Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Eye That Went to the Dogs

Ptosis; Right eye pain; HeadacheA 48-year old female with ptosis, photophobia, right eye pain and right-sided headache.VA: 20/20 OUMRIEnlarged extraocular muscles, anterior/posterior orbital structures and optic nerve ODCorticosteroids; Anti-bacterial agents1. Lesser RL. Ocular manifestations of Lyme Disease. Am J Med 1995 (4A suppl): 4A. 2. Balcer LJ, Winterkorn, JM, Galetta SL. Neuro-ophthalmic manifestations of Lyme Disease. J Neuro Ophthal 1997; 17;108. 3. Seidenberg KB, Leib ML. Orbital myositis with Lyme disease. Am J Ophthalmol 1990; 109:13. 4. Bertuch AW, Rocco E., Scwartz EG. Eye findings in Lyme disease. Conn Med 1987; 51:151. 5. Winterkorn JMS. Lyme disease: Neurologic and ophthalmic manifestations. Surv Ophthalmol 1990; 35:191. 6. Fatterpekar GM, Gottesman RI, Sacher M, Som PM. Orbital Lyme disease: MR imaging before and after treatment: case report. AJNR Am J Neuroradiol. 2002 Apr; 23(4): 657-9. 7. Colucciello M. Ocular Lyme borreliosis. N Engl J Med 2001 Nov 1; 345(18):1350-1. 8. Krist D, Wenkel H. Posterior scleritis associated with Borrelia burgdorferi (Lyme disease) infection. Ophthalmology 2002; 109(1):143-5. 9. Mikkila HO, Seppala IJ, Viljanen MD, Peltomaa MP, Karma A. The expanding clinical spectrum of ocular Lyme borreliosis. Ophthalmology 2000; 107(3):581-7.VBintracranialinfection

Hungarian Child with Recurrent Suprasellar Mass and Sequential Visual Loss

A 12-year-old right-handed white girl presented with 1 week history of painless visual loss in the left eye, preceded by headaches. The day after her visual loss the exam showed BCVA 0.6 O.D and CF at 2 meters 0.S. Critical fusional frequency was 37 Hz O.D., 24 Hz 0.5 O.S. Fundus described as normal G.V. On perimetry cemral temporal defect with macular involvement O.D. and central scotoma 0.S. was noted. MRI of the brain interpreted as 6 x 8 mm non-enhancing suprasellar cystic mass with indentation of the chiasm

High-Resolution Susceptibility-Weighted Imaging Findings in Patients with Swollen Optic Nerves

Susceptibility-weighted imaging (SWI) is a new 3D-reconstructed gradient echo sequence that is highly sensitive for the paramagnetic effect of deoxyhemoglobin serving as an intrinsic contrast agent of cerebral veins. The most frequent cause of symmetrically swollen optic nerves is idiopathic intracranial hypertension, the cause of which is still unknown but thought to be related to the cerebral venous system

Is There Value to the Use of Brain Atlas in Idiopathic Intracranial Hypertension?

This study aimed to develop disease-specific probability brain atlas with disease-relevant parcellation maps from a small cohort of patients with idiopathic intracranial hypertension (IIH). Probability atlases can identify patterns of altered structure and/or function, and can guide image analysis algorithms for further structural and functional examinations, automated image labeling, and tissue classification for volume and shape analysis

Can Sita Fast Be Used As a Reliable Alternative to Goldman Perimetry in Neuro-Ophthalmic Practice

To assess the potential role of SITA Fast (SF) computerized static perimetry compared with Goldmann manual kinetic perimetry (GVF) to reliably detect visual field defects in neuro-ophthalmic practice

Is There a Role for Multifocal Functional MRI-Based Visual Field Mapping in Neuro-Ophthalmology? A Pilot Study

It is known from previous studies mat multifocal fMRI (mffMRI) mapping of visual conical areas gives a rapid and direct exploration of multiple local visual responses, which adds complementary information to phase encoded mapping of rerinotopic areas. OUf aim was to test a combined method of mffMRI and conventional perimetry that allows simultaneous neural and behavioral mapping of visual field deficits mat can be compared to existing memods

Cranial Nerve Imaging and Pathology

This review provides a symptom-driven approach to neuroimaging of disease processes affecting the cranial nerves. In addition to describing characteristic imaging appearances of a disease, the authors emphasize exceptions to the rules and neuroimaging pearls. The focus is on adult neurology although some important pediatric conditions are included. On reviewing this material, the reader should be able to (1) differentiate intra- and extra-axial causes of cranial nerve dysfunction and (2) appropriately use neuroimaging to investigate abnormalities of cranial nerve function

EASY-APP: An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis

BACKGROUND: Acute pancreatitis (AP) is a potentially severe or even fatal inflammation of the pancreas. Early identification of patients at high risk for developing a severe course of the disease is crucial for preventing organ failure and death. Most of the former predictive scores require many parameters or at least 24 h to predict the severity; therefore, the early therapeutic window is often missed. METHODS: The early achievable severity index (EASY) is a multicentre, multinational, prospective and observational study (ISRCTN10525246). The predictions were made using machine learning models. We used the scikit‐learn, xgboost and catboost Python packages for modelling. We evaluated our models using fourfold cross‐validation, and the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and accuracy metrics were calculated on the union of the test sets of the cross‐validation. The most critical factors and their contribution to the prediction were identified using a modern tool of explainable artificial intelligence called SHapley Additive exPlanations (SHAP). RESULTS: The prediction model was based on an international cohort of 1184 patients and a validation cohort of 3543 patients. The best performing model was an XGBoost classifier with an average AUC score of 0.81 ± 0.033 and an accuracy of 89.1%, and the model improved with experience. The six most influential features were the respiratory rate, body temperature, abdominal muscular reflex, gender, age and glucose level. Using the XGBoost machine learning algorithm for prediction, the SHAP values for the explanation and the bootstrapping method to estimate confidence, we developed a free and easy‐to‐use web application in the Streamlit Python‐based framework (http://easy‐app.org/). CONCLUSIONS: The EASY prediction score is a practical tool for identifying patients at high risk for severe AP within hours of hospital admission. The web application is available for clinicians and contributes to the improvement of the model