The Icepack Test in the Diagnosis of Myasthenia Gravis with Ocular Features: A Systematic Review of Diagnostic Accuracy, Technique, and Economic Utility.

BACKGROUND: The diagnosis of myasthenia gravis (MG) may be challenging and require multiple specialised testing modalities. Accessing these investigations can involve significant waiting time and costs. The bedside icepack test (IPT) has been proposed to assist with the diagnosis of MG with ocular features, and may prove an economically viable; however, there have been there is heterogeneity in the literature evaluating the IPT. OBJECTIVES: A systematic review was performed examining the accuracy, described techniques, and economic implications of the IPT for the diagnosis of MG with ocular features. METHOD: The databases EMBASE, PubMed, and the Cochrane Library were searched from inception to July 2022. The systematic review adhered to PRISMA guidelines. Eligibility determination was undertaken with a standardised form using appropriate inclusion criteria. The Cochrane risk of bias assessment tool for diagnostic test accuracy was employed to evaluate studies that presented the diagnostic performance of the IPT. The Johanna Briggs Institute Critical Appraisal Checklist for Economic Evaluations was used for the assessment of studies presenting economic evaluations of the IPT. RESULTS: 20 articles met the specified criteria and included a total of 1264 participants. The IPT had a sensitivity ranging from 38.5% to 100%. Specificity was found to be > 95% in six studies. Excluding two outlier results of 25% and 31.3%, the lowest specificity recorded was 62.5%. The most commonly described method of evaluating the IPT involved applying ice to both eyelids and using a >2 mm change as a threshold for a positive test (evaluated with a ruler). There were no adverse effects described with the IPT. There were no studies that formally examined the economic implications of the IPT. CONCLUSIONS: The IPT is a well-tolerated and readily available diagnostic tool that has an important role in the evaluation of possible MG with ocular features in specific contexts. Despite limited economic evaluation of this test, it is likely the use of the IPT may result in significant financial and time savings.

Verapamil in the treatment of reversible cerebral vasoconstriction syndrome: A systematic review.

INTRODUCTION: Extrapolating from efficacy in subarachnoid haemorrhage (SAH), nimodipine has been used as a treatment for reversible cerebral vasoconstriction syndrome (RCVS). However, 4-hourly dosing is a practical limitation and verapamil has been proposed as an alternative. The potential efficacy, adverse effects, preferred dosing and formulation of verapamil for RCVS have not been systematically reviewed previously. METHOD: A systematic review was conducted of the databases PubMed, EMBASE, and the Cochrane Library from inception to July 2022 for peer-reviewed articles describing the use of verapamil for RCVS. This systematic review adheres to the PRISMA guidelines and was registered on PROSPERO. RESULTS: There were 58 articles included in the review, which included 56 patients with RCVS treated with oral verapamil and 15 patients treated with intra-arterial verapamil. The most common oral verapamil dosing regimen was controlled release 120 mg once daily. There were 54/56 patients described to have improvement in headache following oral verapamil and one patient who died from worsening RCVS. Only 2/56 patients noted possible adverse effects with oral verapamil, with none requiring discontinuation. There was one case of hypotension from combined oral and intra-arterial verapamil. Vascular complications including ischaemic and haemorrhagic stroke were recorded in 33/56 patients. RCVS recurrence was described in 9 patients, with 2 cases upon weaning oral verapamil. CONCLUSIONS: While no randomised studies exist to support the use of verapamil in RCVS, observational data support a possible clinical benefit. Verapamil appears well tolerated in this setting and represents a reasonable treatment option. Randomised controlled trials including comparison with nimodipine are warranted.

A Personalized Risk Model for Azacitidine Outcome in Myelodysplastic Syndrome and Other Myeloid Neoplasms Identified by Machine Learning Model Utilizing Real-World Data.

Azacitidine is an approved therapy for higher-risk myelodysplastic syndrome (MDS). However, only 30-40% patients respond to azacitidine, and the responses may take up to six cycles to become evident. Delayed responses and the myelosuppressive effects of azacitidine make it challenging to predict which patients will benefit. This is further compounded by a lack of uniform prognostic tools to identify patients at risk of early treatment failure. Hence, we performed a retrospective analysis of 273 consecutive azacytidine-treated patients. The median overall survival was 16.25 months with only 9% alive at 5 years. By using pre-treatment variables incorporated into a random forest machine learning model, we successfully identified those patients unlikely to benefit from azacytidine upfront (7.99 vs. 22.8 months, p < 0.0001). This model also identified those who required significantly more hospitalizations and transfusion support. Notably, it accurately predicted survival outcomes, outperforming the existing prognostic scoring system. By integrating somatic mutations, we further refined the model and identified three distinct risk groups with significant differences in survival (5.6 vs. 10.5 vs. 43.5 months, p < 0.0001). These real-world findings emphasize the urgent need for personalized prediction tools tailored to hypomethylating agents, reducing unnecessary complications and resource utilization in MDS treatment.