Citations

AbstractBackgroundThe first step in computed tomography (CT) reconstruction is to estimate attenuation pathlength. Usually, this is done with a logarithm transformation, which is the direct solution to the Beer‐Lambert Law. At low signals, however, the logarithm estimator is biased. Bias arises both from the curvature of the logarithm and from the possibility of detecting zero counts, so a data substitution strategy may be employed to avoid the singularity of the logarithm. Recent progress has been made by Li et al. [IEEE Trans Med Img 42:6, 2023] to modify the logarithm estimator to eliminate curvature bias, but the optimal strategy for mitigating bias from the singularity remains unknown.PurposeThe purpose of this study was to use numerical techniques to construct unbiased attenuation pathlength estimators that are alternatives to the logarithm estimator, and to study the uniqueness and optimality of possible solutions, assuming a photon counting detector.MethodsFormally, an attenuation pathlength estimator is a mapping from integer detector counts to real pathlength values. We constrain our focus to only the small signal inputs that are problematic for the logarithm estimator, which we define as inputs of <100 counts, and we consider estimators that use only a single input and that are not informed by adjacent measurements (e.g., adaptive smoothing). The set of all possible pathlength estimators can then be represented as points in a 100‐dimensional vector space. Within this vector space, we use optimization to select the estimator that (1) minimizes mean squared error and (2) is unbiased. We define “unbiased” as satisfying the numerical condition that the maximum bias be less than 0.001 across a continuum of 1000 object thicknesses that span the desired operating range. Because the objective function is convex and the constraints are affine, optimization is tractable and guaranteed to converge to the global minimum. We further examine the nullspace of the constraint matrix to understand the uniqueness of possible solutions, and we compare the results to the Cramér‐Rao bound of the variance.ResultsWe first show that an unbiased attenuation pathlength estimator does not exist if very low mean detector signals (equivalently, very thick objects) are permitted. It is necessary to select a minimum mean detector signal for which unbiased behavior is desired. If we select two counts, the optimal estimator is similar to Li's estimator. If we select one count, the optimal estimator becomes non‐monotonic. The oscillations cause the unbiased estimator to be noise amplifying. The nullspace of the constraint matrix is high‐dimensional, so that unbiased solutions are not unique. The Cramér‐Rao bound of the variance matches well with the expected scaling law and cannot be attained.ConclusionIf arbitrarily thick objects are permitted, an unbiased attenuation pathlength estimator does not exist. If the maximum thickness is restricted, an unbiased estimator exists but is not unique. An optimal estimator can be selected that minimizes variance, but a bias‐variance tradeoff exists where a larger domain of unbiased behavior requires increased variance.

OBJECTIVES: Telecritical care (TCC) refers to the delivery of critical care using telehealth technologies. Despite increasing utilization, significant practice variation exists and literature regarding efficacy remains sparse. The Telecritical Care Collaborative Network sought to provide expert, consensus-based best practice recommendations for the design and delivery of TCC. DESIGN: We used a modified Delphi methodology. Following literature review, an oversight panel identified core domains and developed declarative statements for review by an expert voting panel. During three voting rounds, voters agreed or disagreed with statements and provided open-ended feedback, which the oversight panel used to revise statements. Statements met criteria for consensus when accepted by greater than or equal to 85% of voters. SETTING/SUBJECTS: The oversight panel included 18 multidisciplinary members of the TCC Collaborative Network, and the voting panel included 32 invited experts in TCC, emphasizing diversity of discipline, care delivery models, and geography. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We identified ten core domains: definitions/terminology; care delivery models; staffing and coverage models; technological considerations; ergonomics and workplace safety; licensing, credentialing, and certification; trust and relationship building; quality, safety, and efficiency, research agenda; and advocacy, leading to 79 practice statements. Of 79 original statements, 67 were accepted in round 1. After revision, nine were accepted in round 2 and two in round 3 (two statements were merged). In total, 78 practice statements achieved expert consensus. CONCLUSIONS: These expert consensus recommendations cover a broad range of topics relevant to delivery of TCC. Experts agreed that TCC is most effective when delivered by care teams with specific expertise and by programs with explicit protocols focusing on effective communication, technical reliability, and real-time availability. Interventions should be tailored to local conditions. Although further research is needed to guide future best practice statements, these results provide valuable and actionable recommendations for the delivery of high-quality TCC.

ABSTRACTThis case report describes the novel use of oxybutynin and acetaminophen as a substitution for oxycodone for the express purpose of diverting oxycodone in a hospital‐based post‐anesthesia care unit (PACU). The report outlines how the physical properties and pharmacologic effects of non‐controlled medications in the PACU, like oxybutynin, can be visually mistaken and even mimic the side effects of controlled substances like oxycodone. Substituting oxybutynin for controlled substances can circumvent diversion surveillance software. The authors describe how the diversion was identified and the process improvements that should be implemented for proactive identification moving forward.

Abstract Purpose: Mutations in hematopoietic progenitor cells accumulate with age leading to clonal expansion, termed clonal hematopoiesis (CH). CH in the general population is associated with hematopoietic neoplasms and reduced overall survival (OS), predominantly through cardiovascular adverse events (CVAE). Because androgen receptor pathway inhibitors (ARPI) used in metastatic castration-resistant prostate cancer (mCRPC) are also associated with CVAEs and because CH negatively impacted survival in an advanced solid tumor cohort, we hypothesized that CH in mCRPC may be associated with increased CVAEs and inferior survival. Experimental Design: A targeted DNA sequencing panel captured common CH mutations in pretreatment blood samples from 957 patients enrolled in Alliance A031201: a randomized trial of enzalutamide ± abiraterone/prednisone in the first-line mCRPC setting. The primary outcome was the impact of CH on OS; the secondary outcomes were progression-free survival (PFS) and CVAEs. Results: Baseline comorbidities were similar by CH status. No differences in OS/progression-free survival were detected regardless of treatment arm or the variant allele frequency threshold used to define CH [primary: 2% (normal-CH, N-CH); exploratory: 0.5% (low-CH) and 10% (high-CH, H-CH)]. Patients with H-CH (7.2%) and TET2-mutated N-CH (6.0%) had greater odds of any CVAE (14.5% vs. 4.0%; P = 0.0004 and 12.3% vs. 4.2%; P = 0.010, respectively). More major CVAEs were observed in patients with H-CH (5.8% vs. 1.9%; P = 0.042) and N-CH (3.4% vs. 1.8%; P = 0.147). Conclusions: CH did not affect survival in patients with mCRPC treated with ARPIs in A031201. H-CH and TET2-mutated CH were associated with more CVAEs. These findings inform the risk/benefit discussion about ARPIs in mCRPC.

Background and Objectives: This survey study aimed to (1) identify patient/family research priorities in pediatric-onset multiple sclerosis (POMS), and (2) delineate optimized methods for research study/clinical trials design, engagement, and implementation. Methods: Participants were as follows: (1) parents of a child (<18 years) with POMS enrolled in a national registry, (2) adolescents (13–17 years) with POMS in the registry, and (3) adults (18–40 years) with POMS receiving care at a registry affiliated clinic. Of 293 eligible participants, 192 completed surveys. Results: Experiences with health care and medications were generally positive but there remain areas of priority improvement. Incentives to participate in clinical trials included medications previously tested and in pill form, bloodwork/study visits required ⩾ every 3 months, cognitive testing ⩽1 hour, compensation for travel and time, ability to continue current multiple sclerosis (MS) medication, option to take study medication if on placebo, and individualized study feedback. Priorities for clinical research were (1) psychosocial impact, (2) cognitive/academic impact, (3) environmental risk, and (4) nutrition. Conclusions: Results highlighted the importance of a holistic approach to study design and a focus on the impact of disease on daily life to best engage patients and families in POMS clinical trials and research.

Fibromyalgia (FM) affects 2% to 8% of the general population. FM patients often experience self-stigma and feel rejected by healthcare providers and families, resulting in isolation and distressing symptoms of pain, fatigue, and poor cognitive functioning, increasing the risk of depressive symptoms. Major Depressive Disorder (MDD) is the most common comorbidity in FM patients (Any depression: 43%; MDD: 32%). Genome-wide association studies (GWAS) have identified a common genetic risk loci for major depression and fibromyalgia. Given that even minor symptoms of depression worsen the outcomes of FM patients, clinicians are challenged to identify and manage depression in these patients. However, due to overlapping symptoms, limited screening, and contamination bias, MDD often goes undiagnosed and presents a critical challenge. Unrecognized and untreated MDD in FM patients can exacerbate fatigue, sleep disturbances, and pain, reduce physical functioning, and increase the risk of developing comorbid conditions, such as substance abuse and cardiovascular disease. These comorbidities are associated with a lower treatment response rate, a higher dropout rate, and a greater risk of relapse. Clinicians may effectively identify and treat MDD in FM patients with appropriate pharmacologic agents combined with aerobic exercise and cognitive-behavioral therapies for core FM symptoms, thus significantly reducing symptom severity for both MDD and FM. Such a comprehensive approach will result in a much-improved quality of life. MedLine content was searched via PubMed to identify eligible articles between 1995 and 2023 using search terms fibromyalgia, major depressive disorder, and treatment of depression in fibromyalgia, and the most current information is presented. In this primer for clinicians caring for FM patients, we describe clinically relevant pharmacologic and non-pharmacologic management approaches for treating MDD in FM patients.