, with women from more disadvantaged countries at higher risk for poor mental health. Implementing more restrictive measures seems to be a protective factor for mental health, at least in the initial phase of the COVID-19.

Age-Related Changes in Serum N-Glycome in Men and Women-Clusters Associated with Comorbidity.

(1) Aim: To describe, in a general adult population, the serum N-glycome in relation to age in men and women, and investigate the association of N-glycome patterns with age-related comorbidity; (2) Methods: The serum N-glycome was studied by hydrophilic interaction chromatography with ultra-performance liquid chromatography in 1516 randomly selected adults (55.3% women; age range 18-91 years). Covariates included lifestyle factors, metabolic disorders, inflammatory markers, and an index of comorbidity. Principal component analysis was used to define clusters of individuals based on the 46 glycan peaks obtained in chromatograms; (3) Results: The serum N-glycome changed with ageing, with significant differences between men and women, both in individual N-glycan peaks and in groups defined by common features (branching, galactosylation, sialylation, fucosylation, and oligomannose). Through K-means clustering algorithm, the individuals were grouped into a cluster characterized by abundance of simpler N-glycans and a cluster characterized by abundance of higher-order N-glycans. The individuals of the first cluster were older, showed higher concentrations of glucose and glycation markers, higher levels of some inflammatory markers, lower glomerular filtration rate, and greater comorbidity index; (4) Conclusions: The serum N-glycome changes with ageing with sex dimorphism. The N-glycome could be, in line with the inflammaging hypothesis, a marker of unhealthy aging.

Time above range for predicting the development of type 2 diabetes.

Aim: To investigate the prognostic value of time range metrics, as measured by continuous glucose monitoring, with respect to the development of type 2 diabetes (T2D). Research design and methods: A total of 499 persons without diabetes from the general population were followed-up for 5 years. Time range metrics were measured at the start and medical records were checked over the period study. Results: Twenty-two subjects (8.3 per 1,000 person-years) developed T2D. After adjusting for age, gender, family history of diabetes, body mass index and glycated hemoglobin concentration, multivariate analysis revealed 'time above range' (TAR, i.e., with a plasma glucose concentration of >140 mg/dL) to be significantly associated with a greater risk (OR = 1.06, CI 1.01-1.11) of developing diabetes (AUC = 0.94, Brier = 0.035). Conclusions: Time above range provides additional information to that offered by glycated hemoglobin to identify patients at a higher risk of developing type 2 diabetes in a population-based study.

Health self-perception is associated with life-styles and comorbidities and its effect on mortality is confounded by age. A population based study.

Background: Health self-perception (HSP) is the individual and subjective concept that a person has of their state of health. Despite its simplicity, HSP is considered a valid and relevant indicator employed in epidemiological research and in professional practice as an overall measure of health. Objectives: (1) To describe and analyze the associations between HSP and demographic variables, lifestyle and diseases prevalent in a population and (2) to investigate the relationship between HSP and mortality. Materials and methods: In a primary care setting, we conducted a longitudinal study of a random populational sample of a Galician municipality, stratified by decade of life. A total of 1,516 adults older than 18 years, recruited by the 2013-2015 AEGIS study, were followed-up for more than 5 years. During the clinical interview, data were collected on lifestyle and prevalent diseases. The HSP was grouped into 2 categories (good/poor). The statistical analysis consisted of a logistic regression, Kaplan-Meier curves and Cox regression. Results: A total of 540 (35.6%) participants reported poor HSP. At the end of the follow-up, 78 participants had died (5.1%). The participants with increased age and body mass index and chronic diseases (anxiety, depression, ischemic heart disease, diabetes, and cancer) presented a poorer subjective health. A high level of physical activity and moderate alcohol consumption were associated with better HSP. A poorer HSP was associated with increased mortality, an association that disappeared after adjusting for the rest of the covariates (HR, 0.82; 95% CI 0.50-1.33). Conclusion: (1) Health self-perception is associated with age, lifestyle, and certain prevalent diseases. (2) A poorer HSP is associated with increased mortality, but this predictive capacity disappeared after adjusting for potential confounders such as age, lifestyle, and prevalent diseases.

Cost-Effectiveness of a New Outpatient Pulmonology Care Model Based on Physician-to-Physician Electronic Consultation.

Introduction: This study assesses the impact of an electronic physician-to-physician consultation program on the waiting list and the costs of a Pulmonology Unit. Materials and Methods: A prepost intervention study was conducted after a new ambulatory pulmonary care protocol was implemented and the capacity of the unit was adopted. In the new model, physicians at all levels of healthcare send electronic consultations to specialists. Results: In the preintervention year (2019), the Unit of Pulmonology attended 7,055 consultations (466 e-consultations and 6,589 first face-to-face visits), which decreased to 6,157 (3,934 e-consultations and 2,223 first face-to-face visits; 12.7% reduction) in the postintervention year (all were e-consultations). The mean wait time for the first appointment was 25.7 days in 2019 versus 3.2 days in 2021 (p < 0.001). In total, 43.5% of cases were solved via physician-to-physiciane-consultation. A total of 2,223 patients needed a face-to-face visit, with a mean wait time of 7.5 days. The mean of patients in the waiting listing decreased from 450.8 in 2019 to 44.8 in 2021 (90% reduction). The annual time devoted to e-consultations and first face-to-face visits following an e-consultation diminished significantly after the intervention (1,724 hours versus 2,312.8; 25.4% reduction). Each query solved via e-consultation represented a saving of €652.8, resulting in a total annual saving of €827,062. Conclusions: Physician-to-physiciane-consultations reduce waiting times, improve access of complex patients to specialty care, and ensure that cases are managed at the appropriate level. E-consultation reduces costs, which benefits both, society and the healthcare system.

Sarcoidosis. Disease progression based on radiological and functional course: Predictive factors.

BACKGROUND: Sarcoidosis is a multiorgan granulomatous disease with a variable course. OOBJECTIVES: The purpose of this study is to identify the patients that are more likely to experience disease progression. METHODS: A retrospective study in patients ≥18 years. Pulmonary function and radiological stage (Scadding criteria) were assessed at diagnosis, and at 1, 3 and 5 years. Sarcoidosis progression was established based on deterioration of radiological or pulmonary function (decrease ≥10% of FVC and/or ≥15% of diffusing capacity of the lung (DLCO). RESULTS: The sample included 277 caucasian patients [mean age, 50±13.6; 69.7% between 31-60 years; 56.3% men]. In total, 65% had stage II sarcoidosis, whereas only 8.3% had stage III/IV disease. Mean pulmonary function (FVC, FEV1, FEV1/FVC and DLCO) at diagnosis was 103±21.8, 96±22.2, 76.2±8 and 81.7±21.7, respectively. The percentage of patients with normal FVC and DLCO was 72.2% and 51.8%, respectively. Radiological stage did not change significantly during follow-up (5 years; p=0.080) and only progressed in 13 patients (5.7%). At 3 years, FVC improved, whereas DLCO exacerbated significantly (p<0.001 for the two). Disease progressed in 34.5% of the patients (57/165) whose pulmonary function and radiological stage were available (both baseline and at 3 years). Age was associated with disease progression [OR=1.04 (95%CI=1.01, 1.06)]. Risk increased by 4% for each year older a patient was at diagnosis. CONCLUSIONS: At 3 years, a third of patients experienced sarcoidosis progression. Age was the only factor associated with disease prognosis.

Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations.

BACKGROUND AND OBJECTIVES: Missing data is a ubiquitous problem in longitudinal studies due to the number of patients lost to follow-up. Kernel methods have enriched the machine learning field by successfully managing non-vectorial predictors, such as graphs, strings, and probability distributions, and have emerged as a promising tool for the analysis of complex data stemming from modern healthcare. This paper proposes a new set of kernel methods to handle missing data in the response variables. These methods will be applied to predict long-term changes in glycated haemoglobin (A1c), the primary biomarker used to diagnose and monitor the progression of diabetes mellitus, making emphasis on exploring the predictive potential of continuous glucose monitoring (CGM). METHODS: We propose a new framework of non-linear kernel methods for testing statistical independence, selecting relevant predictors, and quantifying the uncertainty of the resultant predictive models. As a novelty in the clinical analysis, we used a distributional representation of CGM as a predictor and compared its performance with that of traditional diabetes biomarkers. RESULTS: The results show that, after the incorporation of CGM information, predictive ability increases from R2=0.61 to R2=0.71. In addition, uncertainty analysis is useful for characterising some subpopulations where predictivity is worsened, and a more personalised clinical follow-up is advisable according to expected patient uncertainty in glucose values. CONCLUSIONS: The proposed methods have proven to deal effectively with missing data. They also have the potential to improve the results of predictive tasks by including new complex objects as explanatory variables and modelling arbitrary dependence relations. The application of these methods to a longitudinal study of diabetes showed that the inclusion of a distributional representation of CGM data provides greater sensitivity in predicting five-year A1c changes than classical diabetes biomarkers and traditional CGM metrics.

Aging of glucose profiles in an adult population without diabetes.

AIMS: This study aimed to determine the effect of aging on glucose profiles in a population without diabetes. METHODS: We investigated the evolution of glucose profiles in an adult population without diabetes using continuous glucose monitoring (CGM) in two periods separated by 5 years. Anthropometrics, laboratory tests (HbA1c, fasting blood glucose) and CGM data (mean glycemia level, coefficient of variation, time in range) were measured in both periods to study the change in values over time. RESULTS: 125 participants (68% women) mean age 43.1 ± 12.4 years and classified as normoglycemic at baseline were included. Of the total population 15.2% had worsened glycemic status after 5 years, age and baseline glucose values (HbA1c and percentage of values above 175 mg/dL) were the variables related with this change. Related to CGM, we found that after 5 years there was a decrease in the percentage of values between 70 and 99 mg/dl (45.0% to 38.7%, p = 0.002) and an increase in the 100-139 mg/dL range (52.9% to 57.5% p = 0.016). CONCLUSIONS: Our results indicate that in an adult population without diabetes there are changes in glucose profiles with aging highlighting the reduction of blood glucose values below 100 mg/dL.

Longitudinal relationship of liver injury with inflammation biomarkers in COVID-19 hospitalized patients using a joint modeling approach.

The mechanisms underlying liver disease in patients with COVID-19 are not entirely known. The aim is to investigate, by means of novel statistical techniques, the changes over time in the relationship between inflammation markers and liver damage markers in relation to survival in COVID-19. The study included 221 consecutive patients admitted to the hospital during the first COVID-19 wave in Spain. Generalized additive mixed models were used to investigate the influence of time and inflammation markers on liver damage markers in relation to survival. Joint modeling regression was used to evaluate the temporal correlations between inflammation markers (serum C-reactive protein [CRP], interleukin-6, plasma D-dimer, and blood lymphocyte count) and liver damage markers, after adjusting for age, sex, and therapy. The patients who died showed a significant elevation in serum aspartate transaminase (AST) and alkaline phosphatase levels over time. Conversely, a decrease in serum AST levels was observed in the survivors, who showed a negative correlation between inflammation markers and liver damage markers (CRP with serum AST, alanine transaminase [ALT], and gamma-glutamyl transferase [GGT]; and D-dimer with AST and ALT) after a week of hospitalization. Conversely, most correlations were positive in the patients who died, except lymphocyte count, which was negatively correlated with AST, GGT, and alkaline phosphatase. These correlations were attenuated with age. The patients who died during COVID-19 infection displayed a significant elevation of liver damage markers, which is correlated with inflammation markers over time. These results are consistent with the role of systemic inflammation in liver damage during COVID-19.

Changes in Serum N-Glycome for Risk Drinkers: A Comparison with Standard Markers for Alcohol Abuse in Men and Women.

Background and aim: Glycomic alterations serve as biomarker tools for different diseases. The present study aims to evaluate the diagnostic capability of serum N-glycosylation to identify alcohol risk drinking in comparison with standard markers. Methods: We included 1516 adult individuals (age range 18-91 years; 55.3% women), randomly selected from a general population. A total of 143 (21.0%) men and 50 (5.9%) women were classified as risk drinkers after quantification of daily alcohol consumption and the Alcohol Use Disorders Identification Test (AUDIT). Hydrophilic interaction ultra-performance liquid chromatography (HILIC-UPLC) was used for the quantification of 46 serum N-glycan peaks. Serum gamma-glutamyltransferase (GGT), carbohydrate-deficient transferrin (CDT), and red blood cell mean corpuscular volume (MCV) were measured by standard clinical laboratory methods. Results: Variations in serum N-glycome associated risk drinking were more prominent in men compared to women. A unique combination of N-glycan peaks selected by the selbal algorithm shows good discrimination between risk-drinkers and non-risk drinkers for men and women. Receiver operating characteristics (ROC) curves show accuracy for the diagnosis of risk drinking, which is comparable to that of the golden standards, GGT, MCV and CDT markers for men and women. Additionally, the inclusion of N-glycan peaks improves the diagnostic accuracy of the standard markers, although it remains relatively low, due to low sensitivity. For men, the area under the ROC curve using N-glycome data is 0.75, 0.76, and 0.77 when combined with GGT, MCV, and CDT, respectively. In women, the areas were 0.76, 0.73, and 0.73, respectively. Conclusion: Risk drinking is associated with significant variations in the serum N-glycome, which highlights its potential diagnostic utility.

Clinical evaluation of meibomian gland dysfunction in patients with keratoconus.

PURPOSE: To investigate the association of keratoconus (KC) with meibomian gland dysfunction (MGD) and to describe the epidemiological characteristics of MGD in this disease. METHODS: In this observational study, 120 KC patients seen in the Department of Ophthalmology of the Complexo Hospitalario Universitario de Santiago de Compostela and 87 controls were analyzed. The Ocular surface disease index (OSDI) questionnaire was administered and several DED tests and an evaluation of the meibomian glands and lid margin were performed. MGD signs and DED tests were compared between the groups. Symptoms were further analyzed in patients and controls with and without MGD. RESULTS: KC was significantly associated with MGD after adjusting for age and sex [adjusted odds ratio (ORa), 2.40]. The frequency of MGD in KC patients [59 (49.2%) KC patients and 25 (28.7%) controls had MGD] correlated with the severity of KC (r = 0.206) (P = 0.020). Mean OSDI score in KC patients with and without MGD was 31.1 ± 24.1 and 35.2 ± 26.0 (P = 0.326), and 17.2 ± 22.7 and 13.3 ± 14.1 in controls with and without it (P = 0.366). The most common MGD signs coincided in both groups. Staining with fluorescein (P = 0.000) and lissamine green (P = 0.019) was higher in KC patients, but no differences were detected with TBUT (P = 0.116) or the Schirmer test (P = 0.637). Hypersecretory MGD was the most prevalent variant in both groups. CONCLUSIONS: MGD and DED are common in KC patients. MGD correlates with the severity of KC and is indistinguishable from MGD in patients without KC. No association was found with symptoms. Patients with KC should be screened for MGD because of its possible clinical implications. Further research is needed to clarify the role of MGD in KC patients.