There is limited long-term evidence on the effects of COVID-19 on vascular injury between male and female sex. An adult cohort of COVID-19 survivors (COVID+) and confirmed SARS-CoV-2 antibody-negative participants (COVID-) were prospectively enrolled. COVID+ participants who have documented the presence of persistent symptoms four weeks following infection were considered to have post-acute sequelae of COVID-19 (PASC). Non-invasive, FDA-approved EndoPAT (Endo-PAT2000) was used for endothelial assessment. COVID-(n = 94) were 1:1 propensity score matched to COVID+ (n = 151) on baseline covariates including sex. Among COVID+, 66.2% (n = 100) had PASC. Higher levels of coagulation marker, D-dimer (p = 0.001), and gut permeability marker, zonulin (p = 0.001), were associated with female sex. Estimated differences in augmentation index (AI) between COVID- (0.9 ± 17.2) and COVID+ (8.4 ± 15.7; p = 0.001) and between female and male sex (12.9 ± 1.9; p < .0001) were observed. Among COVID+ with PASC, the average AI (10.5 ± 1.6) was 9.7 units higher than COVID- (p < .0001) and 6.2 units higher compared to COVID+ with no PASC (p = 0.03). COVID+ PASC+ female sex had the highest AI (14.3 ± 1.9). The effects of SARS-CoV-2 infection on vascular function varies across strata of sex and female sex in the post-acute phase of COVID-19 have the worse arterial elasticity (highest AI).

Background and Objectives: In the context of disease prevention, interaction on an additive scale is commonly assessed to determine synergistic effects between exposures. While the \"Relative Excess Risk due to Interaction\" represents the main measure of additive interaction between risk factors, in this study we aimed to extend this approach to assess additive interaction between factors known to prevent the event\'s occurrence, such as medical interventions and drugs. Materials and Methods: We introduced and described the \"Relative Risk Reduction due to Interaction\" (RRRI) as a key measure to assess additive interactions between preventive factors, such as therapeutic interventions and drug combinations. For RRRI values closer to 1, the combination of exposures has a greater impact on reducing the event risk due to their interaction. As a purely illustrative example, we re-evaluated a previous investigation of the synergistic effect between statins and blood pressure-lowering drugs in preventing major adverse cardiovascular events (MACE). Moreover, simulation studies were used to empirically evaluate the performance of a robust Poisson regression model to estimate RRRI across different scenarios. Results: In our example, the drug combination revealed a positive additive interaction in further reducing MACE risk (RRRI > 0), even if not statistically significant. This result is more straightforward to interpret as compared to the original one based on the RERI. Additionally, our simulations highlighted the importance of large sample sizes for detecting significant interaction effects. Conclusion: We recommend RRRI as the main measure to be considered when exploring additive interaction effects between protective exposures, such as the investigation of synergistic effects between drug combinations or preventive treatments.

Evidence on the association between red meat consumption and lung cancer risk is weak. This study examined the associations between red meat and lung cancer across levels of antioxidant intake from foods or supplements. Cox proportional hazard models were applied to assess hazard ratios (HRs) for lung cancer incidence in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cancer screening trial. Baseline food frequency questionnaires measured red meat and antioxidant intake. The food-based Composite Dietary Antioxidant Index (fCDAI) evaluated the overall natural intake of vitamin A, vitamin C, vitamin E, zinc, magnesium, and selenium. During 13 years of follow-up, 95,647 participants developed 1599 lung cancer cases. Higher red meat consumption was associated with a higher risk of lung cancer (HRQ4vsQ1 1.43, 95%CI 1.20-1.71, p-trend < 0.001). We observed similar trends across groups with low or medium levels of antioxidant intake. However, no association was noticed in the group with the highest fCDAI (HRQ4vsQ1 1.24, 95%CI 0.90-1.72, p-trend = 0.08) and highest independent natural antioxidant intake. The attenuated risk was not consistently observed among groups with high supplement use. Lastly, we did not notice evidence of interactions between red meat and antioxidant intake. Our findings emphasize the importance of limiting red meat in lung cancer prevention.

OBJECTIVE: The aim of this study was to investigate the prospective associations between plasma branched-chain amino acids (BCAAs) and the risk of ischemic stroke in men and women.
METHODS: We conducted a nested case-control study within a community-based cohort in China. The cohort consisted of 15,926 participants in 2013-2018. A total of 321 ischemic stroke cases were identified during the follow up and individually matched with 321 controls by date of birth (±1 year) and sex. Females accounted for 55.8% (n = 358, 179 cases vs 179 controls) of the study population. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the association between plasma BCAAs and ischemic stroke risk by conditional logistic regression.
RESULTS: Elevated plasma isoleucine was associated with a higher risk of ischemic stroke in women. The OR for the highest compared to the lowest quartile was 2.22 (95% CI: 1.11-4.44, P trend = 0.005) after adjustment for body mass index, education attainment, smoking, hypertension, renal function, menopause and physical activity. A similar association was found for total BCAAs (adjusted OR = 2.03, 95% CI: 1.05-3.95, P trend = 0.04). In contrast, no significant association of plasma BCAAs with ischemic stroke risk was observed in men.
CONCLUSIONS: Plasma isoleucine and total BCAAs were significantly associated with ischemic stroke risk in women, but not in men, highlighting sex differences in BCAAs metabolism and stroke pathogenesis.

Gender is an observed effect modifier of the association between loneliness and memory aging. However, this effect modification may be a result of information bias due to differential loneliness under-reporting by gender. We applied probabilistic bias analyses to examine whether effect modification of the loneliness-memory decline relationship by gender is retained under three simulation scenarios with various magnitudes of differential loneliness under-reporting between men and women. Data were from biennial interviews with adults aged 50+ in the US Health and Retirement Study from 1996-2016 (5,646 women and 3,386 men). Loneliness status (yes vs. no) was measured from 1996-2004 using the CES-D loneliness item and memory was measured from 2004-2016. Simulated sensitivity and specificity of the loneliness measure were informed by a validation study using the UCLA Loneliness Scale as a gold standard. The likelihood of observing effect modification by gender was higher than 90% in all simulations, although the likelihood reduced with an increasing difference in magnitude of the loneliness under-reporting between men and women. The gender difference in loneliness under-reporting did not meaningfully affect the observed effect modification by gender in our simulations. Our simulation approach may be promising to quantify potential information bias in effect modification analyses.

BACKGROUND: Numerous studies have linked fine particulate matter (PM2.5) to increased cardiovascular mortality. Less is known how the PM2.5-cardiovascular mortality association varies by use of cardiovascular medications. This study sought to quantify effect modification by statin use status on the associations between long-term exposure to PM2.5 and mortality from any cardiovascular cause, coronary heart disease (CHD), and stroke.
METHODS: In this nested case-control study, we followed 1.2 million community-dwelling adults aged ≥66 years who lived in Ontario, Canada from 2000 through 2018. Cases were patients who died from the three causes. Each case was individually matched to up to 30 randomly selected controls using incidence density sampling. Conditional logistic regression models were used to estimate odds ratios (ORs) for the associations between PM2.5 and mortality. We evaluated the presence of effect modification considering both multiplicative (ratio of ORs) and additive scales (the relative excess risk due to interaction, RERI).
RESULTS: Exposure to PM2.5 increased the risks for cardiovascular, CHD, and stroke mortality. For all three causes of death, compared with statin users, stronger PM2.5-mortality associations were observed among non-users [e.g. for cardiovascular mortality corresponding to each interquartile range increase in PM2.5, OR = 1.042 (95% CI, 1.032-1.053) vs OR = 1.009 (95% CI, 0.996-1.022) in users, ratio of ORs = 1.033 (95% CI, 1.019-1.047), RERI = 0.039 (95% CI, 0.025-0.050)]. Among users, partially adherent users exhibited a higher risk of PM2.5-associated mortality than fully adherent users.
CONCLUSIONS: The associations of chronic exposure to PM2.5 with cardiovascular and CHD mortality were stronger among statin non-users compared to users.

Air pollution and noise exposure may synergistically contribute to increased cardiometabolic disorders; however, few studies have examined this potential interaction nor considered exposures beyond residential location. This study investigates the combined impact of dynamic air pollution and transportation noise on cardiometabolic disorders in San Diego County. Using the Community of Mine Study (2014-2017), 602 ethnically diverse participants were assessed for obesity, dyslipidemia, hypertension, and metabolic syndrome (MetS) using anthropometric measurements and biomarkers from blood samples. Time-weighted measures of exposure to PM2.5, NO2, road and aircraft noise were calculated using global positioning system (GPS) mobility data and Kernel Density Estimation. Generalized estimating equation models were used to analyze associations. Interactions were assessed on the multiplicative and additive scales using relative excess risk due to interaction (RERI). We found that air pollution and noise interact to affect metabolic disorders on both multiplicative and additive scales. The effect of noise on obesity and MetS was higher when air pollution was higher. The RERI of aircraft noise and NO2 on obesity and MetS were 0.13 (95%CI 0.03, 0.22) and 0.13 (95%CI 0.02, 0.25), respectively. This finding suggests that aircraft noise and air pollution may have synergistic effects on obesity and MetS.

Limited knowledge is available about the association between autistic spectrum disorder (ASD) and precocious puberty. Our study examined the association between the two medical conditions and effect modification by sex and neuropsychiatric comorbidities in a nationwide population. To compare the risk of precocious puberty between ASD and non-ASD cases, we conducted a Cox regression analysis using ASD as the exposure and time to precocious puberty as the outcome. We adjusted for sex, attention-deficit/hyperactivity disorder (ADHD), tic disorder, obsessive-compulsive disorder (OCD), anxiety disorder, intellectual disability, and epilepsy. We performed a moderation analysis to examine the potential moderating effects of sex and comorbidities. Patients with ASD were prone to have precocious puberty, with an adjusted hazard ratio (aHR) of 1.80 (95% CI: 1.61-2.01). For effect modification, sex, specifically females, moderated the association between ASD and precocious puberty, with a relative excess risk due to interaction (RERI) of 7.35 (95% CI 4.90-9.80). No significant effect modification was found for any of the comorbidities within the scope of additive effect modification. We found that patients with ASD were prone to precocious puberty, regardless of sex or comorbid neuropsychiatric disorders. Girls with ASD are at a particularly higher risk of developing precocious puberty.

UNASSIGNED: The risk of failure associated with different surgical strategies for prosthetic joint infections (PJIs) among patients with and without Staphylococcus aureus is uncertain. The purpose of this study was to assess whether S. aureus modifies the association between retained hardware and failure following revision surgery for PJI of the knee.
UNASSIGNED: This was a single-center retrospective cohort study of 106 first PJIs of the knee between 2016 and 2020 at a rural academic medical center. The exposure was retained hardware following revision surgery for PJI, and the outcomes were recurrent infection, any infection, and a composite outcome including any infection, unplanned revision, failure to undergo reimplantation, amputation, or death within 2 years of revision. We used negative binomial regression to quantify the association between the exposure and outcome and to assess the presence of S. aureus as an effect modifier.
UNASSIGNED: Retained hardware was significantly associated with failure when defined as recurrent infection among S. aureus PJI (adjusted risk difference [aRD], 0.38; 95% CI, 0.12-0.64) but not in the absence of S. aureus (aRD, -0.02; 95% CI, -0.17 to 0.13), and S. aureus was an effect modifier (P interaction = .01).
UNASSIGNED: We report a significant association between the presence of retained hardware and recurrent infection among S. aureus PJI of the knee, but not for non-S. aureus PJI. This could help inform the surgical management of PJI of the knee in cases where the microbiology is known before surgery.

UNASSIGNED: The current medical paradigm of evidence-based medicine relies on clinical guidelines derived from randomized clinical trials (RCTs), but these guidelines often overlook individual variations in treatment effects. Approaches have been proposed to develop models predicting the effects of individualized management, such as predictive allocation, individualizing treatment allocation. It is currently unknown whether widespread implementation of predictive allocation could result in better population-level outcomes over guideline-based therapy. We sought to simulate the potential effect of predictive allocation using data from previously conducted RCTs.
RESULTS: Data from 3 RCTs (positive trial, negative trial, trial stopped for futility) in pediatric cardiology were used in a computational simulation study to quantify the potential benefits of a personalized approach based on predictive allocation. Outcomes were compared when using a universal approach vs predictive allocation where each patient was allocated to the treatment associated with the lowest predicted probability of negative outcome. Compared to results from RCTs, predictive allocation yielded absolute risk reductions of 13.8% (95% confidence interval [CI] -1.9 to 29.5), 13.9% (95% CI 4.5-23.2), and 15.6% (95% CI 1.5-29.6), respectively, corresponding to a number needed to treat of 7.3, 7.2, and 6.4. The net benefit of predictive allocation was directly proportional to the performance of the prediction models and disappeared as model performance degraded below an area under the curve of 0.55.
CONCLUSIONS: These findings highlight that predictive allocation could result in improved group-level outcomes, particularly when highly predictive models are available. These findings will need to be confirmed in simulations of other trials with varying conditions and eventually in RCTs of predictive vs guideline-based treatment allocation.