Citations

AbstractBackgroundKnown risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.MethodsSingle nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer–related cell types.ResultsWe identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.ConclusionsCNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

OBJECTIVES: To engage critical care end-users (survivors and caregivers) to describe their emotions and experiences across their recovery trajectory, and elicit their ideas and solutions for health service improvements to improve the ICU recovery experience. DESIGN: End-user engagement as part of a qualitative design using the Framework Analysis method. SETTING: The Society of Critical Care Medicine’s THRIVE international collaborative sites (follow-up clinics and peer support groups). SUBJECTS: Patients and caregivers following critical illness and identified through the collaboratives. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Eighty-six interviews were conducted. The following themes were identified: 1) Emotions and experiences of patients—“Loss of former self; Experiences of disability and adaptation”; 2) Emotions and experiences of caregivers—“Emotional impacts, adopting new roles, and caregiver burden; Influence of gender roles; Adaptation, adjustment, recalibration”; and 3) Patient and caregiver-generated solutions to improve recovery across the arc of care—“Family-targeted education; Expectation management; Rehabilitation for patients and caregivers; Peer support groups; Reconnecting with ICU post-discharge; Access to community-based supports post-discharge; Psychological support; Education of issues of ICU survivorship for health professionals; Support across recovery trajectory.” Themes were mapped to a previously published recovery framework (Timing It Right) that captures patient and caregiver experiences and their support needs across the phases of care from the event/diagnosis to adaptation post-discharge home. CONCLUSIONS: Patients and caregivers reported a range of emotions and experiences across the recovery trajectory from ICU to home. Through end-user engagement strategies many potential solutions were identified that could be implemented by health services and tested to support the delivery of higher-quality care for ICU survivors and their caregivers that extend from tertiary to primary care settings.

Objectives Social determinants of health (SDoH) contribute to health outcomes. We identified SDoH that were modified by critical illness, and the effect of such modifications on recovery from critical illness. Design In-depth semistructured interviews following hospital discharge. Interview transcripts were mapped against a pre-existing social policy framework: money and work; skills and education; housing, transport and neighbourhoods; and family, friends and social connections. Setting 14 hospital sites in the USA, UK and Australia. Participants Patients and caregivers, who had been admitted to critical care from three continents. Results 86 interviews were analysed (66 patients and 20 caregivers). SDoH, both financial and non-financial in nature, could be negatively influenced by exposure to critical illness, with a direct impact on health-related outcomes at an individual level. Financial modifications included changes to employment status due to critical illness-related disability, alongside changes to income and insurance status. Negative health impacts included the inability to access essential healthcare and an increase in mental health problems. Conclusions Critical illness appears to modify SDoH for survivors and their family members, potentially impacting recovery and health. Our findings suggest that increased attention to issues such as one’s social network, economic security and access to healthcare is required following discharge from critical care.

Importance In patients with severe aortic valve stenosis at intermediate surgical risk, transcatheter aortic valve replacement (TAVR) with a self-expanding supra-annular valve was noninferior to surgery for all-cause mortality or disabling stroke at 2 years. Comparisons of longer-term clinical and hemodynamic outcomes in these patients are limited. Objective To report prespecified secondary 5-year outcomes from the Symptomatic Aortic Stenosis in Intermediate Risk Subjects Who Need Aortic Valve Replacement (SURTAVI) randomized clinical trial. Design, Setting, and Participants SURTAVI is a prospective randomized, unblinded clinical trial. Randomization was stratified by investigational site and need for revascularization determined by the local heart teams. Patients with severe aortic valve stenosis deemed to be at intermediate risk of 30-day surgical mortality were enrolled at 87 centers from June 19, 2012, to June 30, 2016, in Europe and North America. Analysis took place between August and October 2021. Intervention Patients were randomized to TAVR with a self-expanding, supra-annular transcatheter or a surgical bioprosthesis. Main Outcomes and Measures The prespecified secondary end points of death or disabling stroke and other adverse events and hemodynamic findings at 5 years. An independent clinical event committee adjudicated all serious adverse events and an independent echocardiographic core laboratory evaluated all echocardiograms at 5 years. Results A total of 1660 individuals underwent an attempted TAVR (n = 864) or surgical (n = 796) procedure. The mean (SD) age was 79.8 (6.2) years, 724 (43.6%) were female, and the mean (SD) Society of Thoracic Surgery Predicted Risk of Mortality score was 4.5% (1.6%). At 5 years, the rates of death or disabling stroke were similar (TAVR, 31.3% vs surgery, 30.8%; hazard ratio, 1.02 [95% CI, 0.85-1.22]; P = .85). Transprosthetic gradients remained lower (mean [SD], 8.6 [5.5] mm Hg vs 11.2 [6.0] mm Hg; P < .001) and aortic valve areas were higher (mean [SD], 2.2 [0.7] cm 2 vs 1.8 [0.6] cm 2 ; P < .001) with TAVR vs surgery. More patients had moderate/severe paravalvular leak with TAVR than surgery (11 [3.0%] vs 2 [0.7%]; risk difference, 2.37% [95% CI, 0.17%- 4.85%]; P = .05). New pacemaker implantation rates were higher for TAVR than surgery at 5 years (289 [39.1%] vs 94 [15.1%]; hazard ratio, 3.30 [95% CI, 2.61-4.17]; log-rank P < .001), as were valve reintervention rates (27 [3.5%] vs 11 [1.9%]; hazard ratio, 2.21 [95% CI, 1.10-4.45]; log-rank P = .02), although between 2 and 5 years only 6 patients who underwent TAVR and 7 who underwent surgery required a reintervention. Conclusions and Relevance Among intermediate-risk patients with symptomatic severe aortic stenosis, major clinical outcomes at 5 years were similar for TAVR and surgery. TAVR was associated with superior hemodynamic valve performance but also with more paravalvular leak and valve reinterventions.

AbstractAimsTo explore participants' experiences with and perspective of a telephone‐based, peer‐led diabetes self‐management intervention targeting adults with type 2 diabetes (T2D) from speciality care settings. We also sought to identify areas for improvement for future iterations of the intervention.MethodsThis study recruited 25 adults with T2D from the intervention arm of a randomized controlled trial of a peer support intervention for diabetes. Individuals took part in semi‐structured interviews that explored the following topics: perceived impact of the intervention, relationship with peer leader, desirable characteristics in a peer leader, and suggestions for improving the intervention. Focus groups were recorded, transcribed, quality checked, coded, and analysed to develop themes and subthemes.ResultsFour core themes emerged: (1) importance of the ‘participant‐peer leader’ match, (2) peer leader roles and responsibilities, (3) need for flexible support models, and (4) factors affecting intervention implementation and engagement. The quality of the participant‐peer leader relationship appeared to be linked to intervention satisfaction. Beyond demographic features such as age and sex, key characteristics for forming a strong match included stage of life, lifestyle, diabetes‐related factors, and communication style.ConclusionsParticipants have unique ideas about what support should look like and preferences for how support is best delivered. Future models of peer support need to be customizable to individuals' needs and responsive to changes in life circumstances. If participants are the decision makers in the matching process, they may experience greater satisfaction and derive maximal benefits.

AbstractQualified medical physicists (QMPs) are in a unique position to influence the creation and application of key performance indicators (KPIs) across diverse practices in health care. Developing KPIs requires the involvement of stakeholders in the area of interest. Fundamentally, KPIs should provide actionable information for the stakeholders using or viewing them. During development, it is important to strongly consider the underlying data collection for the KPI, making it automatic whenever possible. Once the KPI has been validated, it is important to setup a review cycle and be prepared to adjust the underlying data or action levels if the KPI is not performing as intended. Examples of specific KPIs for QMPs of common scopes of practice are provided to act as models to aid in implementation. KPIs are a useful tool for QMPs, regardless of the scope of practice or practice environment, to enhance the safety and quality of care being delivered.

8549 Background: First-line treatment of early stage non-small cell lung cancer (NSCLC) is surgical resection, but with a 5-year survival of only 54%, rates of future relapse are high. Identifying patients at high risk of relapse can help guide adjuvant treatment decisions. Deep convolutional neural network (DCNN) AI models trained on tumor histology have shown incredible flexibility as potential biomarkers, both in lung cancer and more generally across many malignancies. While DCNN models can obtain extremely accurate results when used for routine purposes such as diagnosis, subtyping, and grading of malignancies, most models trained for prognostication or treatment response prediction do not reach performance sufficient for clinical application. Uncertainty quantification (UQ) – a family of techniques that give DCNN models the ability to report confidence alongside predictions – is an underexplored avenue in cancer AI that may help further improve performance and clinical application of models designed to provide clinicians with estimations of risk. Methods: To explore the potential use of UQ in clinically-oriented DCNN models, we trained models on a single-institution, retrospective digital tumor histology slide cohort from patients with Stage I-III NSCLC who underwent surgical resection to predict risk of future relapse. Estimation of uncertainty was performed using dropout as a Bayesian approximation, and uncertainty thresholds were calculated from training sets using a novel method to identify and remove low-confidence predictions. For comparison, a separate multivariate logistic regression was trained in cross-validation using known clinical risk factors. Results: We trained DCNN models on slides from 198 patients (40 relapsed, 158 without relapse). In this cohort, 130 patients had stage I disease (65.6%), 42 had stage II (21.2%), and 26 had stage III (13.2%). The average age was 69 years, 85% were current or previous smokers, and 38 received guideline-concordant adjuvant chemotherapy. Without UQ, a DCNN model predicted risk of future relapse with an average area under receiver operator curve (AUROC) of 0.74 across three-fold cross-validation. Using UQ estimation, 63% of slides were reported with high confidence. Relapse prediction was significantly improved in the high-confidence cohort, with an average AUROC of 0.83 in cross-validation. With a specificity of 70%, this corresponds to an average sensitivity of 86.8% across the three cross-folds (79.1%, 85.5%, and 95.7%). In comparison, a clinical-only multivariate regression model predicted relapse with a cross-validated AUROC of 0.67. Conclusions: This method of uncertainty quantification appears to be a powerful tool to predict lung cancer recurrence risk from digital histopathology while simultaneously providing clinicians with a measurement of algorithm trustworthiness.

Abstract Background: Delirium is a highly prevalent and morbid syndrome in mechanically ventilated intensive care unit (ICU) patients. Music is a promising non-pharmacological intervention with beneficial effects on anxiety and stress, while its effects on delirium duration and severity are not well understood.Methods/design: Our study is a two-arm, randomized parallel-group, clinical trial to evaluate the efficacy of music intervention compared to a silence-track attention control on delirium/coma duration in mechanically ventilated critically ill older adults. One-hundred-sixty mechanically ventilated adults 50 years of age or older will be randomized to one of two arms within 72 hours of ICU admission: (1) one-hour music listening sessions twice daily through noise-cancelling headphones, or (2) one-hour sessions of a silence track twice daily through noise-cancelling headphones. Our primary aim is to compare delirium/coma free days after randomization during the 7-day study intervention phase using the Confusion Assessment Method for the ICU (CAM ICU) and the Richmond Agitation Sedation Scale (RASS) for delirium and coma. Secondary outcomes include pain and anxiety evaluated twice daily during the intervention phase and throughout the duration of ICU stay using the Critical Care Pain Observation Tool (CPOT) and Visual Analogue Scale-Anxiety (VAS-A). Enrolled participants will be followed after hospital discharge to further measure cognition as well as screening for depression and anxiety using the following telephone-based instruments: Indiana University Telephone-Based Assessment of Neuropsychological Status (IU TBANS), Patient Health Questionnaire-9 (PHQ-9), and Generalized Anxiety Disorder-7 (GAD-7).Discussion: This randomized clinical trial will measure the efficacy of a music listening intervention for delirium and coma duration early in the intensive care unit among older adults.Trial Registration: https://clinicaltrials.gov/ct2/show/NCT04182334