Evaluation of Washout Periods After Dorsal Root Ganglion Stimulation Trial.

OBJECTIVE: Dorsal root ganglion stimulation (DRG-S) is a novel therapy to treat chronic pain. It has shown efficacy when delivered intermittently, suggesting a delayed washout effect exists. To measure the washout period, and to determine whether there are differences in washout times among different types of treated pain, we measured the time for pain to return at the end of the patients' one-week DRG stimulation trials. MATERIALS AND METHODS: Patients who completed a successful DRG-S trial were included. The times until 25% (t25) and 90% (t90) of baseline pain level returned were recorded. The patients were divided into neuropathic, nociceptive, and mixed pain groups for subgroup comparison. t25 and t90 were plotted in the entire cohort and subgroups using reverse Kaplan-Meier plots (failure curves) and compared using a log-rank test. RESULTS: In total, 29 consecutive patients were included. Median t25 and t90 times were 7.1 and 19.5 hours, respectively. Median (interquartile range) times were longest for the nociceptive pain group (n = 17) and shortest for the neuropathic pain group (n = 6), with the mixed-pain group (n = 6) in between (t25: 7.1 [1.7-19.4], 3.40 [1.4-8.4], and 5.7 [0.8-17.6]; t90, 22.0 [10.7-71.0], 7.6 [3.6-19.8], and 20.9 [14.2-31.2], respectively). t90 times differed significantly by pain type (p = 0.040). CONCLUSIONS: This study showed a prolonged washout period after cessation of DRG-S therapy. Washout times vary according to pain type. The observed effects are possibly due to long-term depression of pain signaling and could allow the implementation of alternative stimulation strategies with DRG-S. Further investigations evaluating DRG-S washout times are warranted.

Lead migration rate in dorsal root ganglion stimulation using lead anchoring techniques: A follow-up study.

BACKGROUND: Lead anchoring has previously been shown to reduce the rate of dorsal root ganglion stimulation (DRG-S) lead migration. The aim of this study was to assess longer-term follow-up and consistency of lead migration prevention with lead anchoring in a new cohort of patients. METHODS: We performed a retrospective chart review from September 2017 to November 2022 of all patients who had DRG-S implants at our institute to identify the number of lead migrations that occurred over this period. The first cohort consisted of patients reported on in a previous publication (implanted from September 2017 through September 2020) subdivided into unanchored or anchored lead groups. The second cohort consisted of patients implanted during or after October 2020 who were not previously reported on for whom leads were anchored using silastic anchoring only. RESULTS: At the November 2022 data cutoff, in the initial cohort, 8 migrations had occurred in unanchored leads over an average follow-up of 49 months, equating to a migration rate of 9.1% per lead. Patients with anchored leads in the initial cohort experienced 2 migrations over an average follow-up of 38 months (0.7% migration rate per lead). There were no new lead migrations in these groups over the extended follow-up reported here. The migration rate in the new cohort was similar, with 1 migration over an average follow-up of 13 months (0.5% migration rate per lead). CONCLUSION: These results underscore the necessity of anchor placement during DRG-S lead implantation to prevent lead migration.

The Practicality of Post-mortem Imaging in Prenatal, Perinatal, and Pediatric Cases.

The essential role of the autopsy is seen in its contributions to medical care, scientific research, and family counseling. Major contributions are also noted in forensic pathology as a means to determine cause-of-death for legal and medical experts. However, autopsy acceptance rates are quite low due to an array of reasons including delayed burials, faith, and moral burdening. Thus, non-invasive post-mortem imaging strategies are becoming increasingly popular. The objective of this literature review is to evaluate the strengths and weaknesses of numerous post-mortem imaging modalities and consider their benefits over the traditional autopsy. The need for expertise in image interpretation for pediatric and perinatal cases is also discussed. A variety of publications, totaling 32 pieces, were selected from available literature on the basis of relevance. These articles studied various perinatal and pediatric post-mortem imaging strategies and their applications in clinical practice. Key strategies include post-mortem MRI, post-mortem CT, fetal post-mortem sonography, post-mortem computed tomographic angiography, and three-dimensional surface scanning. There is a general consensus that no standard model for post-mortem imaging currently exists in the United States and European countries. Amongst the imaging modems studied, post-mortem MRI has been acknowledged to show the greatest promise in diagnostic accuracy for fetal age groups. Most studies demonstrated that post-mortem CT had limited use for autopsy. Post-mortem imaging strategies for autopsy have high potential given their minimal invasiveness and increasing popularity. Furthermore, it is vital to crafting a global standard procedure for post-mortem imaging for prenatal, perinatal, and pediatric cases to better understand the cause of death, decomposition factors, and effects in-utero, and to provide an alternative to traditional autopsy.

Applications and challenges of artificial intelligence in diagnostic and interventional radiology.

Purpose: Machine learning (ML) and deep learning (DL) can be utilized in radiology to help diagnosis and for predicting management and outcomes based on certain image findings. DL utilizes convolutional neural networks (CNN) and may be used to classify imaging features. The objective of this literature review is to summarize recent publications highlighting the key ways in which ML and DL may be applied in radiology, along with solutions to the problems that this implementation may face. Material and methods: Twenty-one publications were selected from the primary literature through a PubMed search. The articles included in our review studied a range of applications of artificial intelligence in radiology. Results: The implementation of artificial intelligence in diagnostic and interventional radiology may improve image analysis, aid in diagnosis, as well as suggest appropriate interventions, clinical predictive modelling, and trainee education. Potential challenges include ethical concerns and the need for appropriate datasets with accurate labels and large sample sizes to train from. Additionally, the training data should be representative of the population to which the future ML platform will be applicable. Finally, machines do not disclose a statistical rationale when expounding on the task purpose, making them difficult to apply in medical imaging. Conclusions: As radiologists report increased workload, utilization of artificial intelligence may provide improved outcomes in medical imaging by assisting, rather than guiding or replacing, radiologists. Further research should be done on the risks of AI implementation and how to most accurately validate the results.

Total energy expenditure of bottlenose dolphins (Tursiops truncatus) of different ages.

Marine mammals are thought to have an energetically expensive lifestyle because endothermy is costly in marine environments. However, measurements of total energy expenditure (TEE; kcal day-1) are available only for a limited number of marine mammals, because large body size and inaccessible habitats make TEE measurements expensive and difficult to obtain for many taxa. We measured TEE in 10 adult common bottlenose dolphins (Tursiops truncatus) living in natural seawater lagoons at two facilities (Dolphin Research Center and Dolphin Quest) using the doubly labeled water method. We assessed the relative effects of body mass, age and physical activity on TEE. We also examined whether TEE of bottlenose dolphins, and more generally of marine mammals, differs from that expected for their body mass compared with other eutherian mammals, using phylogenetic least squares (PGLS) regressions. There were no differences in body mass or TEE (unadjusted TEE and TEE adjusted for fat-free mass) between dolphins from the two facilities. Our results show that adjusted TEE decreased and fat mass increased with age. Different measures of activity were not related to age, body fat or adjusted TEE. Both PGLS and the non-phylogenetic linear regression indicate that marine mammals have an elevated TEE compared with that of terrestrial mammals. However, bottlenose dolphins expended 17.1% less energy than other marine mammals of similar body mass. The two oldest dolphins (>40 years) showed a lower TEE, similar to the decline in TEE seen in older humans. To our knowledge, this is the first study to show an age-related metabolic decline in a large non-human mammal.

A Review of Applications of Machine Learning in Mammography and Future Challenges.

BACKGROUND: The aim of this study is to systematically review the literature to summarize the evidence surrounding the clinical utility of artificial intelligence (AI) in the field of mammography. Databases from PubMed, IEEE Xplore, and Scopus were searched for relevant literature. Studies evaluating AI models in the context of prediction and diagnosis of breast malignancies that also reported conventional performance metrics were deemed suitable for inclusion. From 90 unique citations, 21 studies were considered suitable for our examination. Data was not pooled due to heterogeneity in study evaluation methods. SUMMARY: Three studies showed the applicability of AI in reducing workload. Six studies demonstrated that AI can aid in diagnosis, with up to 69% reduction in false positives and an increase in sensitivity ranging from 84 to 91%. Five studies show how AI models can independently mark and classify suspicious findings on conventional scans, with abilities comparable with radiologists. Seven studies examined AI predictive potential for breast cancer and risk score calculation. Key Messages: Despite limitations in the current evidence base and technical obstacles, this review suggests AI has marked potential for extensive use in mammography. Additional works, including large-scale prospective studies, are warranted to elucidate the clinical utility of AI.

Transfer of DNR orders to the ED from extended care facilities.

PURPOSE/OBJECTIVE: With an elderly and chronically ill patient population visiting the emergency department, it is important to know patients' wishes regarding care preferences and advanced directives. Ohio law states DNR orders must be transported with the patient when they leave an extended care facility (ECF). We reviewed the charts of ECF patients to evaluate which patients presenting to the ED had their DNR status recognized by the physician and DNR orders that were made during their hospital stay. METHODS: We prospectively enrolled patients presenting from ECFs to the ED, blinding the treating team to the purpose. We did a chart review for the presence of a DNR form, demographic data and acknowledgement of the DNR forms. RESULTS: Fifty patients were enrolled in this study. The mean age was 77.6years and 56% were female. Twenty-eight percent had a DNR order transported to the ED, but 68% had a DNR preference noted in their ECF notes. Registration only noted an advanced directive on 32% of patients (p=0.09). Eighteen percent had a DNR noted by the ED physician (p=0.42). Sixteen percent of patients had a DNR order written by an ED physician while 28% had a DNR order written by a non-ED physician during their inpatient evaluation. Thirty percent had a palliative care consult while in the hospital, but there was no significant association between DNR from the ECF and these consults. CONCLUSIONS: Hospital staff did a poor job of noting DNR preferences and ECFs were inconsistent with sending Ohio DNR forms.