5 research outputs found
Intraoperative Ultrasonography in Resection of Diffuse Glioma
No full textDiffuse glioma is a primary brain tumor that originates from glial supportive cells and is the most common type of intra-axial brain tumor. Open tumor resection is the first step in the treatment of diffuse gliomas. The extent of resection (EOR) directly influences clinical outcomes in glioma surgery. However, resection of diffuse glioma is encountered with the problem of macroscopic and even microscopic similarity of normal brain and tumor. Furthermore, maximizing EOR requires attention because a mistake in identifying and preserving normal brain regions in complete resection can lead to catastrophic complications
Acute Hemifacial And Hemiparesis Caused By Hemorrhagic Vestibular Schwannoma; A Case Report
No full textVestibular schwannoma is a benign and common slow-growing tumor that develops on the vestibular divisions of cranial nerve VIII. Some risk factors may enhance intratumoral hemorrhage risk which leads to tumor management to early surgical procedures. Hence, we describe a 57-year-old man presented with hearing loss and a 5*8 mm vestibular schwannoma. Eight months later, the patient was referred with headache, nausea and vomiting, right hemifacial paresis, and hemiparesis. Magnetic resonance imaging (MRI) revealed a 45*35 mm hemorrhagic vestibular schwannoma. Surgical pathology reported hemorrhagic vestibular schwannoma. This was a rare case of hemorrhagic vestibular schwannoma with none of the established risk factors for the intratumoral hemorrhage and presented with Wallenberg-like syndrome. Many risk factors can cause hemorrhagic vestibular schwannoma. We present one case of small vestibular schwannoma without any predisposing of hemorrhage and acute onset of same side hemifacial paresis and hemiparesis
The The Research Status of Neurological Surgery Residents; A Survey of Iranian Residency Programs: Research Status of Iranian Neurosurgery Residents
No full textBackground: Research activities promote the appreciation for evidence-based medicine (EBM), quality patient care and clinical competence of resident physicians. We decided to investigate the research background of Iranian neurological surgery residents and their attitude toward research through a survey.Methods: This cross-sectional study was done on Iranian neurological surgery resident physicians between February and April 2020. We provided an online survey, including 13 questions, using Google form and then sent the link to survey via WhatsApp application. Following the first post, two more reminders were sent to the groups after 2 and 4 weeks.Results: Responses were received from 89 respondents from which about 88% used to spend two hours or less per week for research. Almost equal numbers of resident physicians chose academic position (n = 43) or private practice (n = 39) as their future job. Only seven respondents stated immigration for assumed future job position. Clinical research (47%) was the most frequent type of research done by participants and clinical research education (43.2%) during medical school was the most common way of obtaining research experience. Agreement with doing research during residency program (45.6%) was more than disagreement (22.4%) and neutral attitude (32%).Conclusion: There is a low tendency among Iranian neurological surgery residents for conducting research projects during their programs. Lack of a proper research curriculum, heavy clinical duties and consequent shortage of time as well as insufficient encouraging points, are the main reasons. Designing a research plan for residency programs may successfully increase the research involvement rate
A prognostic model for use before elective surgery to estimate the risk of postoperative pulmonary complications (GSU-Pulmonary Score): a development and validation study in three international cohorts
No full textBackground: Pulmonary complications are the most common cause of death after surgery. This study aimed to derive and externally validate a novel prognostic model that can be used before elective surgery to estimate the risk of postoperative pulmonary complications and to support resource allocation and prioritisation during pandemic recovery. Methods: Data from an international, prospective cohort study were used to develop a novel prognostic risk model for pulmonary complications after elective surgery in adult patients (aged ≥18 years) across all operation and disease types. The primary outcome measure was postoperative pulmonary complications at 30 days after surgery, which was a composite of pneumonia, acute respiratory distress syndrome, and unexpected mechanical ventilation. Model development with candidate predictor variables was done in the GlobalSurg-CovidSurg Week dataset (global; October, 2020). Two structured machine learning techniques were explored (XGBoost and the least absolute shrinkage and selection operator [LASSO]), and the model with the best performance (GSU-Pulmonary Score) underwent internal validation using bootstrap resampling. The discrimination and calibration of the score were externally validated in two further prospective cohorts: CovidSurg-Cancer (worldwide; February to August, 2020, during the COVID-19 pandemic) and RECON (UK and Australasia; January to October, 2019, before the COVID-19 pandemic). The model was deployed as an online web application. The GlobalSurg-CovidSurg Week and CovidSurg-Cancer studies were registered with ClinicalTrials.gov, NCT04509986 and NCT04384926. Findings: Prognostic models were developed from 13 candidate predictor variables in data from 86 231 patients (1158 hospitals in 114 countries). External validation included 30 492 patients from CovidSurg-Cancer (726 hospitals in 75 countries) and 6789 from RECON (150 hospitals in three countries). The overall rates of pulmonary complications were 2·0% in derivation data, and 3·9% (CovidSurg-Cancer) and 4·7% (RECON) in the validation datasets. Penalised regression using LASSO had similar discrimination to XGBoost (area under the receiver operating curve [AUROC] 0·786, 95% CI 0·774-0·798 vs 0·785, 0·772-0·797), was more explainable, and required fewer covariables. The final GSU-Pulmonary Score included ten predictor variables and showed good discrimination and calibration upon internal validation (AUROC 0·773, 95% CI 0·751-0·795; Brier score 0·020, calibration in the large [CITL] 0·034, slope 0·954). The model performance was acceptable on external validation in CovidSurg-Cancer (AUROC 0·746, 95% CI 0·733-0·760; Brier score 0·036, CITL 0·109, slope 1·056), but with some miscalibration in RECON data (AUROC 0·716, 95% CI 0·689-0·744; Brier score 0·045, CITL 1·040, slope 1·009). Interpretation: This novel prognostic risk score uses simple predictor variables available at the time of a decision for elective surgery that can accurately stratify patients' risk of postoperative pulmonary complications, including during SARS-CoV-2 outbreaks. It could inform surgical consent, resource allocation, and hospital-level prioritisation as elective surgery is upscaled to address global backlogs. Funding: National Institute for Health Research
SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study
No full textBackground: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling.
Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty.
Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year.
Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population
