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All Journal Jurnal Ners Indonesian Journal of Global Health Research
Rizki Nur Azhadin
Universitas Airlangga
Health Professions Medicine & Pharmacology Nursing

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The Effectiveness of Acupressure in Reducing Pain After Coronary Angiography: a Systematic Review Elvi Kurnia Damayanti; Asroful Hulam Zamroni; Johanes Eban B. Dorman; Rizki Nur Azhadin; Ninuk Dian Kurniawati
Jurnal Ners Vol. 9 No. 2 (2025): APRIL 2025
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jn.v9i2.44237

Abstract

Coronary angiography, a critical diagnostic tool for coronary artery disease, often results in post-procedural pain that affects patient recovery and satisfaction. Acupressure, a non-invasive technique rooted in traditional Chinese medicine, has shown promise in reducing pain by stimulating endorphin release and enhancing physiological responses. This systematic review aimed to evaluate the effectiveness of acupressure in managing pain among patients undergoing coronary angiography. Four databases (Scopus, PubMed, ProQuest, and ScienceDirect) were searched for relevant articles published between 2020 and 2025, using keywords such as "acupressure," "pain," and "coronary angiography." Joanna Briggs Institute guidelines were used to assess study quality. Seven randomized controlled trials involving 774 participants were included. All studies reported significant pain reduction after acupressure interventions (p < 0.05), with durations ranging from 15 to 120 minutes at points like LI4 and PC6. Acupressure not only reduced pain but also stabilized vital signs and reduced anxiety. These findings suggest that acupressure is an effective intervention for post-coronary angiography pain, providing a strong basis for its integration into clinical practice. Further research is needed to standardize protocols and explore long-term effects.
The Effectiveness of Artificial Intelligence in the Early Detection of STEMI: A Systematic Review Rizki Nur Azhadin; Sriyono Sriyono; Erna Dwi Wahyuni
Jurnal Ners Vol. 10 No. 3 (2026): JULI 2026
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jn.v10i3.57907

Abstract

Abstract Introduction: ST-Elevation Myocardial Infarction (STEMI) is one of the most critical manifestations of acute coronary syndrome and requires rapid diagnosis and timely intervention to reduce morbidity and mortality. Recent advances in Artificial Intelligence (AI), particularly in machine learning and deep learning, offer promising solutions for improving the accuracy and speed of early STEMI detection through real-time analysis of electrocardiogram (ECG) and clinical data. Methods: A comprehensive literature search was conducted using five major databases (Scopus, PubMed, ProQuest, ScienceDirect, and Web of Science) for peer-reviewed articles published between 2015 and 2025. Study selection followed the PRISMA guidelines, and methodological quality was evaluated using the Joanna Briggs Institute (JBI) critical appraisal checklist. Data synthesis was performed narratively, focusing on diagnostic accuracy, clinical outcomes, and AI application types. Results: Fifteen studies met the inclusion criteria. The majority reported that AI-based models, particularly those using ECG input, achieved diagnostic accuracies exceeding 90%. Several studies demonstrated that AI outperformed traditional risk scoring systems like the TIMI score. Additionally, AI applications were shown to support remote monitoring and facilitate timely interventions in emergency cardiac care settings. Discussion: The findings of this review indicate that artificial intelligence has substantial potential to enhance early STEMI detection through improved diagnostic accuracy and faster clinical decision-making. AI-based ECG interpretation demonstrated superior performance compared to traditional diagnostic methods, which may reduce delays in reperfusion therapy and improve patient outcomes. Furthermore, AI integration in prehospital settings and remote monitoring systems supports early triage and timely intervention, particularly in resource-limited environments. However, challenges such as data heterogeneity, limited external validation, and ethical considerations remain important barriers to widespread implementation. These findings highlight the need for further large-scale multicenter studies to confirm the clinical effectiveness of AI-based diagnostic tools in real-world emergency cardiac care. Conclusion: AI has demonstrated high potential in improving early STEMI diagnosis, accelerating clinical decision-making, and enhancing patient outcomes in acute cardiac emergencies. However, successful implementation requires addressing external validation, data quality, clinician training, and ethical concerns. Integrating AI into emergency cardiac nursing practice may transform the delivery of care in resource-limited and time-sensitive environments.
Digital-Based and Telerehabilitation Interventions in Orthopaedic Postoperative Recovery: Literature Review Albertina Dete Tabik; Asroful Hulam Zamroni; Aqmarina Abidah; I Made Dwi Budhiasa Ari Serengga; Johanes Eban B. Dorman; Kiki Fajar Nurhidayah; Lisa Isdaryanti; Rizki Nur Azhadin; Nursalam Nursalam; Tintin Sukartini; Akhmad Ja'far; Hendra Kurnia Rakhma
Indonesian Journal of Global Health Research Vol. 8 No. 2 (2026): 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.v8i2.320

Abstract

Orthopedic surgery aims to treat musculoskeletal disorders; however, postoperative recovery often presents functional limitations. Digital interventions and telerehabilitation are increasingly being applied in nursing, although evidence of their effectiveness remains limited. This systematic review evaluated the effectiveness of these technologies in supporting postoperative orthopedic recovery and identified their contributions to evidence-based nursing practice. A systematic review following the PRISMA guidelines was conducted using Scopus, PubMed, Web of Science, ScienceDirect, and SAGE databases. Randomized controlled trials and quasi-experimental studies published between 2015 and 2025 involving adult postoperative orthopedic patients were included. The interventions were compared with conventional rehabilitation. Six outcome domains were evaluated: physical function, quality of life, pain, psychosocial aspects, self-efficacy, patient compliance and satisfaction. A total of 1,508 articles were identified, of which 16 studies met the inclusion criteria. Digital-based interventions and telerehabilitation consistently improved physical function (e.g., Timed Up and Go, Functional Independence Measure), increased quality of life (EQ-5D, SF-36), and reduced postoperative pain more rapidly than conventional rehabilitation did. Improvements were also observed in anxiety, depression, self-efficacy, health literacy, patient satisfaction, and adherence to the rehabilitation program. Digital and telerehabilitation interventions effectively support orthopedic postoperative recovery, positively affecting physical, psychosocial, and behavioral outcomes. A multimodal model integrating education, exercise, occupational therapy, and psychosocial support based on self-efficacy and biopsychosocial approaches yielded optimal results. Integration into surgical nursing practice is recommended, with attention to technological infrastructure and clinician training.
Co-Authors Akhmad Ja'far Albertina Dete Tabik Aqmarina Abidah Asroful Hulam Zamroni Elvi Kurnia Damayanti Hendra Kurnia Rakhma I Made Dwi Budhiasa Ari Serengga Johanes Eban B. Dorman Kiki Fajar Nurhidayah Kurniawati, Ninuk Dian Lisa Isdaryanti Nursalam, Nursalam Sriyono Sriyono Tintin Sukartini Sukartini, Tintin Sukartini Wahyuni, Erna Dwi