Exposure Variables Research Articles

Evaluating the impact of occupational noise exposure on workplace fatal and nonfatal injuries in the U.S. (2006–2020)

ObjectivesThis study assessed the relationship between occupational noise exposure and the incidence of workplace fatal injury (FI) and nonfatal injury (NFI) in the United States from 2006 to 2020. It also examined whether distinct occupational and industrial clusters based on noise exposure characteristics demonstrated varying risks for FI and NFI. MethodsAn ecological study design was utilized, employing data from the U.S. Bureau of Labor Statistics for FI and NFI and demographic data, the U.S. Census Bureau for occupation/industry classification code lists, and the U.S./Canada Occupational Noise Job Exposure Matrix for noise measurements. We examined four noise metrics as predictors of FI and NFI rates: mean Time-Weighted Average (TWA), maximum TWA, standard deviation of TWA, and percentage of work shifts exceeding 85 or 90 dBA for 619 occupation-years and 591 industry-years. K-means clustering was used to identify clusters of noise exposure characteristics. Mixed-effects negative binomial regression examined the relationship between the noise characteristics and FI/NFI rates separately for occupation and industry. ResultsAmong occupations, we found significant associations between increased FI rates and higher mean TWA (IRR: 1.06, 95% CI: 1.01–1.12) and maximum TWA (IRR: 1.10, 95% CI: 1.07–1.14), as well as TWA exceedance (IRR: 1.04, 95% CI: 1.01–1.07). Increased rates of NFI were found to be significantly associated with maximum TWA (IRR: 1.06, 95% CI: 1.04–1.09) and TWA exceedance (IRR: 1.03, 95% CI: 1.01–1.05). In addition, occupations with both higher exposure variability (IRR with FI rate: 1.49, 95% CI: 1.23–1.80; IRR with NFI rate: 1.40, 95% CI: 1.14–1.73) and higher level of sustained exposure (IRR with FI rate: 1.27, 95% CI: 1.12–1.44; IRR with NFI rate: 1.21, 95% CI: 1.05–1.39) were associated with higher rates of FI and NFI compared to occupations with low noise exposure. Among industries, significant associations between increased NFI rates and higher mean TWA (IRR: 1.05, 95% CI: 1.02–1.08) and maximum TWA (IRR: 1.06, 95% CI: 1.04–1.08) were observed. Unlike the occupation-specific analysis, industries with higher exposure variability and higher sustained exposures did not display significantly higher FI/NFI rates compared to industries with low exposure. ConclusionsThe results suggest that occupational noise exposure may be an independent risk factor for workplace FIs/NFIs, particularly for workplaces with highly variable noise exposures. The study highlights the importance of comprehensive occupational noise assessments.

Higher doses of fluconazole are needed to ensure target attainment in critically ill adults on continuous Veno-venous hemodialysis

BackgroundCritically ill patients undergoing Continuous Renal Replacement Therapy (CRRT) are treated with higher doses of fluconazole based on the literature recommendations. However, clinical follow-up data demonstrating the effectiveness of this approach are lacking. PurposeA retrospective cohort study was conducted to evaluate whether target attainment was achieved with higher doses of fluconazole. Additionally, the study focused on identifying factors that may contribute to variability in fluconazole exposure in these patients. MethodsCritically ill patients undergoing Continuous Veno-Venous Hemodialysis (CVVHD) who received either standard or higher doses of intravenous fluconazole were included. Evaluation of target attainment was conducted for each dose regimen. ResultsAdministering higher doses resulted in target attainment in 100 % of the patients, indicating that starting with at least 400 mg twice daily is an adequate dosing guideline. In this study, only the dose of fluconazole was found to significantly influence target attainment (p < 0.001), with no other predefined factors identified as having a significant impact. ConclusionAccording to the results of the study, increasing the fluconazole dose to at least 400 mg twice daily is sufficient to reach the desired target in critically ill patients undergoing CVVHD.

Comparison of a radiofrequency electric and magnetic field source-based job-exposure matrix with personal radiofrequency exposure measurements.

Assessing occupational exposure to radiofrequency electromagnetic fields (RF-EMF) presents significant challenges due to the considerable variability in exposure levels within and between occupations. This spatial and temporal variability complicates the reliable evaluation of potential health risks associated with RF-EMF exposure in the workplace. Accurate assessment methods are crucial to understand the extent of exposure and to evaluate potential health risks, especially given the potential for higher exposures in occupational settings compared to the general population. This study compares the historical RF-EMF exposure estimates in the INTEROCC RF-EMF job-exposure matrix (RF-JEM) with recent personal measurement data collected in 2 countries as part of the OccRF-Health study, to assess the broader applicability of the RF-JEM. Weighted kappa (k w) coefficients and Spearman rank correlation tests were performed to assess the alignment between RF-JEM estimates and measurements for 8h time-weighted average exposure intensity and prevalence estimates across various occupations. The comparisons were mainly based on 22 jobs having ≥5 measured workers in the OccRF-Health study. Poor agreement was found for both exposure prevalence and intensity between both methods (k w < 0.1). RF-JEM values likely overestimated exposure levels for both electric (E) and magnetic (H) fields (mean percentage difference >194%) compared to current personal measurements. Findings suggest that the INTEROCC-JEM likely overestimates current exposure intensity levels in the measured jobs. Adopting a semiquantitative JEM could also mitigate misclassification errors due to exposure variability, improving accuracy in exposure assessment. These findings indicate the need for more targeted personal measurements, including among highly exposed workers, and for potentially considering new exposure metrics to more accurately assess occupational RF-EMF exposures in occupational epidemiological research.

Fellow perceptions of robotic surgery preparedness for fellowship.

Many surgical fellowship programs incorporate robotic surgery, yet not all residency programs offer robotic training for residents. Given the variability of pre-fellowship robotic exposure, the goal of this study was to explore whether standardized robotic skills assessment would be useful to fellows at the start of their training. In partnership with the Fellowship Council, we surveyed current fellows of accredited Thoracic, Colorectal, HPB, and Advanced GI/MIS/Bariatrics/Foregut Fellowship programs. Main outcome measurements included amount of robotic exposure during residency, fellows' robotic skills at the start of fellowship, and fellows' attitudes towards a standardized skills assessment. In total, 78 fellows completed the survey. Mean percentage of cases performed robotically during fellowship was 38.1% (SD ± 32.25%). From our respondents, 46% had no robotic curriculum during residency and 86.9% felt a standardized robotic curriculum during residency would have been beneficial. When asked if they started fellowship with adequate robotic skills to operate autonomously, 31% strongly agreed, but 24.4% strongly disagreed. The majority of fellows reported their fellowship program did not conduct an assessment of their robotic skills (71.5%), or provide a specific robotic curriculum (75.6%). On the other hand, 73.3% felt a formal proficiency assessment at the start of fellowship would be helpful for individualized support and training. Given the significant variability in resident exposure to robotic surgery, a standardized robotic curriculum during residency would likely be beneficial. Additionally, a robotic skills assessment at the start of fellowship could help provide a tailored training experience for fellows interested in this skillset.

A dual-penalized approach to hypothesis testing in high-dimensional linear mediation models

The field of mediation analysis, specifically high-dimensional mediation analysis, has been arousing great interest due to its applications in genetics, economics and other areas. Mediation analysis aims to investigate how exposure variables influence outcome variable via mediators, and it is categorized into direct and indirect effects based on whether the influence is mediated. A novel hypothesis testing method, called the dual-penalized method, is proposed to test direct and indirect effects. This method offers mild conditions and sound theoretical properties. Additionally, the asymptotic distributions of the proposed estimators are established to perform hypothesis testing. Results from simulation studies demonstrate that the dual-penalized method is highly effective, especially in weak signal settings. Further more, the application of this method to the childhood trauma data set reveals a new mediator with a credible basis in biological processes.

The impact of print exposure on deaf student literacy

Abstract Recent studies suggest that benefiting early from both a cochlear implant (CI) and exposure to cued speech (CS, support system for the perception of oral language) positively impacts deaf children’s speech perception, speech intelligibility, and reading. This study aims to show how: 1/CS-based speech perception (“cue reading”), and speech intelligibility might also constitute precise measures for determining the impact of CI and CS on deaf students’ literary performance; 2/print exposure might also be a predictive factor in this equation. We conducted regression analyses to examine the impact of these three variables in two experiments conducted on Grade 2–3 deaf children and Grade 6–9 deaf adolescents. Results indicate print exposure significantly contributes to literacy skills across experiments, with additional contributions from cue reading and speech intelligibility in older students. The predictive aspect of the print exposure, cue reading, and speech intelligibility variables will be discussed, as will the consequences for educational and pedagogical practices.

Maternal morbidity in postpartum severe preeclampsia by obstetric delivery volume

BackgroundPre-eclampsia is a leading cause of maternal morbidity and mortality in the United States. Emerging data suggests that postpartum pre-eclampsia may be associated with a higher incidence of maternal morbidity compared to hypertensive disorders of pregnancy (HDP) diagnosed antenatally. Understanding postpartum maternal risk across facilities with a spectrum of obstetric services is critical with the rising rates of pre-eclampsia in all healthcare settings. ObjectiveWe investigated the relationship between facility delivery volume and rates of nontransfusion severe maternal morbidity (SMM) among patients readmitted postpartum for pre-eclampsia with severe features. Study DesignThis is a retrospective cohort study using the Nationwide Readmissions Database (2015–2019) of postpartum patients readmitted for pre-eclampsia with severe features. Our primary outcome was nontransfusion SMM during readmission, defined per U.S. Centers for Disease Control and Prevention criteria. We also evaluated SMM, cardiac SMM, and individual morbidities. The exposure variable was the number of annual deliveries at the readmitting facility. Restricted cubic splines with 4 knots were used to assess the functional form of the relationship between obstetric delivery volume and nontransfusion SMM; a linear relationship was identified as optimal. Logistic regression was used to estimate adjusted odds ratios (aOR) which controlled for maternal age, nontransfusion SMM at delivery, expanded obstetric comorbidity index, and HDP during delivery. ResultsThe cohort included 29,472 patients readmitted with postpartum pre-eclampsia with severe features. The primary payer was 55% private and 42% governmental. Median age was 31.4 years. Most patients did not have prior HDP (65%) or chronic hypertension (86%) diagnosis antenatally. The median interval from delivery hospitalization to readmission was 3.9 days (25th percentile–75th percentile: 2.2–6.5). Nontransfusion SMM occurred in 7% of patients readmitted to facilities with >2000 deliveries compared to 9% with 1 to 2000 deliveries, and 52% without any delivery hospitalizations. The most common SMM was pulmonary edema and heart failure, observed in 4% of readmissions. We observed that for every increase in 1000 deliveries, the odds of a nontransfusion SMM at readmission decreased by 3.5% (aOR: 0.965; 95% confidence interval: 0.94, 0.99). ConclusionNontransfusion SMM for postpartum readmissions with pre-eclampsia with severe features was inversely associated with readmitting hospital delivery volume. This information may guide risk-reducing initiatives for identifying strategies to optimize postpartum care at facilities with lower or no delivery volume.

Model-Informed Precision Dosing of Tacrolimus: A Systematic Review of Population Pharmacokinetic Models and a Benchmark Study of Software Tools.

Tacrolimus is an immunosuppressant commonly administered after solid organ transplantation. It is characterized by a narrow therapeutic window and high variability in exposure, demanding personalized dosing. In recent years, population pharmacokinetic models have been suggested to guide model-informed precision dosing of tacrolimus. We aimed to provide a comprehensive overview of population pharmacokinetic models and model-informed precision dosing software modules of tacrolimus in all solid organ transplant settings, including a simulation-based investigation of the impact of covariates on exposure and target attainment. We performed a systematic literature search to identify population pharmacokinetic models of tacrolimus in solid organ transplant recipients. We integrated selected population pharmacokinetic models into an interactive software tool that allows dosing simulations, Bayesian forecasting, and investigation of the impact of covariates on exposure and target attainment. We conducted a web survey amongst model-informed precision dosing software tool providers and benchmarked publicly available tools in terms of models, target populations, and clinical integration. We identified 80 population pharmacokinetic models, including 44 one-compartment and 36 two-compartment models. The most frequently retained covariates on clearance and distribution parameters were cytochrome P450 3A5 polymorphisms and body weight, respectively. Our simulation tool, hosted at https://lpmx.shinyapps.io/tacrolimus/ , allows thorough investigation of the impact of covariates on exposure and target attainment. We identified 15 model-informed precision dosing software tool providers, of which ten offer a tacrolimus solution and nine completed the survey. Our work provides a comprehensive overview of the landscape of available tacrolimus population pharmacokinetic models and model-informed precision dosing software modules. Our simulation tool allows an interactive thorough exploration of covariates on exposure and target attainment.

Spatiotemporal modelling of airborne birch and grass pollen concentration across Switzerland: A comparison of statistical, machine learning and ensemble methods

BackgroundStatistical and machine learning models are commonly used to estimate spatial and temporal variability in exposure to environmental stressors, supporting epidemiological studies. We aimed to compare the performances, strengths and limitations of six different algorithms in the retrospective spatiotemporal modeling of daily birch and grass pollen concentrations at a spatial resolution of 1 km across Switzerland. MethodsDaily birch and grass pollen concentrations were available from 14 measurement sites in Switzerland for 2000–2019. To develop the spatiotemporal models, we considered spatiotemporal, spatial and temporal predictors including meteorological factors, land-use, elevation, species distribution and Normalized Difference Vegetation Index (NDVI). We used six statistical and machine learning algorithms: LASSO, Ridge, Elastic net, Random forest, XGBoost and ANNs. We optimized model structures through feature selection and grid search techniques to obtain the best predictive performance. We used train-test split and cross-validation to avoid overfitting and overoptimistic performance indicators. We then combined these six models through multiple linear regression to develop an ensemble hybrid model. ResultsThe 5th-95th percentiles of birch and grass pollen concentrations were 0–151 and 0–105 grains/m3, respectively. The hybrid ensemble model achieved the best RMSE on the test dataset for both birch and grass pollen with 94.4 and 19.7 grains/m3, respectively.Nonlinear models (Random forest, XGBoost and ANNs) achieved lower test RMSE's than linear models (LASSO, Ridge, Elastic net) for both pollen types, with RMSE's ranging from 105.9 to 140.5 grains/m3 for birch and from 20.0 to 25.4 grains/m3 for grass pollen. The Random forest algorithm yielded the best spatial and temporal performance among the six evaluated modelling methods. The ensemble hybrid model outperformed the six linear and nonlinear algorithms. Country-wide pollen concentration, land use, weather, and NDVI were important predictors. ConclusionNonlinear algorithms outperformed linear models and accurately explained complex, nonlinear relationships between environmental factors and measured concentrations.

Duration of immunotherapy in dMMR/MSI-H metastatic colorectal cancer patients

BackgroundImmune checkpoint blockade (ICB) has revolutionized treatment of mismatch repair-deficient (dMMR)/microsatellite instability-high (MSI-H) metastatic colorectal cancer (mCRC). However, there is no evidence on the optimal treatment duration. We aimed to compare outcomes of different immunotherapy durations. MethodsAn international multicenter retrospective cohort study of immunotherapy-naïve dMMR/MSI-H mCRC patients who received immunotherapy between 2014–2024. Fixed treatment duration of two years was compared to treatment duration beyond two years. Fixed treatment duration of one year was compared to treatment duration beyond one year. Subgroup analysis was performed for patients who experienced CR. Kaplan-Meier analysis and Cox proportional hazard regression model were used to analyze the effect of all exposure variables on OS. ResultsThe study cohort included 757 dMMR/MSI-H mCRC patients treated with ICB. Median follow-up time was 46.7 months (IQR 28.5–70.3). There was no statistically significant difference in OS between patients treated for a two-year fixed-duration (n = 83) and those treated beyond two years (n = 139) in both the univariable and multivariable analysis (HR=0.65 95 %CI 0.14–3.07 p = 0.59 and HR=0.61 95 %CI 0.12–3.10 p = 0.6, respectively). The comparison between one-year fixed-duration versus continuing treatment beyond one year included 27 and 330 patients, respectively. For patients who achieved CR, discontinuing treatment after one year was not associated with a negative impact on OS (p = 0.5). ConclusionsDiscontinuing immunotherapy after two years is a reasonable option for dMMR/MSI-H mCRC patients with ongoing response. Treatment discontinuation after one year may be considered for patients achieving CR. Further prospective studies are needed to define the most appropriate duration of therapy.

Self-perceived oral health and happiness

In recent years, studies investigating psychological states such as happiness in individuals’ health have increased. Aim: This study investigated a possible association between self-perceived oral health and happiness in university students. Methods: This cross-sectional study was performed in a cohort of university students who entered in the 2016 academic year at the Federal University of Pelotas, located in southern Brazil. Data were collected using a self-administered questionnaire, including demographic and socioeconomic characteristics, psychosocial traits, and oral health-related questions. Happiness was measured through a question accompanied by the Faces Scale of Andrews and Whitey. Poisson regression models with robust variance were used to assess the association between the exposure variables (oral health measures) and the outcome (happiness). Results: The prevalence of happiness was 48.6%. A significant association between happiness and oral health, including satisfaction with dental appearance (PR 1.86; 95% CI 1.73-2.01), oral health-related to quality of life (PR 1.19; 95% CI 1.09-1.31), and halitosis (PR 1.10; 95% CI 1.01-1.20), was found. Conclusion: Individuals who reported dissatisfaction with dental appearance, an impact on oral health-related to quality of life, and halitosis perceived themselves as unhappy.

The association of solid fuel use in households for cooking with elevated blood pressure among reproductive-aged married women in Bangladesh.

Bangladesh is experiencing a rapid increase in hypertension prevalence, particularly in socio-economically disadvantaged communities. The higher use of solid fuel in these communities could be one of the significant factors contributing to this trend, but evidence supporting this hypothesis is limited in Bangladesh. Therefore, this study aims to investigate the associations of household solid fuel use and its exposure level with systolic and diastolic blood pressure (DBP) and hypertension. We analysed 7,320 women's data from 2017/18 Bangladesh Demographic and Health Survey. We considered three outcome variables: (i) systolic blood pressure (BP) (continuous response), (ii) DBP (continuous response), and (iii) hypertension status (yes, no). Our primary exposures of interest were fuel type (clean vs solid) and the potential level of household air pollution exposure through solid fuel use (unexposed, moderately exposed, and highly exposed). We used a multilevel mixed-effects Poisson regression model with robust variance to determine association between exposure and outcome variables while adjusting for confounders. Of the total respondents analysed, approximately 82% used solid fuel for cooking. The age-standardised prevalence of hypertension was 28%. Respondents using solid fuel were found to be 1.44 times (95% confidence interval [CI], 1.04-1.89) more likely to develop hypertension compared to clean fuel users. Compared to women using clean fuel, the likelihood of hypertension was found to be 1.61 times (95% CI, 1.07-2.20) higher among the moderately exposed group and 1.80 times (95% CI, 1.27-2.32) higher among the highly exposed group. Similar associations were reported for systolic and DBP. The use of solid fuel increases the risk of becoming hypertensive and elevates systolic and DBP. Policies and programmes are necessary to increase awareness of the adverse effects of solid fuel use on health, including hypertension. Efforts should be made to reduce solid fuel use and ensure proper ventilation systems in households where solid fuel is used.

Predicting sleep based on physical activity, light exposure, and Heart rate variability data using wearable devices

Objective We aimed to improve the performance of sleep prediction algorithms by increasing the data amount, adding variables reflecting psychological state, and adjusting the data length. Materials and Methods We used ActiGraph GT3X+® and Galaxy Watch Active2™ to collect physical activity and light exposure data. We collected heart rate variability (HRV) data with the Galaxy Watch. We evaluated the performance of sleep prediction algorithms based on different data sources (wearable devices only, sleep diary only, or both), data lengths (1, 2, or 3 days), and analysis methods. We defined the target outcome, ‘good sleep’, as ≥90% sleep efficiency. Results Among 278 participants who denied having sleep disturbance, we used data including 2136 total days and nights from 230 participants. The performance of the sleep prediction algorithms improved with an increased amount of data and added HRV data. The model with the best performance was the extreme gradient boosting model; XGBoost, using both sources combined data with HRV, and 2-day data (accuracy=.85, area under the curve =.80). Conclusions The results show that the performance of the sleep prediction models improved by increasing the data amount and adding HRV data. Further studies targeting insomnia patients and applied researches on non-pharmacological insomnia treatment are needed.

Optimizing β-lactam-containing antibiotic combination therapy for the treatment of Buruli ulcer.

The current treatment for Buruli ulcer is based on empirical evidence of efficacy. However, there is an opportunity for shortening its duration and improving response rates. Evolving understanding of the pharmacokinetic-pharmacodynamic relationships provides the basis for a stronger dose rationale for antibiotics. In conjunction with modelling and simulation, it is possible to identify dosing regimens with the highest probability of target attainment (PTA). This investigation aims to: (i) assess the dose rationale for a new combination therapy including amoxicillin/clavulanic acid (AMX/CLV) currently in clinical trials; and (ii) compare its performance with alternative dosing regimens including rifampicin, clarithromycin and AMX/CLV. In vitro estimates of the minimum inhibitory (MIC) concentration were selected as a measure of the antibacterial activity of different drug combinations. Clinical trial simulations were used to characterize the concentration vs. time profiles of rifampicin, clarithromycin and amoxicillin in a virtual cohort of adult and paediatric patients, considering the effect of baseline covariates on disposition parameters and interindividual variability in exposure. The PTA of each regimen was then assessed using different thresholds of the time above MIC. A weight-banded dosing regimen including 150-600 mg rifampicin once daily, 250-1000 mg clarithromycin and AMX/CLV 22.5mg/kg /1000 mg twice daily ensures higher PTA than the standard of care with AMX/CLV 45 mg/kg/2000 mg once daily. The higher PTA values support the proposed 4-drug combination (rifampicin, clarithromycin, AMX/CLV) currently under clinical investigation. Our findings also suggest that higher rifampicin doses might contribute to enhanced treatment efficacy.

Lifestyle Habits and Risk of Cardiovascular Mortality in Menopausal Women with Cardiovascular Risk Factors: A Retrospective Cohort Study.

Current cardiovascular prevention guidelines emphasise considering sex, gender, and gender identity in risk assessment. This study evaluated the impact of lifestyle habits and chronic diseases on cardiovascular mortality risk in women over 50 with high vascular risk and developed a predictive model for menopausal women with cardiovascular risk factors. A retrospective cohort study used data from the 2011 Spanish National Health Survey and the national death register, focusing on menopausal and postmenopausal women without prior cardiovascular events but with at least one major risk factor. Participants were followed for up to 10 years, assessing mortality from circulatory system diseases and other causes. Exposure variables included socio-demographics, lifestyle habits, health status, self-perceived health, health service use, and pharmacological treatments. Of the 21,007 respondents, 3057 women met the inclusion criteria. The 10-year cumulative incidence of mortality from circulatory causes was 5.9%, and from other causes, 12.7%. Independent predictors of cardiovascular mortality were never consuming legumes, poor self-perceived health, diabetes treatment, lack of physical activity, and older age. Lipid-lowering treatment was protective. The model demonstrated good fit and predictive capacity (C-index = 0.773). This study highlights the significant influence of physical activity, legume consumption, self-perceived health, and specific treatments on cardiovascular mortality risk in menopausal women.

Nationally Representative Rates of Incident Prescription Opioid Use Among United States Adults and Selected Subpopulations: Longitudinal Cohort Study From the National Health Interview Survey, 2019 to 2020

Nationally representative rates of incident prescription opioid use in the United States adult population and selected subpopulations are unknown. Using the National Health Interview Survey (2019–2020) longitudinal cohort, a cohort with 1-year follow-up created using random cluster probability sampling of noninstitutionalized civilian U.S. adults, we estimated rates and predictors of incident opioid use. Of 21,161 baseline (2019) participants randomly chosen for follow-up, the final analytic sample included 10,415 who also participated in 2020. Exposure variables were selected per the socio-behavioral model of health care utilization: predisposing characteristics (sex, age, race, etc), enabling characteristics (socioeconomic status, insurance status), health status (pain, disability, comorbidities, etc), and health care use (office visits, emergency room visits, and hospitalizations). Among adults who did not use prescription opioids in 2019, a 1-year cumulative incidence of 4.1% (95% confidence interval [CI]: 3.5–4.6) was seen in 2020, with an incidence rate (IR) of 32.6 cases of new prescription opioid use per 1,000 person-years (PYs). Cumulative incidence, IR, and adjusted relative risk (RR) varied by participant characteristics. We observed the highest IR in those with ineffective pain treatment (81.6 cases per 1,000 PY) and those who visited the emergency room ≥3 times (93.8 cases per 1,000 PY). Participants reporting ≥4 painful conditions had an adjusted RR of 2.9 (95% CI: 2.0–4.1), while the RR for those with sleep problems was 2.3 (95% CI: 1.7–3.1). Overall, this study presents nationally representative rates of incident prescription opioid use and suggests that some participants are using prescription opioids as an early-resort analgesic contrary to best-practice guidelines. PerspectiveThis longitudinal cohort study presents nationally representative rates of incident prescription opioid use in U.S. adults and selected subpopulations. Our data suggest that some participants are using prescription opioids as a first-line or early-resort analgesic, contrary to best-practice guidelines.

Association between multiple intubation attempts and complications during emergency department airway management: A national emergency airway registry study

ObjectivePeri-intubation complications are important sequelae of airway management in the emergency department (ED). Our objective was to quantify the increased risk of complications with multiple attempts at emergency airway intubation in the ED. MethodsThis is a secondary analysis of a prospectively collected multicenter registry (National Emergency Airway Registry) consisting of attempted ED intubations among subjects aged >14 years. The primary exposure variable was the number of intubation attempts. The primary outcome measure was the occurrence of peri-intubation major complications within 15 min of intubation including hypotension, hypoxemia, vomiting, dysrhythmias, cardiac arrest, esophageal intubation, and failed airway with cricothyrotomy. We constructed multivariable logistic regression models to determine the associations between complications and the number of intubation attempts while controlling for measured pre-exposure variables. ResultsThere were 19,071 intubations in the NEAR database, of which 15,079 met inclusion for this analysis. Of these, 13,459 were successfully intubated on the first attempt, 1,268 on the second attempt, 269 on the third attempt, 61 on the fourth attempt, and 22 on the fifth or more attempt. A complication occurred in 2,137 encounters (14 %). Major complications accompanied 1,968 encounters (13 %) whereas minor complications affected 315 encounters (2 %). The most common major complication was hypoxia. In our multivariable logistic regression model, odds ratios with 95 % confidence intervals for the occurrence of major complications for multiple attempts compared to first-pass success were 4.4 (3.6–5.3), 7.4 (5.0–10.7), 13.9 (5.6–34.3), and 9.3 (2.1–41.7) for attempts 2–5+ (reference attempt 1), respectively. ConclusionsWe found an independent association between the number of intubation attempts among ED patients undergoing emergency airway intubation and the risk of complications.

Testing the causal relationship of fat and sugar intake with depression and cortisol: a Mendelian Randomisation study

Unhealthy diets high in fat and sugar content may have an impact on psychological health and increase the risk of Major Depressive Disorder (MDD) and stress levels. On the other hand, MDD and stress might be related to food choices and intake. However, it is not clear whether diet, and specifically fat and sugar intake, is causally related to stress and MDD, and whether this relationship may be bi-directional. This study utilised Mendelian Randomisation (MR) to investigate the causal nature of the relationship of fat and sugar intake with MDD and cortisol (as a proxy of stress), and to shed light on the direction of this relationship. Summary-level data for all exposure and outcome variables were obtained from large-scale, non-overlapping GWASs in individuals of European ancestry. Bidirectional analyses were performed: one with macronutrients as exposures and one with MDD/cortisol as exposures. Random-effects inverse-variance weighted regression was used as the primary analytic method for genetic instruments with at least two single nucleotide polymorphisms (SNPs) available (and individual Wald ratio was used when only one SNP was available). Higher levels of genetically predicted relative sugar intake were causally associated with lower MDD risk, for both genome-wide significant p-value threshold of p < 1 × 10−8, (OR = 0.553, 95% CI: 0.395-0.775) and relaxed p-value threshold of p < 1 × 10−6 (OR = 0.786, 95% CI: 0.630–0.981). No reverse causality was detected in the opposite direction as MDD was not associated with sugar consumption. The associations observed for all the other pairs of variables were weak and imprecise. A number of limitations was present in the study, such as low-SNP based heritability for some exposures, inability to prove whether variants were correlated with unmeasured confounders and self-reporting of MDD data. Lifestyle and/or pharmacological interventions targeting sugar-related physiological mechanisms may help to reduce depressive symptoms. However, more research is necessary on short- and long-term effects of sugar on the risk of MDD. Additionally, future studies should investigate whether the amount and type of sugar consumed may underlie the impact of sugar on mood and stress levels.

Comparison of Cranial Cruciate Ligament Rupture Incidence among Parous and Nulliparous Rottweiler Bitches: Evidence from a Lifetime Cohort Study Supporting a Paradigm of Pregnancy-Associated Protection against Subsequent Non-Reproductive Disease Outcomes.

Emerging evidence in women supports the notion that pregnancy may reset disease resistance, thereby providing protection against subsequent adverse health outcomes, but this hypothesis has not been adequately explored in domestic dogs. Cranial cruciate ligament (CCL) rupture is a degenerative orthopedic disease that frequently affects pet dogs, and its risk has been associated with disruption of the reproductive hormone axis. Our research team is conducting a lifetime cohort study of purebred Rottweilers in North America that have lived 30% longer than breed-average. Detailed medical and reproductive histories of 33 nulliparous and 32 parous Rottweilers were generated from questionnaires and review of medical records. Interviews with owners of bitches in the nulliparous group served to limit selection bias, confirming that in no instance was the reason for nulliparity based upon the owner's suspicion that a bitch had a heightened risk for CCL rupture. The risk of CCL rupture associated with parity and other exposure variables was estimated using multivariate logistic regression. Overall, CCL rupture was diagnosed in 17 of 65 (26%) bitches. Median age at first litter and CCL rupture were 3.6 and 6.5 years, respectively. Compared to nulliparous, parous bitches had a significant 94% reduction in CCL rupture risk adjusted for duration of ovary exposure, overweight body condition, dietary pattern, habitual physical activity, and work/sport activity [ORadjusted (95% CI) = 0.06 (0.01-0.46); (p = 0.006)]. The observed parity-associated CCL rupture risk reduction remained robust in sensitivity analysis excluding six nulliparous bitches for which decision not to breed was based on diagnosis of hip or elbow dysplasia, conditions which may be genetically linked to CCL rupture [ORadjusted (95% CI) = 0.08 (0.01-0.58); (p = 0.01)]. This work sets the stage for replication studies in other canine populations that should begin to explore the mechanistic basis for parity-associated CCL rupture risk reduction and to pursue other non-reproductive health outcomes in bitches whose incidence or severity may be parity-sensitive.

Causal relationships between gut microbiota and depression/anxiety disorders: A 2-sample Mendelian randomization study.

Evidence shows that the composition of the gut microbiota (GM) is associated with depression and anxiety disorders. However, the causal relationship between them remains controversial. To investigate the potential causal relationship between the GM and depression/anxiety disorders and to identify specific bacterial taxa, we conducted a 2-sample Mendelian randomization (MR) analysis on the gut microbiome implicated in depression and anxiety disorders. We incorporated summary data from genome-wide association studies (GWAS) of the microbiome derived from 7738 individuals in the Dutch Microbiome Project and 18,340 individuals in the MiBioGen consortium as our exposure variable. Concurrently, the GWAS of depression and anxiety disorders was employed as our outcome variable. The principal estimates were procured using the inverse-variance weighted test complemented by 4 robust methods: MR Egger, weighted median, simple mode, and weighted mode. In addition, we performed comprehensive sensitivity and directionality analyses. The results showed that 5 bacterial taxa were positively correlated with depression, 6 were negatively correlated; 5 were positively correlated with anxiety disorders, and 11 were negatively correlated. This study provides new insights into the connection between the GM and the pathogenesis of depression and anxiety disorders and offers new perspectives for the diagnosis and treatment of these disorders.