Personalized Imputation in metric spaces via conformal prediction: Applications in Predicting Diabetes Development with Continuous Glucose Monitoring Information

The challenge of handling missing data is widespread in modern data analysis, particularly during the preprocessing phase and in various inferential modeling tasks. Although numerous algorithms exist for imputing missing data, the assessment of imputation quality at the patient level often lacks personalized statistical approaches. Moreover, there is a scarcity of imputation methods for metric space based statistical objects. The aim of this paper is to introduce a novel two-step framework that comprises: (i) a imputation methods for statistical objects taking values in metrics spaces, and (ii) a criterion for personalizing imputation using conformal inference techniques. This work is motivated by the need to impute distributional functional representations of continuous glucose monitoring (CGM) data within the context of a longitudinal study on diabetes, where a significant fraction of patients do not have available CGM profiles. The importance of these methods is illustrated by evaluating the effectiveness of CGM data as new digital biomarkers to predict the time to diabetes onset in healthy populations. To address these scientific challenges, we propose: (i) a new regression algorithm for missing responses; (ii) novel conformal prediction algorithms tailored for metric spaces with a focus on density responses within the 2-Wasserstein geometry; (iii) a broadly applicable personalized imputation method criterion, designed to enhance both of the aforementioned strategies, yet valid across any statistical model and data structure. Our findings reveal that incorporating CGM data into diabetes time-to-event analysis, augmented with a novel personalization phase of imputation, significantly enhances predictive accuracy by over ten percent compared to traditional predictive models for time to diabetes

Prevalence of pinguecula and pterygium in a general population in Spain

PURPOSE: To determine the prevalence of pinguecula and pterygium and to investigate their associations in a general adult population in North-Western Spain. METHODS: An age-stratified random sample of 1155 subjects >/= 40 years was selected in O Salnes (Spain). From 937 eligible subjects, 619 (66.1%) participated (mean age (SD): 63.4 (14.5) years, range: 40-96 years, 37.0% males). An interview to collect history of systemic diseases and lifestyle details and a comprehensive ophthalmic evaluation in which pinguecula and pterygium were recorded was carried out. The prevalence of pinguecula and pterygium and their relationship with lifestyle factors and ocular and systemic diseases was investigated. RESULTS: The prevalence of pinguecula was 47.9% (95% confidence interval (CI): 43.9-51.9). This prevalence increased significantly with aging (P = 0.002) and was higher in men (56.4%; 95% CI: 50.0-62.7) than in women (42.7%; 95% CI: 37.8-47.8) (P=0.001). The prevalence of pterygium was 5.9% (95% CI: 4.3-7.9). This prevalence also increased significantly with aging (P = 0.005) and was 4.8% (95% CI: 2.6-8.4) in men and 6.5% (95% CI: 4.5-9.3) in women (P = 0.346). After controlling for age and sex, pinguecula was associated with alcohol intake (adjusted odds ratio (OR(a)): 3.08; 95% CI: 1.60-5.95), pterygium with fluorescein staining (OR(a): 2.64; 95% CI: 1.08-6.46) and both disorders with outer activity (OR(a): 2.07; 95% CI: 1.36-3.15 and 2.28; 95% CI: 1.04-4.98, respectively). CONCLUSIONS: Pinguecula is far more common than pterygium. Alcohol consumption is strongly associated with pinguecula. Fluorescein staining is highly prevalent in subjects with pterygium. Both disorders increase with age and are associated with outer activity

Application of Generalized Additive Models to the Evaluation of Continuous Markers for Classification Purposes

Background: Receiver operating characteristic (ROC) curve and derived measures as the Area Under the Curve (AUC) are often used for evaluating the discriminatory capability of a continuous biomarker in distinguishing between alternative states of health. However, if the marker shows an irregular distribution, with a dominance of diseased subjects in noncontiguous regions, classification using a single cutpoint is not appropriate, and it would lead to erroneous conclusions. This study sought to describe a procedure for improving the discriminatory capacity of a continuous biomarker, by using generalized additive models (GAMs) for binary data.Methods: A new classification rule is obtained by using logistic GAM regression models to transform the original biomarker, with the predicted probabilities being the new transformed continuous biomarker. We propose using this transformed biomarker to establish optimal cut-offs or intervals on which to base the classification. This methodology is applied to different controlled scenarios, and to real data from a prospective study of patients undergoing surgery at a University Teaching Hospital, for examining plasma glucose as postoperative infection biomarker.Results: Both, theoretical scenarios and real data results show that when the risk marker-disease relationship is not monotone, using the new transformed biomarker entails an improvement in discriminatory capacity. Moreover, in these situations, an optimal interval seems more reasonable than a single cutpoint to define lower and higher disease-risk categories.Conclusions: Using statistical tools which allow for greater flexibility (e.g., GAMs) can optimize the classificatory capacity of a potential marker using ROC analysis. So, it is important to question linearity in marker-outcome relationships, in order to avoid erroneous conclusions

Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study

Background: Insulin resistance has been associated with metabolic and hemodynamic alterations and higher cardio metabolic risk. There is great variability in the threshold homeostasis model assessment of insulin resistance (HOMA-IR) levels to define insulin resistance. The purpose of this study was to describe the influence of age and gender in the estimation of HOMA-IR optimal cut-off values to identify subjects with higher cardio metabolic risk in a general adult population. Methods: It included 2459 adults (range 20-92 years, 58.4% women) in a random Spanish population sample. As an accurate indicator of cardio metabolic risk, Metabolic Syndrome (MetS), both by International Diabetes Federation criteria and by Adult Treatment Panel III criteria, were used. The effect of age was analyzed in individuals with and without diabetes mellitus separately. ROC regression methodology was used to evaluate the effect of age on HOMA-IR performance in classifying cardio metabolic risk. Results: In Spanish population the threshold value of HOMA-IR drops from 3.46 using 90th percentile criteria to 2.05 taking into account of MetS components. In non-diabetic women, but no in men, we found a significant non-linear effect of age on the accuracy of HOMA-IR. In non-diabetic men, the cut-off values were 1.85. All values are between 70th-75th percentiles of HOMA-IR levels in adult Spanish population. Conclusions: The consideration of the cardio metabolic risk to establish the cut-off points of HOMA-IR, to define insulin resistance instead of using a percentile of the population distribution, would increase its clinical utility in identifying those patients in whom the presence of multiple metabolic risk factors imparts an increased metabolic and cardiovascular risk. The threshold levels must be modified by age in non-diabetic women

Diagnosing tuberculous pleural effusion using clinical data and pleural fluid analysis A study of patients less than 40 years-old in an area with a high incidence of tuberculosis

SummaryBackgroundTuberculous pleural effusions (TPE) are common. The diagnosis is often problematic. As the determination of ADA is often unavailable in some countries, the aim of this study was to evaluate the diagnostic usefulness of other data from pleural fluid analysis, in young patients from populations with high prevalence of tuberculosis (TB).MethodsWe analysed 218 patients with pleural effusion (165 tuberculous, 21 infectious, 11 neoplastic, 16 miscellaneous, 3 idiopathic). We performed two regression models; one included pleural fluid ADA values (model 1), and the other without ADA (model 2).ResultsModel 1 selected two variables (ADA >35U/L) and lymphocytes (>31.5%) and correctly classified 216/218 effusions (1 false negative, 1 false positive). Model 2 (without ADA) selected three variables: lymphocytes (>31.5%), fever and cough, and correctly classified 207/218 effusions (8 false negatives, 3 false positives). The sensitivity of models 1 and 2 was 99.4% and 95.2%, specificity 98.1% and 94.3% and accuracy 99% and 95%.ConclusionsIn geographic areas with high prevalence of TB and a low prevalence of HIV, in young patients (≤40 years), it is possible to confidently diagnose TPE with either of the two regression tree models, with the utility of ADA providing superior sensitivity, specificity, and accuracy

Evaluation of the surgical difficulty in lower third molar extraction

The ability to predict the surgical difficulty of lower third molar extraction facilitates the design of treatment plans by minimizing complications and improving the preparation of patients and assistants in terms of the postoperative management of inflammation and pain. The aims of this study were to evaluate the value of panoramic radiographs in predicting lower third molar extraction difficulty and technique and to determine if the experience of the practitioner had any influence on this predictive ability. Fourteen dental practitioners with varying levels of experience evaluate the difficulty of lower third molar extraction in a group of patients using a 100-mm visual analog scale (VAS) and a modified version of a surgical difficulty scale. The results were then compared to postoperative scores calculated using the same scale. A tendency to underestimate the difficulty of procedures that was more pronounced in observers with greater levels of experience was observed. A low level of agreement between preoperative and postoperative evaluations using the surgical difficulty scale as well as an association between difficulty assessed preoperatively using the VAS and difficulty assessed postoperatively using the surgical difficulty scale was also found. The use of panoramic radiographs does not allow practitioners to accurately predict lower third molar extraction difficulty and technique, regardless of their level of experience

Interleukin 27 could be useful in the diagnosis of tuberculous pleural effusions

BACKGROUND: The diagnosis of tuberculous pleural effusion (TBPE) has some limitations. We studied the efficacy of interleukin-27 (IL-27) in the diagnosis of TBPE. METHODS: We measured IL-27, adenosine deaminase (ADA), ADA-2, interferon-gamma (IFNgamma), and the ADA.IL-27 and ADA-2.IL-27 products in all the pleural effusion fluids. The diagnostic yield of IL-27 was evaluated with receiver operating characteristic curves. RESULTS: Of 431 pleural effusions, 70 were tuberculous, 146 were neoplastic, 58 were parapneumonic, 28 were empyemas, 88 were transudates, and 41 were other types. With a cutoff point of 0.55 ng/mL, IL-27 had a sensitivity of 91.4% and a specificity of 85.1%, which were significantly less than ADA, ADA-2, IFNgamma, ADA.IL-27, or ADA-2.IL-27. The area under the receiver operating characteristic curve for IL-27 (0.963) was also significantly lower than that for the other markers, except for IFNgamma. However, IL-27 improved the sensitivity of ADA and ADA-2 through ADA.IL-27 and ADA-2.IL-27 products (100% for both). CONCLUSIONS: IL-27 is less efficient than ADA and ADA-2 in the diagnosis of TBPE. However, ADA.IL-27 and ADA-2.IL-27 improve the diagnostic sensitivity of ADA and ADA-2, and thus could be useful in situations of high clinical suspicion and low ADA level. A value above the cutoff point of the latter is practically diagnostic of TBPE

Effects of a Community-Based Behavioral Intervention with a Traditional Atlantic Diet on Cardiometabolic Risk Markers: A Cluster Randomized Controlled Trial (“The GALIAT Study”)

The Atlantic diet, the traditional dietary pattern in northern Portugal and northwest Spain, has been related to metabolic health and low ischemic heart disease mortality. The Galiat Study is a randomized controlled trial aimed to assess the effects of the Atlantic diet on anthropometric variables, metabolic profile, and nutritional habits. The dietary intervention was conducted in 250 families (720 adults and children) and performed at a primary care center. Over six months, families randomized to the intervention group received educational sessions, cooking classes, written supporting material, and foods that form part of the Atlantic diet, whereas those randomized to the control group followed their habitual lifestyle. 213 families (92.4%) completed the trial. Adults in the intervention group lost weight as opposed to controls who gained weight (adjusted mean difference −1.1 kg, p < 0.001) and total serum cholesterol (adjusted mean difference −5.2 mg/dL, p = 0.004). Significant differences in favor of the intervention were found in other anthropometric variables and low-density lipoprotein cholesterol, but changes in triglycerides, high-density lipoprotein cholesterol, inflammation markers, blood pressure, and glucose metabolism were not observed. A family-based nutritional intervention based on the Atlantic diet showed beneficial effects on adiposity and the lipid profileThis project received funding from the ERDF-Innterconecta for Galicia Program (ITC-20133014 & ITC-20151009), managed by the Centre for the Development of Industrial Technology (CDTI), Spanish Ministry of Economy, Industry and CompetitivenessS