The invisible scars: Unseen financial complications worsen every aspect of long-term health in trauma survivors.

BACKGROUND: Trauma survivors are susceptible to experiencing financial toxicity (FT). Studies have shown the negative impact of FT on chronic illness outcomes. However, there is a notable lack of data on FT in the context of trauma. We aimed to better understand prevalence, risk factors, and impact of FT on trauma long-term outcomes. METHODS: Adult trauma patients with an Injury Severity Score (ISS) ≥9 treated at Level I trauma centers were interviewed 6 months to 14 months after discharge. Financial toxicity was considered positive if patients reported any of the following due to the injury: income loss, lack of care, newly applied/qualified for governmental assistance, new financial problems, or work loss. The Impact of FT on Patient Reported Outcome Measure Index System (PROMIS) health domains was investigated. RESULTS: Of 577 total patients, 44% (254/567) suffered some form of FT. In the adjusted model, older age (odds ratio [OR], 0.4; 95% confidence interval [95% CI], 0.2-0.81) and stronger social support networks (OR, 0.44; 95% CI, 0.26-0.74) were protective against FT. In contrast, having two or more comorbidities (OR, 1.81; 95% CI, 1.01-3.28), lower education levels (OR, 1.95; 95% CI, 95%, 1.26-3.03), and injury mechanisms, including road accidents (OR, 2.69; 95% CI, 1.51-4.77) and intentional injuries (OR, 4.31; 95% CI, 1.44-12.86) were associated with higher toxicity. No significant relationship was found with ISS, sex, or single-family household. Patients with FT had worse outcomes across all domains of health. There was a negative linear relationship between the severity of FT and worse mental and physical health scores. CONCLUSION: Financial toxicity is associated with long-term outcomes. Incorporating FT risk assessment into recovery care planning may help to identify patients most in need of mitigative interventions across the trauma care continuum to improve trauma recovery. Further investigations to better understand, define, and address FT in trauma care are warranted. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level III.

Suicide among Cancer Patients: Current Knowledge and Directions for Observational Research.

Cancer is a major public health concern associated with an increased risk of psychosocial distress and suicide. The reasons for this increased risk are still being characterized. The purpose of this study is to highlight existing observational studies on cancer-related suicides in the United States and identify gaps for future research. This work helps inform clinical and policy decision-making on suicide prevention interventions and ongoing research on the detection and quantification of suicide risk among cancer patients. We identified 73 peer-reviewed studies (2010-2022) that examined the intersection of cancer and suicide using searches of PubMed and Embase. Overall, the reviewed studies showed that cancer patients have an elevated risk of suicide when compared to the general population. In general, the risk was higher among White, male, and older cancer patients, as well as among patients living in rural areas and with lower socioeconomic status. Future studies should further investigate the psychosocial aspects of receiving a diagnosis of cancer on patients' mental health as well as the impact of new treatments and their availability on suicide risk and disparities among cancer patients to better inform policies.

Critically reading machine learning literature in neurosurgery: a reader's guide and checklist for appraising prediction models.

OBJECTIVE: Machine learning (ML) has become an increasingly popular tool for use in neurosurgical research. The number of publications and interest in the field have recently seen significant expansion in both quantity and complexity. However, this also places a commensurate burden on the general neurosurgical readership to appraise this literature and decide if these algorithms can be effectively translated into practice. To this end, the authors sought to review the burgeoning neurosurgical ML literature and to develop a checklist to help readers critically review and digest this work. METHODS: The authors performed a literature search of recent ML papers in the PubMed database with the terms "neurosurgery" AND "machine learning," with additional modifiers "trauma," "cancer," "pediatric," and "spine" also used to ensure a diverse selection of relevant papers within the field. Papers were reviewed for their ML methodology, including the formulation of the clinical problem, data acquisition, data preprocessing, model development, model validation, model performance, and model deployment. RESULTS: The resulting checklist consists of 14 key questions for critically appraising ML models and development techniques; these are organized according to their timing along the standard ML workflow. In addition, the authors provide an overview of the ML development process, as well as a review of key terms, models, and concepts referenced in the literature. CONCLUSIONS: ML is poised to become an increasingly important part of neurosurgical research and clinical care. The authors hope that dissemination of education on ML techniques will help neurosurgeons to critically review new research better and more effectively integrate this technology into their practices.

First tobacco product tried among adolescents based on race/ethnicity and socioeconomic status.

In recent years, the tobacco use landscape among youth has changed greatly, underscoring a need to understand current tobacco product initiation patterns. This study aimed to examine if adolescents' first tobacco product tried differs by race/ethnicity and socioeconomic status (SES). Cross-sectional survey data were collected from 6 Connecticut high schools in Spring 2019 (N = 4875). The analytic sample comprised ever users of tobacco products who reported on the first tobacco product they tried (N = 2530; 53.6% female). Of ever tobacco product users, 64.6% reported that their first tobacco product tried was an e-cigarette, 24.4% reported blunts, 6.5% reported another tobacco product, and 4.5% reported cigarettes. A multinomial logistic regression model examined race/ethnicity and SES as predictors of the first tobacco product tried with cigarettes as the reference group. Compared to Non-Hispanic (NH) White students, NH Black students (OR = 0.38, 95%CI = 0.17-0.82), Hispanic students (OR = 0.44, 95%CI = 0.27-0.71), and students of other NH races (OR = 0.30, 95%CI = 0.18-0.52) were less likely to report initiating tobacco product use with e-cigarettes. Additionally, compared to NH White students, NH Black students were more likely to report using blunts as their first tobacco product (OR = 3.01, 95%CI = 1.38-6.56). Compared to low SES, middle SES (OR = 1.62, 95%CI = 1.04-2.52) was associated with greater odds of reporting e-cigarettes as the first tobacco product. These findings suggest that youth of different backgrounds initiate tobacco use with different tobacco products and tailored prevention strategies are needed.

Recent findings in the pharmacology of inhaled nicotine: Preclinical and clinical in vivo studies.

INTRODUCTION: The rise of vaping in adolescents, the recent entrance of new inhaled nicotine products such as iQOS on the market and e-cigarette or vaping product use-associated lung injury cases has created concern for the use of inhaled non-combustible nicotine products. This narrative review discusses recent experimental in vivo studies that utilize human, rat and mouse models to understand the pharmacological impact of nicotine from non-combustible products. METHODS: The search engine PubMed was utilized with the following search terms: inhaled nicotine, nicotine e-cigarette, heated tobacco products, iQOS, electronic cigarette, nicotine inhaler, nicotine vaping. This review highlights recent primary in vivo studies of inhaled nicotine administration experimental paradigms that occurred in laboratory settings using human and rodent (rats and mice) models that have been published from January 2017-December 2019. RESULTS: The pharmacokinetics of nicotine via e-cigarettes is influenced by the PG/VG and flavor constituents in e-liquids, the presence of nicotine salts in e-liquids, puff topography of nicotine and tobacco product users and the power of the e-cigarette device. The pharmacodynamic impact of inhaled nicotine has cardiovascular, pulmonary and central nervous system implications. CONCLUSION: The articles reviewed here highlight the importance of both animal and human models to fully understand the impact of inhaled nicotine pharmacology There is a need for more rodent pharmacokinetic inhaled nicotine studies to understand the influences of factors such as flavor and nicotine salts. Additionally, consensus on nicotine measurement in both human and rodent studies is greatly needed.