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IntroductionThe rise in global temperatures due to climate change has escalated the frequency and intensity of wildfires worldwide. Beyond their direct impact on physical health, these wildfires can significantly impact mental health. Conventional mental health studies predominantly rely on surveys, often constrained by limited sample sizes, high costs, and time constraints. As a result, there is an increasing interest in accessing social media data to study the effects of wildfires on mental health.MethodsIn this study, we focused on Twitter users affected by the California Tubbs Fire in 2017 to extract data signals related to emotional well-being and mental health. Our analysis aimed to investigate tweets posted during the Tubbs Fire disaster to gain deeper insights into their impact on individuals. Data were collected from October 8 to October 31, 2017, encompassing the peak activity period. Various analytical methods were employed to explore word usage, sentiment, temporal patterns of word occurrence, and emerging topics associated with the unfolding crisis.ResultsThe findings show increased user engagement on wildfire-related Tweets, particularly during nighttime and early morning, especially at the onset of wildfire incidents. Subsequent exploration of emotional categories using Linguistic Inquiry and Word Count (LIWC) revealed a substantial presence of negative emotions at 43.0%, juxtaposed with simultaneous positivity in 23.1% of tweets. This dual emotional expression suggests a nuanced and complex landscape, unveiling concerns and community support within conversations. Stress concerns were notably expressed in 36.3% of the tweets. The main discussion topics were air quality, emotional exhaustion, and criticism of the president's response to the wildfire emergency.DiscussionSocial media data, particularly the data collected from Twitter during wildfires, provides an opportunity to evaluate the psychological impact on affected communities immediately. This data can be used by public health authorities to launch targeted media campaigns in areas and hours where users are more active. Such campaigns can raise awareness about mental health during disasters and connect individuals with relevant resources. The effectiveness of these campaigns can be enhanced by tailoring outreach efforts based on prevalent issues highlighted by users. This ensures that individuals receive prompt support and mitigates the psychological impacts of wildfire disasters.

Deployment of clinical testing on a massive scale was an essential control measure for curtailing the burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and the magnitude of the COVID-19 (coronavirus disease 2019) pandemic during its waves. As the pandemic progressed, new preventive and surveillance mechanisms emerged. Implementation of vaccine programs, wastewater (WW) surveillance, and at-home COVID-19 antigen tests reduced the demand for mass SARS-CoV-2 testing. Unfortunately, reductions in testing and test reporting rates also reduced the availability of public health data to support decision-making. This paper proposes a sequential Bayesian approach to estimate the COVID-19 test positivity rate (TPR) using SARS-CoV-2 RNA concentrations measured in WW through an adaptive scheme incorporating changes in virus dynamics. The proposed modeling framework was applied to WW surveillance data from two WW treatment plants in California; the City of Davis and the University of California, Davis campus. TPR estimates are used to compute thresholds for WW data using the Centers for Disease Control and Prevention thresholds for low (10% TPR) transmission. The effective reproductive number estimates are calculated using TPR estimates from the WW data. This approach provides insights into the dynamics of the virus evolution and an analytical framework that combines different data sources to continue monitoring COVID-19 trends. These results can provide public health guidance to reduce the burden of future outbreaks as new variants continue to emerge. IMPORTANCE We propose a statistical model to correlate WW with TPR to monitor COVID-19 trends and to help overcome the limitations of relying only on clinical case detection. We pose an adaptive scheme to model the nonautonomous nature of the prolonged COVID-19 pandemic. The TPR is modeled through a Bayesian sequential approach with a beta regression model using SARS-CoV-2 RNA concentrations measured in WW as a covariable. The resulting model allows us to compute TPR based on WW measurements and incorporates changes in viral transmission dynamics through an adaptive scheme.

Wastewater-based epidemiology (WBE) has been deployed broadly as an early warning tool for emerging COVID-19 outbreaks. WBE can inform targeted interventions and identify communities with high transmission, enabling quick and effective responses. As the wastewater (WW) becomes an increasingly important indicator for COVID-19 transmission, more robust methods and metrics are needed to guide public health decision-making. This research aimed to develop and implement a mathematical framework to infer incident cases of COVID-19 from SARS-CoV-2 levels measured in WW. We propose a classification scheme to assess the adequacy of model training periods based on clinical testing rates and assess the sensitivity of model predictions to training periods. A testing period is classified as adequate when the rate of change in testing is greater than the rate of change in cases. We present a Bayesian deconvolution and linear regression model to estimate COVID-19 cases from WW data. The effective reproductive number is estimated from reconstructed cases using WW. The proposed modeling framework was applied to three Northern California communities served by distinct WW treatment plants. The results showed that training periods with adequate testing are essential to provide accurate projections of COVID-19 incidence.

INTRODUCTION: Over a third of the communities (39%) in the Central Valley of California, a richly diverse and important agricultural region, are classified as disadvantaged-with inadequate access to healthcare, lower socio-economic status, and higher exposure to air and water pollution. The majority of racial and ethnic minorities are also at higher risk of COVID-19 infection, hospitalization, and death according to the Centers for Disease Control and Prevention. Healthy Central Valley Together established a wastewater-based disease surveillance (WDS) program that aims to achieve greater health equity in the region through partnership with Central Valley communities and the Sewer Coronavirus Alert Network. WDS offers a cost-effective strategy to monitor trends in SARS-CoV-2 community infection rates. METHODS: In this study, we evaluated correlations between public health and wastewater data (represented as SARS-CoV-2 target gene copies normalized by pepper mild mottle virus target gene copies) collected for three Central Valley communities over two periods of COVID-19 infection waves between October 2021 and September 2022. Public health data included clinical case counts at county and sewershed scales as well as COVID-19 hospitalization and intensive care unit admissions. Lag-adjusted hospitalization:wastewater ratios were also evaluated as a retrospective metric of disease severity and corollary to hospitalization:case ratios. RESULTS: Consistent with other studies, strong correlations were found between wastewater and public health data. However, a significant reduction in case:wastewater ratios was observed for all three communities from the first to the second wave of infections, decreasing from an average of 4.7 ± 1.4 over the first infection wave to 0.8 ± 0.4 over the second. DISCUSSION: The decline in case:wastewater ratios was likely due to reduced clinical testing availability and test seeking behavior, highlighting how WDS can fill data gaps associated with under-reporting of cases. Overall, the hospitalization:wastewater ratios remained more stable through the two waves of infections, averaging 0.5 ± 0.3 and 0.3 ± 0.4 over the first and second waves, respectively.

BackgroundEfforts to protect residents in nursing homes involve non-pharmaceutical interventions, testing, and vaccine. We sought to quantify the effect of testing and vaccine strategies on the attack rate, length of the epidemic, and hospitalization.MethodsWe developed an agent-based model to simulate the dynamics of SARS-CoV-2 transmission among resident and staff agents in a nursing home. Interactions between 172 residents and 170 staff based on data from a nursing home in Los Angeles, CA. Scenarios were simulated assuming different levels of non-pharmaceutical interventions, testing frequencies, and vaccine efficacy to reduce transmission.ResultsUnder the hypothetical scenario of widespread SARS-CoV-2 in the community, 3-day testing frequency minimized the attack rate and the time to eradicate an outbreak. Prioritization of vaccine among staff or staff and residents minimized the cumulative number of infections and hospitalization, particularly in the scenario of high probability of an introduction. Reducing the probability of a viral introduction eased the demand on testing and vaccination rate to decrease infections and hospitalizations.ConclusionsImproving frequency of testing from 7-days to 3-days minimized the number of infections and hospitalizations, despite widespread community transmission. Vaccine prioritization of staff provides the best protection strategy when the risk of viral introduction is high.

ObjectivesComorbid psychiatric illness has been associated with worse outcomes after some major surgical procedures. We hypothesized that patients with preexisting mood disorders would have worse postoperative and oncologic outcomes after pancreatic cancer resection.MethodsThis retrospective cohort study analyzed Surveillance, Epidemiology, and End Results patients with resectable pancreatic adenocarcinoma. A preexisting mood disorder was classified if a patient was diagnosed and/or treated with medication approved for depression/anxiety within 6 months before surgery.ResultsOf 1305 patients, 16% had a preexisting mood disorder. Mood disorders had no impact on hospital length of stay (12.9 vs 13.2 days, P = 0.75), 30-day complications (26% vs 22%, P = 0.31), 30-day readmissions (26% vs 21%, P = 0.1), or mortality (30 days: 3% vs 4%, P = 0.35); only an increased 90-day readmissions rate (42% vs 31%, P = 0.001) was observed. No effect on adjuvant chemotherapy receipt (62.5% vs 69.2%, P = 0.06) or survival (24 months, 43% vs 39%, P = 0.44) was observed.ConclusionsPreexisting mood disorders influenced 90-day readmissions after pancreatic resection, but not other postoperative or oncologic outcomes. These findings suggest that affected patients should be expected to have outcomes similar to patients without mood disorders.

BackgroundDrowning is a leading cause of death in children ≤5 years old. Detailed data on the epidemiology of drowning in this high-risk population can inform preventative efforts. We aimed to study trends in incidence and case fatality rates (CFR) in the USA among young children hospitalised after drowning.MethodsChildren ≤5 years old hospitalised in the USA after drowning were identified from the Kids Inpatient Database 2000-2016. Incidence and CFRs by calendar year, age, sex, race/ethnicity and hospital region were calculated. Trends over time were evaluated. Factors associated with fatal drowning were assessed.ResultsAmong 30 560 804 hospitalised children ≤5 years old, 9261 drowning cases were included. Patients were more commonly male (62.3%) and white (47.4%). Two years old had the highest incidence of hospitalisation after drowning, regardless of race/ethnicity, sex and region. Overall drowning hospitalisations decreased by 49% from 2000 to 2016 (8.38-4.25 cases per 100 000 children). The mortality rate was 11.4% (n=1060), and most occurred in children ≤3 years old (83.0%). Overall case fatality decreased between 2000 and 2016 (risk ratio (RR) 0.44, 95% CI 0.25 to 0.56). The lowest reduction in incidence and case fatality was observed among Black children (Incidence RR 0.92, 95% CI 0.75 to 1.13; case fatality RR 0.80, 95% CI 0.41 to 1.58).ConclusionsHospitalisations and CFRs for drowning among children ≤5 years old have decreased from 2000 to 2016. Two years old are at the highest risk of both fatal and non-fatal drowning. Disparities exist for Black children in both the relative reduction in drowning hospitalisation incidence and case fatality. Interventions should focus on providing equitable preventative care measures to this population.

ObjectiveCancer patients and survivors may be disproportionately affected by COVID-19. We sought to determine the effects of the pandemic on thyroid cancer survivors' health care interactions and quality of life.MethodsAn anonymous survey including questions about COVID-19 and the Patient-Reported Outcomes Measurement Information System profile (PROMIS-29, version 2.0) was hosted on the Thyroid Cancer Survivors' Association, Inc website. PROMIS scores were compared to previously published data. Factors associated with greater anxiety were evaluated with univariable and multivariable logistic regression.ResultsFrom May 6, 2020, to October 8, 2020, 413 participants consented to take the survey; 378 (92%) met the inclusion criteria: diagnosed with thyroid cancer or noninvasive follicular neoplasm with papillary-like nuclear features, located within the United States, and completed all sections of the survey. The mean age was 53 years, 89% were women, and 74% had papillary thyroid cancer. Most respondents agreed/strongly agreed (83%) that their lives were very different during the COVID-19 pandemic, as were their interactions with doctors (79%). A minority (43%) were satisfied with the information from their doctor regarding COVID-19 changes. Compared to pre-COVID-19, PROMIS scores were higher for anxiety (57.8 vs 56.5; P < .05) and lower for the ability to participate in social activities (46.2 vs 48.1; P < .01), fatigue (55.8 vs 57.9; P < .01), and sleep disturbance (54.7 vs 56.1; P < .01). After adjusting for confounders, higher anxiety was associated with younger age (P < .01) and change in treatment plan (P = .04).ConclusionDuring the COVID-19 pandemic, thyroid cancer survivors reported increased anxiety compared to a pre-COVID cohort. To deliver comprehensive care, providers must better understand patient concerns and improve communication about potential changes to treatment plans.

More than 40% of the deaths recorded in the first wave of the SARS-CoV-2 pandemic were linked to nursing homes. Not only are the residents of long-term care facilities (LTCFs) typically older and more susceptible to endemic infections, the facilities' high degree of connection to wider communities makes them especially vulnerable to local COVID-19 outbreaks. In 2008, in the wake of the SARS-CoV-1 and MERS epidemics and anticipating an influenza pandemic, we created a stochastic compartmental model to evaluate the deployment of non-pharmaceutical interventions (NPIs) in LTCFs during influenza epidemics. In that model, the most effective NPI by far was a staff schedule consisting of 5-day duty periods with onsite residence, followed by an 4-to-5 day off-duty period with a 3-day quarantine period just prior to the return to work. Unlike influenza, COVID-19 appears to have significant rates of pre-symptomatic transmission. In this study, we modified our prior modeling framework to include new parameters and a set of NPIs to identify and control the degree of pre-symptomatic transmission. We found that infections, deaths, hospitalizations, and ICU utilization were projected to be high and largely irreducible, even with rigorous application of all defined NPIs, unless pre-symptomatic carriers can be identified and isolated at high rates. We found that increasingly rigorous application of NPIs is likely to significantly decrease the peak of infections; but even with complete isolation of symptomatic persons, and a 50% reduction in silent transmission, the attack rate is projected to be nearly 95%.

SARS-CoV-2 has infected nearly 3.7 million and killed 61,722 Californians, as of May 22, 2021. Non-pharmaceutical interventions have been instrumental in mitigating the spread of the coronavirus. However, as we ease restrictions, widespread implementation of COVID-19 vaccines is essential to prevent its resurgence. In this work, we addressed the adequacy and deficiency of vaccine uptake within California and the possibility and severity of resurgence of COVID-19 as restrictions are lifted given the current vaccination rates. We implemented a real-time Bayesian data assimilation approach to provide projections of incident cases and deaths in California following the reopening of its economy on June 15, 2021. We implemented scenarios that vary vaccine uptake prior to reopening, and transmission rates and effective population sizes following the reopening. For comparison purposes, we adopted a baseline scenario using the current vaccination rates, which projects a total 11,429 cases and 429 deaths in a 15-day period after reopening. We used posterior estimates based on CA historical data to provide realistic model parameters after reopening. When the transmission rate is increased after reopening, we projected an increase in cases by 21.8% and deaths by 4.4% above the baseline after reopening. When the effective population is increased after reopening, we observed an increase in cases by 51.8% and deaths by 12.3% above baseline. A 30% reduction in vaccine uptake alone has the potential to increase cases and deaths by 35% and 21.6%, respectively. Conversely, increasing vaccine uptake by 30% could decrease cases and deaths by 26.1% and 17.9%, respectively. As California unfolds its plan to reopen its economy on June 15, 2021, it is critical that social distancing and public behavior changes continue to be promoted, particularly in communities with low vaccine uptake. The Centers for Disease Control and Prevention (CDC) recommendation to ease mask-wearing for fully vaccinated individuals despite major inequities in vaccine uptake in counties across the state highlights some of the logistical challenges that society faces as we enthusiastically phase out of this pandemic.

BackgroundAbusive head trauma (AHT) is a leading cause of morbidity and mortality among young children. We aimed to evaluate the long-term impact of AHT.MethodsUsing administrative claims from 2000-2018, children

BackgroundThe novel coronavirus pandemic has had a differential impact on communities of color across the US. The University of California hospital system serves a large population of people who are often underrepresented elsewhere. Data from hospital stays can provide much-needed localized information on risk factors for severe cases and/or death.MethodsPatient-level retrospective case series of laboratory-confirmed COVID-19 hospital admissions at five UC hospitals (N = 4730). Odds ratios of ICU admission, death, and a composite of both outcomes were calculated with univariate and multivariate logistic regression based on patient characteristics, including sex, race/ethnicity, and select comorbidities. Associations between comorbidities were quantified and visualized with a correlation network.ResultsOverall mortality rate was 7.0% (329/4,730). ICU mortality rate was 18.8% (225/1,194). The rate of the composite outcome (ICU admission and/or death) was 27.4% (1298/4730). Comorbidity-controlled odds of a composite outcome were increased for age 75-84 (OR 1.47, 95% CI 1.11-1.93) and 85-59 (OR 1.39, 95% CI 1.04-1.87) compared to 18-34 year-olds, males (OR 1.39, 95% CI 1.21-1.59) vs. females, and patients identifying as Hispanic/Latino (OR 1.35, 95% CI 1.14-1.61) or Asian (OR 1.43, 95% CI 1.23-1.82) compared to White. Patients with 5 or more comorbidities were exceedingly likely to experience a composite outcome (OR 2.74, 95% CI 2.32-3.25).ConclusionsMales, older patients, those with multiple pre-existing comorbidities, and those identifying as Hispanic/Latino or Asian experienced an increased risk of ICU admission and/or death. These results are consistent with reported risks among the Hispanic/Latino population elsewhere in the United States, and confirm multiple concerns about heightened risk among the Asian population in California.

Multiple Sclerosis (MS) is an immune-mediated disease that results in major locomotor deficits. However, recent studies have revealed that fatigue, slow processing speed, and memory impairment are the top variables impacting employment status for MS patients. These suggest that cognitive effects may have a greater impact on productivity, lifestyle, and quality of life than do disease-related motor deficits. However, these debilitating non-locomotive effects have been largely overlooked in rodent models of the disease, such as experimental autoimmune encephalomyelitis (EAE). We hypothesized that murine EAE can also be used to assess non-locomotive dysfunctions (mood, sociability, muscle strength, and balance), as well as potential biases in these dysfunctions due to sex and/or strain. We actively immunized male and female C57BL/6 (B6) and SJL mice for EAE and evaluated their performance on the Deacon's weight grip test, Kondziela's inverted screen test, Hall's rope grip test, manual von Frey test for somatic nociception, and a three-chamber social preference paradigm. We hypothesized that EAE progression is associated with changes in muscle strength, balance, pain, and sociability and that these variations are linked to sex and/or strain. Our results indicate that strain but not sex influenced differences in muscle strength and balance during EAE, and both sex and strain have an impact on mechanical nociception, regardless of EAE disease status. Furthermore, both sex and strain had complex effects on differences in sociability. In conclusion, testing these additional modalities during EAE helps to unveil other signs and symptoms that could be used to determine the efficacy of a drug or treatment in the modulation of a MS-like behavior.

BackgroundTraumatic brain injury (TBI) is the leading cause of death and disability in young children; however, the impact of mechanism on outcomes has not been fully evaluated. We hypothesized that children with TBI due to abuse would have a higher mortality than children with accidental TBI due to motor vehicle collisions (MVC).MethodsWe performed a retrospective review of the National Kids' Inpatient (KID) hospitalizations database of children

The incidence of autism spectrum disorder (ASD) has been rising, however ASD-risk biomarkers remain lacking. We previously identified the presence of maternal autoantibodies to fetal brain proteins specific to ASD, now termed maternal autoantibody-related (MAR) ASD. The current study aimed to create and validate a serological assay to identify ASD-specific maternal autoantibody patterns of reactivity against eight previously identified proteins (CRMP1, CRMP2, GDA, NSE, LDHA, LDHB, STIP1, and YBOX) that are highly expressed in developing brain, and determine the relationship of these reactivity patterns with ASD outcome severity. We used plasma from mothers of children diagnosed with ASD (n = 450) and from typically developing children (TD, n = 342) to develop an ELISA test for each of the protein antigens. We then determined patterns of reactivity a highly significant association with ASD, and discovered several patterns that were ASD-specific (18% in the training set and 10% in the validation set vs. 0% TD). The three main patterns associated with MAR ASD are CRMP1 + GDA (ASD% = 4.2 vs. TD% = 0, OR 31.04, p =

PurposePrescription drug monitoring programs (PDMPs) have been established to combat the opioid epidemic, but there is no data on their efficacy in children. We hypothesized that a statewide PDMP mandate would be associated with fewer opioid prescriptions in pediatric surgical patients.MethodsPatients

The rapid spread of the new SARS-CoV-2 virus triggered a global health crisis, disproportionately impacting people with pre-existing health conditions and particular demographic and socioeconomic characteristics. One of the main concerns of governments has been to avoid health systems becoming overwhelmed. For this reason, they have implemented a series of non-pharmaceutical measures to control the spread of the virus, with mass tests being one of the most effective controls. To date, public health officials continue to promote some of these measures, mainly due to delays in mass vaccination and the emergence of new virus strains. In this research, we studied the association between COVID-19 positivity rate and hospitalization rates at the county level in California using a mixed linear model. The analysis was performed in the three waves of confirmed COVID-19 cases registered in the state to September 2021. Our findings suggest that test positivity rate is consistently associated with hospitalization rates at the county level for all study waves. Demographic factors that seem to be related to higher hospitalization rates changed over time, as the profile of the pandemic impacted different fractions of the population in counties across California.

ObjectiveEndovascular treatment is the mainstay therapy for brain aneurysms. About 15% of patients need re-treatment within six months due to early recanalization. In this study, we investigate risk factors associated with treatment failure.MethodsThis retrospective cohort study includes endovascularly treated aneurysm cases between July 2012 and December 2015 at the University of California Davis Medical Center with pre-treatment and early post-treatment imaging. Thin cut 3D aneurysm volume rendering was used for morphologic analyses. Univariate and bivariate analyses were conducted to evaluate differences between patients and clinical factors by treatment failure.ResultsOf the 50 patients who met the inclusion criteria, 41 (82.0%) were female, with an average age of 61 years. Most aneurysms were on the anterior communicating artery (40%) or posterior communicating artery (22.0%), and 34 (68%) aneurysms were ruptured. Early treatment failure was observed in 14 (28.0%) of endovascularly treated patients. Raymond-Roy class (RRC) was significantly associated with treatment failure (p = 0.0052), with 10 out of the 14 cases (71.4%) with early recanalization having an RRC of 3. Coil packing density did not associate with aneurysm recanalization (p = 0.61).ConclusionIn our single institution series, patient characteristics, aneurysm characteristics, or coil packing density did not affect early aneurysm recanalization. RRC was the best predictor of early recanalization; however, further confirmation with additional studies are required. Although this study focused on early treatment failure, late recanalization has been shown with longer follow up. Further investigation into factors associated with late treatment failure will need further investigation. New intrasaccular devices and flow diverters will also likely play a role in reducing recurrence in the future as these treatments gain usage.

BackgroundThe optimal level of care for hemodynamically stable patients with isolated blunt hepatic, renal, or splenic injuries (solid organ injuries [SOIs]) is unknown. We sought to characterize interhospital variability in intensive care unit (ICU) admission of such patients and to determine whether greater hospital-level ICU use would be associated with improved outcomes.MethodsWe conducted a retrospective cohort study using the 2015 and 2016 National Trauma Data Bank. We included adult patients with blunt trauma with SOIs with an Abbreviated Injury Scale score of 2 to 4. We excluded patients with other significant injuries, hypotension, or another indication for ICU admission, and hospitals with less than 10 eligible patients. We categorized hospitals into quartiles based on the proportion of eligible patients admitted to an ICU. The primary outcome was a composite of organ failure (cardiac arrest, acute lung injury/acute respiratory failure, or acute kidney injury), infection (sepsis, pneumonia, or catheter-related blood stream infection), or death during hospitalization.ResultsAmong 14,312 patients at 444 facilities, 7,225 (50%), 5,050 (35%), and 3,499 (24%) had splenic, hepatic, and renal injuries, respectively. The median proportion of ICU use was 44% (interquartile range, 27-59%, range 0-95%). The composite outcome occurred in 180 patients (1.3%), with death in 76 (0.5%), organ failure in 97 (0.7%), and infection in 53 (0.4%). Relative to hospitals with the lowest ICU use (quartile 1), greater hospital-level ICU use was not associated with decreased likelihood of the composite outcome (adjusted odds ratios, 1.31; 95% confidence interval [95% CI], 0.88-1.95; 0.81; 95% CI, 0.52-1.26; and 0.94; 95% CI, 0.62-1.43 for quartiles 2-4, respectively) or its components. Unplanned ICU transfer was no more likely with lower hospital-level ICU use.ConclusionAdmission location of stable patients with isolated mild to moderate abdominal SOIs is variable across hospitals, but hospitalization at a facility with greater ICU use is not associated with substantially improved outcomes.Level of evidenceTherapeutic/care management, Level IV.

BackgroundSmoking is a risk factor for complications after lung resection. Our primary aim was to ascertain thoracic surgeons' beliefs and practices on smoking cessation before lung resection.MethodsAn anonymous survey was emailed to 846 thoracic surgeons who participate in The Society of Thoracic Surgeons General Thoracic Surgery Database.ResultsThe response rate was 23.6% (n = 200). Surgeons were divided when asked whether it is ethical to require that patients quit smoking (yes, n = 96 [48%]) and whether it is fair to have their outcomes affected by patients who do not quit (yes, n = 87 [43.5%]). Most do not require smoking cessation (n = 120 [60%]). Of those who require it, the most common required period of cessation is 2 weeks or more. Most believe that patient factors are the main barrier to quitting (n = 160 [80%]). Risk of disease progression (39% vs 17.5%, p = 0.02) and alienating patients (17.5% vs 8.8%, p = 0.04) were very important considerations of those who do not require smoking cessation versus those who do. Only 19 (9.5%) always refer to a smoking cessation program and prescribe nicotine replacement therapy and even fewer, 9 (4.5%), always refer to a program and prescribe medical therapy.ConclusionsThoracic surgeons are divided on their beliefs and practices regarding smoking cessation before lung resection. Most believe patient factors are the main barrier to quitting and have concerns about disease progression while awaiting cessation. Very few surgeons refer to a smoking cessation program and prescribe nicotine replacement therapy or medical therapy.

The recent implementation of the International Classification of Diseases, 10th Revision, Clinical Modification and Procedure Coding System (ICD-10-CM/PCS) provides a robust classification of diagnoses and procedures for hospital systems. As researchers begin using ICD-10-CM/PCS for outcomes research from administrative datasets, it is important to understand ICD-10-CM/PCS, as well as the strengths and challenges of these new classifications. In this review, we describe the development of ICD-10-CM/PCS and summarize how it applies specifically to thoracic surgery patients undergoing pulmonary lobectomy, sublobar resection (segmentectomy or wedge resection) and esophagectomy. This myriad of ICD-10-CM/PCS codes presents challenges and questions for thoracic surgery researchers and medical journal reviewers and editors when evaluating thoracic surgical outcomes research utilizing ICD-10-CM/PCS. Additional work is needed to develop consensus guidelines and uniformity for accurate and coherent research methods to utilize ICD-10-CM/PCS in future outcomes research efforts.

BackgroundDespite careful clinical examination, procurement biopsy and assessment on hypothermic machine perfusion, a significant number of potentially useable deceased donor kidneys will be discarded because they are deemed unsuitable for transplantation. Ex vivo normothermic perfusion (EVNP) may be useful as a means to further assess high-risk kidneys to determine suitability for transplantation.MethodsFrom June 2014 to October 2015, 7 kidneys (mean donor age, 54.3 years and Kidney Donor Profile Index, 79%) that were initially procured with the intention to transplant were discarded based on a combination of clinical findings, suboptimal biopsies, long cold ischemia time (CIT) and/or poor hypothermic perfusion parameters. They were subsequently placed on EVNP using oxygenated packed red blood cells and supplemental nutrition for a period of 3 hours. Continuous hemodynamic and functional parameters were assessed.ResultsAfter a mean CIT of 43.7 hours, all 7 kidneys appeared viable on EVNP with progressively increasing renal blood flow over the 3-hour period of perfusion. Five of the 7 kidneys had excellent macroscopic appearance, rapid increase in blood flow to 200 to 250 mL/min, urine output of 40 to 260 mL/h and increasing creatinine clearance.ConclusionsFavorable perfusion characteristics and immediate function after a 3-hour course of EVNP suggests that high-risk kidneys subjected to long CIT may have been considered for transplantation. The combined use of ex vivo hypothermic and normothermic perfusion may be a useful strategy to more adequately assess and preserve high-risk kidneys deemed unsuitable for transplantation. A clinical trial will be necessary to validate the usefulness of this approach.

In this study, we used emerging community engagement frameworks to describe the structure and outcomes of a large-scale, community-engaged, research-to-practice initiative, RADx-UP. Qualitative methods were used to analyze survey and meeting data from 2022 for RADx-UP projects. Most projects had diverse partners, achieved moderate levels of community engagement, and experienced positive outcomes. Challenges related to engagement readiness and partnership functioning. These findings demonstrate that community engagement is measurable and valuable. However, additional support is needed to achieve the highest engagement. (Am J Public Health. 2024;114(S5):S405–S409. https://doi.org/10.2105/AJPH.2024.307615) [ABSTRACT FROM AUTHOR]