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All Journal NURSCOPE: Jurnal Penelitian dan Pemikiran Ilmiah Keperawatan Nurse Media Journal of Nursing Jurnal Kesehatan Masyarakat Jurnal NERS Jurnal Penelitian Kesehatan Suara Forikes Journal Of Holistic Nursing Science Jurnal Keperawatan Terpadu (Integrated Nursing Journal) Jurnal Keperawatan Jurnal Ners Journal of Telenursing (JOTING) Critical Medical and Surgical Nursing Journal Pediomaternal Nursing Journal Psychiatry Nursing Journal (Jurnal Keperawatan Jiwa) Indonesian Journal of Global Health research Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Pengabdian Masyarakat dalam Kesehatan Indonesian Academia Health Sciences Journal Jurnal Pengabdian kepada Masyarakat GENIUS JOURNAL (General Nursing Science Journal) Indonesian Nursing Journal of Education and Clinic (Jurnal Pendidikan dan Praktik Keperawatan Indonesia) Jurnal Keperawatan Jurnal Kesehatan dr. Soebandi
Ika Yuni Widyawati
Department Of Nursing, Universitas Airlangga, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Indonesian Journal of Global Health research

 1 
Effectiveness of Early Warning Score (EWS) in Pre, Intra, and Post Dialysis: A Systematic Review Maharani, Evi Kartika; Widyawati, Ika Yuni; Pratiwi, Ika Nur
Indonesian Journal of Global Health Research Vol 7 No 4 (2025): Indonesian Journal of Global Health Research
Publisher : GLOBAL HEALTH SCIENCE GROUP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37287/ijghr.v7i4.6358

Abstract

The Early Warning Score (EWS) is a crucial tool for detecting early signs of clinical deterioration in hemodialysis (HD) patients. However, previous research has primarily focused on the intra-dialysis phase, necessitating a systematic review to explore the effectiveness of EWS across all phases (pre, intra, and post-dialysis). Objective: This study aims to assess the effectiveness of EWS in detecting complications in hemodialysis patients across these three phases and to evaluate its impact on morbidity, mortality, length of hospital stays, and readmission rates. Methods: This systematic review was conducted following PRISMA guidelines. Literature searches were performed in databases such as PubMed, Scopus, ScienceDirect, ProQuest, and Google Scholar. The keywords used in the search were “Early Warning Score” OR “EWS” AND “Hemodialysis” OR “Renal Dialysis” OR “Dialysis” AND “Pre-dialysis” OR “Intradialysis” OR “Post-dialysis” and can utilize Boolean logic (AND, OR, or NOT) to maximize search results. The screening of articles with respect to limitations including year 2016 - 2024. Results: Out of 1,246 identified articles, 15 studies met the inclusion criteria. The findings indicate that EWS is effective in detecting complications across all hemodialysis phases, with significant improvements in clinical management and reductions in morbidity and mortality rates. Conclusion: The comprehensive application of EWS in the pre, intra, and post-dialysis phases can enhance the safety of hemodialysis patients.
Heliotherapy and Walking Therapy to Reduce Glukosa Levels in Type 2 Diabetes Milletus (T2DM): A Comparative Study Mahmud, Mulyani Hertikawati; Widyawati, Ika Yuni; Wahyudi, Andri Setiya
Indonesian Journal of Global Health Research Vol 6 No 4 (2024): Indonesian Journal of Global Health Research
Publisher : GLOBAL HEALTH SCIENCE GROUP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37287/ijghr.v6i4.3313

Abstract

Diabetes Mellitus is a chronic disease that has bad complications for the sufferer's health, so it requires non-pharmacological treatment. The aim of this study is to explain the effectiveness of non-pharmacological therapies such as heliotherapy and walking therapy in reducing random glucose levels (RBS) in patients with type 2 diabetes mellitus (DM). This study used a Pre-Post Test With Two Group Design research design. The population for this study consisted of 32 respondents, divided into two groups: the heliotherapy intervention group and the walking intervention group, each with 16 respondents. The research subjects were selected based on the criteria for diabetes mellitus patients. The independent variables were heliotherapy and walking therapy, while the dependent variable was the reduction in RBS levels. Research instruments included heliotherapy standard operating procedures (SOP), walking therapy SOP, Glucometer, and observation sheets. Data analysis was performed using paired t-tests and independent t-tests. The statistical test results showed a p-value of 0.353 (α>0.05), indicating that there is no significant difference in effectiveness between heliotherapy and walking therapy in reducing RBS levels in patients with type 2 diabetes mellitus (DM). It can be concluded that the reduction in RBS levels is higher with walking therapy compared to heliotherapy in patients with type 2 DM.
Diagnostic Accuracy of Artificial Intelligence-Based Systems for Detecting Diabetic Retinopathy: A Systematic Review Hidayati, Nurul; Widyawati, Ika Yuni; Suarilah, Ira; Astuti, Trihaningsih Puji; Tsanifiandi, Fauzi; Suraya, Andi Safutra
Indonesian Journal of Global Health Research Vol 7 No 1 (2025): Indonesian Journal of Global Health Research
Publisher : GLOBAL HEALTH SCIENCE GROUP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37287/ijghr.v7i1.4011

Abstract

Diabetic retinopathy (DR) represents a leading cause of blindness worldwide, early detection is critical to prevent vision loss. However, traditional screening methods, which rely on human experts, prove to be costly and time-consuming. The systematic review aims to assess the validity of artificial intelligence (AI) as a screening tool for detecting DR among diabetic patients. A systematic literature search was performed of the following databases: PubMed, Scopus, CINAHL, and Web of Science. The last date of our search was January 31, 2024. We included all observational studies, including cohort, case–control and cross-sectional studies and evaluated their quality using the Joanna Briggs Institute tool. We included diagnostic test accuracy studies evaluating the use of AI algorithms for DR screening in patients with diabetes. Studies were excluded if they exclusively assessed diagnostic accuracy for DR that did not use AI algorithms as a diagnostic tool and studies with incomplete or inaccessible data. Thirteen studies with sample sizes ranging from 69 to 1378 participants, reported good sensitivity of AI for detecting visually threatening DR (VTDR). The lowest sensitivity was 89.2%, and the highest was 100%. In terms of specificity, Any DR exhibited higher specificity compared to RDR and VTDR, ranging from 80.2% to 100%. The sensitivity and specificity of the Artificial Intelligence (AI)-based tools available for DR screening was considered acceptable, especially in detecting VTDR and Any DR, was regarded as good. These results implied the potential usefulness of these tools for DR screening in settings with limited resources. However, further high-quality comparative studies were deemed necessary to evaluate their effectiveness in real-world clinical settings.
Co-Authors Abigael Grace Prasetiani Abu Bakar Ah Yusuf Ah. Yusuf ah. Yusuf Ahmad Abdul Ghofar Abdulloh Aini, Nauvila Fitrotul Ainul Mufidah Ainunnajib, Ilham Akbar, Dian Rahmadin Aldri Frinaldi Anak Agung Istri Sri Wiadnyani Andi Safutra Suraya Andri Setiya Wahyudi Anggia Fajar Hardianti Anggun Perwita Sari Arifin, Hidayat Astuti, Trihaningsih Puji Balmar Morangelita Nuach Budi Artini Candra Panji Asmoro, Candra Panji Desak Putu Kurniawati Desi Susilawati, Desi Devi Rahma Sofia Dewi Irawaty Dhimas Wahyu Wicaksono Dian Retno Pratiwi Diansya, Mohammad Rizal Dunggio, Abdul Rivai Saleh Dwi Susi Pristiwatin Eka Mishbahatul Mar'ah Has Elida Ulfiana Elyana Asnar Endah Panca Lydia Fatma Fernandez, Gratsia Victoria Firda Yusniar Fitria Habibah Nita Yuliana Eka Putri Fitriatul Jannah Gratsia Victoria Fernandez Habsari, Dyah Unggul Putri Hadiyanti, Sonia Hakim Zulkarnain Hana Zumaedza Ulfa Harigustian, Yayang Harmayetty, Harmayetty Hasymi, Yusran Herdina Mariyanti Hidayathillah, Ariska Putri Huda, Nuh Ika Nur Pratiwi Ilma Rosida Rahmawati Indah Sri Cahyanti Intan Widiastuti Joni Haryanto Jujuk Proboningsih, Jujuk Kurniawan, Ardhiles Wahyu Kurniawati, Ninuk Dian Kusnanto Kusnanto Lailatun Ni'mah Laily Hidayati Laily Hidayati Lee, Bih-O Liem, Khatijah Lingga Curnia Dewi Lingga Curnia Dwi Lisa Setyowati Luh Putu Ratna Sundari Luknis Sabri Maharani, Evi Kartika Mahmud, Mulyani Hertikawati Makhfudli Makhfudli Mohammad Nur Firdaus Murdiyanti, Dewi mustakim Nadia Rohmatul Laili Nayluzzuharo' N, Fanny Ni Kadek Arie Octarini Ni Made Sekar Sari Nimah, Lailatun Nursalam Nursalam . Nursalam Nursalam Nursalam, Nursalam Nurul Hidayati Nurviana, Destya Eka Octaviani, Dinda Sesylia Paramita, Fajrinandetya Pawanis, Zulfayandi Pei-Lun Hsieh Purwaningsih - Putu Thrisna Dewi, Ni Luh Qonaah, Arina Rachmat Hargono Rezkisa Dwi Prambudia Rheyma Sinar Al Fitri Rista Fauziningtyas, Rista Rizky Fitryasari RR Dian Tristiana Rustiana Tasya Ariningpraja Rusulustin Mustikaria S.Pd. M Kes I Ketut Sudiana . Sari Tauhidiyah Sari, Ni Made Sekar Sari, Purwanti Sekar Sari Sholihatul Maghfirah Sholihatul Maghfirah Shrimarti Rukmini Devy Sifira Kristiningrum Sigit Sugiharto Siti Muniroh Sonia Hardiyanti Sriyono Sriyono Suarilah, Ira Suhaedi Kuling Sukma Randani Ismono Sulistiawati Sulistiawati Syafaatun Mirzanah Syahri, Alfi Sylvia Dwi Wahyuni Tintin Sukartini Sukartini, Tintin Sukartini Tsanifiandi, Fauzi Vivi Armany Dessy Wahyuni, Erna Dwi Wati, Ni Made Nopita Wiwit Dwi Nurbadriyah Yani Indah Sari Yeni Siswanti Yulis Setiya Dewi Zahrotun Ulum