Local and Systemic Peptide Therapies for Soft Tissue Regeneration: A Narrative Review.

Background: The musculoskeletal system, due to inherent structure and function, lends itself to contributing toward joint pain, whether from inflammatory disorders such as rheumatoid arthritis, degenerative diseases such as osteoarthritis, or trauma causing soft tissue injury. Administration of peptides for treatment of joint pain or inflammation is an emerging line of therapy that seeks to offer therapeutic benefits while remaining safe and relatively non-invasive. Purpose: The purpose of this study is to review the current literature on existing oral peptide agents, intra-articular peptide agents, and new developments in human trials to assess route of administration (RoA) for drug delivery in terms of soft tissue regeneration. Study Design: Narrative Review. Methods: A comprehensive literature search was conducted using the PubMed database. The search included medical subject headings (MeSH) terms related to peptide therapy, soft tissue regeneration, and RoA. Inclusion criteria comprised articles focusing on the mechanisms of action of peptides, clinical or biochemical outcomes, and review articles. Exclusion criteria included insufficient literature or studies not meeting the set evidence level. Conclusion: The review identified various peptides demonstrating efficacy in soft tissue repair. Oral and intra-articular peptides showed distinct advantages in soft tissue regeneration, with intra-articular routes providing localized effects and oral routes offering systemic benefits. However, both routes have limitations in bioavailability and absorption. Still in their infancy, further inquiries/research into the properties and efficacy of emerging peptides will be necessary before widespread use. As a viable alternative prior to surgical intervention, peptide treatments present as promising candidates for positive outcomes in soft tissue regeneration.

Comparisons between human and rodent hepatic glutathione S-Transferase activities reveal sex and species differences.

Glutathione S-transferases (GSTs) are conjugating enzymes involved in drug metabolism, antioxidant defence, and cell signalling. Herein, we investigated hepatic GST conjugation in several mouse and rat strains, including both sexes, with a direct comparison to humans.Using general and isoform-selective substrates, all mouse strains had significantly greater activities than humans for total cytosolic GST, GST-M, GST-T, and microsomal GST activities. Some strains had significantly greater GST-P activities compared to humans. Sex differences between males and females were evident in all strains for total cytosolic GST, GST-M, and GST-P, and sex differences in GST-T and microsomal GST activities within strains were noted.All rats had significantly greater activities than humans for GST-M and GST-T; only some strains were significantly greater than humans for GST-P, total cytosolic GST, and microsomal GST. Sex differences within strains showed significantly greater GST-M and GST-T activities in males compared to females. Select strains showed sex differences for total cytosolic and microsomal GST activities; there were no sex differences in GST-P activities.Significant differences in glutathione conjugation between humans and rodents exist, including sex differences. This highlights the need for careful animal selection in pre-clinical studies where GSTs are the primary metabolic pathway.

The neurosurgeon workforce: a geographical gender-focused analysis of the trends in representation of neurosurgeons and choices in training over 70 years.

OBJECTIVE: Neurosurgeons frequently move throughout their careers, with moves driven by personal and professional factors. In this study, the authors analyzed these migration trends through a dynamic migratory map and statistical review, with a particular focus on differences in education and practice patterns between male and female neurosurgeons. METHODS: A list containing all board-certified and -affiliated US neurosurgeons practicing in 2019 was obtained from the American Association of Neurological Surgeons. The list was augmented to include demographic and location information for medical school, residency, fellowship(s), and current practice for all neurosurgeons with publicly available data. Migration heatmaps were generated, and migration patterns over 10-year intervals were plotted. A web tool was additionally created to allow for dynamic visualization of this database. RESULTS: The database included 5307 neurosurgeons with a mean age of 57.2 ± 11.3 years. The female population made up 8.93% of all neurosurgeons, and were found to be more likely to complete fellowships than their male counterparts, at 54.2% and 39.1%, respectively (p < 0.0001). A total of 39.5% of all neurosurgeons completed at least one fellowship. A large proportion of currently practicing US neurosurgeons completed medical school internationally in the 1990s. Recently, there has been a trend in neurosurgeons choosing to practice in the South, emigrating from the Northeast and the Western US Census regions. By population, the Western US region trained the fewest neurosurgeons at 1 per 115,000 residents, and the Northeastern US region trained the most at 1 per 49,000. The web tool provides a simple interface to visualize the database on a world map. CONCLUSIONS: Diversity, equity, and inclusion in neurosurgery have been a strong point of discussion in recent literature, with neurosurgeons comprising one of the most gender-disparate workforces in the US medical system. This study provides additional metrics to assess these disparities to help motivate further action toward a larger, more diverse neurosurgical community.

Robotic external ventricular drain placement for acute neurosurgical care in low-resource settings: feasibility considerations and a prototype design.

OBJECTIVE: Emergency neurosurgical care in lower-middle-income countries faces pronounced shortages in neurosurgical personnel and infrastructure. In instances of traumatic brain injury (TBI), hydrocephalus, and subarachnoid hemorrhage, the timely placement of external ventricular drains (EVDs) strongly dictates prognosis and can provide necessary stabilization before transfer to a higher-level center of care that has access to neurosurgery. Accordingly, the authors have developed an inexpensive and portable robotic navigation tool to allow surgeons who do not have explicit neurosurgical training to place EVDs. In this article, the authors aimed to highlight income disparities in neurosurgical care, evaluate access to CT imaging around the world, and introduce a novel, inexpensive robotic navigation tool for EVD placement. METHODS: By combining the worldwide distribution of neurosurgeons, CT scanners, and gross domestic product with the incidence of TBI, meningitis, and hydrocephalus, the authors identified regions and countries where development of an inexpensive, passive robotic navigation system would be most beneficial and feasible. A prototype of the robotic navigation system was constructed using encoders, 3D-printed components, machined parts, and a printed circuit board. RESULTS: Global analysis showed Montenegro, Antigua and Barbuda, and Seychelles to be primary candidates for implementation and feasibility testing of the novel robotic navigation system. To validate the feasibility of the system for further development, its performance was analyzed through an accuracy study resulting in accuracy and repeatability within 1.53 ± 2.50 mm (mean ± 2 × SD, 95% CI). CONCLUSIONS: By considering regions of the world that have a shortage of neurosurgeons and a high incidence of EVD placement, the authors were able to provide an analysis of where to prioritize the development of a robotic navigation system. Subsequently, a proof-of-principle prototype has been provided, with sufficient accuracy to target the ventricles for EVD placement.

Evaluating robotic pedicle screw placement against conventional modalities: a systematic review and network meta-analysis.

OBJECTIVE: Several approaches have been studied for internal fixation of the spine using pedicle screws (PSs), including CT navigation, 2D and 3D fluoroscopy, freehand, and robotic assistance. Robot-assisted PS placement has been controversial because training requirements, cost, and previously unclear benefits. This meta-analysis compares screw placement accuracy, operative time, intraoperative blood loss, and overall complications of PS insertion using traditional freehand, navigated, and robot-assisted methods. METHODS: A systematic review was performed of peer-reviewed articles indexed in several databases between January 2000 and August 2021 comparing ≥ 2 PS insertion methods with ≥ 10 screws per treatment arm. Data were extracted for patient outcomes, including PS placement, misplacement, and accuracy; operative time, overall complications, intraoperative blood loss, postoperative hospital length of stay, postoperative Oswestry Disability Index (ODI) score, and postoperative visual analog scale (VAS) score for back pain. Risk of bias was assessed using the Newcastle-Ottawa score and Cochrane tool. A network meta-analysis (NMA) was performed to estimate PS placement accuracy as the primary outcome. RESULTS: Overall, 78 studies consisting of 6262 patients and > 31,909 PSs were included. NMA results showed that robot-assisted and 3D-fluoroscopy PS insertion had the greatest accuracy compared with freehand (p < 0.01 and p < 0.001, respectively), CT navigation (p = 0.02 and p = 0.04, respectively), and 2D fluoroscopy (p < 0.01 and p < 0.01, respectively). The surface under the cumulative ranking (SUCRA) curve method further demonstrated that robot-assisted PS insertion accuracy was superior (S = 0.937). Optimal screw placement was greatest in robot-assisted (S = 0.995) placement, and misplacement was greatest with freehand (S = 0.069) approaches. Robot-assisted placement was favorable for minimizing complications (S = 0.876), while freehand placement had greater odds of complication than robot-assisted (OR 2.49, p < 0.01) and CT-navigation (OR 2.15, p = 0.03) placement. CONCLUSIONS: The results of this NMA suggest that robot-assisted PS insertion has advantages, including improved accuracy, optimal placement, and minimized surgical complications, compared with other PS insertion methods. Limitations included overgeneralization of categories and time-dependent effects.

Using data from food challenges to inform management of consumers with food allergy: A systematic review with individual participant data meta-analysis.

BACKGROUND: Eliciting doses (EDs) (eg, ED01 or ED05 values, which are the amounts of allergen expected to cause objective symptoms in 1% and 5% of the population with an allergy, respectively) are increasingly being used to inform allergen labeling and clinical management. These values are generated from food challenge, but the frequency of anaphylaxis in response to these low levels of allergen exposure and their reproducibility are unknown. OBJECTIVE: Our aim was to determine (1) the rate of anaphylaxis in response to low-level peanut exposure and (2) the reproducibility of reaction thresholds (and anaphylaxis) at food challenge. METHODS: We conducted a systematic review and individual participant data meta-analysis of studies that reported at least 50 individuals with peanut allergy reacting to peanut at double-blind, placebo-controlled food challenge (DBPCFC) and were published between January 2010 and September 2020. Risk of bias was assessed by using National Institute for Clinical Excellence methodologic checklists. RESULTS: A total of 19 studies were included (covering a total of 3151 participants, 534 of whom subsequently underwent further peanut challenge). At individual participant data meta-analysis, 4.5% (95% CI, 1.9% to 10.1%) of individuals reacted to 5 mg or less of peanut protein with anaphylaxis (moderate heterogeneity [I2 = 57%]). Intraindividual thresholds varied by up to 3 logs, although this variation was limited to a half-log change in 71.2% (95% CI, 56.2% to 82.6%) of individuals. In all, 2.4% (95% CI, 1.1% to 5.0%) of patients initially tolerated 5 mg of peanut protein but then reacted to this dose at subsequent challenge (low heterogeneity [I2 = 16%]); none developed anaphylaxis. CONCLUSION: Around 5% of individuals reacting to an ED01 or ED05 level of exposure to peanut might develop anaphylaxis in response to that dose. This equates to 1 and 6 anaphylaxis events per 2500 patients exposed to an ED01 or ED05 dose, respectively, in the broader population of individuals with peanut allergy.

Characterization of Hepatic UDP-Glucuronosyltransferase Enzyme Abundance-Activity Correlations and Population Variability Using a Proteomics Approach and Comparison with Cytochrome P450 Enzymes.

The expression of ten major drug-metabolizing UDP-glucuronosyltransferase (UGT) enzymes in a panel of 130 human hepatic microsomal samples was measured using a liquid chromatography-tandem mass spectrometry-based approach. Simultaneously, ten cytochromes P450 and P450 reductase were also measured, and activity-expression relationships were assessed for comparison. The resulting data sets demonstrated that, with the exception of UGT2B17, 10th to 90th percentiles of UGT expression spanned 3- to 8-fold ranges. These ranges were small relative to ranges of reported mean UGT enzyme expression across different laboratories. We tested correlation of UGT expression with enzymatic activities using selective probe substrates. A high degree of abundance-activity correlation (Spearman's rank correlation coefficient > 0.6) was observed for UGT1As (1A1, 3, 4, 6) and cytochromes P450. In contrast, protein abundance and activity did not correlate strongly for UGT1A9 and UGT2B enzymes (2B4, 7, 10, 15, and 17). Protein abundance was strongly correlated for UGTs 2B7, 2B10, and 2B15. We suggest a number of factors may contribute to these differences including incomplete selectivity of probe substrates, correlated expression of these UGT2B isoforms, and the impact of splice and polymorphic variants on the peptides used in proteomics analysis, and exemplify this in the case of UGT2B10. Extensive correlation analyses identified important criteria for validating the fidelity of proteomics and enzymatic activity approaches for assessing UGT variability, population differences, and ontogenetic changes. SIGNIFICANCE STATEMENT: Protein expression data allow detailed assessment of interindividual variability and enzyme ontogeny. This study has observed that expression and enzyme activity are well correlated for hepatic UGT1A enzymes and cytochromes P450. However, for the UGT2B family, caution is advised when assuming correlation of expression and activity as is often done in physiologically based pharmacokinetic modeling. This can be due to incomplete probe substrate specificities, but may also be related to presence of inactive UGT protein materials and the effect of splicing variations.

Using machine learning and liquid crystal droplets to identify and quantify endotoxins from different bacterial species.

Detection and quantification of bacterial endotoxins is important in a range of health-related contexts, including during pharmaceutical manufacturing of therapeutic proteins and vaccines. Here we combine experimental measurements based on nematic liquid crystalline droplets and machine learning methods to show that it is possible to classify bacterial sources (Escherichia coli, Pseudomonas aeruginosa, Salmonella minnesota) and quantify concentration of endotoxin derived from all three bacterial species present in aqueous solution. The approach uses flow cytometry to quantify, in a high-throughput manner, changes in the internal ordering of micrometer-sized droplets of nematic 4-cyano-4'-pentylbiphenyl triggered by the endotoxins. The changes in internal ordering alter the intensities of light side-scattered (SSC, large-angle) and forward-scattered (FSC, small-angle) by the liquid crystal droplets. A convolutional neural network (Endonet) is trained using the large data sets generated by flow cytometry and shown to predict endotoxin source and concentration directly from the FSC/SSC scatter plots. By using saliency maps, we reveal how EndoNet captures subtle differences in scatter fields to enable classification of bacterial source and quantification of endotoxin concentration over a range that spans eight orders of magnitude (0.01 pg mL-1 to 1 µg mL-1). We attribute changes in scatter fields with bacterial origin of endotoxin, as detected by EndoNet, to the distinct molecular structures of the lipid A domains of the endotoxins derived from the three bacteria. Overall, we conclude that the combination of liquid crystal droplets and EndoNet provides the basis of a promising analytical approach for endotoxins that does not require use of complex biologically-derived reagents (e.g., Limulus amoebocyte lysate).

SCN1A variants from bench to bedside-improved clinical prediction from functional characterization.

Variants in the SCN1A gene are associated with a wide range of disorders including genetic epilepsy with febrile seizures plus (GEFS+), familial hemiplegic migraine (FHM), and the severe childhood epilepsy Dravet syndrome (DS). Predicting disease outcomes based on variant type remains challenging. Despite thousands of SCN1A variants being reported, only a minority has been functionally assessed. We review the functional SCN1A work performed to date, critically appraise electrophysiological measurements, compare this to in silico predictions, and relate our findings to the clinical phenotype. Our results show, regardless of the underlying phenotype, that conventional in silico software correctly predicted benign from pathogenic variants in nearly 90%, however was unable to differentiate within the disease spectrum (DS vs. GEFS+ vs. FHM). In contrast, patch-clamp data from mammalian expression systems revealed functional differences among missense variants allowing discrimination between disease severities. Those presenting with milder phenotypes retained a degree of channel function measured as residual whole-cell current, whereas those without any whole-cell current were often associated with DS (p = .024). These findings demonstrate that electrophysiological data from mammalian expression systems can serve as useful disease biomarker when evaluating SCN1A variants, particularly in view of new and emerging treatment options in DS.

Detection of opioids in umbilical cord lysates: an antibody-based rapid screening approach.

In pregnancy, opioids may be used medically and also misused. We hypothesized that the umbilical cord (UC) could be a good screening tool for determining opioid exposure and improving medical care. One hundred and one UC, each with 50 associated ICD9/ICD10 codes were used. Using predictive pharmacokinetic analysis we determined that opioids could be detected since last ingestion prior to birth. The UC were lysed and screened using ELISA detecting multiple opioids and their metabolites. Statistical comparisons to obstetric and neonatal outcomes were performed. Although the commercial ELISA was less sensitive in UC than blood or urine, there was perfect method selectivity as compared to a subset of cords designated positive or negative by clinical diagnostics, so our results are accurate and reliable. Absolute quantitation was not possible because the antibody cross reacts with multiple compounds, but 'low' or 'high' levels of exposure were assigned. Prevalence of opioids was 11%, which reduced to 7% when cesarean-section births were eliminated. For non-cesarean-section infants adjusted for preterm birth, advanced maternal age and smoking (independent risk factors), opioids were significantly associated with intra-uterine growth restriction (p = 0.017) and admission to neonatal intensive care (p = 0.002). UC can be collected noninvasively and rapidly providing a reliable tools for semi-quantitative opioid screening using ELISA. Moreover, as UC are usually discarded collection presents few technical or safety concerns for staff or patients. Further development of this methodology may provide a rapid, noninvasive clinical screening tool to identify NAS and/or opioid use in late pregnancy.

The effects of UDP-sugars, UDP and Mg2+on uridine diphosphate glucuronosyltransferase activity in human liver microsomes.

1. The UDP-glucuronosyltransferase (UGT) enzymes are important in the metabolism, elimination and detoxification of many xenobiotics and endogenous compounds. As extrapolation of in vitro kinetics of drug metabolizing enzymes to predict in vivo clearance rates becomes more sophisticated, it is important to ensure proper optimization of enzyme assays. The luminal location of the enzyme active site (i.e. latency), and the complexity of UGT kinetics, results in consistent under-prediction of clearance of drugs metabolized by glucuronidation. 2. We examined inhibition of UGT activity in alamethicin-disrupted human liver microsomes (HLM) by uridine diphosphate (UDP), a UGT reaction product, and its reversal by Mg2+ ions. We also determined whether UDP-sugars other than the co-substrate UDP-glucuronic acid (UDP-GlcA) affected glucuronidation. 3. We show that other UDP-sugars do not significantly influence glucuronidation. We also demonstrate that UDP inhibits HLM UGT activity and that this is reversed by including Mg2+ in the assay. The Mg2+ effect can be offset using EDTA, and is dependent on the concentration of UDP-GlcA in the assay. 4. We propose that formation of a Mg2+-UDP complex prevents UDP from affecting the enzyme. Our results suggest that 5 mM UDP-GlcA and 10 mM Mg2+ be used for UGT assays in fully disrupted HLM.

Reverse innovation: an opportunity for strengthening health systems.

BACKGROUND: Canada, when compared to other OECD countries, ranks poorly with respect to innovation and innovation adoption while struggling with increasing health system costs. As a result of its failure to innovate, the Canadian health system will struggle to meet the needs and demands of both current and future populations. The purpose of this initiative was to explore if a competition-based reverse innovation challenge could mobilize and stimulate current and future leaders to identify and lead potential reverse innovation projects that address health system challenges in Canada. METHODS: An open call for applications took place over a 4-month period. Applicants were enticed to submit to the competition with a $50,000 prize for the top submission to finance their project. Leaders from a wide cross-section of sectors collectively developed evaluation criteria and graded the submissions. The criteria evaluated: proof of concept, potential value, financial impact, feasibility, and scalability as well as the use of prize money and innovation team. RESULTS: The competition received 12 submissions from across Canada that identified potential reverse innovations from 18 unique geographical locations that were considered developing and/or emerging markets. The various submissions addressed health system challenges relating to education, mobile health, aboriginal health, immigrant health, seniors health and women's health and wellness. Of the original 12 submissions, 5 finalists were chosen and publically profiled, and 1 was chosen to receive the top prize. CONCLUSIONS: The results of this initiative demonstrate that a competition that is targeted to reverse innovation does have the potential to mobilize and stimulate leaders to identify reverse innovations that have the potential for system level impact. The competition also provided important insights into the capacity of Canadian students, health care providers, entrepreneurs, and innovators to propose and implement reverse innovation in the context of the Canadian health system.

Topological Data Analysis for Particulate Gels.

Soft gels, formed via the self-assembly of particulate materials, exhibit intricate multiscale structures that provide them with flexibility and resilience when subjected to external stresses. This work combines particle simulations and topological data analysis (TDA) to characterize the complex multiscale structure of soft gels. Our TDA analysis focuses on the use of the Euler characteristic, which is an interpretable and computationally scalable topological descriptor that is combined with filtration operations to obtain information on the geometric (local) and topological (global) structure of soft gels. We reduce the topological information obtained with TDA using principal component analysis (PCA) and show that this provides an informative low-dimensional representation of the gel structure. We use the proposed computational framework to investigate the influence of gel preparation (e.g., quench rate, volume fraction) on soft gel structure and to explore dynamic deformations that emerge under oscillatory shear in various response regimes (linear, nonlinear, and flow). Our analysis provides evidence of the existence of hierarchical structures in soft gels, which are not easily identifiable otherwise. Moreover, our analysis reveals direct correlations between topological changes of the gel structure under deformation and mechanical phenomena distinctive of gel materials, such as stiffening and yielding. In summary, we show that TDA facilitates the mathematical representation, quantification, and analysis of soft gel structures, extending traditional network analysis methods to capture both local and global organization.

Dynamic Expansion and Contraction of Multiple Sclerosis T2-weighted Hyperintense Lesions are Present Below the Threshold of Visual Perception.

BACKGROUND AND PURPOSE: The study of T2-weighted hyperintense lesions resulting from autoimmune inflammatory injury and associated volumes within the CNS remains fundamental to the diagnosis and disease surveillance of multiple sclerosis (MS). We investigated the dynamic changes of individual T2-weighted hyperintense MS lesions on MRI and hypothesized that variations may be present below the threshold of visual perception when evaluating longitudinal data. MATERIALS AND METHODS: A retrospective study was performed of people with MS, incorporating data from three consecutive MRI time points acquired within a single academic center. All included MRI studies lacked formal imaging interpretations of newly enlarging or contracting T2-weighted hyperintensities. Well defined, non-coalescing, individual T2-weighted hyperintense lesions were targeted. A total of 8-12 lesions were randomly selected in a blinded fashion at MRI time point 1 and 3-dimensional lesion volumes followed over MRI time points 2 and 3. The impact of treatment on lesion expansion and relationship to brain MRI advancement, patient-reported progression of disease, and physician-identified progression was also studied. RESULTS: The study cohort was comprised of 115 people (81 (70.4%) female; mean disease duration of 6.62 years(y) (standard deviation: 6.68y)) who were primarily White (79.1%). A total of 1,426 focal T2-weighted hyperintense MS lesions were identified on MRI time point 1 and longitudinally followed over MRI time points 2 and 3. In the evaluation of raw changes in individual T2-weighted hyperintense lesion volumes from MRI time point 1 to MRI time point 2, a similar number of individuals were observed with predominantly expanding (49/115; 42.6%) or contracting (51/115; 44.3%) lesions. However, the majority of lesions expanded in volume (48/115; 41.7%) versus those that contracted (45/115; 39.1%) when evaluating MRI time point 3 to time point 1. Those individuals not on active treatment had a 67.15% reduction in the odds of more individual lesions predominantly contracting in volume relative to those on low-efficacy disease modifying therapy treatment (95% CI=[-83.89, -33.01], p=0.0008) and 74.02% reduction for those on high-efficacy treatment (95% CI=[-87.37%,-46.56%], p<0.0001). CONCLUSIONS: Dynamic changes in T2-weighted hyperintense lesions are abundant, occurring below the threshold of visual perception and are present more frequently in untreated individuals. ABBREVIATIONS: MS = multiple sclerosis; DMT = disease modifying therapy; 2D = 2-dimensional; 3D = 3-dimensional; LMS = Lambda, Mu, and Sigma.

Generative artificial intelligence versus clinicians: Who diagnoses multiple sclerosis faster and with greater accuracy?

BACKGROUND: Those receiving the diagnosis of multiple sclerosis (MS) over the next ten years will predominantly be part of Generation Z (Gen Z). Recent observations within our clinic suggest that younger people with MS utilize online generative artificial intelligence (AI) platforms for personalized medical advice prior to their first visit with a specialist in neuroimmunology. The use of such platforms is anticipated to increase given the technology driven nature, desire for instant communication, and cost-conscious nature of Gen Z. Our objective was to determine if ChatGPT (Generative Pre-trained Transformer) could diagnose MS in individuals earlier than their clinical timeline, and to assess if the accuracy differed based on age, sex, and race/ethnicity. METHODS: People with MS between 18 and 59 years of age were studied. The clinical timeline for people diagnosed with MS was retrospectively identified and simulated using ChatGPT-3.5 (GPT-3.5). Chats were conducted using both actual and derivatives of their age, sex, and race/ethnicity to test diagnostic accuracy. A Kaplan-Meier survival curve was estimated for time to diagnosis, clustered by subject. The p-value testing for differences in time to diagnosis was accomplished using a general Wilcoxon test. Logistic regression (subject-specific intercept) was used to capture intra-subject correlation to test the accuracy prior to and after the inclusion of MRI data. RESULTS: The study cohort included 100 unique people with MS. Of those, 50 were members of Gen Z (38 female; 22 White; mean age at first symptom was 20.6 years (y) (standard deviation (SD)=2.2y)), and 50 were non-Gen Z (34 female; 27 White; mean age at first symptom was 37.0y (SD=10.4y)). In addition, a total of 529 people that represented digital simulations of the original cohort of 100 people (333 female; 166 White; 136 Black/African American; 107 Asian; 120 Hispanic, mean age at first symptom was 31.6y (SD=12.4y)) were generated allowing for 629 scripted conversations to be analyzed. The estimated median time to diagnosis in clinic was significantly longer at 0.35y (95% CI=[0.28, 0.48]) versus that by ChatGPT at 0.08y (95% CI=[0.04, 0.24]) (p<0.0001). There was no difference in the diagnostic accuracy between ages and by race/ethnicity prior to the inclusion of MRI data. However, prior to including the MRI data, males had a 47% less likely chance of a correct diagnosis relative to females (p=0.05). Post-MRI data inclusion within GPT-3.5, the odds of an accurate diagnosis was 4.0-fold greater for Gen Z participants, relative to non-Gen Z participants (p=0.01) with the diagnostic accuracy being 68% less in males relative to females (p=0.009), and 75% less for White subjects, relative to non-White subjects (p=0.0004). CONCLUSION: Although generative AI platforms enable rapid information access and are not principally designed for use in healthcare, an increase in use by Gen Z is anticipated. However, the obtained responses may not be generalizable to all users and bias may exist in select groups.

Treatment transitions in neuromyelitis optica spectrum disorder increase risk for disease advancement.

BACKGROUND: People with neuromyelitis optica spectrum disorder (PwNMOSD) commonly switch between disease modifying therapies, yet the consequence of transitions remains unknown. We aimed to understand if treatment transitions due to medical, non-medical, and tolerability reasons were related to disease progression. METHODS: A retrospective study of medical records for PwNMOSD was performed between 2008 and 2022. A comprehensive clinical timeline was created for each person including details related to treatment history and associated clinical and radiological outcomes (i.e., hospital admission, relapses, and MRI advancement). If a transition occurred, the reason for the switch was categorized as being due to medical, non-medical, or tolerability issues. A proportional hazards model was created, and the assumptions were tested based on weighted residuals. RESULTS: The cohort included 164 aquaporin-4 IgG positive NMOSD subjects with 89 (79 female; median disease duration (range) = 10.1 years (y) (1.7-32.8)) people switching therapies at least once (once: 42; twice: 26; three times: 12; four times: 6; 5 or more times: 3). A similar amount of higher efficacy therapies was used by PwNMOSD that switched due to a non-medical/tolerability or a medical-related reason. The results of the recurrent event survival analysis revealed that after an initial transition due to non-medical/tolerability reasons, the risk of a hospital admission, relapse, and MRI advancement decreases by 40.3 % (p = 0.005), 53.1 % (p = 0.002), and 65.9 % (p = 0.005), respectively. However, with each additional discontinuation due to non-medical/tolerability reasons, the risk of hospitalization increased by 25.2 % (p = 0.0003) and risk for MRI advancement increased by 41.9 % (p = 0.03). For transitions due to medical reasons, a significant increased risk of MRI advancement by 32.2 % (p = 0.005) for the first switch was identified with no associated observed risk with each additional discontinuation (p = 0.33). Within the first six months after stopping a medication due to non-medical/tolerability reasons, the rate of starting a new medication was less (p<0.0001) when compared to a discontinuation due to a medical-related event. CONCLUSIONS: The risk associated with the time course of treatment transitions for people with NMOSD may assist in transforming the way healthcare providers bridge the gap between therapies and the approach to the timing of a switch. These data highlight additional factors that may be equatable to the efficacy of prescribed treatments in the prevention of acute neurological events.

Factors associated with the misdiagnosis of neuromyelitis optica spectrum disorder.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is a rare autoimmune condition that is associated with severe disability. Approximately 40% of individuals are misdiagnosed with multiple sclerosis (MS) or other diseases. We aimed to define factors that influence the misdiagnosis of people with NMOSD and provide strategies for reducing error rates. METHODS: A retrospective study was performed involving all people with a confirmed diagnosis of NMOSD within a single academic institution. Comprehensive clinical timelines were constructed for each individual that included presenting symptoms, provider type and timing of evaluations, aquaporin 4-IgG (AQP4) results, and MRI scans. Two-sample comparisons of continuous and categorial variables were performed for people accurately diagnosed with NMOSD and those originally misdiagnosed with another medical condition. A subanalysis of only AQP4-IgG positive people was also performed. RESULTS: The study cohort included 199 people fulfilling International Panel criteria for NMOSD with 71 people (62 female; mean age at first symptom presentation (standard deviation (SD)) = 32.8 years (y) (SD 16.1)) being initially misdiagnosed and 128 people (106 female; 41.14y (SD 15.41)) who were accurately diagnosed. Of the 199 people with NMOSD, 166 had a positive serostatus. Identified factors associated with misdiagnosis, regardless of AQP4-IgG serostatus, were the presence of protracted nausea/vomiting/hiccups without any accompanying neurological symptoms, 23 (32.4%) versus 16 (12.5%) (p = 0.001), a longer median (range) time to see a neuroimmunology specialist 4.2y (0.14-31.8) versus 0.5y (0.0-21.2) (p<0.0001), and a delay in acquiring an MRI study, 4.7y (0.0-27.3) versus 0.3y (0.0-20.2) (p<0.0001). A greater proportion of people misdiagnosed were identified with a negative live-cell based AQP4-IgG serum test result, 13/13 (100%) versus 22/114 (19.3%) (p<0.0001). Additionally, the mean (SD) time between a first negative and successive live-cell based AQP4-IgG positive test result was greater for people misdiagnosed with another condition, 3.9y (SD 5.0) versus 1.5y (SD 2.1) (p = 0.01). Although not significant between groups, a rash was also reported in 63/199 people with NMOSD, with 31/63 having an anti-nuclear antibody titer ≥ 1:160. CONCLUSION: Defined factors can help guide both generalists and specialists in the pursuit of strategies aimed at efficiently diagnosing those with NMOSD such that effective care can be delivered.

High-efficacy therapies reduce clinical and radiological events more effectively than traditional treatments in neuromyelitis optica spectrum disorder.

BACKGROUND: People with neuromyelitis optica spectrum disorder (pwNMOSD) experience debilitating neurological attacks, resulting in permanent disability. OBJECTIVE: To evaluate if high-efficacy treatment was better than traditional agents at preventing disease advancement in pwNMOSD. METHODS: A retrospective study of pwNMOSD at one academic center was performed. Timelines were created for treatments subjects were exposed to along with clinical/radiological events related to disease worsening. High-efficacy treatments included eculizumab, inebilizumab, satralizumab, rituximab, ocrelizumab, tocilizumab, and sarilumab while therapies such as azathioprine, methotrexate, cyclophosphamide, and mycophenolate mofetil were classified as traditional agents. Poisson regression and mixed effects logistics models were constructed, and a subject-specific random intercept was used for intrasubject correlation. RESULTS: Of 189 pwNMOSD identified, 161 were aquaporin-4 IgG positive (AQP4 +) with 92 (77 female; median disease duration (MDD) (range) of 6.6 years (y) (1.2-18.6)) exposed only to high-efficacy therapy, 33 (28 female; 10.4 y (0.8-32.7)) only to traditional therapy, and 64 (54 female; 10.8 y (0.7-20.2)) to both. High-efficacy treatments reduced the rate of MRI advancement by 62.4% (95% CrI = [- 86.9%, - 16.8%]), relapses by 99.8% (95% CrI = [- 99.9%, - 99.6%]), and hospitalizations by 99.3% (95% CrI = [- 99.6%, - 98.8%]) when compared to traditional treatments. For AQP4 + subjects, a 655.7-fold increase in the odds of new spinal cord lesion development (95% CrI = [+ 37.4-fold, + 3239.5-fold]) was observed with traditional agents (p < 0.0001). CONCLUSION: High-efficacy treatments maximize opportunity for preventing disease advancement in newly diagnosed and established pwNMOSD.

The State of Machine Learning in Outcomes Prediction of Transsphenoidal Surgery: A Systematic Review.

The purpose of this analysis is to assess the use of machine learning (ML) algorithms in the prediction of postoperative outcomes, including complications, recurrence, and death in transsphenoidal surgery. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically reviewed all papers that used at least one ML algorithm to predict outcomes after transsphenoidal surgery. We searched Scopus, PubMed, and Web of Science databases for studies published prior to May 12, 2021. We identified 13 studies enrolling 5,048 patients. We extracted the general characteristics of each study; the sensitivity, specificity, area under the curve (AUC) of the ML models developed as well as the features identified as important by the ML models. We identified 12 studies with 5,048 patients that included ML algorithms for adenomas, three with 1807 patients specifically for acromegaly, and five with 2105 patients specifically for Cushing's disease. Nearly all were single-institution studies. The studies used a heterogeneous mix of ML algorithms and features to build predictive models. All papers reported an AUC greater than 0.7, which indicates clinical utility. ML algorithms have the potential to predict postoperative outcomes of transsphenoidal surgery and can improve patient care. Ensemble algorithms and neural networks were often top performers when compared with other ML algorithms. Biochemical and preoperative features were most likely to be selected as important by ML models. Inexplicability remains a challenge, but algorithms such as local interpretable model-agnostic explanation or Shapley value can increase explainability of ML algorithms. Our analysis shows that ML algorithms have the potential to greatly assist surgeons in clinical decision making.

Trends in Technology for Pedicle Screw Placement: A Temporal Meta-Analysis.

STUDY DESIGN: Systematic Review. OBJECTIVE: We sought to determine which method of the pedicle screw (PS) placement is most accurate and understand how the development of subsequent generations of robotic systems has changed placement accuracy over time. SUMMARY OF BACKGROUND DATA: Previous studies have demonstrated the success of robotic PS placement, but how this accuracy compares to other methods is unclear. METHODS: A systematic review following PRISMA Guidelines was performed on articles published between January 2000 and August 2021, comparing PS insertion methods with at least 10 screws per study arm. Single and multiple-arm trials were included. Data were extracted for patient outcomes, including optimal PS placement, misplacement, and accuracy. The logit-event rate of misplacement was calculated for each study. P values were adjusted for multiple comparisons using the Tukey post hoc correction. RESULTS: Our search revealed 127 studies, and 156 comparative arms, with 77,360 pedicle screws placed using five different modalities. Meta-regression of pooled accuracy revealed no significant changes in PS accuracy over time for freehand, 2D fluoroscopic navigation, 3D fluoroscopic navigation, and computed tomography navigation. Robotic navigation had a significant increase in accuracy over time ( P =0.036). Pooled misplacement rates were also compared across all modalities. Robotics was found to have the lowest rates of misplacement for PS compared to freehand ( P =0.0015) and 2D fluoroscopic navigation ( P =0.026). CONCLUSION: Our analysis is the largest study to date on pedicle screw placement. Pedicle screw placement through robotics was found to be superior due to its low misplacement rates compared with other modalities. Intraoperative 3D fluoroscopic navigation was found to have comparable misplacement rates. In addition, pedicle screw placement accuracy with robotics has continued to improve over time. This speaks to both the stability of the technology and the potential for continued improvement with new and more accurate robotic systems.