Risk Reduction Research Articles

Risk of new-onset diabetes and efficacy of pharmacological weight loss therapy.

To develop a clinical risk model to identify individuals at higher risk of developing new-onset diabetes and who might benefit more from weight loss pharmacotherapy. A total of 21 143 patients without type 2 diabetes at baseline from two TIMI clinical trials of stable cardiovascular patients were divided into a derivation (~2/3) and validation (~1/3) cohort. The primary outcome was new-onset diabetes. Twenty-seven candidate risk variables were considered, and variable selection was performed using multivariable Cox regression. The final model was evaluated for discrimination and calibration, and for its ability to identify patients who experienced a larger benefit from the weight loss medication lorcaserin in terms of risk of new-onset diabetes. During a median (interquartile range) follow-up of 2.3 (1.8-2.7) years, new-onset diabetes occurred in 1013 patients (7.7%). The final model included five independent predictors (glycated haemoglobin, fasting glucose, age, body mass index, and triglycerides/high-density lipoprotein). The clinical risk model showed good discrimination (Harrell's C-indices 0.802, 95% confidence interval [CI] 0.788-0.817 and 0.807, 95% CI 0.788-0.826) in the derivation and validation cohorts. The calibration plot demonstrated adequate calibration (2.5-year area under the curve was 81.2 [79.1-83.5]). While hazard ratios for new-onset diabetes with a weight-loss therapy were comparable across risk groups (annual risks of <1%, 1%-5%, and >5%), there was a sixfold gradient in absolute risk reduction from lowest to highest risk group (p = 0.027). The developed clinical risk model effectively predicts new-onset diabetes, with potential implications for personalized patient care and therapeutic decision making.

Association between the use of statins and in-hospital mortality risk in patients with sepsis-induced coagulopathy during ICU stays: a study based on medical information mart for intensive care database

BackgroundThe objective of this study was to explore the correlation between statin administration in the intensive care unit (ICU) setting and the in-hospital mortality risk of patients suffering from sepsis-induced coagulopathy (SIC).MethodsUtilizing a retrospective cohort study design, this investigation collected data from the Medical Information Mart for Intensive Care (MIMIC)-IV spanning 2008 to 2019. The diagnosis of SIC was established based on a SIC score of 4 or above. Statin usage during the ICU period was extracted from the prescription records based on the keywords of statin medications. The primary endpoint analyzed was the in-hospital mortality within the ICU, characterized by any death occurring during the ICU admission.ResultsDuring the follow-up, which had a median duration of approximately 7.28 days, 18.19% of the 4,777 SIC patients died in the ICU. Statin was linked with a decrease in the risk of in-hospital mortality for SIC patients in the ICU [hazard ratio (HR): 0.73, 95% confidence interval (CI): 0.60–0.89, P = 0.002]. Relative to rosuvastatin, the use of atorvastatin (HR: 0.54, 95% CI: 0.34–0.85, P = 0.008) or simvastatin (HR: 0.55, 95% CI: 0.33–0.92, P = 0.024), as well as combinations of multiple statins (HR: 0.36, 95% CI: 0.15–0.86, P = 0.022), was associated with a reduction in ICU in-hospital mortality risk. Subgroup analysis also suggested that the use of atorvastatin, simvastatin, or a combination of statins had an advantage over rosuvastatin in reducing ICU in-hospital mortality in SIC patients older than 65 years of age or SIC patients with respiratory failure or cardiogenic shock (all P < 0.05).ConclusionThe present study supports the potential benefits of statin use in mortality in SIC patients during ICU stays. The study encourages clinicians to consider the benefits of statins and supports the ongoing exploration of statins for enhanced outcomes in critical care settings.

Effects of a psychological first aid (PFA) based on the SIX Cs model on acute stress responses in a simulated emergency.

The SIX Cs model, a neuropsychological framework for psychological first aid, addresses acute stress responses that may lead to functional failure and heighten the risk for posttraumatic stress disorder. Unlike emotional interventions, this model prioritizes Cognitive Communication to diminish emotional overwhelm and bolster cognitive functioning. It introduces a Challenge for active engagement, Control for cognitive management of situations, Commitment from the helper to reduce loneliness, and Continuity to ensure narrative coherence. This study evaluates the SIX Cs model's effectiveness in an experimental setup to alleviate acute stress reaction symptoms. Sixty-three participants voluntarily participated. They were randomly assigned to the SIX Cs intervention (experimental) or to supportive emotional expression (control). They listened to a 3-min audio recording of a real emergency 911 phone call. Interventions were provided before and after listening to the recording. Before, immediately after, and 5 min later (recovery), participants' anxiety, heart rate variability, and mental resilience levels were measured. For all three outcomes, the Time × Group interactions were statistically significant. Follow-up analyses revealed that the SIX Cs participants showed lower anxiety and less reductions in heart rate variability and resilience than controls immediately after the stressor. Furthermore, the SIX Cs participants recovered faster on all three outcomes compared to controls. The results demonstrate the superior effect of the psychological first aid based SIX C's protocol over control in all outcomes, immediately after a simulated stressor and 7 min later as well as possible contribution for posttraumatic stress disorder risk reduction. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Effectiveness of a postpartum vascular risk reduction clinic on behavioral change and long-term cardiovascular outcomes in women who had preeclampsia: a case-control study

Effectiveness of a postpartum vascular risk reduction clinic on behavioral change and long-term cardiovascular outcomes in women who had preeclampsia: a case-control study

The efficacy of prolonged antibiotic prophylaxis in total breast reconstruction with AFT: A retrospective cohort study

BackgroundAutologous fat transfer (AFT) is increasingly adopted as another total breast reconstruction option. The aim of this study is to investigate the efficacy of prolonged antibiotic treatment on the onset of surgical site infections in patients treated with AFT for total breast reconstruction. MethodsThis retrospective cohort study was conducted on patients who received AFT for total breast reconstruction, with antibiotic prophylaxis during their (multiple) AFT procedure(s) from 9 December 2020 to 10 October 2023. Patients were divided into two groups according to their prophylactic antibiotic regimen. The primary outcome was analysed as the cumulative incidence, the relative risk (RR), the absolute risk reduction (ARR), and the number needed to treat (NNT). For the secondary outcome, a multilevel logistic regression analysis was performed. Results765 surgeries in 205 patients were analyzed. 624 surgeries on 168 patients had perioperative antibiotic prophylaxis in combination with post-operative antibiotic prophylaxis was administered (group 1). 141 surgeries on 37 patients had only perioperative antibiotic prophylaxis administered (group 2). The RR was 0.68 (95%CI 0.14 – 3.31) of a surgical site infection (SSI) when receiving peri- and postoperative antibiotic prophylaxis in comparison to treatment with only perioperative prophylaxis. The ARR was 0.46% (95%CI -1.40 – 2.32) with a NNT of 219 patients. ConclusionProlonged antibiotic prophylaxis is ineffective for patients who receive total breast reconstruction with AFT. This study showed no statistically significant difference in SSIs of the reconstructed breast after receiving prolonged antibiotic treatment in comparison to single shot peri-operative antibiotic prophylaxis.

Determining factors influencing flood preparedness among citizens in Jakarta: A protection motivation theory approach

The Jakarta Metropolitan Area is one of the cities heavily affected by floods in Asia. Effective disaster risk reduction strategies require deep understanding of what motivates its citizens towards preparedness and mitigation actions. This study aimed to discern these motivating factors among Jakarta's residents through the Protection Motivation Theory (PMT) approach. Through an online survey, 304 participants provided insights into how the extended PMT factors shape their Protection Motivation (PM) towards flood preparedness. A total of nine (9) variables and 41 constructs were considered in this study. PMT factors were comprised of PM, Perceived Severity (PS), Perceived Vulnerability (PV), Response Efficacy (RE), and Perceived Self-Efficacy (SE) along with additional factors such as Media (M), Government Preventive Actions (GA), Flood Experience (FE), and Geographical Perspectives (GP). Partial Least Square Structural Equation Modeling (PLS-SEM) revealed that SE had the most substantial impact on influencing PM (β = 0.522) followed by PV, PS, and RE. The results also showed the significance of M and GA to both SE and RE. Meanwhile, FE illustrates positive impact to both PV and PS. Interestingly, GP was found to be only significant to PV and not to PS. External factors M and GA demonstrated a significant indirect effect on PM through SE, whereas GP exhibited a significant indirect effect on PM through PV. These findings provide actionable insights for policymakers and disaster management practitioners, emphasizing the power of media and the need for comprehensive strategies that address both the psychological and practical aspects of flood disaster readiness in Jakarta and potentially other flood-prone regions.

Cashflow-driven investment beyond expectations

ABSTRACT This paper presents a computationally tractable optimization model for cashflow-driven investment where the aim is to find asset portfolios whose future payouts cover given liability payments as well as possible. While current industry solutions are largely based on expected future cash flows, we use a stochastic optimization model that seeks portfolios that give the best possible match across time as well as scenarios. Cashflow matching across scenarios is controlled by risk aversion while the timing is driven by illiquidity of money markets. When illiquidity increases, the hedging strategy quickly shifts towards portfolios suggested by deterministic models, but significant uncertainty remains. The model can incorporate hundreds of quoted instruments in the construction of optimal hedging strategies. The hedging strategies are able to employ any statistical connections between the liabilities and publicly quoted assets. The model is solved with simple Monte Carlo approximations and off-the-shelf convex optimization software. Besides optimal hedging strategies, we find the least cost of hedging which provides a market-consistent valuation based on the current quotes and the liquidity factors as well as the views and risk preferences of the investor/regulator. The approach is illustrated by pricing and hedging defined benefit pension liabilities which depend on uncertain longevity developments and the consumer price index. The hedging strategies are constructed from 128 publicly quoted instruments including index-linked bonds and equities. We find that the optimized hedging strategies achieve lower risk at a lower cost than the strategies obtained by matching expected cashflows. The hedging-based liability valuations are robust with respect to model parameters and the additional risk reduction achieved by optimization does not add much to the overall hedging cost.

The effects of specific vegetable subtypes on constipation incidence in the general United States population.

While the intake of larger quantities of vegetables has been linked to a reduction in constipation risk, which vegetables in particular underlie this risk reduction remains incompletely understood. As such, the present study was developed to explore correlations between the intake of particular vegetable types and the risk of constipation. This cross-sectional analysis was based on data from the National Health and Nutrition Examination Survey (NHANES) collected from 2005-2010. Classifications and intake assessments for different vegetables were assessed with the Food Patterns Equivalents Database (FPED), while stool frequency or stool consistency was used to define constipation. Relationships between the intake of particular vegetable components and constipation were assessed through a weighted logistic regression approach. Subgroup and restricted cubic spline (RCS) regression analyses were further employed to explore associations between specific vegetable subtypes and constipation. This study included 13,860 eligible subjects, of whom 1,405 and 12,455 were respectively classified into the constipated and non-constipated groups. Following multivariate adjustment, the intake of non-starchy vegetables including orange, red, dark green, and other vegetables was found to be positively associated with a reduction in constipation risk. In contrast, constipation was unrelated to total starchy vegetable or potato intake. Tomatoes, in particular, were associated with a marked decrease in constipation risk (odds ratios: 0.80, 95% confidence interval: 0.71-0.91). These results were confirmed through RCS and subgroup analyses. Non-starchy vegetables, particularly tomatoes, were found to be associated with a pronounced reduction in constipation risk, which was unaffected by the intake of potatoes or starchy vegetables.

Association of a dietary pattern related to serum vitamin D levels with metabolic syndrome risk among Korean adults: based on the Korean national health and nutrition examination survey.

Vitamin D has a crucial role in our metabolic health. We aimed to examine associations of vitamin D status and its related dietary pattern (DP) with prevalent risk of metabolic syndrome (MetS) in 9,237 Korean adults aged 19-64 years based on the National Health and Nutrition Examination Survey. Vitamin D status was examined by serum 25-hydroxyvitamin D (25(OH)D). A vitamin D-related DP associated with 25(OH)D levels was derived using reduced rank regression (RRR). Associations of vitamin D status and its related DP with MetS prevalence were examined using multivariable logistic regression models adjusted for potential confounders. Men with sufficient vitamin D status had a 44% lower risk of MetS prevalence (OR: 0.56; 95%CI: 0.36-0.87) compared to those with deficiency. A vitamin D-related DP derived using RRR was characterized by high intakes of vegetables, fish, fruits, and nuts and low intakes of eggs, oils, and mushrooms in this study population. Among men, the DP was significantly associated with a lower risk of MetS prevalence, showing a 12% (95%CI: 4-20%) reduction in risk for a one-unit increase in the DP score. However, there was no significant association among women. The study's findings suggest that a sufficient vitamin D status and a related DP with high intakes of vegetables, fish, fruit, and nuts were associated with the risk of MetS, particularly in Korean male adults.

Can short- and long-term maternal and infant risks linked to hypertension and diabetes during pregnancy be reduced by therapy?

Hypertensive disorders of pregnancy (HDP), especially preeclampsia, and diabetes during pregnancy pose significant risks for both maternal and infant health, extending to long-term outcomes such as early-onset cardiovascular disease and metabolic disorders. Current strategies for managing HDP focus on screening, prevention, surveillance, and timely intervention. No disease-modifying therapies exist so far for established preeclampsia; delivery remains the definitive resolution. Preventive measures-including early pregnancy screening, exercise, and low-dose aspirin-show promise. Antihypertensive treatments reduce severe hypertension risks, whereas magnesium sulfate remains the standard for preventing eclampsia. Planned delivery from gestational week 37 can balance maternal benefits and neonatal risks in women with established preeclampsia. Delivery between 34 and 37 weeks gestation in women with preeclampsia has to balance risks for mother and infant. Lifestyle interventions-particularly diet and physical activity-are pivotal in managing gestational diabetes mellitus and type 2 diabetes. The oral antidiabetic metformin has shown benefits in glycaemic control and reducing maternal weight gain, although its long-term effects on offspring remain uncertain. The safety of other peroral antidiabetics in pregnancy is less studied. Advancements in glucose monitoring and insulin administration present encouraging prospects for enhancing outcomes in women with diabetes types 1 and 2. Both HDP and diabetes during pregnancy necessitate vigilant management through a combination of lifestyle modifications, pharmacological interventions, and timely obstetric care. Although certain treatments such as low-dose aspirin and metformin show efficacy in risk reduction, further research is ongoing to ensure safety for both mothers and their offspring to reduce short- and long-term adverse effects.

Unequal Health Burden from Air Pollution among Minors in Education.

Air pollution exposure has been linked to a variety of adverse health outcomes among minors; yet little is known about the associated health inequity across regions and schools. Here, we assessed the unequal health burden linked to particulate matter exposure among minors of 10,358 schools in China through 12,439,232 individual health records. Our findings highlight the persistent health risks with superlinear concentration-response patterns and following inverted U-shaped risk trends, that each 10 μg/m3 increase in PM2.5 exposure resulted in 4.1% (3.9-4.2%) additional school absenteeism risk. Compared to urban well-built schools, minors in rural poor-built schools experienced significantly higher exposure and slower rate of risk reduction and had over 80.0% less medical resources while bearing 145.2% of the health burden. Disparities in pollution exposure, built environment, and resource allocation are intertwined to shape the health inequity pattern, especially between rural and urban schools. These findings underscore the urgency for persistent efforts aimed at disadvantaged schools to reduce pollution exposure and equitably distribute social resources, ultimately securing an impartial health-centered education for minors.

Stroke Risk Reduction in Atrial Fibrillation Through Pharmacist Prescribing

Major gaps in the delivery of appropriate oral anticoagulation therapy (OAC) exist, leaving a large proportion of persons with atrial fibrillation (AF) unnecessarily at risk for stroke and its sequalae. To investigate whether pharmacist-led OAC prescription can increase the delivery of stroke risk reduction therapy in individuals with AF. This prospective, open-label, patient-level randomized clinical trial of early vs delayed pharmacist intervention from January 1, 2019, to December 31, 2022, was performed in 27 community pharmacies in Alberta, Canada. Pharmacists identified patients 65 years or older with 1 additional stroke risk factor and known, untreated AF (OAC nonprescription or OAC suboptimal dosing) or performed screening using a 30-second single-lead electrocardiogram to detect previously unrecognized AF. Patients with undertreated or newly diagnosed AF eligible for OAC therapy were considered to have actionable AF. Data were analyzed from April 3 to November 30, 2023. In the early intervention group, pharmacists prescribed OAC using guideline-based algorithms with follow-up visits at 1 and 3 months. In the delayed intervention group, which served as the usual care control, the primary care physician (PCP) was sent a notification of actionable AF along with a medication list (both enhancement over usual care). After 3 months, patients without OAC optimization in the control group underwent delayed pharmacist intervention. The primary outcome was the difference in the rate of guideline-concordant OAC use in the 2 groups at 3-month follow-up ascertained by a research pharmacist blinded to treatment allocation. Eighty patients were enrolled with actionable AF (9 [11.3%] newly diagnosed in 235 individuals screened). The mean (SD) age was 79.7 (7.4) years, and 45 patients (56.3%) were female. The median CHADS2 (congestive heart failure, hypertension, age, diabetes, and stroke or transient ischemic attack) score was 2 (IQR, 2-3). Seventy patients completed follow-up. Guideline-concordant OAC use at 3 months occurred in 36 of 39 patients (92.3%) in the early intervention group vs 23 of 41 (56.1%) in the control group (P < .001), with an absolute increase of 34% and number needed to treat of 3. Of the 23 patients who received appropriate OAC prescription in the control group, the PCP called the pharmacist for prescribing advice in 6 patients. This randomized clinical trial found that pharmacist OAC prescription is a potentially high-yield opportunity to effectively close gaps in the delivery of stroke risk reduction therapy for AF. Scalability and sustainability of pharmacist OAC prescription will require larger trials demonstrating effectiveness and safety. ClinicalTrials.gov Identifier: NCT03126214.

Quantile mapping technique for enhancing satellite-derived precipitation data in hydrological modelling: a case study of the Lam River Basin, Vietnam

ABSTRACT Accurate precipitation is crucial for hydrological modelling in sparse gauge regions like the Lam River Basin (LRB) in Vietnam. Gridded precipitation data from satellite and numerical models offer significant advantages in such areas. However, satellite precipitation estimates (SPEs) are subject to uncertainties, especially in high variable of topography and precipitation. This study focuses on enhancing the accuracy of Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), Climate Prediction Center morphing technique (CMORPH) using the Quantile Mapping (QM) technique, aligning the cumulative distribution functions of the observed precipitation data with those of the SPEs, and assessing the impact on hydrological predictions. The study highlights that the post-correction IMERG precipitation using QM performs better than other data sets, enhancing the hydrological model's performance for the LRB at different temporal scales. Nash–Sutcliffe efficiency values increased from 0.60 to 0.77, surpassing the original IMERG's 0.52 to 0.74, and correlation coefficients improved from 0.79 to 0.89 (compared with the previous 0.75–0.86) for hydrological modelling. Additionally, Percent Bias (PBIAS) decreased from approximately −1.66 to −2.21% (contrasting with the initial −20.22 and 4.6%) with corrected SPEs. These findings have implications for water resource management and disaster risk reduction initiatives in Vietnam and other countries.

Sex differences in sensitivity to dopamine receptor manipulations of risk-based decision making in rats.

Risky decision making involves the ability to weigh risks and rewards associated with different options to make adaptive choices. Previous work has established a necessary role for the basolateral amygdala (BLA) in mediating effective decision making under risk of punishment, but the mechanisms by which the BLA mediates this process are less clear. Because this form of decision making is profoundly sensitive to dopaminergic (DA) manipulations, we hypothesized that DA receptors in the BLA may be involved in risk-taking behavior. To test this hypothesis, male and female Long-Evans rats were trained in a decision-making task in which rats chose between a small, safe food reward and a larger food reward that was associated with a variable risk of footshock punishment. Once behavioral stability emerged, rats received intra-BLA infusions of ligands targeting distinct dopamine receptor subtypes prior to behavioral testing. Intra-BLA infusions of the dopamine D2 receptor (D2R) agonist quinpirole decreased risk taking in females at all doses, and this reduction in risk taking was accompanied by an increase in sensitivity to punishment. In males, decreased risk taking was only observed at the highest dose of quinpirole. In contrast, intra-BLA manipulations of dopamine D1 or D3 receptors (D1R and D3R, respectively) had no effect on risk taking. Considered together, these data suggest that differential D2R sensitivity in the BLA may contribute to the well-established sex differences in risk taking. Neither D1Rs nor D3Rs, however, appear to contribute to risky decision making in either sex.

Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods

BackgroundIn randomized clinical trials, treatment effects may vary, and this possibility is referred to as heterogeneity of treatment effect (HTE). One way to quantify HTE is to partition participants into subgroups based on individual’s risk of experiencing an outcome, then measuring treatment effect by subgroup. Given the limited availability of externally validated outcome risk prediction models, internal models (created using the same dataset in which heterogeneity of treatment analyses also will be performed) are commonly developed for subgroup identification. We aim to compare different methods for generating internally developed outcome risk prediction models for subject partitioning in HTE analysis.MethodsThree approaches were selected for generating subgroups for the 2,441 participants from the United States enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) randomized controlled trial. An extant proportional hazards-based outcomes predictive risk model developed on the overall ASPREE cohort of 19,114 participants was identified and was used to partition United States’ participants by risk of experiencing a composite outcome of death, dementia, or persistent physical disability. Next, two supervised non-parametric machine learning outcome classifiers, decision trees and random forests, were used to develop multivariable risk prediction models and partition participants into subgroups with varied risks of experiencing the composite outcome. Then, we assessed how the partitioning from the proportional hazard model compared to those generated by the machine learning models in an HTE analysis of the 5-year absolute risk reduction (ARR) and hazard ratio for aspirin vs. placebo in each subgroup. Cochran’s Q test was used to detect if ARR varied significantly by subgroup.ResultsThe proportional hazard model was used to generate 5 subgroups using the quintiles of the estimated risk scores; the decision tree model was used to generate 6 subgroups (6 automatically determined tree leaves); and the random forest model was used to generate 5 subgroups using the quintiles of the prediction probability as risk scores. Using the semi-parametric proportional hazards model, the ARR at 5 years was 15.1% (95% CI 4.0–26.3%) for participants with the highest 20% of predicted risk. Using the random forest model, the ARR at 5 years was 13.7% (95% CI 3.1–24.4%) for participants with the highest 20% of predicted risk. The highest outcome risk group in the decision tree model also exhibited a risk reduction, but the confidence interval was wider (5-year ARR = 17.0%, 95% CI= -5.4–39.4%). Cochran’s Q test indicated ARR varied significantly only by subgroups created using the proportional hazards model. The hazard ratio for aspirin vs. placebo therapy did not significantly vary by subgroup in any of the models. The highest risk groups for the proportional hazards model and random forest model contained 230 participants each, while the highest risk group in the decision tree model contained 41 participants.ConclusionsThe choice of technique for internally developed models for outcome risk subgroups influences HTE analyses. The rationale for the use of a particular subgroup determination model in HTE analyses needs to be explicitly defined based on desired levels of explainability (with features importance), uncertainty of prediction, chances of overfitting, and assumptions regarding the underlying data structure. Replication of these analyses using data from other mid-size clinical trials may help to establish guidance for selecting an outcomes risk prediction modelling technique for HTE analyses.

Project Reducing Psychosocial Risks In Law Enforcement: Training To Wellbeing

The INFAD Association of Psychology and Education, in cooperation with several other partners, especially the Family Law Centre, Faculty of Law of the University of Coimbra-3004–545 Coimbra. Email: cdf@fd.uc.pt http://www.centrodedireitodafamilia.org has participated in the ERASMUS+ PROGRAMME KA220-VET. Project Number| PT01-KA220 - VET- 000028146. A Project that has allowed us from INFAD to intensely approach the topic of “Psychology meeting health”; “I didn’t find psychology so healthy”; “Psychology meeting health”. For INFAD, this and other already completed Erasmus + projects are and have been of vital importance for their contribution to the field of science and to the society to which we owe ourselves, providing efforts and conclusions,such as those we present in this Project Information-Presentation. The World Health Organization (WHO) describes mental well-being as a fundamental component of health and places it as one of the main concerns for the coming years (Mental Health Action Plan, 2013-2020). Mental health is being the subject of significant investments from all states in the world, with strategies that empower people to maintain healthy behaviours related to mental health, improving the quality of life (WHO) and reducing the psychosocial risks of mental health disorders. This is also a concern of the member states in their national mental health strategies (Portuguese National Mental Health Program - Priority Health Programs 2020 Goals) and in the production of legislation that specifically refers to the balance between work and life and the reduction of psychosocial risks.

Death Risk Response of High-Altitude Resident Populations to COVID-19 Vaccine: A Retrospective Cohort Study.

Vásquez-Velásquez, Cinthya, Diego Fano-Sizgorich, and Gustavo F Gonzales. Death risk response of high-altitude resident populations to COVID-19 vaccine: Retrospective cohort study. High Alt Med Biol. 00:00-00, 2024. Background: Peru had one of the highest mortality rates caused by the coronavirus disease 2019 (COVID-19) pandemic worldwide. Vaccination significantly reduces mortality. However, the effectiveness of vaccination might differ at different altitudinal levels. The study aimed to evaluate the effect modification of altitude on the association between vaccination and COVID-19 mortality in Peru. Methodology: A retrospective cohort, using open access databases of deaths, COVID-19 cases, hospitalizations, and vaccination was obtained from the Peruvian Ministry of Health. Deaths due to COVID-19 were evaluated in vaccinated and nonvaccinated patients. Crude (RR) and adjusted relative risks (aRR) were calculated using generalized linear models of Poisson family with robust variances. Models were adjusted for age, sex, pandemic wave, and Human Development Index. To evaluate the interaction by altitude, a stratified analysis by this variable was performed. The variable altitude was categorized as, 0-499 m (828,298 cases), 500-1,499 m (64,735 cases), 1,500-2,499 m (106,572 cases), and ≥2,500 m (179,004 cases). The final sample studied included 1,362,350 cases. Results: The vaccine showed a considerable reduction of death risk with the second (aRR: 0.41, 95% confidence interval [CI]: 0.38-0.44) and third doses (aRR: 0.21, 95% CI: 0.20-0.23). In the adjusted and interaction model, it can be observed that medium and high altitude present a higher risk of death compared to sea level (aRR: 2.58 and 2.03, respectively). Likewise, the two doses' group presents an aRR:1.22 for medium altitude (1,500-2,499 m) and 1.6 for high altitude (≥2,500 m), compared with low-altitude population, suggesting that the action of vaccination at high altitude is altered by the effect of the altitude itself. Conclusions: Altitude might modify the protective effect of SARS-CoV-2 vaccine against COVID-19 death.

Vaccinome landscape in nearly 620,000 patients with diabetes.

Type 1 (T1D) and type 2 diabetes (T2D) are associated with an elevated incidence of infectious diseases and a higher risk of infections-related hospitalization and death. In this study, we delineated the "vaccinome" landscape obtained with a large immunization schedule offered by the Regional Government of Lombardy in a cohort of 618,396 patients with diabetes (T1D and T2D). Between September 2021 and September 2022, immunization coverage for influenza, meningococcus, pneumococcus, and herpes zoster was obtained from the public computerized registry of the healthcare system of Lombardy Region (Italy) in 618,396 patients with diabetes and in 9,534,087 subjects without diabetes. Type of diabetes, age, mortality, and hospitalizations were retrospectively analyzed in vaccinated and unvaccinated patients. Among patients with diabetes (T1D and T2D), 44.6% received the influenza vaccine, 10.9% the pneumococcal vaccine, 2.5% the anti-meningococcus vaccine and 0.7% the anti-zoster vaccine. Patients with diabetes immunized for influenza, zoster and meningococcus showed a 2-fold overall reduction in mortality risk and a decrease in hospitalizations. A 3-fold lower risk of mortality and a decrease in hospitalizations for both cardiac and pulmonary causes were also observed after influenza, zoster, and meningococcus immunization in older patients with diabetes. Immunization coverage is still far from the recommended targets in patients with diabetes. Despite this, influenza vaccination protected nearly 3,800 per 100,000 patients with diabetes from risk of death. The overall impressive decrease in mortality and hospitalizations observed in vaccinated patients strengthens the need for scaling up the "vaccinome" landscape in patients with diabetes.

Fat-Free Mass Index in Sport: Normative Profiles and Applications for Collegiate Athletes.

Jagim, AR, Harty, PS, Jones, MT, Fields, JB, Magee, M, Smith-Ryan, AE, Luedke, J, and Kerksick, CM. Fat-free mass index in sport: normative profiles and applications for collegiate athletes. J Strength Cond Res XX(X): 000-000, 2024-Recent concerns have been raised regarding the ethical considerations of conducting body composition assessments in sports. Specific apprehensions pertain to the inappropriate use of percent body fat and the limited application of the results to performance and recovery. Fat-free mass index (FFMI), a height-adjusted assessment of FFM, can serve as an alternative body composition metric to focus on in sports. Fat-free mass index provides valuable context regarding an optimal amount of FFM, accounting for skeletal frame and height while helping to qualify an athlete's FFM as low, moderate, or high. This review posits that shifting the focus of body composition measures to FFM can support more ideal targets across athletic seasons, careers, and the return to play after injury. In addition, a FFM focus may help change the perception of body composition assessment and how athletes perceive their current body because of the increased focus on the FFM compartment and the goal of maximizing tissue accrual, rather than focusing on fat loss. Fat-free mass index is calculated by dividing FFM (kg) by height (m2) and can serve to normalize FFM, relative to height, and enable comparisons across athletes, sport types, and sex. Previous research has identified differences in FFMI across sex and among sport categories. Still, there is a need for more published data to develop optimal ranges for FFMI across sex, sports, and positions. As more data become available, FFMI has the potential to provide normative guidelines for optimal FFM development, performance, and injury risk reduction. The purpose of the current review was to summarize FFMI values across collegiate sport categories and competitive status to provide normative profiles, according to sex and sport type.

Chronic kidney disease in type 2 diabetes: The size of the problem, addressing residual renal risk and what we have learned from the CREDENCE trial.

Chronic kidney disease (CKD) associated with type 2 diabetes (T2DM) is a global challenge; progression to end-stage kidney disease (ESKD) and increased risk of cardiovascular disease (CVD) associated with advancing nephropathy are a significant source of morbidity, mortality, and healthcare expenditure. Until recently, renin-angiotensin system (RAS) blockade was the mainstay of pharmacotherapy in diabetic kidney disease (DKD), representing a therapeutic paradigm shift towards interventions that delay disease progression independently of antihypertensive effects. However, a significant residual risk of DKD progression persisted in patients established on RAS blockade, highlighting the need for additional treatment options. Sodium-glucose cotransporter-2 (SGLT2) inhibitors, originally licensed as glucose-lowering agents in people with T2DM, serendipitously demonstrated beneficial renal and cardiovascular outcomes in clinical trials designed primarily to evaluate their cardiovascular safety. The Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) trial was the first to study the effect of SGLT2 inhibition on a primary composite renal endpoint of ESKD, doubling of serum creatinine, or renal or cardiovascular death in 4401 people with T2DM and CKD established on RAS blockade. The trial was stopped early due to efficacy, demonstrating a 30% relative risk reduction in the primary endpoint in the canagliflozin group (hazard ratio 0.70, 95% confidence interval 0.59-0.82; p = 0.00001). Through discussion of the primary analysis from CREDENCE, and selected post hoc analyses, we review the significant benefits highlighted by this landmark study, its role in shaping clinical guidelines, and in re-establishing interest in interventions that reduce the residual risk of progression of DKD, alongside its interrelation with cardiovascular morbidity and heart failure. We also provide a brief narrative summary of key renal outcome trials since CREDENCE, which indicate emerging avenues for pharmacotherapy beyond SGLT2 inhibition.