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MNJ (Malang Neurology Journal)
Published by Universitas Brawijaya
ISSN : 24076724     EISSN : 24425001     DOI : -
Core Subject : Science,
Neuroscience
Malang Neurology Journal is a peer-reviewed and open access journal that focuses on promoting neurological sciences generated from basic neurosciences and clinical neurology. This journal publishes original articles, reviews, and also interesting case reports. Brief communications containing short features of medicine, latest developments in diagnostic procedures of neurology disease, treatment, or other health issues related to neurology that is important also acceptable. Letters and commentaries of our published articles are welcome.
Arjuna Subject : -
Articles 12 Documents
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Search results for , issue "Vol. 12 No. 1 (2026): January" : 12 Documents clear
IMPACT OF TRIGLYCERIDE GLUCOSE INDEX AND TG/HDL RATIO ON TREATMENT OUTCOMES IN ACUTE ISCHEMIC STROKE Akpinar, Ahmet; Kalyoncu Aslan, Işıl; Ramazanoğlu, Leyla
MNJ (Malang Neurology Journal) Vol. 12 No. 1 (2026): January
Publisher : PERDOSSI (Perhimpunan Dokter Spesialis Saraf Indonesia Cabang Malang) - Indonesian Neurological Association Branch of Malang cooperated with Neurology Residency Program, Faculty of Medicine Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.mnj.2026.012.01.11

Abstract

Background: Insulin resistance is one of the modifiable risk factors for ischemic stroke. Objective: This study aimed to investigate the relationship between treatment success, complications, and the functional status of the patients at 3 months follow up, Triglyceride/Glucose index and Triglyceride/High Density Lipoprotein values in patients who were received intravenous thrombolytic and/or mechanical thrombectomy treatments. Methods: A total of 432 patients aged over 18 years who were treated for acute ischemic stroke were included in the study. The Triglyceride Glucose index was computed using the formula Ln (Fasting Blood Sugar (mg/dl) x Fasting Triglyceride Level (mg/dl)/2) based on blood samples taken on the first day of hospitalization. Etiological evaluation of stroke was performed according to the TOAST classification. Results: Twenty-four hours following intravenous thrombolysis and/or mechanical thrombectomy, patients exhibiting elevated Triglyceride/Glucose index values demonstrated higher NIHSS scores. Moreover, individuals diagnosed with large vessel occlusions had significantly increased Triglyceride/Glucose index and Triglyceride/High Density Lipoprotein ratio levels compared to those with cardioembolic stroke etiology. On the other hand, no meaningful association was identified between Triglyceride/Glucose index and Triglyceride/High Density Lipoprotein values and the duration of hospitalization or modified rankin score outcomes. Conclusion: In this study, no strong evidence was shown regarding the relationship between Triglyceride/Glucose index and Triglyceride/High Density Lipoprotein values and treatment-related complications and functional status at 3-month follow-up in patients who underwent iv thrombolytic and mechanical thrombectomy treatment due to acute ischemic stroke. Prospective studies with longer follow-up of patients are needed on this subject.
HARNESSING CLIENT-SIDE AI: DEVELOPMENT AND VALIDATION OF A TENSORFLOW.JS APPLICATION FOR NON-INVASIVE SNORING DETECTION Afif, Zamroni; Rakhmatiar, Rodhiyan; Munir, Badrul; Ala Qoonita Najma Haq, Nabiila; Sabda Alam, Satria; Amrus Ernanda, Shelby; Ayu Irnanda, Miranthi; Riandono, Dody
MNJ (Malang Neurology Journal) Vol. 12 No. 1 (2026): January
Publisher : PERDOSSI (Perhimpunan Dokter Spesialis Saraf Indonesia Cabang Malang) - Indonesian Neurological Association Branch of Malang cooperated with Neurology Residency Program, Faculty of Medicine Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.mnj.2026.012.01.08

Abstract

Background: Obstructive sleep apnea (OSA) is a prevalent global health issue, yet current monitoring methods are often inaccessible or impractical for routine, at-home use. Objective: This study addresses the need for simple, non-invasive tools for sleep quality assessment. Methods: We developed and evaluated a novel, browser-based snoring detection application leveraging TensorFlow.js. A binary classification model was trained on a balanced dataset of snoring and background noise audio. A key feature of the application is its client-side architecture, where all audio processing and model inference occur locally on the user's device, ensuring real-time performance and preserving user privacy. The model's performance was validated on a holdout test set using standard classification metrics. Results: The model demonstrated robust performance, achieving an overall accuracy of 94.12%, a sensitivity of 95.00%, and a specificity of 93.22% in distinguishing snoring from ambient noise. The application successfully generated useful session statistics for users, including total snoring duration, frequency, and the percentage of snoring time during a monitoring session. Conclusion: This study validates the use of a browser-based AI system as a reliable, scalable, and privacy-preserving tool for sleep quality monitoring. While not a diagnostic instrument, the application serves as a highly accessible preliminary screening and awareness tool. This approach represents a significant step toward democratizing sleep health monitoring and empowering individuals to take an active role in managing their well-being.

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