Video-Based Performance Analysis in Pituitary Surgery-Part 1: Surgical Outcomes.

BACKGROUND: Endoscopic pituitary adenoma surgery has a steep learning curve, with varying surgical techniques and outcomes across centers. In other surgeries, superior performance is linked with superior surgical outcomes. This study aimed to explore the prediction of patient-specific outcomes using surgical video analysis in pituitary surgery. METHODS: Endoscopic pituitary adenoma surgery videos from a single center were annotated by experts for operative workflow (3 surgical phases and 15 surgical steps) and operative skill (using modified Objective Structured Assessment of Technical Skills [mOSATS]). Quantitative workflow metrics were calculated, including phase duration and step transitions. Poisson or logistic regression was used to assess the association of workflow metrics and mOSATS with common inpatient surgical outcomes. RESULTS: 100 videos from 100 patients were included. Nasal phase mean duration was 24 minutes and mean mOSATS was 21.2/30. Mean duration was 34 minutes and mean mOSATS was 20.9/30 for the sellar phase, and 11 minutes and 21.7/30, respectively, for the closure phase. The most common adverse outcomes were new anterior pituitary hormone deficiency (n = 26), dysnatremia (n = 24), and cerebrospinal fluid leak (n = 5). Higher mOSATS for all 3 phases and shorter operation duration were associated with decreased length of stay (P = 0.003 &P < 0.001). Superior closure phase mOSATS were associated with reduced postoperative cerebrospinal fluid leak (P < 0.001), and superior sellar phase mOSATS were associated with reduced postoperative visual deterioration (P = 0.041). CONCLUSIONS: Superior surgical skill and shorter surgical time were associated with superior surgical outcomes, at a generic and phase-specific level. Such video-based analysis has promise for integration into data-driven training and service improvement initiatives.

Empowering Early Career Neurosurgeons in the Critical Appraisal of Artificial Intelligence and Machine Learning: The Design and Evaluation of a Pilot Course.

BACKGROUND: Artificial intelligence (AI) is expected to play a greater role in neurosurgery. There is a need for neurosurgeons capable of critically appraising AI literature to evaluate its implementation or communicate information to patients. However, there are a lack of courses delivered at a level appropriate for individuals to develop such skills. We assessed the impact of a 2-day (non-credit bearing) online digital literacy course on the ability of individuals to critically appraise AI literature in neurosurgery. METHODS: We performed a prospective, quasi-experimental non-randomized, controlled study with an intervention arm comprising individuals enrolled in our 2-day digital health literacy course and a waiting-list control arm used for comparison. We assessed participants' pre- and post-course knowledge, confidence, and course acceptability using Qualtrics surveys designed for the purpose of this study. RESULTS: A total of 62 individuals (33 participants, 29 waitlist controls), including neurosurgical trainees and both undergraduate and post-graduate students, attended the course and completed the pre-course survey. The 2 groups did not vary significantly in terms of age or demographics. Following the course, participants significantly improved in their knowledge of AI (mean difference = 3.86, 95% CI = 2.97-4.75, P-value < 0.0001) and confidence in critically appraising literature using AI (P-value = 0.002). Similar differences in knowledge (mean difference = 3.15, 95% CI = 1.82-4.47, P-value < 0.0001) and confidence (P-value < 0.0001) were found when compared to the control group. CONCLUSIONS: Bespoke courses delivered at an appropriate level can improve clinicians' understanding of the application of AI in neurosurgery, without the need for in-depth technical knowledge or programming skills.

Mapping the Clinical Pathway for Patients Undergoing Vestibular Schwannoma Resection.

BACKGROUND: The introduction of the electronic health record (EHR) has improved the collection and storage of patient information, enhancing clinical communication and academic research. However, EHRs are limited by data quality and the time-consuming task of manual data extraction. This study aimed to use process mapping to help identify critical data entry points within the clinical pathway for patients with vestibular schwannoma (VS) ideal for structured data entry and automated data collection to improve patient care and research. METHODS: A 2-stage methodology was used at a neurosurgical unit. Process maps were developed using semi-structured interviews with stakeholders in the management of VS resection. Process maps were then retrospectively validated against EHRs for patients admitted between August 2019 and December 2021, establishing critical data entry points. RESULTS: In the process map development, 20 stakeholders were interviewed. Process maps were validated against EHRs of 36 patients admitted for VS resection. Operative notes, surgical inpatient reviews (including ward rounds), and discharge summaries were available for all patients, representing critical data entry points. Areas for documentation improvement were in the preoperative clinics (30/36; 83.3%), preoperative skull base multidisciplinary team (32/36; 88.9%), postoperative follow-up clinics (32/36; 88.9%), and postoperative skull base multidisciplinary team meeting (29/36; 80.6%). CONCLUSIONS: This is a first use to our knowledge of a 2-stage methodology for process mapping the clinical pathway for patients undergoing VS resection. We identified critical data entry points that can be targeted for structured data entry and for automated data collection tools, positively impacting patient care and research.

Design, infectability, and transcriptomic analysis of transregionally differentiated and scalable lung organoids derived from adult bronchial cells.

The lung is a primary target for many lethal respiratory viruses, leading to significant global mortality. Current organoid models fail to completely mimic the cellular diversity and intricate tubular and branching structures of the human lung. Lung organoids derived from adult primary cells have so far only included cells from the input cell region, proximal or distal. Existing models are expensive. They often require cells from invasive deep lung tissue biopsies. The present study aimed to address these limitations. The lung organoids obtained using an original protocol exhibited transregional differentiation and were derived from relatively more accessible primary cells from the trachea/bronchi. Immortal bronchial cell lines were also used to simplify organoid fabrication and improve its scalability. The lung organoids are formed starting from bronchial cells with fibroblasts feeder cells in an alginate hydrogel coated with base membrane zone proteins. Characterizations were performed using bulk RNA sequencing and tandem mass tags. The resulting organoids express markers of different lung regions and mimic to some extent the tubular and branching morphology of the lung. The proteomic profile of organoid from primary cells and from cell lines was found to evolve towards that of mature lung tissue. Upregulated genes were mostly related to the respiratory system, tube development, and various aspects of respiratory viral infections. Infection with SARS-CoV-2 and influenza H1N1 was successful and did not require organoid disassembly. The organoids matured within 21 days and did not require complex or expensive culture methods. Transregionally differentiated lung organoid may find applications for the study of emerging or re-emerging viral infections and fostering the development of novel in-vitro therapeutic strategies.

Mapping patient education encounters in elective surgery: a cohort study and cross-sectional survey.

OBJECTIVE: Develop a process map of when patients learn about their proposed surgery and what resources patients use to educate themselves. DESIGN: A mixed methods design, combining semistructured stakeholder interviews, quantitative validation using electronic healthcare records (EHR) in a retrospective cohort and a cross-sectional patient survey. SETTING: A single surgical centre in the UK. PARTICIPANTS: Fourteen members of the spinal multidisciplinary team were interviewed to develop the process map.This process map was validated using the EHR of 50 patients undergoing elective spine surgery between January and June 2022. Postprocedure, feedback was gathered from 25 patient surveys to identify which resources they used to learn about their spinal procedure. Patients below the age of 18 or who received emergency surgery were excluded. INTERVENTIONS: Elective spine surgery and patient questionnaires given postoperatively either on the ward or in follow-up clinic. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was the percentage of the study cohort that was present at encounters on the process map. Key timepoints were defined if >80% of patients were present. The secondary outcome was the percentage of the study cohort that used educational resources listed in the patient questionnaire. RESULTS: There were 342 encounters which occurred across the cohort, with 16 discrete event categories identified. The initial surgical clinic (88%), anaesthetic preoperative assessment (96%) and admission for surgery (100%) were identified as key timepoints. Surveys identified that patients most used verbal information from their surgeon (100%) followed by written information from their surgeon (52%) and the internet (40%) to learn about their surgery. CONCLUSIONS: Process mapping is an effective method of illustrating the patient pathway. The initial surgical clinic, anaesthetic preoperative assessment and surgical admission are key timepoints where patients receive information. This has future implications for guiding patient education interventions to focus at key timepoints.

A randomised, double blind, placebo-controlled trial of a two-week course of dexamethasone for adult patients with a symptomatic Chronic Subdural Haematoma (Dex-CSDH trial).

Background: Chronic subdural haematoma is a collection of 'old blood' and its breakdown products in the subdural space and predominantly affects older people. Surgical evacuation remains the mainstay in the management of symptomatic cases. Objective: The Dex-CSDH (DEXamethasone in Chronic SubDural Haematoma) randomised trial investigated the clinical effectiveness and cost-effectiveness of dexamethasone in patients with a symptomatic chronic subdural haematoma. Design: This was a parallel, superiority, multicentre, pragmatic, randomised controlled trial. Assigned treatment was administered in a double-blind fashion. Outcome assessors were also blinded to treatment allocation. Setting: Neurosurgical units in the UK. Participants: Eligible participants included adults (aged ≥ 18 years) admitted to a neurosurgical unit with a symptomatic chronic subdural haematoma confirmed on cranial imaging. Interventions: Participants were randomly assigned in a 1 : 1 allocation to a 2-week tapering course of dexamethasone or placebo alongside standard care. Main outcome measures: The primary outcome was the Modified Rankin Scale score at 6 months dichotomised to a favourable (score of 0-3) or an unfavourable (score of 4-6) outcome. Secondary outcomes included the Modified Rankin Scale score at discharge and 3 months; number of chronic subdural haematoma-related surgical interventions undertaken during the index and subsequent admissions; Barthel Index and EuroQol 5-Dimension 5-Level utility index score reported at discharge, 3 months and 6 months; Glasgow Coma Scale score reported at discharge and 6 months; mortality at 30 days and 6 months; length of stay; discharge destination; and adverse events. An economic evaluation was also undertaken, during which the net monetary benefit was estimated at a willingness-to-pay threshold of £20,000 per quality-adjusted life-year. Results: A total of 748 patients were included after randomisation: 375 were assigned to dexamethasone and 373 were assigned to placebo. The mean age of the patients was 74 years and 94% underwent evacuation of their chronic subdural haematoma during the trial period. A total of 680 patients (91%) had 6-month primary outcome data available for analysis: 339 in the placebo arm and 341 in the dexamethasone arm. On a modified intention-to-treat analysis of the full study population, there was an absolute reduction in the proportion of favourable outcomes of 6.4% (95% confidence interval 11.4% to 1.4%; p = 0.01) in the dexamethasone arm compared with the control arm at 6 months. At 3 months, the between-group difference was also in favour of placebo (-8.2%, 95% confidence interval -13.3% to -3.1%). Serious adverse events occurred in 60 out of 375 (16.0%) in the dexamethasone arm and 24 out of 373 (6.4%) in the placebo arm. The net monetary benefit of dexamethasone compared with placebo was estimated to be -£97.19. Conclusions: This trial reports a higher rate of unfavourable outcomes at 6 months, and a higher rate of serious adverse events, in the dexamethasone arm than in the placebo arm. Dexamethasone was also not estimated to be cost-effective. Therefore, dexamethasone cannot be recommended for the treatment of chronic subdural haematoma in this population group. Future work and limitations: A total of 94% of individuals underwent surgery, meaning that this trial does not fully define the role of dexamethasone in conservatively managed haematomas, which is a potential area for future study. Trial registration: This trial is registered as ISRCTN80782810. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 13/15/02) and is published in full in Health Technology Assessment; Vol. 28, No. 12. See the NIHR Funding and Awards website for further award information.

Chronic subdural haematoma is one of the most common conditions managed in adult neurosurgery and mainly affects older people. It is an 'old' collection of blood and blood breakdown products found on the surface of the brain. Surgery to drain the liquid collection is effective, with most patients improving. Given that inflammation is involved in the disease process, a commonly used steroid, dexamethasone, has been used alongside surgery or instead of surgery since the 1970s. However, there is no consensus or high-quality studies confirming the effectiveness of dexamethasone for the treatment of chronic subdural haematoma. This study was designed to determine the effectiveness of adding dexamethasone to the normal treatment for patients with a symptomatic chronic subdural haematoma. The benefit of adding dexamethasone was measured using a disability score called the Modified Rankin Scale, which can be divided into favourable and unfavourable outcomes. This was assessed at 6 months after entry into the study. In total, 748 adults with a symptomatic chronic subdural haematoma treated in neurosurgical units in the UK participated. Each participant had an equal chance of receiving either dexamethasone or a placebo because they were assigned randomly. Neither the patients nor the investigators knew who received dexamethasone and who received placebo. Most patients in both groups had an operation to drain the haematoma and experienced significant functional improvement at 6 months compared with their initial admission to hospital. However, patients who received dexamethasone had a lower chance than patients who received placebo of favourable recovery at 6 months. Specifically, 84% of patients who received dexamethasone had recovered well at 6 months, compared with 90% of patients who received placebo. There were more complications in the group that received dexamethasone. This trial demonstrates that adding dexamethasone to standard treatment reduced the chance of a favourable outcome compared with standard treatment alone. Therefore, this study does not support the use of dexamethasone in treating patients with a symptomatic chronic subdural haematoma.

PitSurgRT: real-time localization of critical anatomical structures in endoscopic pituitary surgery.

PURPOSE: Endoscopic pituitary surgery entails navigating through the nasal cavity and sphenoid sinus to access the sella using an endoscope. This procedure is intricate due to the proximity of crucial anatomical structures (e.g. carotid arteries and optic nerves) to pituitary tumours, and any unintended damage can lead to severe complications including blindness and death. Intraoperative guidance during this surgery could support improved localization of the critical structures leading to reducing the risk of complications. METHODS: A deep learning network PitSurgRT is proposed for real-time localization of critical structures in endoscopic pituitary surgery. The network uses high-resolution net (HRNet) as a backbone with a multi-head for jointly localizing critical anatomical structures while segmenting larger structures simultaneously. Moreover, the trained model is optimized and accelerated by using TensorRT. Finally, the model predictions are shown to neurosurgeons, to test their guidance capabilities. RESULTS: Compared with the state-of-the-art method, our model significantly reduces the mean error in landmark detection of the critical structures from 138.76 to 54.40 pixels in a 1280 × 720-pixel image. Furthermore, the semantic segmentation of the most critical structure, sella, is improved by 4.39% IoU. The inference speed of the accelerated model achieves 298 frames per second with floating-point-16 precision. In the study of 15 neurosurgeons, 88.67% of predictions are considered accurate enough for real-time guidance. CONCLUSION: The results from the quantitative evaluation, real-time acceleration, and neurosurgeon study demonstrate the proposed method is highly promising in providing real-time intraoperative guidance of the critical anatomical structures in endoscopic pituitary surgery.

Can ChatGPT outperform a neurosurgical trainee? A prospective comparative study.

PURPOSE: This study aimed to compare the performance of ChatGPT, a large language model (LLM), with human neurosurgical applicants in a neurosurgical national selection interview, to assess the potential of artificial intelligence (AI) and LLMs in healthcare and provide insights into their integration into the field. METHODS: In a prospective comparative study, a set of neurosurgical national selection-style interview questions were asked to eight human participants and ChatGPT in an online interview. All participants were doctors currently practicing in the UK who had applied for a neurosurgical National Training Number. Interviews were recorded, anonymised, and scored by three neurosurgical consultants with experience as interviewers for national selection. Answers provided by ChatGPT were used as a template for a virtual interview. Interview transcripts were subsequently scored by neurosurgical consultants using criteria utilised in real national selection interviews. Overall interview score and subdomain scores were compared between human participants and ChatGPT. RESULTS: For overall score, ChatGPT fell behind six human competitors and did not achieve a mean score higher than any individuals who achieved training positions. Several factors, including factual inaccuracies and deviations from expected structure and style may have contributed to ChatGPT's underperformance. CONCLUSIONS: LLMs such as ChatGPT have huge potential for integration in healthcare. However, this study emphasises the need for further development to address limitations and challenges. While LLMs have not surpassed human performance yet, collaboration between humans and AI systems holds promise for the future of healthcare.

mRNA Delivery: Challenges and Advances through Polymeric Soft Nanoparticles.

Single-stranded messenger ribonucleic acid (mRNA) plays a pivotal role in transferring genetic information, and tremendous effort has been devoted over the years to utilize its transcription efficacy in therapeutic interventions for a variety of diseases with high morbidity and mortality. Lipid nanocarriers have been extensively investigated for mRNA delivery and enabled the rapid and successful development of mRNA vaccines against SARS-CoV-2. Some constraints of lipid nanocarriers have encouraged the development of alternative delivery systems, such as polymer-based soft nanoparticles, which offer a modular gene delivery platform. Such macromolecule-based nanocarriers can be synthetically articulated for tailored parameters including mRNA protection, loading efficacy, and targeted release. In this review, we highlight recent advances in the development of polymeric architectures for mRNA delivery, their limitations, and the challenges that still exist, with the aim of expediting further research and the clinical translation of such formulations.

The IDEAL framework for surgical robotics: development, comparative evaluation and long-term monitoring.

The next generation of surgical robotics is poised to disrupt healthcare systems worldwide, requiring new frameworks for evaluation. However, evaluation during a surgical robot's development is challenging due to their complex evolving nature, potential for wider system disruption and integration with complementary technologies like artificial intelligence. Comparative clinical studies require attention to intervention context, learning curves and standardized outcomes. Long-term monitoring needs to transition toward collaborative, transparent and inclusive consortiums for real-world data collection. Here, the Idea, Development, Exploration, Assessment and Long-term monitoring (IDEAL) Robotics Colloquium proposes recommendations for evaluation during development, comparative study and clinical monitoring of surgical robots-providing practical recommendations for developers, clinicians, patients and healthcare systems. Multiple perspectives are considered, including economics, surgical training, human factors, ethics, patient perspectives and sustainability. Further work is needed on standardized metrics, health economic assessment models and global applicability of recommendations.

CRISPR/Cas9 bioluminescence-based assay for monitoring CFTR trafficking to the plasma membrane.

CFTR is a membrane protein that functions as an ion channel. Mutations that disrupt its biosynthesis, trafficking or function cause cystic fibrosis (CF). Here, we present a novel in vitro model system prepared using CRISPR/Cas9 genome editing with endogenously expressed WT-CFTR tagged with a HiBiT peptide. To enable the detection of CFTR in the plasma membrane of live cells, we inserted the HiBiT tag in the fourth extracellular loop of WT-CFTR. The 11-amino acid HiBiT tag binds with high affinity to a large inactive subunit (LgBiT), generating a reporter luciferase with bright luminescence. Nine homozygous clones with the HiBiT knock-in were identified from the 182 screened clones; two were genetically and functionally validated. In summary, this work describes the preparation and validation of a novel reporter cell line with the potential to be used as an ultimate building block for developing unique cellular CF models by CRISPR-mediated insertion of CF-causing mutations.

Benchtop simulation of the retrosigmoid approach: Validation of a surgical simulator and development of a task-specific outcome measure score.

Background: Neurosurgical training is changing globally. Reduced working hours and training opportunities, increased patient safety expectations, and the impact of COVID-19 have reduced operative exposure. Benchtop simulators enable trainees to develop surgical skills in a controlled environment. We aim to validate a high-fidelity simulator model (RetrosigmoidBox, UpSurgeOn) for the retrosigmoid approach to the cerebellopontine angle (CPA). Methods: Novice and expert Neurosurgeons and Ear, Nose, and Throat surgeons performed a surgical task using the model - identification of the trigeminal nerve. Experts completed a post-task questionnaire examining face and content validity. Construct validity was assessed through scoring of operative videos employing Objective Structured Assessment of Technical Skills (OSATS) and a novel Task-Specific Outcome Measure score. Results: Fifteen novice and five expert participants were recruited. Forty percent of experts agreed or strongly agreed that the brain tissue looked real. Experts unanimously agreed that the RetrosigmoidBox was appropriate for teaching. Statistically significant differences were noted in task performance between novices and experts, demonstrating construct validity. Median total OSATS score was 14/25 (IQR 10-19) for novices and 22/25 (IQR 20-22) for experts (p < 0.05). Median Task-Specific Outcome Measure score was 10/20 (IQR 7-17) for novices compared to 19/20 (IQR 18.5-19.5) for experts (p < 0.05). Conclusion: The RetrosigmoidBox benchtop simulator has a high degree of content and construct validity and moderate face validity. The changing landscape of neurosurgical training mean that simulators are likely to become increasingly important in the delivery of high-quality education. We demonstrate the validity of a Task-Specific Outcome Measure score for performance assessment of a simulated approach to the CPA.

A synthetic model simulator for intracranial aneurysm clipping: validation of the UpSurgeOn AneurysmBox.

Background and objectives: In recent decades, the rise of endovascular management of aneurysms has led to a significant decline in operative training for surgical aneurysm clipping. Simulation has the potential to bridge this gap and benchtop synthetic simulators aim to combine the best of both anatomical realism and haptic feedback. The aim of this study was to validate a synthetic benchtop simulator for aneurysm clipping (AneurysmBox, UpSurgeOn). Methods: Expert and novice surgeons from multiple neurosurgical centres were asked to clip a terminal internal carotid artery aneurysm using the AneurysmBox. Face and content validity were evaluated using Likert scales by asking experts to complete a post-task questionnaire. Construct validity was evaluated by comparing expert and novice performance using the modified Objective Structured Assessment of Technical Skills (mOSATS), developing a curriculum-derived assessment of Specific Technical Skills (STS), and measuring the forces exerted using a force-sensitive glove. Results: Ten experts and eighteen novices completed the task. Most experts agreed that the brain looked realistic (8/10), but far fewer agreed that the brain felt realistic (2/10). Half the expert participants (5/10) agreed that the aneurysm clip application task was realistic. When compared to novices, experts had a significantly higher median mOSATS (27 vs. 14.5; p < 0.01) and STS score (18 vs. 9; p < 0.01); the STS score was strongly correlated with the previously validated mOSATS score (p < 0.01). Overall, there was a trend towards experts exerting a lower median force than novices, however, these differences were not statistically significant (3.8 N vs. 4.0 N; p = 0.77). Suggested improvements for the model included reduced stiffness and the addition of cerebrospinal fluid (CSF) and arachnoid mater. Conclusion: At present, the AneurysmBox has equivocal face and content validity, and future versions may benefit from materials that allow for improved haptic feedback. Nonetheless, it has good construct validity, suggesting it is a promising adjunct to training.

Optimising trajectory planning for stereotactic brain tumour biopsy using artificial intelligence: a systematic review of the literature.

PURPOSE: Despite advances in technology, stereotactic brain tumour biopsy remains challenging due to the risk of injury to critical structures. Indeed, choosing the correct trajectory remains essential to patient safety. Artificial intelligence can be used to perform automated trajectory planning. We present a systematic review of automated trajectory planning algorithms for stereotactic brain tumour biopsies. METHODS: A PRISMA adherent systematic review was conducted. Databases were searched using keyword combinations of 'artificial intelligence', 'trajectory planning' and 'brain tumours'. Studies reporting applications of artificial intelligence (AI) to trajectory planning for brain tumour biopsy were included. RESULTS: All eight studies were in the earliest stage of the IDEAL-D development framework. Trajectory plans were compared through a variety of surrogate markers of safety, of which the minimum distance to blood vessels was the most common. Five studies compared manual to automated planning strategies and favoured automation in all cases. However, this comes with a significant risk of bias. CONCLUSIONS: This systematic review reveals the need for IDEAL-D Stage 1 research into automated trajectory planning for brain tumour biopsy. Future studies should establish the congruence between expected risk of algorithms and the ground truth through comparisons to real world outcomes.

Current and Future Advances in Surgical Therapy for Pituitary Adenoma.

The vital physiological role of the pituitary gland, alongside its proximity to critical neurovascular structures, means that pituitary adenomas can cause significant morbidity or mortality. While enormous advancements have been made in the surgical care of pituitary adenomas, numerous challenges remain, such as treatment failure and recurrence. To meet these clinical challenges, there has been an enormous expansion of novel medical technologies (eg, endoscopy, advanced imaging, artificial intelligence). These innovations have the potential to benefit each step of the patient's journey, and ultimately, drive improved outcomes. Earlier and more accurate diagnosis addresses this in part. Analysis of novel patient data sets, such as automated facial analysis or natural language processing of medical records holds potential in achieving an earlier diagnosis. After diagnosis, treatment decision-making and planning will benefit from radiomics and multimodal machine learning models. Surgical safety and effectiveness will be transformed by smart simulation methods for trainees. Next-generation imaging techniques and augmented reality will enhance surgical planning and intraoperative navigation. Similarly, surgical abilities will be augmented by the future operative armamentarium, including advanced optical devices, smart instruments, and surgical robotics. Intraoperative support to surgical team members will benefit from a data science approach, utilizing machine learning analysis of operative videos to improve patient safety and orientate team members to a common workflow. Postoperatively, neural networks leveraging multimodal datasets will allow early detection of individuals at risk of complications and assist in the prediction of treatment failure, thus supporting patient-specific discharge and monitoring protocols. While these advancements in pituitary surgery hold promise to enhance the quality of care, clinicians must be the gatekeepers of the translation of such technologies, ensuring systematic assessment of risk and benefit prior to clinical implementation. In doing so, the synergy between these innovations can be leveraged to drive improved outcomes for patients of the future.

Effect of Selenium Nanoparticle Size on IL-6 Detection Sensitivity in a Lateral Flow Device.

Sepsis is the body's response to an infection. Existing diagnostic testing equipment is not available in primary care settings and requires long waiting times. Lateral flow devices (LFDs) could be employed in point-of-care (POC) settings for sepsis detection; however, they currently lack the required sensitivity. Herein, LFDs are constructed using 150-310 nm sized selenium nanoparticles (SeNPs) and are compared to commercial 40 nm gold nanoparticles (AuNPs) for the detection of the sepsis biomarker interleukin-6 (IL-6). Both 310 and 150 nm SeNPs reported a lower limit of detection (LOD) than 40 nm AuNPs (0.1 ng/mL compared to 1 ng/mL), although at the cost of test line visual intensity. This is to our knowledge the first use of larger SeNPs (>100 nm) in LFDs and the first comparison of the effect of the size of SeNPs on assay sensitivity in this context. The results herein demonstrate that large SeNPs are viable alternatives to existing commercial labels, with the potential for higher sensitivity than standard 40 nm AuNPs.

Ionocyte-Specific Regulation of Cystic Fibrosis Transmembrane Conductance Regulator.

CFTR (cystic fibrosis transmembrane conductance regulator) is a tightly regulated anion channel that mediates chloride and bicarbonate conductance in many epithelia and in other tissues, but whether its regulation varies depending on the cell type has not been investigated. Epithelial CFTR expression is highest in rare cells called ionocytes. We studied CFTR regulation in control and ionocyte-enriched cultures by transducing bronchial basal cells with adenoviruses that encode only eGFP or FOXI1 (forkhead box I1) + eGFP as separate polypeptides. FOXI1 dramatically increased the number of transcripts for ionocyte markers ASCL3 (Achaete-Scute Family BHLH Transcription Factor 3), BSND, ATP6V1G3, ATP6V0D2, KCNMA1, and CFTR without altering those for secretory (SCGB1A1), basal (KRT5, KRT6, TP63), goblet (MUC5AC), or ciliated (FOXJ1) cells. The number of cells displaying strong FOXI1 expression was increased 7-fold, and there was no evidence for a broad increase in background immunofluorescence. Total CFTR mRNA and protein levels increased 10-fold and 2.5-fold, respectively. Ionocyte-enriched cultures displayed elevated basal current, increased adenylyl cyclase 5 expression, and tonic suppression of CFTR activity by the phosphodiesterase PDE1C, which has not been shown previously to regulate CFTR activity. The results indicate that CFTR regulation depends on cell type and identifies PDE1C as a potential target for therapeutics that aim to increase CFTR function specifically in ionocytes.

Is dementia more likely following traumatic brain injury? A systematic review.

BACKGROUND: The association between traumatic brain injury (TBI) and dementia is controversial, and of growing importance considering the ageing demography of TBI. OBJECTIVE: To review the scope and quality of the existing literature investigating the relationship between TBI and dementia. METHODS: We conducted a systematic review following PRISMA guidelines. Studies that compared TBI exposure and dementia risk were included. Studies were formally assessed for quality with a validated quality-assessment tool. RESULTS: 44 studies were included in the final analysis. 75% (n = 33) were cohort studies and data collection was predominantly retrospective (n = 30, 66.7%). 25 studies (56.8%) found a positive relationship between TBI and dementia. Clearly defined and valid measures of assessing TBI history were lacking (case-control studies-88.9%, cohort studies-52.9%). Most studies failed to justify a sample size (case-control studies-77.8%, cohort studies-91.2%), blind assessors to exposure (case-control-66.7%) or blind assessors to exposure status (cohort-3.00%). Studies that identified a relationship between TBI and dementia had a longer median follow-up time (120 months vs 48 months, p = 0.022) and were more likely to use validated TBI definitions (p = 0.01). Studies which clearly defined TBI exposure (p = 0.013) and accounted for TBI severity (p = 0.036) were also more likely to identify an association between TBI and dementia. There was no consensus method by which studies diagnosed dementia and neuropathological confirmation was only available in 15.5% of studies. CONCLUSIONS: Our review suggests a relationship between TBI and dementia, but we are unable to predict the risk of dementia for an individual following TBI. Our conclusions are limited by heterogeneity in both exposure and outcome reporting and by poor study quality. Future studies should; (a) use validated methods to define TBI, accounting for TBI severity; (b) follow consensus agreement on criteria for dementia diagnosis; and (c) undertake follow-up that is both longitudinal, to determine if there is a progressive neurodegenerative change or static post-traumatic deficit, and of sufficient duration.

Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl- d -Aspartate Receptor Antibody Encephalitis.

PURPOSE: Anti-N-methyl- d -aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG was able to predict outcomes in patients with suspected anti-NMDAR encephalitis. METHODS: A retrospective, observational study was conducted of patients admitted to a tertiary clinical neuroscience center with suspected anti-NMDAR encephalitis. Peak power and peak frequency within delta (<4 Hz), theta (4-8 Hz), alpha (8 - 13 Hz), and beta (13-30 Hz) frequency bands were calculated for the first clinical EEG recording. Outcome was based on the modified Rankin Scale (mRS) score at 1 year after hospital discharge. Binomial logistic regression using backward elimination was performed with peak frequency and power, anti-NMDAR Encephalitis One-Year Functional Status score, age, and interval from symptom onset to EEG entered as predictors. RESULTS: Twenty patients were included (mean age 48.6 years, 70% female), of which 7 (35%) had a poor clinical outcome (mRS 2-6) at 1 year. There was no association between reported EEG abnormalities and outcome. The final logistic regression model was significant (χ 2 (1) = 6.35, P < 0.012) with peak frequency in the delta range (<4 Hz) the only retained predictor. The model explained 38% of the variance (Nagelkerke R2 ) and correctly classified 85% of cases. Higher peak frequency in the delta range was significantly associated ( P = 0.04) with an increased likelihood of poor outcome. CONCLUSIONS: In this exploratory study, it was found that quantitative EEG on routinely collected EEG recordings in patients with suspected anti-NMDAR encephalitis was feasible. A higher peak frequency within the delta range was associated with poorer clinical outcome and may indicate anti-NMDAR-mediated synaptic dysfunction. Quantitative EEG may have clinical utility in predicting outcomes in patients with suspected NMDAR antibody encephalitis, thereby serving as a useful adjunct to qualitative EEG assessment; however, given the small sample size, replication in a larger scale is indicated.