Case Series: Continued Remission of PTSD Symptoms After Discontinuation of Prazosin

Post-traumatic stress disorder is a debilitating chronic illness that affects 6 out of 100 adults after a severe trauma. The alpha-adrenergic antagonist prazosin, which is prescribed off-label for flashbacks and nightmares due to trauma, is often continued indefinitely due to reports of symptoms returning upon discontinuation. There is no standard guidance for a trial of discontinuation of prazosin due to intolerance or side effects. In this case series, three patients are started on prazosin leading to remission of trauma-related symptoms, and symptoms continue to remit after treatment for an average of about 2 years followed by discontinuation of the medication. There are many similarities in these case reports which serve to provide guidance as to when a trial of prazosin discontinuation may be warranted

Turning data into decisions : clinical decision support in orthopaedic oncology

Background: The treatment of patients with skeletal metastases is predicated on each patient’s estimated survival. In order to maximize function and quality of life, orthopaedic surgeons must carefully avoid over- or undertreatment of the disease. Unfortunately, physician estimates are notoriously inaccurate and there are no validated means by which to estimate patient survival in patients with long-bone skeletal metastases. The purpose of this thesis is to apply machine learning (ML) approaches to (1) develop a clinical decision support (CDS) tool capable of estimating survival in patients with operable skeletal metastases, and (2) establish guidelines so that this approach may be used in other relevant topics within the field of orthopaedics. Methods: We first defined the scope of the problem using data from the Karolinska Skeletal Metastasis Registry. We then developed objective criteria by which to estimate patient survival using data gleaned from the Memorial Sloan-Kettering Skeletal Metastasis Database (n=189). We employed ML techniques to find patterns within the data associated with short- and long-term survival. We chose three and 12 months because they are widely accepted to guide orthopaedic surgical decisionmaking. We developed an Artificial Neural Network (ANN), a Bayesian Belief Network (BBN), and a traditional Logistic Regression (LR) model. Each resulting model was internally validated and compared using Receiver Operator Characteristic (ROC) analysis. In addition, we performed decision analysis to determine which model, if any, was suited for clinical use. Next, we externally validated the models using Scandinavian Registry data (n=815), and again using data collected by the Societ. Italiana di Ortopedia e Traumatologia (SIOT) (n=287). We then created a web-based CDS tool as well as the infrastructure to collect prospective data on a global scale, so the models could be improved over time. Finally, we used BBN modeling to describe the hierarchical relationships between features associated with the treatment of highgrade soft tissue sarcomas (STS), and codify this complex information into a graphical representation to promote a more thorough understanding of the disease process. Results: We found that implant failures in patients with skeletal metastases remain relatively common—even in the revision setting—as patients outlive their implants. On the other hand, perioperative deaths are relatively common, indicating that an estimation of life expectancy should be part of the surgical decision making process. Using ML approaches, we found several criteria that can be used to estimate longevity in this patient population. When compared to other techniques, the ANN model was most accurate, and also resulted in highest net benefit on decision analysis, compared to the BBN and LR models. However, the BBN is the best suited to accommodate missing data, which is common in the clinical setting. The three- and 12-month BBN models were successfully externally validated using the SSMR database (Area under the ROC curve (AUC) of 0.79 and 0.76, respectively), and again using SIOT data (AUC 0.80 and 0.77). In the setting of high-grade, completely excised STS, BBN Modeling identified the first-degree associates of disease-specific survival to be the size of the primary tumor, and the presence and timing of local and distant recurrence. Conclusions: We successfully developed and validated a CDS tool designed to estimate survival in patients with operable skeletal metastases. In addition, we made this tool available to orthopaedic surgeons, worldwide, at www.pathfx.org. We also created an international skeletal metastasis registry to continue to collect data on patients with skeletal metastases. Within this framework, prognostic models have the capacity to improve over time, as treatment philosophies evolve and more effective systemic therapies become available. These techniques may now be applied to other disciplines, in an effort to turn quality data into decision support tools

ACTH: The Uninhibitable (or is it)?

Adrenal corticotropic hormone, or ACTH, is a peptide hormone secreted by the anterior pituitary gland. The full-length peptide is 39 amino acids long. ACTH signals through a G-protein linked receptor in humans, using the adenylyl cyclase pathway. Potassium and chloride channels have also been implicated in human ACTH signaling. Tetrahymena thermophila are free-living, ciliated ptotozoans. These organisms exhibit avoidance behavior toward many polycationic peptides, which serve as chemorepellents. The reason for this is unknown; however, it is hypothesized that natural predators of T. thermophila secrete polycationic peptides, and that polycation avoidance allows T. thermophila to escape predation. We obtained a number of peptides derived from ACTH, including ACTH 1-39, ACTH 1-24, ACTH 11-24, ACTH 6-24, and ACTH 1-14. We hypothesized that the more highly charged peptide derivatives would be the most effective chemorepellents. This hypothesis was proven correct, with the most highly charged ACTH derivative, ACTH 6-24, demonstrated as the most effective chemorepellent. The least charged form of ACTH, ACTH 1-39, was least effective at causing avoidance. We hypothesized that ACTH signaling in T. thermophila would use similar signaling pathways to those previously identified in humans. This, however, has not proven to be the case. We have tested G-protein inhibitors, adenylyl cyclase inhibitors, potassium channel blockers, and chloride channel blockers in T. thermphila. None of these drugs had any measurable effect on ACTH signaling. In addition, we have chelated extracellular calcium (using EGTA) and depleted ER calcium stores (using thapsigargin). Neither of these interventions inhibited ACTH signaling in this organism. Calcium channel blockers also failed to affect avoidance. This is highly unexpected, since all known chemorepellent pathways discovered in Tetrahymena to date are calcium-dependent. It is possible that ACTH is using a novel signaling pathway in T. thermophila. We hope that further testing will enable us to discover more about this signaling mechanism

Estimating Survival in Patients with Operable Skeletal Metastases: An Application of a Bayesian Belief Network

BACKGROUND: Accurate estimations of life expectancy are important in the management of patients with metastatic cancer affecting the extremities, and help set patient, family, and physician expectations. Clinically, the decision whether to operate on patients with skeletal metastases, as well as the choice of surgical procedure, are predicated on an individual patient's estimated survival. Currently, there are no reliable methods for estimating survival in this patient population. Bayesian classification, which includes bayesian belief network (BBN) modeling, is a statistical method that explores conditional, probabilistic relationships between variables to estimate the likelihood of an outcome using observed data. Thus, BBN models are being used with increasing frequency in a variety of diagnoses to codify complex clinical data into prognostic models. The purpose of this study was to determine the feasibility of developing bayesian classifiers to estimate survival in patients undergoing surgery for metastases of the axial and appendicular skeleton. METHODS: We searched an institution-owned patient management database for all patients who underwent surgery for skeletal metastases between 1999 and 2003. We then developed and trained a machine-learned BBN model to estimate survival in months using candidate features based on historical data. Ten-fold cross-validation and receiver operating characteristic (ROC) curve analysis were performed to evaluate the BNN model's accuracy and robustness. RESULTS: A total of 189 consecutive patients were included. First-degree predictors of survival differed between the 3-month and 12-month models. Following cross validation, the area under the ROC curve was 0.85 (95% CI: 0.80-0.93) for 3-month probability of survival and 0.83 (95% CI: 0.77-0.90) for 12-month probability of survival. CONCLUSIONS: A robust, accurate, probabilistic naïve BBN model was successfully developed using observed clinical data to estimate individualized survival in patients with operable skeletal metastases. This method warrants further development and must be externally validated in other patient populations

Compulsory medical intervention versus external constraint in pandemic control

Would compulsory treatment or vaccination for Covid-19 be justified? In England, there would be significant legal barriers to it. However, we offer a conditional ethical argument in favour of allowing compulsory treatment and vaccination, drawing on an ethical comparison with external constraints—such as quarantine, isolation and ‘lockdown’—that have already been authorised to control the pandemic. We argue that, if the permissive English approach to external constraints for Covid-19 has been justified, then there is a case for a similarly permissive approach to compulsory medical interventions

Carbonic anhydrase III (Car3) is not required for fatty acid synthesis and does not protect against high-fat diet induced obesity in mice

Carbonic anhydrases are a family of enzymes that catalyze the reversible condensation of water and carbon dioxide to carbonic acid, which spontaneously dissociates to bicarbonate. Carbonic anhydrase III (Car3) is nutritionally regulated at both the mRNA and protein level. It is highly enriched in tissues that synthesize and/or store fat: liver, white adipose tissue, brown adipose tissue, and skeletal muscle. Previous characterization of Car3 knockout mice focused on mice fed standard diets, not high-fat diets that significantly alter the tissues that highly express Car3. We observed lower protein levels of Car3 in high-fat diet fed mice treated with niclosamide, a drug published to improve fatty liver symptoms in mice. However, it is unknown if Car3 is simply a biomarker reflecting lipid accumulation or whether it has a functional role in regulating lipid metabolism. We focused our in vitro studies toward metabolic pathways that require bicarbonate. To further determine the role of Car3 in metabolism, we measured de novo fatty acid synthesis with in vitro radiolabeled experiments and examined metabolic biomarkers in Car3 knockout and wild type mice fed high-fat diet. Specifically, we analyzed body weight, body composition, metabolic rate, insulin resistance, serum and tissue triglycerides. Our results indicate that Car3 is not required for de novo lipogenesis, and Car3 knockout mice fed high-fat diet do not have significant differences in responses to various diets to wild type mice

Brain MR Spectroscopy Changes Precede Frontotemporal Lobar Degeneration Phenoconversion in Mapt Mutation Carriers.

Background and purposeThe objective of this study was to longitudinally investigate the trajectory of change in 1 H MRS measurements in asymptomatic MAPT mutation carriers who became symptomatic during follow-up, and to determine the time at which the neurochemical alterations accelerated during disease progression.MethodsWe identified eight MAPT mutations carriers who transitioned from asymptomatic to symptomatic disease during follow-up. All participants were longitudinally followed with an average of 7.75 years (range 4-11 years) and underwent two or more single voxel 1 H MRS examinations from the posterior cingulate voxel, with a total of 60 examinations. The rate of longitudinal change for each metabolite was estimated using linear mixed models. A flex point model was used to estimate the flex time point of the change in slope.ResultsThe decrease in the NAA/mI ratio accelerated 2.09 years prior to symptom onset, and continued to decline. A similar trajectory was observed in the presumed glial marker mI/Cr ratio accelerating 1.86 years prior to symptom onset.ConclusionsOur findings support the potential use of longitudinal 1 H MRS for monitoring the neurodegenerative progression in MAPT mutation carriers starting from the asymptomatic stage