CSF Rhinorrhoea After Endonasal Intervention to the Skull Base (CRANIAL) - Part 1: Multicenter Pilot Study

Khan, Danyal Z.; Marcus, Hani J.; Horsfall, Hugo Layard; Bandyopadhyay, Soham; Schroeder, Benjamin E; Patel, Vikesh; O’Donnell, Alice; Ahmed, Shahzada; Alalade, Andrew F.; Ali, Ahmad M.; Allison, Callum; Al-Barazi, Sinan; Al-Mahfoudh, Rafid; Amarouche, Meriem; Bahl, Anuj; Bennett, David; Bhalla, Raj; Bhatt, Pragnesh; Boukas, Alexandros; Cabrilo, Ivan; Chadwick, Angelina; Chowdhury, Yasir A; Choi, David; Cudlip, Simon; Donnelly, Neil; Dorward, Neil; Dow, Graham; Fountain, Daniel M; Grieve, Joan; Giamouriadis, Anastasios; Gilkes, Catherine; Gnanalingham, Kanna; Halliday, Jane; Hanna, Brendan; Hayhurst, Caroline; Hempenstall, Jonathan; Henderson, Duncan; Hossain-Ibrahim, Kismet; Hirst, Theodore C.; Hughes, Mark; Javadpour, Mohsen; Jenkins, Alistair; Kamel, Mahmoud; Kolias, Angelos; Khan, Mohammad Habibullah; Khan, Mohammad Saud; Lacy, Peter D.; Mahmood, Shumail; Maratos, Eleni; Martin, Andrew; Mathad, Nijaguna; McAleavey, Patrick; Mendoza, Nigel; Millward, Christopher P; Mirza, Showkat; Muquit, Sam; Murray, Daniel D.; Naik, Paresh; Nair, Ramesh; Nicholson, Claire; Paluzzi, Alex; Pathmanaban, Omar; Paraskevopoulos, Dimitris; Pollock, Jonathan; Phillips, Nick; Piper, Rory J; Ram, Bhaskar; Robertson, Iain; Román, Elena; Ross, Peter; Santarius, Thomas; Sayal, Parag; Shapey, Jonathan; Sharma, Rishi; Shaw, Simon; Shoakazemi, Alireza; Shumon, Syed; Sinha, Saurabh; Solomou, Georgios; Soon, Wai Cheong; Stapleton, Simon; Statham, Patrick; Stew, Benjamin; Thomas, Nick; Tsermoulas, Georgios; Tysome, James R.; Varma, Adithya; Weir, Philip; Williams, Adam; Youssef, Mohamed

doi:10.1016/j.wneu.2020.12.171

Cited by 19 publications

(11 citation statements)

References 26 publications

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“…A detailed description of the generation of the CRANIAL dataset is described in ( 25 ). In brief, it is a multicentre dataset (30 centres in the UK and Ireland), collected via a prospective observational study in 3 phases encompassing November 2019 – July 2020 ( 22 – 25 ). All TSA (defined as transsphenoidal access to the sella alone) and EEA [defined as acquiring surgical access to an area beyond the sella ( 17 , 19 )] were included.…”

Section: Methodsmentioning

confidence: 99%

“…All TSA (defined as transsphenoidal access to the sella alone) and EEA [defined as acquiring surgical access to an area beyond the sella ( 17 , 19 )] were included. The dataset is composed of baseline characteristic data (e.g., age; sex; tumour diameter), operative data (e.g., intraoperative CSF leak presence; skull base repair method) and postoperative outcomes (e.g., CSFR) ( 22 – 25 ). A taxonomy for skull base repair was adapted from a systematic review of the literature ( 10 , 24 ).…”

Section: Methodsmentioning

confidence: 99%

“…CRANIAL (CSF rhinorrhoea after endonasal intervention to the skull base) was a prospective, multicentre observational study seeking to determine the: (1) scope of the methods of skull base repair; and (2) corresponding rates of CSFR ( 22 – 25 ). It represents the largest dataset of its kind, seeking to audit practice across the UK and Ireland.…”

Section: Introductionmentioning

confidence: 99%

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Machine learning driven prediction of cerebrospinal fluid rhinorrhoea following endonasal skull base surgery: A multicentre prospective observational study

2023

Front. Oncol.

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BackgroundCerebrospinal fluid rhinorrhoea (CSFR) is a common complication following endonasal skull base surgery, a technique that is fundamental to the treatment of pituitary adenomas and many other skull base tumours. The CRANIAL study explored CSFR incidence and related risk factors, particularly skull base repair techniques, via a multicentre prospective observational study. We sought to use machine learning to leverage this complex multicentre dataset for CSFR prediction and risk factor analysis.MethodsA dataset of 865 cases - 725 transsphenoidal approach (TSA) and 140 expanded endonasal approach (EEA) - with cerebrospinal fluid rhinorrhoea as the primary outcome, was used. Relevant variables were extracted from the data, and prediction variables were divided into two categories, preoperative risk factors; and repair techniques, with 6 and 11 variables respectively. Three types of machine learning models were developed in order to predict CSFR: logistic regression (LR); decision tree (DT); and neural network (NN). Models were validated using 5-fold cross-validation, compared via their area under the curve (AUC) evaluation metric, and key prediction variables were identified using their Shapley additive explanations (SHAP) score.ResultsCSFR rates were 3.9% (28/725) for the transsphenoidal approach and 7.1% (10/140) for the expanded endonasal approach. NNs outperformed LR and DT for CSFR prediction, with a mean AUC of 0.80 (0.70-0.90) for TSA and 0.78 (0.60-0.96) for EEA, when all risk factor and intraoperative repair data were integrated into the model. The presence of intraoperative CSF leak was the most prominent risk factor for CSFR. Elevated BMI and revision surgery were also associated with CSFR for the transsphenoidal approach. CSF diversion and gasket sealing appear to be strong predictors of the absence of CSFR for both approaches.ConclusionNeural networks are effective at predicting CSFR and uncovering key CSFR predictors in patients following endonasal skull base surgery, outperforming traditional statistical methods. These models will be improved further with larger and more granular datasets, improved NN architecture, and external validation. In the future, such predictive models could be used to assist surgical decision-making and support more individualised patient counselling.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Machine learning driven prediction of cerebrospinal fluid rhinorrhoea following endonasal skull base surgery: A multicentre prospective observational study

2023

Front. Oncol.

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“…After piloting at 12 centres, preliminary results suggested practice heterogeneity ( 15 , 16 ). Thus, the study was expanded UK and Ireland wide, and herein, we present the results.…”

Section: Introductionmentioning

confidence: 99%

CSF rhinorrhoea after endonasal intervention to the skull base (CRANIAL): A multicentre prospective observational study

2023

Front. Oncol.

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ObjectiveDespite progress in endonasal skull-base neurosurgery, cerebrospinal fluid (CSF) rhinorrhoea remains common and significant. The CRANIAL study sought to determine 1) the scope of skull-base repair methods used, and 2) corresponding rates of postoperative CSF rhinorrhoea in the endonasal transsphenoidal approach (TSA) and the expanded endonasal approach (EEA) for skull-base tumors.MethodsA prospective observational cohort study of 30 centres performing endonasal skull-base neurosurgery in the UK and Ireland (representing 91% of adult units). Patients were identified for 6 months and followed up for 6 months. Data collection and analysis was guided by our published protocol and pilot studies. Descriptive statistics, univariate and multivariable logistic regression models were used for analysis.ResultsA total of 866 patients were included - 726 TSA (84%) and 140 EEA (16%). There was significant heterogeneity in repair protocols across centres. In TSA cases, nasal packing (519/726, 72%), tissue glues (474/726, 65%) and hemostatic agents (439/726, 61%) were the most common skull base repair techniques. Comparatively, pedicled flaps (90/140, 64%), CSF diversion (38/140, 27%), buttresses (17/140, 12%) and gasket sealing (11/140, 9%) were more commonly used in EEA cases. CSF rhinorrhoea (biochemically confirmed or requiring re-operation) occurred in 3.9% of TSA (28/726) and 7.1% of EEA (10/140) cases. A significant number of patients with CSF rhinorrhoea (15/38, 39%) occurred when no intraoperative CSF leak was reported. On multivariate analysis, there may be marginal benefits with using tissue glues in TSA (OR: 0.2, CI: 0.1-0.7, p<0.01), but no other technique reached significance. There was evidence that certain characteristics make CSF rhinorrhoea more likely – such as previous endonasal surgery and the presence of intraoperative CSF leak.ConclusionsThere is a wide range of skull base repair techniques used across centres. Overall, CSF rhinorrhoea rates across the UK and Ireland are lower than generally reported in the literature. A large proportion of postoperative leaks occurred in the context of occult intraoperative CSF leaks, and decisions for universal sellar repairs should consider the risks and cost-effectiveness of repair strategies. Future work could include longer-term, higher-volume studies, such as a registry; and high-quality interventional studies.

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“…of publications ENTICE [ 16 ] Retrospective study assessing adherence of cauda equina syndrome referrals to published national guidelines. Supported by the BNTRC 2016 2017 86 56 28 4441 2 1 STUN [ 14 ] Cross-sectional study of undergraduate neuroanatomy teaching in the UK and Ireland 2019 2020 11 6 24 N/A 1 1 ELISAR-GB Prospective evaluation of intraoperative surgical adjuncts used in the resection of glioblastoma tumours 2019 Ongoing 84 46 28 291 2 - SPICE-19 [ 5 , 8 , 34 ] Prospective observational study of mental health and well-being of medical students and foundation doctors during the COVID-19 pandemic 2020 2020 35 34 32 2075 10 4 CRANIAL [ 9 , 10 , 24 ] Prospective observational cohort study of cerebrospinal fluid rhinorrhoea rates after endonasal intervention to the skull base 2020 Ongoing 148 34 30 869 5 3 …”

Section: Introductionmentioning

confidence: 99%

The Neurology and Neurosurgery Interest Group (NANSIG)—ten years of cultivating interest in clinical neurosciences

et al. 2022

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Collaboration and successful teamworking are important components of clinical practise, and these skills should be cultivated early in medical school. The breadth of current medical school curricula means that students often have limited exposure to clinical neurosciences. Since its inception in 2009, the Neurology and Neurosurgery Interest Group (NANSIG) has become a national (UK and Republic of Ireland) example of student and junior doctor synergistic collaboration to deliver educational materials, research, conferences, seminars and workshops, as well as advocating for diversity in this field. Recently, it has expanded to incorporate an international audience and cater for a larger group of young medical professionals. The organisation has overcome numerous challenges and is constantly innovating new approaches to harness the necessary knowledge, skills and network to succeed in a career in neurosciences, neurology and neurosurgery. This article summarises the initiatives undertaken by the group over its first 10 years of existence and its organisational structure, as well as its future plans.

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CSF Rhinorrhoea After Endonasal Intervention to the Skull Base (CRANIAL) - Part 1: Multicenter Pilot Study

Cited by 19 publications

References 26 publications

Machine learning driven prediction of cerebrospinal fluid rhinorrhoea following endonasal skull base surgery: A multicentre prospective observational study

Machine learning driven prediction of cerebrospinal fluid rhinorrhoea following endonasal skull base surgery: A multicentre prospective observational study

CSF rhinorrhoea after endonasal intervention to the skull base (CRANIAL): A multicentre prospective observational study

The Neurology and Neurosurgery Interest Group (NANSIG)—ten years of cultivating interest in clinical neurosciences

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