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Background: Previous studies showed that lifestyle behaviors (cigarette smoking, alcohol, coffee) are inversely associated with Parkinson’s disease (PD). The prodromal phase of PD raises the possibility that these associations may be explained by reverse causation. Objective: To examine associations of lifestyle behaviors with PD using two-sample Mendelian randomisation (MR) and the potential for survival and incidence-prevalence biases. Methods: We used summary statistics from publicly available studies to estimate the association of genetic polymorphisms with lifestyle behaviors, and from Courage-PD (7,369 cases, 7,018 controls; European ancestry) to estimate the association of these variants with PD. We used the inverse-variance weighted method to compute odds ratios (ORIVW) of PD and 95%confidence intervals (CI). Significance was determined using a Bonferroni-corrected significance threshold (p = 0.017). Results: We found a significant inverse association between smoking initiation and PD (ORIVW per 1-SD increase in the prevalence of ever smoking = 0.74, 95%CI = 0.60–0.93, p = 0.009) without significant directional pleiotropy. Associations in participants ≤67 years old and cases with disease duration ≤7 years were of a similar size. No significant associations were observed for alcohol and coffee drinking. In reverse MR, genetic liability toward PD was not associated with smoking or coffee drinking but was positively associated with alcohol drinking. Conclusion: Our findings are in favor of an inverse association between smoking and PD that is not explained by reverse causation, confounding, and survival or incidence-prevalence biases. Genetic liability toward PD was positively associated with alcohol drinking. Conclusions on the association of alcohol and coffee drinking with PD are hampered by insufficient statistical power.

Abstract Glioblastomas (GBM) are routinely treated with ionizing radiation (IR) but inevitably recur and develop therapy resistance. During treatment, the tissue surrounding tumors is also irradiated. IR potently induces senescence, and senescent stromal cells can promote the growth of neighboring tumor cells by secreting factors that create a senescence-associated secretory phenotype (SASP). Here, we carried out transcriptomic and tumorigenicity analyses in irradiated mouse brains to elucidate how radiotherapy-induced senescence of non-neoplastic brain cells promotes tumor growth. Following cranial irradiation, widespread senescence in the brain occurred, with the astrocytic population being particularly susceptible. Irradiated brains showed an altered transcriptomic profile characterized by upregulation of CDKN1A (p21), a key enforcer of senescence, and several SASP factors, including HGF, the ligand of the receptor tyrosine kinase (RTK) Met. Preirradiation of mouse brains increased Met-driven growth and invasiveness of orthotopically implanted glioma cells. Importantly, irradiated p21−/− mouse brains did not exhibit senescence and consequently failed to promote tumor growth. Senescent astrocytes secreted HGF to activate Met in glioma cells and to promote their migration and invasion in vitro, which could be blocked by HGF-neutralizing antibodies or the Met inhibitor crizotinib. Crizotinib also slowed the growth of glioma cells implanted in preirradiated brains. Treatment with the senolytic drug ABT-263 (navitoclax) selectively killed senescent astrocytes in vivo, significantly attenuating growth of glioma cells implanted in preirradiated brains. These results indicate that SASP factors in the irradiated tumor microenvironment drive GBM growth via RTK activation, underscoring the potential utility of adjuvant senolytic therapy for preventing GBM recurrence after radiotherapy. Significance: This study uncovers mechanisms by which radiotherapy can promote GBM recurrence by inducing senescence in non-neoplastic brain cells, suggesting that senolytic therapy can blunt recurrent GBM growth and aggressiveness.

AbstractBackgroundAutomated wide complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) may be accomplished using novel calculations that quantify the extent of mean electrical vector changes between the WCT and baseline electrocardiogram (ECG). At present, it is unknown whether quantifying mean electrical vector changes within three orthogonal vectorcardiogram (VCG) leads (X, Y, and Z leads) can improve automated VT and SWCT classification.MethodsA derivation cohort of paired WCT and baseline ECGs was used to derive five logistic regression models: (i) one novel WCT differentiation model (i.e., VCG Model), (ii) three previously developed WCT differentiation models (i.e., WCT Formula, VT Prediction Model, and WCT Formula II), and (iii) one “all‐inclusive” model (i.e., Hybrid Model). A separate validation cohort of paired WCT and baseline ECGs was used to trial and compare each model's performance.ResultsThe VCG Model, composed of WCT QRS duration, baseline QRS duration, absolute change in QRS duration, X‐lead QRS amplitude change, Y‐lead QRS amplitude change, and Z‐lead QRS amplitude change, demonstrated effective WCT differentiation (area under the curve [AUC] 0.94) for the derivation cohort. For the validation cohort, the diagnostic performance of the VCG Model (AUC 0.94) was similar to that achieved by the WCT Formula (AUC 0.95), VT Prediction Model (AUC 0.91), WCT Formula II (AUC 0.94), and Hybrid Model (AUC 0.95).ConclusionCustom calculations derived from mathematically synthesized VCG signals may be used to formulate an effective means to differentiate WCTs automatically.

IMPORTANCE: Even with its proclivity for older age, coronavirus disease 2019 has been shown to affect all age groups. However, there remains a lack of research focused primarily on the young adult population. OBJECTIVES: To describe the epidemiology and outcomes of coronavirus disease 2019 and identify the risk factors associated with critical illness and mortality in hospitalized young adults. DESIGN, SETTINGS, AND PARTICIPANTS: A retrospective cohort study of the Society of Critical Care Medicine’s Viral Infection and Respiratory Illness Universal Study registry. Patients 18–40 years old, hospitalized from coronavirus disease 2019 from March 2020 to April 2021, were included in the analysis. MAIN OUTCOMES AND MEASURES: Critical illness was defined as a composite of mortality and 21 predefined interventions and complications. Multivariable logistic regression was used to assess associations with critical illness and mortality. RESULTS: Data from 4,005 patients (152 centers, 19 countries, 18.6% non-U.S. patients) were analyzed. The median age was 32 years (interquartile range, 27–37 yr); 51% were female, 29.4% Hispanic, and 42.9% had obesity. Most patients (63.2%) had comorbidities, the most common being hypertension (14.5%) and diabetes (13.7%). Hospital and ICU mortality were 3.2% (129/4,005) and 8.3% (109/1,313), respectively. Critical illness occurred in 25% (n = 996), and 34.3% (n = 1,376) were admitted to the ICU. Older age (p = 0.03), male sex (adjusted odds ratio, 1.83 [95% CI, 1.2–2.6]), and obesity (adjusted odds ratio, 1.6 [95% CI, 1.1–2.4]) were associated with hospital mortality. In addition to the above factors, the presence of any comorbidity was associated with critical illness from coronavirus disease 2019. Multiple sensitivity analyses, including analysis with U.S. patients only and patients admitted to high-volume sites, showed similar risk factors. CONCLUSIONS: Among hospitalized young adults, obese males with comorbidities are at higher risk of developing critical illness or dying from coronavirus disease 2019.

Objectives: Multicenter data on the characteristics and outcomes of children hospitalized with coronavirus disease 2019 are limited. Our objective was to describe the characteristics, ICU admissions, and outcomes among children hospitalized with coronavirus disease 2019 using Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study: Coronavirus Disease 2019 registry. Design: Retrospective study. Setting: Society of Critical Care Medicine Viral Infection and Respiratory Illness Universal Study (Coronavirus Disease 2019) registry. Patients: Children (< 18 yr) hospitalized with coronavirus disease 2019 at participating hospitals from February 2020 to January 2021. Interventions: None. Measurements and Main Results: The primary outcome was ICU admission. Secondary outcomes included hospital and ICU duration of stay and ICU, hospital, and 28-day mortality. A total of 874 children with coronavirus disease 2019 were reported to Viral Infection and Respiratory Illness Universal Study registry from 51 participating centers, majority in the United States. Median age was 8 years (interquartile range, 1.25–14 yr) with a male:female ratio of 1:2. A majority were non-Hispanic (492/874; 62.9%). Median body mass index (n = 817) was 19.4 kg/m2 (16–25.8 kg/m2), with 110 (13.4%) overweight and 300 (36.6%) obese. A majority (67%) presented with fever, and 43.2% had comorbidities. A total of 238 of 838 (28.2%) met the Centers for Disease Control and Prevention criteria for multisystem inflammatory syndrome in children, and 404 of 874 (46.2%) were admitted to the ICU. In multivariate logistic regression, age, fever, multisystem inflammatory syndrome in children, and pre-existing seizure disorder were independently associated with a greater odds of ICU admission. Hospital mortality was 16 of 874 (1.8%). Median (interquartile range) duration of ICU (n = 379) and hospital (n = 857) stay were 3.9 days (2–7.7 d) and 4 days (1.9–7.5 d), respectively. For patients with 28-day data, survival was 679 of 787, 86.3% with 13.4% lost to follow-up, and 0.3% deceased. Conclusions: In this observational, multicenter registry of children with coronavirus disease 2019, ICU admission was common. Older age, fever, multisystem inflammatory syndrome in children, and seizure disorder were independently associated with ICU admission, and mortality was lower among children than mortality reported in adults.

12086 Background: Patients with bone metastases may experience pain and decreased quality of life. Standard of care therapies such as radiation therapy could take weeks for pain relief and carry a risk of radiation induced fracture. Minimally invasive percutaneous radiofrequency ablation (RFA) have been shown in small observational studies to be an alternative treatment for bone metastases. We report the results of the OPuS One trial evaluating RFA for the palliative treatment of patients with painful bone metastases. Methods: OPuS One (NCT03249584) was a multicenter prospective trial. 218 subjects with painful bone metastases (≥ 4/10 worst pain scores, Brief Pain Inventory [BPI], at target treated site) were enrolled from 15 sites. RFA was performed under image guidance at one or two locations. Vertebral augmentation was followed based on physician’s discretion. Subjects’ pain (BPI) and quality of life (EQ-5D) scores were calculated in subjects at three days, one week, and one, three, six, and 12 months post RFA. Rate of complete (0 pain score at treated site with no concomitant analgesic increase) and partial responders (≥ 2 pain score reduction without analgesic increase or analgesic reduction of ≥ 25% from baseline) were calculated. Device-, procedure-, and/or therapy-related adverse events (AEs) were collected. Results: 206 subjects, 113 (55%) female and 93 (45%) males (mean age was 63.7 years) were treated with RFA. Most common primary cancers were breast (23%), lung (23%), and kidney (10%). 184 (89%) subjects were treated for metastatic lesions involving the thoracolumbar spine and 22 (11%) subjects were treated for iliac crest, periacetabulum, sacrum or mixed vertebral and pelvic location. 99% (262/264) of RFA procedures were technically successful and 97% were followed by vertebral augmentation. Subjects reported significant improvement in worst pain from baseline at 7.8 to 5.5, 4.7, 3.6, 3.2, 2.4, and 2.6 at three days, one week and one, three, six, and 12 months post RFA, respectively (p < 0.0001 for all visits). Significant improvements were also seen in average pain (p < 0.0001 for all visits), pain interference (p < 0.0001 for all visits), and quality of life scores (p < 0.0001 for all visits). Overall response rates were 53%, 58%, 61%, 63%, 70%, and 75% at three days, one week, one month, three months, six months, and twelve months post RFA, respectively. Six AEs were reported with three as serious: intra-abdominal fluid collection, pneumonia and respiratory failure. 82 deaths were reported during the study, none were related to the device, therapy, and/or procedure. No skeletal related events were reported. Conclusions: In a large prospective multicenter trial, OPuS One, RFA provided rapid, significant, and durable improvements in pain relief and quality of life up to 12 months. Clinical trial information: NCT03249584.

6594 Background: Patient reported financial hardship (FH) in cancer care is a growing challenge for patients, their caregivers and healthcare providers. As treatment costs escalate, it is imperative to develop effective strategies to proactively recognize and mitigate FH within oncology practice. Using automated processes to screen and refer patients to appropriate resources is a potential option. At Mayo Clinic, screening for FH involves using a single financial strain question ‘ How hard is it for you to pay for the very basics like food, housing, medical care, and heating?’ completed by all cancer patients annually as part of the Social Determinants of Health (SDOH) assessment. In this study, we describe the prevalence and predictors for FH (denoted by the answer ‘hard and very hard’) in our patient population. Methods: Patients receiving cancer care at the three Mayo Clinic sites (Minnesota, Arizona, and Florida) who completed the FH screen at least once were included in this study. Demographics (age, gender, race/ ethnicity, insurance, employment status, marital status, and zip code) and disease state data for included patients was extracted from the EMR and Mayo Clinic Cancer Registry. Disease state was categorized by type of cancer (hematological or solid malignancy) and cancer stage. Zip code was used to derive median income, rural/urban residence and distance from the cancer center. Multivariable logistic regression models were utilized to examine factors associated with FH. Results: The final study cohort included 31,969 patients with median age 66 years (IQR 57,73), 51% females, and 76% married. Race/ethnicity composition was 93% White, 3% Black, and 4% Hispanic. 52% of patients had Medicare and 43% had commercial insurance. Other notable factors included 48% retired, 41% working/ students, 76% married, and 72% urban residents. Median time from cancer diagnosis was 1.1 year (IQR 0.1, 3.8) and median income was $64,406 (IQR 53,067, 82,038). 31% of patients had hematological malignancies, 20% of the cancers for which staging information was available were metastatic. FH was reported by 4% (n = 1194) of the patients. A significantly higher likelihood of endorsing FH (p < 0.001 for all) was noted in Hispanic (OR 1.64), Black (OR 1.84), American Indian/Alaskan native (OR 2.02), below median income (OR 1.48), rural (OR 1.17), self-pay (OR 2.77), Medicaid (OR 2.29), Medicare (OR 1.43), unemployed/disabled (OR 2.39), single (OR 2.07), or divorced (OR 2.43) patients. Older age, being retired, and living farther from the cancer center were associated with significantly less likelihood of endorsing FH. Conclusions: Our study successfully leveraged the EMR to identify key sociodemographic groups more likely to report FH. An electronic trigger to flag such patients at high-risk of FH and proactively address FH is currently being developed.