Effect of glucose variability on the mortality of adults aged 75 years and over during the first year of the COVID-19 pandemic.

BACKGROUND: To our knowledge, only one study has examined the association between glucose variability (GV) and mortality in the elderly population with diabetes. GV was assessed by HbA1c, and a J-shaped curve was observed in the relationship between HbA1c thresholds and mortality. No study of GV was conducted during the COVID-19 pandemic and its lockdown. This study aims to evaluate whether GV is an independent predictor of all-cause mortality in patients aged 75 years or older with and without COVID-19 who were followed during the first year of the COVID-19 pandemic and its lockdown measures. METHODS: This was a retrospective cohort study of 407,492 patients from the AGED-MADRID dataset aged 83.5 (SD 5.8) years; 63.2% were women, and 29.3% had diabetes. GV was measured by the coefficient of variation of fasting plasma glucose (CV-FPG) over 6 years of follow-up (2015-2020). The outcome measure was all-cause mortality in 2020. Four models of logistic regression were performed, from simple (age, sex) to fully adjusted, to assess the effect of CV-FPG on all-cause mortality. RESULTS: During follow-up, 34,925 patients died (14,999 women and 19,926 men), with an all-cause mortality rate of 822.3 per 10,000 person-years (95% confidence interval (CI), 813.7 to 822.3) (739 per 10,000; 95% CI 728.7 to 739.0 in women and 967.1 per 10,000; 95% CI 951.7 to 967.2 in men). The highest quartile of CV-FPG was significantly more common in the deceased group (40.1% vs. 23.6%; p < 0.001). In the fully adjusted model including dementia (Alzheimer's disease) and basal FPG, the odds ratio for mortality ranged from 1.88 to 2.06 in patients with T2DM and from 2.30 to 2.61 in patients with normoglycaemia, according to different sensitivity analyses. CONCLUSIONS: GV has clear implications for clinical practice, as its assessment as a risk prediction tool should be included in the routine follow-up of the elderly and in a comprehensive geriatric assessment. Electronic health records can incorporate tools that allow its calculation, and with this information, clinicians will have a broader view of the medium- and long-term prognosis of their patients.

Multimorbidity Patterns in Older Adults: the Role of Social Variables and Lifestyle Behaviors.

INTRODUCTION: While some condition clusters represent the chance co-occurrence of common individual conditions, others may represent shared causal factors. The aims of this study were to identify multimorbidity patterns in older adults and to explore the relationship between social variables, lifestyle behaviors, and the multimorbidity patterns identified. METHODS: This was a cross-sectional design. Data came from 3,273 individuals aged ≥65 from the Seniors-ENRICA-2 cohort; information on 60 chronic disease categories, categorized according to the 2nd edition of the International Classification of Primary Care and the 10th edition of the International Classification of Diseases, was obtained from clinical record linkage. To identify multimorbidity patterns, an exploratory factor analysis was conducted over chronic disease categories with a prevalence >5%, using Oblimin rotation and Kaiser's eigenvalues-greater-than-one rule. The association between multimorbidity patterns and their potential determinants was assessed with multivariable linear regression. RESULTS: The three-factor solution (Musculoskeletal diseases and mental disorders, Cardiometabolic diseases, and Cardiopulmonary diseases) explained 64.5% of the total variance. Being older, lower occupational category, higher levels of loneliness, lower levels of physical activity, and higher body mass index were associated with higher scores in the multimorbidity patterns identified. Female sex was linked to the Musculoskeletal diseases and mental disorders pattern, while being male was revealed to the two remaining multimorbidity patterns. A high diet quality was inversely related to Cardiometabolic diseases, while optimal sleep duration was inversely related to Cardiopulmonary diseases. CONCLUSION: Three multimorbidity patterns were identified in older adults. Multimorbidity patterns were differently associated with social variables and lifestyles behavioral factors.

Use of statins and associated factors in nonagenarians in the Community of Madrid, Spain.

BACKGROUND: The role of statins in the management of dyslipidemia in elderly patients with different cardiovascular risks remains unclear. OBJECTIVE: To study use of statins and associated factors in subjects aged 90 or over in the Community of Madrid, Spain. METHODS: Observational, cross-sectional study that included all people aged 90 or more residing in the Community of Madrid as of December 31, 2015. The clinical information was obtained from the database that contains the electronic medical records collected by family doctors in primary care. Comorbidity data are collected according to the International Classification of Primary Care, Second Edition (ICPC-2). RESULTS: The study population comprised 59,423 subjects, with a mean age of 93.3 (2.5) years (25.8% males). Slightly more than one quarter of the population (28.2%) was in treatment with statins, 21.9% were in primary prevention, and 48.1% in secondary prevention. The multivariate analysis revealed the factors independently associated with statin treatment to be younger age, not being institutionalized, a higher Barthel score, a lower Charlson score, a higher body mass index, and a history of diabetes, dyslipidemia, chronic kidney disease, and cardiovascular disease. CONCLUSIONS: A significant percentage of nonagenarians-mainly less frail patients with more comorbidities-in the Community of Madrid receive statin treatment. No clear efficacy has been demonstrated in reducing cardiovascular events in an age group with such a short life expectancy.

Periodontal disease in adults with diabetes, prevalence and risk factors. Results of an observational study.

AIM: We sought (a) to assess the association between periodontal disease and diabetes, controlling for socio-demographic characteristics, comorbidities, oral health status and lifestyle variables; (b) to identify which of these variables are independently associated with periodontal disease among diabetes sufferers. METHODS: We conducted a case-control study using data from the National/European Health Interview Surveys, conducted from 2003 to 2014 in Spain. We included 65 295 subjects ≥40 years. Diabetes status was self-reported. One non-diabetic control was matched by the year-of-survey, age and sex for each diabetic patient. The presence of periodontal disease was defined using the answer "my teeth bleed spontaneously or while brushing" or/and "my teeth move" to the following question: "Do you suffer of any of these dental and oral disorders or disease?". Independent variables included demographic, socio-economic and healthcare related variables, oral health status and comorbidities. RESULTS: The prevalence of periodontal disease was higher among those suffering from diabetes than their non-diabetes controls (23.8% vs 19.5%; P < 0.001). Adjusted OR of periodontal disease for subjects with diabetes was 1.22 (95% CI; 1.03-1.45). Among diabetes sufferers, missing teeth status (OR 2.08, 95% CI; 1.70-2.53), suffering osteoporosis (OR 1.41, 95% CI; 1.07-1.63) and suffering depression (OR 1.39, 95% CI; 1.12-1.71) were positively associated with higher risk of periodontal disease. Older ages, using private insurance and university education level were associated with lower rates of periodontitis. CONCLUSIONS: Diabetes subjects have an increased likelihood of periodontal disease. Dentists and physicians should increase their awareness with their diabetic patients, especially those with lower educational level, with missing teeth, osteoporosis and depression.

Cross-sectional Association Between Plasma Biomarkers and Multimorbidity Patterns in Older Adults.

Multimorbidity is the simultaneous presence of 2 or more chronic conditions. Metabolomics could identify biomarkers potentially related to multimorbidity. We aimed to identify groups of biomarkers and their association with different multimorbidity patterns. Cross-sectional analyses were conducted within the Seniors-ENRICA-2 cohort in Spain, with information from 700 individuals aged ≥65 years. Biological samples were analyzed using high-throughput proton nuclear magnetic resonance metabolomics. Biomarker groups were identified with exploratory factor analysis, and multimorbidity was classified into 3 types: cardiometabolic, neuropsychiatric, and musculoskeletal. Logistic regression was used to estimate the association between biomarker groups and multimorbidity patterns, after adjusting for potential confounders including sociodemographics, lifestyle, and body mass index. Three factors were identified: the "lipid metabolism" mainly reflected biomarkers related to lipid metabolism, such as very-low-density lipoprotein and low-density lipoprotein cholesterol; the "high-density lipoprotein cholesterol" mainly included high-density lipoprotein cholesterol subclasses and other lipids not included in the first factor; and the "amino acid/glycolysis/ketogenesis," composed of some amino acids, glycolysis-related metabolites, and ketone bodies. Higher scores in the "lipid metabolism" factor were associated with a higher likelihood of cardiometabolic multimorbidity, odds ratio for tertile 3 versus tertile 1 was 1.79 (95% confidence interval: 1.17-2.76). The "high-density lipoprotein cholesterol" factor was associated with lower odds of cardiometabolic multimorbidity [0.51 (0.32-0.82)], and the "amino acid/glycolysis/ketogenesis" factor was associated with more frequent cardiometabolic multimorbidity [1.85 (1.18-2.90)]. Different metabolomic biomarkers are associated with different multimorbidity patterns; therefore, multiple biomarker measurements are needed for a complete picture of the molecular mechanisms of multimorbidity.

External validation of three diabetes prediction scores in a Spanish cohort: does adding high risk for depression improve the validation of the FINDRISC score (FINDRISC-MOOD)?

OBJECTIVES: To evaluate the external validity of the FINDRISC, DESIR and ADA risk scores for the prediction of diabetes in a Spanish population aged >45 years and to test the possible improvement of FINDRISC by adding a new variable of high risk of depression when Patient Health Questionnaire-9 (PHQ-9) questionnaire score ≥10 (FINDRISC-MOOD). DESIGN: Prospective population-based cohort study. SETTING: 10 primary healthcare centres in the north of the city of Madrid (Spain). PARTICIPANTS: A total of 1242 participants without a history of diabetes and with 2-hour oral glucose tolerance test (OGTT) plasma glucose <200 mg/dL (<11.1 mmol/L) were followed up for 7.3 years (median) using their electronic health records (EHRs) and telephone contact. PRIMARY AND SECONDARY OUTCOME MEASURES: Diabetes risk scores (FINDRISC, DESIR, ADA), PHQ-9 questionnaire and 2-hour-OGTT were measured at baseline. Incident diabetes was defined as treatment for diabetes, fasting plasma glucose ≥126 mg/dL (≥7.0 mmol/L), new EHR diagnosis or self-reported diagnosis. External validation was performed according to optimal cut-off, sensitivity, specificity and Youden Index. Comparison between diabetes risk scores, including FINDRISC-MOOD (original FINDRISC score plus five points if PHQ-9 ≥10), was measured by area under the receiver operating characteristic curve (AUROC). RESULTS: During follow-up, 104 (8.4%; 95% CI, 6.8 to 9.9) participants developed diabetes and 185 had a PHQ-9 score ≥10. The AUROC values were 0.70 (95% CI, 0.67 to 0.72) for FINDRISC-MOOD and 0.68 (95% CI, 0.65 to 0.71) for the original FINDRISC. The AUROCs for DESIR and ADA were 0.66 (95% CI, 0.63 to 0.68) and 0.66 (95% CI, 0.63 to 0.69), respectively. There were no significant differences in AUROC between FINDRISC-MOOD and the other scores. CONCLUSIONS: The results of FINDRISC-MOOD were like those of the other risk scores and do not allow it to be recommended for clinical use.

Prospective Association Between Plasma Amino Acids and Multimorbidity in Older Adults.

BACKGROUND: Some amino acids have been associated with aging-related disorders and risk of physical impairment. The aim of this study was to assess the association between plasma concentrations of 9 amino acids, including branched-chain and aromatic amino acids, and multimorbidity. METHODS: This research uses longitudinal data from the Seniors-ENRICA 2 study, a population-based cohort from Spain that comprises noninstitutionalized adults older than 65. Blood samples were extracted at baseline and after a follow-up period of 2 years for a total of 1 488 subjects. Participants' information was linked with electronic health records. Chronic diseases were grouped into a list of 60 mutually exclusive conditions. A quantitative measure of multimorbidity, weighting morbidities by their regression coefficients on physical functioning, was employed and ranged from 0 to 100. Generalized estimating equation models were used to explore the relationship between plasma amino acids and multimorbidity, adjusting for sociodemographics, socioeconomic status, and lifestyle behaviors. RESULTS: The mean age of participants at baseline was 73.6 (SD = 4.2) years, 49.6% were women. Higher concentrations of glutamine (coef. per mmol/l [95% confidence interval] = 10.1 [3.7, 16.6]), isoleucine (50.3 [21.7, 78.9]), and valine (15.5 [3.1, 28.0]) were significantly associated with higher multimorbidity scores, after adjusting for potential confounders. Body mass index could have influenced the relationship between isoleucine and multimorbidity (p = .016). CONCLUSIONS: Amino acids could play a role in regulating aging-related diseases. Glutamine and branched-chain amino acids as isoleucine and valine are prospectively associated and could serve as risk markers for multimorbidity in older adults.

Prospective Association Between Plasma Concentrations of Fatty Acids and Other Lipids, and Multimorbidity in Older Adults.

Biological mechanisms that lead to multimorbidity are mostly unknown, and metabolomic profiles are promising to explain different pathways in the aging process. The aim of this study was to assess the prospective association between plasma fatty acids and other lipids, and multimorbidity in older adults. Data were obtained from the Spanish Seniors-ENRICA 2 cohort, comprising noninstitutionalized adults ≥65 years old. Blood samples were obtained at baseline and after a 2-year follow-up period for a total of 1 488 subjects. Morbidity was also collected at baseline and end of the follow-up from electronic health records. Multimorbidity was defined as a quantitative score, after weighting morbidities (from a list of 60 mutually exclusive chronic conditions) by their regression coefficients on physical functioning. Generalized estimating equation models were employed to assess the longitudinal association between fatty acids and other lipids, and multimorbidity, and stratified analyses by diet quality, measured with the Alternative Healthy Eating Index-2010, were also conducted. Among study participants, higher concentrations of omega-6 fatty acids [coef. per 1-SD increase (95% CI) = -0.76 (-1.23, -0.30)], phosphoglycerides [-1.26 (-1.77, -0.74)], total cholines [-1.48 (-1.99, -0.96)], phosphatidylcholines [-1.23 (-1.74, -0.71)], and sphingomyelins [-1.65 (-2.12, -1.18)], were associated with lower multimorbidity scores. The strongest associations were observed for those with a higher diet quality. Higher plasma concentrations of omega-6 fatty acids, phosphoglycerides, total cholines, phosphatidylcholines, and sphingomyelins were prospectively associated with lower multimorbidity in older adults, although diet quality could modulate the associations found. These lipids may serve as risk markers for multimorbidity.

Validation of diagnosis of acute myocardial infarction and stroke in electronic medical records: a primary care cross-sectional study in Madrid, Spain (the e-MADVEVA Study).

OBJECTIVES: To validate the diagnoses of acute myocardial infarction (AMI) and stroke recorded in electronic medical records (EMR) and to estimate the population prevalence of both diseases in people aged ≥18 years. DESIGN: Cross-sectional validation study. SETTING: 45 primary care centres. PARTICIPANTS: Simple random sampling of diagnoses of AMI and stroke (International Classification of Primary Care-2 codes K75 and K90, respectively) registered by 55 physicians and random age-matched and sex-matched sampling of the records that included in primary care EMRs in Madrid (Spain). PRIMARY AND SECONDARY OUTCOME MEASURES: Sensitivity, specificity, positive and negative predictive values and overall agreement were calculated using the kappa statistic. Applied gold standards were ECGs, brain imaging studies, hospital discharge reports, cardiology reports and neurology reports. In the case of AMI, the ESC/ACCF/AHA/WHF Expert Consensus Document was also used. Secondary outcomes were the estimated prevalence of both diseases considering the sensitivity and specificity obtained (true prevalence). RESULTS: The sensitivity of a diagnosis of AMI was 98.11% (95% CI, 96.29 to 99.03), and the specificity was 97.42% (95% CI, 95.44 to 98.55). The sensitivity of a diagnosis of stroke was 97.56% (95% CI, 95.56 to 98.68), and the specificity was 94.51% (95% CI, 91.96 to 96.28). No differences in the results were found after stratification by age and sex (both diseases). The prevalence of AMI and stroke was 1.38% and 1.27%, respectively. CONCLUSION: The validation results show that diagnoses of AMI and stroke in primary care EMRs constitute a helpful tool in epidemiological studies. The prevalence of AMI and stroke was lower than 2% in the population aged over 18 years.

Effect of depression on mortality and cardiovascular morbidity in type 2 diabetes mellitus after 3 years follow up. The DIADEMA study protocol.

BACKGROUND: Type 2 diabetes mellitus and depression are highly prevalent diseases that are associated with an increased risk of cardiovascular disease and mortality. There is evidence about a bidirectional association between depressive symptoms and type 2 diabetes mellitus. However, prognostic implications of the joint effects of these two diseases on cardiovascular morbidity and mortality are not well-known. METHOD/DESIGN: A three-year, observational, prospective, cohort study, carried out in Primary Health Care Centres in Madrid (Spain). The project aims to analyze the effect of depression on cardiovascular events, all-cause and cardiovascular mortality in patients with type 2 diabetes mellitus, and to estimate a clinical predictive model of depression in these patients.The number of patients required is 3255, all them with type 2 diabetes mellitus, older than 18 years, who regularly visit their Primary Health Care Centres and agree to participate. They are chosen by simple random sampling from the list of patients with type 2 diabetes mellitus of each general practitioner.The main outcome measures are all-cause and cardiovascular mortality and cardiovascular morbidity; and exposure variable is the major depressive disorder.There will be a comparison between depressed and not depressed patients in all-cause mortality, cardiovascular mortality, coronary artery disease and stroke using the Chi-squared test. Logistic regression with random effects will be used to adjust for prognostic factors. Confounding factors that might alter the effect recorded will be taken into account in this analysis. To assess the effect of depression on the mortality, a survival analysis will be used comparing the two groups using the log-rank test. The control of potential confounding variables will be performed by the construction of a Cox regression model. DISCUSSION: Our study's main contribution is to evaluate the increase in the risk of cardiovascular morbidity and mortality, in depressed Spanish adults with type 2 diabetes mellitus attended in Primary Health Care Setting. It would also be useful to identify subgroups of patients for which the interventions could be more beneficial.

Pre-infection HDL-cholesterol levels and mortality among elderly patients infected with SARS-CoV-2.

BACKGROUND AND AIMS: Low HDL-cholesterol (HDLc) concentration is associated with a greater risk of infection-related mortality. We wanted to evaluate the relationship between pre-infection HDLc levels and mortality among older patients infected with SARS-Cov-2. METHODS: This is a population-based, cohort study, comprising all individuals residing in Madrid (Spain) born before 1 January 1945, and alive on 31 December 2019. Demographic, clinical, and analytical data were obtained from the primary care electronic clinical records. Confirmed SARS-CoV-2 infection was defined as a positive result in the RT-qPCR or in the antigen test. A death from COVID-19 was defined as that registered in the hospital chart, or as any death occurring in the 15 days following a confirmed SARS-CoV-2 infection. Data on infection, hospitalization, or death due to SAR-CoV-2 were collected from 1 March 2020 through 31 December 2020. RESULTS: Of the 593,342 individuals comprising the cohort, 36,966 had a SARS-CoV-2 infection during 2020, and at least one HDLc measurement in the previous five years. Among them, 9689 (26.2%) died from COVID-19. After adjustment for age and sex, the relative risk (95% confidence interval) of COVID-19 death across increasing quintiles of HDLc was 1.000, 0.896 (0.855-0.940), 0.816 (0.776-0.860), 0.758 (0.719-0.799), and 0.747 (0.708-0.787). The association was maintained after further adjustment for comorbidities, statin treatment and markers of malnutrition. While in females this association was linear, in males it showed a U-shaped curve. CONCLUSIONS: In older subjects, a higher HDLc measured before SARS-CoV-2 infection was associated with a lower risk of death.

Glycemic variability and all-cause mortality in a large prospective southern European cohort of patients with differences in glycemic status.

BACKGROUND: Few studies have analyzed the relationship between glucose variability (GV) and adverse health outcomes in patients with differences in glycemic status. The present study tests the hypothesis that GV predicts all-cause mortality regardless of glycemic status after simple adjustment (age and sex) and full adjustment (age, sex, cardiovascular disease, hypertension, use of aspirin, statins, GLP-1 receptor agonists, SGLT-2 inhibitors and DPP-4 inhibitors, baseline FPG and average HbA1c). METHODS: Prospective cohort study with 795 normoglycemic patients, 233 patients with prediabetes, and 4,102 patients with type 2 diabetes. GV was measured using the coefficient of variation of fasting plasma glucose (CV-FPG) over 12 years of follow-up. The outcome measure was all-cause mortality. RESULTS: A total of 1,223 patients (657 men, 566 women) died after a median of 9.8 years of follow-up, with an all-cause mortality rate of 23.35/1,000 person-years. In prediabetes or T2DM patients, the fourth quartile of CV-FPG exerted a significant effect on all-cause mortality after simple and full adjustment. A sensitivity analysis excluding participants who died during the first year of follow-up revealed the following results for the highest quartile in the fully adjusted model: overall, HR (95%CI) = 1.54 (1.26-1.89); dysglycemia (prediabetes and T2DM), HR = 1.41 (1.15-1.73); T2DM, HR = 1.36 (1.10-1.67). CONCLUSION: We found CV-FPG to be useful for measurement of GV. It could also be used for the prognostic stratification of patients with dysglycemia.

Validation of diabetes mellitus and hypertension diagnosis in computerized medical records in primary health care.

BACKGROUND: Computerized Clinical Records, which are incorporated in primary health care practice, have great potential for research. In order to use this information, data quality and reliability must be assessed to prevent compromising the validity of the results.The aim of this study is to validate the diagnosis of hypertension and diabetes mellitus in the computerized clinical records of primary health care, taking the diagnosis criteria established in the most prominently used clinical guidelines as the gold standard against which what measure the sensitivity, specificity, and determine the predictive values.The gold standard for diabetes mellitus was the diagnostic criteria established in 2003 American Diabetes Association Consensus Statement for diabetic subjects. The gold standard for hypertension was the diagnostic criteria established in the Joint National Committee published in 2003. METHODS: A cross-sectional multicentre validation study of diabetes mellitus and hypertension diagnoses in computerized clinical records of primary health care was carried out. Diagnostic criteria from the most prominently clinical practice guidelines were considered for standard reference.Sensitivity, specificity, positive and negative predictive values, and global agreement (with kappa index), were calculated. Results were shown overall and stratified by sex and age groups. RESULTS: The agreement for diabetes mellitus with the reference standard as determined by the guideline was almost perfect (κ=0.990), with a sensitivity of 99.53%, a specificity of 99.49%, a positive predictive value of 91.23% and a negative predictive value of 99.98%.Hypertension diagnosis showed substantial agreement with the reference standard as determined by the guideline (κ=0.778), the sensitivity was 85.22%, the specificity 96.95%, the positive predictive value 85.24%, and the negative predictive value was 96.95%. Sensitivity results were worse in patients who also had diabetes and in those aged 70 years or over. CONCLUSIONS: Our results substantiate the validity of using diagnoses of diabetes and hypertension found within the computerized clinical records for epidemiologic studies.

Establishing Technical Values for Nursing Diagnoses in Primary Healthcare.

PURPOSE: To establish technical values for nursing diagnoses in primary healthcare with which to weight the delivery of care based on criteria of complexity and relevance. METHODS: A three-phase cross-sectional descriptive study: (1) establishing and weighting of the assessment criteria of technical values, (2) scoring of the assessment criteria per diagnosis, and (3) assigning technical values. FINDINGS: Diagnoses were ordered on the scoring scale obtained and a technical value of 1 to 4 was assigned according to their quartile. CONCLUSIONS: Having a technical value for each nursing diagnosis helps to measure the diversity and complexity of care. IMPLICATIONS FOR NURSING PRACTICE: Technical values may contribute to improving nursing management indicators, as they incorporate a quantitative view into the assessment process.

OBJETIVO: Definir un valor técnico para los diagnósticos enfermeros en Atención Primaria que permita ponderar la prestación de cuidados en base a criterios de complejidad y relevancia. MÉTODOS: Estudio descriptivo transversal realizado en 3 fases: 1) definición y ponderación de los criterios de valoración del valor técnico, 2) puntuación de los criterios de valoración por diagnóstico, 3) asignación del valor técnico. RESULTADOS: Se ordenaron los diagnósticos en la escala de puntuación obtenida y se asignó un valor técnico del 1 al 4 en función del cuartil. CONCLUSIONES: Disponer de un valor técnico de cada diagnóstico enfermero permite dimensionar la diversidad y la complejidad de los cuidados. IMPLICACIONES: El valor técnico puede contribuir a mejorar los indicadores de gestión de servicios enfermeros al añadir una visión cuantitativa al proceso evaluativo. PALABRAS CLAVE: diagnóstico de enfermería; terminología normalizada de enfermería; Atención Primaria de salud; indicadores de calidad de la atención de salud; indicadores de gestión.

Population-based cross-sectional study of 11 645 Spanish nonagenarians with type 2 diabetes mellitus: cardiovascular profile, cardiovascular preventive therapies, achievement goals and sex differences.

OBJECTIVES: To evaluate the risk profile, achievement of cardiometabolic goals, and frequency and optimal use of cardiovascular preventive therapies among nonagenarians with type 2 diabetes mellitus (T2DM). To investigate possible sex differences. DESIGN AND SETTING: A cross-sectional population study of 11 645 persons aged ≥90 years with T2DM living in Madrid (Spain). Sociodemographic, clinical and therapy profiles were collected through electronic records in primary care. We considered antihypertensive therapy and lipid-lowering therapy to be optimal when known patients with hypertension with albuminuria received renin-angiotensin system blockers and statins had been prescribed for overt cardiovascular disease. RESULTS: The prevalence of coronary artery disease was higher in males than in females (21.5% vs 12.6%, p<0.01), as was that of peripheral artery disease (8.5% vs 2.3%, p<0.01). However, the prevalence of cerebrovascular disease was similar in both sexes (16.5% vs 16%; p=0.44). Haemoglobin A1c was lower than 7% in 64.4% of cases, with female predominance in patients with known dementia (67.1% female vs 59.9% male; p<0.01). Antiplatelet therapy was significantly more frequent in males than in females (48.1% vs 44.3%; p<0.01), as were statins (43.2% vs 40.2%; p<0.01). Both in primary and in secondary prevention, rates for simultaneous achievement of the HbA1c, blood pressure, LDL-C goals were significantly lower among females (p<0.01). For each criterion of optimal use of cardiovascular preventive therapies, adherence was significantly better in males than in females. CONCLUSION: Our study showed that the risk of cerebrovascular disease was similar in both male and female Spanish nonagenarians. Adherence was poorer in females for all criteria of optimal use of cardiovascular preventive therapies. Our findings indicate that the known sex differences in younger patients with T2DM persist in patients aged ≥90 years. There is considerable room for improvement in standards of preventive care in nonagenarians with T2DM, especially in females.

Prevalence of depression in patients with type 2 diabetes mellitus in Spain (the DIADEMA Study) : results from the MADIABETES cohort.

OBJECTIVE: To estimate the prevalence of depression in patients diagnosed with type 2 diabetes mellitus (T2DM), and to identify sociodemographic, clinical and psychological factors associated with depression in this population. Additionally, we examine the annual incidence rate of depression among patients with T2DM. METHODS: We performed a large prospective cohort study of patients with T2DM from the Madrid Diabetes Study. The first recruitment drive included 3443 patients. The second recruitment drive included 727 new patients. Data have been collected since 2007 (baseline visit) and annually during the follow-up period (since 2008). RESULTS: Depression was prevalent in 20.03% of patients (n=592; 95% CI 18.6% to 21.5%) and was associated with previous personal history of depression (OR 6.482; 95% CI 5.138 to 8.178), mental health status below mean (OR 1.423; 95% CI 1.452 to 2.577), neuropathy (OR 1.951; 95% CI 1.423 to 2.674), fair or poor self-reported health status (OR 1.509; 95% CI 1.209 to 1.882), treatment with oral antidiabetic agents plus insulin (OR 1.802; 95% CI 1.364 to 2.380), female gender (OR 1.333; 95% CI 1.009 to 1.761) and blood cholesterol level (OR 1.005; 95% CI 1.002 to 1.009). The variables inversely associated with depression were: being in employment (OR 0.595; 95% CI 0.397 to 0.894), low physical activity (OR 0.552; 95% CI 0.408 to 0.746), systolic blood pressure (OR 0.982; 95% CI 0.971 to 0.992) and social support (OR 0.978; 95% CI 0.963 to 0.993). In patients without depression at baseline, the incidence of depression after 1 year of follow-up was 1.20% (95% CI 1.11% to 2.81%). CONCLUSIONS: Depression is very prevalent among patients with T2DM and is associated with several key diabetes-related outcomes. Our results suggest that previous mental status, self-reported health status, gender and several diabetes-related complications are associated with differences in the degree of depression. These findings should alert practitioners to the importance of detecting depression in patients with T2DM.

Influenza vaccination in people with type 2 diabetes, coverage, predictors of uptake, and perceptions. Result of the MADIABETES cohort a 7years follow up study.

OBJECTIVES: We aim to determine influenza vaccination uptake among people with diabetes included in the MADIABETES cohort study in order to identify predictors of uptake and to analyze reasons for adherence and non-adherence with vaccination. METHODS: Using data from the MADIABETES Study we conducted a retrospective case record form based study without controls. We included outpatients with type 2 diabetes mellitus. Information was obtained from computerized clinical records and by telephone survey. The main dependent variables were influenza vaccination uptake in the year 2013 and the reason for receiving or refusing vaccination. RESULTS: Overall, 65.7% had received the influenza vaccine in 2013. The mean number of influenza vaccines received from 2007 to 2013 was 3.24 (SD1.15), although 19.23% had not received any influenza vaccine and 23.3% had been vaccinated against pneumococcus. The variables that increased the probability of being vaccinated were inclusion in the age-based recommendation (⩾60years), having a chronic respiratory disease, previous pneumococcal vaccination, higher number of visits to the general practitioner, higher number of influenza vaccines, and longer time since diabetes diagnosis. A higher mean glycated haemoglobin value in 2013 was associated with a reduced probability of vaccination. Most patients (90%) agreed to be vaccinated following their physician's advice because of their age or their chronic conditions. The most common reason for refusal among men was the belief that they were not at risk (41.6% vs. 29.79% in women); the most common reason for refusal among women was fear of adverse reactions (32.53% vs. 20.23% in men). CONCLUSIONS: The uptake of influenza vaccination among diabetic patients in the present study was below desirable levels. The main barrier to vaccination was lack of knowledge regarding the need for and risks and advantages of influenza vaccination. Healthcare professionals should educate and encourage influenza vaccination among people with diabetes.

Correction: Predictors of Adherence to Multiple Clinical Preventive Recommendations among Adults with Diabetes in Spain.

[This corrects the article DOI: 10.1371/journal.pone.0131844.].

Correction: Trends in the Prevalence of Depression in Hospitalized Patients with Type 2 Diabetes in Spain: Analysis of Hospital Discharge Data from 2001 to 2011.

[This corrects the article DOI: 10.1371/journal.pone.0117346.].