The Impact of Quality of Life on Cardiac Arrhythmias: A Clinical, Demographic, and AI-Assisted Statistical Investigation
<b>Background/Objectives</b>: Cardiac arrhythmias impact quality of life (QoL) and are often linked to psychological distress. This study examines the relationship between QoL, depression, and arrhythmias using AI-assisted analysis to enhance patient management. <b>Methods</b>...
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MDPI AG
2025-03-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/15/7/856 |
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| author | Luiza Camelia Nechita Ancuta Elena Tupu Aurel Nechita Daniel Voipan Andreea Elena Voipan Dana Tutunaru Carmina Liana Musat |
| author_facet | Luiza Camelia Nechita Ancuta Elena Tupu Aurel Nechita Daniel Voipan Andreea Elena Voipan Dana Tutunaru Carmina Liana Musat |
| author_sort | Luiza Camelia Nechita |
| collection | DOAJ |
| description | <b>Background/Objectives</b>: Cardiac arrhythmias impact quality of life (QoL) and are often linked to psychological distress. This study examines the relationship between QoL, depression, and arrhythmias using AI-assisted analysis to enhance patient management. <b>Methods</b>: A total of 145 patients with arrhythmias were assessed using an SF-36 health survey (QoL) and a PHQ-9 questionnaire (depression). Statistical analyses included regression, clustering, and AI-based models such as K-means and logistic regression to identify risk factors and patient subgroups. <b>Results</b>: Patients with comorbidities had lower QoL and higher depression scores. PHQ-9 scores negatively correlated with SF-36 mental health components. AI-assisted clustering identified distinct patient subgroups, with older individuals and those with longer disease duration exhibiting the lowest QoL. Logistic regression predicted depression with 93% accuracy, and XGBoost achieved an AUC of 0.97. <b>Conclusions</b>: QoL plays a key role in arrhythmia management, with depression significantly influencing outcomes. AI-driven predictive models offer personalized interventions, improving early detection and treatment. Future research should integrate wearable technology and AI-based monitoring to optimize patient care. |
| format | Article |
| id | doaj-art-28261ca26f0b4fd996445b431b58d665 |
| institution | DOAJ |
| issn | 2075-4418 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj-art-28261ca26f0b4fd996445b431b58d6652025-08-20T03:08:46ZengMDPI AGDiagnostics2075-44182025-03-0115785610.3390/diagnostics15070856The Impact of Quality of Life on Cardiac Arrhythmias: A Clinical, Demographic, and AI-Assisted Statistical InvestigationLuiza Camelia Nechita0Ancuta Elena Tupu1Aurel Nechita2Daniel Voipan3Andreea Elena Voipan4Dana Tutunaru5Carmina Liana Musat6Faculty of Medicine and Pharmacy, ‘Dunarea de Jos’ University of Galati, 800008 Galati, RomaniaFaculty of Medicine and Pharmacy, ‘Dunarea de Jos’ University of Galati, 800008 Galati, RomaniaFaculty of Medicine and Pharmacy, ‘Dunarea de Jos’ University of Galati, 800008 Galati, RomaniaFaculty of Automation, Computers, Electrical Engineering and Electronics, ‘Dunarea de Jos’ University of Galati, 800008 Galati, RomaniaFaculty of Automation, Computers, Electrical Engineering and Electronics, ‘Dunarea de Jos’ University of Galati, 800008 Galati, RomaniaFaculty of Medicine and Pharmacy, ‘Dunarea de Jos’ University of Galati, 800008 Galati, RomaniaFaculty of Medicine and Pharmacy, ‘Dunarea de Jos’ University of Galati, 800008 Galati, Romania<b>Background/Objectives</b>: Cardiac arrhythmias impact quality of life (QoL) and are often linked to psychological distress. This study examines the relationship between QoL, depression, and arrhythmias using AI-assisted analysis to enhance patient management. <b>Methods</b>: A total of 145 patients with arrhythmias were assessed using an SF-36 health survey (QoL) and a PHQ-9 questionnaire (depression). Statistical analyses included regression, clustering, and AI-based models such as K-means and logistic regression to identify risk factors and patient subgroups. <b>Results</b>: Patients with comorbidities had lower QoL and higher depression scores. PHQ-9 scores negatively correlated with SF-36 mental health components. AI-assisted clustering identified distinct patient subgroups, with older individuals and those with longer disease duration exhibiting the lowest QoL. Logistic regression predicted depression with 93% accuracy, and XGBoost achieved an AUC of 0.97. <b>Conclusions</b>: QoL plays a key role in arrhythmia management, with depression significantly influencing outcomes. AI-driven predictive models offer personalized interventions, improving early detection and treatment. Future research should integrate wearable technology and AI-based monitoring to optimize patient care.https://www.mdpi.com/2075-4418/15/7/856quality of lifecardiac arrhythmiasdepressionartificial intelligencestatistical methodsPHQ-9 |
| spellingShingle | Luiza Camelia Nechita Ancuta Elena Tupu Aurel Nechita Daniel Voipan Andreea Elena Voipan Dana Tutunaru Carmina Liana Musat The Impact of Quality of Life on Cardiac Arrhythmias: A Clinical, Demographic, and AI-Assisted Statistical Investigation Diagnostics quality of life cardiac arrhythmias depression artificial intelligence statistical methods PHQ-9 |
| title | The Impact of Quality of Life on Cardiac Arrhythmias: A Clinical, Demographic, and AI-Assisted Statistical Investigation |
| title_full | The Impact of Quality of Life on Cardiac Arrhythmias: A Clinical, Demographic, and AI-Assisted Statistical Investigation |
| title_fullStr | The Impact of Quality of Life on Cardiac Arrhythmias: A Clinical, Demographic, and AI-Assisted Statistical Investigation |
| title_full_unstemmed | The Impact of Quality of Life on Cardiac Arrhythmias: A Clinical, Demographic, and AI-Assisted Statistical Investigation |
| title_short | The Impact of Quality of Life on Cardiac Arrhythmias: A Clinical, Demographic, and AI-Assisted Statistical Investigation |
| title_sort | impact of quality of life on cardiac arrhythmias a clinical demographic and ai assisted statistical investigation |
| topic | quality of life cardiac arrhythmias depression artificial intelligence statistical methods PHQ-9 |
| url | https://www.mdpi.com/2075-4418/15/7/856 |
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