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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 surgical workflow (3 phases, 15 steps) and surgical 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 24mins and mean mOSATS was 21.2/30. Mean duration was 34mins and mean mOSATS was 20.9/30 for the sellar phase, and 11mins 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 (CSF) leak (n=5). Higher mOSATS for all three phases and shorter operation duration was associated with decreased length of stay (p=0.003 & p<0.001). Superior closure phase mOSATS were associated with reduced post-operative CSF leak (p<0.001), and superior sellar phase mOSATS were associated with reduced post-operative visual deterioration (p=0.041). CONCLUSION: 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.
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BACKGROUND: Superior surgical skill improves surgical outcomes in endoscopic pituitary adenoma surgery. Video-based coaching programs, pioneered in professional sports, have shown promise in surgical training. In this study, we developed and assessed a video-based coaching program, using artificial intelligence (AI). METHODS: AI-assisted video-based surgical coaching was implemented over 6 months with the pituitary surgery team. The program consisted of 1) monthly random video analysis and review; and 2) quarterly 2-hour educational meetings discussing these videos and learning points. Each video was annotated for surgical phases and steps using AI, which improved video interactivity and allowed calculation of quantitative metrics. Primary outcomes were program feasibility, acceptability and appropriateness. Surgical performance (via modified Objective Structured Assessment of Technical Skills; mOSATS) and early surgical outcomes were recorded for every case during the 6-month coaching period, and a preceding 6-month control period. Beta and logistic regression were used to assess the change in mOSATS and surgical outcomes after the coaching program implementation. RESULTS: All participants highly rated the program's feasibility, acceptability and appropriateness. During the coaching program, 63 endoscopic pituitary adenoma cases were included, with 41 in the control group. Surgical performance across all operative phases improved during the coaching period (p<0.001), with a reduction in new post-operative anterior pituitary hormone deficit (p=0.01). CONCLUSION: We have developed a novel AI-assisted video surgical coaching program for endoscopic pituitary adenoma surgery - demonstrating its viability and impact on surgical performance. Early results also suggest improvement in patient outcomes. Future studies should be multicenter and longer term.
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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.
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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.
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The Expanded Endoscopic Endonasal Approach, one of the best examples of endoscopic neurosurgery, allows access to the skull base through the natural orifice of the nostril. Current standard instruments lack articulation limiting operative access and surgeon dexterity, and thus, could benefit from robotic articulation. In this study, a handheld robotic system with a series of detachable end-effectors for this approach is presented. This system is comprised of interchangeable articulated 2/3 degrees-of-freedom 3 mm instruments that expand the operative workspace and enhance the surgeon's dexterity, an ergonomically designed handheld controller with a rotating joystick-body that can be placed at the position most comfortable for the user, and the accompanying control box. The robotic instruments were experimentally evaluated for their workspace, structural integrity, and force-delivery capabilities. The entire system was then tested in a pre-clinical context during a phantom feasibility test, followed up by a cadaveric pilot study by a cohort of surgeons of varied clinical experience. Results from this series of experiments suggested enhanced dexterity and adequate robustness that could be associated with feasibility in a clinical context, as well as improvement over current neurosurgical instruments.
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OBJECTIVE: The aim of this study was to provide a quantitative synthesis of the survival outcomes for patients with skull base chordomas, focusing on the role of 1) the extent of resection (gross-total [GTR] vs non-GTR), 2) the type of surgery (primary vs revision), 3) tumor histology, and 4) the different use of adjuvant therapies (proton beam radiotherapy [PBRT], photon radiotherapy [RT], or none). METHODS: A systematic review with a meta-analysis was conducted following the 2020 PRISMA guidelines. Observational studies describing adult and pediatric patient cohorts harboring skull base chordomas were included. The primary outcome measures were represented by the 5-year overall survival (OS) and progression-free survival (PFS) rates. The main intervention effects were represented by the extent of resection (GTR vs non-GTR), type of surgical excision (primary vs revision surgeries), tumor histology, and the different use of adjuvant therapies (PBRT, RT, or none). The pooled estimates were calculated using random forest models. The risk of bias was evaluated using the Joanna Briggs Institute checklist for case series. RESULTS: Six hundred forty-four studies were identified through a database and register search. After study selection, 51 studies and 3871 patients were included in the meta-analysis. The overall 5-year OS rate was 73%, which increased to 84% among patients undergoing GTR. The overall 5-year PFS rate was 52%, increasing to 74% for patients receiving GTR. The 5-year OS and PFS rates for patients undergoing PBRT were 86% and 71%, compared with 71% and 54% for patients receiving RT, and 55% and 25% when no adjuvant treatments were used. Patients undergoing their first surgery had 2.13-fold greater chances of being disease-free and 1.4-fold greater chances of being alive at 5 years follow-up compared with patients who received a revision surgery. Patients harboring chondroid chordomas had 1.13- and 1.9-fold greater chances of being alive at 5 years compared with patients with conventional and de-differentiated chordomas, respectively. The overall risk of bias was low in the included studies. CONCLUSIONS: The results of this comprehensive meta-analysis highlight the tremendous impact of GTR and adjuvant PBRT on improving OS and PFS of patients harboring skull base chordomas, with better survival rates demonstrated for patients with chondroid tumors. Even in experienced hands, the rate of surgical morbidity remains high. Proper management in high-volume centers is mandatory to reach the expected resection goal at the first surgical attempt and to reduce surgical morbidity. The introduction of the endoscopic endonasal approach was related to improved surgical and functional outcomes.
Subject(s)
Chordoma , Observational Studies as Topic , Skull Base Neoplasms , Humans , Skull Base Neoplasms/surgery , Skull Base Neoplasms/radiotherapy , Chordoma/surgery , Observational Studies as Topic/methods , Neurosurgical Procedures/methods , Progression-Free SurvivalABSTRACT
PURPOSE: Accessible patient information sources are vital in educating patients about the benefits and risks of spinal surgery, which is crucial for obtaining informed consent. We aim to assess the effectiveness of a natural language processing (NLP) pipeline in recognizing surgical procedures from clinic letters and linking this with educational resources. METHODS: Retrospective examination of letters from patients seeking surgery for degenerative spinal disease at a single neurosurgical center. We utilized MedCAT, a named entity recognition and linking NLP, integrated into the electronic health record (EHR), which extracts concepts and links them to systematized nomenclature of medicine-clinical terms (SNOMED-CT). Investigators reviewed clinic letters, identifying words or phrases that described or identified operations and recording the SNOMED-CT terms as ground truth. This was compared to SNOMED-CT terms identified by the model, untrained on our dataset. A pipeline linking clinic letters to patient-specific educational resources was established, and precision, recall, and F1 scores were calculated. RESULTS: Across 199 letters the model identified 582 surgical procedures, and the overall pipeline after adding rules a total of 784 procedures (precision = 0.94, recall = 0.86, F1 = 0.91). Across 187 letters with identified SNOMED-CT terms the integrated pipeline linking education resources directly to the EHR was successful in 157 (78%) patients (precision = 0.99, recall = 0.87, F1 = 0.92). CONCLUSIONS: NLP accurately identifies surgical procedures in pre-operative clinic letters within an untrained subspecialty. Performance varies among letter authors and depends on the language used by clinicians. The identified procedures can be linked to patient education resources, potentially improving patients' understanding of surgical procedures.
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Natural Language Processing , Patient Education as Topic , Humans , Patient Education as Topic/methods , Retrospective Studies , Electronic Health Records , Systematized Nomenclature of MedicineABSTRACT
The convergence of digital pathology and artificial intelligence could assist histopathology image analysis by providing tools for rapid, automated morphological analysis. This systematic review explores the use of artificial intelligence for histopathological image analysis of digitised central nervous system (CNS) tumour slides. Comprehensive searches were conducted across EMBASE, Medline and the Cochrane Library up to June 2023 using relevant keywords. Sixty-eight suitable studies were identified and qualitatively analysed. The risk of bias was evaluated using the Prediction model Risk of Bias Assessment Tool (PROBAST) criteria. All the studies were retrospective and preclinical. Gliomas were the most frequently analysed tumour type. The majority of studies used convolutional neural networks or support vector machines, and the most common goal of the model was for tumour classification and/or grading from haematoxylin and eosin-stained slides. The majority of studies were conducted when legacy World Health Organisation (WHO) classifications were in place, which at the time relied predominantly on histological (morphological) features but have since been superseded by molecular advances. Overall, there was a high risk of bias in all studies analysed. Persistent issues included inadequate transparency in reporting the number of patients and/or images within the model development and testing cohorts, absence of external validation, and insufficient recognition of batch effects in multi-institutional datasets. Based on these findings, we outline practical recommendations for future work including a framework for clinical implementation, in particular, better informing the artificial intelligence community of the needs of the neuropathologist.
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Artificial Intelligence , Central Nervous System Neoplasms , Humans , Central Nervous System Neoplasms/pathology , Image Processing, Computer-Assisted/methodsABSTRACT
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.
Subject(s)
Elective Surgical Procedures , Patient Education as Topic , Humans , Cross-Sectional Studies , Elective Surgical Procedures/statistics & numerical data , Female , Male , Surveys and Questionnaires , Middle Aged , Patient Education as Topic/methods , Patient Education as Topic/statistics & numerical data , Cohort Studies , Retrospective Studies , United Kingdom , Aged , AdultABSTRACT
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.
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Endoscopy , Pituitary Neoplasms , Humans , Endoscopy/methods , Pituitary Neoplasms/surgery , Surgery, Computer-Assisted/methods , Deep Learning , Pituitary Gland/surgery , Pituitary Gland/anatomy & histology , Pituitary Gland/diagnostic imaging , Sphenoid Sinus/surgery , Sphenoid Sinus/anatomy & histology , Sphenoid Sinus/diagnostic imagingABSTRACT
BACKGROUND: Informed consent is an essential process in clinical decision-making, through which healthcare providers educate patients about benefits, risks, and alternatives of a procedure. Statistical risk information is difficult to communicate and the effectiveness of aids aimed at supporting this type of communication is uncertain. This systematic review aims to study the impact of risk communication adjuncts on patients' understanding of statistical risk in surgery and interventional procedures. METHODS: A systematic search was performed across Medline, Embase, PsycINFO, Scopus, and Web of Science until July 2021 with a repeated search in September 2022. RCTs and observational studies examining risk communication tools (e.g., information leaflets and audio-video) in adult (age >16) patients undergoing a surgical or interventional procedure were included. Primary outcomes included the objective assessment of statistical risk recall. Secondary outcomes included patient attitudes with respect to statistical information. Due to the study heterogeneity, a narrative synthesis was performed. RESULTS: A total of 4348 articles were identified, and following abstract and full-text screening 14 articles, including 9 RCTs, were included. The total number of adult patients was 1513. The most common risk communication tool used was written information (n = 7). Most RCTs (7/9, 77.8%) showed statistically significant improvements in patient understanding of statistical risk in the intervention group. Quality assessment found some concerns with all RCTs. CONCLUSION: Risk communication tools appear to improve recall of statistical risk. Additional prospective trials comparing various aids simultaneously are warranted to determine the most effective method of improving understanding.
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Informed Consent , Humans , Patient Education as Topic , Surgical Procedures, Operative , Risk Assessment , Comprehension , CommunicationABSTRACT
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.
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Hematoma, Subdural, Chronic , Adult , Humans , Aged , Hematoma, Subdural, Chronic/drug therapy , Hospitalization , Cost-Benefit Analysis , Double-Blind Method , Dexamethasone/therapeutic useABSTRACT
Post-operative tumour progression in patients with non-functioning pituitary neuroendocrine tumours is variable. The aim of this study was to use machine learning (ML) models to improve the prediction of post-operative outcomes in patients with NF PitNET. We studied data from 383 patients who underwent surgery with or without radiotherapy, with a follow-up period between 6 months and 15 years. ML models, including k-nearest neighbour (KNN), support vector machine (SVM), and decision tree, showed superior performance in predicting tumour progression when compared with parametric statistical modelling using logistic regression, with SVM achieving the highest performance. The strongest predictor of tumour progression was the extent of surgical resection, with patient age, tumour volume, and the use of radiotherapy also showing influence. No features showed an association with tumour recurrence following a complete resection. In conclusion, this study demonstrates the potential of ML models in predicting post-operative outcomes for patients with NF PitNET. Future work should look to include additional, more granular, multicentre data, including incorporating imaging and operative video data.
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Objectives: To characterize the distribution of case volumes within a surgical field. Design: An analysis of British Spine Registry. Setting: 295 centers in England that conducted at least one spinal operation either within the NHS or private settings between 1 May 2016 and 27 February 2021. Participants: 644 surgeons. Main outcome measures: Mathematical descriptions of distributions of cases among surgeons and the extent of workforce-level case-volume concentration as a surrogate marker. Results: There were wide variations in monthly caseloads between surgeons, ranging from 0 to average monthly high of 81.8 cases. The curves showed that 37.7% of surgeons were required to perform 80% of all spinal operations, which is substantially less than in fields outside of healthcare.With the COVID-19 pandemic, the case volumes of surgeons with the highest volumes dropped dramatically, whereas those with the lowest case numbers remained nearly unchanged. This, along with the relatively low level of case-volume concentration within spinal surgery, may indicate an inevitability of at least some level of surgical care being provided by the relatively lower volume surgeons. Conclusions: While there is a reasonable degree of workforce-level case volume concentration within spinal surgery, with high volume spinal surgeons providing a large proportion of care, it is not clear whether a further concentration of case volumes into those few hands is possible or desirable.
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Introduction: Informed consent is a fundamental component in the work-up for surgical procedures. Statistical risk information pertaining to a procedure is by nature probabilistic and challenging to communicate, especially to those with poor numerical literacy. Visual aids and audio/video tools have previously been shown to improve patients' understanding of statistical information. In this study, we aimed to explore the impact of different methods of risk communication in healthy participants randomized to either undergo the consent process with visual aids or the standard consent process for lumbar puncture. Material and methods: Healthy individuals above 18 years old were eligible. The exclusion criteria were prior experience of the procedure or relevant medical knowledge, lack of capacity to consent, underlying cognitive impairment and hospitalised individuals. After randomisation, both groups received identical medical information about the procedure of a lumbar puncture in a hypothetical clinical scenario via different means of consent. The control group underwent the standard consent process in current clinical practice (Consent Form 1 without any illustrative examples), whereas the intervention group received additional anatomy diagrams, the Paling Palette and the Paling perspective scale. Anonymised questionnaires were received to evaluate their perception of the procedure and its associated risks. Results: Fifty-two individuals were eligible without statistically significant differences in age, sex, professional status and the familiarity of the procedure. Visual aids were noted to improve the confidence of participants to describe the risks by themselves (p = 0.009) and participants in the intervention group felt significantly less overwhelmed with medical information (p = 0.028). The enhanced consent process was found to be significantly more acceptable by participants (p = 0.03). There was a trend towards greater appropriateness (p = 0.06) and it appeared to have "good" usability (median SUS = 76.4), although this also did not reach statistical significance (p = 0.06). Conclusion: Visual aids could be an appropriate alternative method for medical consent without being inferior regarding the understanding of the procedure, its risks and its benefits. Future studies could possibly compare or incorporate multiple interventions to determine the most effective tools in a larger scale of population including patients as well as healthy individuals.
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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.
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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.