A Compendium of Genetic Modifiers of Mitochondrial Dysfunction Reveals Intra-organelle Buffering.

Mitochondrial dysfunction is associated with a spectrum of human conditions, ranging from rare, inborn errors of metabolism to the aging process. To identify pathways that modify mitochondrial dysfunction, we performed genome-wide CRISPR screens in the presence of small-molecule mitochondrial inhibitors. We report a compendium of chemical-genetic interactions involving 191 distinct genetic modifiers, including 38 that are synthetic sick/lethal and 63 that are suppressors. Genes involved in glycolysis (PFKP), pentose phosphate pathway (G6PD), and defense against lipid peroxidation (GPX4) scored high as synthetic sick/lethal. A surprisingly large fraction of suppressors are pathway intrinsic and encode mitochondrial proteins. A striking example of such "intra-organelle" buffering is the alleviation of a chemical defect in complex V by simultaneous inhibition of complex I, which benefits cells by rebalancing redox cofactors, increasing reductive carboxylation, and promoting glycolysis. Perhaps paradoxically, certain forms of mitochondrial dysfunction may best be buffered with "second site" inhibitors to the organelle.

Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans.

How the human cortex integrates ("binds") information encoded by spatially distributed neurons remains largely unknown. One hypothesis suggests that synchronous bursts of high-frequency oscillations ("ripples") contribute to binding by facilitating integration of neuronal firing across different cortical locations. While studies have demonstrated that ripples modulate local activity in the cortex, it is not known whether their co-occurrence coordinates neural firing across larger distances. We tested this hypothesis using local field-potentials and single-unit firing from four 96-channel microelectrode arrays in the supragranular cortex of 3 patients. Neurons in co-rippling locations showed increased short-latency co-firing, prediction of each other's firing, and co-participation in neural assemblies. Effects were similar for putative pyramidal and interneurons, during non-rapid eye movement sleep and waking, in temporal and Rolandic cortices, and at distances up to 16 mm (the longest tested). Increased co-prediction during co-ripples was maintained when firing-rate changes were equated, indicating that it was not secondary to non-oscillatory activation. Co-rippling enhanced prediction was strongly modulated by ripple phase, supporting the most common posited mechanism for binding-by-synchrony. Co-ripple enhanced prediction is reciprocal, synergistic with local upstates, and further enhanced when multiple sites co-ripple, supporting re-entrant facilitation. Together, these results support the hypothesis that trans-cortical co-occurring ripples increase the integration of neuronal firing of neurons in different cortical locations and do so in part through phase-modulation rather than unstructured activation.

Regulatory Considerations in the Approval of Rezafungin (REZZAYO) for the Treatment of Candidemia and Invasive Candidiasis in Adults.

On March 22, 2023, the FDA approved rezafungin (REZZAYO) for the treatment of candidemia and invasive candidiasis in adults with limited or no alternative treatment options. Rezafungin is an echinocandin that supports weekly dosing, enabling outpatient parenteral treatment that potentially avoids the need for a central venous catheter. Approval of rezafungin was based on a single adequate and well-controlled phase 3 study designed with a Day 30 all-cause mortality primary endpoint and 20% noninferiority margin, which demonstrated that rezafungin is noninferior to the comparator echinocandin. Nonclinical studies of rezafungin in non-human primates identified a neurotoxicity safety signal; however, rezafungin's safety profile in the completed clinical studies was similar to other FDA-approved echinocandins. Here we describe the rationale for this approval and important considerations during the review process for a flexible development program intended to expedite the availability of antimicrobial therapies to treat serious infections in patients with limited treatment options.

Moving Beyond Mortality: Development and Application of a Desirability of Outcome Ranking (DOOR) Endpoint for Hospital-Acquired Bacterial Pneumonia and Ventilator-Associated Bacterial Pneumonia.

BACKGROUND: Hospital-acquired and ventilator-associated bacterial pneumonia (HABP/VABP) are frequently caused by multidrug-resistant organisms. Patient-centered endpoints in clinical trials are needed to develop new antibiotics for HABP/VABP. Desirability of outcome ranking (DOOR) is a paradigm for the design, analysis, and interpretation of clinical trials based on a patient-centered, benefit-risk evaluation. METHODS: A multidisciplinary committee created an infectious diseases DOOR endpoint customized for HABP/VABP, incorporating infectious complications, serious adverse events, and mortality. We applied this to 2 previously completed, large randomized controlled trials for HABP/VABP. ZEPHyR compared vancomycin to linezolid and VITAL compared linezolid to tedizolid. For each trial, we evaluated the DOOR distribution and probability, including DOOR component and partial credit analyses. We also applied DOOR in subgroup analyses. RESULTS: In both trials, the HABP/VABP DOOR demonstrated similar overall clinical outcomes between treatment groups. In ZEPHyR, the probability that a participant treated with linezolid would have a more desirable outcome than a participant treated with vancomycin was 50.2% (95% confidence interval [CI], 45.1%--55.3%). In VITAL, the probability that a participant treated with tedizolid would have a more desirable outcome than a participant treated with linezolid was 48.7% (95% CI, 44.8%-52.6%). The DOOR component analysis revealed that participants treated with tedizolid had a less desirable outcome than those treated with linezolid when considering clinical response alone. However, participants with decreased renal function had improved overall outcomes with tedizolid. CONCLUSIONS: The HABP/VABP DOOR provided more granular information about clinical outcomes than is typically presented in clinical trials. HABP/VABP trials would benefit from prospectively using DOOR.

Exploration of a Potential DOOR Endpoint for Hospital-Acquired Bacterial Pneumonia and Ventilator-Associated Bacterial Pneumonia Using Six Registrational Trials for Antibacterial Drugs.

BACKGROUND: Desirability of outcome ranking (DOOR) is an innovative approach to clinical trial design and analysis that uses an ordinal ranking system to incorporate the overall risks and benefits of a therapeutic intervention into a single measurement. Here, we derived and evaluated a disease-specific DOOR endpoint for registrational trials for hospital-acquired bacterial pneumonia and ventilator-associated bacterial pneumonia (HABP/VABP). METHODS: Through comprehensive examination of data from nearly 4,000 participants enrolled in six registrational trials for HABP/VABP submitted to the FDA between 2005-2022, we derived and applied a HABP/VABP specific endpoint. We estimated the probability that a participant assigned to the study treatment arm would have a more favorable overall DOOR or component outcome than a participant assigned to comparator. RESULTS: DOOR distributions between treatment arms were similar in all trials. DOOR probability estimates ranged from 48.3% to 52.9% and were not statistically different. There were no significant differences between treatment arms in the component analyses. Though infectious complications and serious adverse events occurred more frequently in ventilated participants compared to non-ventilated participants, the types of events were similar. CONCLUSIONS: Through a data-driven approach, we constructed and applied a potential DOOR endpoint for HABP/VABP trials. The inclusion of syndrome-specific events may help to better delineate and evaluate participant experiences and outcomes in future HABP/VABP trials and could help inform data collection and trial design.

Confronting Health Misinformation Surrounding COVID-19 Vaccines in the State of Florida.

COVID-19 vaccination is estimated to have averted more than 2.4 million deaths globally. In the United States (U.S.) alone, more than 120,000 deaths and 700,000 hospitalizations are reportedly estimated to have been prevented during the first six months of the vaccine campaign. Despite the overwhelming evidence regarding the safety and efficacy of vaccination, COVID-19 vaccine hesitancy continues to pose a significant threat to public health. Notably, an unexpected source of vaccine misinformation has been the Surgeon General of the State of Florida, Dr. Joseph Ladapo. While both a tenured faculty member of the University of Florida, College of Medicine and the Surgeon General of Florida, Dr. Ladapo has delivered official Florida Department of Health statements regarding COVID-19 vaccines that run contrary to those of the U.S. Centers for Disease Control and Prevention (CDC). While tenure is designed to protect those with contrarian views, we believe that the University has an ethical obligation to condemn misleading statements that put public health at risk. Herein, we explore the challenges of managing misinformation disseminated by someone who is simultaneously a tenured professor at a public, state-supported university, and a politically appointed public health official.

Quantitative metrics of the LV trabeculated layer by cardiac CT and cardiac MRI in patients with suspected noncompaction cardiomyopathy.

OBJECTIVES: To compare cardiac computed tomography (CCT) and cardiac magnetic resonance (CMR) for the quantitative assessment of the left ventricular (LV) trabeculated layer in patients with suspected noncompaction cardiomyopathy (NCCM). MATERIALS AND METHODS: Subjects with LV excessive trabeculation who underwent both CMR and CCT imaging as part of the prospective international multicenter NONCOMPACT clinical study were included. For each subject, short-axis CCT and CMR slices were matched. Four quantitative metrics were estimated: 1D noncompacted-to-compacted ratio (NCC), trabecular-to-myocardial area ratio (TMA), trabecular-to-endocardial cavity area ratio (TCA), and trabecular-to-myocardial volume ratio (TMV). In 20 subjects, end-diastolic and mid-diastolic CCT images were compared for the quantification of the trabeculated layer. Relationships between the metrics were investigated using linear regression models and Bland-Altman analyses. RESULTS: Forty-eight subjects (49.9 ± 12.8 years; 28 female) were included in this study. NCC was moderately correlated (r = 0.62), TMA and TMV were strongly correlated (r = 0.78 and 0.78), and TCA had excellent correlation (r = 0.92) between CMR and CCT, with an underestimation bias from CCT of 0.3 units, and 5.1, 4.8, and 5.4 percent-points for the 4 metrics, respectively. TMA, TCA, and TMV had excellent correlations (r = 0.93, 0.96, 0.94) and low biases (- 3.8, 0.8, - 3.8 percent-points) between the end-diastolic and mid-diastolic CCT images. CONCLUSIONS: TMA, TCA, and TMV metrics of the LV trabeculated layer in patients with suspected NCCM demonstrated high concordance between CCT and CMR images. TMA and TCA were highly reproducible and demonstrated minimal differences between mid-diastolic and end-diastolic CCT images. CLINICAL RELEVANCE STATEMENT: The results indicate similarity of CCT to CMR for quantifying the LV trabeculated layer, and the small differences in quantification between end-diastole and mid-diastole demonstrate the potential for quantifying the LV trabeculated layer from clinically performed coronary CT angiograms. KEY POINTS: • Data on cardiac CT for quantifying the left ventricular trabeculated layer are limited. • Cardiac CT yielded highly reproducible metrics of the left ventricular trabeculated layer that correlated well with metrics defined by cardiac MR. • Cardiac CT appears to be equivalent to cardiac MR for the quantification of the left ventricular trabeculated layer.

Trends and In-Hospital Mortality for Perioperative Myocardial Infarction After the Introduction of a Diagnostic Code for Type 2 Myocardial Infarction in the United States Between 2016 and 2018.

BACKGROUND: The frequency of perioperative myocardial infarction has been declining; however, previous studies have only described type 1 myocardial infarctions. Here, we evaluate the overall frequency of myocardial infarction with the addition of an International Classification of Diseases 10th revision (ICD-10-CM) code for type 2 myocardial infarction and the independent association with in-hospital mortality. METHODS: A longitudinal cohort study spanning the introduction of the ICD-10-CM diagnostic code for type 2 myocardial infarction using the National Inpatient Sample (NIS) from 2016 to 2018. Hospital discharges that included a primary surgical procedure code for intrathoracic, intraabdominal, or suprainguinal vascular surgery were included. Type 1 and type 2 myocardial infarctions were identified using ICD-10-CM codes. We used segmented logistic regression to estimate change in frequency of myocardial infarctions and multivariable logistic regression to determine the association with in-hospital mortality. RESULTS: A total of 360,264 unweighted discharges were included, representing 1,801,239 weighted discharges, with median age 59 and 56% female. The overall incidence of myocardial infarction was 0.76% (13,605/1,801,239). Before the introduction of type 2 myocardial infarction code, there was a small baseline decrease in the monthly frequency of perioperative myocardial infarctions (odds ratio [OR], 0.992; 95% confidence interval [CI], 0.984-1.000; P = .042), but no change in the trend after the introduction of the diagnostic code (OR, 0.998; 95% CI, 0.991-1.005; P = .50). In 2018, where there was an entire year where type 2 myocardial infarction was officially a diagnosis, the distribution of myocardial infarction type 1 was 8.8% (405/4580) ST elevation myocardial infarction (STEMI), 45.6% (2090/4580) non-ST elevation myocardial infarction (NSTEMI), and 45.5% (2085/4580) type 2 myocardial infarction. STEMI and NSTEMI were associated with increased in-hospital mortality (OR, 8.96; 95% CI, 6.20-12.96; P < .001 and OR, 1.59; 95% CI, 1.34-1.89; P < .001). A diagnosis of type 2 myocardial infarction was not associated with increased odds of in-hospital mortality (OR, 1.11; 95% CI, 0.81-1.53; P = .50) when accounting for surgical procedure, medical comorbidities, patient demographics, and hospital characteristics. CONCLUSIONS: The frequency of perioperative myocardial infarctions did not increase after the introduction of a new diagnostic code for type 2 myocardial infarctions. A diagnosis of type 2 myocardial infarction was not associated with increased in-patient mortality; however, few patients received invasive management that may have confirmed the diagnosis. Further research is needed to identify what type of intervention, if any, may improve outcomes in this patient population.

Comprehensive geriatric assessment predicts listing for kidney transplant in patients with end-stage renal disease: a retrospective cohort study.

BACKGROUND: Comprehensive geriatric assessment (CGA) involves a formal broad approach to assess frailty and creating a plan for management. However, the impact of CGA and its components on listing for kidney transplant in older adults has not been investigated. METHODS: We performed a single-center retrospective study of patients with end-stage renal disease who underwent CGA during kidney transplant candidacy evaluation between 2017 and 2021. All patients ≥ 65 years old and those under 65 with any team member concern for frailty were referred for CGA, which included measurements of healthcare utilization, comorbidities, social support, short physical performance battery, Montreal Cognitive Assessment (MoCA), and Physical Frailty Phenotype (FPP), and estimate of surgical risk by the geriatrician. RESULTS: Two hundred and thirty patients underwent baseline CGA evaluation; 58.7% (135) had high CGA ("Excellent" or "Good" rating for transplant candidacy) and 41.3% (95) had low CGA ratings ("Borderline," "Fair," or "Poor"). High CGA rating (OR 8.46; p < 0.05), greater number of CGA visits (OR 4.93; p = 0.05), younger age (OR 0.88; p < 0.05), higher MoCA scores (OR 1.17; p < 0.05), and high physical activity (OR 4.41; p < 0.05) were all associated with listing on transplant waitlist. CONCLUSIONS: The CGA is a useful, comprehensive tool to help select older adults for kidney transplantation. Further study is needed to better understand the predictive value of CGA in predicting post-operative outcomes.

Barriers and facilitators to smartwatch-based prehabilitation participation among frail surgery patients: a qualitative study.

BACKGROUND: For older, frail adults, exercise before surgery through prehabilitation (prehab) may hasten return recovery and reduce postoperative complications. We developed a smartwatch-based prehab program (BeFitMe) for older adults that encourages and tracks at-home exercise. The objective of this study was to assess patient perceptions about facilitators and barriers to prehab generally and to using a smartwatch prehab program among older adult thoracic surgery patients to optimize future program implementation. METHODS: We recruited patients, aged ≥50 years who had or were having surgery and were screened for frailty (Fried's Frailty Phenotype) at a thoracic surgery clinic at a single academic institution. Semi-structured interviews were conducted by telephone after obtaining informed consent. Participants were given a description of the BeFitMe program. The interview questions were informed by The Five "Rights" of Clinical Decision-Making framework (Information, Person, Time, Channel, and Format) and sought to identify the factors perceived to influence smartwatch prehab program participation. Interview transcripts were transcribed and independently coded to identify themes in for each of the Five "Rights" domains. RESULTS: A total of 29 interviews were conducted. Participants were 52% men (n = 15), 48% Black (n = 14), and 59% pre-frail (n = 11) or frail (n = 6) with a mean age of 68 ± 9 years. Eleven total themes emerged. Facilitator themes included the importance of providers (right person) clearly explaining the significance of prehab (right information) during the preoperative visit (right time); providing written instructions and exercise prescriptions; and providing a preprogrammed and set-up (right format) Apple Watch (right channel). Barrier themes included pre-existing conditions and disinterest in exercise and/or technology. Participants provided suggestions to overcome the technology barrier, which included individualized training and support on usage and responsibilities. CONCLUSIONS: This study reports the perceived facilitators and barriers to a smartwatch-based prehab program for pre-frail and frail thoracic surgery patients. The future BeFitMe implementation protocol must ensure surgical providers emphasize the beneficial impact of participating in prehab before surgery and provide a written prehab prescription; must include a thorough guide on smartwatch use along with the preprogrammed device to be successful. The findings are relevant to other smartwatch-based interventions for older adults.

Implementing a Frailty-Specific Postoperative Order Set to Improve Postoperative Outcomes in Frail Adults After Elective Thoracic Surgery.

BACKGROUND: Frailty is independently associated with adverse patient outcomes after surgery. The current standards of postoperative care rarely consider frailty status. LOCAL PROBLEM: There was no standardized protocol to optimize specialized postoperative care for frail patients at an academic medical center. METHODS: A quasi-experimental pre-/postimplementation study design, using the Reach, Effectiveness, Adoption, Implementation, Maintenance implementation framework, was utilized. INTERVENTIONS: A frailty-specific postoperative order set (FPOS) was developed, including tailored nursing care, activity levels, and nutritional goals. RESULTS: There were significant improvements in nurse's self-reported familiarity with frailty (P = .003) and FPOS awareness (P < .001). The number of orders for delirium prevention, elimination, nutrition, sleep promotion, and sensory support increased (P < .001). CONCLUSIONS: Implementing an FPOS showed improvements in nurse frailty knowledge, awareness, and order set utilization.

Learned Motor Patterns Are Replayed in Human Motor Cortex during Sleep.

Consolidation of memory is believed to involve offline replay of neural activity. While amply demonstrated in rodents, evidence for replay in humans, particularly regarding motor memory, is less compelling. To determine whether replay occurs after motor learning, we sought to record from motor cortex during a novel motor task and subsequent overnight sleep. A 36-year-old man with tetraplegia secondary to cervical spinal cord injury enrolled in the ongoing BrainGate brain-computer interface pilot clinical trial had two 96-channel intracortical microelectrode arrays placed chronically into left precentral gyrus. Single- and multi-unit activity was recorded while he played a color/sound sequence matching memory game. Intended movements were decoded from motor cortical neuronal activity by a real-time steady-state Kalman filter that allowed the participant to control a neurally driven cursor on the screen. Intracortical neural activity from precentral gyrus and 2-lead scalp EEG were recorded overnight as he slept. When decoded using the same steady-state Kalman filter parameters, intracortical neural signals recorded overnight replayed the target sequence from the memory game at intervals throughout at a frequency significantly greater than expected by chance. Replay events occurred at speeds ranging from 1 to 4 times as fast as initial task execution and were most frequently observed during slow-wave sleep. These results demonstrate that recent visuomotor skill acquisition in humans may be accompanied by replay of the corresponding motor cortex neural activity during sleep.SIGNIFICANCE STATEMENT Within cortex, the acquisition of information is often followed by the offline recapitulation of specific sequences of neural firing. Replay of recent activity is enriched during sleep and may support the consolidation of learning and memory. Using an intracortical brain-computer interface, we recorded and decoded activity from motor cortex as a human research participant performed a novel motor task. By decoding neural activity throughout subsequent sleep, we find that neural sequences underlying the recently practiced motor task are repeated throughout the night, providing direct evidence of replay in human motor cortex during sleep. This approach, using an optimized brain-computer interface decoder to characterize neural activity during sleep, provides a framework for future studies exploring replay, learning, and memory.

Improving Traditional Registrational Trial End Points: Development and Application of a Desirability of Outcome Ranking End Point for Complicated Urinary Tract Infection Clinical Trials.

BACKGROUND: Traditional end points used in registrational randomized, controlled trials (RCTs) often do not allow for complete interpretation of the full range of potential clinical outcomes. Desirability of outcome ranking (DOOR) is an approach to the design and analysis of clinical trials that incorporates benefits and risks of novel treatment strategies and provides a global assessment of patient experience. METHODS: Through a multidisciplinary committee of experts in infectious diseases, clinical trial design, drug regulation, and patient experience, we developed a DOOR end point for infectious disease syndromes and demonstrated how this could be applied to 3 registrational drug trials (ZEUS, APEKS-cUTI, and DORI-05) for complicated urinary tract infections (cUTIs). ZEUS compared fosfomycin to piperacillin/tazobactam, APEKS-cUTI compared cefiderocol to imipenem, and DORI-05 compared doripenem to levofloxacin. Using DOOR, we estimated the probability of a more desirable outcome with each investigational antibacterial drug. RESULTS: In each RCT, the DOOR distribution was similar and the probability that a patient in the investigational arm would have a more desirable outcome than a patient in the control arm had a 95% confidence interval containing 50%, indicating no significant difference between treatment arms. DOOR facilitated improved understanding of potential trade-offs between clinical efficacy and safety. Partial credit and subgroup analyses also highlight unique attributes of DOOR. CONCLUSIONS: DOOR can effectively be used in registrational cUTI trials. The DOOR end point presented here can be adapted for other infectious disease syndromes and prospectively incorporated into future clinical trials.

Exploration of a Potential Desirability of Outcome Ranking Endpoint for Complicated Intra-Abdominal Infections Using 9 Registrational Trials for Antibacterial Drugs.

BACKGROUND: Desirability of outcome ranking (DOOR) is a novel approach to clinical trial design that incorporates safety and efficacy assessments into an ordinal ranking system to evaluate overall outcomes of clinical trial participants. Here, we derived and applied a disease-specific DOOR endpoint to registrational trials for complicated intra-abdominal infection (cIAI). METHODS: Initially, we applied an a priori DOOR prototype to electronic patient-level data from 9 phase 3 noninferiority trials for cIAI submitted to the US Food and Drug Administration between 2005 and 2019. We derived a cIAI-specific DOOR endpoint based on clinically meaningful events that trial participants experienced. Next, we applied the cIAI-specific DOOR endpoint to the same datasets and, for each trial, estimated the probability that a participant assigned to the study treatment would have a more desirable DOOR or component outcome than if assigned to the comparator. RESULTS: Three key findings informed the cIAI-specific DOOR endpoint: (1) a significant proportion of participants underwent additional surgical procedures related to their baseline infection; (2) infectious complications of cIAI were diverse; and (3) participants with worse outcomes experienced more infectious complications, more serious adverse events, and underwent more procedures. DOOR distributions between treatment arms were similar in all trials. DOOR probability estimates ranged from 47.4% to 50.3% and were not significantly different. Component analyses depicted risk-benefit assessments of study treatment versus comparator. CONCLUSIONS: We designed and evaluated a potential DOOR endpoint for cIAI trials to further characterize overall clinical experiences of participants. Similar data-driven approaches can be utilized to create other infectious disease-specific DOOR endpoints.

Examination of fully automated mammographic density measures using LIBRA and breast cancer risk in a cohort of 21,000 non-Hispanic white women.

BACKGROUND: Breast density is strongly associated with breast cancer risk. Fully automated quantitative density assessment methods have recently been developed that could facilitate large-scale studies, although data on associations with long-term breast cancer risk are limited. We examined LIBRA assessments and breast cancer risk and compared results to prior assessments using Cumulus, an established computer-assisted method requiring manual thresholding. METHODS: We conducted a cohort study among 21,150 non-Hispanic white female participants of the Research Program in Genes, Environment and Health of Kaiser Permanente Northern California who were 40-74 years at enrollment, followed for up to 10 years, and had archived processed screening mammograms acquired on Hologic or General Electric full-field digital mammography (FFDM) machines and prior Cumulus density assessments available for analysis. Dense area (DA), non-dense area (NDA), and percent density (PD) were assessed using LIBRA software. Cox regression was used to estimate hazard ratios (HRs) for breast cancer associated with DA, NDA and PD modeled continuously in standard deviation (SD) increments, adjusting for age, mammogram year, body mass index, parity, first-degree family history of breast cancer, and menopausal hormone use. We also examined differences by machine type and breast view. RESULTS: The adjusted HRs for breast cancer associated with each SD increment of DA, NDA and PD were 1.36 (95% confidence interval, 1.18-1.57), 0.85 (0.77-0.93) and 1.44 (1.26-1.66) for LIBRA and 1.44 (1.33-1.55), 0.81 (0.74-0.89) and 1.54 (1.34-1.77) for Cumulus, respectively. LIBRA results were generally similar by machine type and breast view, although associations were strongest for Hologic machines and mediolateral oblique views. Results were also similar during the first 2 years, 2-5 years and 5-10 years after the baseline mammogram. CONCLUSION: Associations with breast cancer risk were generally similar for LIBRA and Cumulus density measures and were sustained for up to 10 years. These findings support the suitability of fully automated LIBRA assessments on processed FFDM images for large-scale research on breast density and cancer risk.

Atrial fibrillation ablation outcome prediction with a machine learning fusion framework incorporating cardiac computed tomography.

BACKGROUND: Structural changes in the left atrium (LA) modestly predict outcomes in patients undergoing catheter ablation for atrial fibrillation (AF). Machine learning (ML) is a promising approach to personalize AF management strategies and improve predictive risk models after catheter ablation by integrating atrial geometry from cardiac computed tomography (CT) scans and patient-specific clinical data. We hypothesized that ML approaches based on a patient's specific data can identify responders to AF ablation. METHODS: Consecutive patients undergoing AF ablation, who had preprocedural CT scans, demographics, and 1-year follow-up data, were included in the study for a retrospective analysis. The inputs of models were CT-derived morphological features from left atrial segmentation (including the shape, volume of the LA, LA appendage, and pulmonary vein ostia) along with deep features learned directly from raw CT images, and clinical data. These were merged intelligently in a framework to learn their individual importance and produce the optimal classification. RESULTS: Three hundred twenty-one patients (64.2 ± 10.6 years, 69% male, 40% paroxysmal AF) were analyzed. Post 10-fold nested cross-validation, the model trained to intelligently merge and learn appropriate weights for clinical, morphological, and imaging data (AUC 0.821) outperformed those trained solely on clinical data (AUC 0.626), morphological (AUC 0.659), or imaging data (AUC 0.764). CONCLUSION: Our ML approach provides an end-to-end automated technique to predict AF ablation outcomes using deep learning from CT images, derived structural properties of LA, augmented by incorporation of clinical data in a merged ML framework. This can help develop personalized strategies for patient selection in invasive management of AF.

Low-count whole-body PET/MRI restoration: an evaluation of dose reduction spectrum and five state-of-the-art artificial intelligence models.

PURPOSE: To provide a holistic and complete comparison of the five most advanced AI models in the augmentation of low-dose 18F-FDG PET data over the entire dose reduction spectrum. METHODS: In this multicenter study, five AI models were investigated for restoring low-count whole-body PET/MRI, covering convolutional benchmarks - U-Net, enhanced deep super-resolution network (EDSR), generative adversarial network (GAN) - and the most cutting-edge image reconstruction transformer models in computer vision to date - Swin transformer image restoration network (SwinIR) and EDSR-ViT (vision transformer). The models were evaluated against six groups of count levels representing the simulated 75%, 50%, 25%, 12.5%, 6.25%, and 1% (extremely ultra-low-count) of the clinical standard 3 MBq/kg 18F-FDG dose. The comparisons were performed upon two independent cohorts - (1) a primary cohort from Stanford University and (2) a cross-continental external validation cohort from Tübingen University - in order to ensure the findings are generalizable. A total of 476 original count and simulated low-count whole-body PET/MRI scans were incorporated into this analysis. RESULTS: For low-count PET restoration on the primary cohort, the mean structural similarity index (SSIM) scores for dose 6.25% were 0.898 (95% CI, 0.887-0.910) for EDSR, 0.893 (0.881-0.905) for EDSR-ViT, 0.873 (0.859-0.887) for GAN, 0.885 (0.873-0.898) for U-Net, and 0.910 (0.900-0.920) for SwinIR. In continuation, SwinIR and U-Net's performances were also discreetly evaluated at each simulated radiotracer dose levels. Using the primary Stanford cohort, the mean diagnostic image quality (DIQ; 5-point Likert scale) scores of SwinIR restoration were 5 (SD, 0) for dose 75%, 4.50 (0.535) for dose 50%, 3.75 (0.463) for dose 25%, 3.25 (0.463) for dose 12.5%, 4 (0.926) for dose 6.25%, and 2.5 (0.534) for dose 1%. CONCLUSION: Compared to low-count PET images, with near-to or nondiagnostic images at higher dose reduction levels (up to 6.25%), both SwinIR and U-Net significantly improve the diagnostic quality of PET images. A radiotracer dose reduction to 1% of the current clinical standard radiotracer dose is out of scope for current AI techniques.

Preoperative ß-Blocker Therapy and Stroke or Major Adverse Cardiac Events in Major Abdominal Surgery: A Retrospective Cohort Study.

BACKGROUND: Perioperative ß-blocker therapy has been associated with increased risk of stroke. However, the association between ß-blocker initiation before the day of surgery and the risk of stroke is unknown. The authors hypothesized there would be no association between preoperative ß-blocker initiation within 60 days of surgery or chronic ß-blockade (more than 60 days) and the risk of stroke in patients undergoing major abdominal surgery. METHODS: Data on elective major abdominal surgery were obtained from the IBM (USA) Truven Health MarketScan 2005 to 2015 Commercial and Medicare Supplemental Databases. Patients were stratified by ß-blocker dispensing exposure: (1) ß-blocker-naïve, (2) preoperative ß-blocker initiation within 60 days of surgery, and (3) chronic ß-blocker dispensing (more than 60 days). The authors compared in-hospital stroke and major adverse cardiac events between the different ß-blocker therapy exposures. RESULTS: There were 204,981 patients who underwent major abdominal surgery. ß-Blocker exposure was as follows: perioperative initiation within 60 days of surgery for 4,026 (2.0%) patients, chronic ß-blocker therapy for 45,424 (22.2%) patients, and ß-blocker-naïve for 155,531 (75.9%) patients. The unadjusted frequency of stroke for patients with ß-blocker initiation (0.4%, 17 of 4,026) and chronic ß-blocker therapy (0.4%, 171 of 45,424) was greater than in ß-blocker-naïve patients (0.2%, 235 of 155,531; P < 0.001). After propensity score weighting, patients initiated on a ß-blocker within 60 days of surgery (odds ratio, 0.90; 95% CI, 0.31 to 2.04; P = 0.757) or on chronic ß-blocker therapy (odds ratio, 0.86; 95% CI, 0.65 to 1.15; P = 0.901) demonstrated similar stroke risk compared to ß-blocker-naïve patients. Patients on chronic ß-blocker therapy demonstrated lower adjusted risk of major adverse cardiac events compared to ß-blocker-naïve patients (odds ratio, 0.81; 95% CI, 0.72 to 0.91; P = 0.007), despite higher unadjusted absolute event rate (2.6% [1,173 of 45,424] vs. 0.6% [872 of 155,531]). CONCLUSIONS: Among patients undergoing elective major abdominal surgery, the authors observed no association between preoperative ß-blocker initiation within 60 days of surgery or chronic ß-blocker therapy and stroke.

Nonalcoholic fatty liver disease (NAFLD) detection and deep learning in a Chinese community-based population.

OBJECTIVES: We aimed to develop and validate a deep learning system (DLS) by using an auxiliary section that extracts and outputs specific ultrasound diagnostic features to improve the explainable, clinical relevant utility of using DLS for detecting NAFLD. METHODS: In a community-based study of 4144 participants with abdominal ultrasound scan in Hangzhou, China, we sampled 928 (617 [66.5%] females, mean age: 56 years ± 13 [standard deviation]) participants (2 images per participant) to develop and validate DLS, a two-section neural network (2S-NNet). Radiologists' consensus diagnosis classified hepatic steatosis as none steatosis, mild, moderate, and severe. We also explored the NAFLD detection performance of six one-section neural network models and five fatty liver indices on our data set. We further evaluated the influence of participants' characteristics on the correctness of 2S-NNet by logistic regression. RESULTS: Area under the curve (AUROC) of 2S-NNet for hepatic steatosis was 0.90 for ≥ mild, 0.85 for ≥ moderate, and 0.93 for severe steatosis, and was 0.90 for NAFLD presence, 0.84 for moderate to severe NAFLD, and 0.93 for severe NAFLD. The AUROC of NAFLD severity was 0.88 for 2S-NNet, and 0.79-0.86 for one-section models. The AUROC of NAFLD presence was 0.90 for 2S-NNet, and 0.54-0.82 for fatty liver indices. Age, sex, body mass index, diabetes, fibrosis-4 index, android fat ratio, and skeletal muscle via dual-energy X-ray absorptiometry had no significant impact on the correctness of 2S-NNet (p > 0.05). CONCLUSIONS: By using two-section design, 2S-NNet had improved the performance for detecting NAFLD with more explainable, clinical relevant utility than using one-section design. KEY POINTS: • Based on the consensus review derived from radiologists, our DLS (2S-NNet) had an AUROC of 0.88 by using two-section design and yielded better performance for detecting NAFLD than using one-section design with more explainable, clinical relevant utility. • The 2S-NNet outperformed five fatty liver indices with the highest AUROCs (0.84-0.93 vs. 0.54-0.82) for different NAFLD severity screening, indicating screening utility of deep learning-based radiology may perform better than blood biomarker panels in epidemiology. • The correctness of 2S-NNet was not significantly influenced by individual's characteristics, including age, sex, body mass index, diabetes, fibrosis-4 index, android fat ratio, and skeletal muscle via dual-energy X-ray absorptiometry.

Disparities in Shared Decision-Making Research and Practice: The Case for Black American Patients.

OBJECTIVE: The extent of shared decision making (SDM) use in the care of Black patients is limited. We explored preferences, needs, and challenges of Black patients to enhance SDM offerings. METHODS: We performed interviews with 32 Black patients receiving type 2 diabetes care in safety-net primary care practices caring predominantly for Black people. RESULTS: The following 4 themes emerged: preference for humanistic communication, need to account for the role of family in decision making, need for medical information sharing, and mistrust of clinicians. CONCLUSION: Given the dearth of research on SDM among ethnic and racial minorities, this study offers patient-perspective recommendations to improve SDM offerings for Black patients in primary care settings. To enhance SDM with Black patients, acknowledgment of the importance of storytelling as a strategy, to place medical information in a context that makes it meaningful and memorable, is recommended. Triadic SDM, in which family members are centrally involved in decision making, is preferred over classical dyadic SDM. There is a need to reconsider the universalism assumption underlying contemporary SDM models and the relevancy of current SDM practices that were developed mostly without the feedback of participants of ethnic, racial, and cultural minorities.Annals "Online First" article.