Effect of frailty status on mortality risk among chilean community-dwelling older adults.

INTRODUCTION: The study of frailty and its effect on the risk of mortality in older people is of utmost importance, but understanding the critical factors is still limited. Our main objective was to analyze the association of frailty with all-cause mortality in a prospective community cohort of older people. METHODS: A five-year longitudinal follow-up study was conducted with 1,174 community-dwelling older adults (men and women≥65 years old) from different Family Health Centers and community groups from Chile. We evaluated the functional risk, socioeconomic status, and anthropometric variables. The frailty status was evaluated by modified Fried criteria. RESULTS: The diagnosis of frailty was reached in 290 older adult participants, who had significantly increased 5-year all-cause mortality independently of age, sex, cognitive impairment, and socioeconomic status (adjusted HR 1.51, 1.06-2.15). CONCLUSION: Frailty is a predictor of increased mortality independently of age, sex, socio-economic and cognitive factors.

Genetic characteristics involved in COVID-19 severity. The CARGENCORS case-control study and meta-analysis.

Pre-existing coronary artery disease (CAD), and thrombotic, inflammatory, or virus infectivity response phenomena have been associated with COVID-19 disease severity. However, the association of candidate single nucleotide variants (SNVs) related to mechanisms of COVID-19 complications has been seldom analysed. Our aim was to test and validate the effect of candidate SNVs on COVID-19 severity. CARGENCORS (CARdiovascular GENetic risk score for Risk Stratification of patients positive for SARS-CoV-2 [COVID-19] virus) is an age- and sex-matched case-control study with 818 COVID-19 cases hospitalized with hypoxemia, and 1636 controls with COVID-19 treated at home. The association between severity and SNVs related to CAD (n = 32), inflammation (n = 19), thrombosis (n = 14), virus infectivity (n = 11), and two published to be related to COVID-19 severity was tested with adjusted logistic regression models. Two external independent cohorts were used for meta-analysis (SCOURGE and UK Biobank). After adjustment for potential confounders, 14 new SNVs were associated with COVID-19 severity in the CARGENCORS Study. These SNVs were related to CAD (n = 10), thrombosis (n = 2), and inflammation (n = 2). We also confirmed eight SNVs previously related to severe COVID-19 and virus infectivity. The meta-analysis showed five SNVs associated with severe COVID-19 in adjusted analyses (rs11385942, rs1561198, rs6632704, rs6629110, and rs12329760). We identified 14 novel SNVs and confirmed eight previously related to COVID-19 severity in the CARGENCORS data. In the meta-analysis, five SNVs were significantly associated to COVID-19 severity, one of them previously related to CAD.

Analysis of myocardial infarction incidence and case-fatality in the last three decades in the province of Girona.

INTRODUCTION AND OBJECTIVES: Myocardial infarction (MI) incidence and case fatality trends are highly informative but relatively untested at the population level. The objective of this work was to estimate MI incidence and case fatality in the Girona population aged 35-74 years, and to determine their 30-year trends (1990-2019). METHODS: The REGICOR (Girona Heart Registry) monitored MI incidence and case fatality rates from 1990 to 2008. For the period 2008 to 2019, we linked discharges from Girona hospitals (n=4 974 977) and mortality registry (n=70 405) during this period. Our linkage algorithm selected key MI diagnostic codes and removed duplicates. Estimates from the linkage algorithm and the REGICOR registry were compared using chi-square tests for overlapping years (2008-2009). We estimated the annual percent change (APC) of standardized MI incidence and 28-day case fatality, and analyzed their trends using joinpoint regression. RESULTS: MI incidence and case fatality estimates were similar in the linkage algorithm and the REGICOR registry. We observed significant decreasing trends in the incidence of MI. The trend was APC, -0.96% (95% confidence interval (95%CI), -1.4 to -0.53) in women from 1990 to 2019 and -4.2% (95%CI, -5.5 to -3.0) in men from 1994 to 2019. The largest decrease in case fatality was -3.8% (95%CI, -5.1 to -2.5) from 1995 to 2003 in women and -2.4% (95%CI, -2.9 to -1.9) from 1995 to 2004 in men, mainly due to prehospital case fatality declines: -1.8% (95%CI, -2.6 to -1.1) in men and -3.2% (95%CI, -4.6 to -1.8) in women. CONCLUSIONS: In Girona, MI incidence and case fatality decreased between 1990 and 2019. The incidence showed a slow but continuous decrease while case fatality only stabilized in the last decade, particularly in women.

Predictive capacity of a genetic risk score for coronary artery disease in assessing recurrences and cardiovascular mortality among patients with myocardial infarction.

Aim: This study aimed to evaluate the capacity of a genetic risk score (GRS) for coronary artery disease (CAD) independent of classical cardiovascular risk factors to assess the risk of recurrence in patients with first myocardial infarction. The secondary aim was to determine the predictive value of this GRS. Methods: We performed a meta-analysis of individual data from three studies, namely, a prospective study including 75 patients aged <55 years, a prospective study including 184 patients with a mean age of 60.5 years, and a case-control study (77 cases and 160 controls) nested in a cohort of patients with first myocardial infarction. A GRS including 12 CAD genetic variants independent of classical cardiovascular risk factors was developed. The outcome was a composite of cardiovascular mortality and recurrent acute coronary syndrome. Results: The GRS was associated with a higher risk of recurrence [hazard ratio = 1.24; 95% confidence interval (CI): 1.04-1.47]. The inclusion of the GRS in the clinical model did not increase the model's discriminative capacity (change in C-statistic/area under the curve: 0.009; 95% CI: -0.007 to 0.025) but improved its reclassification (continuous net reclassification index: 0.29; 95% CI: 0.08-0.51). Conclusion: The GRS for CAD, independent of classical cardiovascular risk factors, was associated with a higher risk of recurrence in patients with first myocardial infarction. The predictive capacity of this GRS identified a subgroup of high-risk patients who could benefit from intensive preventive strategies.

Time-loss Injuries among Female and Male Spanish Rink Hockey Players.

The present study describes the time-loss injuries among female and male athletes of the Spanish rink hockey league during the 2021/22 season.We performed a retrospective cohort study on time-loss injuries, whereby the athlete is prevented from participating in a training session or game because of the injury.A total of 463 athletes were included, with 326 (70.4%) senior male and 137 (29.6%) female. Two hundred and eighty-two time-loss injuries were recorded, the most common form being muscle injuries (112 episodes, 39.7%), especially those affecting the hip adductor muscles (52 episodes, 46.4% of muscle injuries). Most injuries were classified as mild (1-7 days of time-loss) and the median return-to-play was 9.5 days (range 1-180).Injury patterns were compared according to gender, position and moment: the results showed significant differences between senior males and females, between field players and goalkeepers, as well as between training and game, in terms of injury nature and type. The injury incidence proportion was significantly higher for field players compared to goalkeepers), and senior males had a significantly higher risk than senior females.The present study provides a starting point for studying and preventing injuries in rink hockey athletes.

Development and Validation of a Risk Score for Predicting Non-Adherence to Antiretroviral Therapy.

Several patient-related factors that influence adherence to antiretroviral therapy (ART) have been described. However, studies that propose a practical and simple tool to predict nonadherence after ART initiation are still scarce. In this study, we develop and validate a score to predict the risk of nonadherence in people starting ART. The model/score was developed and validated using a cohort of people living with HIV starting ART at the Hospital del Mar, Barcelona, between 2012 and 2015 (derivation cohort) and between 2016 and 2018 (validation cohort),. Adherence was evaluated every 2 months using both pharmacy refills and patient self-reports. Nonadherence was defined as taking <90% of the prescribed dose and/or ART interruption for more than 1 week. Predictive factors for nonadherence were identified by logistic regression. Beta coefficients were used to develop a predictive score. Optimal cutoffs were identified using the bootstrapping methodology, and performance was evaluated with the C statistic. Our study is based on 574 patients: 349 in the derivation cohort and 225 in the validation cohort. A total of 104 patients (29.8%) of the derivation cohort were nonadherent. Nonadherence predictors were patient prejudgment; previous medical appointment failures; cultural and/or idiomatic barriers; heavy alcohol use; substance abuse; unstable housing; and severe mental illness. The cutoff point (receiver operating characteristic curve) for nonadherence was 26.3 (sensitivity 0.87 and specificity 0.86). The C statistic (95% confidence interval) was 0.91 (0.87-0.94). These results were consistent with those predicted by the score in the validation cohort. This easy-to-use, highly sensitive, and specific tool could be easily used to identify patients at highest risk for nonadherence, thus allowing resource optimization and achieving optimal treatment goals.

Validity of prognostic models of critical COVID-19 is variable. A systematic review with external validation.

OBJECTIVES: To identify prognostic models which estimate the risk of critical COVID-19 in hospitalized patients and to assess their validation properties. STUDY DESIGN AND SETTING: We conducted a systematic review in Medline (up to January 2021) of studies developing or updating a model that estimated the risk of critical COVID-19, defined as death, admission to intensive care unit, and/or use of mechanical ventilation during admission. Models were validated in two datasets with different backgrounds (HM [private Spanish hospital network], n = 1,753, and ICS [public Catalan health system], n = 1,104), by assessing discrimination (area under the curve [AUC]) and calibration (plots). RESULTS: We validated 18 prognostic models. Discrimination was good in nine of them (AUCs ≥ 80%) and higher in those predicting mortality (AUCs 65%-87%) than those predicting intensive care unit admission or a composite outcome (AUCs 53%-78%). Calibration was poor in all models providing outcome's probabilities and good in four models providing a point-based score. These four models used mortality as outcome and included age, oxygen saturation, and C-reactive protein among their predictors. CONCLUSION: The validity of models predicting critical COVID-19 by using only routinely collected predictors is variable. Four models showed good discrimination and calibration when externally validated and are recommended for their use.

Five-Year Changes in Inflammatory, Metabolic, and Oxidative Biomarkers and 10-Year Cardiovascular Disease Incidence: The REGICOR Cohort Study.

Ischemic cardiovascular diseases (CVD) originate from an imbalance between atherosclerotic plaque formation, instability, and endothelial healing dynamics. Our aim was to examine the relationship between 5-year changes in inflammatory, metabolic, and oxidative biomarkers and 10-year CVD incidence in a population without previous CVD. This was a prospective cohort study of individuals aged 35-74 years (n = 419) randomly selected from 5263 REGICOR participants without CVD recruited in 2005. Biomarkers were measured at baseline and in 2010. Participants were followed up until 2020 for a composite CVD endpoint including coronary artery disease, stroke, and peripheral artery disease. We used Cox regression to analyze the effect of biomarker levels on the occurrence of the composite endpoint, adjusted for traditional CVD risk factors and baseline levels of each biomarker. Individuals with elevated IL-6 or insulin after 5 years had a higher independent risk of CVD at 10 years, compared to those with lower levels. Each rise of 1 pg/mL of IL-6 or 10 pg/mL of insulin increased the 10-year risk of a CVD event by 32% and 2%, respectively. Compared to a model with traditional CVD risk factors only, the inclusion of IL-6 and insulin improved continuous reclassification by 51%. Elevated serum levels of IL-6 and insulin were associated with a higher risk of CVD at 10 years, independently of traditional CVD risk factors.

Therapeutic Drug Monitoring of Vancomycin Concentrations for the Management of Bone and Joint Infections: An Urgent Need.

Vancomycin is used for the treatment of bone and joint infections (BJI), but scarce information is available about its pharmacokinetic/pharmacodynamic (PK/PD) characteristics. We aimed to identify the risk factors associated with the non-achievement of an optimal PK/PD target in the first therapeutic drug monitoring (TDM). Methods: A retrospective study was conducted in a tertiary hospital from January 2020 to January 2022. Patients with BJI and TDM of vancomycin on day 2 of treatment were included. Initial vancomycin fixed doses (1 g every 8 h or 12 h) was decided by the responsible doctors. According to TDM results, dosage adjustments were performed. An AUC24h/MIC < 400 mg × h/L, between 400 and 600 mg × h/L and >600 mg × h/L, were defined as suboptimal, optimal and supratherapeutic, respectively. Patients were grouped into these three categories. Demographic, clinical and PK characteristics were compared between groups. Nephrotoxicity at the end of treatment was assessed. Results: A total of 94 patients were included: 22 (23.4%), 42 (44.7%) and 30 (31.9%) presented an infratherapeutic, optimal and supratherapeutic PK/PD targets, respectively. A younger age and initial vancomycin dose <40 mg/kg/day were predictive factors for achieving a suboptimal PK/PD target, while older age, higher serum-creatinine and dose >40 mg/kg/day were associated with overexposure. The nephrotoxicity rate was 22.7%. More than 50% of patients did not achieve an optimal PK/PD. Considering age, baseline serum-creatinine and body weight, TDM is required to readily achieve an optimal and safe exposure.

Impact of Phenol-Enriched Olive Oils on Serum Metabonome and Its Relationship with Cardiometabolic Parameters: A Randomized, Double-Blind, Cross-Over, Controlled Trial.

Phenol-rich foods consumption such as virgin olive oil (VOO) has been shown to have beneficial effects on cardiovascular diseases. The broader biochemical impact of VOO and phenol-enriched OOs remains, however, unclear. A randomized, double-blind, cross-over, controlled trial was performed with thirty-three hypercholesterolemic individuals who ingested for 3-weeks (25 mL/day): (1) an OO enriched with its own olive oil phenolic compounds (PCs) (500 ppm; FOO); (2) an OO enriched with its own olive oil PCs (250 ppm) plus thyme PCs (250 ppm; FOOT); and (3) a VOO with low phenolic content (80 ppm). Serum lipid and glycemic profiles, serum 1H-NMR spectroscopy-based metabolomics, endothelial function, blood pressure, and cardiovascular risk were measured. We combined OPLS-DA with machine learning modelling to identify metabolites discrimination of the treatment groups. Both phenol-enriched OO interventions decreased the levels of glutamine, creatinine, creatine, dimethylamine, and histidine in comparison to VOO one. In addition, FOOT decreased the plasma levels of glycine and DMSO2 compared to VOO, while FOO decreased the circulating alanine concentrations but increased the plasma levels of acetone and 3-HB compared to VOO. Based on these findings, phenol-enriched OOs were shown to result in a favorable shift in the circulating metabolic phenotype, inducing a reduction in metabolites associated with cardiometabolic diseases.

Cholesterol and Hypertension Treatment Improve Coronary Risk Prediction but Not Time-Dependent Covariates or Competing Risks.

Background and Aims: Cardiovascular (CV) risk functions are the recommended tool to identify high-risk individuals. However, their discrimination ability is not optimal. While the effect of biomarkers in CV risk prediction has been extensively studied, there are no data on CV risk functions including time-dependent covariates together with other variables. Our aim was to examine the effect of including time-dependent covariates, competing risks, and treatments in coronary risk prediction. Methods: Participants from the REGICOR population cohorts (North-Eastern Spain) aged 35-74 years without previous history of cardiovascular disease were included (n = 8470). Coronary and stroke events and mortality due to other CV causes or to cancer were recorded during follow-up (median = 12.6 years). A multi-state Markov model was constructed to include competing risks and time-dependent classical risk factors and treatments (2 measurements). This model was compared to Cox models with basal measurement of classical risk factors, treatments, or competing risks. Models were cross-validated and compared for discrimination (area under ROC curve), calibration (Hosmer-Lemeshow test), and reclassification (categorical net reclassification index). Results: Cancer mortality was the highest cumulative-incidence event. Adding cholesterol and hypertension treatment to classical risk factors improved discrimination of coronary events by 2% and reclassification by 7-9%. The inclusion of competing risks and/or 2 measurements of risk factors provided similar coronary event prediction, compared to a single measurement of risk factors. Conclusion: Coronary risk prediction improves when cholesterol and hypertension treatment are included in risk functions. Coronary risk prediction does not improve with 2 measurements of covariates or inclusion of competing risks.

Mortality Risk Prediction Dynamics After Heart Failure Treatment Optimization: Repeat Risk Assessment Using Online Risk Calculators.

Objectives: Heart failure (HF) management has significantly improved over the past two decades, leading to better survival. This study aimed to assess changes in predicted mortality risk after 12 months of management in a multidisciplinary HF clinic. Materials and Methods: Out of 1,032 consecutive HF outpatients admitted from March-2012 to November-2018, 357 completed the 12-months follow-up and had N-terminal pro-B-type natriuretic peptide (NTproBNP), high sensitivity troponin T (hs-TnT), and interleukin-1 receptor-like-1 (known as ST2) measurements available both at baseline and follow-up. Three contemporary risk scores were used: MAGGIC-HF, Seattle HF Model (SHFM), and the Barcelona Bio-HF (BCN Bio-HF) calculator, which incorporates the three above mentioned biomarkers. The predicted risk of all-cause death at 1 and 3 years was calculated at baseline and re-evaluated after 12 months. Results: A significant decline in predicted 1-and 3-year mortality risk was observed at 12 months: MAGGIC ~16%, SHFM ~22% and BCN Bio-HF ~15%. In the HF with reduced ejection fraction (HFrEF) subgroup guideline-directed medical therapy led to a complete normalization of left ventricular ejection fraction (≥50%) in almost a third of the patients and to a partial normalization (41-49%) in 30% of them. Repeated risk assessment after 12 months with SHFM and BCN Bio-HF provided adequate discrimination for all-cause 3-year mortality (C-Index: MAGGIC-HF 0.762, SHFM 0.781 and BCN Bio-HF 0.791). Conclusion: Mortality risk declines in patients with HF managed for 12 months in a multidisciplinary HF clinic. Repeating the mortality risk assessment after optimizing the HF treatment is recommended, particularly in the HFrEF subgroup.

Usefulness of Cardiac Computed Tomography in Coronary Risk Prediction: A Five-Year Follow-Up of the SPICA Study (Secure Prevention with Imaging of the Coronary Arteries).

Accurate identification of individuals at high coronary risk would reduce acute coronary syndrome incidence and morbi-mortality. We analyzed the effect on coronary risk prediction of adding coronary artery calcification (CAC) and Segment Involvement Score (SIS) to cardiovascular risk factors. This was a prospective cohort study of asymptomatic patients recruited between 2013-2017. All participants underwent a coronary computed tomography angiography to determine CAC and SIS. The cohort was followed-up for a composite endpoint of myocardial infarction, coronary angiography and/or revascularization (median = five years). Discrimination and reclassification of the REGICOR function with CAC/SIS were examined with the Sommer's D index and with the Net reclassification index (NRI). Nine of the 251 individuals included had an event. Of the included participants, 94 had a CAC = 0 and 85 a SIS = 0, none of them had an event. The addition of SIS or of SIS and CAC to the REGICOR risk function significantly increased the discrimination capacity from 0.74 to 0.89. Reclassification improved significantly when SIS or both scores were included. CAC and SIS were associated with five-year coronary event incidence, independently of cardiovascular risk factors. Discrimination and reclassification of the REGICOR risk function were significantly improved by both indexes, but SIS overrode the effect of CAC.

Personalized assessment of the cumulative complication risk of the atrial fibrillation ablation track: The AF-TRACK calculator.

Background: Atrial fibrillation (AF) ablation strategy is associated with a non-negligible risk of complications and often requires repeat procedures (AF ablation track), implying repetitive exposure to procedural risk. Objective: The purpose of this study was to develop and validate a model to estimate individualized cumulative risk of complications in patients undergoing the AF ablation track (Atrial Fibrillation TRAck Complication risK [AF-TRACK] calculator). Methods: The model was derived from a multicenter cohort including 3762 AF ablation procedures in 2943 patients. A first regression model was fitted to predict the propensity for repeat ablation. The AF-TRACK calculator computed the risk of AF ablation track complications, considering the propensity for repeat ablation. Internal (cross-validation) and external (independent cohort) validation were assessed for discrimination capacity (area under the curve [AUC]) and goodness of fit (Hosmer-Lemeshow [HL] test). Results: Complications (N = 111) occurred in 3.7% of patients (2.9% of procedures). Predictors included female sex, heart failure, sleep apnea syndrome, and repeat procedures. The model showed fair discrimination capacity to predict complications (AUC 0.61 [0.55-0.67]) and likelihood of repeat procedure (AUC 0.62 [0.60-0.64]), with good calibration (HL χ2 12.5; P = .13). The model maintained adequate discrimination capacity (AUC 0.67 [0.57-0.77]) and calibration (HL χ2 5.6; P = .23) in the external validation cohort. The validated model was used to create the Web-based AF-TRACK calculator. Conclusion: The proposed risk model provides individualized estimates of the cumulative risk of complications of undergoing the AF ablation track. The AF-TRACK calculator is a validated, easy-to-use, Web-based clinical tool to calibrate the risk-to-benefit ratio of this treatment strategy.

Increased COVID-19 Mortality in People With Previous Cerebrovascular Disease: A Population-Based Cohort Study.

BACKGROUND: The aim of the study was to determine the association between previous stroke and mortality after coronavirus disease 2019 (COVID-19) according to sex, age groups, and stroke subtypes. METHODS: Prospective population-based cohort study including all COVID-19 positive cases between February 1 and July 31, 2020. Comorbidities and mortality were extracted using linked health administration databases. Previous stroke included transient ischemic attack, ischemic stroke, hemorrhagic stroke, spontaneous subarachnoid hemorrhage, and combined stroke for cases with more than one category. Other comorbidities were obesity, diabetes, hypertension, ischemic heart disease, atrial fibrillation, heart failure, chronic obstructive pulmonary disease, chronic kidney disease, cirrhosis, dementia, individual socioeconomic index, and deprivation index. Cases were followed up until December 31, 2020. Primary outcome was mortality of any cause after COVID-19 positivity. Cox proportional regression analysis adjusted for comorbidities was used. Stratified analyses were performed for sex and age (<60, 60-79, and ≥80 years). RESULTS: There were 91 629 COVID-19 cases. Previous strokes were 5752 (6.27%), of which 3887 (67.57%) were ischemic, 1237 (21.50%) transient ischemic attack, 255 (4.43%) combined, 203 (3.53%) hemorrhagic, and 170 (2.96%) subarachnoid hemorrhage. There were 9512 deaths (10.38%). Mortality was associated with previous stroke (hazard ratio [HR]=1.12 [95% CI, 1.06-1.18]; P<0.001), in both sexes separately (men=1.13 [1.05-1.22]; P=0.001; women=1.09 [1.01-1.18]; P=0.023), in people <60 years (HR=2.97 [1.97-4.48]; P<0.001) and 60 to 79 years (HR=1.32 [1.19-1.48]; P<0.001) but not in people ≥80 years (HR=1.02 [0.96-1.09]; P=0.437). Ischemic (HR=1.11 [1.05-1.18]; P=0.001), hemorrhagic (HR=1.53 [1.20-1.96]; P=0.001) and combined (HR=1.31 [1.05-1.63]; P=0.016) strokes were associated but not transient ischemic attack. Subarachnoid hemorrhage was associated only in people <60 years (HR=5.73 [1.82-18.06]; P=0.003). CONCLUSIONS: Previous stroke was associated with a higher mortality in people younger than 80 years. The association occurred for both ischemic and hemorrhagic stroke but not for transient ischemic attack. These data might help healthcare authorities to establish prioritization strategies for COVID-19 vaccination.