Prevalence and Risk Factors for Intensive Care Unit Delirium After Traumatic Brain Injury: A Retrospective Cohort Study.

BACKGROUND: Delirium remains understudied after traumatic brain injury (TBI). We sought to identify independent predictors of delirium among intensive care unit (ICU) patients with TBI. METHODS: This single-center retrospective cohort study evaluated adult patients with TBI requiring ICU admission. Outcomes included delirium days within the first 14 days, as assessed by the Confusion Assessment Method-ICU (CAM-ICU). Models were adjusted for age, sex, insurance, Marshall head computed tomography classification, presence of subarachnoid hemorrhage (SAH), Injury Severity Score (ISS), need for cardiopulmonary resuscitation, maximum admission Glasgow Coma motor score, glucose level, hemoglobin level, and pupil reactivity. RESULTS: Delirium prevalence was 60%, with a median duration of 4 days (interquartile range: 2-8) among ICU patients with TBI (n = 2,664). Older age, higher ISS, maximum motor score < 6, Marshall class II-IV, and SAH were associated with risk of increased delirium duration (all p < 0.001). CONCLUSIONS: In this large cohort, ICU delirium after TBI affected three of five patients for a median duration of 4 days. Age, general injury severity, motor score, and features of intracranial hemorrhage were predictive of more TBI-associated delirium days. Given the high prevalence of ICU delirium after TBI and its impact on hospitalization, further work is needed to understand the impact of delirium and TBI on outcomes and to determine whether delirium risk can be minimized.

Development and Evaluation of Brief Web-Based Education for Primary Care Providers to Address Inequities in Lung Cancer Screening and Smoking Cessation Treatment.

Annual lung cancer screening (LCS) is recommended for individuals at high risk for lung cancer. However, primary care provider-initiated discussions about LCS and referrals for screening are low overall, particularly among Black or African Americans and other minoritized racial and ethnic groups. Disparities also exist in receiving provider advice to quit smoking. Effective methods are needed to improve provider knowledge about LCS and tobacco-related disparities, and to provide resources to achieve equity in LCS rates. We report the feasibility and impact of pairing a self-directed Lung Cancer Health Disparities (HD) Web-based course with the National Training Network Lung Cancer Screening (LuCa) course on primary care providers' knowledge about LCS and the health disparities associated with LCS. In a quasi-experimental study, primary care providers (N = 91) recruited from the MedStar Health System were assigned to complete the LuCa course only vs. the LuCa + HD courses. We measured pre-post-LCS-related knowledge and opinions about the courses. The majority (60.4%) of providers were resident physicians. There was no significant difference between groups on post-test knowledge (p > 0.05). However, within groups, there was an improvement in knowledge from pre- to post-test (LuCa only (p = 0.03); LuCa + HD (p < 0.001)). The majority of providers (81%) indicated they planned to improve their screening and preventive practices after having reviewed the educational modules. These findings provide preliminary evidence that this e-learning course can be used to educate providers on LCS, smoking cessation, and related disparities impacting patients.

Improved motivation and readiness to quit shortly after lung cancer screening: Evidence for a teachable moment.

BACKGROUND: For patients at high risk for lung cancer, screening using low-dose computed tomography (lung cancer screening [LCS]) is recommended. The purpose of this study was to examine whether screening may serve as a teachable moment for smoking-related outcomes. METHODS: In a smoking-cessation trial, participants (N = 843) completed 2 phone interviews before randomization: before LCS (T0) and after LCS (T1). By using logistic and linear regression, the authors examined teachable moment variables (perceived risk, lung cancer worry) and outcomes (readiness, motivation, and cigarettes per day [CPD]). RESULTS: Participants were a mean ± SD age of 63.7 ± 5.9 years, had 47.8 ± 7.1 pack-years of smoking, 35.2% had a high school diploma or General Educational Development (high school equivalency) degree or less, and 42.3% were undergoing their first scan. Between T0 and T1, 25.7% of participants increased readiness to quit, 9.6% decreased readiness, and 64.7% reported no change (P < .001). Motivation to quit increased (P < .05) and CPD decreased between assessments (P < .001), but only 1.3% self-reported quitting. Compared with individuals who reported no lung cancer worry/little worry, extreme worry was associated with readiness to quit in the next 30 days (odds ratio, 1.8; 95% CI, 1.1-3.0) and with higher motivation (b = 0.83; P < .001) at T1. Individuals undergoing a baseline (vs annual) scan were more ready to quit in the next 30 days (odds ratio, 1.8; 95% CI, 1.3-2.5). CONCLUSIONS: During the brief window between registering for LCS and receiving the results, the authors observed that very few participants quit smoking, but a significant proportion improved on readiness and motivation to quit, particularly among individuals who were undergoing their first scan and those who were extremely worried about lung cancer. These results indicate that providing evidence-based tobacco treatment can build upon this teachable moment.

Management and Challenges of Severe Traumatic Brain Injury.

Traumatic brain injury (TBI) is the leading cause of death and disability in trauma patients, and can be classified into mild, moderate, and severe by the Glasgow coma scale (GCS). Prehospital, initial emergency department, and subsequent intensive care unit (ICU) management of severe TBI should focus on avoiding secondary brain injury from hypotension and hypoxia, with appropriate reversal of anticoagulation and surgical evacuation of mass lesions as indicated. Utilizing principles based on the Monro-Kellie doctrine and cerebral perfusion pressure (CPP), a surrogate for cerebral blood flow (CBF) should be maintained by optimizing mean arterial pressure (MAP), through fluids and vasopressors, and/or decreasing intracranial pressure (ICP), through bedside maneuvers, sedation, hyperosmolar therapy, cerebrospinal fluid (CSF) drainage, and, in refractory cases, barbiturate coma or decompressive craniectomy (DC). While controversial, direct ICP monitoring, in conjunction with clinical examination and imaging as indicated, should help guide severe TBI therapy, although new modalities, such as brain tissue oxygen (PbtO2) monitoring, show great promise in providing strategies to optimize CBF. Optimization of the acute care of severe TBI should include recognition and treatment of paroxysmal sympathetic hyperactivity (PSH), early seizure prophylaxis, venous thromboembolism (VTE) prophylaxis, and nutrition optimization. Despite this, severe TBI remains a devastating injury and palliative care principles should be applied early. To better affect the challenging long-term outcomes of severe TBI, more and continued high quality research is required.

A Scoping Review of Personalized, Interactive, Web-Based Clinical Decision Tools Available for Breast Cancer Prevention and Screening in the United States.

Introduction. Personalized web-based clinical decision tools for breast cancer prevention and screening could address knowledge gaps, enhance patient autonomy in shared decision-making, and promote equitable care. The purpose of this review was to present evidence on the availability, usability, feasibility, acceptability, quality, and uptake of breast cancer prevention and screening tools to support their integration into clinical care. Methods. We used the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews Checklist to conduct this review. We searched 6 databases to identify literature on the development, validation, usability, feasibility, acceptability testing, and uptake of the tools into practice settings. Quality assessment for each tool was conducted using the International Patient Decision Aid Standard instrument, with quality scores ranging from 0 to 63 (lowest-highest). Results. We identified 10 tools for breast cancer prevention and 9 tools for screening. The tools included individual (e.g., age), clinical (e.g., genomic risk factors), and health behavior (e.g., alcohol use) characteristics. Fourteen tools included race/ethnicity, but no tool incorporated contextual factors (e.g., insurance, access) associated with breast cancer. All tools were internally or externally validated. Six tools had undergone usability testing in samples including White (median, 71%; range, 9%-96%), insured (99%; 97%-100%) women, with college education or higher (60%; 27%-100%). All of the tools were developed and tested in academic settings. Seven (37%) tools showed potential evidence of uptake in clinical practice. The tools had an average quality assessment score of 21 (range, 9-39). Conclusions. There is limited evidence on testing and uptake of breast cancer prevention and screening tools in diverse clinical settings. The development, testing, and integration of tools in academic and nonacademic settings could potentially improve uptake and equitable access to these tools. Highlights: There were 19 personalized, interactive, Web-based decision tools for breast cancer prevention and screening.Breast cancer outcomes were personalized based on individual clinical characteristics (e.g., age, medical history), genomic risk factors (e.g., BRCA1/2), race and ethnicity, and health behaviors (e.g., smoking). The tools did not include contextual factors (e.g., insurance status, access to screening facilities) that could potentially contribute to breast cancer outcomes.Validation, usability, acceptability, and feasibility testing were conducted mostly among White and/or insured patients with some college education (or higher) in academic settings. There was limited evidence on testing and uptake of the tools in nonacademic clinical settings.

A scoping review of web-based, interactive, personalized decision-making tools available to support breast cancer treatment and survivorship care.

PURPOSE: We reviewed existing personalized, web-based, interactive decision-making tools available to guide breast cancer treatment and survivorship care decisions in clinical settings. METHODS: The study was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). We searched PubMed and related databases for interactive web-based decision-making tools developed to support breast cancer treatment and survivorship care from 2013 to 2023. Information on each tool's purpose, target population, data sources, individual and contextual characteristics, outcomes, validation, and usability testing were extracted. We completed a quality assessment for each tool using the International Patient Decision Aid Standard (IPDAS) instrument. RESULTS: We found 54 tools providing personalized breast cancer outcomes (e.g., recurrence) and treatment recommendations (e.g., chemotherapy) based on individual clinical (e.g., stage), genomic (e.g., 21-gene-recurrence score), behavioral (e.g., smoking), and contextual (e.g., insurance) characteristics. Forty-five tools were validated, and nine had undergone usability testing. However, validation and usability testing included mostly White, educated, and/or insured individuals. The average quality assessment score of the tools was 16 (range: 6-46; potential maximum: 63). CONCLUSIONS: There was wide variation in the characteristics, quality, validity, and usability of the tools. Future studies should consider diverse populations for tool development and testing. IMPLICATIONS FOR CANCER SURVIVORS: There are tools available to support personalized breast cancer treatment and survivorship care decisions in clinical settings. It is important for both cancer survivors and physicians to carefully consider the quality, validity, and usability of these tools before using them to guide care decisions.

Dynamic predictors of in-hospital and 3-year mortality after traumatic brain injury: A retrospective cohort study.

BACKGROUND: Mortality risks after Traumatic Brain Injury (TBI) are understudied in critical illness. We sought to identify risks of mortality in critically ill patients with TBI using time-varying covariates. METHODS: This single-center, six-year (2006-2012), retrospective cohort study measured demographics, injury characteristics, and daily data of acute TBI patients in the Intensive Care Unit (ICU). Time-varying Cox proportional hazards models assessed in-hospital and 3-year mortality. RESULTS: Post-TBI ICU patients (n = 2664) experienced 20% in-hospital mortality (n = 529) and 27% (n = 706) 3-year mortality. Glasgow Coma Scale motor subscore (hazard ratio (HR) 0.58, p < 0.001), pupil reactivity (HR 3.17, p < 0.001), minimum glucose (HR 1.44, p < 0.001), mSOFA score (HR 1.81, p < 0.001), coma (HR 2.26, p < 0.001), and benzodiazepines (HR 1.38, p < 0.001) were associated with in-hospital mortality. At three years, public insurance (HR 1.78, p = 0.011) and discharge disposition (HR 4.48, p < 0.001) were associated with death. CONCLUSIONS: Time-varying characteristics influenced in-hospital mortality post-TBI. Socioeconomic factors primarily affect three-year mortality.

Engaging Patients in Smoking Cessation Treatment within the Lung Cancer Screening Setting: Lessons Learned from an NCI SCALE Trial.

Offering smoking cessation treatment at lung cancer screening (LCS) will maximize mortality reduction associated with screening, but predictors of treatment engagement are not well understood. We examined participant characteristics of engagement in an NCI SCALE cessation trial. Eligible LCS patients (N = 818) were randomized to the Intensive arm (8 phone counseling sessions +8 weeks of nicotine replacement therapy (NRT)) vs. Minimal arm (3 sessions + 2 weeks of NRT). Engagement was measured by number of sessions completed (none, some, or all) and NRT mailed (none vs. any) in each arm. In the Intensive arm, those with ≥some college (OR = 2.1, 95% CI = 1.1, 4.0) and undergoing an annual scan (OR = 2.1, 95% CI = 1.1, 4.2) engaged in some counseling vs. none. Individuals with higher nicotine dependence were more likely (OR = 2.8, 95% CI = 1.3, 6.2) to request NRT. In the Minimal arm, those with higher education (OR = 2.1, 95% CI = 1.1, 3.9) and undergoing an annual scan (OR = 2.0, 95% CI = 1.04, 3.8) completed some sessions vs. none. Requesting NRT was associated with more pack-years (OR = 1.9, 95% CI = 1.1, 3.5). Regardless of treatment intensity, additional strategies are needed to engage those with lower education, less intensive smoking histories, and undergoing a first scan. These efforts will be important given the broader 2021 LCS guidelines.

Cost-Effectiveness of a Telephone-Based Smoking Cessation Randomized Trial in the Lung Cancer Screening Setting.

BACKGROUND: There are limited data on the cost-effectiveness of smoking cessation interventions in lung cancer screening settings. We conducted an economic analysis embedded in a national randomized trial of 2 telephone counseling cessation interventions. METHODS: We used a societal perspective to compare the short-term cost per 6-month bio-verified quit and long-term cost-effectiveness of the interventions. Trial data were used to micro-cost intervention delivery, and the data were extended to a lifetime horizon using an established Cancer Intervention Surveillance and Modeling Network lung cancer model. We modeled the impact of screening accompanied by 8 weeks vs 3 weeks of telephone counseling (plus nicotine replacement) vs screening alone based on 2021 screening eligibility. Lifetime downstream costs (2021 dollars) and effects (life-years gained, quality-adjusted life-years [QALYs]) saved were discounted at 3%. Sensitivity analyses tested the effects of varying quit rates and costs; all analyses assumed nonrelapse after quitting. RESULTS: The costs for delivery of the 8-week vs 3-week protocol were $380.23 vs $144.93 per person, and quit rates were 7.14% vs 5.96%, respectively. The least costly strategy was a 3-week counseling approach. An 8-week (vs 3-week) counseling approach increased costs but gained QALYs for an incremental cost-effectiveness ratio of $4029 per QALY. Screening alone cost more and saved fewer QALYs than either counseling strategy. Conclusions were robust in sensitivity analyses. CONCLUSIONS: Telephone-based cessation interventions with nicotine replacement are considered cost-effective in the lung screening setting. Integrating smoking cessation interventions with lung screening programs has the potential to maximize long-term health benefits at reasonable costs.

A Randomized Trial of Telephone-Based Smoking Cessation Treatment in the Lung Cancer Screening Setting.

BACKGROUND: Lung cancer mortality is reduced via low-dose computed tomography screening and treatment of early-stage disease. Evidence-based smoking cessation treatment in the lung screening setting can further reduce mortality. We report the results of a cessation trial from the National Cancer Institute's Smoking Cessation at Lung Examination collaboration. METHODS: Eligible patients (n = 818) aged 50-80 years were randomly assigned (May 2017-January 2021) to the intensive vs minimal arms (8 vs 3 phone sessions plus 8 vs 2 weeks of nicotine patches, respectively). Bio-verified (primary) and self-reported 7-day abstinence rates were assessed at 3, 6, and 12 months post random assignment. Logistic regression analyses evaluated the effects of study arm. All statistical tests were 2-sided. RESULTS: Participants reported 48.0 (SD = 17.2) pack-years, and 51.6% were not ready to quit in less than 30 days. Self-reported 3-month quit rates were statistically significantly higher in the intensive vs minimal arm (14.3% vs 7.9%; odds ratio [OR] = 2.00, 95% confidence interval [CI] = 1.26 to 3.18). Bio-verified abstinence was lower but with similar relative differences between arms (9.1% vs 3.9%; OR = 2.70, 95% CI = 1.44 to 5.08). Compared with the minimal arm, the intensive arm was more effective among those with greater nicotine dependence (OR = 3.47, 95% CI = 1.55 to 7.76), normal screening results (OR = 2.58, 95% CI = 1.32 to 5.03), high engagement in counseling (OR = 3.03, 95% CI = 1.50 to 6.14), and patch use (OR = 2.81, 95% CI = 1.39 to 5.68). Abstinence rates did not differ statistically significantly between arms at 6 months (OR = 1.2, 95% CI = 0.68 to 2.11) or 12 months (OR = 1.4, 95% CI = 0.82 to 2.42). CONCLUSIONS: Delivering intensive telephone counseling and nicotine replacement with lung screening is an effective strategy to increase short-term smoking cessation. Methods to maintain short-term effects are needed. Even with modest quit rates, integrating cessation treatment into lung screening programs may have a large impact on tobacco-related mortality.

A qualitative study exploring older smokers' attitudes and motivation toward quitting during the COVID-19 pandemic.

Older individuals who smoke are at increased risk of having severe outcomes from COVID-19, due to their long-term smoking and underlying health conditions. In this qualitative study, we explored the impact of COVID-19 on attitudes toward smoking and motivation to quit. Participants (N = 30) were enrolled in a larger ongoing randomized controlled smoking cessation trial conducted in the lung cancer screening setting. From March to May 2020, we assessed quantitative and qualitative responses to participants' overall concern about COVID-19, changes in amount smoked, and motivation to reduce/quit smoking. Responses to the quantitative questions indicated that 64.3% of participants were extremely concerned with COVID-19, 20.7% reported reductions in amount smoked, and 37.9% reported increased motivation to quit. The qualitative responses, which were transcribed and coded using Consensual Qualitative Research guidelines, expanded upon these findings by providing the content of participants' concerns, which included perceived risk of contracting COVID-19, the added stressors caused by COVID-19, and a variable impact on the amount smoked and motivation to quit. Although half of participants expressed extreme concern regarding COVID-19, fewer indicated increased motivation or reduced smoking. Qualitative themes suggested that the initial two months of the pandemic prompted some smokers to reduce or quit, but it exacerbated smoking triggers for others. Understanding how the pandemic continues to affect this vulnerable group will aid in adapting methods to support their efforts to stop smoking and remain abstinent.

Predictors of attrition in a smoking cessation trial conducted in the lung cancer screening setting.

SIGNIFICANCE: Although it is a requirement that tobacco treatment is offered to cigarette smokers undergoing low-dose computed tomographic lung cancer screening (LCS), not all smokers engage in treatment. To understand the barriers to tobacco treatment in this setting, we evaluated predictors of attrition in a smoking cessation trial among individuals undergoing LCS. METHODS: Prior to LCS, 926 participants, 50-80 years old, completed the baseline (T0) phone assessment, including demographic, clinical, tobacco, and psychological characteristics. Following LCS and receipt of the results, participants completed the pre-randomization (T1) assessment. RESULTS: At the T1 assessment, 735 (79%) participants were retained and 191 (21%) dropped out. In multivariable analyses, attrition was higher among those who: smoked >1 pack per day (OR = 1.44, CI 1.01, 2.06) or had undergone their first (vs. annual) LCS scan (OR = 1.70, CI 1.20, 2.42). Attrition was lower among those with: more education (associates (OR = 0.67, CI = 0.46, 0.98) or bachelor's degree (OR = 0.56, CI 0.35, 0.91) vs. high school/GED), some (vs. none/a little) worry about lung cancer (OR = 0.60, CI 0.39, 0.92), or a screening result that was benign (OR = 0.57, CI 0.39, 0.82) or probably benign (OR = 0.38, CI 0.16, 0.90) vs. negative. CONCLUSIONS: This study illuminated several LCS-related factors that contributed to trial attrition. Increasing tobacco treatment in this setting will require targeted strategies for those who report little lung cancer worry, are undergoing their first LCS exam, and/or who have a negative LCS result. Addressing attrition and reducing barriers to tobacco treatment will increase the likelihood of cessation, thereby reducing the risk of developing lung cancer.