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Background Guillain–Barré syndrome, a rare autoimmune polyneuropathy, typically follows infections and rarely surgical procedures. Post-surgical Guillain–Barré syndrome is an uncommon subset with significant clinical implications. Case presentation We report the case of a 76-year-old Middle Eastern (Bahrainian) male who developed Guillain–Barré syndrome immediately after undergoing routine knee arthroscopy under spinal anesthesia. Shortly postoperatively the patient developed urinary incontinence, followed by progressive bilateral lower limb weakness and sensory deficits. Neurological symptoms rapidly deteriorated by day two and urgent neurological evaluation was taken. Initial and repeat spinal magnetic resonance imaging showed no structural abnormalities, and cerebrospinal fluid analysis lacked albuminocytological dissociation, complicating diagnosis. Electrodiagnostic studies confirmed Guillain–Barré syndrome with demyelinating patterns. Treatment with intravenous immunoglobulin was initiated promptly, resulting in remarkable recovery. By discharge, the patient had regained full motor and sensory function and achieved complete recovery at 6 months follow-up. Conclusion This case highlights the challenges of diagnosing early post-surgical Guillain–Barré syndrome, which can present atypically and without classical cerebrospinal fluid findings. However, early recognition, multidisciplinary collaboration, and timely intravenous immunoglobulin therapy facilitated a favorable outcome. This report highlights the challenges of diagnosing early post-surgical Guillain–Barré syndrome and demonstrates the potential for complete recovery with prompt intervention, emphasizing the need for awareness and timely management in similar cases.

Background: Critical illness polyneuropathy (CIP) is a common complication of severe sepsis and systemic inflammatory response syndrome (SIRS). The risk factors for sepsis-induced CIP have not been well established. Aim: The aim of this study was to find out the risk factors of sepsis-induced CIP, especially its relationship with the severity of illness. Patients and Methods: A cohort of 100 patients with sepsis defined as SIRS of proven or presumed microbial etiology were followed up with nerve conduction studies (NCS) performed within the first 14 days of admission. If the assessment was normal then the study was repeated between day 21 and 28. The two groups (with and without neuropathy) were compared. The following risk factors were evaluated for the development of sepsis-related CIP: Duration of symptoms, stay in Intensive Care Unit, and mechanical ventilation; use of neuromuscular blocking agents (NMBAs), steroids, insulin infusion, and inotropes. The following laboratory parameters recorded in the first 24 h of admission were included: Hemoglobin (Hb), total leukocyte count, serum urea, creatinine, aminotransaminases (aspartate aminotransferase and alanine aminotransferase), total protein, albumin, potassium, creatinine kinase, plasma glucose, HbA1C, and Acute Physiology and Chronic Health Evaluation II (APACHE II) score at admission or within 24 h. Results: Thirty-seven patients had features of neuropathy. Among these 37 patients, 30 patients (81%) developed it in the first 14 days. Multivariate analysis using linear regression showed the APACHE II score and use of NMBAs to be significant factors in its development. An APACHE II score of ≥15 was associated with a significant risk of developing CIP (relative risk: 11.6, 95% confidence interval: 4.9-27.2, P < 0.0001). Conclusion: Critically ill patients with sepsis and APACHE II score at admission or within 24 h of ≥15 are at risk for the development of CIP.

Objectives: Study was conducted with aim of comparing subtypes types of NMOSD based on serology. Methods: In this retrospective study, patients ≥18 years were included satisfying IPND 2015 criteria. Three groups were created based on seropositivity for AQP4 antibody, MOG antibody or double seronegative. Demographic, clinical and imaging were compared using regression analysis. Results: Forty-six patients, 28 (60.9%) AQP4+, 11 (23.9%) MOG + and remaining 7 (15.2%) double seronegative were included. Thirty-seven patients (80.4%) had presenting symptoms localized to optic nerve and/or cord [AQP4 + 22 (78.5%), MOG + 9 (81.8%) and double seronegative 6 (85.7%)]. Presentation with bilateral optic neuritis was more common in AQP4- patients. Twenty (86.8%) out of the 23 patients who had relapsing disease localized to optic nerve and/or spinal cord [AQP4 + 13/14 (92.8%), MOG + 3/5 (60%) and double seronegative 4/4 (100%)]. Relapses were more common in AQP4+ (77% vs 12% vs10%). In AQP4 negative group disability (EDSS 4.2 vs 3.3) and progression index was relatively less (1.6 vs 1.1). CSF pleocytosis (38.8% vs 17.9%) and raised proteins (66.6% vs 32.1%) were also more common. Optic nerve MRI (>50% optic nerve and chiasma involvement) was more commonly abnormal in AQP4 negative (52.9% vs 31.2%). Regression analysis revealed females to be significantly higher in AQP4 positive NMOSD (89.3%) when compared to MOG positive (36.4%) and double seronegative (42.9%). Conclusion: Gender was the only significant difference between the three groups. There was trend towards greater disability and more relapses in AQP4 + groups.

SARS-CoV2 pandemic exposed the limitations of artificial intelligence based medical imaging systems. Earlier in the pandemic, the absence of sufficient training data prevented effective deep learning (DL) solutions for the diagnosis of COVID-19 based on X-Ray data. Here, addressing the lacunae in existing literature and algorithms with the paucity of initial training data; we describe CovBaseAI, an explainable tool using an ensemble of three DL models and an expert decision system (EDS) for COVID-Pneumonia diagnosis, trained entirely on pre-COVID-19 datasets. The performance and explainability of CovBaseAI was primarily validated on two independent datasets. Firstly, 1401 randomly selected CxR from an Indian quarantine center to assess effectiveness in excluding radiological COVID-Pneumonia requiring higher care. Second, curated dataset; 434 RT-PCR positive cases and 471 non-COVID/Normal historical scans, to assess performance in advanced medical settings. CovBaseAI had an accuracy of 87% with a negative predictive value of 98% in the quarantine-center data. However, sensitivity was 0.66–0.90 taking RT-PCR/radiologist opinion as ground truth. This work provides new insights on the usage of EDS with DL methods and the ability of algorithms to confidently predict COVID-Pneumonia while reinforcing the established learning; that benchmarking based on RT-PCR may not serve as reliable ground truth in radiological diagnosis. Such tools can pave the path for multi-modal high throughput detection of COVID-Pneumonia in screening and referral.

Background: Missed findings in chest X-ray interpretation are common and can have serious consequences. Methods: Our study included 2407 chest radiographs (CXRs) acquired at three Indian and five US sites. To identify CXRs reported as normal, we used a proprietary radiology report search engine based on natural language processing (mPower, Nuance). Two thoracic radiologists reviewed all CXRs and recorded the presence and clinical significance of abnormal findings on a 5-point scale (1—not important; 5—critical importance). All CXRs were processed with the AI model (Qure.ai) and outputs were recorded for the presence of findings. Data were analyzed to obtain area under the ROC curve (AUC). Results: Of 410 CXRs (410/2407, 18.9%) with unreported/missed findings, 312 (312/410, 76.1%) findings were clinically important: pulmonary nodules (n = 157), consolidation (60), linear opacities (37), mediastinal widening (21), hilar enlargement (17), pleural effusions (11), rib fractures (6) and pneumothoraces (3). AI detected 69 missed findings (69/131, 53%) with an AUC of up to 0.935. The AI model was generalizable across different sites, geographic locations, patient genders and age groups. Conclusion: A substantial number of important CXR findings are missed; the AI model can help to identify and reduce the frequency of important missed findings in a generalizable manner.

To address this gap in knowledge, we designed this study to document the presence of certain predefined risk factors in patients with extracranial cervical artery dissection causing stroke. Patients who were 18 years or older and with a confirmed diagnosis of ischemic stroke due to extracranial cervical (carotid or vertebral) artery dissection proven by angiography were included in the study. the presence or absence of the following risk factors were documented: History of unaccustomed physical activity or trauma in the preceding one week, history of cervical manipulation in the preceding two weeks, hypertension (treated or untreated), diabetes (treated or untreated), smoking, hypercholesterolemia (>200 mg/dL), overweight (BMI >27 kg/m2), alcohol consumption at least once a week, coronary artery disease (CAD), migraine, family history of stroke, past history of stroke, and preceding infection in the previous week.

Knowledge related to SARS-CoV-2 or 2019 novel coronavirus (2019-nCoV) is still emerging and rapidly evolving. We know little about the effects of this novel coronavirus on various body systems and its behaviour among patients with underlying neurological conditions, especially those on immunomodulatory medications. The aim of the present consensus expert opinion document is to appraise the potential concerns when managing our patients with underlying CNS autoimmune demyelinating disorders during the current COVID-19 pandemic.

Background: Intracranial pressure (ICP) can be raised in many neurological conditions and must be treated early to prevent poor clinical outcomes. To detect the rising ICP, it is important to measure it repeatedly using a tool that is noninvasive, safe, accurate, and portable with minimal inter- and intraobserver variability. The aim of our study was to correlate cerebrospinal fluid (CSF) pressure with ultrasound (US)-measured optic nerve sheath diameter (ONSD) and find out a measurement which correlates best with CSF pressure of >20 cm of water. Materials and Methods: All patients in whom lumbar puncture (LP) was indicated and CSF pressure could be measured using manometer were included in the study. Ocular US was used to measure the ONSD. Results: A hundred patients were included in the study out of which 81% were males. The mean age was 60.5 years (±15.6) with a range of 26-90 years. Significant positive correlation was found between the ONSD and CSF pressure. Correlation coefficient (r) was 0.715 (P < 0.001). Receiver's operating characteristic curve was used to find out the ONSD value correlating with a CSF pressure of >20 cm of water. An ONSD >0.63 cm had a sensitivity of 77.3% [95% confidence interval (CI) 54.6-92.1] and specificity of 92.3% (95% CI 84.0-97.1) in predicting a CSF pressure of >20 cm of water (likelihood ratio [LR] + 10.05, LR − 0.25). Conclusion: There is a positive correlation of US-measured ONSD and LP-measured CSF pressure. ONSD of >0.63 cm suggests a CSF pressure of >20 cm of water.