Multimorbidity as specific disease combinations, an important predictor factor for mortality in octogenarians: the Octabaix study

BACKGROUND: The population is aging and multimorbidity is becoming a common problem in the elderly. OBJECTIVE: To explore the effect of multimorbidity patterns on mortality for all causes at 3- and 5-year follow-up periods. MATERIALS AND METHODS: A prospective community-based cohort (2009-2014) embedded within a randomized clinical trial was conducted in seven primary health care centers, including 328 subjects aged 85 years at baseline. Sociodemographic variables, sensory status, cardiovascular risk factors, comorbidity, and geriatric tests were analyzed. Multimorbidity patterns were defined as combinations of two or three of 16 specific chronic conditions in the same individual. RESULTS: Of the total sample, the median and interquartile range value of conditions was 4 (3-5). The individual morbidities significantly associated with death were chronic obstructive pulmonary disease (COPD; hazard ratio [HR]: 2.47; 95% confidence interval [CI]: 1.3; 4.7), atrial fibrillation (AF; HR: 2.41; 95% CI: 1.3; 4.3), and malignancy (HR: 1.9; 95% CI: 1.0; 3.6) at 3-year follow-up; whereas dementia (HR: 2.04; 95% CI: 1.3; 3.2), malignancy (HR: 1.84; 95% CI: 1.2; 2.8), and COPD (HR: 1.77; 95% CI: 1.1; 2.8) were the most associated with mortality at 5-year follow-up, after adjusting using Barthel functional index (BI). The two multimorbidity patterns most associated with death were AF, chronic kidney disease (CKD), and visual impairment (HR: 4.19; 95% CI: 2.2; 8.2) at 3-year follow-up as well as hypertension, CKD, and malignancy (HR: 3.24; 95% CI: 1.8; 5.8) at 5 years, after adjusting using BI. CONCLUSION: Multimorbidity as specific combinations of chronic conditions showed an effect on mortality, which would be higher than the risk attributable to individual morbidities. The most important predicting pattern for mortality was the combination of AF, CKD, and visual impairment after 3 years. These findings suggest that a new approach is required to target multimorbidity in octogenarians

Multifactorial assessment and targeted intervention in nutritional status among the older adults: a randomized controlled trial: the Octabaix study

Background: Malnutrition is frequent among older people and is associated with morbi-mortality.he aim of the study is to assess the effectiveness of a multifactorial and multidisciplinary intervention in the nutritional status among the elderly. Methods: Randomized, single-blind, parallel-group, clinical trial conducted from January 2009 to December 2010 in seven primary health care centers in Baix Llobregat (Barcelona). Of 696 referred people, born in 1924, 328 subjects were randomized to an intervention group or a control group. The intervention model used an algorithm and was multifaceted for both the patients and their primary care providers. The main outcome was improvement in nutritional status assessed by Mini Nutritional Assessment (MNA). Data analyses were done by intention-to-treat. Results: Two-year assessment was completed for 127 patients (77.4%) in the intervention group and 98 patients (59.7%) in the control group. In the adjusted linear mixed models for MNA, intervention showed no significant effect during all follow-up period with −0.21 (CI: − 0.96; 0.26). In subjects with nutritional risk (MNA ≤ 23.5 / 30) existed a tendency towards improvement in MNA score 1.13 (95% CI −0.48; 2.74) after 2 years. Conclusion: A universal multifactorial assessment and target intervention over a two year period in subjects at nutritional risk showed a tendency to improve nutrition but not in the rest of community-dwelling studied subjects. Cognitive impairment was an independent factor strongly associated with a decline in nutritional status

Utility of geriatric assessment to predict mortality in the oldest old: the Octabaix Study 3-year follow-up

Objective: Few studies have prospectively evaluated the utility of geriatric assessment tools as predictors of mortality in the oldest population. We investigated predictors of death in an oldest-old cohort after 3 years of follow-up. Methods: The Octabaix study is a prospective, community-based study with a follow-up period of 3 years involving 328 subjects aged 85 at baseline. Data were collected on functional and cognitive status, co-morbidity, nutritional and falls risk, quality of life, social risk, and long-term drug prescription. Vital status for the total cohort was evaluated after 3 years of follow-up. Results: Mortality after 3 years was 17.3%. Patients who did not survive had significantly poorer baseline functional status for basic and instrumental activities of daily living (Barthel and Lawton Index), higher co-morbidity (Charlson), higher nutritional risk (Mini Nutritional Assessment), higher risk of falls (Tinetti Gait Scale), poor quality of life (visual analog scale of the Quality of Life Test), and higher number of chronic drugs prescribed. Cox regression analysis identified the Lawton Index (hazard ratio [HR] 0.82, 95% confidence interval [CI] 0.73-0.89) and the number of chronic drugs prescribed (HR 1.09, 95% CI 1.01-1.18) as independent predictors of mortality at 3 years. Conclusions: Among the variables studied, the ability to perform instrumental activities of daily living and using few drugs on a chronic basis at baseline are the best predictors of which oldest-old community-dwelling subjects survive after a 3-year follow-up period

Multifactorial assessment and targeted intervention to reduce falls among the oldest-old: a randomized controlled trial

Background: The purpose of this study was to assess the effectiveness of a multifactorial intervention to reduce falls among the oldest-old people, including individuals with cognitive impairment or comorbidities. Methods: A randomized, single-blind, parallel-group clinical trial was conducted from January 2009 to December 2010 in seven primary health care centers in Baix Llobregat (Barcelona). Of 696 referred people who were born in 1924, 328 were randomized to an intervention group or a control group. The intervention model used an algorithm and was multifaceted for both patients and their primary care providers. Primary outcomes were risk of falling and time until falls. Data analyses were by intention-to-treat. Results: Sixty-five (39.6%) subjects in the intervention group and 48 (29.3%) in the control group fell during follow-up. The difference in the risk of falls was not significant (relative risk 1.28, 95% confidence interval [CI] 0.94-1.75). Cox regression models with time from randomization to the first fall were not significant. Cox models for recurrent falls showed that intervention had a negative effect (hazard ratio [HR] 1.46, 95% CI 1.03-2.09) and that functional impairment (HR 1.42, 95% CI 0.97-2.12), previous falls (HR 1.09, 95% CI 0.74-1.60), and cognitive impairment (HR 1.08, 95% CI 0.72-1.60) had no effect on the assessment. Conclusion: This multifactorial intervention among octogenarians, including individuals with cognitive impairment or comorbidities, did not result in a reduction in falls. A history of previous falls, disability, and cognitive impairment had no effect on the program among the community-dwelling subjects in this study

Analysis of factors affecting the variability of a quantitative suspension bead array assay measuring IgG to multiple Plasmodium antigens

Reducing variability of quantitative suspension array assays is key for multi-center and large sero-epidemiological studies. To maximize precision and robustness of an in-house IgG multiplex assay, we analyzed the effect of several conditions on variability to find the best combination. The following assay conditions were studied through a fractional factorial design: antigen-bead coupling (stock vs. several), sample predilution (stock vs. daily), temperature of incubation of sample with antigen-bead (22°C vs. 37°C), plate washing (manual vs. automatic) and operator expertise (expert vs. apprentice). IgG levels against seven P. falciparum antigens with heterogeneous immunogenicities were measured in test samples, in a positive control and in blanks. We assessed the variability and MFI quantification range associated to each combination of conditions, and their interactions, and evaluated the minimum number of samples and blank replicates to achieve good replicability. Results showed that antigen immunogenicity and sample seroreactivity defined the optimal dilution to assess the effect of assay conditions on variability. We found that a unique antigen-bead coupling, samples prediluted daily, incubation at 22°C, and automatic washing, had lower variability. However, variability increased when performing several couplings and incubating at 22°C vs. 37°C. In addition, no effect of temperature was seen with a unique coupling. The expertise of the operator had no effect on assay variability but reduced the MFI quantification range. Finally, differences between sample replicates were minimal, and two blanks were sufficient to capture assay variability, as suggested by the constant Intraclass Correlation Coefficient of three and two blanks. To conclude, a single coupling was the variable that most consistently reduced assay variability, being clearly advisable. In addition, we suggest having more sample dilutions instead of replicates to increase the likelihood of sample MFIs falling in the linear part of the antigen-specific curve, thus increasing precision

Antibody responses to α-Gal in African children vary with age and site and are associated with malaria protection

Naturally-acquired antibody responses to malaria parasites are not only directed to protein antigens but also to carbohydrates on the surface of Plasmodium protozoa. Immunoglobulin M responses to α-galactose (α-Gal) (Galα1-3Galβ1-4GlcNAc-R)-containing glycoconjugates have been associated with protection from P. falciparum infection and, as a result, these molecules are under consideration as vaccine targets; however there are limited field studies in endemic populations. We assessed a wide breadth of isotype and subclass antibody response to α-Gal in children from Mozambique (South East Africa) and Ghana (West Africa) by quantitative suspension array technology. We showed that anti-α-Gal IgM, IgG and IgG1–4 levels vary mainly depending on the age of the child, and also differ in magnitude in the two sites. At an individual level, the intensity of malaria exposure to P. falciparum and maternally-transferred antibodies affected the magnitude of α-Gal responses. There was evidence for a possible protective role of anti-α-Gal IgG3 and IgG4 antibodies. However, the most consistent findings were that the magnitude of IgM responses to α-Gal was associated with protection against clinical malaria over a one-year follow up period, especially in the first months of life, while IgG levels correlated with malaria risk

Modulation of innate immune responses at birth by prenatal malaria exposure and association with malaria risk during the first year of life

Background: Factors driving inter-individual differences in immune responses upon different types of prenatal malaria exposure (PME) and subsequent risk of malaria in infancy remain poorly understood. In this study, we examined the impact of four types of PME (i.e., maternal peripheral infection and placental acute, chronic, and past infections) on both spontaneous and toll-like receptors (TLRs)-mediated cytokine production in cord blood and how these innate immune responses modulate the risk of malaria during the first year of life. Methods: We conducted a birth cohort study of 313 mother-child pairs nested within the COSMIC clinical trial (NCT01941264), which was assessing malaria preventive interventions during pregnancy in Burkina Faso. Malaria infections during pregnancy and infants’ clinical malaria episodes detected during the first year of life were recorded. Supernatant concentrations of 30 cytokines, chemokines, and growth factors induced by stimulation of cord blood with agonists of TLRs 3, 7/8, and 9 were measured by quantitative suspension array technology. Crude concentrations and ratios of TLR-mediated cytokine responses relative to background control were analyzed. Results: Spontaneous production of innate immune biomarkers was significantly reduced in cord blood of infants exposed to malaria, with variation among PME groups, as compared to those from the non-exposed control group. However, following TLR7/8 stimulation, which showed higher induction of cytokines/chemokines/growth factors than TLRs 3 and 9, cord blood cells of infants with evidence of past placental malaria were hyper-responsive in comparison to those of infants not-exposed. In addition, certain biomarkers, which levels were significantly modified depending on the PME category, were independent predictors of either malaria risk (GM-CSF TLR7/8 crude) or protection (IL-12 TLR7/ 8 ratio and IP-10 TLR3 crude, IL-1RA TLR7/8 ratio) during the first year of life. Conclusions: These findings indicate that past placental malaria has a profound effect on fetal immune system and that the differential alterations of innate immune responses by PME categories might drive heterogeneity between individuals to clinical malaria susceptibility during the first year of lif

Baseline exposure, antibody subclass, and hepatitis B response differentially affect malaria protective immunity following RTS,S/AS01E vaccination in African children

Background: The RTS,S/AS01E vaccine provides partial protection against malaria in African children, but immune responses have only been partially characterized and do not reliably predict protective efficacy. We aimed to evaluate comprehensively the immunogenicity of the vaccine at peak response, the factors affecting it, and the antibodies associated with protection against clinical malaria in young African children participating in the multicenter phase 3 trial for licensure. Methods: We measured total IgM, IgG, and IgG1–4 subclass antibodies to three constructs of the Plasmodium falciparum circumsporozoite protein (CSP) and hepatitis B surface antigen (HBsAg) that are part of the RTS,S vaccine, by quantitative suspension array technology. Plasma and serum samples were analyzed in 195 infants and children from two sites in Ghana (Kintampo) and Mozambique (Manhiça) with different transmission intensities using a case-control study design. We applied regression models and machine learning techniques to analyze immunogenicity, correlates of protection, and factors affecting them. Results: RTS,S/AS01E induced IgM and IgG, predominantly IgG1 and IgG3, but also IgG2 and IgG4, subclass responses. Age, site, previous malaria episodes, and baseline characteristics including antibodies to CSP and other antigens reflecting malaria exposure and maternal IgGs, nutritional status, and hemoglobin concentration, significantly affected vaccine immunogenicity. We identified distinct signatures of malaria protection and risk in RTS,S/AS01E but not in comparator vaccinees. IgG2 and IgG4 responses to RTS,S antigens post-vaccination, and anti-CSP and anti-P. falciparum antibody levels pre-vaccination, were associated with malaria risk over 1-year follow-up. In contrast, antibody responses to HBsAg (all isotypes, subclasses, and timepoints) and post-vaccination IgG1 and IgG3 to CSP C-terminus and NANP were associated with protection. Age and site affected the relative contribution of responses in the correlates identified. Conclusions: Cytophilic IgG responses to the C-terminal and NANP repeat regions of CSP and anti-HBsAg antibodies induced by RTS,S/AS01E vaccination were associated with malaria protection. In contrast, higher malaria exposure at baseline and non-cytophilic IgG responses to CSP were associated with disease risk. Data provide new correlates of vaccine success and failure in African children and reveal key insights into the mode of action that can guide development of more efficacious next-generation vaccines

Support Vector Machines for Survival Analysis: Methods and Variable Relevance = Màquines de Suport Vectorial per Anàlisi de la Supervivència: Mètodes i Rellevància de Variables

[eng] The process of creating an efficacious malaria vaccine is complex due to the characteristics of the disease that are directly related to the responsible parasite. In the disease-vaccine interaction several aspects need to be taken into account to improve and understand the vaccine and for that reason different types of data need to be analyzed. Current assays technology allows analyzing several proteins simultaneously with a small blood volume. The combination of the medium throughput dataset of some assays and the small sample size of some malaria studies may hinder the use of classical statistical methods. In the context of low number of observations and medium or high number of variables the support vector machines (SVM) models are a powerful tool to analyze sparse data, i.e., data in which the number of predictors is larger or approximately equal to the number of observations, especially when handling binary outcomes. However, biomedical research often involves analysis of time-to-event outcomes. Several methods have been tested in the literature to deal with censored data into the SVM framework. Most of these methods are based on a support vector regression (SVR) approach and results found in the literature suggest no significant differences with Cox proportional hazards model and kernel Cox regression. Another perspective is a SVM for binary classification, however, almost no work has been done into this approach: only SVM learning using privileged information and SVM with uncertain classes have been described. This PhD thesis aims to propose alternative methods and extensions to the ones existing in the binary classification framework, specifically, proposing a conditional survival approach for weighting censored observations, a semi-supervised SVM with local invariances perspective and evaluating a weighted SVM model. Another important aspect in biomedical research is to identify the relevance of the variables in a model, i.e., which variables are important related to the response variable. In the SVM framework most of the work done is related to linear kernels, however, the main advantage of SVM is using non-linear kernels. This PhD thesis aims to propose three approaches based on the Recursive Feature Elimination (RFE) algorithm to rank variables based on non-linear SVM and SVM for survival analysis. Moreover, the proposed algorithms are focused on interpretation and visualization of each one the RFE iterations, allowing to identify relevant variables associated with the response variable and among predictor variables. After evaluating all proposed methods in a simulation study under several scenarios, a real dataset applying these methods has been analyzed: the Mal067 data aims to identify immune responses correlated with protection from malaria that were elicited by the malaria RTS,S vaccine and by natural immunity. All SVM for survival analysis methods have been implemented in R, since neither R packages nor R functions have been found.[cat] El procés de crear una vacuna eficaç contra la malària és complex degut a les característiques del paràsit responsable. Les tècniques de laboratori actuals permeten analitzar moltes proteïnes simultàniament amb molt poc volum de sang, això, juntament amb la poca grandària mostral de molts estudis de malària fa que els mètodes estadístics clàssics no siguin adequats. Les màquines de suport vectorial (SVM) són una eina molt potent per tractar aquest tipus de dades en el context de poques observacions i moltes variables, moltes vegades, però, la recerca està enfocada en variables resposta temps fins a esdeveniment. Gran part de la recerca feta a la literatura en aproximar els mètodes SVM a dades de supervivència està enfocada des de la perspectiva de SVM per regressió. Una altra perspectiva molt poc desenvolupada i avaluada és la de SVM per classificació binària. En aquesta tesi proposem extensions i mètodes alternatius basats en SVM per classificació binària, específicament, proposant una ponderació de les dades censurades basada en la supervivència condicionada, una perspectiva semi-supervisada de SVM amb invariàncies locals i l’avaluació de SVM ponderant les observacions censurades. Un aspecte important en la recerca biomèdica és la identificació de la rellevància de variables en el model, és a dir, quines variables són importants en relació a la variable resposta. En el context de SVM, gran part de la recerca està enfocada a kernels lineals, però el gran avantatge dels SVM és la possibilitat d’utilitzar kernels no lineals. En aquesta tesi proposem tres aproximacions basades en l’algoritme recursiu d’eliminació de característiques (RFE) per ordenar variables, des d’una perspectiva de kernels no lineals i SVM per l’anàlisi de supervivència. A més, els mètodes proposats permeten ser interpretats i visualitzats a cada iteració de l’algoritme RFE, permeten identificar la rellevància de les variables predictores amb respecte la variable resposta i l’associació entre variables predictores. Després d’avaluar tots els mètodes proposats per SVM amb dades censurades i rellevància de variables, mitjançant simulacions, s’han analitzat les dades reals de l’estudi Mal067 que estudia correlats de protecció contra la malària induïts per la vacuna RTS,S